Link prediction by correlation on social network
- Rahman, Md Shafiur, Dey, Leema Rani, Haider, Sajal, Uddin, Md Ashraf, Islam, Manowarul
- Authors: Rahman, Md Shafiur , Dey, Leema Rani , Haider, Sajal , Uddin, Md Ashraf , Islam, Manowarul
- Date: 2017
- Type: Text , Conference proceedings
- Relation: 2017 20th International Conference of Computer and Information Technology (ICCIT); Dhaka, Bangladesh; 22-24 December 2017 p. 1-6
- Full Text: false
- Reviewed:
- Description: In a social network, the topology of the network grows through the formation of the link. the connection between two nodes in a social network indicates a confidence in terms of the similarity of some activities. Generally, a new link in the social network is created from different perspectives such as familiarity, cohesiveness, geographical locations etc. The concept of the link in the social network has been utilized to discover the hidden meaning of different fields such as e-commerce, bioinformatics and information retrieval. The prediction of a new link between two nodes in the social network is normally accomplished based on the nature of the topology and the similarity function among the nodes is defined with the help of the number of common friends. In this paper, we propose two link prediction algorithms: Local Link Prediction Algorithm and Global Link prediction by taking into consideration of user's activities as well as the common friends. We apply two formulas called correlation based cScore and influential score based iScore to measure the similarity between the two predicted nodes. Finally, we analyze the performance of the proposed algorithms by using DBLP, PPI, PB, and USAir data sets and the experimental result attests that our link predicted algorithm outperforms over the existing algorithms.
CRICRATE : A cricket match conduction and player evaluation framework
- Uddin, Md Ashraf, Hasan, Mahmudul, Halder, Sajal, Ahamed, Sajeeb, Acharjee, Uzzal
- Authors: Uddin, Md Ashraf , Hasan, Mahmudul , Halder, Sajal , Ahamed, Sajeeb , Acharjee, Uzzal
- Date: 2019
- Type: Text , Conference paper
- Relation: International Conference on Emerging Technologies in Data Mining and Information Security, IEMIS 2018 Vol. 755, p. 491-500
- Full Text: false
- Reviewed:
- Description: Cricket has appeared as one of the most favorite outdoor games in the present world. The cricket players represent a country and create economic, political, and diplomatic relations among nations. The cricket board of a country requires selecting the fittest players for the upcoming team among some good players. We propose an architecture called Cricket Match Conduction and Player Evaluation Framework by developing some algorithms to predict the score of the players as well as the algorithm to evaluate the man of the match in one day or test cricket match. We implemented the framework by Weka and web technology. © Springer Nature Singapore Pte Ltd. 2019.
- Authors: Mestrom, Sanne
- Date: 2012
- Type: Text , Visual art work
- Full Text:
Soil moisture, organic carbon, and nitrogen content prediction with hyperspectral data using regression models
- Datta, Dristi, Paul, Manoranjan, Murshed, Manzur, Teng, Shyh Wei, Schmidtke, Leigh
- Authors: Datta, Dristi , Paul, Manoranjan , Murshed, Manzur , Teng, Shyh Wei , Schmidtke, Leigh
- Date: 2022
- Type: Text , Journal article
- Relation: Sensors (Basel, Switzerland) Vol. 22, no. 20 (2022), p.
- Full Text:
- Reviewed:
- Description: Soil moisture, soil organic carbon, and nitrogen content prediction are considered significant fields of study as they are directly related to plant health and food production. Direct estimation of these soil properties with traditional methods, for example, the oven-drying technique and chemical analysis, is a time and resource-consuming approach and can predict only smaller areas. With the significant development of remote sensing and hyperspectral (HS) imaging technologies, soil moisture, carbon, and nitrogen can be estimated over vast areas. This paper presents a generalized approach to predicting three different essential soil contents using a comprehensive study of various machine learning (ML) models by considering the dimensional reduction in feature spaces. In this study, we have used three popular benchmark HS datasets captured in Germany and Sweden. The efficacy of different ML algorithms is evaluated to predict soil content, and significant improvement is obtained when a specific range of bands is selected. The performance of ML models is further improved by applying principal component analysis (PCA), a dimensional reduction method that works with an unsupervised learning method. The effect of soil temperature on soil moisture prediction is evaluated in this study, and the results show that when the soil temperature is considered with the HS band, the soil moisture prediction accuracy does not improve. However, the combined effect of band selection and feature transformation using PCA significantly enhances the prediction accuracy for soil moisture, carbon, and nitrogen content. This study represents a comprehensive analysis of a wide range of established ML regression models using data preprocessing, effective band selection, and data dimension reduction and attempt to understand which feature combinations provide the best accuracy. The outcomes of several ML models are verified with validation techniques and the best- and worst-case scenarios in terms of soil content are noted. The proposed approach outperforms existing estimation techniques.
- Authors: Datta, Dristi , Paul, Manoranjan , Murshed, Manzur , Teng, Shyh Wei , Schmidtke, Leigh
- Date: 2022
- Type: Text , Journal article
- Relation: Sensors (Basel, Switzerland) Vol. 22, no. 20 (2022), p.
- Full Text:
- Reviewed:
- Description: Soil moisture, soil organic carbon, and nitrogen content prediction are considered significant fields of study as they are directly related to plant health and food production. Direct estimation of these soil properties with traditional methods, for example, the oven-drying technique and chemical analysis, is a time and resource-consuming approach and can predict only smaller areas. With the significant development of remote sensing and hyperspectral (HS) imaging technologies, soil moisture, carbon, and nitrogen can be estimated over vast areas. This paper presents a generalized approach to predicting three different essential soil contents using a comprehensive study of various machine learning (ML) models by considering the dimensional reduction in feature spaces. In this study, we have used three popular benchmark HS datasets captured in Germany and Sweden. The efficacy of different ML algorithms is evaluated to predict soil content, and significant improvement is obtained when a specific range of bands is selected. The performance of ML models is further improved by applying principal component analysis (PCA), a dimensional reduction method that works with an unsupervised learning method. The effect of soil temperature on soil moisture prediction is evaluated in this study, and the results show that when the soil temperature is considered with the HS band, the soil moisture prediction accuracy does not improve. However, the combined effect of band selection and feature transformation using PCA significantly enhances the prediction accuracy for soil moisture, carbon, and nitrogen content. This study represents a comprehensive analysis of a wide range of established ML regression models using data preprocessing, effective band selection, and data dimension reduction and attempt to understand which feature combinations provide the best accuracy. The outcomes of several ML models are verified with validation techniques and the best- and worst-case scenarios in terms of soil content are noted. The proposed approach outperforms existing estimation techniques.
