Computer Sciences Commons^™

Multi-Label Voice Disorder Classification Using Raw Waveforms, Gökay Di̇şken

Turkish Journal of Electrical Engineering and Computer Sciences

Automated voice disorder systems that distinguish pathological voices from healthy ones have been developed with the aid of machine learning methods. Both clinicians and patients can benefit from these systems as they provide many advantages, compared to the invasive techniques. These systems can produce binary (healthy/pathological) or multi-class (healthy/selected pathologies) decisions. However, multiple disorders might exist in an individual’s voice. Multi-label classification should be considered in such cases. By this time, only a single report is available on this topic, where hand-crafted features were used, and a data augmentation technique was utilized to overcome class imbalances. In this study, a …

Ensemble Learning For Accurate Prediction Of Heart Sounds Using Gammatonegram Images, Sinam Ashinikumar Singh, Sinam Ajitkumar Singh, Aheibam Dinamani Singh

Turkish Journal of Electrical Engineering and Computer Sciences

The analysis of heart sound signals constitutes a pivotal domain in healthcare, with the prediction of imbalanced heart sounds offering critical diagnostic insights. However, the inherent diversity in cardiac sound patterns presents a substantial challenge in predicting imbalanced signals. Many scientific disciplines have focused a great deal of emphasis on the problem of class inequality. We introduce an ensemble learning approach employing a convolutional neural network model-based deep learning algorithm to effectively tackle the challenges associated with predicting imbalanced heart sound signals. We use a Gammatone filter bank to extract relevant features from the heard sound signal. Our approach leverages …

Detection And Classification Of Unauthorized Use Of Irrigation Motors In Agricultural Irrigation, Önder Ci̇velek, Sedat Görmüş, Hali̇l İbrahi̇m Okumuş, Orhan Gazi̇ Kederoglu

Turkish Journal of Electrical Engineering and Computer Sciences

The decarbonisation of electricity generation requires the real-time monitoring and control of grid components in order to efficiently and timely dispatch demand. This highly automated system, known as the Smart Grid, relies on smart or sensor-equipped distribution network components to optimise energy flow and minimise losses. However, energy theft, a major obstacle to efficient resource utilisation, poses a significant challenge to achieving this goal. This study proposes and evaluates a real-time telemetry and control system designed to mitigate energy theft in agricultural irrigation applications. The system increases energy efficiency by tracking the energy use in agricultural irrigation. The key challenge …

Survey Of Space Professionals’ Perception Of Satellite Cybersecurity From 2012 To 2022: Decision-Makers’ Thoughts On Satellite Cybersecurity Evolving, Rachel C. Jones

Aerospace Sciences Student Publications

Cyberattacks on space assets are often portrayed in vague terms of doubt and mystery. Several claims depict satellites being compromised or attacked, but little corroboration has been published or made publicly available. As the commercial space industry grows, increased concern with space cybersecurity will prompt commercial satellite decision-makers to analyze the often-undefined risk of cyberattacks against satellites. This article identifies and characterizes the nature of cybersecurity risks to space assets and postulates why space professionals might not prioritize cybersecurity. Additional information was captured from a decadal survey of space professionals conducted in 2012 and 2022. The results show a rise …

The Potential Influence Of Immune Modulatory Molecules (Tgf-Βiii And Ctla-4) In Pathogenicity Of Pcos, Mustafa Riyadh Abdullah, Hazima Mossa Alabassi

Karbala International Journal of Modern Science

Polycystic ovary syndrome (PCOS) is characterised by chronic anovulation, hyperandrogenism, polycystic ovaries, and immunological dysregulation. Immune homeostasis and inflammation management require immune functions. T-regulatory cells (Tregs) regulate PCOS's immune system, inflammation, insulin resistance, ovarian function, and homeostasis. Transforming growth factor βIII (TGF-βIII) and Cytotoxic-T-lymphocyte-associated-protein-4 (CTLA-4) receptors on the surfaces of Treg cells are important for controlling the immune system. The study included 68 PCOS patients and 22 non-PCOS women controls aged 20–45. The waist-hip ratio (WHR) determines obesity. We evaluated serum levels and gene expression of TGF-βIII and CTLA-4 via ELISA and real-time PCR. Women with PCOS had significantly higher …

Enhanced Optoelectronics Performance Of Hybrid Self Power Photodetectors Go: Tio2- Ad / N-Si Heterojunctions, Mohammed J. Alsultani, Maysoon F. Alias

