Engineering Commons^™

Paddle Mixer-Extrusion Reactor For Torrefaction And Pyrolysis, Stas Zinchik

Dissertations, Master's Theses and Master's Reports

This work is focused on the fundamental understanding and the development of paddle mixer reactors (or modified screw augers). This work will contribute to the effort of the thermal conversion of biomass and wastes. We developed and studied two paddle systems (i) 25-mm lab-scale (up to 1 kg/hr) and (ii) 101-mm pilot-scale (up to 100 kg/hr). Thermal behavior of the two systems was studied and it was estimated that the lab-scale system has a high heating rate of up to 530 °C/s. Residence times were thoroughly measured and were determined as a function of rotation frequency and volume fraction. We …

Technology For Integrated Groyne-Vetiver Erosion Reduction (Tiger): Case Study In A West African River, Chase M. West

Dissertations, Master's Theses and Master's Reports

River erosion is a problem all over the world. The effects of river erosion are especially hard for farmers in developing countries, where the river is an important part of their farming practices and daily lives. A case study was done in the small village of Fode Binea in Senegal, West Africa to reduce this stream erosion. A new hybrid approach, Technology for Integrated Groyne-Vetiver Erosion Reduction (TIGER) method, was developed. The method includes combining groynes at the toe of the riverbank to reduce toe erosion in the channel and planting a buffer strip with vetiver grass to reduce erosion …

Mse Annual Report 2019, Department Of Materials Science And Engineering, Michigan Technological University

Department of Materials Science and Engineering Annual Reports

Table of Contents

• Faculty and Staff News
• Faculty Research
• Student News
• Alumni News
• By the Numbers
• K-12 Outreach

A Survey Of State-Of-The-Art Gan-Based Approaches To Image Synthesis, Shahram Latifi, Shirin Nasr Esfahani

Electrical & Computer Engineering Faculty Research

In the past few years, Generative Adversarial Networks (GANs) have received immense attention by researchers in a variety of application domains. This new field of deep learning has been growing rapidly and has provided a way to learn deep representations without extensive use of annotated training data. Their achievements may be used in a variety of applications, including speech synthesis, image and video generation, semantic image editing, and style transfer. Image synthesis is an important component of expert systems and it attracted much attention since the introduction of GANs. However, GANs are known to be difficult to train especially when …

Biom 4110/6110: The Science Of Medicine (Syllabus), Bradford D. Pendley

Biomedical Engineering Syllabi Archive

Course Description: Integration of fundamental principles from physics, chemistry, biology and mathematics, and applications of these principles to solve problems in medicine.

End-To-End Learning Via A Convolutional Neural Network For Cancer Cell Line Classification, Darlington A. Akogo, Xavier-Lewis Palmer

Electrical & Computer Engineering Faculty Publications

Purpose: Computer vision for automated analysis of cells and tissues usually include extracting features from images before analyzing such features via various machine learning and machine vision algorithms. The purpose of this work is to explore and demonstrate the ability of a Convolutional Neural Network (CNN) to classify cells pictured via brightfield microscopy without the need of any feature extraction, using a minimum of images, improving work-flows that involve cancer cell identification.

Design/methodology/approach: The methodology involved a quantitative measure of the performance of a Convolutional Neural Network in distinguishing between two cancer lines. In their approach, they trained, validated and …

Sustainability In Higher Education: Perceptions Of Social Responsibility Among University Students, Younghan Jung, Kayoung Park, Junyong Ahn

Engineering Technology Faculty Publications

Many construction-related training and education programs in the United States have now embraced the concept of sustainability, offering sustainable construction courses that highlight sustainable design and construction practices. These courses have mainly focused on green building strategies for the design and construction of built environments and indoor environmental quality necessary for students’ knowledge enhancement and career development. This study examined the effect of sustainability course on students’ knowledge as well as their perceptions of social responsibility and sustainable behaviors. Data were collected by conducting a survey from construction related programs in U.S. universities. Students were categorized based on their experience …

The Global Disinformation Order: 2019 Global Inventory Of Organised Social Media Manipulation, Samantha Bradshaw, Philip N. Howard

Copyright, Fair Use, Scholarly Communication, etc.

