A new image dissimilarity measure incorporating human perception
- Shojanazeri, Hamid, Teng, Shyh, Aryal, Sunil, Zhang, Dengsheng, Lu, Guojun
- Authors: Shojanazeri, Hamid , Teng, Shyh , Aryal, Sunil , Zhang, Dengsheng , Lu, Guojun
- Date: 2018
- Type: Text , Unpublished work
- Full Text:
- Description: Pairwise (dis) similarity measure of data objects is central to many applications of image anlaytics, such as image retrieval and classification. Geometric distance, particularly Euclidean distance ((
- Authors: Shojanazeri, Hamid , Teng, Shyh , Aryal, Sunil , Zhang, Dengsheng , Lu, Guojun
- Date: 2018
- Type: Text , Unpublished work
- Full Text:
- Description: Pairwise (dis) similarity measure of data objects is central to many applications of image anlaytics, such as image retrieval and classification. Geometric distance, particularly Euclidean distance ((
A Hybrid data dependent dissimilarity measure for image retrieval
- Shojanazeri, Hamid, Teng, Shyh, Lu, Guojun
- Authors: Shojanazeri, Hamid , Teng, Shyh , Lu, Guojun
- Date: 2017
- Type: Text , Unpublished work
- Full Text:
- Description: Abstract— In image retrieval, an effective dissimilarity measure is required to retrieve the perceptually similar images. Minkowski-type (lp ) distance is widely used for image retrieval, however it has its limitations. It focuses on distance between image features and ignores the data distribution of the image features, which can play an important role in measuring perceptual similarity of images. !! also favours the most dominant components in calculating the total dissimilarity. A data dependent measure, named !! -dissimilarity, which estimates the dissimilarity using the data distribution, has been proposed recently. Rather than relying on geometric distance, it measures the dissimilarity between two instances in each dimension as a probability mass in a region that encloses the two instances. It considers two instances in a sparse region to be more similar than in a dense region. Using the probability of data mass enables all the dimensions of feature vectors to contribute in the final estimate of dissimilarity, so it does not just heavily bias towards the most dominant components. However, relying only on data distribution and completely ignoring the geometric distance raise another limitation. This can result in finding two instances similar only due to being in a sparse region, however if the geometric distance between them is large then they are not perceptually similar. To address this limitation we proposed a new hybrid data dependent dissimilarity (HDDD) measure that considers both data distribution as well as geometric distance. Our experimental results using Corel database and Caltech 101 show that (HDDD) leads to higher image retrieval performance than lp distance (lpD) and mp.
- Authors: Shojanazeri, Hamid , Teng, Shyh , Lu, Guojun
- Date: 2017
- Type: Text , Unpublished work
- Full Text:
- Description: Abstract— In image retrieval, an effective dissimilarity measure is required to retrieve the perceptually similar images. Minkowski-type (lp ) distance is widely used for image retrieval, however it has its limitations. It focuses on distance between image features and ignores the data distribution of the image features, which can play an important role in measuring perceptual similarity of images. !! also favours the most dominant components in calculating the total dissimilarity. A data dependent measure, named !! -dissimilarity, which estimates the dissimilarity using the data distribution, has been proposed recently. Rather than relying on geometric distance, it measures the dissimilarity between two instances in each dimension as a probability mass in a region that encloses the two instances. It considers two instances in a sparse region to be more similar than in a dense region. Using the probability of data mass enables all the dimensions of feature vectors to contribute in the final estimate of dissimilarity, so it does not just heavily bias towards the most dominant components. However, relying only on data distribution and completely ignoring the geometric distance raise another limitation. This can result in finding two instances similar only due to being in a sparse region, however if the geometric distance between them is large then they are not perceptually similar. To address this limitation we proposed a new hybrid data dependent dissimilarity (HDDD) measure that considers both data distribution as well as geometric distance. Our experimental results using Corel database and Caltech 101 show that (HDDD) leads to higher image retrieval performance than lp distance (lpD) and mp.