Karbala International Journal of Modern Science

A GO:TiO₂/n-Si heterostructure has been submerged in an anthocyanin dye solution that extracted from the red cabbage plant creates a high responsivity, self-powered UV, and visible photodetectors fabricated by the spray pyrolysis technique. The GO concentrations are varied, whereas TiO₂ is fixed. Thin films' structure, shape, and optical characteristics were examined using X-ray diffraction, field emission scanning electron microscopy, and UV-Vis spectrophotometers respectively. Island-like polycrystalline film powders with grain boundaries and granular shapes are created. Two direct energy gaps between 3.33-3.02 and 2.39-2.04 eV exist in all films. J-V characteristics were examined. The saturation current density (J …

A Scalable Parallel Processing Design For The Data Washing Machine: An Unsupervised Entity Resolution System, Nicholas Kofi Akortia Hagan

Theses and Dissertations

Entity Resolution (ER) has been one of the bedrocks in the creation of information systems by ensuring ambiguous entities are identified and resolved by linking. One common design approach of traditional ER systems is to run in single-threaded mode, which makes the system prone to out-of-memory error when processing larger datasets. The Data Washing Machine (DWM) as a proof-of-concept of an unsupervised cluster ER system is indifferent from this common design bottleneck. The original prototype design of the DWM requires shared memory tables and dictionaries of tokens, and its single-threaded nature makes it not scalable, hence not viable for real-world …

Transforming Libraries Through Engagement: Lessons From A Library Ai Interest Group, Lily Dubach, Rachel Vacek

Faculty Scholarship and Creative Works

Learn how one academic library is engaging with its employees to explore the latest trends, tools, and topics in AI through an interest group (IG). Through stimulating discussions, webinars, guest speakers, demos, and sharing of experiences with AI, the IG empowers its library community to explore and become more comfortable with AI. This session caters to varying levels of AI expertise. Challenges, successes, and valuable insights for deeper engagement will be shared so you can learn how to establish a similar initiative in your library.

Constructing Problemology That Is Symmetrical To Methodology—Taking Computer Science As An Example, Yuhang Liu, Yunquan Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Institutionalized scientific research encourages free exploration while emphasizing the organization and coordination of research activities. Nevertheless, overcoming dispersion and repetition in the research process is an urgent problem to be addressed. Taking computer science as an example, to implement the problem-oriented concept, this study proposes constructing problemology that is symmetrical to methodology. Methodology is the important manifestation of scientific and technological achievements, and symmetrically, problemology is needed by the scientific research community. The problematique is a crucial component of problemology, representing the level of understanding of problems within the scientific research community. Through problematique as a medium, it connects, bridges, …

Empowering Traditional Industries With Digital Intelligence For Transformation And Upgrading, Jiyuan Zang, Huanyong Ji, Qingxue Huang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Traditional industries are the basic support and driving force for the high-quality development of the economy. Digital intelligence is an important lever for traditional industries to achieve the transformation of old and new kinetic energy and the leapfrogging of the global value chain. This study firstly deconstructs the rich connotations of digital intelligence from the perspectives of digitalization, networkization, and intelligentization. Secondly, it analyzes the transformation mechanism and various pathways through which digital intelligence impacts traditional industries. Thirdly, it analyzes the barriers faced by traditional industries in the process of adopting digital intelligence technologies. Finally, this study puts forward four …

Predicting Choroidal Nevus Transformation To Melanoma Using Machine Learning, Prashant D. Tailor, Piotr K. Kopinski, Haley S. D'Souza, David A. Leske, Timothy W. Olsen, Carol L. Shields, Jerry A. Shields, Lauren A. Dalvin

Wills Eye Hospital Papers

PURPOSE: To develop and validate machine learning (ML) models to predict choroidal nevus transformation to melanoma based on multimodal imaging at initial presentation.

DESIGN: Retrospective multicenter study.

PARTICIPANTS: Patients diagnosed with choroidal nevus on the Ocular Oncology Service at Wills Eye Hospital (2007-2017) or Mayo Clinic Rochester (2015-2023).