An efficient hybrid system for anomaly detection in social networks
- Rahman, Md Shafiur, Halder, Sajal, Uddin, Ashraf, Acharjee, Uzzal
- Authors: Rahman, Md Shafiur , Halder, Sajal , Uddin, Ashraf , Acharjee, Uzzal
- Date: 2021
- Type: Text , Journal article
- Relation: Cybersecurity Vol. 4, no. 1 (2021), p.
- Full Text:
- Reviewed:
- Description: Anomaly detection has been an essential and dynamic research area in the data mining. A wide range of applications including different social medias have adopted different state-of-the-art methods to identify anomaly for ensuring user’s security and privacy. The social network refers to a forum used by different groups of people to express their thoughts, communicate with each other, and share the content needed. This social networks also facilitate abnormal activities, spread fake news, rumours, misinformation, unsolicited messages, and propaganda post malicious links. Therefore, detection of abnormalities is one of the important data analysis activities for the identification of normal or abnormal users on the social networks. In this paper, we have developed a hybrid anomaly detection method named DT-SVMNB that cascades several machine learning algorithms including decision tree (C5.0), Support Vector Machine (SVM) and Naïve Bayesian classifier (NBC) for classifying normal and abnormal users in social networks. We have extracted a list of unique features derived from users’ profile and contents. Using two kinds of dataset with the selected features, the proposed machine learning model called DT-SVMNB is trained. Our model classifies users as depressed one or suicidal one in the social network. We have conducted an experiment of our model using synthetic and real datasets from social network. The performance analysis demonstrates around 98% accuracy which proves the effectiveness and efficiency of our proposed system. © 2021, The Author(s).
- Authors: Rahman, Md Shafiur , Halder, Sajal , Uddin, Ashraf , Acharjee, Uzzal
- Date: 2021
- Type: Text , Journal article
- Relation: Cybersecurity Vol. 4, no. 1 (2021), p.
- Full Text:
- Reviewed:
- Description: Anomaly detection has been an essential and dynamic research area in the data mining. A wide range of applications including different social medias have adopted different state-of-the-art methods to identify anomaly for ensuring user’s security and privacy. The social network refers to a forum used by different groups of people to express their thoughts, communicate with each other, and share the content needed. This social networks also facilitate abnormal activities, spread fake news, rumours, misinformation, unsolicited messages, and propaganda post malicious links. Therefore, detection of abnormalities is one of the important data analysis activities for the identification of normal or abnormal users on the social networks. In this paper, we have developed a hybrid anomaly detection method named DT-SVMNB that cascades several machine learning algorithms including decision tree (C5.0), Support Vector Machine (SVM) and Naïve Bayesian classifier (NBC) for classifying normal and abnormal users in social networks. We have extracted a list of unique features derived from users’ profile and contents. Using two kinds of dataset with the selected features, the proposed machine learning model called DT-SVMNB is trained. Our model classifies users as depressed one or suicidal one in the social network. We have conducted an experiment of our model using synthetic and real datasets from social network. The performance analysis demonstrates around 98% accuracy which proves the effectiveness and efficiency of our proposed system. © 2021, The Author(s).
The molecular epidemiology of influenza in Cambodia
- Authors: Suttie, Annika
- Date: 2019
- Type: Text , Thesis , PhD
- Full Text:
- Description: Avian influenza viruses (AIVs) represent a risk to the health of humans and animals. The prevalence of AIVs in live bird markets in Cambodia is among the highest in the world, being detected in 45.5% of tested poultry in 2015. To better understand the potential risk presented by AIVs, this thesis investigated the genetic characteristics of AIVs circulating in Cambodia between 2014 to 2018; focusing on subtypes that pose the greatest risk to human and animal health (H5, H7 and H9). Highly pathogenic (HP) H5N1 clade 2.3.2.1c viruses and low pathogenic H9N2 BJ/94-like h9-4.2.5 clade viruses were the most frequently detected subtypes, and circulate endemically in Cambodia’s domestic poultry. Co-infections were detected and facilitated the production of two novel reassortant H5N1 AIVs with single genes from H9N2 viruses. Additionally, numerous intrasubtypic reassortment events were detected for H5 and H9 AIVs. This is concerning as reassortment events can rapidly produce novel viruses of public health risk. Phylogenetic analyses showed some genes of the Cambodian H5, H7 and H9 AIVs clustered with zoonotic viruses, suggesting a common origin. There are parallels between H5N1 and H9N2 AIVs detected in Cambodia and Vietnam, likely facilitated through the illegal trade of live poultry and/or the migration of wild birds. Molecular analyses showed H9 AIVs have major markers associated with adaptation to mammals; though during the study period the only human AIV cases were the result of HP H5N1. Molecular markers of resistance to adamantine antivirals was observed in 3% of H5 and 41% of H9 AIVs; however, both subtypes remain susceptible to first line antiviral treatment, neuraminidase inhibitors. The data presented in this thesis demonstrates that circulation of Cambodian AIVs represents a risk for the emergence of novel viruses. Interventions are urgently needed to mitigate the threat posed to poultry and humans.