Executive Summary

Over the past three years, we have monitored the global organization of social media manipulation by governments and political parties. Our 2019 report analyses the trends of computational propaganda and the evolving tools, capacities, strategies, and resources.

1. Evidence of organized social media manipulation campaigns which have taken place in 70 countries, up from 48 countries in 2018 and 28 countries in 2017. In each country, there is at least one political party or government agency using social media to shape public attitudes domestically.

2.Social media has become co-opted by many authoritarian regimes. In 26 countries, computational propaganda …

Fatigue Identification And Management In Flight Training: An Investigation Of Collegiate Aviation Pilots, Flavio A. C. Mendonca Ph.D.

Publications

Pilot fatigue is a significant hazard affecting flight operations;

• Generally the product of one or more factors: Disrupted or lack of sleep;
• Inadequate food and or fluid intake;
• Mental;
• and Physical fatigue.

Previous studies have focused on military and commercial flight operations;

• Little to nothing has been done to investigate fatigue identification & management by general aviation pilots!

Optically Transparent Antennas And Filters For Smart City Communication, Ryan B. Green

Theses and Dissertations

Incremental usage of mobile devices demand a new generation of wireless networks (5G) to provide faster data rates, more reliable coverage, monitor city infrastructure usage, and increase network capacity. The frequencies proposed for the upcoming 5G network would result in shorter broadcast distances and network dead zones, countered by incorporating transparent antennas into glass high rises. Transparent antennas possess, however a major challenge: low gain. This lower gain can be countered by means of employing antennas in an antenna array, boosting the gain and even giving the array the ability to beam form for the upcoming 5G network. The 5G …

Let’S Face It: The Effect Of Orthognathic Surgery On Facial Recognition Algorithm Analysis, Carolyn Bradford Dragon

Theses and Dissertations

Aim: To evaluate the ability of a publicly available facial recognition application program interface (API) to calculate similarity scores for pre- and post-surgical photographs of patients undergoing orthognathic surgeries. Our primary objective was to identify which surgical procedure(s) had the greatest effect(s) on similarity score.

Methods: Standard treatment progress photographs for 25 retrospectively identified, orthodontic-orthognathic patients were analyzed using the API to calculate similarity scores between the pre- and post-surgical photographs. Photographs from two pre-surgical timepoints were compared as controls. Both relaxed and smiling photographs were included in the study to assess for the added impact of facial pose on …

Exploring And Expanding The One-Pixel Attack, Umairullah Khan, Walt Woods

Maseeh Summer Undergraduate Research Experience

In machine learning research, adversarial examples are normal inputs to a classifier that have been specifically perturbed to cause the model to misclassify the input. These perturbations rarely affect the human readability of an input, even though the model’s output is drastically different. Recent work has demonstrated that image-classifying deep neural networks (DNNs) can be reliably fooled with the modification of a single pixel in the input image, without knowledge of a DNN’s internal parameters. This “one-pixel attack” utilizes an iterative evolutionary optimizer known as differential evolution (DE) to find the most effective pixel to perturb, via the evaluation of …

Antenna Selection And Transmission Power For Energy Efficiency In Downlink Massive Mimo Systems, Adeeb Salh, Lukman Audah, Nor Shahida Mohd Shah, Shipun Anuar Hamzah, Hasan Saeed Mir

Turkish Journal of Electrical Engineering and Computer Sciences

Massive multiinput-multioutput (M-MIMO) systems are crucial for maximizing energy efficiency (EE) in fifth-generation (5G) wireless networks. A M-MIMO system's achievable high data rate is highly related to the number of antennas, but increasing the number of antennas the system raises energy consumption. In this paper, we derive ergodic EE based on the optimal transmit power and joint optimization antenna selection (AS) with impact pilot reuse sequences (PRSs). We apply Newton's method and the Lagrange multiplier to derive jointly optimized AS and optimal transmission power under the effect of PRSs. The proposed algorithm prevents repeated searching for joint optimal AS and …

On Spectral Analysis Of The Internet Delay Space And Detecting Anomalous Routing Paths, Gonca Gürsun