METHODS: Multimodal imaging was obtained, including fundus photography, fundus autofluorescence, spectral domain OCT, and B-scan ultrasonography. Machine learning models were created (XGBoost, LGBM, Random Forest, Extra Tree) and optimized for area under receiver operating characteristic curve (AUROC). The Wills Eye Hospital cohort was used for training and testing (80% training-20% testing) with …

Strategic Study On Leading Construction Of Modern Agricultural System By Technology Innovation, Yan Yan, Xurong Mei, Xiudong Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Technology innovation is the fundamental solution to build a modern agricultural system, and it is also an important support for building the large base, large enterprise, and large industry of modern agriculture and achieving the modernization of material equipment, technology, management, agricultural informatization, and sustainable resource utilization of agriculture. This paper explains the scientific concepts and logical relationships of the agricultural production system, industrial system and management system, which are the main components of a modern agricultural system. It emphasizes that ensuring food security, promoting industrial integration and upgrading, and cultivating leading enterprises are current key tasks. Nevertheless, from the …

Innovation Path At Institute For Protein Design Of Washington University And Its Enlightenment For Construction Of New Life Sciences R&D Institutions, Runzhou Zhao, Ming Ni, Yunzhi Fa, Xiaochen Bo, Jian Jiao

Bulletin of Chinese Academy of Sciences (Chinese Version)

The Institute for Protein Design (IPD) at the University of Washington is a pioneering local and state-supported non-profit scientific research institution. Since its establishment in 2012, IPD has seized the opportunity of AI for Science and open science, and continuously enhanced its capabilities of fundamental innovations, breakthrough technologies, and industrial impact. We summarized five factors contributing to IPD’s development, including focusing on the cutting-edge issues of basic scientific research to gain a first-mover advantage and then further expand, integrating AI-enhanced digital tools and solid experimental validations, facilitating the integrated development of innovation and industrial chains, giving full play to the …

A New Optimization Approach Based On Neural Architecture Search To Enhance Deep U-Net For Efficient Road Segmentation, Narges Saeedizadeh, Seyed Mohammad Jafar Jalali, Burhan Khan, Parham Mohsenzadeh Kebria, Shady Mohamed

Research outputs 2022 to 2026

Neural Architecture Search (NAS) has significantly improved the accuracy of image classification and segmentation. However, these methods concentrate on finding segmentation structures for natural or medical applications. In this study, we introduce a NAS approach based on gradient optimization to identify ideal cell designs for road segmentation. To the best of our knowledge, this work represents the first application of gradient-based NAS to road extraction. Taking insight from the U-Net model and its successful variations in different image segmentation tasks, we propose NAS-enhanced U-Net, illustrated by an equal number of cells in both encoder and decoder levels. While cross-entropy combined …

Memetic Memory As Vital Conduits Of Troublemakers In Digital Culture, Alexander O. Smith, Jordan Loewen-Colón

School of Information Studies - Post-doc and Student Scholarship

Recent fears of data capitalism and colonialism often argue using implicit assumptions about cybernetic technology’s ability to automate data about culture. As such, the level of data granularity made possible by cybernetic engineering can be used to dominate society and culture. Here we unpack these implicit assumptions about the datafication of culture through memes, which both act as cultural data and cultural memory. Using Alexander Galloway’s critical method of protocological analysis and descriptions of media tactics, we respond to fears of cybernetic domination. Protocols – the source by which cybernetic technologies enable automated datafication – enables us to respond to …

Using Cache Files To Improve The Efficiency Of The Ucgretina Simulation Code, Blake Mcnulty

Physics and Astronomy Summer Fellows

UCGretina is a program that is used to simulate the Gretina gamma-ray tracking array used in experiments at the Facility for Rare Isotope Beams (FRIB) to collect gamma rays produced in reactions such as proton scattering. This is done by generating a simulation of the beam particles used and sending them into a simulated recreation that mimics the experimental environment. My job this summer was to tackle a major issue that the program had which is the speed or efficiency at which it ran. The main issue was that it would take days for certain simulation sets to run which …

A Qualitative Study On The Integration Of Artificial Intelligence In Cultural Heritage Conservation, Kholoud Ghaith, James Hutson

Faculty Scholarship

The widespread adoption of generative artificial intelligence (GAI) technologies heralds an era of expanding possibilities in the domain of cultural heritage conservation. This paradigm shift is marked by a confluence of innovative methodologies, including digital twin mapping, digital archiving, and enhanced preservation strategies, aimed at safeguarding the vestiges of our shared past. The application of AI within this field represents a frontier where technology and tradition intersect, offering new vistas for the preservation of historical structures and artifacts that are at risk of deterioration or oblivion. This article endeavors to elucidate the perspectives of professionals within the conservation domain on …

Gender-Specific Mental Health Outcomes In Central America: A Natural Experiment, Thea Nagasuru

Computer Science Summer Fellows

While COVID lockdown measures have had varying effects on the mental health of different demographics, several bodies of research have noted their disparate effect on women. Why is women's mental health more negatively impacted by lockdown measures, and how much more are they impacted than men? How can we predict and mitigate these negative effects on women? This paper aims to contribute to answering those questions by comparing COVID stringency measures and their effect on the gap in depression rates between men and women in two neighboring countries: Nicaragua and Honduras.