- Description: Doctor of Philosophy
- Authors: Suttie, Annika
- Date: 2019
- Type: Text , Thesis , PhD
- Full Text:
- Description: Avian influenza viruses (AIVs) represent a risk to the health of humans and animals. The prevalence of AIVs in live bird markets in Cambodia is among the highest in the world, being detected in 45.5% of tested poultry in 2015. To better understand the potential risk presented by AIVs, this thesis investigated the genetic characteristics of AIVs circulating in Cambodia between 2014 to 2018; focusing on subtypes that pose the greatest risk to human and animal health (H5, H7 and H9). Highly pathogenic (HP) H5N1 clade 2.3.2.1c viruses and low pathogenic H9N2 BJ/94-like h9-4.2.5 clade viruses were the most frequently detected subtypes, and circulate endemically in Cambodia’s domestic poultry. Co-infections were detected and facilitated the production of two novel reassortant H5N1 AIVs with single genes from H9N2 viruses. Additionally, numerous intrasubtypic reassortment events were detected for H5 and H9 AIVs. This is concerning as reassortment events can rapidly produce novel viruses of public health risk. Phylogenetic analyses showed some genes of the Cambodian H5, H7 and H9 AIVs clustered with zoonotic viruses, suggesting a common origin. There are parallels between H5N1 and H9N2 AIVs detected in Cambodia and Vietnam, likely facilitated through the illegal trade of live poultry and/or the migration of wild birds. Molecular analyses showed H9 AIVs have major markers associated with adaptation to mammals; though during the study period the only human AIV cases were the result of HP H5N1. Molecular markers of resistance to adamantine antivirals was observed in 3% of H5 and 41% of H9 AIVs; however, both subtypes remain susceptible to first line antiviral treatment, neuraminidase inhibitors. The data presented in this thesis demonstrates that circulation of Cambodian AIVs represents a risk for the emergence of novel viruses. Interventions are urgently needed to mitigate the threat posed to poultry and humans.
- Description: Doctor of Philosophy
Efficient data gathering in 3D linear underwater wireless sensor networks using sink mobility
- Akbar, Mariam, Javaid, Nadeem, Khan, Ayesha, Imran, Muhammad, Shoaib, Muhammad, Vasilakos, Athanasios
- Authors: Akbar, Mariam , Javaid, Nadeem , Khan, Ayesha , Imran, Muhammad , Shoaib, Muhammad , Vasilakos, Athanasios
- Date: 2016
- Type: Text , Journal article
- Relation: Sensors (Switzerland) Vol. 16, no. 3 (2016), p.
- Full Text:
- Reviewed:
- Description: Due to the unpleasant and unpredictable underwater environment, designing an energy-efficient routing protocol for underwater wireless sensor networks (UWSNs) demands more accuracy and extra computations. In the proposed scheme, we introduce a mobile sink (MS), i.e., an autonomous underwater vehicle (AUV), and also courier nodes (CNs), to minimize the energy consumption of nodes. MS and CNs stop at specific stops for data gathering; later on, CNs forward the received data to the MS for further transmission. By the mobility of CNs and MS, the overall energy consumption of nodes is minimized. We perform simulations to investigate the performance of the proposed scheme and compare it to preexisting techniques. Simulation results are compared in terms of network lifetime, throughput, path loss, transmission loss and packet drop ratio. The results show that the proposed technique performs better in terms of network lifetime, throughput, path loss and scalability. © 2016 by the authors; licensee MDPI, Basel, Switzerland.
- Authors: Akbar, Mariam , Javaid, Nadeem , Khan, Ayesha , Imran, Muhammad , Shoaib, Muhammad , Vasilakos, Athanasios
- Date: 2016
- Type: Text , Journal article
- Relation: Sensors (Switzerland) Vol. 16, no. 3 (2016), p.
- Full Text:
- Reviewed:
- Description: Due to the unpleasant and unpredictable underwater environment, designing an energy-efficient routing protocol for underwater wireless sensor networks (UWSNs) demands more accuracy and extra computations. In the proposed scheme, we introduce a mobile sink (MS), i.e., an autonomous underwater vehicle (AUV), and also courier nodes (CNs), to minimize the energy consumption of nodes. MS and CNs stop at specific stops for data gathering; later on, CNs forward the received data to the MS for further transmission. By the mobility of CNs and MS, the overall energy consumption of nodes is minimized. We perform simulations to investigate the performance of the proposed scheme and compare it to preexisting techniques. Simulation results are compared in terms of network lifetime, throughput, path loss, transmission loss and packet drop ratio. The results show that the proposed technique performs better in terms of network lifetime, throughput, path loss and scalability. © 2016 by the authors; licensee MDPI, Basel, Switzerland.
A patient agent controlled customized blockchain based framework for internet of things
- Authors: Uddin, Md Ashraf
- Date: 2021
- Type: Text , Thesis , PhD
- Full Text:
- Description: Although Blockchain implementations have emerged as revolutionary technologies for various industrial applications including cryptocurrencies, they have not been widely deployed to store data streaming from sensors to remote servers in architectures known as Internet of Things. New Blockchain for the Internet of Things models promise secure solutions for eHealth, smart cities, and other applications. These models pave the way for continuous monitoring of patient’s physiological signs with wearable sensors to augment traditional medical practice without recourse to storing data with a trusted authority. However, existing Blockchain algorithms cannot accommodate the huge volumes, security, and privacy requirements of health data. In this thesis, our first contribution is an End-to-End secure eHealth architecture that introduces an intelligent Patient Centric Agent. The Patient Centric Agent executing on dedicated hardware manages the storage and access of streams of sensors generated health data, into a customized Blockchain and other less secure repositories. As IoT devices cannot host Blockchain technology due to their limited memory, power, and computational resources, the Patient Centric Agent coordinates and communicates with a private customized Blockchain on behalf of the wearable devices. While the adoption of a Patient Centric Agent offers solutions for addressing continuous monitoring of patients’ health, dealing with storage, data privacy and network security issues, the architecture is vulnerable to Denial of Services(DoS) and single point of failure attacks. To address this issue, we advance a second contribution; a decentralised eHealth system in which the Patient Centric Agent is replicated at three levels: Sensing Layer, NEAR Processing Layer and FAR Processing Layer. The functionalities of the Patient Centric Agent are customized to manage the tasks of the three levels. Simulations confirm protection of the architecture against DoS attacks. Few patients require all their health data to be stored in Blockchain repositories but instead need to select an appropriate storage medium for each chunk of data by matching their personal needs and preferences with features of candidate storage mediums. Motivated by this context, we advance third contribution; a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The mapping between health data features and characteristics of each repository is learned using machine learning. The Blockchain’s capacity to make transactions and store records without central oversight enables its application for IoT networks outside health such as underwater IoT networks where the unattended nature of the nodes threatens their security and privacy. However, underwater IoT differs from ground IoT as acoustics signals are the communication media leading to high propagation delays, high error rates exacerbated by turbulent water currents. Our fourth contribution is a customized Blockchain leveraged framework with the model of Patient-Centric Agent renamed as Smart Agent for securely monitoring underwater IoT. Finally, the smart Agent has been investigated in developing an IoT smart home or cities monitoring framework. The key algorithms underpinning to each contribution have been implemented and analysed using simulators.
