Computer Engineering Commons^™

Memory Foreshadow: Memory Forensics Of Hardware Cryptocurrency Wallets – A Tool And Visualization Framework, Tyler Thomas, Mathew Piscitelli, Ilya Shavrov, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

We present Memory FORESHADOW: Memory FOREnSics of HArDware cryptOcurrency Wallets. To the best of our knowledge, this is the primary account of cryptocurrency hardware wallet client memory forensics. Our exploratory analysis revealed forensically relevant data in memory including transaction history, extended public keys, passphrases, and unique device identifiers. Data extracted with FORESHADOW can be used to associate a hardware wallet with a computer and allow an observer to deanonymize all past and future transactions due to hierarchical deterministic wallet address derivation. Additionally, our novel visualization framework enabled us to measure both the persistence and integrity of artifacts produced by the …

Exploring The Learning Efficacy Of Digital Forensics Concepts And Bagging & Tagging Of Digital Devices In Immersive Virtual Reality, Courtney Hassenfeldt, Jillian Jacques, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

This work presents the first account of evaluating learning inside a VR experience created to teach Digital Forensics (DF) concepts, and a hands-on laboratory exercise in Bagging & Tagging a crime scene with digital devices. First, we designed and developed an immersive VR experience which included a lecture and a lab. Next, we tested it with (n = 57) participants in a controlled experiment where they were randomly assigned to a VR group or a physical group. Both groups were subjected to the same lecture and lab, but one was in VR and the other was in the real world. …

Forecasting Vegetation Health In The Mena Region By Predicting Vegetation Indicators With Machine Learning Models, Sachi Perera, Wenzhao Li, Erik Linstead, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Machine learning (ML) techniques can be applied to predict and monitor drought conditions due to climate change. Predicting future vegetation health indicators (such as EVI, NDVI, and LAI) is one approach to forecast drought events for hotspots (e.g. Middle East and North Africa (MENA) regions). Recently, ML models were implemented to predict EVI values using parameters such as land types, time series, historical vegetation indices, land surface temperature, soil moisture, evapotranspiration etc. In this work, we collected the MODIS atmospherically corrected surface spectral reflectance imagery with multiple vegetation related indices for modeling and evaluation of drought conditions in the MENA …

Fixing Social Media: Toward A Democratic Digital Commons, Michael Kwet

Markets, Globalization & Development Review

In the past few years, big Social Media networks like Facebook, Twitter, and YouTube have received intense scrutiny from the intellectual classes. This article critiques the dominant strain of criticism, the neo-Brandeisian School of antitrust, for its narrow focus on “regulated competition” as an appropriate means to “fix social media”. This essay calls for a socialist alternative: a democratic social media commons based on free and open source technology, decentralization, and democratic socialist legal solutions. It reviews how existing solutions like the Fediverse and LibreSocial work, and how they may provide answers for a better way forward.

The Role Of Network Components In Improving The Reliability And Survivability Of Mobile Communication Networks, Dilmurod Davronbekov, Utkir Karimovich Matyokubov

Acta of Turin Polytechnic University in Tashkent

This article compares the different architectures of mobile communication networks (MCN) and examines the survivability of the network. Typical survival strategies for improving MCN survivability, failure mitigation strategies for network elements, wireless network survival rates, failure scenarios at MCN levels, and survival indicators are presented. The importance of fiber-optic communication in the construction of communication lines between MCN components has been studied. The issue of designing MCNs in a cost-effective and highly viable way is considered, and the necessary expressions of the design process are given.

A Comparative Study For Methodologies And Algorithms Used In Colon Cancer Diagnoses And Detection, Mona Mohamed Nasr, Laila Mohamed Abdelhamid, Naglaa Shehata

Future Computing and Informatics Journal

Colon cancer is also referred to as colorectal cancer; it is a kind of cancer that starts with colon damage to the large intestine in the last section of the digestive tract. Elderly people typically suffer from colon cancer, but this may occur at any age. It normally starts as a little, noncancerous (benign) mass of cells named polyps that structure within the colon. After a period of time these polyps can turn into advanced malignant tumors that attack the human body and some of these polyps can become colon cancers. So far, no concrete causes have been identified and …

Machine Learning Techniques For Credit Card Fraud Detection, Hossam Eldin Mohammed Abd El-Hamid Ahmed Abdou, Wael Khalifa, Mohamed Ismail Roushdy, Abdel-Badeeh M. Salem

Future Computing and Informatics Journal

The term “fraud”, it always concerned about credit card fraud in our minds. And after the significant increase in the transactions of credit card, the fraud of credit card increased extremely in last years. So the fraud detection should include surveillance of the spending attitude for the person/customer to the determination, avoidance, and detection of unwanted behavior. Because the credit card is the most payment predominant way for the online and regular purchasing, the credit card fraud raises highly. The Fraud detection is not only concerned with capturing of the fraudulent practices, but also, discover it as fast as they …

Proposed Framework For Smart Healthcare Services, Dalia K. A. A. Rizk, Hoda Hosny Prof. Dr., El-Sayed M. El-Horbaty Prof. Dr., Abdel-Badeeh M. Salem Prof. Dr.

