Physical Sciences and Mathematics Commons^™

Graphical Method For Solving Neutrosophical Nonlinear Programming Models, Florentin Smarandache, Maissam Ahmad Jdid

Branch Mathematics and Statistics Faculty and Staff Publications

An important method for finding the optimal solution for linear and nonlinear models is the graphical method, which is used if the linear or nonlinear mathematical model contains one, two, or three variables. The models that contain only two variables are among the most models for which the optimal solution has been obtained graphically, whether these models are linear or non-linear in references and research that are concerned with the science of operations research, when the data of the issue under study is classical data. In this research, we will present a study through, which we present the graphical method …

Advances And Applications Of Dsmt For Information Fusion. Collected Works, Volume 5, Florentin Smarandache, Jean Dezert, Albena Tchamova

Branch Mathematics and Statistics Faculty and Staff Publications

This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 (available at fs.unm.edu/DSmT-book4.pdf or www.onera.fr/sites/default/files/297/2015-DSmT-Book4.pdf) in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered.

First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of …

Approach To The Personnel Selection Process In A Group Decision-Making Environment Based On The Psi Method, Maja Stanujkic, Gabrijela Popovic, Dragisa Stanujkic, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

The selection of adequate personnel is significant for the successful operation of companies. Therefore, this article observed the application of the Preference Selection Index (PSI) method for evaluating personnel in the conditions of group decision-making. The PSI method was chosen because it does not require determining the weights of the criteria, which is why it can be suitable for application by HR managers unfamiliar with the application of multiple criteria decision-making methods.

Beyond Negation And Excluded Middle: An Exploration To Embrace The Otherness Beyond Classical Logic System And Into Neutrosophic Logic, Florentin Smarandache, Victor Christianto

Branch Mathematics and Statistics Faculty and Staff Publications

As part of our small contribution in dialogue toward better peace development and reconciliation studies, and following Toffler & Toffler’s War and Antiwar (1993), the present article delves into a realm of logic beyond the traditional confines of negation and the excluded middle principle, exploring the nuances of "Otherness" that transcend classical and Nagatomo logics. Departing from the foundational premises of classical Aristotelian logic systems, this exploration ventures into alternative realms of reasoning, specifically examining Neutrosophic Logic and Klein bottle logic (cf. Smarandache, 2005). The study challenges conventional boundaries and explores the implications of embracing paradoxes and self-reference in logic …

Superhyperfunction, Superhyperstructure, Neutrosophic Superhyperfunction And Neutrosophic Superhyperstructure: Current Understanding And Future Directions, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

The n-th PowerSet of a Set {or Pn(S)} better describes our real world, because a system S (which may be a company, institution, association, country, society, set of objects/plants/animals/beings, set of concepts/ideas/propositions, etc.) is formed by sub-systems, which in their turn by sub-sub-systems, and so on. We prove that the SuperHyperFunction is a generalization of classical Function, SuperFunction, and HyperFunction. And the SuperHyperAlgebra, SuperHyperGraph are part of the SuperHyperStructure. Almost all structures in our real world are Neutrosophic SuperHyperStructures since they have indeterminate/incomplete/uncertain/conflicting data.

Graphical Method For Solving Neutrosophical Nonlinear Programming Models, Maissam Ahmad Jdid, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

One important method for finding the optimal solution for linear and nonlinear models is the graphical method, which is used if the linear or nonlinear mathematical model contains one, two, or three variables. Models that contain only two variables are models for which the optimal solution has been obtained graphically, whether these models are linear or non-linear in references that rely on classical logic. In this research, we present a study through which we present the graphical method for solving nonlinear neutrosophical models in the following case: (1) The objective function is a nonlinear function, and the constraints are linear …

On Characterizing Efficient And Properly Efficient Solutions For Multi- Objective Programming Problems In A Complex Space, Alhanouf Alburaikan, Hamiden Abd El-Wahed Khalifa, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

In this paper, a complex non- linear programming problem with the two parts (real and imaginary) is considered. The efficient and proper efficient solutions in terms of optimal solutions of related appropriate scalar optimization problems are characterized. Also, the Kuhn-Tuckers' conditions for efficiency and proper efficiency are derived. This paper is divided into two independently parts: The first provides the relationships between the optimal solutions of a complex single-objective optimization problem and solutions of two related real programming problems. The second part is concerned with the theory of a multi-objective optimization in complex space.