- Description: Doctor of Philosophy
- Authors: Uddin, Md Ashraf
- Date: 2021
- Type: Text , Thesis , PhD
- Full Text:
- Description: Although Blockchain implementations have emerged as revolutionary technologies for various industrial applications including cryptocurrencies, they have not been widely deployed to store data streaming from sensors to remote servers in architectures known as Internet of Things. New Blockchain for the Internet of Things models promise secure solutions for eHealth, smart cities, and other applications. These models pave the way for continuous monitoring of patient’s physiological signs with wearable sensors to augment traditional medical practice without recourse to storing data with a trusted authority. However, existing Blockchain algorithms cannot accommodate the huge volumes, security, and privacy requirements of health data. In this thesis, our first contribution is an End-to-End secure eHealth architecture that introduces an intelligent Patient Centric Agent. The Patient Centric Agent executing on dedicated hardware manages the storage and access of streams of sensors generated health data, into a customized Blockchain and other less secure repositories. As IoT devices cannot host Blockchain technology due to their limited memory, power, and computational resources, the Patient Centric Agent coordinates and communicates with a private customized Blockchain on behalf of the wearable devices. While the adoption of a Patient Centric Agent offers solutions for addressing continuous monitoring of patients’ health, dealing with storage, data privacy and network security issues, the architecture is vulnerable to Denial of Services(DoS) and single point of failure attacks. To address this issue, we advance a second contribution; a decentralised eHealth system in which the Patient Centric Agent is replicated at three levels: Sensing Layer, NEAR Processing Layer and FAR Processing Layer. The functionalities of the Patient Centric Agent are customized to manage the tasks of the three levels. Simulations confirm protection of the architecture against DoS attacks. Few patients require all their health data to be stored in Blockchain repositories but instead need to select an appropriate storage medium for each chunk of data by matching their personal needs and preferences with features of candidate storage mediums. Motivated by this context, we advance third contribution; a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The mapping between health data features and characteristics of each repository is learned using machine learning. The Blockchain’s capacity to make transactions and store records without central oversight enables its application for IoT networks outside health such as underwater IoT networks where the unattended nature of the nodes threatens their security and privacy. However, underwater IoT differs from ground IoT as acoustics signals are the communication media leading to high propagation delays, high error rates exacerbated by turbulent water currents. Our fourth contribution is a customized Blockchain leveraged framework with the model of Patient-Centric Agent renamed as Smart Agent for securely monitoring underwater IoT. Finally, the smart Agent has been investigated in developing an IoT smart home or cities monitoring framework. The key algorithms underpinning to each contribution have been implemented and analysed using simulators.
- Description: Doctor of Philosophy
Conical averagedness and convergence analysis of fixed point algorithms
- Bartz, Sedi, Dao, Minh, Phan, Hung
- Authors: Bartz, Sedi , Dao, Minh , Phan, Hung
- Date: 2022
- Type: Text , Journal article
- Relation: Journal of Global Optimization Vol. 82, no. 2 (2022), p. 351-373
- Full Text:
- Reviewed:
- Description: We study a conical extension of averaged nonexpansive operators and the role it plays in convergence analysis of fixed point algorithms. Various properties of conically averaged operators are systematically investigated, in particular, the stability under relaxations, convex combinations and compositions. We derive conical averagedness properties of resolvents of generalized monotone operators. These properties are then utilized in order to analyze the convergence of the proximal point algorithm, the forward–backward algorithm, and the adaptive Douglas–Rachford algorithm. Our study unifies, improves and casts new light on recent studies of these topics. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
- Authors: Bartz, Sedi , Dao, Minh , Phan, Hung
- Date: 2022
- Type: Text , Journal article
- Relation: Journal of Global Optimization Vol. 82, no. 2 (2022), p. 351-373
- Full Text:
- Reviewed:
- Description: We study a conical extension of averaged nonexpansive operators and the role it plays in convergence analysis of fixed point algorithms. Various properties of conically averaged operators are systematically investigated, in particular, the stability under relaxations, convex combinations and compositions. We derive conical averagedness properties of resolvents of generalized monotone operators. These properties are then utilized in order to analyze the convergence of the proximal point algorithm, the forward–backward algorithm, and the adaptive Douglas–Rachford algorithm. Our study unifies, improves and casts new light on recent studies of these topics. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Magic and antimagic labeling of graphs
- Authors: Sugeng, Kiki Ariyanti
- Date: 2005
- Type: Text , Thesis , PhD
- Full Text:
- Description: "A bijection mapping that assigns natural numbers to vertices and/or edges of a graph is called a labeling. In this thesis, we consider graph labelings that have weights associated with each edge and/or vertex. If all the vertex weights (respectively, edge weights) have the same value then the labeling is called magic. If the weight is different for every vertex (respectively, every edge) then we called the labeling antimagic. In this thesis we introduce some variations of magic and antimagic labelings and discuss their properties and provide corresponding labeling schemes. There are two main parts in this thesis. One main part is on vertex labeling and the other main part is on edge labeling."
- Description: Doctor of Philosophy
- Authors: Sugeng, Kiki Ariyanti
- Date: 2005
- Type: Text , Thesis , PhD
- Full Text:
- Description: "A bijection mapping that assigns natural numbers to vertices and/or edges of a graph is called a labeling. In this thesis, we consider graph labelings that have weights associated with each edge and/or vertex. If all the vertex weights (respectively, edge weights) have the same value then the labeling is called magic. If the weight is different for every vertex (respectively, every edge) then we called the labeling antimagic. In this thesis we introduce some variations of magic and antimagic labelings and discuss their properties and provide corresponding labeling schemes. There are two main parts in this thesis. One main part is on vertex labeling and the other main part is on edge labeling."
- Description: Doctor of Philosophy
Strongly regular points of mappings
- Abbasi, Malek, Théra, Michel
- Authors: Abbasi, Malek , Théra, Michel
- Date: 2021
- Type: Text , Journal article
- Relation: Fixed Point Theory and Algorithms for Sciences and Engineering Vol. 2021, no. 1 (Journal article 2021), p.
- Full Text:
- Reviewed:
- Description: In this paper, we use a robust lower directional derivative and provide some sufficient conditions to ensure the strong regularity of a given mapping at a certain point. Then, we discuss the Hoffman estimation and achieve some results for the estimate of the distance to the set of solutions to a system of linear equalities. The advantage of our estimate is that it allows one to calculate the coefficient of the error bound. © 2021, The Author(s).
