Open Access. Powered by Scholars. Published by Universities.®

Digital Commons Network™

Open Access. Powered by Scholars. Published by Universities.®

Engineering

Institution
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 1591 - 1620 of 2861

Full-Text Articles in Entire DC Network

Isolation And Onboarding: Gender Bias In Aviation Training Documents, William Hart Jan 2018

Isolation And Onboarding: Gender Bias In Aviation Training Documents, William Hart

Technical Communication Capstone Course

There is a growing interest in male-dominated industries and the challenges women face finding their place within the workplace community. Yet, there seems to be little research on how training documents, generally created by technical communicators, may isolate and limit women who seek to pursue careers in these fields. Technical communication and gender scholars have examined women in the technical communication field and gender bias in male-dominated industries but have not yet examined gender stereotypes in training documents. Training documents are designed to provide written instructions and a reference guide for job functions, workplace rules, orientation, and company policies. This …

Go to article

Adapt At Semeval-2018 Task 9: Skip-Gram Word Embeddings For Unsupervised Hypernym Discovery In Specialised Corpora, Alfredo Maldonado, Filip Klubicka Jan 2018

Adapt At Semeval-2018 Task 9: Skip-Gram Word Embeddings For Unsupervised Hypernym Discovery In Specialised Corpora, Alfredo Maldonado, Filip Klubicka

Other resources

This paper describes a simple but competitive unsupervised system for hypernym discovery. The system uses skip-gram word embeddings with negative sampling, trained on specialised corpora. Candidate hypernyms for an input word are predicted based on cosine similar- ity scores. Two sets of word embedding mod- els were trained separately on two specialised corpora: a medical corpus and a music indus- try corpus. Our system scored highest in the medical domain among the competing unsu- pervised systems but performed poorly on the music industry domain. Our approach does not depend on any external data other than raw specialised corpora.

Go to article

Examination Of Gain Scheduling And Fuzzy Controllers With Hybrid Reachability, Aaron W. Fifarek Jan 2018

Examination Of Gain Scheduling And Fuzzy Controllers With Hybrid Reachability, Aaron W. Fifarek

Browse all Theses and Dissertations

Modern aircraft with nonlinear flight envelopes predominately utilize gain scheduled controllers to provide stability of flight. Using gain scheduled control techniques, nonlinear envelopes can be linearized into collections of linear systems that operate under various system dynamics. Linear controllers approximate the nonlinear response over setpoints of operating conditions which allow traditional linear theory to be applied to maintain stability. Techniques to prove linear stability are well understood and realized in control systems, but when controllers are switched, interpolation methods must be used. Interpolation is necessary as gain scheduled systems do not have foundational switching paradigms as part of their realization …

Go to article

Computer Aided Drawing Software Delivered Through Emotional Learning. The Use Of Emoticons And Gifs As A Tool For Increasing Student Engagement., Matteo Zallio, Damon Berry Jan 2018

Computer Aided Drawing Software Delivered Through Emotional Learning. The Use Of Emoticons And Gifs As A Tool For Increasing Student Engagement., Matteo Zallio, Damon Berry

Conference Papers

It is known that one of the key factors for many manufacturing companies, who are involved in the design and development process, is represented by the quality of the skills, capacity and experience of computer-aided design draftsman and designers. This means that effective, up-to-date and engaging training has to be performed by teachers and instructors, since the early stage lectures for novice engineering students. When learners are engaged and actively participate in the training process, then this transfers in to a high, deep level of learning, quality of the learnt topics and perceived passion. The following question arises, “how can …

Go to article

Detecting Clickbait: Here’S How To Do It, Christopher Brogly, Victoria Rubin Jan 2018

Detecting Clickbait: Here’S How To Do It, Christopher Brogly, Victoria Rubin

Data and Test Instruments

Automatic clickbait detection is a relatively novel task in natural language processing (NLP) and machine learning (ML). “Clickbait” is a hyperlink created primarily to attract attention to its target content. This article introduces a binary classifier, the Language and Information Technology Research Lab (LiT.RL, pronounced “literal”) Clickbait Detector, which automatically distinguishes clickbait from nonclickbait. We used NLP and ML for 38 textual features, contrasting clickbait with “headlinese.” When tested on 11,000 hyperlinks, it achieves 94 per cent accuracy using a support vector machine. Integrated with the LiT.RL News Verification Browser, a downloadable stand-alone research tool, the Clickbait Detector user interface …

