Business Commons^™

Exploring Social Networks: An Analysis Of Intra-Organizational Networks, Ximeng Chen, Yiding Cao, Jiachen Liu, Danushka Bandara, Hiroki Sayama

Northeast Journal of Complex Systems (NEJCS)

This research investigates intra-organizational social networks by employing network science methods, aiming to provide actionable insights for both managers and employees. Using datasets from the Colorado Index of Complex Networks (ICON), this study examines four intra-organizational networks from a consulting firm and a research team, focusing on advice requests and skill awareness. The analysis includes network topology, degree distribution, community detection, correlation between communities and node attributes, maximal clique detection, and multilayer network analysis. The findings reveal that intra-organizational networks are intricate and significantly impact organizational efficiency and individual career development. Key insights include the importance of mid-level employees in …

Insights On Strategy And Approach For China To Construct A Modern Integrated Circuits Industrial System, Ximing Yin, Beibei Zhang, Tailun Chen, Jiang Yu, Jin Chen

Bulletin of Chinese Academy of Sciences (Chinese Version)

The integrated circuit (IC) industry is highly complex and systematic, and its key core technology breakthroughs are highly dependent on the support of systematic capabilities. The West especially the United States has accelerated the promotion of the “small-yard, high-fence” strategy, the “New Washington Consensus”, the “de-risking”, and other systematic policies to curb China’s rise. China’s IC industry chain is facing extreme risks such as rupture or blockage. Meanwhile, facing the new mission and requirements of Chinese modernization and new-quality productivity, China needs to accelerate the modernization of the IC industry with new development paradigms, new strategies, and new approaches. Based …

Deep Integration Of Technological Innovation And Industrial Innovation In Modern Industrial System: Inspiration From Global New Generation Lithography Systems, Jiang Yu, Feng Chen, Yue Guo

Bulletin of Chinese Academy of Sciences (Chinese Version)

Utilizing technological innovation to lead the construction of a modern industrial system is a strategic choice for seizing the opportunities of the new round of technological revolution and industrial transformation. It is also a necessary step for winning the strategic initiative towards high-level self-reliance and self-improvement. Technological innovation is the intrinsic driving force behind industrial innovation, and industrial innovation is the value embodiment of technological innovation. The deep integration of technological innovation and industrial innovation is the key to constructing and improving a modern industrial system. Taking the global extreme ultra-violet (EUV) lithography system as an example, based on the …

2024 Marine Energy Collegiate Competition, Nora Riedinger, Miles Mikkelsen, Brendan Stratford, Derek Tom, Zach Kwast, Harmon Yanikian-Sutton, Kennedy Urcelay, Tori Thomas, Brady Caron

Mechanical Engineering

PolyWave Energy is the second team from California Polytechnic University at San Luis Obispo to compete in the Marine Energy Collegiate Competition. PolyWave Energy consists of Mechanical Engineering, Electrical Engineering, and Business Administration students who have worked together from September 2023 to May 2024 on designing, building, and testing a marine power device to serve a selected market.

In response to the escalating concerns surrounding carbon emissions, climate change, and the depletion of fossil fuels, California Polytechnic State University’s Polywave Energy team has developed a sustainable and reliable energy source for Autonomous Underwater Vehicle (AUV) charging. Through extensive research of …

Effect Of Recommending Users And Opinions On The Network Connectivity And Idea Generation Process, Sriniwas Pandey, Hiroki Sayama

Northeast Journal of Complex Systems (NEJCS)

The growing reliance on online services underscores the crucial role of recommendation systems, especially on social media platforms seeking increased user engagement. This study investigates how recommendation systems influence the impact of personal behavioral traits on social network dynamics. It explores the interplay between homophily, users’ openness to novel ideas, and recommendation-driven exposure to new opinions. Additionally, the research examines the impact of recommendation systems on the diversity of newly generated ideas, shedding light on the challenges and opportunities in designing effective systems that balance the exploration of new ideas with the risk of reinforcing biases or filtering valuable, unconventional …

