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https://www.readbyqxmd.com/read/28176905/effect-of-roll-compaction-on-granule-size-distribution-of-microcrystalline-cellulose-mannitol-mixtures-computational-intelligence-modeling-and-parametric-analysis
#1
Pezhman Kazemi, Mohammad Hassan Khalid, Ana Pérez Gago, Peter Kleinebudde, Renata Jachowicz, Jakub Szlęk, Aleksander Mendyk
Dry granulation using roll compaction is a typical unit operation for producing solid dosage forms in the pharmaceutical industry. Dry granulation is commonly used if the powder mixture is sensitive to heat and moisture and has poor flow properties. The output of roll compaction is compacted ribbons that exhibit different properties based on the adjusted process parameters. These ribbons are then milled into granules and finally compressed into tablets. The properties of the ribbons directly affect the granule size distribution (GSD) and the quality of final products; thus, it is imperative to study the effect of roll compaction process parameters on GSD...
2017: Drug Design, Development and Therapy
https://www.readbyqxmd.com/read/28138223/computational-intelligence-models-to-predict-porosity-of-tablets-using-minimum-features
#2
Mohammad Hassan Khalid, Pezhman Kazemi, Lucia Perez-Gandarillas, Abderrahim Michrafy, Jakub Szlęk, Renata Jachowicz, Aleksander Mendyk
The effects of different formulations and manufacturing process conditions on the physical properties of a solid dosage form are of importance to the pharmaceutical industry. It is vital to have in-depth understanding of the material properties and governing parameters of its processes in response to different formulations. Understanding the mentioned aspects will allow tighter control of the process, leading to implementation of quality-by-design (QbD) practices. Computational intelligence (CI) offers an opportunity to create empirical models that can be used to describe the system and predict future outcomes in silico...
2017: Drug Design, Development and Therapy
https://www.readbyqxmd.com/read/28126242/artificial-intelligence-in-medicine
#3
Pavel Hamet, Johanne Tremblay
Artificial Intelligence (AI) is a general term that implies the use of a computer to model intelligent behavior with minimal human intervention. AI is generally accepted as having started with the invention of robots. The term derives from the Czech word robota, meaning biosynthetic machines used as forced labor. In this field, Leonardo Da Vinci's lasting heritage is today's burgeoning use of robotic-assisted surgery, named after him, for complex urologic and gynecologic procedures. Da Vinci's sketchbooks of robots helped set the stage for this innovation...
January 11, 2017: Metabolism: Clinical and Experimental
https://www.readbyqxmd.com/read/28117445/dermatologist-level-classification-of-skin-cancer-with-deep-neural-networks
#4
Andre Esteva, Brett Kuprel, Roberto A Novoa, Justin Ko, Susan M Swetter, Helen M Blau, Sebastian Thrun
Skin cancer, the most common human malignancy, is primarily diagnosed visually, beginning with an initial clinical screening and followed potentially by dermoscopic analysis, a biopsy and histopathological examination. Automated classification of skin lesions using images is a challenging task owing to the fine-grained variability in the appearance of skin lesions. Deep convolutional neural networks (CNNs) show potential for general and highly variable tasks across many fine-grained object categories. Here we demonstrate classification of skin lesions using a single CNN, trained end-to-end from images directly, using only pixels and disease labels as inputs...
February 2, 2017: Nature
https://www.readbyqxmd.com/read/28113586/a-robust-approach-for-the-background-subtraction-based-on-multi-layered-self-organizing-maps
#5
Giorgio Gemignani, Alessandro Rozza
Motion detection in video streams is a challenging task for several computer vision applications. Indeed, segmentation of moving and static elements in the scene allows to increase the efficiency of several challenging tasks such as human computer interface (HCI), robot visions, and intelligent surveillance systems. In this paper, we approach motion detection through a multilayered artificial neural network, which is able to build for each background pixel a multi-modal color distribution evolving over time through self organization...
August 31, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28110106/fast-learning-method-for-convolutional-neural-networks-using-extreme-learning-machine-and-its-application-to-lane-detection
#6
Jihun Kim, Jonghong Kim, Gil-Jin Jang, Minho Lee
Deep learning has received significant attention recently as a promising solution to many problems in the area of artificial intelligence. Among several deep learning architectures, convolutional neural networks (CNNs) demonstrate superior performance when compared to other machine learning methods in the applications of object detection and recognition. We use a CNN for image enhancement and the detection of driving lanes on motorways. In general, the process of lane detection consists of edge extraction and line detection...