Future Computing and Informatics Journal

Smart healthcare is of great interest to researchers and governments due to the increasing development of new smart cities. However, there is no current standard practice to format the cloud computing infrastructure and to assist the healthcare system architect in designing a comprehensive solution for the basic services that are required by the healthcare users while taking into consideration a balanced approach towards their specific functional and non-functional needs such as openness, scalability, concurrency, interoperability and security factors. The integration of smart healthcare services with cloud computing needs a concrete framework. The main objective of this paper is to analyze …

Intelligent Technique For Automating The Conversion Between Major And Minor Melodies, Nermin N. J. Siphocly, El-Sayed M. El-Horbaty, Abd El-Badea Mohamed Salem Prof

Future Computing and Informatics Journal

Nowadays, computers are extremely beneficial to music composers. Computer music generation tools are developed for aiding composers in producing satisfying musical pieces. The automation of music composition tasks is a challenging research point, specially to the field of Artificial Intelligence. Converting melodies that are played on a major scale to minor (or vice versa) is interesting to both composers and music listeners. Newly converted melodies of famous songs, either from major to minor or the opposite, are becoming blockbusters on the social media. In this paper we propose an intelligent method for automating the conversion between major and minor melodies …

Ontological Engineering For Source Code Generation, Anas Hamid Aloklah, Walaa Gad, Mostafa Mohamed Aref Prof, Abd El-Badea Mohamed Salem Prof

Future Computing and Informatics Journal

Source Code Generation (SCG) is the sub-domain of the Automatic Programming (AP) that helps programmers to program using high-level abstraction. Recently, many researchers investigated many techniques to access SCG. The problem is to use the appropriate technique to generate the source code due to its purposes and the inputs. This paper introduces a review and an analysis related SCG techniques. Moreover, comparisons are presented for: techniques mapping, Natural Language Processing (NLP), knowledge base, ontology, Specification Configuration Template (SCT) model and deep learning

Detecting Symptoms Of Chronic Obstructive Pulmonary Disease And Congestive Heart Failure Via Cough And Wheezing Sounds Using Smart-Phones And Machine Learning, Anthony Windmon

USF Tampa Graduate Theses and Dissertations

Chronic Obstructive Pulmonary Disease (COPD) and Congestive Heart Failure (CHF) are progressive disorders, and major health concerns among today’s aging population. COPD causes a large mucus buildup in the lungs, leading to chronic cough and difficulty to breathe. CHF causes fluid buildup in the lower lungs due to the failing heart, causing cough and difficulty to breath. People who are clinically diagnosed with COPD or CHF are expected to regularly monitor their symptoms and follow complex medical recommendations in an effort to prevent exacerbation. In this dissertation, we elaborate upon three different machine learning based techniques that we developed for …

Chess As A Testing Grounds For The Oracle Approach To Ai Safety, James D. Miller, Roman Yampolskiy, Olle Häggström, Stuart Armstrong

Faculty and Staff Scholarship

To reduce the danger of powerful super-intelligent AIs, we might make the first such AIs oracles that can only send and receive messages. This paper proposes a possibly practical means of using machine learning to create two classes of narrow AI oracles that would provide chess advice: those aligned with the player's interest, and those that want the player to lose and give deceptively bad advice. The player would be uncertain which type of oracle it was interacting with. As the oracles would be vastly more intelligent than the player in the domain of chess, experience with these oracles might …

3d-Printed Leg Design And Modification For Improved Support On A Quadruped Robot, Jasmin S. Collins

Maseeh Summer Undergraduate Research Experience

The Agile and Adaptive Robotics Lab aims to uncover the biological and physiological complexities in animal agility and adaptive control, which can be replicated through robotics and provide further applications in biology and medicine. One project within the lab focuses on understanding structure, actuation, and control through the modeling of a canine quadruped robot.