Bidding Strategy For A Wind Power Producer In Us Energy And Reserve Markets, Anne Stratman

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Wind power is one of the world's fastest-growing renewable energy resources and has expanded quickly within the US electric grid. Currently, wind power producers (WPPs) may sell energy products in US markets but are not allowed to sell reserve products, due to the uncertain and intermittent nature of wind power. However, as wind’s share of the power supply grows, it may eventually be necessary for WPPs to contribute to system-wide reserves. This paper proposes a stochastic optimization model to determine the optimal offer strategy for a WPP that participates in the day-ahead and real-time energy and spinning reserve markets. The …

Effectiveness Of Cnn-Lstm Models Used For Apple Stock Forecasting, Ethan White

Electronic Theses, Projects, and Dissertations

This culminating experience project investigates the effectiveness of convolutional neural networks mixed with long short-term memory (CNN-LSTM) models, and an ensemble method, extreme gradient boosting (XGBoost), in predicting closing stock prices. This quantitative analysis utilizes recent AAPL stock data from the NASDAQ index. The chosen research questions (RQs) are: RQ1. What are the optimal hyperparameters for CNN-LSTM models in stock price forecasting? RQ2. What is the best architecture for CNN-LSTM models in this context? RQ3. How can ensemble techniques like XGBoost effectively enhance the predictions of CNN-LSTM models for stock price forecasting?

The research questions were answered through a thorough …

A Study On The Incentives And Barriers For The Adoption Of Electric Vehicles In South Alabama, Marianne Loes, Daniela Wolter Ferreira Touma, Jennifer C. Zoghby

Association of Marketing Theory and Practice Proceedings 2024

ABSTRACT

Through a series of public policy incentives and consumer demand, more electric vehicles are being sold nationwide than ever before. Although electric vehicles (EVs) are being adopted nationwide by many consumers in recent years, car-buyers across South Alabama have not followed the trend. This research considers different stakeholders in the complex consumer buying process of car purchases, and it uses the extant technology adoption models to assess the public policy incentives, as well as statewide roadblocks, to EV adoption.

Energy Efficiency In Additive Manufacturing: Condensed Review, Ismail Fidan, Vivekanand Naikwadi, Suhas Alkunte, Roshan Mishra, Khalid Tantawi

Engineering Technology Faculty Publications

Today, it is significant that the use of additive manufacturing (AM) has growing in almost every aspect of the daily life. A high number of sectors are adapting and implementing this revolutionary production technology in their domain to increase production volumes, reduce the cost of production, fabricate light weight and complex parts in a short period of time, and respond to the manufacturing needs of customers. It is clear that the AM technologies consume energy to complete the production tasks of each part. Therefore, it is imperative to know the impact of energy efficiency in order to economically and properly …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Novel Non-Invasive Detection Of Thin Film Biofilm And Classification Of Deposits Using Machine Learning, Sachin Davis

Theses and Dissertations

Clean, safe, readily available water is vital for public health, irrespective of whether it is used for drinking, domestic use, food production, or recreational purposes. Globally, around two billion people use feces-contaminated water sources, which poses a high risk to the safety of drinking water due to the high probability of water contamination. Microbial-influenced corrosion is a significant problem in several industries, including but not limited to wastewater treatment, drinking water distribution systems, food industries, power plants, paper industries, and chemical manufacturing facilities. The presence of microorganisms causes around 70% of the corrosion in gas transmission pipelines, and corrosion accounts …

Rattus Norvegicus As A Biological Detector Of Clandestine Remains And The Use Of Ultrasonic Vocalizations As A Locating Mechanism, Gabrielle M. Johnston

Master's Theses

In investigations, locating missing persons and clandestine remains are imperative. One way that first responder and police agencies can search for the remains is by using cadaver dogs as biological detectors. Cadaver dogs are typically used due to their olfactory sensitivity and ability to detect low concentrations of volatile organic compounds produced by biological remains. Cadaver dogs are typically chosen for their stamina, agility, and olfactory sensitivity. However, what is not taken into account often is the size of the animal and the expense of maintaining and training the animal. Cadaver dogs are typically large breeds that cannot fit in …

