Artificial Intelligence and Robotics Commons^™

The Use Of Machine Learning To Detect Suckling In Pre-Weaned Calves, Sukumar Katamreddy

Theses

The weaning of cattle is a process which is known to be labour intensive and to have stressful effects on both cow and calf Common methods used in the weaning process include the temporary removal of a mother from the calf and manual observation and intervention. Early and speedy weaning is known to have a number of benefits, including health benefits for both cow and calf, additional weight gains for the calves as well as reduced labour and feed requirements. The process known as Two-Stage Weaning is recognised to be an effective low-stress approach to weaning in which the calf …

Crop Height Estimation With Unmanned Aerial Vehicles, Carrick Detweiler, David Anthony, Sebastian Elbaum

School of Computing: Faculty Publications

An unmanned aerial vehicle (UAV) can be configured for crop height estimation. In some examples, the UAV includes an aerial propulsion system, a laser scanner configured to face downwards while the UAV is in flight, and a control system. The laser scanner is configured to scan through a two-dimensional scan angle and is characterized by a maxi mum range. The control system causes the UAV to fly over an agricultural field and maintain, using the aerial propulsion system and the laser scanner, a distance between the UAV and a top of crops in the agricultural field to within a programmed …

The Ability Of Different Imputation Methods To Preserve The Significant Genes And Pathways In Cancer, Rosa Aghdam, Taban Baghfalaki, Pegah Khosravi, Elnaz Saberi Ansari

Publications and Research

Deciphering important genes and pathways from incomplete gene expression data could facilitate a better understanding of cancer. Different imputation methods can be applied to estimate the missing values. In our study, we evaluated various imputation methods for their performance in preserving significant genes and pathways. In the first step, 5% genes are considered in random for two types of ignorable and non-ignorable missingness mechanisms with various missing rates. Next, 10 well-known imputation methods were applied to the complete datasets. The significance analysis of microarrays (SAM) method was applied to detect the significant genes in rectal and lung cancers to showcase …

Machine Learning Based Protein Sequence To (Un)Structure Mapping And Interaction Prediction, Sumaiya Iqbal

LSU New Orleans Theses and Dissertations

Proteins are the fundamental macromolecules within a cell that carry out most of the biological functions. The computational study of protein structure and its functions, using machine learning and data analytics, is elemental in advancing the life-science research due to the fast-growing biological data and the extensive complexities involved in their analyses towards discovering meaningful insights. Mapping of protein’s primary sequence is not only limited to its structure, we extend that to its disordered component known as Intrinsically Disordered Proteins or Regions in proteins (IDPs/IDRs), and hence the involved dynamics, which help us explain complex interaction within a cell that …

Geometry-Based Mass Grading Of Mango Fruits Using Image Processing, M. A. Momin, Md Towfiqur Rahman, M. S. Sultana, C. Igathinathane, A. T. M. Ziauddin, T. E. Grift

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Mango (Mangifera indica) is an important, and popular fruit in Bangladesh. However, the post-harvest processing of it is still mostly performed manually, a situation far from satisfactory, in terms of accuracy and throughput. To automate the grading of mangos (geometry and shape), we developed an image acquisition and processing system to extract projected area, perimeter, and roundness features. In this system, images were acquired using a XGA format color camera of 8-bit gray levels using fluorescent lighting. An image processing algorithm based on region based global thresholding color binarization, combined with median filter and morphological analysis was developed …

Hexarray: A Novel Self-Reconfigurable Hardware System, Fady Hussein

Boise State University Theses and Dissertations

Evolvable hardware (EHW) is a powerful autonomous system for adapting and finding solutions within a changing environment. EHW consists of two main components: a reconfigurable hardware core and an evolutionary algorithm. The majority of prior research focuses on improving either the reconfigurable hardware or the evolutionary algorithm in place, but not both. Thus, current implementations suffer from being application oriented and having slow reconfiguration times, low efficiencies, and less routing flexibility. In this work, a novel evolvable hardware platform is proposed that combines a novel reconfigurable hardware core and a novel evolutionary algorithm.

