Investigating Semi-Supervised Learning Algorithms in Text Datasets

Using large training datasets enhances the generalization capabilities of neural networks. Semi-supervised learning (SSL) is useful when there are few labeled data and a lot of unlabeled data. SSL methods that use data augmentation are most successful for image datasets. In contrast, texts do not have consistent augmentation methods as images. Consequently, methods that use augmentation are not as effective in text data as they are in image data. In this study, we compared SSL algorithms that do not require augmentation; these are self-training, co-training, tri-training, and tri-training with disagreement. In the experiments, we used 4 different text datasets for different tasks. We examined the algorithms from a variety of perspectives by asking experiment questions and suggested several improvements. Among the algorithms, tri-training with disagreement showed the closest performance to the Oracle; however, performance gap shows that new semi-supervised algorithms or improvements in existing methods are needed.Comment: Innovations in Intelligent Systems and Applications Conference (ASYU

Machine learning for human-centered and value-sensitive building energy efficiency

Enhancing building energy efficiency is one of the best strategies to reduce energy consumption and associated CO2 emissions. Recent studies emphasized the importance of occupant behavior as a key means of enhancing building energy efficiency. However, it is also critical that while we strive to enhance the energy efficiency of buildings through improving occupant behavior, we still pay enough attention to occupant comfort and satisfaction. Towards this goal, this research proposes a data-driven machine-learning-based approach to behavioral building energy efficiency, which could help better understand and predict the impact of occupant behavior on building energy consumption and occupant comfort; and help optimize occupant behavior for both energy saving and occupant comfort. Three types of models were developed and tested – simulation-data-driven, real-data-driven, and hybrid. Accordingly, the research included five primary research tasks. First, the importance levels of energy-related human values (e.g., thermal comfort) to building occupants and their current satisfaction levels with these values were identified, in order to better understand the factors that are associated with higher/lower importance and/or satisfaction levels and identify the potential factors that could help predict occupant comfort. Second, a data sensing and occupant feedback collection plan was developed, in order to capture and monitor the indoor environmental conditions, energy consumption, energy-related occupant behavior, and occupant comfort in real buildings. Third, a set of buildings were simulated, in order to model the energy consumption of different buildings in different contexts – in terms of occupant behavior, building sizes, weather conditions, etc.; and a simulation-data-driven occupant-behavior-sensitive machine learning-based model, which learns from simulation data, was developed for predicting hourly cooling energy consumption. Fourth, a set of real-data-driven occupant-behavior-sensitive machine learning-based models, which learn from real data (data collected from real buildings and real occupants), were developed for predicting hourly cooling and lighting energy consumption and thermal and visual occupant comfort; and a genetic algorithm-based optimization model for determining the optimal occupant behavior that can simultaneously reduce energy consumption and improve occupant comfort was developed. Compared to the simulation-data-driven approach, the real-data-driven approach aims to better capture and model the real-life behavior and comfort of occupants and the real-life energy-consumption patterns of buildings. Although successful in this regard, the resulting models may not generalize well outside of their training range. Fifth, a hybrid, occupant-behavior-sensitive machine learning-based model, which learns from both simulation data and real data, was developed for predicting hourly cooling and lighting energy consumption. The hybrid approach aims to overcome the limitations of both simulation-data-driven and real-data-driven approaches – especially the limited ability to capture occupant behavior and real-life consumption patterns in simulation-data-driven approaches and the limited generalizability of real-data-driven approaches to different cases – by learning from both types of data simultaneously. The experimental results show the potential of the proposed approach. The energy consumption prediction models achieved high prediction performance, and the thermal and visual comfort models were able to accurately represent the individual and group comfort levels. The optimization results showed potential behavioral energy savings in the range of 11% and 22%, with significant improvement in occupant comfort

Occupants’ Perceptions about Indoor Environment Comfort and Energy Related Values in Commercial and Residential Buildings