Trace Dna Detection Using Diamond Dye: A Recovery Technique To Yield More Dna, Leah Davis

Master's Theses

This study aspires to find a new screening approach to trace DNA recovery techniques to yield a higher quantity of trace DNA from larger items of evidence. It takes the path of visualizing trace DNA on items of evidence with potential DNA so analysts can swab a more localized area rather than attempting to recover trace DNA through the general swabbing technique currently used for trace DNA recovery. The first and second parts consisted of observing trace DNA interaction with Diamond Dye on porous and non-porous surfaces.

The third part involved applying the Diamond Dye solution by spraying it onto …

Geopolitics Of Semiconductor Supply Chains: The Case Of Tsmc, Us-China-Taiwan Relations, And The Covid-19 Crisis, Aditya Sehgal

Independent Study Project (ISP) Collection

As the demand for more advanced forms of technology continues to grow, so does the global importance and reliance on semiconductors. This research paper examines the impact of semiconductor shortages on both consumer and military production, as well as the geopolitical implications embedded within the global supply chain.

The paper begins by providing an overview of semiconductors, the global semiconductor market, and the impact of COVID-19 on the industry’s supply chain. It also discusses the importance of the Taiwan Semiconductor Manufacturing Company (TSMC) in the industry and its role in addressing semiconductor shortages.

Next, the paper discusses the impact of …

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …

Ads-B Communication Interference In Air Traffic Management, George Ray

International Journal of Aviation, Aeronautics, and Aerospace

Automated Dependent Surveillance Broadcast (ADS-B) provides position and state information about aircraft and is becoming an essential component in the global air traffic management system. ADS-B transponders broadcast this key information on a common frequency to both other aircraft and to secondary surveillance radar systems located at ground stations. Both the aircraft transponders and the ground stations work together to assist in managing the commercial airspace. Since the aircraft transponders all broadcast on the same frequency and are in close proximity there is an apparent risk of interference and the garbling of the communications needed to manage the airspace.

The …

Development Of Sensing And Programming Activities For Engineering Technology Pathways Using A Virtual Arduino Simulation Platform, Murat Kuzlu, Vukica Jovanovic, Otilia Popescu, Salih Sarp

Engineering Technology Faculty Publications

The Arduino platform has long been an efficient tool in teaching electrical engineering technology, electrical engineering, and computer science concepts in schools and universities and introducing new learners to programming and microcontrollers. Numerous Arduino projects are widely available through the open-source community, and they can help students to have hands-on experience in building circuits and programming electronics with a wide variety of topics that can make learning electrical prototyping fun. The educational fields of electrical engineering and electrical engineering technology need continuous updating to keep up with the continuous evolution of the computer system. Although the traditional Arduino platform has …

A Low-Cost, Low-Power, Scada Testbed Solution For Secure Remote Monitoring, Connor Berger

Symposium of Student Scholars

Similar to software application systems adopted by companies and businesses for product logging, payroll, human resources, Supervisory Control and Data Acquisition (SCADA) systems control the distributed processes with multiple components located on different machines that communicate and coordinate actions in order to appear as a single coherent system. SCADA systems severely lack the appropriate security and hack prevention measures. We propose a low cost, low power SCADA testbed solution for secure remote monitoring. The goal of this research is to implement and test the testbed’s security by emulating attack vectors on both hardware components and communication channels to probe the …

Study Of Stochastic Market Clearing Problems In Power Systems With High Renewable Integration, Saumya Sakitha Sashrika Ariyarathne

Operations Research and Engineering Management Theses and Dissertations

Integrating large-scale renewable energy resources into the power grid poses several operational and economic problems due to their inherently stochastic nature. The lack of predictability of renewable outputs deteriorates the power grid’s reliability. The power system operators have recognized this need to account for uncertainty in making operational decisions and forming electricity pricing. In this regard, this dissertation studies three aspects that aid large-scale renewable integration into power systems. 1. We develop a nonparametric change point-based statistical model to generate scenarios that accurately capture the renewable generation stochastic processes; 2. We design new pricing mechanisms derived from alternative stochastic programming …

