Digital Commons Network^™

Multi-Strategy Partheno-Genetic Algorithm Based On Dynamic Reduction Mechanism For Solving Cvrp Problem, Jiajun Chen, Dailun Tan

Journal of System Simulation

Abstract: Aiming at the problems of premature, slow convergence and low accuracy of traditional genetic algorithm in solving capacitated vehicle routing problem,a multi-strategy partheno-genetic algorithm based on dynamic reduction mechanism is proposed. The algorithm divides the optimization space based on similar individuals, and uses simulated annealing criterion to eliminate or update the lowest category subspace, which constitutes the reduction and movement mechanism of the optimization space. Based on parthenogenetic algorithm,a variety of genetic evolution strategies including intra-group, inter-group, global search, disturbance and jump strategy are designed Based on the three penalty factors of individual development, population evolution and overall convergence, …

Unmanned Vehicle Path Planning And Tracking Control Based On Improved Artificial Potential Field Method, Minghao Guo, Peng Ji, Haiwei Huang

Journal of System Simulation

Abstract: A path planning algorithm based on improved artificial potential field method and a tracking control strategy based on model predictive controller are proposed for the unmanned vehicle avoiding dynamic obstacles in the complex scene of lane changing and overtaking. The theory of safety ellipse and the concept of prediction distance are introduced to adjust the influence region of potential field. By adding velocity potential field to change potential field function, the problem of vehicle avoiding dynamic obstacles is solved. Based on the linear three-degree-of-freedom vehicle dynamics model, a model prediction controller including potential field environment is established. The effectiveness …

Path Following Control And Simulation Analysis Of Multi-Articulated Vehicles, Yu Zhao, Caijin Yang, Tanming Wang, Jing Xu, Shuai Zhou

Journal of System Simulation

Abstract: The structure of multi-articulated vehicle body limits the flexibility of the vehicle and causes the deviation of the rear vehicle. Taking the ideal articulation angle as the control target, a feedforward plus feedback path following control method is proposed, which realizes the precise path following of rear vehicle bodies by minimizing the deviation between the ideal articulation angle and the actual articulation angle. According to the geometric position relationship between the vehicle and the desired path, the traditional calculation method of the ideal articulation angle is improved from two perspectives of application range and error accumulation. Based on the …

Improved Foggy Pedestrian And Vehicle Detection Algorithm Based On Yolov5, Tong Su, Ying Wang, Qiyang Deng, Zhaobin Li

Journal of System Simulation

Abstract: Due to the poor environment perception of car in bad weather, the detection ability on dynamic targets is significantly reduced, and thus the problems such as low accuracy and poor robustness of the deep learning-based target detection network will occur when detecting pedestrians and vehicles in foggy days. A YOLOv5-SGE foggy detection network is proposed on the basis of the combination of image dehazing DehazeNet and the improved YOLOv5. The adaptive calculation of anchor frame is realized by canceling the initial anchor frame of YOLOv5, and the anchor frame suitable for the current dataset is generated. A three-dimensional weighted …

Peer-To-Peer Energy-Carbon Management Method Of Multiple Integrated Energy Systems Considering Multi-Agent Interaction Strategy, Yudong Wang, Junjie Hu

Journal of System Simulation

Abstract: To explore a new energy management model of P2P transaction of electricity, heat and carbon among IES with the participation of ESP, a P2P energy-carbon management method of IES considering multi-agent interaction strategy is proposed. A two-layer energy management framework with the multiagent participation of involving ESP and IES is established. A two-layer electricity-heat-carbon energy management model is constructed in which the upper model is constructed based on reinforcement learning framework to optimize the energy management strategy between ESP and IES cooperative alliance and the lower model is based on Nash negotiation game theory to optimize the cooperative operation …

Wormhole Attack Mitigation In Wireless Network Using Propagation Delay, Harry May, Travis Atkison

Journal of Cybersecurity Education, Research and Practice

This paper presents a novel approach for mitigating wormhole attacks on wireless networks using propagation delay timing. The wormhole attack is a persistent security threat that threatens the integrity of network communications, potentially leading to data theft or other malicious activities. While various methods exist for combating wormhole attacks, our approach offers advantages that set it apart. Our approach involves a combination of proactive and reactive measures, harnessing box plot analysis and weighting factor techniques to identify and isolate outlier node links effectively. Unlike traditional methods, our solution not only detects outlier links but also defines dynamic weighting factors, providing …

