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Full-Text Articles in Engineering

Fair Treatment Dec 2020

Fair Treatment

In The Loop

Initiatives in DePaul's College of Computing and Digital Media are addressing racial inequity in health care. One initiative is looking at Black maternal health. Another is trying to build models and requirements of what should be automated to consider racial inequity first.


Conditional Generative Adversarial Network Demosaicing Strategy For Division Of Focal Plane Polarimeters, Garrett Sargent, Bradley M. Ratliff, Vijayan K. Asari Dec 2020

Conditional Generative Adversarial Network Demosaicing Strategy For Division Of Focal Plane Polarimeters, Garrett Sargent, Bradley M. Ratliff, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Division of focal plane (DoFP), or integrated microgrid polarimeters, typically consist of a 2 × 2 mosaic of linear polarization filters overlaid upon a focal plane array sensor and obtain temporally synchronized polarized intensity measurements across a scene, similar in concept to a Bayer color filter array camera. However, the resulting estimated polarimetric images suffer a loss in resolution and can be plagued by aliasing due to the spatially-modulated microgrid measurement strategy. Demosaicing strategies have been proposed that attempt to minimize these effects, but result in some level of residual artifacts. In this work we propose a conditional generative adversarial …


Fault Diagnosability Of Regular Graphs, Mei-Mei Gu, Rong-Xia Hao, Eddie Cheng Dec 2020

Fault Diagnosability Of Regular Graphs, Mei-Mei Gu, Rong-Xia Hao, Eddie Cheng

Theory & Applications of Graphs

An interconnection network's diagnosability is an important measure of its self-diagnostic capability. In 2012, Peng et al. proposed a measure for fault diagnosis of the network, namely, the h-good-neighbor conditional diagnosability, which requires that every fault-free node has at least h fault-free neighbors. There are two well-known diagnostic models, PMC model and MM* model. The h-good-neighbor diagnosability under the PMC (resp. MM*) model of a graph G, denoted by thPMC(G) (resp. thMM*(G)), is the maximum value of t such that G is h-good-neighbor t-diagnosable under the PMC (resp. MM*) …


Survey On Deep Neural Networks In Speech And Vision Systems, M. Alam, Manar D. Samad, Lasitha Vidyaratne, ‪Alexander Glandon, Khan M. Iftekharuddin Dec 2020

Survey On Deep Neural Networks In Speech And Vision Systems, M. Alam, Manar D. Samad, Lasitha Vidyaratne, ‪Alexander Glandon, Khan M. Iftekharuddin

Computer Science Faculty Research

This survey presents a review of state-of-the-art deep neural network architectures, algorithms, and systems in speech and vision applications. Recent advances in deep artificial neural network algorithms and architectures have spurred rapid innovation and development of intelligent speech and vision systems. With availability of vast amounts of sensor data and cloud computing for processing and training of deep neural networks, and with increased sophistication in mobile and embedded technology, the next-generation intelligent systems are poised to revolutionize personal and commercial computing. This survey begins by providing background and evolution of some of the most successful deep learning models for intelligent …


A Novel Spatiotemporal Prediction Method Of Cumulative Covid-19 Cases, Junzhe Cai Dec 2020

A Novel Spatiotemporal Prediction Method Of Cumulative Covid-19 Cases, Junzhe Cai

School of Computing: Dissertations, Theses, and Student Research

Prediction methods are important for many applications. In particular, an accurate prediction for the total number of cases for pandemics such as the Covid-19 pandemic could help medical preparedness by providing in time a sufficient supply of testing kits, hospital beds and medical personnel. This thesis experimentally compares the accuracy of ten prediction methods for the cumulative number of Covid-19 pandemic cases. These ten methods include two types of neural networks and extrapolation methods based on best fit linear, best fit quadratic, best fit cubic and Lagrange interpolation, as well as an extrapolation method from Revesz. We also consider the …


Suffix Tree, Minwise Hashing And Streaming Algorithms For Big Data Analysis In Bioinformatics, Sairam Behera Dec 2020

Suffix Tree, Minwise Hashing And Streaming Algorithms For Big Data Analysis In Bioinformatics, Sairam Behera

School of Computing: Dissertations, Theses, and Student Research

In this dissertation, we worked on several algorithmic problems in bioinformatics using mainly three approaches: (a) a streaming model, (b) sux-tree based indexing, and (c) minwise-hashing (minhash) and locality-sensitive hashing (LSH). The streaming models are useful for large data problems where a good approximation needs to be achieved with limited space usage. We developed an approximation algorithm (Kmer-Estimate) using the streaming approach to obtain a better estimation of the frequency of k-mer counts. A k-mer, a subsequence of length k, plays an important role in many bioinformatics analyses such as genome distance estimation. We also developed new methods that use …


