Towards a mood sensitive integrated development environment to enhance the performance of programmers

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The aim of the research was to analyze the possibility of developing an Integrated Development Environment (IDE) that could improve a programmer‘s performance by considering their current mood. Various experiments were conducted to study this idea. However, the impact of moods on programmer performance was initially examined in the literature. Based on this, a Cognitive Programming Task Model (CPTM) was developed showing that various cognitive functions and programming activities are interrelated. A second model derived from the literature, the Cognitive Mood Model (CMM), suggested that moods are also interrelated with various cognitive functions. Combining these two models indirectly suggests a relation between moods and programming tasks, which was presented as the Mood Programming Model (MPM). As direct empirical support was lacking for this relation, two experiments were conducted to study the effect mood could have on performance in a debug task. Validated mood-inducing movie clips were used to induce specific moods along two-mood dimensions: valence and arousal. The first study was conducted online. The results showed that arousal is a significant factor when considering programmer performance whereas valence was found to have no significant effect. The second study was a continuation study to validate the findings from the first study within lab conditions. The results were not able to confirm the findings of the first experiment. The reasons for these findings were explained accordingly. As mood was found to have an effect on a programmer‘s coding and debugging performance, this factor might be considered when developing a support system. The next step in the research was therefore to consider mood measuring in a non-interruptive way. The next two experiments were based around the hypothesis that ―moods can be measured from the keyboard and mouse interaction of the computer user‖. In the first experiment an application was installed on participants‘ computers to record their key presses and mouse clicks in a log file. Their self reported moods in intervals of 20 minutes were also stored in the same file over an average period of eight days. Correlations between participants‘ self reported moods and their keyboard and mouse use revealed that it might be possible to measure moods of the some of the participants. The second experiment took place in the lab, where participants were asked to perform programming like tasks while listening to ii mood inducing background music. Their moods were measured with a Galvanic Skin Response (GSR) meter whereas key presses and mouse clicks again were recorded in log files. The correlations between GSR measurements and keyboard and mouse interaction validated the findings of the experiment in the field that it might be possible to measure the mood of some users from their computer use. Analyzing participants‘ personality traits showed dutifulness and self discipline as indicators that a person‘s mood correlates with his/her interaction behaviour. Considering that mood has an effect on programmer performance and that it might be possible to measure mood in a non-intrusive manner, the last question to focus on was whether a computer-generated intervention could change a programmer‘s mood and consequently improve their performance. In the final experiment programmers had to dry run algorithms for 16 minutes with the expectation that a level of boredom would set in. After this the video clip instructed them to participate in some physical exercises. Participants continued tracing algorithms for 8 minutes after the intervention. Results showed that the mood change after the intervention coincided with a programmers improved ability to provide the correct output of the algorithms. Together these findings lay the foundation for developing an IDE that can measure the programmer mood in a non-intrusive way and make effective interventions to improve programmer performance

Rising atmospheric temperature impact on wheat and thermotolerance strategies

Temperature across the globe is increasing continuously at the rate of 0.15–0.17 °C per decade since the industrial revolution. It is influencing agricultural crop productivity. Therefore, thermotolerance strategies are needed to have sustainability in crop yield under higher temperature. However, improving thermotolerance in the crop is a challenging task for crop scientists. Therefore, this review work was conducted with the aim of providing information on the wheat response in three research areas, i.e., physiology, breeding, and advances in genetics, which could assist the researchers in improving thermotolerance. The optimum temperature for wheat growth at the heading, anthesis, and grain filling duration is 16 ± 2.3 °C, 23 ± 1.75 °C, and 26 ± 1.53 °C, respectively. The high temperature adversely influences the crop phenology, growth, and development. The pre-anthesis high temperature retards the pollen viability, seed formation, and embryo development. The post-anthesis high temperature declines the starch granules accumulation, stem reserve carbohydrates, and translocation of photosynthates into grains. A high temperature above 40 °C inhibits the photosynthesis by damaging the photosystem-II, electron transport chain, and photosystem-I. Our review work highlighted that genotypes which can maintain a higher accumulation of proline, glycine betaine, expression of heat shock proteins, stay green and antioxidant enzymes activity viz., catalase, peroxidase, super oxide dismutase, and glutathione reductase can tolerate high temperature efficiently through sustaining cellular physiology. Similarly, the pre-anthesis acclimation with heat treatment, inorganic fertilizer such as nitrogen, potassium nitrate and potassium chloride, mulches with rice husk, early sowing, presoaking of a 6.6 mM solution of thiourea, foliar application of 50 ppm dithiothreitol, 10 mg per kg of silicon at heading and zinc ameliorate the crop against the high temperature. Finally, it has been suggested that modern genomics and omics techniques should be used to develop thermotolerance in wheat.Higher Education Commission (HEC) Pakistan | Ref. 1a55b19f0b99ca1