Go to article

Modular Product Architecture’S Decisions Support For Remanufacturing-Product Service System Synergy, Johnson Adebayo Fadeyi Jan 2018

Modular Product Architecture’S Decisions Support For Remanufacturing-Product Service System Synergy, Johnson Adebayo Fadeyi

Wayne State University Dissertations

Remanufacturing is identified as the most viable product end-of-life (EOL) management strategy. However, about 80% of manufactured products currently end up as wastes. Besides other benefits, the product service system (PSS) could curtail the main bottlenecks to remanufacturing namely quantity, quality, recovery time of used product, and negative perception of remanufactured products. Therefore, the integration of PSS and remanufacturing has been increasingly recommended as an enhanced product offering. However, an integration that is informed by mathematical analysis is missing. Meanwhile, the variables that bolster the performance of PSS and remanufacturing are substantially influenced by product development (PD) decisions. Among the …

Go to article

Using Regular Languages To Explore The Representational Capacity Of Recurrent Neural Architectures, Abhijit Mahalunkar, John D. Kelleher Jan 2018

Using Regular Languages To Explore The Representational Capacity Of Recurrent Neural Architectures, Abhijit Mahalunkar, John D. Kelleher

Conference papers

The presence of Long Distance Dependencies (LDDs) in sequential data poses significant challenges for computational models. Various recurrent neural architectures have been designed to mitigate this issue. In order to test these state-of-the-art architectures, there is growing need for rich benchmarking datasets. However, one of the drawbacks of existing datasets is the lack of experimental control with regards to the presence and/or degree of LDDs. This lack of control limits the analysis of model performance in relation to the specific challenge posed by LDDs. One way to address this is to use synthetic data having the properties of subregular languages. …

Go to article

Information Theory And Cognition: A Review, Khalid Sayood Jan 2018

Information Theory And Cognition: A Review, Khalid Sayood

Department of Electrical and Computer Engineering: Faculty Publications

We examine how information theory has been used to study cognition over the last seven decades. After an initial burst of activity in the 1950s, the backlash that followed stopped most work in this area. The last couple of decades has seen both a revival of interest, and a more firmly grounded, experimentally justified use of information theory. We can view cognition as the process of transforming perceptions into information—where we use information in the colloquial sense of the word. This last clarification is one of the problems we run into when trying to use information theoretic principles to understand …

Go to article

The Rock 2018, School Of Engineering And Computer Science Jan 2018

The Rock 2018, School Of Engineering And Computer Science

The Rock

No abstract provided.

Go to article

Performance Predication Model For Advance Traffic Control System (Atcs) Using Field Data, Masood Mirza Jan 2018

Performance Predication Model For Advance Traffic Control System (Atcs) Using Field Data, Masood Mirza

Electronic Theses and Dissertations

Reductions in capital expenditure revenues have created greater demands from users for quality service from existing facilities at lower costs forcing agencies to evaluate the performance of projects in more comprehensive and "greener" ways. The use of Adaptive Traffic Controls Systems (ATCS) is a step in the right direction by enabling practitioners and engineers to develop and implement traffic optimization strategies to achieve greater capacity out of the existing systems by optimizing traffic signal based on real time traffic demands and flow pattern. However, the industry is lagging in developing modeling tools for the ATCS which can predict the changes …

Go to article

Real-Time Implementation Of Three-Level Inverter-Based D-Statcom Using Neuro-Fuzzy Controller, Resul Çöteli̇, Hakan Açikgöz, Beşi̇r Dandil, Servet Tuncer Jan 2018

Real-Time Implementation Of Three-Level Inverter-Based D-Statcom Using Neuro-Fuzzy Controller, Resul Çöteli̇, Hakan Açikgöz, Beşi̇r Dandil, Servet Tuncer

Turkish Journal of Electrical Engineering and Computer Sciences

A distribution static compensator (D-STATCOM) is a custom power device connected in parallel to a power system to address electric power quality problems caused by reactive power and harmonics. To obtain high performance from a D-STATCOM, the D-STATCOM's \textit{dq}-axis currents must be controlled in an internal control loop. However, control of the D-STATCOM's currents is difficult because of its nonlinear structure, cross-coupling effect between the \textit{d}- and \textit{q}-axis, undefined dynamics, and fast changing load. Therefore, the controller to be preferred for a D-STATCOM should have a nonlinear and robust structure. In this study, a neuro-fuzzy controller (NFC), which is a …