Use Of Viscoplastic Damper For Improving The Resistance Of Steel Frames To Blast Loading, Gholamreza Abdollahzadeh, Hadi Faghihmaleki, Hamed Hamidi Jamnani, Atefeh Ebrahimi Bardar Dec 2020

Use Of Viscoplastic Damper For Improving The Resistance Of Steel Frames To Blast Loading, Gholamreza Abdollahzadeh, Hadi Faghihmaleki, Hamed Hamidi Jamnani, Atefeh Ebrahimi Bardar

Makara Journal of Technology

In this paper, we evaluated the effect of viscoplastic dampers on the response of steel frames under blast loading. We used SAP2000 software and link elements to investigate the responses of nine-story steel frames with and without dampers. The proposed viscoplastic damper is a new type of viscous damper. The application of this damper is based on the availability of its constituent materials. The damper acts as a viscoelastic damper at low levels of vibration, but it acts as a combination of viscoelastic operator and metal-yielding device at extreme levels of vibration. With respect to the height of the structure, …


Influence Of Lithium Bromide On Electrical Properties In Bio-Based Polymer Electrolytes, Ahmad Faizrin Fuzlin, Bouchta Sahraoui, Ahmad Salihin Samsudin Dec 2020

Influence Of Lithium Bromide On Electrical Properties In Bio-Based Polymer Electrolytes, Ahmad Faizrin Fuzlin, Bouchta Sahraoui, Ahmad Salihin Samsudin

Makara Journal of Technology

This research presents the influence of lithium bromide (LiBr) on the electrical properties of alginate in bio-based polymer electrolytes (BBPEs) system. Bio-based alginate was prepared using the solution casting technique with various LiBr compositions. The ionic conductivity and electrical properties of the prepared BBPEs samples were studied using electrical impedance spectroscopy over a frequency range of 50 Hz–1 MHz. A maximum ionic conductivity of 7.46 × 10−5 S cm-1 was obtained for a sample containing 15 wt. % lithium bromide-doped alginate BBPEs at ambient temperature (303 K). The electrical analysis revealed that the most conductive sample based on alginate-LiBr BBPEs …


Mechanical Alloying-Assisted Coating Of Fe–Al Powders On Steel Substrate, Alfian Noviyanto, Sri Harjanto, Wahyu Bambang Widayatno, Agus Sukarto Wismogroho, Muhamad Ikhlasul Amal, Nurul Taufiqu Rochman Dec 2020

Mechanical Alloying-Assisted Coating Of Fe–Al Powders On Steel Substrate, Alfian Noviyanto, Sri Harjanto, Wahyu Bambang Widayatno, Agus Sukarto Wismogroho, Muhamad Ikhlasul Amal, Nurul Taufiqu Rochman

Makara Journal of Technology

The coating layer of Fe–Al powders on the steel substrate was prepared by mechanical alloying at room temperature. Fe, Al, and the steel substrates were milled with high-energy ball milling for 32 h with a ball-to-powder ratio of 8 in an argon atmosphere to prevent oxidation during milling. Although mechanical alloying was performed for 32 h, no new phases were observed after mechanical alloying, as analyzed by X-ray diffraction. However, the crystallite size of the milled powders for 32 h decreased by factor two compared with the initial powders. Scanning electron micrographs showed that the coating layers formed >8 h …


Performance Of Free-Space Optical Communication Systems Using Optical Amplifiers Under Amplify-Forward And Amplify-Received Configurations, Ucuk Darusalam, Arockia Bazil Raj, Fitri Yuli Zulkifli, Purnomo Sidi Priambodo, Eko Tjipto Rahardjo Dec 2020

Performance Of Free-Space Optical Communication Systems Using Optical Amplifiers Under Amplify-Forward And Amplify-Received Configurations, Ucuk Darusalam, Arockia Bazil Raj, Fitri Yuli Zulkifli, Purnomo Sidi Priambodo, Eko Tjipto Rahardjo

Makara Journal of Technology

With the growth of digital technology in the stage of industrial revolution 4.0, the demand for broadcasting large amounts of information to last mile users has increased. Free-space optical (FSO) communication is one of the telecommunication platforms that has shown immense potential in meeting the demand for information broadcasting. In this work, the performance of FSO communication based on wavelength division multiplexing with a data rate of 80 Gbps is investigated through simulations. The configuration of optical amplifiers in the FSO system is set up on the basis of the amplify-forward and amplify-received configurations to expand the network. The investigation …