December 10, 2016: Neural Networks: the Official Journal of the International Neural Network Society
https://www.readbyqxmd.com/read/28002840/suprasegmental-characteristics-of-spontaneous-speech-produced-in-good-and-challenging-communicative-conditions-by-talkers-aged-9-14-years
#7
Valerie Hazan, Outi Tuomainen, Michèle Pettinato
Purpose: This study investigated the acoustic characteristics of spontaneous speech by talkers aged 9-14 years and their ability to adapt these characteristics to maintain effective communication when intelligibility was artificially degraded for their interlocutor. Method: Recordings were made for 96 children (50 female participants, 46 male participants) engaged in a problem-solving task with a same-sex friend; recordings for 20 adults were used as reference. The task was carried out in good listening conditions (normal transmission) and in degraded transmission conditions...
December 1, 2016: Journal of Speech, Language, and Hearing Research: JSLHR
https://www.readbyqxmd.com/read/27996165/mimicking-classical-conditioning-based-on-a-single-flexible-memristor
#8
Chaoxing Wu, Tae Whan Kim, Tailiang Guo, Fushan Li, Dea Uk Lee, J Joshua Yang
The mimicking of classical conditioning, including acquisition, extinction, recovery, and generalization, can be efficiently achieved by using a single flexible memristor. In particular, the experiment of Pavlov's dog is successfully demonstrated. This demonstration paves the way for reproducing advanced neural processes and provides a frontier approach to the design of artificial intelligence systems with dramatically reduced complexity.
December 20, 2016: Advanced Materials
https://www.readbyqxmd.com/read/27919375/software-intelligent-system-for-effective-solutions-for-hearing-impaired-subjects
#9
Rajkumar S, Muttan S, Sapthagirivasan V, Jaya V, Vignesh S S
PURPOSE: The anatomy and physiology of the ear is complex in nature, which makes it a challenge for audiologists to prescribe solutions for varied hearing-impaired subjects. There is a need to increase the satisfaction level of hearing-aid users by adopting better strategies that involve modern technological advancements. AIM: To design and develop a decision support Software Intelligent System (SIS) that performs audiological investigations to assess the degree of hearing loss and to suggest appropriate hearing-aid gain values...
January 2017: International Journal of Medical Informatics
https://www.readbyqxmd.com/read/27881212/building-machines-that-learn-and-think-like-people
#10
Brenden M Lake, Tomer D Ullman, Joshua B Tenenbaum, Samuel J Gershman
Recent progress in artificial intelligence (AI) has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn, and how they learn it...
November 24, 2016: Behavioral and Brain Sciences
https://www.readbyqxmd.com/read/27830257/public-health-and-epidemiology-informatics
#11
A Flahault, A Bar-Hen, N Paragios
OBJECTIVES: The aim of this manuscript is to provide a brief overview of the scientific challenges that should be addressed in order to unlock the full potential of using data from a general point of view, as well as to present some ideas that could help answer specific needs for data understanding in the field of health sciences and epidemiology. METHODS: A survey of uses and challenges of big data analyses for medicine and public health was conducted. The first part of the paper focuses on big data techniques, algorithms, and statistical approaches to identify patterns in data...
November 10, 2016: Yearbook of Medical Informatics
https://www.readbyqxmd.com/read/27828292/intelligent-estimation-of-noise-and-blur-variances-using-ann-for-the-restoration-of-ultrasound-images
#12
Muhammad Shahin Uddin, Kalyan Kumar Halder, Murat Tahtali, Andrew J Lambert, Mark R Pickering, Margaret Marchese, Iain Stuart
Ultrasound (US) imaging is a widely used clinical diagnostic tool in medical imaging techniques. It is a comparatively safe, economical, painless, portable, and noninvasive real-time tool compared to the other imaging modalities. However, the image quality of US imaging is severely affected by the presence of speckle noise and blur during the acquisition process. In order to ensure a high-quality clinical diagnosis, US images must be restored by reducing their speckle noise and blur. In general, speckle noise is modeled as a multiplicative noise following a Rayleigh distribution and blur as a Gaussian function...
November 1, 2016: Applied Optics
https://www.readbyqxmd.com/read/27812931/primer-on-ontologies
#13
Janna Hastings
As molecular biology has increasingly become a data-intensive discipline, ontologies have emerged as an essential computational tool to assist in the organisation, description and analysis of data. Ontologies describe and classify the entities of interest in a scientific domain in a computationally accessible fashion such that algorithms and tools can be developed around them. The technology that underlies ontologies has its roots in logic-based artificial intelligence, allowing for sophisticated automated inference and error detection...