- Authors: Abbasi, Malek , Théra, Michel
- Date: 2021
- Type: Text , Journal article
- Relation: Fixed Point Theory and Algorithms for Sciences and Engineering Vol. 2021, no. 1 (Journal article 2021), p.
- Full Text:
- Reviewed:
- Description: In this paper, we use a robust lower directional derivative and provide some sufficient conditions to ensure the strong regularity of a given mapping at a certain point. Then, we discuss the Hoffman estimation and achieve some results for the estimate of the distance to the set of solutions to a system of linear equalities. The advantage of our estimate is that it allows one to calculate the coefficient of the error bound. © 2021, The Author(s).
On graphs with cyclic defect or excess
- Delorme, Charles, Pineda-Villavicencio, Guillermo
- Authors: Delorme, Charles , Pineda-Villavicencio, Guillermo
- Date: 2010
- Type: Text , Journal article
- Relation: Electronic Journal of Combinatorics Vol. 17, no. 1 (2010), p.
- Full Text:
- Reviewed:
- Description: The Moore bound constitutes both an upper bound on the order of a graph of maximum degree d and diameter D = k and a lower bound on the order of a graph of minimum degree d and odd girth g = 2k + 1. Graphs missing or exceeding the Moore bound by ε are called graphs with defect or excess ε, respectively. While Moore graphs (graphs with ε = 0) and graphs with defect or excess 1 have been characterized almost completely, graphs with defect or excess 2 represent a wide unexplored area. Graphs with defect (excess) 2 satisfy the equation Gd,k(A) = Jn +B (Gd,k(A) = Jn - B), where A denotes the adjacency matrix of the graph in question, n its order, Jn the n × n matrix whose entries are all 1's, B the adjacency matrix of a union of vertex-disjoint cycles, and Gd,k(x) a polynomial with integer coefficients such that the matrix Gd,k(A) gives the number of paths of length at most k joining each pair of vertices in the graph. In particular, if B is the adjacency matrix of a cycle of order n we call the corresponding graphs graphs with cyclic defect or excess; these graphs are the subject of our attention in this paper. We prove the non-existence of infinitely many such graphs. As the highlight of the paper we provide the asymptotic upper bound of O(64/3 d3/2) for the number of graphs of odd degree d ≥ 3 and cyclic defect or excess. This bound is in fact quite generous, and as a way of illustration, we show the non-existence of some families of graphs of odd degree d ≥ 3 and cyclic defect or excess. Actually, we conjecture that, apart from the Möbius ladder on 8 vertices, no non-trivial graph of any degree ≥ 3 and cyclic defect or excess exists.
- Authors: Delorme, Charles , Pineda-Villavicencio, Guillermo
- Date: 2010
- Type: Text , Journal article
- Relation: Electronic Journal of Combinatorics Vol. 17, no. 1 (2010), p.
- Full Text:
- Reviewed:
- Description: The Moore bound constitutes both an upper bound on the order of a graph of maximum degree d and diameter D = k and a lower bound on the order of a graph of minimum degree d and odd girth g = 2k + 1. Graphs missing or exceeding the Moore bound by ε are called graphs with defect or excess ε, respectively. While Moore graphs (graphs with ε = 0) and graphs with defect or excess 1 have been characterized almost completely, graphs with defect or excess 2 represent a wide unexplored area. Graphs with defect (excess) 2 satisfy the equation Gd,k(A) = Jn +B (Gd,k(A) = Jn - B), where A denotes the adjacency matrix of the graph in question, n its order, Jn the n × n matrix whose entries are all 1's, B the adjacency matrix of a union of vertex-disjoint cycles, and Gd,k(x) a polynomial with integer coefficients such that the matrix Gd,k(A) gives the number of paths of length at most k joining each pair of vertices in the graph. In particular, if B is the adjacency matrix of a cycle of order n we call the corresponding graphs graphs with cyclic defect or excess; these graphs are the subject of our attention in this paper. We prove the non-existence of infinitely many such graphs. As the highlight of the paper we provide the asymptotic upper bound of O(64/3 d3/2) for the number of graphs of odd degree d ≥ 3 and cyclic defect or excess. This bound is in fact quite generous, and as a way of illustration, we show the non-existence of some families of graphs of odd degree d ≥ 3 and cyclic defect or excess. Actually, we conjecture that, apart from the Möbius ladder on 8 vertices, no non-trivial graph of any degree ≥ 3 and cyclic defect or excess exists.
Comparative analysis of machine and deep learning models for soil properties prediction from hyperspectral visual band
- Datta, Dristi, Paul, Manoranjan, Murshed, Manzur, Teng, Shyh Wei, Schmidtke, Leigh
- Authors: Datta, Dristi , Paul, Manoranjan , Murshed, Manzur , Teng, Shyh Wei , Schmidtke, Leigh
- Date: 2023
- Type: Text , Journal article
- Relation: Environments Vol. 10, no. 5 (2023), p. 77
- Full Text:
- Reviewed:
- Description: Estimating various properties of soil, including moisture, carbon, and nitrogen, is crucial for studying their correlation with plant health and food production. However, conventional methods such as oven-drying and chemical analysis are laborious, expensive, and only feasible for a limited land area. With the advent of remote sensing technologies like multi/hyperspectral imaging, it is now possible to predict soil properties non-invasive and cost-effectively for a large expanse of bare land. Recent research shows the possibility of predicting those soil contents from a wide range of hyperspectral data using good prediction algorithms. However, these kinds of hyperspectral sensors are expensive and not widely available. Therefore, this paper investigates different machine and deep learning techniques to predict soil nutrient properties using only the red (R), green (G), and blue (B) bands data to propose a suitable machine/deep learning model that can be used as a rapid soil test. Another objective of this research is to observe and compare the prediction accuracy in three cases i. hyperspectral band ii. full spectrum of the visual band, and iii. three-channel of RGB band and provide a guideline to the user on which spectrum information they should use to predict those soil properties. The outcome of this research helps to develop a mobile application that is easy to use for a quick soil test. This research also explores learning-based algorithms with significant feature combinations and their performance comparisons in predicting soil properties from visual band data. For this, we also explore the impact of dimensional reduction (i.e., principal component analysis) and transformations (i.e., empirical mode decomposition) of features. The results show that the proposed model can comparably predict the soil contents from the three-channel RGB data.