Iso 9001:2015 Risk-Based Thinking: A Framework Using Fuzzy-Support Vector Machine, Ralph Sherwin A. Corpuz Dec 2020

Iso 9001:2015 Risk-Based Thinking: A Framework Using Fuzzy-Support Vector Machine, Ralph Sherwin A. Corpuz

Makara Journal of Technology

Risk-based thinking (RBT) is one of the distinct new features of the International Organization for Standardization 9001:2015. Interestingly, the standard does not prescribe any tools. Hence, organizations are puzzled as to the extent of conformance. Some organizations have adopted formal tools. However, these tools seem insufficient in linking the standard into an evidence-based decision support system. To resolve gaps in RBT implementation, this paper proposes a framework based on fuzzy inference system (FIS) and support vector machine (SVM) to automate risk analysis and evaluation, proposal and verification of action plans, and prediction of the feasibility of risks and opportunities according …


Influence Of The Shaping Process On The Tensile Properties Of Steel Reinforcement Bars Carbon Steel Grades Bjtp24 And Bjts40, Nuraziz Handika, Ridha Amalia Idhar, Jessica Sjah, Essy Arijoeni, Elly Tjahjono Dec 2020

Influence Of The Shaping Process On The Tensile Properties Of Steel Reinforcement Bars Carbon Steel Grades Bjtp24 And Bjts40, Nuraziz Handika, Ridha Amalia Idhar, Jessica Sjah, Essy Arijoeni, Elly Tjahjono

Makara Journal of Technology

According to the current applicable national standard in Indonesia, i.e. SNI 07 2529 1991, in addition to the limitation on the loading rate, the steel bar must be reduced, formed, or lathed, as part of the shaping process of samples. This study determined and compared the effect of the shaping process on the yield strength, ultimate strength, and percent elongation by conducting tensile tests of steel bar grade BJTS40, i.e. deformed bar type of steel, and grade BJTP24, i.e., plain bar type of steel. Three diameters of the deformed bar (BJTS40) and one diameter of the plain bar (BJTP24) were …


Ionic Conductiviy Of Alginate-Nh4cl Polymer Electrolyte, Nurhasniza Mamajan Khan, Noor Saadiah Mohd Ali, Ahmad Faizrin Ahmad Fuzlin, Ahmad Salihin Samsudin Dec 2020

Ionic Conductiviy Of Alginate-Nh4cl Polymer Electrolyte, Nurhasniza Mamajan Khan, Noor Saadiah Mohd Ali, Ahmad Faizrin Ahmad Fuzlin, Ahmad Salihin Samsudin

Makara Journal of Technology

This study aims to produce a solid biopolymer electrolyte (SBE) by doping ammonium chloride (NH4Cl) into alginate. Solution casting was used to prepare the alginate–NH4Cl SBE system. Electrical impedance spectroscopy was performed to analyze the electrical properties of the SBE under the applied frequency range of 50 Hz–1 MHz. The incorporation of 8 wt.% NH4Cl enhances the ionic conductivity of the SBE up to 3.18 × 10-7 S/cm at ambient room temperature. Fourier transform infrared spectroscopy shows that complexation occurs between the hydroxyl (-OH), carboxylate (COO-) and ether linkage (C-O-C) functional groups due to the formation of inter- and intra-molecular …


A Density Functional Theory Study On Using Montmorillonite To Reduce Air Pollution, Triati Dewi Kencana Wungu, Meqorry Yusfi, Suprijadi Suprijadi Dec 2020

A Density Functional Theory Study On Using Montmorillonite To Reduce Air Pollution, Triati Dewi Kencana Wungu, Meqorry Yusfi, Suprijadi Suprijadi

Makara Journal of Technology

In this study, density functional theory (DFT) method is used to investigate the possibility of using a smectite clay mineral called montmorillonite (MMT) in reducing heavy metals, such as Cd, through Cd adsorption. The mechanism of Cd adsorption in MMT is observed theoretically, and the tetrahedrally isomorphic substitution on the upper layer of MMT is considered to observe the role of Al and Fe in strengthening Cd adsorption. Two types of MMT are modeled in this study: Al-MMT and Fe-MMT. The Al-MMT means that Al substitutes one atom in the upper tetrahedral layer of MMT, while Fe-MMT means that Fe …


Object Recognition And Voice Assistant With Augmented Reality, Juan Estrella Dec 2020

Object Recognition And Voice Assistant With Augmented Reality, Juan Estrella

Publications and Research

Our research project aims to provide a visually impaired person with a superimposed map that will guide the individual to the desired destination through a voice controlled virtual assistant application that integrates Augmented Reality (AR) with Artificial Intelligence (AI) Computer Vision and Natural Language Processing (subfields of AI) will be combined to identify the spatial environment and then create a graphic enhancement that provides the most direct route to the specific destination These technologies will be incorporated into the Microsoft Hololens which will be controlled by the user.


