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Parameters Spring 2024, Usawc Press

The US Army War College Quarterly: Parameters

No abstract provided.

From The Editor In Chief, Antulio J. Echevarria Ii

The US Army War College Quarterly: Parameters

Welcome to the Spring 2024 issue of Parameters. Readers will note a few differences in the formatting for this issue: we are now using endnotes instead of footnotes to facilitate switching from pdf to html via Adobe's Liquid App; also, readers will be able to click on each endnote number to view the full endnote and then switch back to the text to resume reading. Please drop us a note to let us know how you like the changes. More are coming!

Ability Of Detecting And Willingness To Share Fake News, K. Peren Arin, Deni Mazrekaj, Marcel Thum

All Works

By conducting large-scale surveys in Germany and the United Kingdom, we investigate the individual-level determinants of the ability to detect fake news and the inclination to share it. We distinguish between deliberate and accidental sharing of fake news. We document that accidental sharing is much more common than deliberate sharing. Furthermore, our results indicate that older, male, high-income, and politically left-leaning respondents better detect fake news. We also find that accidental sharing decreases with age and is more prevalent among right-leaning respondents. Deliberate sharing of fake news is more prevalent among younger respondents in the United Kingdom. Finally, our results …

Specific Educational Needs Detection In Autism Spectrum Disorder (Asd) In Superior Middle Level Students Students, Rebeca Thelma Martínez Villarreal, Brenda Elizabeth Salas Herrera, Alan Fernando García Martínez, Claudia Cecilia Salazar Garza, José Guadalupe Sánchez Hernández, Irma Cecilia Rico Ramírez

Research Symposium

Purpose: Detection ASD and intervention in superior middle level students at Universidad Autónoma de Nuevo León (UANL), Mexico.

Description: Upon admission to superior middle level at UANL, modified Gilliam Asperger's disorder scale (GADS) was applied to parents in a Program to identify behavioral characteristics associated to ASD.

Parents of students with positive GADS were informed and students were scheduled for standard psychological testing in order to evaluate cognitive process, study habits, social anxiety and self-esteem, prior to an intervention.

From 2014 to 2020, 178 013 GADS were applied; there were 332 (0.19%) students with definite or suggestive pattern of ASD. …

A Machine Learning Approach To Deepfake Detection, Delaney Conrad

All Undergraduate Theses and Capstone Projects

The ability to manipulate videos has been around for decades but a process that once would take time, money, and professionals, can now be created by anyone due to the rapid advancement of deepfake technology. Deepfakes use deep learning artificial intelligence to make fake digital content, typically in the form of swapping a person’s face in a video or image. This technology could easily threaten and manipulate individuals, corporations, and political organizations, so it is essential to find methods for detecting deepfakes. As the technology for creating deepfakes continues to improve, these manipulated videos are becoming increasingly undetectable. It is …

An Update On The Influence Of Natural Climate Variability And Anthropogenic Climate Change On Tropical Cyclones, Suzana J. Camargo, Hiroyuki Murakami, Nadia Bloemendaal, Savin S. Chand, Medha S. Deshpande, Christian Dominguez-Sarmiento, Juan Jesús González-Alemán, Thomas R. Knutson, I. I. Lin, Il- Ju Moon, Christina M. Patricola, Kevin A. Reed, Malcolm J. Roberts, Enrico Scoccimarro, Chi Yung Tam, Elizabeth J. Wallace, Liguang Wu, Yohei Yamada, Wei Zhang, Haikun Zhao

OES Faculty Publications

A substantial number of studies have been published since the Ninth International Workshop on Tropical Cyclones (IWTC-9) in 2018, improving our understanding of the effect of climate change on tropical cyclones (TCs) and associated hazards and risks. These studies have reinforced the robustness of increases in TC intensity and associated TC hazards and risks due to anthropogenic climate change. New modeling and observational studies suggested the potential influence of anthropogenic climate forcings, including greenhouse gases and aerosols, on global and regional TC activity at the decadal and century time scales. However, there are still substantial uncertainties owing to model uncertainty …