Turkish Journal of Electrical Engineering and Computer Sciences

Latency is one of the most critical performance metrics for a wide range of applications. Therefore, it is important to understand the underlying mechanisms that give rise to the observed latency values and diagnose the ones that are unexpectedly high. In this paper, we study the Internet delay space via robust principal component analysis (RPCA). Using RPCA, we show that the delay space, i.e. the matrix of measured round trip times between end hosts, can be decomposed into two components: the estimated latency between end hosts with respect to the current state of the Internet and the inflation on the …

Measurement Of Network-Based And Random Meetings In Social Networks, Pranav Nerurkar, Madhav Chandane, Sunil Bhirud

Turkish Journal of Electrical Engineering and Computer Sciences

Social networks are created by the underlying behavior of the actors involved in them. Each actor has interactions with other actors in the network and these interactions decide whether a social relationship should develop between them. Such interactions may occur due to meeting processes such as chance-based meetings or network-based (choice) meetings. Depending upon which of these two types of interactions plays a greater role in creation of links, a social network shall evolve accordingly. This evolution shall result in the social network obtaining a suitable structure and certain unique features. The aim of this work is to determine the …

Refugees' Social Media Activities In Turkey: A Computational Analysis And Demonstration Method, Muhammed Abdullah Bülbül, Salah Haj Ismail

Turkish Journal of Electrical Engineering and Computer Sciences

This study performs a data analysis on refugees in Turkey based on their social media activities. In order to achieve this, we first propose a method to find their relevant public accounts and collect their activities generating a dataset. Then, we perform spatial and temporal analysis over this dataset to shed light on the most important topics and events discussed in social networks. We present the results graphically for ease of understanding and comparison. Our results indicate that we can reveal the most shared topics over a specific time and place as well as the change of pattern in refugees' …

Classification Of Generic System Dynamics Model Outputs Via Supervised Time Series Pattern Discovery, Mert Edali, Mustafa Gökçe Baydoğan, Gönenç Yücel

Turkish Journal of Electrical Engineering and Computer Sciences

System dynamics (SD) is a simulation-based approach for analyzing feedback-rich systems. An ideal SD modeling cycle requires evaluating the qualitative pattern characteristics of a large set of time series model output for testing, validation, scenario analysis, and policy analysis purposes. This traditionally requires expert judgement, which limits the extent of experimentation due to time constraints. Although time series recognition approaches can help to automate such an evaluation, utilization of them has been limited to a hidden Markov model classifier, namely the Indirect Structure Testing Software (ISTS) algorithm. Despite being used within several automated model-analysis tools, ISTS has several shortcomings. In …

Graph Analysis Of Network Flow Connectivity Behaviors, Hangyu Hu, Xuemeng Zhai, Mingda Wang, Guangmin Hu

Turkish Journal of Electrical Engineering and Computer Sciences

Graph-based approaches have been widely employed to facilitate in analyzing network flow connectivity behaviors, which aim to understand the impacts and patterns of network events. However, existing approaches suffer from lack of connectivity-behavior information and loss of network event identification. In this paper, we propose network flow connectivity graphs (NFCGs) to capture network flow behavior for modeling social behaviors from network entities. Given a set of flows, edges of a NFCG are generated by connecting pairwise hosts who communicate with each other. To preserve more information about network flows, we also embed node-ranking values and edge-weight vectors into the original …

Design And Development Of A Stewart Platform Assisted And Navigated Transsphenoidal Surgery, Selçuk Ki̇zi̇r, Zafer Bi̇ngül

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, technical details of a Stewart platform (SP) based robotic system as an endoscope positioner and holder for endoscopic transsphenoidal surgery are presented. Inverse and forward kinematics, full dynamics, and the Jacobian matrix of the robotic system are derived and simulated in MATLAB/Simulink. The required control structure for the trajectory and position control of the SP is developed and verified by several experiments. The robotic system can be navigated using a six degrees of freedom (DOF) joystick and a haptic device with force feedback. Position and trajectory control of the SP in the joint space is achieved using …