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/27782023/an-integrated-patient-information-and-in-home-health-monitoring-system-using-smartphones-and-web-services
#14
Golam Sorwar, Mortuza Ali, Md Kamrul Islam, Mohammad Selim Miah
Modern healthcare systems are undergoing a paradigm shift from in-hospital care to in-home monitoring, leveraging the emerging technologies in the area of bio-sensing, wireless communication, mobile computing, and artificial intelligence. In-home monitoring promises to significantly reduce healthcare spending by preventing unnecessary hospital admissions and visits to healthcare professionals. Most of the in-home monitoring systems, proposed in the literature, focus on monitoring a set of specific vital signs...
2016: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/27777555/the-predictive-processing-paradigm-has-roots-in-kant
#15
Link R Swanson
Predictive processing (PP) is a paradigm in computational and cognitive neuroscience that has recently attracted significant attention across domains, including psychology, robotics, artificial intelligence and philosophy. It is often regarded as a fresh and possibly revolutionary paradigm shift, yet a handful of authors have remarked that aspects of PP seem reminiscent of the work of 18th century philosopher Immanuel Kant. To date there have not been any substantive discussions of how exactly PP links back to Kant...
2016: Frontiers in Systems Neuroscience
https://www.readbyqxmd.com/read/27720605/a-fuzzy-logic-based-decision-making-approach-for-identification-of-groundwater-quality-based-on-groundwater-quality-indices
#16
M Vadiati, A Asghari-Moghaddam, M Nakhaei, J Adamowski, A H Akbarzadeh
Due to inherent uncertainties in measurement and analysis, groundwater quality assessment is a difficult task. Artificial intelligence techniques, specifically fuzzy inference systems, have proven useful in evaluating groundwater quality in uncertain and complex hydrogeological systems. In the present study, a Mamdani fuzzy-logic-based decision-making approach was developed to assess groundwater quality based on relevant indices. In an effort to develop a set of new hybrid fuzzy indices for groundwater quality assessment, a Mamdani fuzzy inference model was developed with widely-accepted groundwater quality indices: the Groundwater Quality Index (GQI), the Water Quality Index (WQI), and the Ground Water Quality Index (GWQI)...
December 15, 2016: Journal of Environmental Management
https://www.readbyqxmd.com/read/27715099/quantum-enhanced-machine-learning
#17
Vedran Dunjko, Jacob M Taylor, Hans J Briegel
The emerging field of quantum machine learning has the potential to substantially aid in the problems and scope of artificial intelligence. This is only enhanced by recent successes in the field of classical machine learning. In this work we propose an approach for the systematic treatment of machine learning, from the perspective of quantum information. Our approach is general and covers all three main branches of machine learning: supervised, unsupervised, and reinforcement learning. While quantum improvements in supervised and unsupervised learning have been reported, reinforcement learning has received much less attention...
September 23, 2016: Physical Review Letters
https://www.readbyqxmd.com/read/27664506/meta-glare-a-meta-system-for-defining-your-own-computer-interpretable-guideline-system-architecture-and-acquisition
#18
Alessio Bottrighi, Paolo Terenziani
CONTEXT: Several different computer-assisted management systems of computer interpretable guidelines (CIGs) have been developed by the Artificial Intelligence in Medicine community. Each CIG system is characterized by a specific formalism to represent CIGs, and usually provides a manager to acquire, consult and execute them. Though there are several commonalities between most formalisms in the literature, each formalism has its own peculiarities. OBJECTIVE: The goal of our work is to provide a flexible support to the extension or definition of CIGs formalisms, and of their acquisition and execution engines...
September 2016: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/27608458/a-robust-approach-for-the-background-subtraction-based-on-multi-layered-self-organizing-maps
#19
Giorgio Gemignani, Alessandro Rozza
Motion detection in video streams is a challenging task for several computer vision applications. Indeed, segmentation of moving and static elements in the scene allows to increase the efficiency of several challenging tasks, such as human-computer interface, robot visions, and intelligent surveillance systems. In this paper, we approach motion detection through a multi-layered artificial neural network, which is able to build for each background pixel a multi-modal color distribution evolving over time through self-organization...
November 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/27589267/curiosity-search-producing-generalists-by-encouraging-individuals-to-continually-explore-and-acquire-skills-throughout-their-lifetime
#20
Christopher Stanton, Jeff Clune
Natural animals are renowned for their ability to acquire a diverse and general skill set over the course of their lifetime. However, research in artificial intelligence has yet to produce agents that acquire all or even most of the available skills in non-trivial environments. One candidate algorithm for encouraging the production of such individuals is Novelty Search, which pressures organisms to exhibit different behaviors from other individuals. However, we hypothesized that Novelty Search would produce sub-populations of specialists, in which each individual possesses a subset of skills, but no one organism acquires all or most of the skills...
2016: PloS One
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