Higher-Degree Asymptotes Of A Rational-Polynomial Function, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

By a straight-forward method we extend the horizontal and slant asymptotes to the higher -degree asymptotes of a function, and we give several examples and prove a theorem.

Another Way To Divide Two Complex Numbers: Identification Method, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

In this short note to design another method to divide two complex numbers and present a numerical example.

Robots And Reference Services, Abdullahi Olayinka Isiaka, Biliamin Abiola Aremu, Abdulfatai Soliu, Fahisat Romoke Isiaq

Library Philosophy and Practice (e-journal)

Abstract

This paper explores the integration of robots into reference services in various library and information settings. The use of robots in these contexts has gained momentum in recent years, offering innovative solutions to enhance user experiences, improve access to information, and expand the capabilities of reference librarians. This paper reviews the current state of robots in reference services, discusses their potential benefits and challenges, and examines case studies to illustrate their practical applications. Furthermore, it offers insights into the future prospects and ethical considerations associated with the integration of robots in this domain. This paper delves into the fascinating …

Learning Feature Embedding Refiner For Solving Vehicle Routing Problems, Jingwen Li, Yining Ma, Zhiguang Cao, Yaoxin Wu, Wen Song, Jie Zhang, Yeow Meng Chee

Research Collection School Of Computing and Information Systems

While the encoder–decoder structure is widely used in the recent neural construction methods for learning to solve vehicle routing problems (VRPs), they are less effective in searching solutions due to deterministic feature embeddings and deterministic probability distributions. In this article, we propose the feature embedding refiner (FER) with a novel and generic encoder–refiner–decoder structure to boost the existing encoder–decoder structured deep models. It is model-agnostic that the encoder and the decoder can be from any pretrained neural construction method. Regarding the introduced refiner network, we design its architecture by combining the standard gated recurrent units (GRU) cell with two new …

A Diversity-Enhanced Memetic Algorithm For Solving Electric Vehicle Routing Problems With Time Windows And Mixed Backhauls, Jianhua Xiao, Jingguo Du, Zhiguang Cao, Xingyi Zhang, Yunyun Niu

Research Collection School Of Computing and Information Systems

The electric vehicle routing problem (EVRP) has been studied increasingly because of environmental concerns. However, existing studies on the EVRP mainly focus on time windows and sole linehaul customers, which might not be practical as backhaul customers are also ubiquitous in reality. In this study, we investigate an EVRP with time windows and mixed backhauls (EVRPTWMB), where both linehaul and backhaul customers exist and can be served in any order. To address this challenging problem, we propose a diversity-enhanced memetic algorithm (DEMA) that integrates three types of novel operators, including genetic operators based on adaptive selection mechanism, a selection operator …

Seven Pillars For The Future Of Artificial Intelligence, Erik Cambria, Rui Mao, Melvin Chen, Zhaoxia Wang, Seng-Beng Ho

Research Collection School Of Computing and Information Systems

In recent years, AI research has showcased tremendous potential to impact positively humanity and society. Although AI frequently outperforms humans in tasks related to classification and pattern recognition, it continues to face challenges when dealing with complex tasks such as intuitive decision-making, sense disambiguation, sarcasm detection, and narrative understanding, as these require advanced kinds of reasoning, e.g., commonsense reasoning and causal reasoning, which have not been emulated satisfactorily yet. To address these shortcomings, we propose seven pillars that we believe represent the key hallmark features for the future of AI, namely: Multidisciplinarity, Task Decomposition, Parallel Analogy, Symbol Grounding, Similarity Measure, …

Champions For Social Good: How Can We Discover Social Sentiment And Attitude-Driven Patterns In Prosocial Communication?, Raghava Rao Mukkamala, Robert J. Kauffman, Helle Zinner Henriksen

Research Collection School Of Computing and Information Systems

The UN High Commissioner on Refugees (UNHCR) is pursuing a social media strategy to inform people about displaced populations and refugee emergencies. It is actively engaging public figures to increase awareness through its prosocial communications and improve social informedness and support for policy changes in its services. We studied the Twitter communications of UNHCR social media champions and investigated their role as high-profile influencers. In this study, we offer a design science research and data analytics framework and propositions based on the social informedness theory we propose in this paper to assess communication about UNHCR’s mission. Two variables—refugee-emergency and champion …