From Classroom Interaction To Academic Success: Tracing The Mediating Role Of Effective Communication In Faculty-Student Dynamics, Nadia Dahmani, Wael Ali, Mohammed Aboelenein, Mohammad A.K. Alsmairat, Mursal Faizi

All Works

This paper aimed to determine the impact of faculty communication style, student proactiveness, and academic discipline on student academic performance and student-faculty relationship quality in the United Arab Emirates (UAE) higher education context. This study also aimed to contribute to the literature by verifying the mediating impact of communication effectiveness between the selected factors. Using a cross-sectional survey design, the study sample comprised 193 university students, and it was analyzed using partial least squares structural equation modeling (PLS-SEM). The results revealed that academic discipline and the professor’s communication style enhanced communication effectiveness, whereas student proactiveness had a minimal effect. The …

Riesz Particle Markov Chain Monte Carlo Methods, Xiongming Dai

LSU Doctoral Dissertations

Markov chain Monte Carlo (MCMC) methods are simulations that explore complex statistical distributions, while bypassing the cumbersome requirement of a specific analytical expression for the target. This stochastic exploration of an uncertain parameter space comes at the expense of a large number of ``burn-in'' samples, and the computational complexity leads to the curse of dimensionality. Although at the exploration level, some methods have been proposed to accelerate the convergence of the algorithm, such as tempering, Hamiltonian Monte Carlo, Rao-redwellization, and scalable methods for better performance, they cannot avoid the stochastic nature of this exploration. We develop algorithms for the energy …

Effective Position Intelligent Decision Method Based On Model Fusion And Generative Network, Liqiang Guo, Liang Ma, Hui Zhang, Jing Yang, Lianfeng Li, Yaqi Zhai

Journal of System Simulation

Abstract: Military intelligence technology is currently the most dynamic frontier and the inevitable trend for the development of unmanned equipment in the future. Aiming at the dual requirements of reliability and real-time performance of unmanned platform autonomous decision-making in complex environments and the shortcomings of existing combat simulation technology based on rule reasoning in terms of dynamics and flexibility, a research method of principle analysis and experimental verification is adopted. Based on the shooting experiment dataset of an unmanned platform, the effective position recognition link of attack decision-making is transformed into a binary classification problem with imbalanced categories in the …

Digital Twin Modeling And Control Of Robots For Intelligent Manufacturing Scenarios, Ying Li, Lan Gao, Zhisong Zhu

Journal of System Simulation

Abstract: The introduction of Industry 4.0 and the Made in China 2025 development policy has accelerated the transformation of the manufacturing industry from automation to intelligence. Industrial robots, as the representative equipment of intelligent manufacturing, will also become more intelligent. Based on digital twin technology, digital modeling, and simulation debugging are conducted for such problems as interference and collision, tedious operation, and low efficiency of industrial robot spot welding debugging in production. Process Simulate from TECNOMATIX software is utilized to digitally model the robot spot welding station and define its motion, and TIA Portal and S7-PLCSIM Advanced are applied to …

Research On Learnable Wargame Agent Driven By Battle Scheme, Yifeng Sun, Zhi Li, Jiang Wu, Yubin Wang

Journal of System Simulation

Abstract: To enable the agent to cope with complex battle scenarios and objectives in wargame, a learnable wargame agent architecture driven by a battle scheme is proposed. By analyzing the "attachment characteristics" and "loose coupling characteristics" of the agent to wargame system, the learnable requirements of the agent are obtained. In the design of the agent framework, battle schemes are used to reduce the learning range of the agent. The finite state machine corresponds to the knowledge of the operational phase in the battle scheme, and the decision-making space of the agent is determined according to the framework of the …

A Deep Fuzzy Classifier Based On Feature Transform And Reconstruction, Rui Yin, Wei Lu, Jianhua Yang

Journal of System Simulation

Abstract: To obtain a classifier with good classification accuracy and interpretability, a deep fuzzy classifier based on feature transform and reconstruction (FR-DFC) is proposed. In FR-DFC, several fuzzy systems (FT_FS) for feature transform and a multi-prototype fuzzy classification system (MPRFD_FS) are stacked together to realize the classification process of the model, based on the hierarchically stacked thought originated from deep learning. Specifically, the stacked FT_FSs explore the hidden features in the data by transferring data from the original data space to the high-level feature space. MPRFD_FS, on the other hand, implements classification based on multiple prototypes that characterize the distribution …