Afnd: Arabic Fake News Dataset For The Detection And Classification Of Articles Credibility, Ashwaq Khalil, Moath Jarrah, Monther Aldwairi, Manar Jaradat

All Works

The news credibility detection task has started to gain more attention recently due to the rapid increase of news on different social media platforms. This article provides a large, labeled, and diverse Arabic Fake News Dataset (AFND) that is collected from public Arabic news websites. This dataset enables the research community to use supervised and unsupervised machine learning algorithms to classify the credibility of Arabic news articles. AFND consists of 606912 public news articles that were scraped from 134 public news websites of 19 different Arab countries over a 6-month period using Python scripts. The Arabic fact-check platform, Misbar, is …

Indicators Of Deception: Science Or Non-Science, Kristina Vasquez

Undergraduate Honors Theses

Deception detection is used by many law enforcement professionals who work in interviews and interrogations. The ability to detect deception or having knowledge on the signs of deception is very important in not only law enforcement, but in other careers and everyday life. The question remains: is deception detection a science or not a science? There are three areas where someone can learn how to detect deception and those are verbal communication, non-verbal communication, and paralanguage. The use of verbal communication looks at what the person is saying with their words. The use of non-verbal communication looks at what someone …

Proof Positive: Applications Of Chemical Analysis Techniques In Art Forgery Detection, Joseph Fryc

Museum Studies Theses

In response to the subjective nature of older forgery detection techniques, modern forgery detection methods rely heavily on chemical analysis of the materials utilized in a given piece of work in order to make authenticity determinations. Chemical methods of detection at their core provide an objective determination of facts regarding the composition of materials utilized in contested pieces and provide a relative date of production for those materials. In this way, chemical analysis helps service the field of modern forgery detection as a direct compliment to traditional stylistic analysis, by providing extra data on the piece that can often be …

A Hybrid Unsupervised Clustering-Based Anomaly Detection Method, Guo Pu, Lijuan Wang, Jun Shen, Fang Dong

Faculty of Engineering and Information Sciences - Papers: Part B

In recent years, machine learning-based cyber intrusion detection methods have gained increasing popularity. The number and complexity of new attacks continue to rise; therefore, effective and intelligent solutions are necessary. Unsupervised machine learning techniques are particularly appealing to intrusion detection systems since they can detect known and unknown types of attacks as well as zero-day attacks. In the current paper, we present an unsupervised anomaly detection method, which combines Sub-Space Clustering (SSC) and One Class Support Vector Machine (OCSVM) to detect attacks without any prior knowledge. The proposed approach is evaluated using the well-known NSL-KDD dataset. The experimental results demonstrate …

Vulnerabilities To Online Social Network Identity Deception Detection Research And Recommendations For Mitigation, Max Ismailov, Michail Tsikerdekis, Sherali Zeadally

Information Science Faculty Publications

Identity deception in online social networks is a pervasive problem. Ongoing research is developing methods for identity deception detection. However, the real-world efficacy of these methods is currently unknown because they have been evaluated largely through laboratory experiments. We present a review of representative state-of-the-art results on identity deception detection. Based on this analysis, we identify common methodological weaknesses for these approaches, and we propose recommendations that can increase their effectiveness for when they are applied in real-world environments.

Investigation Of The History Of Fingerprinting, Advancements In The Field, And Development Of Potential Methods That Could Improve The Detection Of Endogenous And Exogenous Drugs In Latent Prints, Kristen Malloy

Honors Theses

When someone thinks of fingerprinting, they are most likely going to picture how a latent print is matched to the fingerprint of a suspect based on ridge pattern analysis. However, there is much more information that can be obtained from a latent print. The work performed in this thesis focuses the detection of exogenous and endogenous drugs in latent prints. The experiments performed analyzed fingerprints from volunteers that were contaminated with one of three common painkillers: acetaminophen, acetylsalicylic acid (ASA), and ibuprofen. Three different instruments were tested for this purpose: MALDI-MS, ATR-FTIR, and LC-MS. Based on the results gathered, it …

