Foreword

This special issue of the Industrial and Systems Engineering Review once again showcases the top papers from the annual General Donald R. Keith memorial capstone conference at the United States Military Academy in West Point, NY.  After consideration of over 40 academic papers, the eight listed in this issue were selected for publication in this journal.  Topics addressed in the papers span a wide spectrum, however the distinguishing aspects of each paper included a common trend; each of these papers clearly implemented some aspect of systems or industrial engineering underpinned by thoughtful analysis.  The papers focus on three general bodies of knowledge:  systems engineering, modeling and simulation, and system dynamics modeling.Systems engineering topics included two unique contributions.  The work of Byers et. al examined the trades between weapon weight and weapon lethality.  Bares et. al. examined computing and storage needs of a simulation-intense analytical organization, considering the processing, storage, and growth that such an organization would need to consider as part of their IT solution. Three papers created unique contributions primarily through modeling and simulation studies.  Grubaugh et al. explored anomaly detection in categorical data, a notoriously difficult problem domain.  Bieger et al. used discrete event simulation to analyze rail yard operations in support of military deployments.  Kumar and Mittal analyzed the feasibility and benefits of alternative organizational structures to support cyber defense, primarily using a value modeling approach.       Lastly, applied system dynamics modeling and research produced several outstanding papers, primarily across social science problems.  Led by the extensive advising efforts of Jillian Wisniewski, three of her students contributed notably.  Ferrer and Wisniewski used system dynamics to understand the growth of Boko Haram over the course of the last decade.  Riedlinger and Wisniewski applied system dynamics to better understand the replication of mass killings across the United States.  Lastly, Provaznik and Wisniewski explored the diffusion of news and information using system dynamics, analyzing important social problems created by echo chambers for ideologies. Please join me in congratulating our authors, especially the young undergraduate scholars that provided the primary intellectual efforts that created the contents of this issue.COL Paul F. Evangelista, PhD, P

Computer Intrusion Detection Through Statistical Analysis and Prediction Modeling

Information security is very important in today’s society. Computer intrusion is one type of security infraction that poses a threat to all of us. Almost every person in modern parts of the world depend upon automated information. Information systems deliver paychecks on time, manage taxes, transfer funds, deliver important information that enables decisions, and maintain situational awareness in many different ways. Interrupting, corrupting, or destroying this information is a real threat. Computer attackers, often posing as intruders masquerading as authentic users, are the nucleus of this threat. Preventive computer security measures often do not provide enough; digital firms need methods to detect attackers who have breached firewalls or other barriers. This thesis explores techniques to detect computer intruders based upon UNIX command usage of authentic users compared against command usage of attackers. The hypothesis is that computing behavior of authentic users differs from the computing behavior of attackers. In order to explore this hypothesis, seven different variables that measure computing commands are created and utilized to perform predictive modeling to determine the presence or absence of a attacker. This is a classification problem that involves two known groups: intruders and non intruders. Techniques explored include a proven algorithm published by Matthius Schonlau in [17] and several predictive model variations utilizing the aforementioned seven variables; predictive models include linear discrimination analysis, clustering, kernel partial least squares learning machines

The Unbalanced Classification Problem: Detecting Breaches in Security

This research proposes several methods designed to improve solutions for security classification problems. The security classification problem involves unbalanced, high-dimensional, binary classification problems that are prevalent today. The imbalance within this data involves a significant majority of the negative class and a minority positive class. Any system that needs protection from malicious activity, intruders, theft, or other types of breaches in security must address this problem. These breaches in security are considered instances of the positive class. Given numerical data that represent observations or instances which require classification, state of the art machine learning algorithms can be applied. However, the unbalanced and high-dimensional structure of the data must be considered prior to applying these learning methods. High-dimensional data poses a “curse of dimensionality” which can be overcome through the analysis of subspaces. Exploration of intelligent subspace modeling and the fusion of subspace models is proposed. Detailed analysis of the one-class support vector machine, as well as its weaknesses and proposals to overcome these shortcomings are included. A fundamental method for evaluation of the binary classification model is the receiver operating characteristic (ROC) curve and the area under the curve (AUC). This work details the underlying statistics involved with ROC curves, contributing a comprehensive review of ROC curve construction and analysis techniques to include a novel graphic for illustrating the connection between ROC curves and classifier decision values. The major innovations of this work include synergistic classifier fusion through the analysis of ROC curves and rankings, insight into the statistical behavior of the Gaussian kernel, and novel methods for applying machine learning techniques to defend against computer intrusion detection. The primary empirical vehicle for this research is computer intrusion detection data, and both host-based intrusion detection systems (HIDS) and network-based intrusion detection systems (NIDS) are addressed. Empirical studies also include military tactical scenarios

Modelado dinámico y control de la ventilación pulmonar

La ventilación asistida es un mecanismo de soporte vital utilizado cuando las demandas de aire no pueden ser satisfechas por el paciente. La propuesta de procesos de identificación y la obtención de modelos son la base de aplicaciones clínicas como detección y diagnóstico de enfermedades, monitoreo respiratorio, optimización de tratamientos y diseño de equipos de ventilación robustos y autónomos.Área: TICs, Electrónica e Informática