- Authors: Datta, Dristi , Paul, Manoranjan , Murshed, Manzur , Teng, Shyh Wei , Schmidtke, Leigh
- Date: 2023
- Type: Text , Journal article
- Relation: Environments Vol. 10, no. 5 (2023), p. 77
- Full Text:
- Reviewed:
- Description: Estimating various properties of soil, including moisture, carbon, and nitrogen, is crucial for studying their correlation with plant health and food production. However, conventional methods such as oven-drying and chemical analysis are laborious, expensive, and only feasible for a limited land area. With the advent of remote sensing technologies like multi/hyperspectral imaging, it is now possible to predict soil properties non-invasive and cost-effectively for a large expanse of bare land. Recent research shows the possibility of predicting those soil contents from a wide range of hyperspectral data using good prediction algorithms. However, these kinds of hyperspectral sensors are expensive and not widely available. Therefore, this paper investigates different machine and deep learning techniques to predict soil nutrient properties using only the red (R), green (G), and blue (B) bands data to propose a suitable machine/deep learning model that can be used as a rapid soil test. Another objective of this research is to observe and compare the prediction accuracy in three cases i. hyperspectral band ii. full spectrum of the visual band, and iii. three-channel of RGB band and provide a guideline to the user on which spectrum information they should use to predict those soil properties. The outcome of this research helps to develop a mobile application that is easy to use for a quick soil test. This research also explores learning-based algorithms with significant feature combinations and their performance comparisons in predicting soil properties from visual band data. For this, we also explore the impact of dimensional reduction (i.e., principal component analysis) and transformations (i.e., empirical mode decomposition) of features. The results show that the proposed model can comparably predict the soil contents from the three-channel RGB data.
Structural properties and labeling of graphs
- Dafik
- Authors: Dafik
- Date: 2007
- Type: Text , Thesis , PhD
- Full Text:
- Description: The complexity in building massive scale parallel processing systems has re- sulted in a growing interest in the study of interconnection networks design. Network design affects the performance, cost, scalability, and availability of parallel computers. Therefore, discovering a good structure of the network is one of the basic issues. From modeling point of view, the structure of networks can be naturally stud- ied in terms of graph theory. Several common desirable features of networks, such as large number of processing elements, good throughput, short data com- munication delay, modularity, good fault tolerance and diameter vulnerability correspond to properties of the underlying graphs of networks, including large number of vertices, small diameter, high connectivity and overall balance (or regularity) of the graph or digraph. The first part of this thesis deals with the issue of interconnection networks ad- dressing system. From graph theory point of view, this issue is mainly related to a graph labeling. We investigate a special family of graph labeling, namely antimagic labeling of a class of disconnected graphs. We present new results in super (a; d)-edge antimagic total labeling for disjoint union of multiple copies of special families of graphs. The second part of this thesis deals with the issue of regularity of digraphs with the number of vertices close to the upper bound, called the Moore bound, which is unobtainable for most values of out-degree and diameter. Regularity of the underlying graph of a network is often considered to be essential since the flow of messages and exchange of data between processing elements will be on average faster if there is a similar number of interconnections coming in and going out of each processing element. This means that the in-degree and out-degree of each processing element must be the same or almost the same. Our new results show that digraphs of order two less than Moore bound are either diregular or almost diregular.
- Description: Doctor of Philosophy
- Authors: Dafik
- Date: 2007
- Type: Text , Thesis , PhD
- Full Text:
- Description: The complexity in building massive scale parallel processing systems has re- sulted in a growing interest in the study of interconnection networks design. Network design affects the performance, cost, scalability, and availability of parallel computers. Therefore, discovering a good structure of the network is one of the basic issues. From modeling point of view, the structure of networks can be naturally stud- ied in terms of graph theory. Several common desirable features of networks, such as large number of processing elements, good throughput, short data com- munication delay, modularity, good fault tolerance and diameter vulnerability correspond to properties of the underlying graphs of networks, including large number of vertices, small diameter, high connectivity and overall balance (or regularity) of the graph or digraph. The first part of this thesis deals with the issue of interconnection networks ad- dressing system. From graph theory point of view, this issue is mainly related to a graph labeling. We investigate a special family of graph labeling, namely antimagic labeling of a class of disconnected graphs. We present new results in super (a; d)-edge antimagic total labeling for disjoint union of multiple copies of special families of graphs. The second part of this thesis deals with the issue of regularity of digraphs with the number of vertices close to the upper bound, called the Moore bound, which is unobtainable for most values of out-degree and diameter. Regularity of the underlying graph of a network is often considered to be essential since the flow of messages and exchange of data between processing elements will be on average faster if there is a similar number of interconnections coming in and going out of each processing element. This means that the in-degree and out-degree of each processing element must be the same or almost the same. Our new results show that digraphs of order two less than Moore bound are either diregular or almost diregular.