The AARL has developed a full-body quadruped robot with artificial muscles that control limb movement and a body that is built from 3D-printed parts. This specific project involved modification of these existing parts to (a) minimize deflections in the front legs, causing unwanted lateral and abduction/adduction …

Autonomous Pev Charging Scheduling Using Dyna-Q Reinforcement Learning, Fan Wang, Jie Gao, Mushu Li, Lian Zhao

Electrical and Computer Engineering Faculty Research and Publications

This paper proposes a demand response method to reduce the long-term charging cost of single plug-in electric vehicles (PEV) while overcoming obstacles such as the stochastic nature of the user's driving behaviour, traffic condition, energy usage, and energy price. The problem is formulated as a Markov Decision Process (MDP) with an unknown transition probability matrix and solved using deep reinforcement learning (RL) techniques. The proposed method does not require any initial data on the PEV driver's behaviour and shows improvement on learning speed when compared to a pure model-free reinforcement learning method. A combination of model-based and model-free learning methods …

The Expansion From System Simulation To Domain Simulation, Xiaogang Qiu, Yazhou Chen, Zhang Peng

Journal of System Simulation

Abstract: With the generalization of simulation application and complex system simulation becoming the focus, domain simulation is becoming more and more important. In 1995 United States Department of Defense (DoD) presented the master plan of modeling and simulation, which gives birth to the basic idea of domain simulation. The advances in information technology such as network technology and cloud computing help domain simulation to access to use. Taking the change of simulation research object as the basis, the development of simulation research from the aspects of model researches, simulation tools and simulation applications are summarized. The goal of domain simulation …

Review On Agv Scheduling Optimization, Jianlin Fu, Hengzhi Zhang, Zhang Jian, Liangkui Jiang

Journal of System Simulation

Abstract: AGV scheduling plays an important role in improving the efficiency and reducing manufacturing cost, but it is also a very complex combinatorial optimization procedure. AGV scheduling optimization is divided into three types, AGV static scheduling, AGV dynamic scheduling and AGV simultaneous scheduling with other resources scheduling. Various methods are summarized and listed, including traditional analysis method, modeling and simulation method, intelligent optimization algorithm and hybrid optimization method, and the advantages and disadvantages of each method are also analyzed. The deficiencies of AGV scheduling research are pointed out and the research directions for future are presented.

Research On Recursive Variable Sampling Period Scheduling Algorithm Based On Two-Parameter Priority, Weiguo Shi, Xu Chao, Wang Xun, Xiangtai Wang

Journal of System Simulation

Abstract: A recursive variable sampling periodic dynamic scheduling algorithm based on two-parameter priority is proposed for the resource-constrained network control system. The network demand degree and network urgency double parameter of the control loop are calculated, and the two-parameter weight is established by the two-square root mapping function which is created by the absolute value of the control loop error to realize the scheduling of the sensor priority. The comprehensive analysis of the control loop performance recursively adjusts the sampling period of each control loop, and completes the scheduling adjustment under the premise of ensuring the stability of the …

Finite Element Method Evaluation On Chest Blunt Injury By Rubber Projectile, Wang Song, Renjun Zhan, Xiongyi Duan

Journal of System Simulation

Abstract: In order to reveal the non-lethal injury mechanism of rubber projectile and improve its safety service level, the 18.4 mm rubber projectile finite element model and the improved chest blunt injury assessment model are constructed and verified. The virtual impact test experiments under different loads are carried out, and the stress-time response and deformation-time response data are obtained. The results show that the time to reach the peak stress (less than 0.2 ms) is much shorter than the time to reach the maximum deformation variable (4~5 ms), which means the damage is not caused by the impact itself …

Simulation Analysis On Penetration To Aircraft Carrier Of Image Homing Rocket, Shidong Fang, Chen Dong, Quanli Ning, Zhang Jie, Li Yong

Journal of System Simulation

Abstract: The effect of image homing rocket projectile penetrating aircraft carrier is the important basis for its operation. According to the characteristics of projectile and aircraft carrier, the geometric equivalent model and simulation model are established, and the penetration process is simulated by LS-DYNA. Simulation results are verified by the failure form and penetration limit velocity, and show the correctness of the model. Using the established models, the penetration processes are simulated under the different conditions. The overall force on the projectile is analyzed according to the extreme acceleration value of projectile. Based on the analysis of some collected key …

Operation Loss Reduction Control For Large-Scale Wind Farm Based On Hybrid Modeling Simulation, Yunqi Xiao, Wang Yi

Journal of System Simulation

Abstract: Due to the large number of transformers and collection lines in large-scale wind farms, the losses of collecting system is serious in actual operation. A reactive power/voltage control strategy is proposed, which takes wind turbines as the distributed reactive power sources to optimize the power flow in wind farm and reduce the overall losses of collector system. To improve the efficiency of wind farm modeling and multi-scene loss reduction simulation, a hybrid modeling and simulation scheme based on combining object model configuration and control algorithm programming is proposed. The wind farm model consists of module configuration, and can be …