Military Resource Allocation as a Set Covering Problem

Fixed location resource allocation modeled as a set covering problem is a classic integer program.  This framework has been widely applied to emergency service resource allocation, and this paper extends this approach to military resource allocation.  Using military air medical evacuation resource allocation in Afghanistan as a proof of concept, a methodology is presented that could easily extend to other operational environments and other military resource allocation problems.  Unique contributions include clustering of enemy activity reports to support demand signal analysis and consideration of set covering requirements for varying demand signal density

Representation of Search and Target Acquisition Protocol in Models and Simulation

This research evaluates the representation of individual Soldier Search and Target Acquisition (STA) protocols in models and simulation and identifies gaps in the current methodology and implementation. The primary contributions of this research include a synthesis of related literature, an algorithmic exploration of the current STA algorithms implemented in military simulation models, a functional analysis of three systems with a significant relationship to STA, and a determination of gaps and proposed solutions to improve the representation of human STA in military simulation models. The analysis highlighted gaps in three important STA representations: (1) field of view search, (2) identification in a field of view, and (3) information acquisition and situational awareness. Implications and recommendations to resolve these gaps are discussed

Soldier Power Operational Benefit Analysis

An operational benefit analysis of military small unit power (SUP) equipment is presented in detail.  SUP equipment is designed to improve power generation, conservation, and overall power management strategies for dismounted military units.  The operational benefit analysis examines four tactical scenarios and considers a naïve power management strategy and a SUP enabled power management strategy.  The major findings and conclusions discussed in this paper include: specific conservation and generation strategies for select dismounted tactical scenarios; the importance of proper solar blanket employment; identification of a capability gap between 100W and 1000W in the power generation spectrum; the benefits of using conformal batteries; and the impact of inefficient PRC 154 battery swaps in the naïve case

Anomaly Detection and Accuracy Measurement for Categorical Data

The Department of Defense (DoD) recently initiated an effort to compile all inter-service maintenance data for equipment and infrastructure, requiring the consolidation of maintenance records from over 40 different data sources.  This research evaluates and improves the accuracy of this maintenance data warehouse by means of value modeling and statistical methods for anomaly detection. The first step in this work included the categorization of error-identifying metadata, which was then consolidated into a weighted scoring model. The most novel aspect of the work involved error identification processes using conditional probability combinations and likelihood measures. This analysis showed promising results, successfully identifying numerous invalid maintenance description labels through the use of conditional probability tests. This process has potential to both reduce the amount of manual labor necessary to clean the DoD maintenance data records and provide better fidelity on DoD maintenance activities

Local Knowledge of Plants and Their Uses Among Women in the Bale Mountains, Ethiopia

Women’s local ecological knowledge (LEK) is noted by many scholars to be unique and important for local conservation and development planning. Although LEK integration is inherent to ethnobotanical research, in Ethiopia, the knowledge-gender link has not been fully explored, and few studies focus on women’s distinct plant knowledge. We catalogued rural women’s knowledge of a wide range of plant uses in south-central Ethiopia, conducted through picture identification of 337 local plants. Fifty-seven plant species were identified, constituting 38 families, with the top five families being Lamiaceae, Solanaceae, Asteraceae, Rosaceae, and Pteridaceae. An array of uses were identified ranging from food, livestock and wildlife forage, to honey production and cosmetics. The most prevalent use noted (nearly 70%) was human medicine. This study reveals the important contribution of rural women’s plant knowledge in the Bale Mountains, and the potential benefits of including this gender-distinct understanding of local flora in community-based conservation planning

Efecto del Bullying en la conducta suicida: el rol mediador de la autoestima en estudiantes de secundaria de Chimbote, 2023

La actual investigación tuvo como objetivo explicar la conducta suicida a partir del bullying y autoestima, fue una investigación aplicada de carácter correlacional teniendo como muestra 270 alumnos de ambos sexos pertenecientes al nivel secundaria con edades de 12 a 17 años en un colegio de la ciudad de Chimbote. El enfoque utilizado es de naturaleza básica y cuantitativa, con un diseño transversal predictivo. Los resultados mediante este estudio demuestran que el acoso escolar se relaciona en sentido negativo con la autoestima (r= -.220** a - .308**), en comparación al suicidio, siendo esta positiva (r=.114 a .340**). Asimismo, en cuanto a la correlación entre la autoestima con suicidio se relaciona en sentido negativo (r=-.530**). En lo que concierne a materia de sexo, se aprecia que, en mujeres hay un mayor grado de correlación entre victimización y autoestima (r=-.338**) y en autoestima con suicidio (r=-.595**); en tanto, a varones se da mayor grado de correlación en agresión y autoestima (r=-.294**), suicidio con el acoso total y sus dimensiones (r=.226** a .384**). En base a las conclusiones, la investigación encontró correlaciones significativas entre el bullying, la autoestima y la conducta suicida, enfatizando la relevancia de promover una autoestima positiva como medida de prevención