Seqadver: Automatic Payload Construction And Injection In Sequence-Based Android Adversarial Attack, Fei Zhang, Ruitao Feng, Xiaofei Xie, Xiaohong Li, Lianshuan Shi

Research Collection School Of Computing and Information Systems

Machine learning has achieved a great success in the field of Android malware detection. In order to avoid being caught by these ML-based Android malware detection, malware authors are inclined to initiate adversarial sample attacks by tampering with mobile applications. Although machine learning has high capability, it lacks robustness against adversarial attacks. Currently, many of the adversarial attacking tools not only inject dead code into target applications, which can never be executed, but also require the injection of many benign features into a malicious APK. This can be easily noticeable by program analysis techniques. In this paper, we propose SeqAdver, …

Coordinating Multi-Party Vehicle Routing With Location Congestion Via Iterative Best Response, Waldy Joe, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

This work is motivated by a real-world problem of coordinating B2B pickup-delivery operations to shopping malls involving multiple non-collaborative logistics service providers (LSPs) in a congested city where space is scarce. This problem can be categorized as a vehicle routing problem with pickup and delivery, time windows and location congestion with multiple LSPs (or ML-VRPLC in short), and we propose a scalable, decentralized, coordinated planning approach via iterative best response. We formulate the problem as a strategic game where each LSP is a self-interested agent but is willing to participate in a coordinated planning as long as there are sufficient …

Design Of An Internal Osculating Waverider Intake, Mark E. Noftz, Andrew J. Shuck, Joseph S. Jewell, Jonathan Poggie, Andrew N. Bustard, Thomas J. Juliano, Nicholas J. Bisek

Publications

The design of an inward-turning, high-speed, three-dimensional streamline traced intake is presented from osculating axisymmetric theory. To satisfy the osculating intake design criteria, a stitched Busemann diffuser and Internal Conical Flow-A solution is used as the basic isentropic compressive streamline. This new contour provides efficient compression, high flow uniformity, and straight leading edge shocks of equal strength. Additionally, a novel method for constructing the inlet cowl is presented. The combined process leads to a new method of high-speed intake design. A generic shape-transitioned intake is constructed and named the Indiana Inlet for the Indiana universities that contributed to the project. …

Estimating Potential Exposure From Abandoned Uranium Mine Sites Through Machine Learning Classification Of Animal Behavior: A Case Study In The Navajo Nation, Christopher Girlamo

Geography ETDs

Waste from Abandoned Uranium Mines (AUMs) has negatively impacted Indigenous communities for generations. To answer these concerns, this research collaborated with Navajo Nation community members in Cove, AZ and Red Valley, AZ in order to better predict the potential AUM waste exposure their flocks face. A GIS-Multi-Criteria Decision Analysis (GIS-MCDA) model quantified potential exposure to AUM waste. Animal behavior was classified based on GPS and accelerometer data utilizing a Hidden Markov Model (HMM). The results of both the GIS-MCDA and animal behavior classification modeling was combined into a cumulative exposure potential value for each animal. This study found that livestock …

2-Uniform Covering Groups Of Elementary Abelian 2-Groups, Dana Saleh, Rachel Quinlan

All Works

This article is concerned with the classification of Schur covering groups of the elementary abelian group of order (Formula presented.), up to isomorphism. We consider those covering groups possessing a generating set of n elements having only two distinct squares. We show that such groups may be represented by 2-vertex-colored and 2-edge-colored graphs of order n. We show that in most cases, the isomorphism type of the group is determined by that of the 2-colored graph, and we analyze the exceptions.