The proposed reconfigurable hardware core is a …

K-Mer Analysis Pipeline For Classification Of Dna Sequences From Metagenomic Samples, Russell Kaehler

Graduate Student Theses, Dissertations, & Professional Papers

Biological sequence datasets are increasing at a prodigious rate. The volume of data in these datasets surpasses what is observed in many other fields of science. New developments wherein metagenomic DNA from complex bacterial communities is recovered and sequenced are producing a new kind of data known as metagenomic data, which is comprised of DNA fragments from many genomes. Developing a utility to analyze such metagenomic data and predict the sample class from which it originated has many possible implications for ecological and medical applications. Within this document is a description of a series of analytical techniques used to process …

Novel Neuroevolution Techniques For The Life Science Domain, Timothy Manning

Theses

The life science domain is a high value research area, both in terms of the benefits in increased knowledge and in societal impact. Much of the research funding has focused on wet lab based approaches to increase visibility into biological processes and producing maximal relevant information on which to make decisions. Given the complexity of biological functions, in many cases this has led to an information overload. Researchers are now able to routinely generate and access petabytes of data as a result of high throughput experiments, and this capability is growing. This data can be difficult to interpret and intractable …

Towards Deeper Understanding In Neuroimaging, Rex Devon Hjelm

Computer Science ETDs

Neuroimaging is a growing domain of research, with advances in machine learning having tremendous potential to expand understanding in neuroscience and improve public health. Deep neural networks have recently and rapidly achieved historic success in numerous domains, and as a consequence have completely redefined the landscape of automated learners, giving promise of significant advances in numerous domains of research. Despite recent advances and advantages over traditional machine learning methods, deep neural networks have yet to have permeated significantly into neuroscience studies, particularly as a tool for discovery. This dissertation presents well-established and novel tools for unsupervised learning which aid in …

Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang

COBRA Preprint Series

Non-negative matrix factorization (NMF) is a widely used machine learning algorithm for dimension reduction of large-scale data. It has found successful applications in a variety of fields such as computational biology, neuroscience, natural language processing, information retrieval, image processing and speech recognition. In bioinformatics, for example, it has been used to extract patterns and profiles from genomic and text-mining data as well as in protein sequence and structure analysis. While the scientific performance of NMF is very promising in dealing with high dimensional data sets and complex data structures, its computational cost is high and sometimes could be critical for …

Object Recognition And Visual Search With A Physiologically Grounded Model Of Visual Attention, Frederik Beuth, Fred H. Hamker

MODVIS Workshop

Visual attention models can explain a rich set of physiological data (Reynolds & Heeger, 2009, Neuron), but can rarely link these findings to real-world tasks. Here, we would like to narrow this gap with a novel, physiologically grounded model of visual attention by demonstrating its objects recognition abilities in noisy scenes.

To base the model on physiological data, we used a recently developed microcircuit model of visual attention (Beuth & Hamker, in revision, Vision Res) which explains a large set of attention experiments, e.g. biased competition, modulation of contrast response functions, tuning curves, and surround suppression. Objects are represented by …

Modeling Visual Features To Recognize Biological Motion: A Developmental Approach, Giulio Sandini, Nicoletta Noceti, Alessia Vignolo, Alessandra Sciutti, Francesco Rea, Alessandro Verri, Francesca Odone

MODVIS Workshop

In this work we deal with the problem of designing and developing computational vision models – comparable to the early stages of the human development – using coarse low-level information.

More specifically, we consider a binary classification setting to characterize biological movements with respect to non-biological dynamic events. To this purpose, our model builds on top of the optical flow estimation, and abstract the representation to simulate the limited amount of visual information available at birth. We take inspiration from known biological motion regularities explained by the Two-Thirds Power Law, and design a motion representation that includes different low-level features, …

Using Wild I.D. As A Reliable Source For Mark And Recapture Studies On Northern Pike (Esox Lucius), Martin Evans

Journal of Earth and Life Science

Mark and recapture studies are a very popular method fisheries biologists use to assess certain fish populations in lakes. This process can be very labor intensive and expensive. Wild I.D. is free software developed by Dartmouth College that uses SIFT program to find unique features in photographs. Initially developed for identification of African land mammals the program gives each photo a score and percent match to other photos. Northern pike were used in this study to determine if the program can recognize simulated recapture events. Photos of sample fish were taken at two separate locations, the photos were then copied …