AbstractThe building sector has been recognized as one of the biggest contributors to energy consumption and greenhouse gas emissions. Building occupants play an essential role in enhancing building energy efficiency. This paper presents the results of two types of questionnaire surveys, which solicited the input of residential and commercial building occupants in Doha, Qatar and Arizona, U.S. The survey focused on soliciting occupant feedback on their indoor environment comfort, energy-related values, and energy use behaviour. The analysis of the survey results showed similarities and differences in occupants’ perceptions across Doha and Arizona

Single dominant left coronary artery: An autopsy case report with review of literature

Coronary artery anomalous course is rare, reported incidence is approximately 0.3–1.3% of patients undergoing coronary angiography and approximately 1% of routine autopsy examinations. A single coronary artery is an unusual congenital anomaly where only one coronary artery arises from the aortic trunk from a single coronary ostium, supplying the entire heart. We describe here a rare case with an unusual dominant left circumflex artery and absent right coronary artery

Lingual ortodonti

Currently, aesthetics of the anterior teeth is a significant issue in general dentistry and the most frequently cited reason for patients seeking orthodontic treatment. For many years, lingual orthodontics was perceived as complex and problematic treatment procedures and therefore not widely used internationally. However, during the last decade, the percentage of patients treated with lingual orthodontics has increased, appliance systems have renewed, and the technique has developed to such an extent that in some cases, it is easier, quicker, and more accurate than traditional buccal orthodontics. The aim of this review is to evaluate and generally consider the usage of lingual orthodontics which commonly preferred by patients in routine orthodontic procedures and look through current applications. Additionally, special considerations regarding the contemporary diagnosis and treatment planning in lingual orthodontics are presented in this study. ÖZET Günümüzde, ön dişlerin estetik olarak dizilimi ve görünümü genel diş hekimliğinde önemli bir konu olmuş ve bu önem hastalar için lingual ortodonti tercihinde birinci sebep halini almıştır. Lingual ortodonti yıllardır karmaşık ve uygulanması zor tedavi yöntemlerinden kabul edilmiş ve uluslar arası alanda yaygın bir kullanım alanı bulamamıştır. Ancak son dönemlerde, bu yöntem aracılığıyla tedavi edilen hasta yüzdesi artmış, vakalarda uygulanan aygıtlar yenilenmiş, tedaviler kolaylaştırılmış, hızlandırılmış ve her geçen gün geleneksel ortodontik tedavilerle elde edilen başarılara ulaşılmaya başlanmıştır. Bu derlemenin amacı, ortodontide her geçen gün daha fazla hastanın tercih ettiği bu uygulamayı genel olarak değerlendirmek ve güncel uygulamalara genel bir bakış yapmaktır. Ayrıca lingual ortodontik uygulamalardaki güncel muayene ve tedavi planlamalarından, karşılaşılan özel durumlardan da bu çalışmada bahsedilecektir. Anahtar Kelimeler: Lingual ortodonti, güncel uygulamala

Coronary-Subclavian Steal Syndrome Presenting with Ventricular Tachycardia

Coronary-subclavian steal through the left internal mammary graft is a rare cause of myocardial ischemia in patients who have had a coronary bypass surgery. We report a 70-year-old man who presented with sustained monomorphic ventricular tachycardia 5 years after the surgical creation of a left internal mammary to the left anterior descending artery. Cardiac catheterization illustrated that the left subclavian artery was occluded proximally and that the distal course was visualized by retrograde filling through the left internal mammary graft. Clinical ventricular tachycardia was reproducibly induced with a single ventricular extrastimulus, and antitachycardia pacing terminated the tachycardia. Restoration of blood flow by way of a Dacron graft placed between the descending aorta and the subclavian artery resulted in the total relief of symptoms. Ventricular tachycardia could not be induced during the control electrophysiologic study after surgical revascularization

A rare complication of inguinal hernia repair: Total testicular ischemia and necrosis

Testicular ischemia and necrosis are quite rare complications following inguinal hernia repair. There is still no consensus on the mechanism of infarction and necrosis in the literature. We present a case with total testicular ischemia and necrosis in the early period following the inguinal hernia repair with prolene mesh, ending up with orchiectomy