Deep Gabor Neural Network For Automatic Detection Of Mine-Like Objects In Sonar Imagery, Hoang Thanh Le, Son Lam Phung, Philip B. Chapple, Abdesselam Bouzerdoum, Christian H. Ritz, Le Chung Tran

Faculty of Engineering and Information Sciences - Papers: Part B

With the advances in sonar imaging technology, sonar imagery has increasingly been used for oceanographic studies in civilian and military applications. High-resolution imaging sonars can be mounted on various survey platforms, typically autonomous underwater vehicles, which provide enhanced speed and improved data quality with long-range support. This paper addresses the automatic detection of mine-like objects using sonar images. The proposed Gabor-based detector is designed as a feature pyramid network with a small number of trainable weights. Our approach combines both semantically weak and strong features to handle mine-like objects at multiple scales effectively. For feature extraction, we introduce a parameterized …

Air Void Detection Using Variational Mode Decomposition With Low Rank, Fok Hing Chi Tivive, Abdesselam Bouzerdoum, Shivakumar Karekal

Faculty of Engineering and Information Sciences - Papers: Part B

This paper presents an air-void detection technique for air-coupled radar, which emits electromagnetic waves to interrogate an air-void inside a medium or between two media. The reflections from the air-medium interfaces are usually corrupted by air-coupling, antenna ringing, and internal reflections, rendering air-void detection very difficult or, in certain cases, impossible. The proposed method exploits the low-rank structure of the background clutter to suppress these nuisance signals. A variational mode decomposition model is developed to extract the backscattering at different air-medium interfaces as signal modes. Real experiments are conducted using a stepped frequency radar. The experimental results show that the …

Ensemble Machine Learning Approaches For Webshell Detection In Internet Of Things Environments, Binbin Yong, Wei Wei, Kuan-Ching Li, Jun Shen, Qingguo Zhou, Marcin Wozniak, Dawid Polap, Robertas Damasevicius

Faculty of Engineering and Information Sciences - Papers: Part B

The Internet of things (IoT), made up of a massive number of sensor devices interconnected, can be used for data exchange, intelligent identification, and management of interconnected “things.” IoT devices are proliferating and playing a crucial role in improving the living quality and living standard of the people. However, the real IoT is more vulnerable to attack by countless cyberattacks from the Internet, which may cause privacy data leakage, data tampering and also cause significant harm to society and individuals. Network security is essential in the IoT system, and Web injection is one of the most severe security problems, especially …

Do Faces Facilitate Or Distract Children From Attending To Threats?, Sarah A. Skidmore

Senior Honors Projects, 2010-2019

Threatening stimuli may produce an attentional bias in humans, capturing and holding attention to a greater extent than other types of stimuli. Humans rely on others to alert their attention to threats in their environment, and social stimuli, such as faces, have privileged processing compared to nonsocial stimuli. We wanted to explore whether task-irrelevant fearful or neutral faces facilitate, distract, or have no effect on the detection of threatening or neutral images (spiders and frogs, respectively). Three- to-five-year-old children (N=37) completed a visual search task in which they searched for threatening or neutral animals. Consistent with previous literature, we found …

Lidar-Based Sinkhole Detection And Mapping In Knox County, Tennessee, J Clint Shannon, David Moore, Yingkui Li, Cathy Olsen

Pursuit - The Journal of Undergraduate Research at The University of Tennessee

Sinkholes are one of the major causes of damage to roads, buildings, and other infrastructure throughout the US. Sinkholes near or on roads are especially costly and occasionally deadly. Knox County and much of East Tennessee are located within karst areas (comprised of porous and soluble limestone and dolomite), deeming it at risk for sinkholes. Currently, Knox County uses contour maps to manually identify sinkholes. Supported by a geographic information system (GIS), we developed a streamlined model to identify the locations and extents of potential sinkholes using 1.3-ft resolution LiDAR (Light Detection and Ranging) data and applied it to the …

Social Isolation Detection Checklist, Sheridan Centre For Elder Research

Social Isolation Detection Checklist

The Social Isolation Detection Checklist is a preliminary screening tool that can help you determine if an older adult might be at risk of social isolation. This tool can be completed one on one with an older adult. Alternatively, if you have been working with an older adult for an extended period of time and are familiar with their case history you can use your insider knowledge, intake records and case notes to complete this tool and determine risk. A list of recommendations (referrals) that correspond directly with the various categories in the Detection Tool is also included.