A Method For Battlefield Situation Information Ontology Construction Based On Top-Down And Bottom-Up Integration, Cong Zhou, Sihang Zhou, Jian Huang, Dong Wang

Journal of System Simulation

Abstract: The construction of the unified expression model of battlefield situational information is challenging due to the complexity of data sources and the significant differences in data structures and expression methods. Ontologies, as semantic conceptual models, are often used to describe concepts, relationships, and attributes within knowledge domains. An ontology construction method for the battlefield situational information domain based on a top-down and bottom-top integration is proposed. The top-down method is used to construct the upper ontology, in which a conceptual hierarchy model with a clear top-down structure is designed to establish the hierarchical relationships and semantic associations. A bottom-up …

Wip: An Engaging Undergraduate Intro To Model Checking In Software Engineering Using Tla+, Konstantin Laufer, Gunda Mertin, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

Background: In this Innovative Practice Work in Progress, we present our initial efforts to integrate formal methods, with a focus on model-checking specifications written in Temporal Logic of Actions (TLA⁺), into computer science education, targeting undergraduate juniors/seniors and graduate students. Many safety-critical systems and services crucially depend on correct and reliable behavior. Formal methods can play a key role in ensuring correct and safe system behavior, yet remain underutilized in educational and industry contexts.

Aims: We aim to (1) qualitatively assess the state of formal methods in computer science programs, (2) construct level-appropriate examples that could be included …

Distributed Software Build Assurance For Software Supply Chain Integrity, Ken Lew, Arijet Sarker, Simeon Wuthier, Jinoh Kim

Faculty Publications

Computing and networking are increasingly implemented in software. We design and build a software build assurance scheme detecting if there have been injections or modifications in the various steps in the software supply chain, including the source code, compiling, and distribution. Building on the reproducible build and software bill of materials (SBOM), our work is distinguished from previous research in assuring multiple software artifacts across the software supply chain. Reproducible build, in particular, enables our scheme, as our scheme requires the software materials/artifacts to be consistent across machines with the same operating system/specifications. Furthermore, we use blockchain to deliver the …

Intelligrader: A Framework For Automatic Short Answer Grading, Inconsistency Check And Feedback In Educational Context - Conception, Implementation And Evaluation, Paradesi Sree Lakshmi, Jay B. Simha, Rajeev Ranjan

Karbala International Journal of Modern Science

Automatic Short Answer Grading (ASAG), an escalating realm in natural language understanding, constitutes a focal point of research within the broader field of learning analytics. Over time, many ASAG solutions have been proposed to address the difficulties in teaching. However, no work addressed three crucial aspects of evaluation together, i.e., i) automatic evaluation of brief subjective/descriptive answers written in English, ii) identifying the evaluation inconsistency, and iii) provision of providing feedback about inconsistent evaluation to the evaluator. The current work proposes IntelliGrader, a comprehensive ASAG system that addresses the above-mentioned issues. Automated grading is accomplished through a model answer-based approach. …

Isolation And Characterization Of Fermenting Bacterial Isolates From Vinegar Industry Waste In Local Markets Of Wasit Province, Tayseer Shamran Al-Deresawi

Karbala International Journal of Modern Science

The use of waste in the vinegar industry is an important practice of the food industry worldwide; however, this critical practice is neglected in many parts of Iraq. According to this, the current study was conducted to isolate and characterize fermenting bacterial organisms from this waste in Wasit Province, Iraq. Samples of vinegar industry by-products were collected from local businesses. These samples were prepared by using Hestrin-Schramm (HS) medium. Two methods, direct and indirect inoculations, were followed. The purified growth was examined using morphological and biochemical tests. Moreover, PCR was employed to confirm the identity of each bacterial isolate. The …

Historical Review Of Variants Of Informal Semantics For Logic Programs Under Answer Set Semantics: Gl’88, Gl’91, Gk’14, D-V’12, Yuliya Lierler

Computer Science Faculty Publications

This note presents a historical survey of informal semantics that are associated with logic programming under answer set semantics. We review these in uniform terms and align them with two paradigms: Answer Set Programming and ASP-Prolog — two prominent Knowledge Representation and Reasoning Paradigms in Artificial Intelligence.