- Description: Doctor of Philosophy
Toxicity of opal Australian paper weak black liquors towards actinobacillus succinogenes 130Z
- Authors: Halder, Dibyadeep
- Date: 2022
- Type: Text , Thesis , Masters
- Full Text:
- Description: The objective of this study was to gain a better understanding of Opal Australian Paper’s (AP’s) waste streams as a potential substrate for biomanufacturing. Three low-value process streams were included in this study: Continuous Kraft Mill (CKM) weak black liquor (WBL), Neutral Sulphite Semi-Chemical (NSSC) WBL and WBL extracted from NSSC clean-pulp (CP). The primary focus of the study was to determine the chemical composition and extent of toxicity of these WBLs towards Actinobacillus succinogenes 130Z. This genetically engineered bacterium can produce a valuable platform chemical, succinic acid, using various carbohydrate sources. This project sought to increase knowledge of AP’s WBL and its suitability as a biomanufacturing substrate. Literature has been reviewed on various pre-treatment pathways for this waste stream, A. succinogenes 130Z and its effectiveness on producing succinic acid, and the analytical techniques that have been used to answer the project objectives. The effectiveness of pre-treating the NSSC and CP WBLs was measured using the following characteristics: (a) the colour content (specific absorbance) using UV-Vis spectroscopy, (b) indicative yields of several organic constituents through pyrolysis-gas chromatography-mass spectroscopy, (c) the atomic H/C and S/C ratios using an elemental analysis and (d) toxicity of the samples using a combination of semi-quantitative (plating trials) and quantitative (determination of minimum bactericidal concentration) techniques. The impact of an additional pre-treatment step of granular activated carbon for NSSC WBL was also researched here. InfraRed spectroscopy and toxicity analysis helped to conclude that CKM WBL is extremely toxic to Actinobacillus succinogenes 130Z and contained negligible amounts of residual sugar units. Characterising the NSSC and CP WBLs at the molecular level revealed the untreated WBLs are rich in lignin-derived methoxyphenols (up to 160 mg/kg) and contained low concentrations of elemental sulphur (up to approx. 1 mg/kg). Infra-red spectroscopy and gas chromatography indicated that the fermentable sugars in the WBLs were very low (< 1.2 mg/kg) even after pre-treatment. Both methoxyphenols and sulphur are known to be toxic to many bacteria and A. succinogenes 130Z could not tolerate more than 0.45 mg/ml (db, dry basis) and 0.78 mg/ml (db) of NSSC and CP WBLs respectively. Employing Amberlite® XAD7HP resins to pre-treat the NSSC and CP WBLs reduced their toxicity 2- to 5-fold, enabling the bacterium to survive in about 2.5 mg/ml (db) and 1 mg/ml (db) of NSSC and CP WBLs respectively. One possible reason for this is the significant reduction in lignin content afforded by this pre-treatment technique. These results conclude that AP’s WBLs are toxic and need to undergo pre-treatment prior to utilisation as a substrate for succinic acid production via fermentation.
- Description: Masters by Research
- Authors: Halder, Dibyadeep
- Date: 2022
- Type: Text , Thesis , Masters
- Full Text:
- Description: The objective of this study was to gain a better understanding of Opal Australian Paper’s (AP’s) waste streams as a potential substrate for biomanufacturing. Three low-value process streams were included in this study: Continuous Kraft Mill (CKM) weak black liquor (WBL), Neutral Sulphite Semi-Chemical (NSSC) WBL and WBL extracted from NSSC clean-pulp (CP). The primary focus of the study was to determine the chemical composition and extent of toxicity of these WBLs towards Actinobacillus succinogenes 130Z. This genetically engineered bacterium can produce a valuable platform chemical, succinic acid, using various carbohydrate sources. This project sought to increase knowledge of AP’s WBL and its suitability as a biomanufacturing substrate. Literature has been reviewed on various pre-treatment pathways for this waste stream, A. succinogenes 130Z and its effectiveness on producing succinic acid, and the analytical techniques that have been used to answer the project objectives. The effectiveness of pre-treating the NSSC and CP WBLs was measured using the following characteristics: (a) the colour content (specific absorbance) using UV-Vis spectroscopy, (b) indicative yields of several organic constituents through pyrolysis-gas chromatography-mass spectroscopy, (c) the atomic H/C and S/C ratios using an elemental analysis and (d) toxicity of the samples using a combination of semi-quantitative (plating trials) and quantitative (determination of minimum bactericidal concentration) techniques. The impact of an additional pre-treatment step of granular activated carbon for NSSC WBL was also researched here. InfraRed spectroscopy and toxicity analysis helped to conclude that CKM WBL is extremely toxic to Actinobacillus succinogenes 130Z and contained negligible amounts of residual sugar units. Characterising the NSSC and CP WBLs at the molecular level revealed the untreated WBLs are rich in lignin-derived methoxyphenols (up to 160 mg/kg) and contained low concentrations of elemental sulphur (up to approx. 1 mg/kg). Infra-red spectroscopy and gas chromatography indicated that the fermentable sugars in the WBLs were very low (< 1.2 mg/kg) even after pre-treatment. Both methoxyphenols and sulphur are known to be toxic to many bacteria and A. succinogenes 130Z could not tolerate more than 0.45 mg/ml (db, dry basis) and 0.78 mg/ml (db) of NSSC and CP WBLs respectively. Employing Amberlite® XAD7HP resins to pre-treat the NSSC and CP WBLs reduced their toxicity 2- to 5-fold, enabling the bacterium to survive in about 2.5 mg/ml (db) and 1 mg/ml (db) of NSSC and CP WBLs respectively. One possible reason for this is the significant reduction in lignin content afforded by this pre-treatment technique. These results conclude that AP’s WBLs are toxic and need to undergo pre-treatment prior to utilisation as a substrate for succinic acid production via fermentation.
- Description: Masters by Research
Does CD1a expression influence T cell function in patients with langerhans cell histiocytosis?
- Mitchell, Jenee, Kannourakis, George
- Authors: Mitchell, Jenee , Kannourakis, George
- Date: 2021
- Type: Text , Journal article
- Relation: Frontiers in Immunology Vol. 12, no. (2021), p.
- Full Text:
- Reviewed:
- Description: Langerhans cell histiocytosis lesions are characterized by CD1a+ myeloid lineage LCH cells and an inflammatory infiltrate of cytokines and immune cells, including T cells. T cells that recognize CD1a may be implicated in the pathology of many disease states including cancer and autoimmunity but have not been studied in the context of LCH despite the expression of CD1a by LCH cells. In this perspective article, we discuss the expression of CD1a by LCH cells, and we explore the potential for T cells that recognize CD1a to be involved in LCH pathogenesis. Copyright © 2021 Mitchell and Kannourakis.
- Authors: Mitchell, Jenee , Kannourakis, George
- Date: 2021
- Type: Text , Journal article
- Relation: Frontiers in Immunology Vol. 12, no. (2021), p.
- Full Text:
- Reviewed:
- Description: Langerhans cell histiocytosis lesions are characterized by CD1a+ myeloid lineage LCH cells and an inflammatory infiltrate of cytokines and immune cells, including T cells. T cells that recognize CD1a may be implicated in the pathology of many disease states including cancer and autoimmunity but have not been studied in the context of LCH despite the expression of CD1a by LCH cells. In this perspective article, we discuss the expression of CD1a by LCH cells, and we explore the potential for T cells that recognize CD1a to be involved in LCH pathogenesis. Copyright © 2021 Mitchell and Kannourakis.
Linkedness of cartesian products of complete graphs
- Jorgensen, Leif, Pineda-Villavicencio, Guillermo, Ugon, Julien
- Authors: Jorgensen, Leif , Pineda-Villavicencio, Guillermo , Ugon, Julien
- Date: 2022
- Type: Text , Journal article
- Relation: Ars Mathematica Contemporanea Vol. 22, no. 2 (2022), p.