Go to article

Using Virtual Reality And Photogrammetry To Enrich 3d Object Identity, Cole Juckette, Heather Richards-Rissetto, Hector Eluid Guerra Aldana, Norman Martinez Jan 2018

Using Virtual Reality And Photogrammetry To Enrich 3d Object Identity, Cole Juckette, Heather Richards-Rissetto, Hector Eluid Guerra Aldana, Norman Martinez

Department of Anthropology: Faculty Publications

The creation of digital 3D models for cultural heritage is commonplace. With the advent of efficient and cost effective technologies archaeologists are making a plethora of digital assets. This paper evaluates the identity of 3D digital assets and explores how to enhance or expand that identity by integrating photogrammetric models into VR. We propose that when a digital object acquires spatial context from its virtual surroundings, it gains an identity in relation to that virtual space, the same way that embedding the object with metadata gives it a specific identity through its relationship to other information. We explore this concept …

Go to article

A Study Of Eeg Signature Associated With Emotional And Stress Responses Due To Cyberbullying, Ashraf Alhujailli Jan 2018

A Study Of Eeg Signature Associated With Emotional And Stress Responses Due To Cyberbullying, Ashraf Alhujailli

Electronic Theses and Dissertations

The human brain processes vital information regarding human feelings. Prior research has focused on the problems of underage bullying, workplace bullying, burnout, mobbing and, most recently, cyberbullying. Scholars have traditionally examined the adverse outcomes of cyberbullying using subjective measures of stress and emotion for decades. However, very few studies examined cyberbullying using objective measures like EEG. The main goal of this study was to explore the relationship between the brain's EEG, expressed by the power spectral density, and emotions and stress due to two types of cyberbullying, specifically: 1) social exclusion, and 2) verbal harassment. This research also examined how …

Go to article

Caregiver Assessment Using Smart Gaming Technology: A Preliminary Approach, Garrett Goodman, Tanvi Banerjee, William Romine, Cogan Shimizu, Jennifer Hughes Jan 2018

Caregiver Assessment Using Smart Gaming Technology: A Preliminary Approach, Garrett Goodman, Tanvi Banerjee, William Romine, Cogan Shimizu, Jennifer Hughes

Computer Science and Engineering Faculty Publications

As pre-diagnostic technologies are becoming increasingly accessible, using them to improve the quality of care available to dementia patients and their caregivers is of increasing interest. Specifically, we aim to develop a tool for non- invasively assessing task performance in a simple gaming application. To address this, we have developed Caregiver Assessment using Smart Technology (CAST), a mobile application that personalizes a traditional word scramble game. Its core functionality uses a Fuzzy Inference System (FIS) optimized via a Genetic Algorithm (GA) to provide customized performance measures for each user of the system. With CAST, we match the relative level of …

Go to article

Construction Of A Turkish Proposition Bank, Koray Ak, Cansu Toprak, Volkan Esgel, Olcay Taner Yildiz Jan 2018

Construction Of A Turkish Proposition Bank, Koray Ak, Cansu Toprak, Volkan Esgel, Olcay Taner Yildiz

Turkish Journal of Electrical Engineering and Computer Sciences

This paper describes our approach to developing the Turkish PropBank by adopting the semantic role-labeling guidelines of the original PropBank and using the translation of the English Penn-TreeBank as a resource. We discuss the semantic annotation process of the PropBank and language-specific cases for Turkish, the tools we have developed for annotation, and quality control for multiuser annotation. In the current phase of the project, more than 9500 sentences are semantically analyzed and predicate-argument information is extracted for 1330 verbs and 1914 verb senses. Our plan is to annotate 17,000 sentences by the end of 2017.

