Related papers: Data Science In Olfaction
Software systems naturally evolve, and this evolution often brings design problems that cause system degradation. Architectural smells are typical symptoms of such problems, and several of these smells are related to undesired dependencies…
Animals have evolved to rapidly detect and recognise brief and intermittent encounters with odour packages, exhibiting recognition capabilities within milliseconds. Artificial olfaction has faced challenges in achieving comparable results…
Selectivity of olfactory receptor neuron (ORN) is compared with that of its receptor proteins (R) with fluctuations of odor binding-releasing process taken into account. The binding-releasing process is modeled as N Bernoulli trials, where…
The vibrational theory of olfaction was posited to explain subtle effects in the sense of smell inexplicable by models in which molecular structure alone determines an odorant's smell. Amazingly, behavioral and neurophysiological evidence…
Use case modeling is very popular to represent the functionality of the system to be developed, and it consists of two parts: use case diagram and use case description. Use case descriptions are written in structured natural language (NL),…
We introduce a framework for reasoning about what meaning is captured by the neurons in a trained neural network. We provide a strategy for discovering meaning by training a second model (referred to as an observer model) to classify the…
Code smell is a great challenge in software refactoring, which indicates latent design or implementation flaws that may degrade the software maintainability and evolution. Over the past of decades, the research on code smell has received…
Integrating vision and language has long been a dream in work on artificial intelligence (AI). In the past two years, we have witnessed an explosion of work that brings together vision and language from images to videos and beyond. The…
Machine learning (ML) is becoming prevalent in embedded AI sensing systems. These "ML sensors" enable context-sensitive, real-time data collection and decision-making across diverse applications ranging from anomaly detection in industrial…
In recent years, there have been unprecedented technological advances in sensor technology, and sensors have become more affordable than ever. Thus, sensor-driven data collection is increasingly becoming an attractive and practical option…
Dust storms are associated with certain respiratory illnesses across different areas in the world. Researchers have devoted time and resources to study the elements surrounding dust storm phenomena. This paper reviews the efforts of those…
We investigate the effect of style and category similarity in multiple datasets used for object detection pretraining. We find that including an additional stage of object-detection pretraining can increase the detection performance…
Code smells indicate software design problems that harm software quality. Data-intensive systems that frequently access databases often suffer from SQL code smells besides the traditional smells. While there have been extensive studies on…
Test smells, similar to code smells, can negatively impact both the test code and the production code being tested. Despite extensive research on test smells in languages like Java, Scala, and Python, automated tools for detecting test…
While multilingual users often switch between languages when seeking information, this process remains undersupported by current systems where information is typically siloed by language. Our formative study reveals that users'…
Visual sensation and perception refers to the process of sensing, organizing, identifying, and interpreting visual information in environmental awareness and understanding. Computational models inspired by visual perception have the…
Internet of Things (IoT) has gained substantial attention recently and play a significant role in smart city application deployments. A number of such smart city applications depend on sensor fusion capabilities in the cloud from diverse…
As Deep learning (DL) systems continuously evolve and grow, assuring their quality becomes an important yet challenging task. Compared to non-DL systems, DL systems have more complex team compositions and heavier data dependency. These…
Olfactory search in turbulent environments is a sensorimotor challenge solved with remarkable efficiency by many animals, yet replicating this ability in artificial systems remains difficult because detections are intermittent and wind…
Automated deployment and management of Cloud applications relies on descriptions of their deployment topologies, often referred to as Infrastructure Code. As the complexity of applications and their deployment models increases, developers…