Improve The Prototype Of Low-Cost Near-Infrared Diffuse Optical Imaging System, Chen Xu, Mohammed Z. Shakil Dec 2020

Improve The Prototype Of Low-Cost Near-Infrared Diffuse Optical Imaging System, Chen Xu, Mohammed Z. Shakil

Publications and Research

Diffuse Optical Tomography (DOT) and Optical Spectroscopy using near-infrared (NIR) diffused light has demonstrated great potential for the initial diagnosis of tumors and in the assessment of tumor vasculature response to neoadjuvant chemotherapy. The aims of this project are 1) to test the different types of LEDs in the near-infrared range, and design the driving circuit, and test the modulation of LEDs at different frequencies; 2) to test the APDs as a detector, and build the receiver system and compare efficiency with pre-built systems. In this project, we are focusing on creating a low-cost infrared transmission system for tumor and …


Representational Learning Approach For Predicting Developer Expertise Using Eye Movements, Sumeet Maan Dec 2020

Representational Learning Approach For Predicting Developer Expertise Using Eye Movements, Sumeet Maan

School of Computing: Dissertations, Theses, and Student Research

The thesis analyzes an existing eye-tracking dataset collected while software developers were solving bug fixing tasks in an open-source system. The analysis is performed using a representational learning approach namely, Multi-layer Perceptron (MLP). The novel aspect of the analysis is the introduction of a new feature engineering method based on the eye-tracking data. This is then used to predict developer expertise on the data. The dataset used in this thesis is inherently more complex because it is collected in a very dynamic environment i.e., the Eclipse IDE using an eye-tracking plugin, iTrace. Previous work in this area only worked on …


Bibliometric Analysis Of The Literature In The Field Of Information Technology Relatedness, Ilham M, Anis Eliyana, Praptini Yulianti Dec 2020

Bibliometric Analysis Of The Literature In The Field Of Information Technology Relatedness, Ilham M, Anis Eliyana, Praptini Yulianti

Library Philosophy and Practice (e-journal)

This bibliometric describe Information Technology Relateness is defined as the use of information technology infrastructure and information technology management processes betweeWas this submission previously published in a journal? Bepress will automatically create an OpenURL for published articles. Learn more about OpenURLsn business units together. There is not much research on Information Technology Relateness by providing a big picture that is visualized from year to year. This study aims to map research in the field of Information Technology Relateness with data from all international research publications. This study performs a bibliometric method and analyzes research data using the Services Analyze …


Evaluation Of Characteristics Of Wireless Sensor Networks With Analytical Modeling, Halim Khujamatov, Ernazar Reypnazarov, Doston Hasanov, Elaman Nurullaev, Shahzod Sobirov Dec 2020

Evaluation Of Characteristics Of Wireless Sensor Networks With Analytical Modeling, Halim Khujamatov, Ernazar Reypnazarov, Doston Hasanov, Elaman Nurullaev, Shahzod Sobirov

Bulletin of TUIT: Management and Communication Technologies

In this paper, a mathematical model of the operation process of the ZigBee standard wireless network for remote monitoring systems based on the Markov chain apparatus was developed. Using the model was evaluated of the operation process of the CSMA/CA algorithm of the MAC level of the IEEE 802.15.4 ZigBee standard. The peculiarity of this mathematical model is that it takes into account the level of loading of network elements and potential distortions in the transmitted packets as a result of the influence of interference. Using the developed mathematical model, the main characteristics of the network operation process, such as …


Predicting Residential Energy Consumption Using Wavelet Decomposition With Deep Neural Network, Dagimawi Eneyew, Miriam A M Capretz, Girma Bitsuamlak, London Hydro Dec 2020

Predicting Residential Energy Consumption Using Wavelet Decomposition With Deep Neural Network, Dagimawi Eneyew, Miriam A M Capretz, Girma Bitsuamlak, London Hydro