- Relation: http://purl.org/au-research/grants/arc/DP180100602
- Full Text:
- Reviewed:
- Description: This paper is concerned with the linkedness of Cartesian products of complete graphs. A graph with at least 2k vertices is k-linked if, for every set of 2k distinct vertices organised in arbitrary k pairs of vertices, there are k vertex-disjoint paths joining the vertices in the pairs. We show that the Cartesian product Kd1+1 × Kd2+1 of complete graphs Kd1+1 and Kd2+1 is
- Authors: Jorgensen, Leif , Pineda-Villavicencio, Guillermo , Ugon, Julien
- Date: 2022
- Type: Text , Journal article
- Relation: Ars Mathematica Contemporanea Vol. 22, no. 2 (2022), p.
- Relation: http://purl.org/au-research/grants/arc/DP180100602
- Full Text:
- Reviewed:
- Description: This paper is concerned with the linkedness of Cartesian products of complete graphs. A graph with at least 2k vertices is k-linked if, for every set of 2k distinct vertices organised in arbitrary k pairs of vertices, there are k vertex-disjoint paths joining the vertices in the pairs. We show that the Cartesian product Kd1+1 × Kd2+1 of complete graphs Kd1+1 and Kd2+1 is
You Can’t Beat Relating with God for Spiritual Well-Being: Comparing a Generic Version with the Original Spiritual Well-Being Questionnaire Called SHALOM
- Authors: Fisher, John
- Date: 2013
- Type: Text , Journal article
- Relation: Religions Vol. 2013, no. 4 (2013), p. 325-335
- Full Text:
- Reviewed:
- Description: The Spiritual Health And Life-Orientation Measure (SHALOM) is a 20-item instrument that assesses the quality of relationships of the respondent with self, others, the environment and/or a Transcendent Other. In the Transcendental domain, four of the five items had the words ‘God, ‘Divine’ and ‘Creator’ replaced by the word ‘Transcendent’ to make the survey more generic by removing any implied reference to any god or religion. Invitations to complete a web survey were sent to people who had published papers in spirituality, or belonged to associations for spirituality or religious studies, as well as the Australian Atheist Forum. 409 respondents from 14 geographic regions, completed the survey. Confirmatory factor analysis revealed that the modified, generic form of SHALOM showed acceptable model fit, comprising four clearly delineated domains of spiritual well-being. The paper analyses the results derived from using the modified, generic version and, in comparison with results of applications of the original survey instrument, concludes with discussion of the comparative utility of each of the versions of SHALOM. Further studies with more people are warranted, but, from evidence presented here, it looks like you can’t beat relating with God for spiritual well-being.
- Authors: Fisher, John
- Date: 2013
- Type: Text , Journal article
- Relation: Religions Vol. 2013, no. 4 (2013), p. 325-335
- Full Text:
- Reviewed:
- Description: The Spiritual Health And Life-Orientation Measure (SHALOM) is a 20-item instrument that assesses the quality of relationships of the respondent with self, others, the environment and/or a Transcendent Other. In the Transcendental domain, four of the five items had the words ‘God, ‘Divine’ and ‘Creator’ replaced by the word ‘Transcendent’ to make the survey more generic by removing any implied reference to any god or religion. Invitations to complete a web survey were sent to people who had published papers in spirituality, or belonged to associations for spirituality or religious studies, as well as the Australian Atheist Forum. 409 respondents from 14 geographic regions, completed the survey. Confirmatory factor analysis revealed that the modified, generic form of SHALOM showed acceptable model fit, comprising four clearly delineated domains of spiritual well-being. The paper analyses the results derived from using the modified, generic version and, in comparison with results of applications of the original survey instrument, concludes with discussion of the comparative utility of each of the versions of SHALOM. Further studies with more people are warranted, but, from evidence presented here, it looks like you can’t beat relating with God for spiritual well-being.
New Farkas-type results for vector-valued functions : A non-abstract approach
- Dinh, Nguyen, Goberna, Miguel, Long, Dang, Lopez-Cerda, Marco
- Authors: Dinh, Nguyen , Goberna, Miguel , Long, Dang , Lopez-Cerda, Marco
- Date: 2019
- Type: Text , Journal article
- Relation: Journal of Optimization Theory and Applications Vol. 182, no. 1 (2019), p. 4-29
- Full Text:
- Reviewed:
- Description: This paper provides new Farkas-type results characterizing the inclusion of a given set, called contained set, into a second given set, called container set, both of them are subsets of some locally convex space, called decision space. The contained and the container sets are described here by means of vector functions from the decision space to other two locally convex spaces which are equipped with the partial ordering associated with given convex cones. These new Farkas lemmas are obtained via the complete characterization of the conic epigraphs of certain conjugate mappings which constitute the core of our approach. In contrast with a previous paper of three of the authors (Dinh et al. in J Optim Theory Appl 173:357-390, 2017), the aimed characterizations of the containment are expressed here in terms of the data.
- Authors: Dinh, Nguyen , Goberna, Miguel , Long, Dang , Lopez-Cerda, Marco
- Date: 2019
- Type: Text , Journal article
- Relation: Journal of Optimization Theory and Applications Vol. 182, no. 1 (2019), p. 4-29
- Full Text:
- Reviewed:
- Description: This paper provides new Farkas-type results characterizing the inclusion of a given set, called contained set, into a second given set, called container set, both of them are subsets of some locally convex space, called decision space. The contained and the container sets are described here by means of vector functions from the decision space to other two locally convex spaces which are equipped with the partial ordering associated with given convex cones. These new Farkas lemmas are obtained via the complete characterization of the conic epigraphs of certain conjugate mappings which constitute the core of our approach. In contrast with a previous paper of three of the authors (Dinh et al. in J Optim Theory Appl 173:357-390, 2017), the aimed characterizations of the containment are expressed here in terms of the data.
Post-modernism and witchcraft history
- Authors: Waldron, David
- Date: 2001
- Type: Text , Journal article
- Relation: The Pomegranate: Journal of Neo-Pagan Thought Vol. 15, no. 7 (2001), p. 16-22
- Full Text: false
- Reviewed:
- Description: C1
- Description: 2003003419