3d Indoor Modeling And Game Theory Based Navigation For Pre And Post Covid-19 Situation, Jaiteg Singh, Noopur Tyagi, Saravjeet Singh, Babar Shah, Farman Ali, Ahmad Ali Alzubi, Abdulrhman Alkhanifer

All Works

The COVID-19 pandemic has greatly affected human behavior, creating a need for individuals to be more cautious about health and safety protocols. People are becoming more aware of their surroundings and the importance of minimizing the risk of exposure to potential sources of infection. This shift in mindset is particularly important in indoor environments, especially hospitals, where there is a greater risk of virus transmission. The implementation of route planning in these areas, aimed at minimizing interaction and exposure, is crucial for positively influencing individual behavior. Accurate maps of buildings help provide location-based services, prepare for emergencies, and manage infrastructural …

Harvesting Publication Data To The Institutional Repository From Scopus, Web Of Science, Dimensions And Unpaywall Using A Custom R Script, Yrjo Lappalainen, Nikesh Narayanan

All Works

Institutional repositories are established tools for archiving and increasing the visibility and availability of academic outputs. Although the potential benefits of institutional repositories are well researched and many funders and institutions already mandate open access publishing via gold or green open access routes, institutional repositories often struggle with lack of growth and sustained workflows for content recruitment. Institutions have come up with various (and often creative) workflows for populating their repositories, including institutional open access mandates, library-mediated self-archiving, fully or partially automated content harvesting and integrations between repositories and Current Research Information Systems (CRIS). Zayed University launched the ZU Scholars …

Forecasting Energy Consumption Demand Of Customers In Smart Grid Using Temporal Fusion Transformer (Tft), Amril Nazir, Abdul Khalique Shaikh, Abdul Salam Shah, Ashraf Khalil

All Works

Energy consumption prediction has always remained a concern for researchers because of the rapid growth of the human population and customers joining smart grids network for smart home facilities. Recently, the spread of COVID-19 has dramatically increased energy consumption in the residential sector. Hence, it is essential to produce energy per the residential customers' requirements, improve economic efficiency, and reduce production costs. The previously published papers in the literature have considered the overall energy consumption prediction, making it difficult for production companies to produce energy per customers' future demand. Using the proposed study, production companies can accurately have energy per …

Of Stances, Themes, And Anomalies In Covid-19 Mask-Wearing Tweets, Jwen Fai Low, Benjamin C.M. Fung, Farkhund Iqbal, Ebrahim Bagheri

All Works

COVID-19 is an opportunity to study public acceptance of a ‘‘new’’ healthcare intervention, universal masking, which unlike vaccination, is mostly alien to the Anglosphere public despite being practiced in ages past. Using a collection of over two million tweets, we studied the ways in which proponents and opponents of masking vied for influence as well as the themes driving the discourse. Pro-mask tweets encouraging others to mask up dominated Twitter early in the pandemic though its continued dominance has been eroded by anti-mask tweets criticizing others for their masking behavior. Engagement, represented by the counts of likes, retweets, and replies, …

The Application Of Statistical Modeling To Identify Genetic Associations With Mild Traumatic Brain Injury Outcomes, Caroline Schott

Masters Theses

"Traumatic brain injury (TBI) is a growing health concern, with millions of TBI diagnoses in the United States each year. The vast majority of TBI diagnoses are mild traumatic brain injuries (mTBI), which can be challenging to manage due to variation in symptoms and outcomes. Most individuals with mTBI successfully recover quickly, but a small subset has a delayed recovery. Although the factors that contribute to this variation in recovery are not clearly understood, it is possible that genetic differences may play a role. Very few studies have investigated the association between single nucleotide polymorphisms (SNPs) with mTBI outcomes and …

Computer Vision In Adverse Conditions: Small Objects, Low-Resoltuion Images, And Edge Deployment, Raja Sunkara

Masters Theses

"Computer vision based on deep learning is an essential field that plays a significant role in object detection, image classification, semantic segmentation, instance segmentation, and other applications. However, these models face significant challenges in adverse conditions, such as small objects, low-resolution images, and edge deployment. These challenges limit the accuracy and efficiency of computer vision algorithms, making it difficult to obtain reliable results.