A Comparative Study Of Author Gender Identification, Tuğba Yildiz

Turkish Journal of Electrical Engineering and Computer Sciences

In recent years, author gender identification has gained considerable attention in the fields of information retrieval and computational linguistics. In this paper, we employ and evaluate different learning approaches based on machine learning (ML) and neural network language models to address the problem of author gender identification. First, several ML classifiers are applied to the features obtained by bag-of-words. Secondly, datasets are represented by a low-dimensional real-valued vector using Word2vec, GloVe, and Doc2vec, which are on par with ML classifiers in terms of accuracy. Lastly, neural networks architectures, the convolution neural network and recurrent neural network, are trained and their …

Prediction Of Preference And Effect Of Music On Preference: A Preliminary Study On Electroencephalography From Young Women, Bülent Yilmaz, Cengi̇z Gazeloğlu, Fati̇h Altindi̇ş

Turkish Journal of Electrical Engineering and Computer Sciences

Neuromarketing is the application of the neuroscientific approaches to analyze and understand economically relevant behavior. In this study, the effect of loud and rhythmic music in a sample neuromarketing setup is investigated. The second aim was to develop an approach in the prediction of preference using only brain signals. In this work, 19-channel EEG signals were recorded and two experimental paradigms were implemented: no music/silence and rhythmic, loud music using a headphone, while viewing women shoes. For each 10-sec epoch, normalized power spectral density (PSD) of EEG data for six frequency bands was estimated using the Burg method. The effect …

Multiscanning Mode Laser Scanning Confocal Microscopy System, Mert Aktürk, Gökhan Gümüş, Baykal Sarioğlu, Yi̇ği̇t Dağhan Gökdel

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a table-top, reflective mode, laser scanning confocal microscopy system that is capable of scanning the target specimen alternately through various scanning devices and methods is proposed. We have developed a laser scanning confocal microscopy system to utilize combinations of various scanning devices and methods and to be able to characterize the optical performance of different scanners and micromirrors that are frequently used in scanning microscopy systems such as multiphoton microscopy, optical coherence tomography, or confocal microscopy. By integrating the scanner to be characterized on the same optical path with a galvanometric scan mirror, which is the conventional …

Hybrid Self-Controlled Precharge-Free Cam Design For Low Power And High Performance, V V Satyanarayana Satti, Sridevi Sriadibhatla

Turkish Journal of Electrical Engineering and Computer Sciences

Content-addressable memory (CAM) is a prominent hardware for high-speed lookup search, but consumes larger power. Traditional NOR and NAND match-line (ML) architectures suffer from a short circuit current path sharing and charge sharing respectively during precharge. The recently proposed precharge-free CAM suffers from high search delay and the subsequently proposed self-controlled precharge-free CAM suffers from high power consumption. This paper presents a hybrid self-controlled precharge-free (HSCPF) CAM architecture, which uses a novel charge control circuitry to reduce search delay as well as power consumption. The proposed and existing CAM ML architectures were developed using CMOS 45nm technology node with a …

Structure Tensor Adaptive Total Variation For Image Restoration, Surya Prasath, Dang Nh Thanh

Turkish Journal of Electrical Engineering and Computer Sciences

Image denoising and restoration is one of the basic requirements in many digital image processing systems. Variational regularization methods are widely used for removing noise without destroying edges that are important visual cues. This paper provides an adaptive version of the total variation regularization model that incorporates structure tensor eigenvalues for better edge preservation without creating blocky artifacts associated with gradient-based approaches. Experimental results on a variety of noisy images indicate that the proposed structure tensor adaptive total variation obtains promising results and compared with other methods, gets better structure preservation and robust noise removal.