Electrical and Computer Engineering Publications

Electricity consumption is accelerating due to economic and population growth. Hence, energy consumption prediction is becoming vital for overall consumption management and infrastructure planning. Recent advances in smart electric meter technology are making high-resolution energy consumption data available. However, many parameters influencing energy consumption are not typically monitored for residential buildings. Therefore, this study’s main objective is to develop a data-driven energy consumption forecasting model (next-hour consumption) for residential houses solely based on analyzing electricity consumption data. This research proposes a deep neural network architecture that combines stationary wavelet transform features and convolutional neural networks. The proposed approach utilizes automatically …


Deep Neural Network For Load Forecasting Centred On Architecture Evolution, Santiago Gomez-Rosero, Miriam A M Capretz, London Hydro Dec 2020

Deep Neural Network For Load Forecasting Centred On Architecture Evolution, Santiago Gomez-Rosero, Miriam A M Capretz, London Hydro

Electrical and Computer Engineering Publications

Nowadays, electricity demand forecasting is critical for electric utility companies. Accurate residential load forecasting plays an essential role as an individual component for integrated areas such as neighborhood load consumption. Short-term load forecasting can help electric utility companies reduce waste because electric power is expensive to store. This paper proposes a novel method to evolve deep neural networks for time series forecasting applied to residential load forecasting. The approach centres its efforts on the neural network architecture during the evolution. Then, the model weights are adjusted using an evolutionary optimization technique to tune the model performance automatically. Experimental results on …


Transfer-To-Transfer Learning Approach For Computer Aided Detection Of Covid-19 In Chest Radiographs, Barath Narayanan Narayanan, Russell C. Hardie, Vignesh Krishnaraja, Christina Karam, Venkata Salini Priyamvada Davuluru Dec 2020

Transfer-To-Transfer Learning Approach For Computer Aided Detection Of Covid-19 In Chest Radiographs, Barath Narayanan Narayanan, Russell C. Hardie, Vignesh Krishnaraja, Christina Karam, Venkata Salini Priyamvada Davuluru

Electrical and Computer Engineering Faculty Publications

The coronavirus disease 2019 (COVID-19) global pandemic has severely impacted lives across the globe. Respiratory disorders in COVID-19 patients are caused by lung opacities similar to viral pneumonia. A Computer-Aided Detection (CAD) system for the detection of COVID-19 using chest radiographs would provide a second opinion for radiologists. For this research, we utilize publicly available datasets that have been marked by radiologists into two-classes (COVID-19 and non-COVID-19). We address the class imbalance problem associated with the training dataset by proposing a novel transfer-to-transfer learning approach, where we break a highly imbalanced training dataset into a group of balanced mini-sets and …


Using Agile Methodology To Create A Working Software Application, Aaron Cuadras Dec 2020

Using Agile Methodology To Create A Working Software Application, Aaron Cuadras

Honors Theses

This thesis explains the importance of Agile in the process of writing a web application. A team of three developers worked for sixteen weeks to create a booking site able to hold important information related to customers and hotel owners. The framework used for the project is Ruby on Rails and we stress the importance of the Models-View-Controller pattern and its relation with the Agile methodology, the problem of creating a new application is the pace in which everything should be written as well as the ability to write features independent from one another. The results that we expect are …


Proportional Voting Based Semi-Unsupervised Machine Learning Intrusion Detection System, Yang G. Kim, Ohbong Kwon, John Yoon Dec 2020

Proportional Voting Based Semi-Unsupervised Machine Learning Intrusion Detection System, Yang G. Kim, Ohbong Kwon, John Yoon

Publications and Research

Feature selection of NSL-KDD data set is usually done by finding co-relationships among features, irrespective of target prediction. We aim to determine the relationship between features and target goals to facilitate different target detection goals regardless of the correlated feature selection. The unbalanced data structure in NSL-KDD data can be relaxed by Proportional Representation (PR). However, adopting PR would deny the notion of winner-take-all by attracting a majority of the vote and also provide a fairly proportional share for any grouping of like-minded data. Furthermore, minorities and majorities would get a fair share of power and representation in data structure …


Ppmexplorer: Using Information Retrieval, Computer Vision And Transfer Learning Methods To Index And Explore Images Of Pompeii, Cindy Roullet Dec 2020

Ppmexplorer: Using Information Retrieval, Computer Vision And Transfer Learning Methods To Index And Explore Images Of Pompeii, Cindy Roullet