Prevention Of Attacks Via Requested Displayable Content, Mingkui Wei, Yao Liu, Zhuo Lu, Junjie Xiong

Computer Science Faculty Research & Creative Works

A method and system disable executable script in requested displayable content. Responsive to requesting displayable content, a non-executable code sequence and a mis-matched font file that maps a plurality of characters of the requested displayable content to the non-executable code sequence is received. The non-executable code sequence is displayed as a text string in accordance with the received mis-matched font file.

Data Quality Based Intelligent Instrument Selection With Security Integration, Sergei Chuprov, Raman Zatsarenko, Leon Reznik, Igor Khokhlov

Computer Science Faculty Publications

We propose a novel Data Quality with Security (DQS) integrated instrumentation selection approach that facilitates aggregation of multi-modal data from heterogeneous sources. As our major contribution, we develop a framework that incorporates multiple levels of integration in finding the best DQS-based instrument selection: data fusion from multi-modal sensors embedded into heterogeneous platforms, using multiple quality and security metrics and knowledge integration. Our design addresses the security aspect in the instrumentation design, which is commonly overlooked in real applications, by aggregating it with other metrics into an integral DQS calculus. We develop DQS calculus that formalizes the problem of finding the …

Intensional Functions, Zachary Palmer, N. W. Filardo, K. Wu

Computer Science Faculty Works

Functions in functional languages have a single elimination form—application—and cannot be compared, hashed, or subjected to other non-application operations. These operations can be approximated via defunctionalization: functions are replaced with first-order data and calls are replaced with invocations of a dispatch function. Operations such as comparison may then be implemented for these first-order data to approximate e.g. deduplication of continuations in algorithms such as unbounded searches. Unfortunately, this encoding is tedious, imposes a maintenance burden, and obfuscates the affected code. We introduce an alternative in intensional functions, a language feature which supports the definition of non-application operations in terms …

Ai And Future-Making: Design, Biases, And Human-Plant Interactions, Maliheh Ghajargar

Art Faculty Articles and Research

Design researchers and practitioners are turning to generative AI (genAI) to support activities such as ideation and concept development in pursuit of preferred futures. At the same time, genAI is known to have biases, which prompts questions about how these biases might adversely affect design practices. In the domain of sustainable HCI, with its recent trends in human-nature interactions and more-than-human design, the question can be further refined into whether and how genAI biases might perpetuate anthropocentric biases that these practices are increasingly seeking to confront. In the present research, we conducted three workshops, focusing on genAI for human-plant interactions; …

"The Words We Do Not Yet Have." A Creative Inquiry Into Human-Plant Relationships, Maliheh Ghajargar

Art Faculty Articles and Research

Climate change, loss of plant biodiversity, and ocean pollution signal the drastic changes in our ecology that call us to attend to the needs of more than human forms of life on Earth. Sustainable design and HCI research are responding to this call by offering methods and approaches to design more sustainable products and systems and recently, more than human design is building momentum. This agenda seeks to reform traditional design processes by decentering the creative agency of the dominant socio-economical group of humans and foregrounding those of diverse Others. In this paper, I focus on plants as a nonhuman …

Happy Hours, Not Office Hours: Socially Engaging Cybersecurity Students In A Large Online Graduate Course, James T. Mccafferty

Journal of Cybersecurity Education, Research and Practice

Engagement is a critical part of student learning and student success. This is especially true in online classes where students have less interaction with their classmates and instructors when compared to traditional face-to-face courses. Research on engagement has shown that when students are meaningfully engaged it can increase student satisfaction and it may also increase levels of academic achievement, including grades earned and degree progression (e.g. Wong et al., 2024). This paper focuses on social engagement in a graduate cybersecurity program that uses large, expandable online courses as described by Whitman and Mattord (2023). Large online graduate classes (i.e., more …

Empowering Entrepreneurial Evolution: A Beyond Founder Strategic Approach To Small Business Growth, D. Jared Knisley

USF Tampa Graduate Theses and Dissertations

Growing a business beyond its founder’s capacities and talents presents a challenging undertaking. When a founder is no longer involved or motivated to grow the business, firm decline is a likely outcome. Small businesses often have a deep and, at times, hindering reliance on their early founders for development. Therefore, a continuous engaging plan to advance entrepreneurial success is needed to grow a small business.