Go to article

Relation Extraction Via One-Shot Dependency Parsing On Intersentential, Higher-Order, And Nested Relations, Gözde Gül Şahi̇n, Erdem Emekli̇gi̇l, Seçi̇l Arslan, Onur Ağin, Gülşen Eryi̇ği̇t Jan 2018

Relation Extraction Via One-Shot Dependency Parsing On Intersentential, Higher-Order, And Nested Relations, Gözde Gül Şahi̇n, Erdem Emekli̇gi̇l, Seçi̇l Arslan, Onur Ağin, Gülşen Eryi̇ği̇t

Turkish Journal of Electrical Engineering and Computer Sciences

Despite the emergence of digitalization, people still interact with institutions via traditional means such as submitting free formatted petitions, orders, or applications. These noisy documents generally consist of complex relations that are nested, higher-order, and intersentential. Most of the current approaches address extraction of only sentence-level and binary relations from grammatically correct text and generally require high-level linguistic features coming from preprocessors such as a parts-of-speech tagger, chunker, or syntactic parser. In this article, we focus on extracting complex relations in order to automate the task of understanding user intentions. We propose a novel language-agnostic and noise-immune approach that does …

Go to article

Effect Of Intuitionistic Fuzzy Normalization In Microarray Gene Selection, Prema Ramasamy, Premalatha Kandhasamy Jan 2018

Effect Of Intuitionistic Fuzzy Normalization In Microarray Gene Selection, Prema Ramasamy, Premalatha Kandhasamy

Turkish Journal of Electrical Engineering and Computer Sciences

Analysis of gene expression data is essential in microarray gene expression in order to retrieve the required information. Gene expression data generally contain a large number of genes but a small number of samples. The complicated relations among the different genes make analysis more difficult, and removing irrelevant genes improves the quality of results. This paper presents two fuzzy preprocessing techniques, using a fuzzy set (FS) and intuitionistic fuzzy set (IFS), to normalize datasets. In the feature selection part, four statistical methods were used. Using three publicly available gene expression datasets, the fuzzy normalization techniques were compared with two standard …

Go to article

Implementing Universal Dependency, Morphology, And Multiword Expression Annotation Standards For Turkish Language Processing, Umut Sulubacak, Gülşen Eryi̇ği̇t Jan 2018

Implementing Universal Dependency, Morphology, And Multiword Expression Annotation Standards For Turkish Language Processing, Umut Sulubacak, Gülşen Eryi̇ği̇t

Turkish Journal of Electrical Engineering and Computer Sciences

Released only a year ago as the outputs of a research project (``Parsing Web 2.0 Sentences'', supported in part by a TÜBİTAK 1001 grant (No. 112E276) and a part of the ICT COST Action PARSEME (IC1207)), IMST and IWT are currently the most comprehensive Turkish dependency treebanks in the literature. This article introduces the final states of our treebanks, as well as a newly integrated hierarchical categorization of the multiheaded dependencies and their organization in an exclusive deep dependency layer in the treebanks. It also presents the adaptation of recent studies on standardizing multiword expression and named entity annotation schemes …

Go to article

Automated Citation Sentiment Analysis Using High Order N-Grams: A Preliminary Investigation, Muhammad Touseef Ikram, Muhammad Tanvir Afzal, Naveed Anwer Butt Jan 2018

Automated Citation Sentiment Analysis Using High Order N-Grams: A Preliminary Investigation, Muhammad Touseef Ikram, Muhammad Tanvir Afzal, Naveed Anwer Butt

Turkish Journal of Electrical Engineering and Computer Sciences

Scientific papers hold an association with previous research contributions (i.e. books, journals or conference papers, and web resources) in the form of citations. Citations are deemed as a link or relatedness of the previous work to the cited work. The nature of the cited material could be supportive (positive), contrastive (negative), or objective (neutral). Extraction of the author's sentiment towards the cited scientific articles is an emerging research discipline due to various linguistic differences between the citation sentences and other domains of sentiment analysis. In this paper, we propose a technique for the identification of the sentiment of the citing …

Go to article

Large Vocabulary Recognition For Online Turkish Handwriting With Sublexical Units, Esma Fatima Bi̇lgi̇n Taşdemi̇r, Ayşe Berri̇n Yanikoğlu Yeşi̇lyurt Jan 2018

Large Vocabulary Recognition For Online Turkish Handwriting With Sublexical Units, Esma Fatima Bi̇lgi̇n Taşdemi̇r, Ayşe Berri̇n Yanikoğlu Yeşi̇lyurt