Project Khepri: Mining Asteroid Bennu For Water, Erika Frost, Gowtham Boyala, Adam Gremm, Ahmet Gungor, Amirhossein Taghipour, Massimo Biella, Jiawei "Jackson" Qiu, Athip Thirupathi Raj, Arjun Chhabra, Adam Gee, Saanjali Maharaj, Erin Richardson, Julia Empey, Haidar Ali Abdul-Nabi, Lindsay Richards, Ariyaan Talukder, Aaron Groh, Brie Miklaucic, Jd Carlson, Kristina Kim, Maverick Cue

Undergraduate Student Research Internships Conference

Deep space asteroid mining presents the opportunity for the collection of critical resources required to establish a cis-lunar infrastructure. In specific, the Project Khepri team has focused on the collection of water from asteroid Bennu. This water has the potential to provide a source of clean-energy propellant as well as an essential consumable for humans or agriculture on crewed trips to the Moon or Mars. This would avoid the high costs of launching from Earth - making it a highly desirable element for the future of cis-lunar infrastructure. The OSIRIS-REx mission provided a complete survey of asteroid Bennu and is …

Credit Card Fraud Detection Using Machine Learning Techniques, Nermin Samy Elhusseny, Shimaa Mohamed Ouf, Amira M. Idrees Ami

Future Computing and Informatics Journal

This is a systematic literature review to reflect the previous studies that dealt with credit card fraud detection and highlight the different machine learning techniques to deal with this problem. Credit cards are now widely utilized daily. The globe has just begun to shift toward financial inclusion, with marginalized people being introduced to the financial sector. As a result of the high volume of e-commerce, there has been a significant increase in credit card fraud. One of the most important parts of today's banking sector is fraud detection. Fraud is one of the most serious concerns in terms of monetary …

Electrical Equipment Industry Cluster, Pragati Gautam

2022 REYES Proceedings

The growing collaboration between two or more industries in a specific region in which they work in a symbiotic relationship, providing benefits to each other and contributing in the overall development of the region, is what is popularly known as business clusters. Even though this concept is commonly known and implemented in the West, South Asian economies are unfamiliar with the advantages of this unique business strategy. There are, undeniably, many potential business clusters in these developing countries, which if tapped efficiently, could result into an industrial boom.

This research focuses on investigating the existence of a business cluster in …

Effective Green Marketing Strategies On Social Media: Selling Companies And Their Consumers On Investing In Carbon Offsetting And Solar Energy In 2021, Melvin Richard Springer Iv

Honors Theses

In a digital world where consumers and businesses alike care significantly about sustainability and corporate social responsibility (CSR), the success of startup companies hinges on constant, clear, and thoughtful communication. Through my research into successfully marketing such concerns on social media as well as my internship at Clearloop, I discovered some of the best ways to convince both companies and consumers that preserving the planet should be a primary concern for every environmentally conscious company. Companies that ignore their impacts on the environment are synonymous with companies doomed to fail in the 21^st century. Clearloop’s model of partnering with …

Representing And Analyzing The Dynamics Of An Agent-Based Adaptive Social Network Model With Partial Integro-Differential Equations, Hiroki Sayama

Northeast Journal of Complex Systems (NEJCS)

We formulated and analyzed a set of partial integro-differential equations that capture the dynamics of our adaptive network model of social fragmentation involving behavioral diversity of agents. Previous results showed that, if the agents’ cultural tolerance levels were diversified, the social network could remain connected while maintaining cultural diversity. Here we converted the original agent-based model into a continuous equation-based one so we can gain more theoretical insight into the model dynamics. We restricted the node states to 1-D continuous values and assumed the network size was very large. As a result, we represented the whole system as a set …

The Music Bluetooth Controller: An Intersection Between Technology And Music, Lydia Wu

Senior Honors Theses

The modern musician faces a new challenge: how can technology be used to enhance a performance? This thesis documents the development of a Bluetooth remote controller that will aid today’s performing musicians by interacting with a digital display (e.g., an iPad) to flip musical score pages remotely. At its core, while mimicking a Bluetooth pedal (the current industry standard), this device attaches to the musician’s hand. In its pilot stages, the device has been referred to “MBC” (Music Bluetooth Controller).