My research objective aims to find methods and designs, through academic literature and practitioner interviews, that transition leadership responsibilities and increase team empowerment within a small business, enabling these firms to continue growing as the …

Discrete Time Series Forecasting Of Hive Weight, In-Hive Temperature, And Hive Entrance Traffic In Non-Invasive Monitoring Of Managed Honey Bee Colonies: Part I, Vladimir A. Kulyukin, Daniel Coster, Aleksey V. Kulyukin, William Meikle, Milagra Weiss

Computer Science Faculty and Staff Publications

From June to October, 2022, we recorded the weight, the internal temperature, and the hive entrance video traffic of ten managed honey bee (Apis mellifera) colonies at a research apiary of the Carl Hayden Bee Research Center in Tucson, AZ, USA. The weight and temperature were recorded every five minutes around the clock. The 30 s videos were recorded every five minutes daily from 7:00 to 20:55. We curated the collected data into a dataset of 758,703 records (208,760–weight; 322,570–temperature; 155,373–video). A principal objective of Part I of our investigation was to use the curated dataset to investigate …

Towards A Global Food Systems Datahub: Editorial, Hande Küçük Mcginty, Cogan Shimizu, Pascal Hitzler, Ajay Sharda

Computer Science and Engineering Faculty Publications

In the quest for agricultural sustainability, we face the challenge of feeding the global population under the constraints of finite resources and a delicate ecological balance. The intricate interplay of climate dynamics, socio-economic factors, and environmental stewardship demands an approach to agriculture that is as intelligent and adaptive as it is respectful of our planet’s capacities. Central to this endeavor is the synthesis and utilization of vast, heterogeneous datasets that span from crop genomics to market trends, and from soil health to consumer preferences. Yet, the current paradigm is fragmented, with valuable data isolated across domains, lacking the coherence and …

2024 Gateway Magazine, College Of Computing, Michigan Technological University

College of Computing Annual Magazines

Table of Contents

• 50 Years of Computer Science at Michigan Tech
• Data Science for a Changing Planet
• Healthcare Transformed
• Mechatronics Matters
• Powered by Michigan Tech Talent
• Esports: Bringing Everything Great about Sports to More People
• The Michigander Scholars Program: Electrifying Careers in Michigan
• College of Computing News

Interpretable Spatio-Temporal Embedding For Brain Structural-Effective Network With Ordinary Differential Equation, Haoteng Tang, Guodong Liu, Siyuan Dai, Kai Ye, Kun Zhao, Wenlu Wang, Carl Yang, Lifang He, Alex D. Leow, Paul Thompson

Computer Science Faculty Publications

The MRI-derived brain network serves as a pivotal instrument in elucidating both the structural and functional aspects of the brain, encompassing the ramifications of diseases and developmental processes. However, prevailing methodologies, often focusing on synchronous BOLD signals from functional MRI (fMRI), may not capture directional influences among brain regions and rarely tackle temporal functional dynamics. In this study, we first construct the brain-effective network via the dynamic causal model. Subsequently, we introduce an interpretable graph learning framework termed Spatio-Temporal Embedding ODE (STE-ODE). This framework incorporates specifically designed directed node embedding layers, aiming at capturing the dynamic inter-play between structural and …

Deep Learning-Based Depth Estimation Methods From Monocular Image And Videos: A Comprehensive Survey, Uchitha Rajapaksha, Ferdous Sohel, Hamid Laga, Dean A. Diepeveen, Mohammed Bennamoun

Horticulture Research Articles

Estimating depth from single RGB images and videos is of widespread interest due to its applications in many areas, including autonomous driving, 3D reconstruction, digital entertainment, and robotics. More than 500 deep learning-based papers have been published in the past 10 years, which indicates the growing interest in the task. This paper presents a comprehensive survey of the existing deep learning-based methods, the challenges they address, and how they have evolved in their architecture and supervision methods. It provides a taxonomy for classifying the current work based on their input and output modalities, network architectures, and learning methods. It also …

Advancements In The Programmable Hyperspectral Seawater Scanner Measurement Technology For Enhanced Detection Of Harmful Algal Blooms, John J. Langan, Jungyun Bae