A Comparative Analysis of Pre and Post Privatization Efficiency of Pakistani Banks

In this study, we present estimates of changes in productivity and efficiencies of privatized banks in Pakistan during the period 1987-2014. We measure the performance of banks by cost-effectiveness and technical efficiency of five leading banks of Pakistan.  All estimated results are statistically significant and support the general hypotheses that increase the efficiency and productivity after privatization

Current Knowledge and Therapeutic Strategies of Herbal Medicine for Acute Diarrhea

Diarrhea is a common gastrointestinal problem characterized by loose watery stool and mild to severe dehydration. Annually, about 1.7–5 billion new cases of diarrhea were reported. In developing countries, it is more common, where young kids have diarrhea approximately three times/year. In 2013, 1.26 million deaths occurred due to diarrhea, whereas in 1990, the figure was slightly higher (2.58 million). In 2012, diarrhea was the second most common reason of death (11%, n = 0.76 million) in children less than 5 years. Although various synthetic drugs are being prescribed as standard therapy for diarrhea, they have side effects. It is possible to prescribe the herbal medicine for diarrhea, which is safe and effective. In this study, medicinal plants discussed are proven to be scientifically active in diarrheal diseases. This study reviews about current medicinal plants used in the treatment of diarrhea. The use of medicinal plants for diarrhea results in improvement of the symptom. Moreover, studies on large scale are needed to characterize the beneficial role of medicinal plants in the treatment of diarrhea

Perforated appendix! An experience of a Public teaching hospital

Introduction  The most common cause of non-traumatic acute abdominal pain as well as the most common acute abdominal condition presenting to Surgical Emergency is none other than Acute Appendicitis hence it becomes the most common entity undergoing surgery in Emergencies all over the world. The lifetime risk for someone to develop acute appendicitis is 8.6% and 6.7% for males and females respectively, with 90% found in children and young adults and 10% in patients over 60 years of age.1 Increasing age or in other words decreasing immunity does affect the incidence of perforated appendix as we see the  the perforation rate in acute appendicitis is approximately 20~30%  but as the age goes beyond 60 years it inclines to  32-72%.2 Delay in the diagnosis caused by indefinite  history and physical examination  tends to contribute to higher incidence of perforated appendix as reported by Siripong et al. In another study the risk factors that were found to be associated with perforated appendicitis were male sex, fever ≥ 38°C, anorexia, and duration of pain in the pre-admission period.3 In one of the the study pre-hospital delays were exceeding related to perforation as compared to in-hospital delays which was explainable because of a linear relationship present among the pathological grade  to hospital interval ratio , thus leading to increased risk of perforation.4 As far as the blood work was concerned , an increase in Total Leucocyte count with majority being polymorphonuclear leukocytes (PMN), and raised C-reactive protein (CRP) levels were found to be responsible for substantial increment in the  risk and gravity of complications in appendicitis. Presence of comorbid diseases didn't show any significant affect on perforation rate.5

Proliposome powder or tablets for generating inhalable liposomes using a medical nebulizer