The primary objective of this thesis is to assess the performance of deep learning- based computer vision models in challenging conditions and provide viable solutions to overcome the obstacles. The study will specifically address three key challenges, …

Characteristics And Color Varieties Of Spinels From Main Deposits, Boonyapak Aksorn

Chulalongkorn University Theses and Dissertations (Chula ETD)

This study investigates the characteristics and color variations of spinels from main deposits, including Liolava in Madagascar, Tunduru in Tanzania, Mogok in Myanmar, and three deposits in Vietnam (Minh Tien, Lang Chap, and An Phu). These spinel samples are categorized into four color varieties, i.e., red, orange, blue, and purple. All samples yielded the common properties of spinels. In addition, most red and orange spinels display strong red fluorescence under long wave ultraviolet (LWUV) and short wave ultraviolet (SWUV) lamps, however, some orange spinels exhibit non-fluorescence to red fluorescence under SWUV lamps. Blue spinel displays non-fluorescence under LWUV and SWUV …

Development Of Electrochemical Biosensor For Detection Of Thyroid–Stimulating Hormone, Kittirat Kitticharoenwiwat

Chulalongkorn University Theses and Dissertations (Chula ETD)

This dissertation focused on the development of electrochemical paper-based immunosensor for determining thyroid-stimulating hormone (TSH) using a label-free immunoassay. Thyroid-stimulating hormone is a pituitary hormone that stimulates the thyroid gland to produce thyroid hormones for the body’s metabolism. The current electrochemiluminescence method for determining TSH as a specific biomarker indicating congenital hypothyroidism (CHT) onset is unfortunately restricted to laboratory settings, thereby resulting in limited practical utilization, delayed diagnosis, and severe outcomes. Herein, we proposed a simple, rapid, portable, and sensitive electrochemical biosensor with a label-free format based on bovine serum albumin (BSA)/graphene oxide (GO) nanocomposite for TSH determination. Caboxylated GO …

Bamboo Biochar For Bar Adsorptive Microextraction Of Parabens In Water, Maytinee Jantorn

Chulalongkorn University Theses and Dissertations (Chula ETD)

In this research, bamboo biochar bar was prepared in the form of small-sized rods using starch as a binder and applied as a sorbent in bar adsorptive microextraction (BAµE) of parabens (methyl paraben, ethyl paraben, propyl paraben and butyl paraben) in water. The mixture of bamboo biochar which has a size of 60-80 mesh, a surface area of 102.6 m²g-1 and a pore size of 0.7 nm and starch in a weight ratio of 1:13 gave the good mechanical stability and high removal efficiency of parabens. When applied the bamboo biochar bar as a sorbent, the optimum conditions for BAµE …

Selective Photodegradation Of Food Contaminants Using Titania-Silica-Iron Oxide Nanocomposites With Molecularly Imprinted Technology, Mehak Un Nisa

Chulalongkorn University Theses and Dissertations (Chula ETD)

In this study, magnetic imprinted photocatalysts (Fe3O4@SiO2@TiO2@MIP and Fe3O4@SiO2@MIP@TiO2) have been synthesized successfully by surface molecular imprinting technique. 5,7-dimethoxy-coumarin was used as a dummy template to give specific recognition ability to AFB1. A range of analytical techniques including X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared (FT-IR), vibrating sample magnetometer (VSM), and Branauer-Emmett-Teller (BET) were employed to study the crystal structure, morphology, and chemical composition of the nanocomposites. The HPLC-DAD was used to quantify the photodegradation efficiency of imprinted photocatalysts under different factors such as the source of irradiation light, initial concentration of analyte, amount of photocatalyst, and …

Polyaniline/Cellulose Nanofiber/Polyvinyl Alcohol Hydrogel-Modified Screen-Printed Graphene Electrode For Cd2+ And Ni2+ Detection, Pichapon Boonkrong

Chulalongkorn University Theses and Dissertations (Chula ETD)

Heavy metal contamination in wastewater has been an environmental issue, so the determination of heavy metals by an accurate and simple method is important. In this work, polyaniline/cellulose nanofiber/polyvinyl alcohol hydrogel-modified screen-printed graphene electrode (PANI/CNF/PVA hydrogel-modified SPGE) was fabricated by combining the advantages of graphene and conductive hydrogel to increase the conductivity and preconcentrate the metal ions to fabricate the modified electrode for the simultaneous detection of Cd2+ and Ni2+. First, PANI/CNF nanocomposite was synthesized by in situ chemical polymerization, and CNF was shown to prevented PANI aggregation and provided sufficient porous structure on the modified electrode. The PANI/CNF nanocomposite …