Turkish Journal of Electrical Engineering and Computer Sciences

We present a system for large vocabulary recognition of online Turkish handwriting, using hidden Markov models. While using a traditional approach for the recognizer, we have identified and developed solutions for the main problems specific to Turkish handwriting recognition. % First, since large amounts of Turkish handwriting samples are not available, the system is trained and optimized using the large UNIPEN dataset of English handwriting, before extending it to Turkish using a small Turkish dataset. % The delayed strokes, which pose a significant source of variation in writing order due to the large number of diacritical marks in Turkish, are …

Go to article

Extended Correlated Principal Component Analysis With Svm-Puk In Opinion Mining, Kollimarla Anusha Devi, Deepak Chowdary Edara, Venkatrama Phani Kumar Sistla, Venkata Krishna Kishore Kolli Jan 2018

Extended Correlated Principal Component Analysis With Svm-Puk In Opinion Mining, Kollimarla Anusha Devi, Deepak Chowdary Edara, Venkatrama Phani Kumar Sistla, Venkata Krishna Kishore Kolli

Turkish Journal of Electrical Engineering and Computer Sciences

With the rapid growth of microblogs and online sites, an inordinate number of product reviews are available on the Internet. They not only help in analyzing, but also assist in making informed decisions about product quality. In the proposed work, an extended correlated principal component analysis (ECPCA) is used for dimensionality reduction. A comparative analysis is conducted on movie reviews (DB-1) and Twitter datasets (DB-2 and DB-3) in opinion mining extraction. The performance of naive Bayes, CHIRP, and support vector machine (SVM) with kernel methods such as radial basis function (RBF), polynomial, and Pearson (PUK) are compared and analyzed on …

Go to article

Enlarging Multiword Expression Dataset By Co-Training, Senem Kumova Meti̇n Jan 2018

Enlarging Multiword Expression Dataset By Co-Training, Senem Kumova Meti̇n

Turkish Journal of Electrical Engineering and Computer Sciences

In multiword expressions (MWEs), multiple words unite to build a new unit in language. When MWE identification is accepted as a binary classification task, one of the most important factors in performance is to train the classifier with enough number of labelled samples. Since manual labelling is a time-consuming task, the performances of MWE recognition studies are limited with the size of the training sets. In this study, we propose the comparison-based and common-decision co-training approaches in order to enlarge the MWE dataset. In the experiments, the performances of the proposed approaches were compared to those of the standard co-training …

Go to article

Design Of A Multiagent-Based Smart Microgrid System For Building Energy And Comfort Management, Batyrkhan Omarov, Aigerim Altayeva Jan 2018

Design Of A Multiagent-Based Smart Microgrid System For Building Energy And Comfort Management, Batyrkhan Omarov, Aigerim Altayeva

Turkish Journal of Electrical Engineering and Computer Sciences

Modern intelligent control system design methodology in the electric power industry and their features are considered when providing the required comfort in multizone buildings with the use of multiagent power consumption and comfort management systems. Such a control system covers all the monitored zones of a building and, if necessary, can provide the greatest possible overall comfort in the building while reducing the required electric power. The purpose of this study was to develop a comfort management system in a multizoned building that can provide comfort while reducing the required electric power.

Go to article

Blood Glucose Control Using An Abc Algorithm-Based Fuzzy-Pid Controller, Seli̇m Soylu, Kenan Danişman Jan 2018

Blood Glucose Control Using An Abc Algorithm-Based Fuzzy-Pid Controller, Seli̇m Soylu, Kenan Danişman

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a Mamdani-type fuzzy controller is proposed as the controller part of an artificial pancreas. The controller is optimized with the artificial bee colony optimization algorithm. The glucose{insulin regulatory system, based on a nonlinear differential model in the presence of delay, is used both for virtual patient and healthy person data. The main target of the controller is to mimic a blood glucose concentration profile of the healthy person with exogenous insulin infusion. Simulations are performed to assess the control function in terms of tracking the blood glucose concentration profile of the healthy person and minimizing errors. To …

Go to article

Developing A Recurrent Neural Network With High Accuracy For Binary Sentiment Analysis, Kevin Cunanan Jan 2018

Developing A Recurrent Neural Network With High Accuracy For Binary Sentiment Analysis, Kevin Cunanan

CMC Senior Theses

Sentiment analysis has taken on various machine learning approaches in order to optimize accuracy, precision, and recall. However, Long Short-Term Memory (LSTM) Recurrent Neural Networks (RNNs) account for the context of a sentence by using previous predictions as additional input for future sentence predictions. Our approach focused on developing an LSTM RNN that could perform binary sentiment analysis for positively and negatively labeled sentences. In collaboration with Mariam Salloum, I developed a collection of programs to classify individual sentences as either positive or negative. This paper additionally looks into machine learning, neural networks, data preprocessing, implementation, and resulting comparisons.