Purpose: The aim of this study was to develop and compare proliposome powder and proliposome tablet formulations for drug delivery from a Pari-LC Sprint nebulizer. Methods: Proliposome powders were prepared by the slurry method and sorbitol or mannitol carbohydrate carrier were used in a 1:10 and 1:15 w/w lipid phase to carrier ratio. Beclometasone dipropionate (BDP; 2 mol%) was incorporated in the lipid phase. Proliposome powders were compressed into tablets, and liposomes were generated from proliposome powders or tablets within the nebulizer reservoir for subsequent aerosolization. Results: Comparatively, shorter sputtering times were reported for the tablet formulations (≈ < 2.7±0.45 min), indicating uniform aerosolization. Post-nebulization, liposomes size was larger in the nebulizer reservoir in the range of 7.79±0.48 µm–9.73±1.53 µm for both powder and tablet formulations as compared to freshly prepared liposomes (5.38±0.73 µm–5.85±0.86 µm), suggesting liposome aggregation/fusion in the nebulizer’s reservoir. All formulations exhibited more than 80% mass output regardless of formulation type, but greater BDP proportions (circa 50%) were delivered to the Two-stage Impinger when tablet formulations were used. Moreover, the nebulized droplet median size and size distribution were lower for all tablet formulations in comparison to the powder formulations. Proliposome tablet and powdered formulations demonstrated the ability to generate vesicles that sustained the release of BDP. Conclusion: Overall, this study showed that proliposome tablets could be disintegrated within a Pari-LC Sprint nebulizer to generate inhalable aerosol, with high drug output and hence can be manufactured on large scale to overcome the storage problems associated with powder formulations

Electricity theft detection in smart grid using machine learning

Nowadays, electricity theft is a major issue in many countries and poses a significant financial loss for global power utilities. Conventional Electricity Theft Detection (ETD) models face challenges such as the curse of dimensionality and highly imbalanced electricity consumption data distribution. To overcome these problems, a hybrid system Multi-Layer Perceptron (MLP) approach with Gated Recurrent Units (GRU) is proposed in this work. The proposed hybrid system is applied to analyze and solve electricity theft using data from the Chinese National Grid Corporation (CNGC). In the proposed hybrid system, first, preprocess the data; second, balance the data using the k-means Synthetic Minority Oversampling Technique (SMOTE) technique; third, apply the GTU model to the extracted purified data; fourth, apply the MLP model to the extracted purified data; and finally, evaluate the performance of the proposed system using different performance measures such as graphical analysis and a statistical test. To verify the consistency of our proposed hybrid system, we use three different ratios for training and testing the dataset. The outcomes show that the proposed hybrid system for ETD is highly accurate and efficient compared to the other models like Alexnet, GRU, Bidirectional Gated Recurrent Unit (BGRU) and Recurrent Neural Network (RNN)

Towards a mood sensitive integrated development environment to enhance the performance of programmers

The aim of the research was to analyze the possibility of developing an Integrated Development Environment (IDE) that could improve a programmer‘s performance by considering their current mood. Various experiments were conducted to study this idea. However, the impact of moods on programmer performance was initially examined in the literature. Based on this, a Cognitive Programming Task Model (CPTM) was developed showing that various cognitive functions and programming activities are interrelated. A second model derived from the literature, the Cognitive Mood Model (CMM), suggested that moods are also interrelated with various cognitive functions. Combining these two models indirectly suggests a relation between moods and programming tasks, which was presented as the Mood Programming Model (MPM). As direct empirical support was lacking for this relation, two experiments were conducted to study the effect mood could have on performance in a debug task. Validated mood-inducing movie clips were used to induce specific moods along two-mood dimensions: valence and arousal. The first study was conducted online. The results showed that arousal is a significant factor when considering programmer performance whereas valence was found to have no significant effect. The second study was a continuation study to validate the findings from the first study within lab conditions. The results were not able to confirm the findings of the first experiment. The reasons for these findings were explained accordingly. As mood was found to have an effect on a programmer‘s coding and debugging performance, this factor might be considered when developing a support system. The next step in the research was therefore to consider mood measuring in a non-interruptive way. The next two experiments were based around the hypothesis that ―moods can be measured from the keyboard and mouse interaction of the computer user‖. In the first experiment an application was installed on participants‘ computers to record their key presses and mouse clicks in a log file. Their self reported moods in intervals of 20 minutes were also stored in the same file over an average period of eight days. Correlations between participants‘ self reported moods and their keyboard and mouse use revealed that it might be possible to measure moods of the some of the participants. The second experiment took place in the lab, where participants were asked to perform programming like tasks while listening to ii mood inducing background music. Their moods were measured with a Galvanic Skin Response (GSR) meter whereas key presses and mouse clicks again were recorded in log files. The correlations between GSR measurements and keyboard and mouse interaction validated the findings of the experiment in the field that it might be possible to measure the mood of some users from their computer use. Analyzing participants‘ personality traits showed dutifulness and self discipline as indicators that a person‘s mood correlates with his/her interaction behaviour. Considering that mood has an effect on programmer performance and that it might be possible to measure mood in a non-intrusive manner, the last question to focus on was whether a computer-generated intervention could change a programmer‘s mood and consequently improve their performance. In the final experiment programmers had to dry run algorithms for 16 minutes with the expectation that a level of boredom would set in. After this the video clip instructed them to participate in some physical exercises. Participants continued tracing algorithms for 8 minutes after the intervention. Results showed that the mood change after the intervention coincided with a programmers improved ability to provide the correct output of the algorithms. Together these findings lay the foundation for developing an IDE that can measure the programmer mood in a non-intrusive way and make effective interventions to improve programmer performance.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Towards a mood sensitive integrated development environment to enhance the performance of programmers