Adaptive Particle Swarm Optimization Algorithm Based On Trap Label And Lazy Ant, Wei Zhang, Yuefeng Jiang

Journal of System Simulation

Abstract: Many existing strategies for improving particle swarm optimization (PSO) fall short in assisting particles trapped in local optima and experiencing premature convergence to recover optimization performance. In response, an adaptive particle swarm optimization algorithm based on trap label and lazy ant (TLLA-APSO) is proposed. Firstly, the trap label strategy dynamically adjusts particle velocities, enabling the particle swarm to escape from local optima. Secondly, the lazy ant optimization strategy is employed to diversify particle velocity and enhance population diversity. Finally, the inertia cognition strategy introduces historical position into velocity updates, promoting path diversity and particle exploration while effectively mitigating the …

Simulation Optimization Of Airport Baggage Import System Based On Multi-Objective Wolf Pack Algorithm, Yifei Tao, Xiaopeng Ding, Junbin Luo, Xiao Fu, Jiaxing Wu, Yirong Li

Journal of System Simulation

Abstract: Aiming at the problems of long waiting time for passenger baggage import and high system energy consumption during the operation of the baggage import system in civil aviation airports, a simulation optimization framework for solving this problem is proposed by comprehensively considering the influence of key control parameters on the operation efficiency of the baggage import system in airports, including the virtual window control mode, the operation speed of the collection belt conveyor, the length of the virtual window and the number of check-in counters opened at the same time. By analyzing the actual operating conditions of the airport …

Task Analysis Methods Based On Deep Reinforcement Learning, Xue Gong, Pengfei Peng, Li Rong, Yalian Zheng, Jun Jiang

Journal of System Simulation

Abstract: In response to the high coupling of task interaction and many influencing factors in task analysis, a task analysis method based on sequence decoupling and deep reinforcement learning (DRL) is proposed, which can achieve task decomposition and task sequence reconstruction under complex constraints. The method designs an environment for deep reinforcement learning based on task information interaction, while improving the SumTree algorithm based on the difference between the loss functions of the target network and the evaluation network, achieving the priority evaluation among tasks. The activation function operation mechanism is introduced into the deep reinforcement learning network, followed by …

Modeling And Verification Of Cooperative Vehicle Infrastructure System At Unsignalized Intersection Based On Time Automata, Wei Liu, Qirui Xiao, Xinhai Chen, Chang Rao, Yu Zhang, Bosi Wang

Journal of System Simulation

Abstract: Cooperative vehicle infrastructure system (CVIS) is one of the advanced solutions to enhance intersection vehicle passage safety. Due to the lack of clear specifications and standards regarding the dynamic timing and transition processes of system object state interaction in existing CVIS technologies, ensuring the safety of passage control logic is challenging. This study utilizes formal language to describe the functional logic of CVIS in unsignalized intersections, verifying the safety of system object state interaction and control logic to improve vehicle passage safety at unsignalized intersections. Simulations are conducted for scenarios including single-vehicle non-conflict, dual-vehicle conflict, and multi-vehicle conflict to …

Real-Time Non-Photorealistic Rendering Method For Black And White Comic Style In Games And Animation, Yan Hu, Lizhe Chen, Hanna Xie, Yuyao Ge, Shun Zhou, Xingquan Cai

Journal of System Simulation

Abstract: To address the issues of high resource consumption and lengthy workflow in general nonphotorealistic, this paper proposes a real-time non-photorealistic rendering method for black and white comic style in games and animation. A specialized lighting model is designed to highlight the main environmental light and the grayscale grading of diffuse reflection based on the analysis of the lighting model effect. The pre-processing of the scene is achieved by merging the various components of the lighting model. A screen space three-phase edge detection method is proposed to sequentially perform depth edge detection, normal edge detection, and color edge detection on …

Simulation System For Carrier-Based Aircraft Ammunition Support Scheduling, Zhe Liu, Jiafeng Chen, Junfei Ma, Songhua Ma

Journal of System Simulation

Abstract: For inefficient scheduling of carrier-based aircraft ammunition support on the flight deck of aircraft carriers, a Unity3D-based 3D virtual demonstration method for carrier-based aircraft ammunition scheduling is proposed, and a 3D virtual simulation system for carrier-based aircraft ammunition scheduling on the flight deck of aircraft carriers is constructed. A problem model targeted at carrierbased aircraft ammunition transportation and loading scheduling process as well as processing rules for path determination, sequence constraint, and loading position compensation are established based on the defining system. An optimal solution for the scheduling process is realized by using the improved discrete grey wolf optimizer …