Go to article

Fostering Giftedness And Creativity: Implementing Engineering By Design In Kuwait, Nathan Mentzer, Philip A. Reed, Meshari Alnouri, Mohammad Barbarji Jan 2018

Fostering Giftedness And Creativity: Implementing Engineering By Design In Kuwait, Nathan Mentzer, Philip A. Reed, Meshari Alnouri, Mohammad Barbarji

STEMPS Faculty Publications

The article offers information on a partnership between the International Technology & Engineering Educators Association (ITEEA) and the Sabah Al Ahmad Center for Giftedness and Creativity (SACGC) to support innovation and design education. The partnership is aimed towards the implementation of the Engineering byDesign (EbD) curriculum and contribute towards building a Kuwaiti society that fosters giftedness and creativity.

Go to article

Slim Embedding Layers For Recurrent Neural Language Models, Zhongliang Li Jan 2018

Slim Embedding Layers For Recurrent Neural Language Models, Zhongliang Li

Browse all Theses and Dissertations

Recurrent neural language (RNN) models are the state-of-the-art method for language modeling. When the vocabulary size is large, the space taken to store the model parameters becomes the bottleneck for the use of these type of models. We introduce a simple space compression method that stochastically shares the structured parameters at both the input and output embedding layers of RNN models to significantly reduce the size of model parameters, but still compactly represents the original input and the output embedding layers. The method is easy to implement and tune. Experiments on several data sets show that the new method achieves …

Go to article

Special Issue: Neutrosophic Information Theory And Applications, Florentin Smarandache, Jun Ye Jan 2018

Special Issue: Neutrosophic Information Theory And Applications, Florentin Smarandache, Jun Ye

Branch Mathematics and Statistics Faculty and Staff Publications

Neutrosophiclogic,symboliclogic,set,probability,statistics,etc.,are,respectively,generalizations of fuzzy and intuitionistic fuzzy logic and set, classical and imprecise probability, classical statistics, and so on. Neutrosophic logic, symbol logic, and set are gaining significant attention in solving many real-life problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistency, and indeterminacy. A number of new neutrosophic theories have been proposed and have been applied in computational intelligence, multiple-attribute decision making, image processing, medical diagnosis, fault diagnosis, optimization design, etc. This Special Issue gathers original research papers that report on the state of the art, as well as on recent advancements in neutrosophic information theory in soft computing, artificial intelligence, …

Go to article

Fundamentals Of Neutrosophic Logic And Sets And Their Role In Artificial Intelligence (Fundamentos De La Lógica Y Los Conjuntos Neutrosóficos Y Su Papel En La Inteligencia Artificial ), Florentin Smarandache, Maykel Leyva-Vazquez Jan 2018

Fundamentals Of Neutrosophic Logic And Sets And Their Role In Artificial Intelligence (Fundamentos De La Lógica Y Los Conjuntos Neutrosóficos Y Su Papel En La Inteligencia Artificial ), Florentin Smarandache, Maykel Leyva-Vazquez

Branch Mathematics and Statistics Faculty and Staff Publications

Neutrosophy is a new branch of philosophy which studies the origin, nature and scope of neutralities. This has formed the basis for a series of mathematical theories that generalize the classical and fuzzy theories such as the neutrosophic sets and the neutrosophic logic. In the paper, the fundamental concepts related to neutrosophy and its antecedents are presented. Additionally, fundamental concepts of artificial intelligence will be defined and how neutrosophy has come to strengthen this discipline.

Go to article

Modelo De Recomendación Basado En Conocimiento Y Números Svn, Maykel Leyva-Vazquez, Florentin Smarandache Jan 2018

Modelo De Recomendación Basado En Conocimiento Y Números Svn, Maykel Leyva-Vazquez, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

Recommendation models are useful in the decision-making process that allow the user a set of options that are expected to meet their expectations. Recommendation models are useful in the decision-making process that offer the user a set of options that are expected to meet their SVN expectations to express linguistic terms.

Go to article

First Prev Next Last