Learning Emotions: A Software Engine For Simulating Realistic Emotion In Artificial Agents, Douglas Code

Senior Independent Study Theses

This paper outlines a software framework for the simulation of dynamic emotions in simulated agents. This framework acts as a domain-independent, black-box solution for giving actors in games or simulations realistic emotional reactions to events. The emotion management engine provided by the framework uses a modified Fuzzy Logic Adaptive Model of Emotions (FLAME) model, which lets it manage both appraisal of events in relation to an individual’s emotional state, and learning mechanisms through which an individual’s emotional responses to a particular event or object can change over time. In addition to the FLAME model, the engine draws on the design …

Graph-Based Regularization In Machine Learning: Discovering Driver Modules In Biological Networks, Xi Gao

Theses and Dissertations

Curiosity of human nature drives us to explore the origins of what makes each of us different. From ancient legends and mythology, Mendel's law, Punnett square to modern genetic research, we carry on this old but eternal question. Thanks to technological revolution, today's scientists try to answer this question using easily measurable gene expression and other profiling data. However, the exploration can easily get lost in the data of growing volume, dimension, noise and complexity. This dissertation is aimed at developing new machine learning methods that take data from different classes as input, augment them with knowledge of feature relationships, …

A Network That Really Works - The Application Of Artificial Neural Networks To Improve Yield Predictions And Nitrogen Management In Western Australia, Jinsong Leng, Andreas Neuhaus, Leisa Armstrong

Research outputs 2014 to 2021

Yield predictions are notorious for being difficult due to many interdependent factors such as rainfall, soil properties, plant health, plant density etc. This study is based upon the author’s previously published work and extends its findings by further investigating the best mathematical solution to this dilemma. Artificial intelligence (AI) techniques have been applied to a large set of soil, plant, rainfall, and yield data from CSBP’s field research trial program. Here we further differentiate by investigate two ANN techniques, a genetic algorithm with back propagation neural networks (GA-BP-NN) and a particle swarm optimization with back propagation neural networks (PSO-BP-NN). Results …

An Artificial Neural Network For Predicting Crops Yield In Nepal, Tirtha Ranjeet, Leisa Armstrong

Research outputs 2014 to 2021

This paper examines the application of artificial neural networks (ANNs) for predicting crop yields for an agricultural region in Nepal. The neural network algorithm has become an effective data mining tool and the outcome produced by this algorithm is considered to be less error prone than other computer science techniques. The backpropagation algorithm which iteratively finds a suitable weight value is considered for computing the error derivative. Agricultural data was collected from thirteen years from paddy field cultivation in the Siraha district, an eastern region in Nepal, and used for this investigation of neural networks. Additionally, climatic parameters including rainfall, …

Integrating Soil And Plant Tissue Tests And Using An Artificial Intelligence Method For Data Modelling Is Likely To Improve Decisions For In-Season Nitrogen Management, Andreas Neuhaus, Leisa Armstrong, Jinsong Leng, Dean Diepeveen, Geoff Anderson

Research outputs 2014 to 2021

This paper hypothesizes that there is value in combining soil, climate and plant tissue data to give more reliable advice on nitrogen top-ups in-season when compared with models that are currently available. The benefit of soil and climate data is to factor in N mineralisation and potential yield while plant test data is a more direct approach of yield estimates when considering firstly plant N uptake from the whole soil profile and secondly biomass (important yield component). Plant test data are closer to yield in time and space than soil test data, shortening the time period for any yield prognosis …

Towards Personalized Medicine Using Systems Biology And Machine Learning, Calin Voichita

Wayne State University Dissertations

The rate of acquiring biological data has greatly surpassed our ability to interpret it. At the same time, we have started to understand that evolution of many diseases such as cancer, are the results of the interplay between the disease itself and the immune system of the host. It is now well accepted that cancer is not a single disease, but a “complex collection of distinct genetic diseases united by common hallmarks”. Understanding the differences between such disease subtypes is key not only in providing adequate treatments for known subtypes but also identifying new ones. These unforeseen disease subtypes are …