Michigan Tech Publications

The Programmable Hyperspectral Seawater Scanner (PHySS) represents a significant breakthrough in monitoring harmful algal blooms (HABs), specifically targeting the “Florida red tide” caused by Karenia brevis. By utilizing a Fourth-Derivative Spectral Similarity Index (SI), this study establishes a strong positive correlation between the SI and phytoplankton counts, underscoring the PHySS’s potential for early detection and effective management of HABs. Our findings suggest that the PHySS could act as a predictive tool, offering crucial lead time to mitigate the ecological and economic repercussions of blooms. However, this study also identifies certain limitations of the PHySS technology, such as its inability to …

A Survey Of Advanced Border Gateway Protocol Attack Detection Techniques, Ben A. Scott, Michael N. Johnstone, Patryk Szewczyk

Research outputs 2022 to 2026

The Internet's default inter-domain routing system, the Border Gateway Protocol (BGP), remains insecure. Detection techniques are dominated by approaches that involve large numbers of features, parameters, domain-specific tuning, and training, often contributing to an unacceptable computational cost. Efforts to detect anomalous activity in the BGP have been almost exclusively focused on single observable monitoring points and Autonomous Systems (ASs). BGP attacks can exploit and evade these limitations. In this paper, we review and evaluate categories of BGP attacks based on their complexity. Previously identified next-generation BGP detection techniques remain incapable of detecting advanced attacks that exploit single observable detection approaches …

Mental Model-Based Designs: The Study In Privacy Policy Landscape, Hanieh Atashpanjeh, Rizu Paudel, Mahdi Nasrullah Al-Ameen

Computer Science Student Research

Users' mental models influence secure and privacy-preserving behavior in a computing environment. Prior studies on users' mental models of Internet, security tools, and digital privacy show that there is no one-size-fits-all solution when it comes to security and privacy design. However, little study to date has explored the ways to translate users' mental models into interactive security and privacy designs. As we begin to address this gap, we focus on privacy policy in this paper. The typical text-based privacy policy suffers from poor readability and usability. A recent study proposed a Visual Interactive Privacy Policy (VIPP), showing promise to offer …

Predictive Residual Neural Networks For Optical Trapping Of Small Particles, Nasim Mohammadi Estrakhri, Ponthea Zahraii, Saman Kashanchi, Nooshin M. Estakhri

Engineering Faculty Articles and Research

Optical tweezers provide a non-contact method to trap, move, and manipulate micro- and nano-sized objects. Using properly designed dielectric and plasmonic nanostructure configurations, optical tweezers have been tailored to create stable and precise trapping for nanoscale objects. Recent advances in numerical optimization techniques allow further enhancement in nanoscale optical traps through inverse optimization of such configurations. One of the main challenges in such optimization approaches is the time-consuming nature of full-wave simulation of nanostructures and postprocessing steps to extract optical forces. To address this challenge, we introduce a surrogate solver based on residual neural networks that can accurately predict the …

Instructional Systems Design: The Diffusion And Adoption Of Technology: (Volume 2), Cassandra Celaya (Author), Pamela J. Downing (Author), Jessica Shifflett (Author), Debbie Gdula (Author), Tracie Barr (Author), Miguel Ramlatchan (Author & Editor)

University Administration Bookshelf

Instructional designers, instructional systems designers, and other educational technologists are, by their nature, innovators. These professionals apply and extend the applied science of learning, systems, communication, and instructional design theory to help students learn. Technology in some capacity is used to make the connections between subject matter experts, teachers, instructors, and their learners. It is common for instructional designers to seek new tools, techniques, and innovations for the improvement of learning, access, quality, and student satisfaction. However, the adoption and diffusion of new educational technology and innovation is a complex process that depends on many variables. Understanding these processes and …

Bi-Directional Transformers Vs. Word2vec: Discovering Vulnerabilities In Lifted Compiled Code, Gary Mccully, John Hastings, Shengjie Xu, Adam Fortier

Research & Publications

Detecting vulnerabilities within compiled binaries is challenging due to lost high-level code structures and other factors such as architectural dependencies, compilers, and optimization options. To address these obstacles, this research explores vulnerability detection using natural language processing (NLP) embedding techniques with word2vec, BERT, and RoBERTa to learn semantics from intermediate representation (LLVM IR) code. Long short-term memory (LSTM) neural networks were trained on embeddings from encoders created using approximately 48k LLVM functions from the Juliet dataset. This study is pioneering in its comparison of word2vec models with multiple bidirectional transformers (BERT, RoBERTa) embeddings built using LLVM code to train neural …