This resource …

Large Expert-Curated Database For Benchmarking Document Similarity Detection In Biomedical Literature Search, Peter Brown, Relish Consortium, Yaoqi Zhou

Faculty of Engineering and Information Sciences - Papers: Part B

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were …

A Numerical Approach To Design The Kretschmann Configuration Based Refractive Index Graphene-Mos2 Hybrid Layers With Tio2-Sio2 Nano For Formalin Detection, Md. Biplob Hossain, Tamanna Tasnim, Lway Abdulrazak, Md Masud Rana, Md Rabiul Islam

Faculty of Engineering and Information Sciences - Papers: Part B

In this paper, a Kretschmann configuration based surface plasmon resonance (SPR) sensor is numerically designed using graphene-MoS2 hybrid structure TiO2-SiO2 nano particles for formalin detection. In this design, the observations of SPR angle versus minimum reflectance and SPR frequency (FSPR) versus maximum transmittance (Tmax) are considered. The chitosan is used as probe legend to perform reaction with the formalin (40% formaldehyde) which acts as target legend. In this paper, both graphene and MoS2 are used as biomolecular acknowledgment element (BAE) and TiO2 as well as SiO2 bilayers is used to improve the sensitivity of the sensor. The numerical results show …

Internal Gravity Wave Detection During The 21 August 2017 Total Solar Eclipse, Michael J.W. Stewart

Theses and Dissertations

Total solar eclipses supply both visual captivation and a controlled meteorological experiment through a sudden decrease in solar radiation. However, along with commonly expected changes in weather conditions, prior research suggests an adjustment of atmospheric dynamics caused by both a decrease in local incident solar radiation and the Moon’s sweeping shadow across the Earth at supersonic speed. The result is the potential production of internal gravity waves, which transfer both energy and momentum vertically to and from the upper levels of the atmosphere. A series of radiosondes were launched before, during, and after the 21 August 2017 eclipse in Batesburg, …

Spatial-Temporal Visible Contrast Energy Predictions Of Detection Thresholds, Albert Ahumada, Andrew B. Watson, Jihyun Yeonan-Kim

MODVIS Workshop

The Barten (1994) spatial-temporal model was used to predict the Gabor stimulus contrast energy thresholds reported by Carney et al. (2013). The RMS error of fit was 1.6 dB, corrected for the number of parameters (6) estimated. The model has two lowpass spatial-temporal channels, combined by inhibition as in our spatial models (Watson & Ahumada, 2005; Ahumada & Watson, 2013). Computation of models predictions were greatly simplified by the spatial-temporal separability of the stimuli and the simplifications that result from using Gaussian filters in the spatial domain. The best fitting spatial filter frequency cutoffs are 11.4 and 0.88 cpd. The …

Effects Of Weather On Detection Of Landmines By Giant African Pouched Rats, Ian Mclean, Rebecca Sargisson

The Journal of Conventional Weapons Destruction

Although APOPO has trained mine detection rats for many years, no published data exist on how weather parameters relate to detection accuracy. Using data taken during routine training, we show that there was little relationship between the detection success of rats and rainfall but find that rates decreased, on average, with increasing temperatures and increased with higher humidities. Individual rats vary in terms of sensitivity to temperature in that

Integrated Condition Monitoring And Prognosis Method For Incipient Defect Detection And Remaining Life Prediction Of Low Speed Slew Bearings, Wahyu Caesarendra, Tegoeh Tjahjowidodo, Buyung Kosasih, Anh Kiet Tieu