A Spatially Explicit Agent Based Model Of Muscovy Duck Home Range Behavior, James Howard Anderson

USF Tampa Graduate Theses and Dissertations

ABSTRACT

Research in GIScience has identified agent-based simulation methodologies as effective in the study of complex adaptive spatial systems (CASS). CASS are characterized by the emergent nature of their spatial expressions and by the changing relationships between their constituent variables and how those variables act on the system's spatial expression over time. Here, emergence refers to a CASS property where small-scale, individual action results in macroscopic or system-level patterns over time. This research develops and executes a spatially-explicit agent based model of Muscovy Duck home range behavior. Muscovy duck home range behavior is regarded as a complex adaptive spatial system …

Imbalanced Learning For Functional State Assessment, Feng Li, Frederick Mckenzie, Jiang Li, Guanfan Zhang, Roger Xu, Carl Richey, Tom Schnell, Thomas E. Pinelli (Ed.)

Electrical & Computer Engineering Faculty Publications

This paper presents results of several imbalanced learning techniques applied to operator functional state assessment where the data is highly imbalanced, i.e., some function states (majority classes) have much more training samples than other states (minority classes). Conventional machine learning techniques usually tend to classify all data samples into majority classis and perform poorly for minority classes. In this study, we implemented five imbalanced learning techniques, including random under-sampling, random over-sampling, synthetic minority over-sampling technique (SMOTE), borderline-SMOTE and adaptive synthetic sampling (ADASYN) to solve this problem. Experimental results on a benchmark driving test dataset show that accuracies for minority classes …

Automated Interpretation Of The Tandem Mass Spectra Of Peptides Using Artificial Neural Networks, Timothy Patrick Manning

Theses

The manual interpretation of mass spectra is a complex and time consuming task. The problem of manually interpreting this data is further exacerbated by the large numbers of mass spectra which can potentially be produced in a single proteoniics experiment. This shows the need for high throughput approaches to the interpretation of mass spectra. Existing automated approaches are however error prone due to the complexity of the task. Accordingly, this thesis discusses and evaluates the application of neural networks to improving the sensitivity, specificity and robustness of current approaches to the automated interpretation of such mass spectral data.

Several neural …

A Neural Network Method For Protein Classification, Arie D. Jones

All-Inclusive List of Electronic Theses and Dissertations

The investigation detailed in this paper attempts to utilize a Leaming Vector Quantization network in order to classify a set of mitochondrial proteins based upon their amino acid sequence. The Learning Vector Quantization network uses a nearest neighbor approach to classification. Input vectors are fed into the network, which produces output vectors. Those output vectors are then matched by means of a distance bias to a corresponding classification vector. The learning and test sets consisted of thirteen similar mitochodrial proteins from seventy-two different species. This provided a pool of over nine hundred proteins to use. Half of the species were …

Designing An Intelligent System For Genetic Biology Learning, Seenivasagam S.Gangatharan

Student Works (2000-2009)

With the changing education scenario, an issue which has come strongly on how to create intelligent tutoring system to educate learners in a more intelligent way. So a need has emerged for the development of an intelligent tutoring system. This part or thesis describes the design of a collection of intelligent systems under the name GENETIC BIOLOGY for basic genetic biology tutoring. GENETIC BIOLOGY consist of three intelligent systems which arc designed for cell, DNA and gene learning. GENETIC BIOLOGY systems employ natural language processing and various techniques normally used in the construction of intelligent systems. Production rules and frames …

Application Of Ai In Medicine, Tarmizi Amirul Hisyam

Student Works (2000-2009)

From the beginning of human civilization, mankind have been trying to fins solution on how to make life easier. They create, modify and adapt, as they would please their need. From the smallest things in our life to the biggest part of all technologies, has improved our life tremendously. Computer technology nowadays has an important role in education, communication, medicine, and many more. In the field of medicine, we have seen many support systems had been developed and use to help human in their daily lives. Application of AI in medicine was proposed in this reason in mind, as a …

Sistem Pakar Bermultimedia Untuk Pengenalpastian Serangga, Osman Aizul Hussin

Student Works (2000-2009)