Bistability And Switching Behavior In Moving Animal Groups, Daniel Strömbom, Stephanie Nickerson, Catherine Futterman, Alyssa Difazio, Cameron Costello, Kolbjørn Tunstrøm

Northeast Journal of Complex Systems (NEJCS)

Moving animal groups such as schools of fish and flocks of birds frequently switch between different group structures. Standard models of collective motion have been used successfully to explain how stable groups form via local interactions between individuals, but they are typically unable to produce groups that exhibit spontaneous switching. We are only aware of one model, constructed for barred flagtail fish that are known to rely on alignment and attraction to organize their collective motion, that has been shown to generate this type of behavior in 2D (or 3D). Interestingly, another species of fish, golden shiners, do exhibit switching …

Cloud-Based Machine Learning And Sentiment Analysis, Emmanuel C. Opara

Electronic Theses and Dissertations

The role of a Data Scientist is becoming increasingly ubiquitous as companies and institutions see the need to gain additional insights and information from data to make better decisions to improve the quality-of-service delivery to customers. This thesis document contains three aspects of data science projects aimed at improving tools and techniques used in analyzing and evaluating data. The first research study involved the use of a standard cybersecurity dataset and cloud-based auto-machine learning algorithms were applied to detect vulnerabilities in the network traffic data. The performance of the algorithms was measured and compared using standard evaluation metrics. The second …

Laptop Recycling Case Study: Estimating The Contained Value And Value Recovery Process Feasibility Of End-Of-Life Consumer Electronics, Zebulon Hart

Theses and Dissertations--Mining Engineering

Work has been done to establish, through the development and use of novel assay techniques and analysis metrics, the contained value of a sampling of laptop computers (as an analog for myriad e-waste sources). This work has conceptualized e-waste as an alternative to geologic-origin complex metallic ores and has likewise evaluated the feasibility of value recovery from e-waste sources in a similar manner to an ore. The application of conventional and novel mineral separation techniques to e-waste recycling processes has been evaluated and positive results are demonstrated. Further, this work has demonstrated the ability to identify the presence of base …

Leveraging Maching Learning In Financial Fraud Forensics In The Age Of Cybersecurity, Md. Ariful Haque, Sachin Shetty

VMASC Publications

Financial sectors are lucrative cyber-attack targets because of their immediate financial gain. As a result, financial institutions face challenges in developing systems that can automatically identify security breaches and separate fraudulent transactions from legitimate transactions. Today, organizations widely use machine learning techniques to identify any fraudulent behavior in customers' transactions. However, machine learning techniques are often challenging because of financial institutions' confidentiality policy, leading to not sharing the customer transaction data. This chapter discusses some crucial challenges of handling cybersecurity and fraud in the financial industry and building machine learning-based models to address those challenges. The authors utilize an open-source …

Bitcoin Selfish Mining Modeling And Dependability Analysis, Chencheng Zhou, Liudong Xing, Jun Guo, Qisi Liu

Electrical & Computer Engineering Faculty Publications

Blockchain technology has gained prominence over the last decade. Numerous achievements have been made regarding how this technology can be utilized in different aspects of the industry, market, and governmental departments. Due to the safety-critical and security-critical nature of their uses, it is pivotal to model the dependability of blockchain-based systems. In this study, we focus on Bitcoin, a blockchain-based peer-to-peer cryptocurrency system. A continuous-time Markov chain-based analytical method is put forward to model and quantify the dependability of the Bitcoin system under selfish mining attacks. Numerical results are provided to examine the influences of several key parameters related to …