Graduate Theses and Dissertations

In this dissertation, we present and analyze the technology used in the making of PPMExplorer: Search, Find, and Explore Pompeii. PPMExplorer is a software tool made with data extracted from the Pompei: Pitture e Mosaic (PPM) volumes. PPM is a valuable set of volumes containing 20,000 historical annotated images of the archaeological site of Pompeii, Italy accompanied by extensive captions. We transformed the volumes from paper, to digital, to searchable. PPMExplorer enables archaeologist researchers to conduct and check hypotheses on historical findings. We present a theory that such a concept is possible by leveraging computer generated correlations between artifacts using …


Imparting 3d Representations To Artificial Intelligence For A Full Assessment Of Pressure Injuries., Sofia Zahia Dec 2020

Imparting 3d Representations To Artificial Intelligence For A Full Assessment Of Pressure Injuries., Sofia Zahia

Electronic Theses and Dissertations

During recent decades, researches have shown great interest to machine learning techniques in order to extract meaningful information from the large amount of data being collected each day. Especially in the medical field, images play a significant role in the detection of several health issues. Hence, medical image analysis remarkably participates in the diagnosis process and it is considered a suitable environment to interact with the technology of intelligent systems. Deep Learning (DL) has recently captured the interest of researchers as it has proven to be efficient in detecting underlying features in the data and outperformed the classical machine learning …


Simple Modification For An Apriori Algorithm With Combination Reduction And Iteration Limitation Technique, Adie Wahyudi Oktavia Gama, Ni Made Widnyani Dec 2020

Simple Modification For An Apriori Algorithm With Combination Reduction And Iteration Limitation Technique, Adie Wahyudi Oktavia Gama, Ni Made Widnyani

Knowledge Engineering and Data Science

Apriori algorithm is one of the methods with regard to association rules in data mining. This algorithm uses knowledge from an itemset previously formed with frequent occurrence frequencies to form the next itemset. An a priori algorithm generates a combination by iteration methods that are using repeated database scanning process, pairing one product with another product and then recording the number of occurrences of the combination with the minimum limit of support and confidence values. The a priori algorithm will slow down to an expanding database in the process of finding frequent itemset to form association rules. Modification techniques are …


Segmentation Method For Face Modelling In Thermal Images, Albar Albar, Hendrick Hendrick, Rahmat Hidayat Dec 2020

Segmentation Method For Face Modelling In Thermal Images, Albar Albar, Hendrick Hendrick, Rahmat Hidayat

Knowledge Engineering and Data Science

Face detection is mostly applied in RGB images. The object detection usually applied the Deep Learning method for model creation. One method face spoofing is by using a thermal camera. The famous object detection methods are Yolo, Fast Region Based Convolutional Neural Networks (RCNN), Faster RCNN, SSD, and Mask RCNN. We proposed a segmentation Mask RCNN method to create a face model from thermal images. This model was able to locate the face area in images. The dataset was established using 1600 images. The images were created from direct capturing and collecting from the online dataset. The Mask RCNN was …


Generating Javanese Stopwords List Using K-Means Clustering Algorithm, Aji Prasetya Wibawa, Hidayah Kariima Fithri, Ilham Ari Elbaith Zaeni, Andrew Nafalski Dec 2020

Generating Javanese Stopwords List Using K-Means Clustering Algorithm, Aji Prasetya Wibawa, Hidayah Kariima Fithri, Ilham Ari Elbaith Zaeni, Andrew Nafalski

Knowledge Engineering and Data Science

Stopword removal necessary in Information Retrieval. It can remove frequently appeared and general words to reduce memory storage. The algorithm eliminates each word that is precisely the same as the word in the stopword list. However, generating the list could be time-consuming. The words in a specific language and domain must be collected and validated by specialists. This research aims to develop a new way to generate a stop word list using the K-means Clustering method. The proposed approach groups words based on their frequency. The confusion matrix calculates the difference between the findings with a valid stopword list created …


Authentication Based On Blockchain, Norah Alilwit Dec 2020

Authentication Based On Blockchain, Norah Alilwit

Doctoral Dissertations and Master's Theses

Across past decade online services have enabled individuals and organizations to perform different types of transactions such as banking, government transactions etc. The online services have also enabled more developments of applications, at cheap cost with elastic and scalable, fault tolerant system. These online services are offered by services providers which are use authentication, authorization and accounting framework based on client-server model. Though this model has been used over decades, study shows it is vulnerable to different hacks and it is also inconvenient to use for the end users. In addition, the services provider has total control over user data …