A Kalman Filter Application For Rainfall Estimation Using Radar Reflectivity Measurements, Engi̇n Maşazade, Ali̇ Kemal Bakir, Pinar Kirci

Turkish Journal of Electrical Engineering and Computer Sciences

The rainfall amount observed at a given location mostly depend on the cloud density, which can be quantified with the reflectivity values observed by meteorology weather radars. In this study, we aim to estimate the rainfall amount using a Kalman filter with radar reflectivity measurements. We first assume that the amount of rainfall observed at automatic weather observation stations (AWOSs) are elements of an unknown state vector and consider the Kalman filter process model as the true rainfall amounts observed at these AWOSs over time. For the measurement model of the Kalman filter, we use the radar reflectivity values observed …

Probabilistic Small-Signal Stability Analysis Of Power System With Solar Farm Integration, Samundra Gurung, Sumate Naetiladdanon, Anawach Sangswang

Turkish Journal of Electrical Engineering and Computer Sciences

Currently, large-scale solar farms are being rapidly integrated in electrical grids all over the world. However, the photovoltaic (PV) output power is highly intermittent in nature and can also be correlated with other solar farms located at different places. Moreover, the increasing PV penetration also results in large solar forecast error and its impact on power system stability should be estimated. The effects of these quantities on small-signal stability are difficult to quantify using deterministic techniques but can be conveniently estimated using probabilistic methods. For this purpose, the authors have developed a method of probabilistic analysis based on combined cumulant …

A Hybrid Model For The Prediction Of Aluminum Foil Output Thickness In Cold Rolling Process, Ali̇ Öztürk, Ri̇fat Şeherli̇

Turkish Journal of Electrical Engineering and Computer Sciences

This study proposes a hybrid model composed of multiple prediction algorithms and an autoregressive moving average (ARMA) module for the thickness prediction. In order to attain higher accuracy, the prediction algorithms were globally combined by simple voting to reduce the effect of the inductive bias imposed by each algorithm on the dataset. The global multiexpert combination (GMEC) system included the multilayer perceptron neural network (MLPNN), radial basis function network (RBFN), multiple linear regression (MLR), and support vector machines (SVM) algorithms. The proposed hybrid model extends the GMEC system by integrating an ARMA module for the output. On the test dataset, …

Optimal Training And Test Sets Design For Machine Learning, Burkay Genç, Hüseyi̇n Tunç

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we describe histogram matching, a metric for measuring the distance of two datasets with exactly the same features, and embed it into a mixed integer programming formulation to partition a dataset into fixed size training and test subsets. The partition is done such that the pairwise distances between the dataset and the subsets are minimized with respect to histogram matching. We then conduct a numerical study using a well-known machine learning dataset. We demonstrate that the training set constructed with our approach provides feature distributions almost the same as the whole dataset, whereas training sets constructed via …

Triangular Slotted Ground Plane: A Key To Realizing High-Gain, Cross-Polarization-Free Microstrip Antenna With Improved Bandwidth, Abhijyoti Ghosh, Banani Basu

Turkish Journal of Electrical Engineering and Computer Sciences

A simple rectangular microstrip antenna with triangular slotted ground plane has been studied both theoretically and experimentally to improve shortcomings like low gain (5 - 6 dBi), narrow bandwidth (3% - 4%), and poor copolarization (CP) to cross-polarization (XP) isolation, i.e. polarization purity (typically 10 - 12 dB), of conventional rectangular microstrip patch antennas. By placing two pairs of triangular shaped slots on the ground plane just below the nonradiating edges of the patch, high gain (around 9 dBi) and more than 22 dB polarization purity over a wide elevation angle has been achieved. The proposed antenna covers almost the …

Invisible Watermarking Framework That Authenticates And Prevents The Visualization Of Anaglyph Images For Copyright Protection, David-Octavio Muñoz-Ramirez, Volodymyr Ponomaryov, Rogelio Reyes-Reyes, Clara Cruz-Ramos, Beatriz-Paulina Garcia-Salgado

Turkish Journal of Electrical Engineering and Computer Sciences

In this work, a watermarking framework to authenticate and protect the copyright that prevents the visualization of nonauthorized anaglyph images is proposed. Designed scheme embeds a binary watermark and the Blue channel of the anaglyph image into the discrete cosine transform domain of the original image. The proposed method applies the quantization index modulation-dither modulation algorithm and a combination of Bose-Chaudhuri-Hocquenghem with repetition codes, which permit to increase the capability in recovering the watermark. Additionally, Hash algorithm is used to scramble the component where the watermark should be embedding, guaranteeing a higher security performance of the scheme. This new technique …