• Methods of Seizure Detection: A Literature Review 

  Ibrahim, Lamis (2021)

  epileptic seizure is a neurological disorder caused by abnormal activity of nerve cells in the brain. Epileptic seizures may happen while the patient is awake or asleep, and may cause loss of consciousness, falling, or ...
• A Literature Review of the Development Trends of Visual Neural Protheses 

  Givens, Jordan (2021)

  According to a systemic review of population-based data sets relevant to global vision impairment and or blindness between 1980 in 2015, there is an estimated 36 million people who suffer from blindness [4]. An additional ...
• EEG-Based BCI for Household IoT Control 

  Dunn, Bryce (2021)

  Brain-computer interface (BCI) paradigms have existed for decades to improve communication and technological control. Electroencephalography (EEG) represents one of the most common non-invasive approaches toward recording ...
• Neural Control of Cardiac Function, Rhythm, and Contraction 

  O'Connell, Rachel (2021)

  This literature review discusses how researchers can control cardiac cells with neural networks. The cardiac system is controlled by the autonomic nervous system and coordinates with the respiratory system. Numerous ...
• The Future of Personalized Brain Stimulation for the Treatment of Neuropsychiatric Disorders 

  Fredriksz, Madeline (2021)

  Over a billion individuals worldwide suffer from neuropsychiatric disorders, many of which are resistant to traditional medications and therapy. Both invasive and non-invasive electrical stimulation have emerged as promising ...
• A CNN/MLP Neural Processing Engine, Powered by Novel Temporal-Carry-deferring MACs 

  Mirzaeian, Ali (2021)

  The applications of machine learning algorithms are innumerable and cover nearly every domain of modern technology. During this rapid growth of this area, more and more companies have expressed a desire to utilize machine ...
• Understanding changes in the olfactory system could help with early diagnosis and treatment of Anosmia 

  Saghir, Urba (2021)

  Anosmia is an olfactory disease that is associated with the inability to smell. This disease affects 3-20% of the population, consisting of younger as well as aged adults. Anosmia is found mostly in aged adults, that are ...
• Investigating Zolpidem for Treatment of Various Neurological Conditions 

  Stewart, Carson (2021)

  While Neural Engineering has had breakthrough technologies including cochlear implants for hearing restoration and deep brain stimulation for a range of diseases including Parkinson’s, engineering approaches to several ...
• Effects of NGF on PC12 Neurite Growth 

  Alex, Albin (2021)

  Pheochromocytoma cells, or PC12s, are a cell line used for neuroscience research. Even though these cells are derived from a rat adrenal medulla tumor, these cells mimic and behave similar to neurons. To further model these ...
• Detection of X-Linked Juvenile Retinoschisis 

  Zhang, Jeremy (2021)

  A child’s education during adolescence is essential for mental and confidence development. As one is exposed to a constantly changing learning environment, unaccounted factors are extremely detrimental. One such factor is ...
• Exploring Two Alternative BCIs for Improving Alzheimer’s Disease Rehabilitation 

  Beaini, Fayez (2021)

  Neurodegenerative diseases affect the nervous system of the body, ultimately disturbing movement and or mental function where Alzheimer's disease (AD) is the most common form [1]. Brain-computer interface (BCI) is a ...
• Toward Understanding Civic Data Bias in 311 Systems: An Information Deserts Perspective 

  Lee, Myeong; Wang, Jieshu; Johnston, Erik; Harlow, John; Gordon, Eric; Janzen, Shawn; Winter, Susan (CSCW Workshop on Civic Technologies: Research, Practice, and Open Challenges, 2020-10)

  While civic technologies for public issues and services such as 311 systems are widely adopted in many U.S. cities, the impact of the emerging civic technologies and their data-level dynamics are unclear. Because the ...
• Information Retrieval Model for Social Media Applications 

  Bhandari, Shova (2021-01)

  Social networks are rich source of data to analyze user habits in all aspects of life. User’s behaviour is decisiv e component of a health system in various countries. Promoting good behaviour can improve the public health ...
• Explicit programming strategies 

  LaToza, Thomas D.; Arab, Maryam; Loksa, Dastyni; Ko, Amy J. (Empirical Software Engineering, 2020-03-07)

  Software developers solve a diverse and wide range of problems. While software engineering research often focuses on tools to support this problem solving, the strategies that developers use to solve problems are at least ...
• Machine Learning Model to Detect Emergency in the Global Pandemic 

  Raju, Rini (2021-01-11)

  It is crucial to use advanced machine learning models to improve disaster and emergency response in critical events around the world. In this paper, we introduce a new model, which can highlight the essential help that ...
• Sentiment Analysis Methods to Mitigate Negative Effect of the COVID-19 Pandemic 

  Mohamud, Sofia A (2021-01-11)

  The goal of this research is to determine crucial factors that played a role in the number of confirmed COVID-19 infections within a given location. We hypothesize that political bias plays a significant role in the rise ...
• A Technical Report on Security Evaluation of Logic Locking: Attacks and Defenses 

  Zamiri Azar, Kimia (2020)
• Conditional Classification: A Solution for Computational Energy Reduction 

  Mirzaeian, Ali; Manoj P D, Sai; Vakil, Ashkan; Homayoun, Houman; Sasan, Avesta (2021)

  Deep convolutional neural networks have shown high efficiency in computer visions and other applications. However, with the increase in the depth of the networks, the computational complexity is growing exponentially. In ...
• Diverse Knowledge Distillation (DKD): A Solution for Improving The Robustness of Ensemble Models Against Adversarial Attacks 

  Mirzaeian, Ali; Kosecka, Jana; Homayoun, Houman; Mohsenin, Tinoosh; Sasan, Avesta (2021)

  This paper proposes an ensemble learning model that is resistant to adversarial attacks. To build resilience, we introduced a training process where each member learns a radically distinct latent space. Member models are ...
• A Technical Report On Accelerator Design For Deep Neural Networks 

  Mirzaeian, Ali (2019)

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