The aim of the research was to analyze the possibility of developing an Integrated Development Environment (IDE) that could improve a programmer‘s performance by considering their current mood. Various experiments were conducted to study this idea. However, the impact of moods on programmer performance was initially examined in the literature. Based on this, a Cognitive Programming Task Model (CPTM) was developed showing that various cognitive functions and programming activities are interrelated. A second model derived from the literature, the Cognitive Mood Model (CMM), suggested that moods are also interrelated with various cognitive functions. Combining these two models indirectly suggests a relation between moods and programming tasks, which was presented as the Mood Programming Model (MPM). As direct empirical support was lacking for this relation, two experiments were conducted to study the effect mood could have on performance in a debug task. Validated mood-inducing movie clips were used to induce specific moods along two-mood dimensions: valence and arousal. The first study was conducted online. The results showed that arousal is a significant factor when considering programmer performance whereas valence was found to have no significant effect. The second study was a continuation study to validate the findings from the first study within lab conditions. The results were not able to confirm the findings of the first experiment. The reasons for these findings were explained accordingly. As mood was found to have an effect on a programmer‘s coding and debugging performance, this factor might be considered when developing a support system. The next step in the research was therefore to consider mood measuring in a non-interruptive way. The next two experiments were based around the hypothesis that ―moods can be measured from the keyboard and mouse interaction of the computer user‖. In the first experiment an application was installed on participants‘ computers to record their key presses and mouse clicks in a log file. Their self reported moods in intervals of 20 minutes were also stored in the same file over an average period of eight days. Correlations between participants‘ self reported moods and their keyboard and mouse use revealed that it might be possible to measure moods of the some of the participants. The second experiment took place in the lab, where participants were asked to perform programming like tasks while listening to ii mood inducing background music. Their moods were measured with a Galvanic Skin Response (GSR) meter whereas key presses and mouse clicks again were recorded in log files. The correlations between GSR measurements and keyboard and mouse interaction validated the findings of the experiment in the field that it might be possible to measure the mood of some users from their computer use. Analyzing participants‘ personality traits showed dutifulness and self discipline as indicators that a person‘s mood correlates with his/her interaction behaviour. Considering that mood has an effect on programmer performance and that it might be possible to measure mood in a non-intrusive manner, the last question to focus on was whether a computer-generated intervention could change a programmer‘s mood and consequently improve their performance. In the final experiment programmers had to dry run algorithms for 16 minutes with the expectation that a level of boredom would set in. After this the video clip instructed them to participate in some physical exercises. Participants continued tracing algorithms for 8 minutes after the intervention. Results showed that the mood change after the intervention coincided with a programmers improved ability to provide the correct output of the algorithms. Together these findings lay the foundation for developing an IDE that can measure the programmer mood in a non-intrusive way and make effective interventions to improve programmer performance.EThOS - Electronic Theses Online ServiceGBUnited Kingdo