Sistem Pakar Bermultimedia untuk domain pengenalpastian serangga ,Insect Identification Expert System,(IIES ) merupakan sistem pakar untuk membantu proses pengenalpastian pangkat serangga dalam Hierarki Linnean. Sistem ini menggunakan pendekatan berorientasikan objek di mana konsep kelas dan objek akan digunakan untuk merekodkan pengetahuan ke bentuk yang akan difahami oleh sistem pakar. Strategi inferens yang digunakan ialah teknik rantaian ke hadapan di mana sistem pakar akan menghasilkan konklusi berdasarkan data-data yang diberi. Sistem pakar mempunyai ciri-ciri multimedia untuk membantu memberi panduan bagi pengguna untuk mengenal pasti ciri-ciri kunci serangga dan memberi penjelasan tentang domain di samping memberi pendekatan yang berlainan dari sistem pakar …

Sistem Diagnosis Penyakit Tanaman Padi (Pakar Padi), Jin Gee Tee

Student Works (2000-2009)

Beras adalah makanan utama rakyat Malaysia. Banyak kajian dan penyelidikan dibuat untuk meningkatkan hasil tanaman padi. Di antaranya termasuklah mengkaji cara-cara kawalan serangga perosak dan kerja-kerja diagnosis penyakit tanaman padi. Maklumat-maklumat daripada hasil kajian harus disimpan dengan baik supaya kerja diagnosis dapat dijalankan dengan lebih lancar. Memandangkan keperluan ini, satu sistem berkomputeran yang menyimpan data data mengenai tanaman padi adalah penting dan dijangka akan memberi bantuan dalam pengurusan dan kerja-kerja diagnosis. Ini telah membawa kepada idea untuk membangunkan satu sistem diagnosis penyakit bagi tanaman padi. Sistem Diagnosis Penyakit Tanaman Padi, diberikan nama Pakar Padi adalah satu sistem berpangkalan komputer yang …

Interview: Brenda Laurel, Jason Challas

SWITCH

This interview with Brenda Laurel, Virtual Reality (VR) author and thinker, discusses the applications and challenges of VR. Creating an emphatic experience using VR technology is possible, but the challenge lies in designing an environment that models the senses to stimulate emotions. VR enables experiences of different genders, but physiological differences between the sexes exist and are important to understand. However, technology used to create the environment and simulation of physical objects in VR is only in the developmental stage. Laurel believes in the importance of keeping the mind grounded in the physical body, in order to strengthen the appreciation …

Ua35/11 Wku Student Honors Research Bulletin, Wku University Honors Program

WKU Administration Documents

The Western Kentucky University Student Honors Research Bulletin is dedicated to scholarly involvement and student research. These papers represent work done by students from throughout the university.

• Kesselring, Marcia. Attitudes Toward the Need for Computer Literacy
• Tuck, Janna & Karen Wiggins. Methylation and Confirmation of PGE
• Lewis, Gloria. John Donne's Attitude Toward Love
• Johnson, Linda. International Telecommunications Trade with Japan
• Sharpe, Greg. Precipitation Patterns in Bowling Green, Kentucky, 1980-1985
• Smith, Sandy. Religion and the Media: Alliance or War?
• Bell, Suzanne. Early Secret Involvement of the United States Military in Cambodia
• Scariot, Linda. Parental Divorce and Childhood Emotional Disturbances
• Daniel, Janice. …

Ua35/11 Student Honors Research Bulletin, Wku Honors Program

WKU Administration Documents

The WKU Student Honors Research Bulletin is dedicated to scholarly involvement and student research. These papers are representative of work done by students from throughout the university.

• Whicker, Garth. Agriculture and the Development of Malaysia
• McGaha. Rape, Passion, Lechery, Usury, Incest, Murder and other Matters in The Ravenger's Tragedy
• Harrison, Robert. It was a Day of Very General Awakening . . : Reformation and Revival in Russellville, Kentucky
• King, Betty. An Affirmative Decision for James's Isabel Archer
• Sutton, Joyce. Sex Bias in Performance of Women
• Logsdon, Doug. Poe's Women
• Yoder, Nate. Emily Dickinson and Her Puritan Heritage
• Davis, Aleen. Jay …