Faculty of Engineering and Information Sciences - Papers: Part B

This paper presents an application of multivariate state estimation technique (MSET), sequential probability ratio test (SPRT) and kernel regression for low speed slew bearing condition monitoring and prognosis. The method is applied in two steps. Step (1) is the detection of the incipient slew bearing defect. In this step, combined MSET and SPRT is used with circular-domain kurtosis, time-domain kurtosis, wavelet decomposition (WD) kurtosis, empirical mode decomposition (EMD) kurtosis and the largest Lyapunov exponent (LLE) feature. Step (2) is the prediction of the selected features' trends and the estimation of the remaining useful life (RUL) of the slew bearing. In …

Gvm Based Intuitive Simulation Web Application For Collision Detection, Binbin Yong, Jun Shen, Zebang Shen, Huaming Chen, Xin Wang, Qingguo Zhou

Faculty of Engineering and Information Sciences - Papers: Part B

Computer simulation, which has been proved to be an effective approach to problem solving, is nowadays widely used in modern science. However, it requires a lot of computing resources, which are difficult for general users to acquire. In this paper, we design a Web based system to implement on-line simulation system for ordinary users. As a useful example, the simulation of one type of collision detection model is presented in this paper. Moreover, the software application of simulation is offered as a service on Web. Meanwhile, the incorporation of general vector machine (GVM, a type of neural network) to intelligently …

Parallel Gpu-Based Collision Detection Of Irregular Vessel Wall For Massive Particles, Binbin Yong, Jun Shen, Hongyu Sun, Huaming Chen, Qingguo Zhou

Faculty of Engineering and Information Sciences - Papers: Part A

In this paper, we present a novel GPU-based limit space decomposition collision detection algorithm (LSDCD) for performing collision detection between a massive number of particles and irregular objects, which is used in the design of the ADS (Accelerator Driven Sub-Critical) system. Test results indicate that, the collisions between ten million particles and the vessel can be detected on a general personal computer in only 0.5 second per frame. With this algorithm, the collision detection of maximum sixty million particles are calculated in 3.488030 seconds. Experiment results show that our algorithm is promising for fast collision detection.

Gpu Based Simulations Of Collision Detection Of Irregular Vessel Walls, Binbin Yong, Jun Shen, Hongyu Sun, Zijian Xu, Jingfeng Liu, Qingguo Zhou

Faculty of Engineering and Information Sciences - Papers: Part B

No abstract provided.

Latent Semantic Indexing In The Discovery Of Cyber-Bullying In Online Text, Jacob L. Bigelow

Computer Science Summer Fellows

The rise in the use of social media and particularly the rise of adolescent use has led to a new means of bullying. Cyber-bullying has proven consequential to youth internet users causing a need for a response. In order to effectively stop this problem we need a verified method of detecting cyber-bullying in online text; we aim to find that method. For this project we look at thirteen thousand labeled posts from Formspring and create a bank of words used in the posts. First the posts are cleaned up by taking out punctuation, normalizing emoticons, and removing high and low …

Detection Of Cyberbullying In Sms Messaging, Bryan W. Bradley

Computer Science Summer Fellows

Cyberbullying is a type of bullying that uses technology such as cell phones to harass or malign another person. To detect acts of cyberbullying, we are developing an algorithm that will detect cyberbullying in SMS (text) messages. Over 80,000 text messages have been collected by software installed on cell phones carried by participants in our study. This paper describes the development of the algorithm to detect cyberbullying messages, using the cell phone data collected previously. The algorithm works by first separating the messages into conversations in an automated way. The algorithm then analyzes the conversations and scores the severity and …

Planogram Compliance Checking Based On Detection Of Recurring Patterns, Song Liu, Wanqing Li, Stephen J. Davis, Christian H. Ritz, Hongda Tian

Faculty of Engineering and Information Sciences - Papers: Part A

In this article, the authors propose a novel method for automatic planogram compliance checking in retail chains that doesn't require product template images for training. Product layout is extracted from an input image by means of unsupervised recurring pattern detection and matched via graph matching, with the expected product layout specified by a planogram to measure the level of compliance. A divide-and-conquer strategy is employed to improve the speed. Specifically, the input image is divided into several regions based on the planogram. Recurring patterns are detected in each region, respectively, and then merged together to estimate the product layout.