A new perceptual dissimilarity measure for image retrieval and clustering
- Authors: Shojanazeri, Hamid
- Date: 2018
- Type: Text , Thesis , PhD
- Full Text:
- Description: Image retrieval and clustering are two important tools for analysing and organising images. Dissimilarity measure is central to both image retrieval and clustering. The performance of image retrieval and clustering algorithms depends on the effectiveness of the dissimilarity measure. ‘Minkowski’ distance, or more specifically, ‘Euclidean’ distance, is the most widely used dissimilarity measure in image retrieval and clustering. Euclidean distance depends only on the geometric position of two data instances in the feature space and completely ignores the data distribution. However, data distribution has an effect on human perception. The argument that two data instances in a dense area are more perceptually dissimilar than the same two instances in a sparser area, is proposed by psychologists. Based on this idea, a dissimilarity measure called, ‘mp’, has been proposed to address Euclidean distance’s limitation of ignoring the data distribution. Here, mp relies on data distribution to calculate the dissimilarity between two instances. As prescribed in mp, higher data mass between two data instances implies higher dissimilarity, and vice versa. mp relies only on data distribution and completely ignores the geometric distance in its calculations. In the aggregation of dissimilarities between two instances over all the dimensions in feature space, both Euclidean distance and mp give same priority to all the dimensions. This may result in a situation that the final dissimilarity between two data instances is determined by a few dimensions of feature vectors with relatively much higher values. As a result, the dissimilarity derived may not align well with human perception. The need to address the limitations of Minkowski distance measures, along with the importance of a dissimilarity measure that considers both geometric distance and the perceptual effect of data distribution in measuring dissimilarity between images motivated this thesis. It studies the performance of mp for image retrieval. It investigates a new dissimilarity measure that combines both Euclidean distance and data distribution. In addition to these, it studies the performance of such a dissimilarity measure for image retrieval and clustering. Our performance study of mp for image retrieval shows that relying only on data distribution to measure the dissimilarity results in some situations, where the mp’s measurement is contrary to human perception. This thesis introduces a new dissimilarity measure called, perceptual dissimilarity measure (PDM). PDM considers the perceptual effect of data distribution in combination with Euclidean distance. PDM has two variants, PDM1 and PDM2. PDM1 focuses on improving mp by weighting it using Euclidean distance in situations where mp may not retrieve accurate results. PDM2 considers the effect of data distribution on the perceived dissimilarity measured by Euclidean distance. PDM2 proposes a weighting system for Euclidean distance using a logarithmic transform of data mass. The proposed PDM variants have been used as alternatives to Euclidean distance and mp to improve the accuracy in image retrieval. Our results show that PDM2 has consistently performed the best, compared to Euclidean distance, mp and PDM1. PDM1’s performance was not consistent, although it has performed better than mp in all the experiments, but it could not outperform Euclidean distance in some cases. Following the promising results of PDM2 in image retrieval, we have studied its performance for image clustering. k-means is the most widely used clustering algorithm in scientific and industrial applications. k-medoids is the closest clustering algorithm to k-means. Unlike k-means which works only with Euclidean distance, k-medoids gives the option to choose the arbitrary dissimilarity measure. We have used Euclidean distance, mp and PDM2 as the dissimilarity measure in k-medoids and compared the results with k-means. Our clustering results show that PDM2 has perfromed overally the best. This confirms our retrieval results and identifies PDM2 as a suitable dissimilarity measure for image retrieval and clustering.
- Description: Doctor of Philosophy
- Authors: Shojanazeri, Hamid
- Date: 2018
- Type: Text , Thesis , PhD
- Full Text:
- Description: Image retrieval and clustering are two important tools for analysing and organising images. Dissimilarity measure is central to both image retrieval and clustering. The performance of image retrieval and clustering algorithms depends on the effectiveness of the dissimilarity measure. ‘Minkowski’ distance, or more specifically, ‘Euclidean’ distance, is the most widely used dissimilarity measure in image retrieval and clustering. Euclidean distance depends only on the geometric position of two data instances in the feature space and completely ignores the data distribution. However, data distribution has an effect on human perception. The argument that two data instances in a dense area are more perceptually dissimilar than the same two instances in a sparser area, is proposed by psychologists. Based on this idea, a dissimilarity measure called, ‘mp’, has been proposed to address Euclidean distance’s limitation of ignoring the data distribution. Here, mp relies on data distribution to calculate the dissimilarity between two instances. As prescribed in mp, higher data mass between two data instances implies higher dissimilarity, and vice versa. mp relies only on data distribution and completely ignores the geometric distance in its calculations. In the aggregation of dissimilarities between two instances over all the dimensions in feature space, both Euclidean distance and mp give same priority to all the dimensions. This may result in a situation that the final dissimilarity between two data instances is determined by a few dimensions of feature vectors with relatively much higher values. As a result, the dissimilarity derived may not align well with human perception. The need to address the limitations of Minkowski distance measures, along with the importance of a dissimilarity measure that considers both geometric distance and the perceptual effect of data distribution in measuring dissimilarity between images motivated this thesis. It studies the performance of mp for image retrieval. It investigates a new dissimilarity measure that combines both Euclidean distance and data distribution. In addition to these, it studies the performance of such a dissimilarity measure for image retrieval and clustering. Our performance study of mp for image retrieval shows that relying only on data distribution to measure the dissimilarity results in some situations, where the mp’s measurement is contrary to human perception. This thesis introduces a new dissimilarity measure called, perceptual dissimilarity measure (PDM). PDM considers the perceptual effect of data distribution in combination with Euclidean distance. PDM has two variants, PDM1 and PDM2. PDM1 focuses on improving mp by weighting it using Euclidean distance in situations where mp may not retrieve accurate results. PDM2 considers the effect of data distribution on the perceived dissimilarity measured by Euclidean distance. PDM2 proposes a weighting system for Euclidean distance using a logarithmic transform of data mass. The proposed PDM variants have been used as alternatives to Euclidean distance and mp to improve the accuracy in image retrieval. Our results show that PDM2 has consistently performed the best, compared to Euclidean distance, mp and PDM1. PDM1’s performance was not consistent, although it has performed better than mp in all the experiments, but it could not outperform Euclidean distance in some cases. Following the promising results of PDM2 in image retrieval, we have studied its performance for image clustering. k-means is the most widely used clustering algorithm in scientific and industrial applications. k-medoids is the closest clustering algorithm to k-means. Unlike k-means which works only with Euclidean distance, k-medoids gives the option to choose the arbitrary dissimilarity measure. We have used Euclidean distance, mp and PDM2 as the dissimilarity measure in k-medoids and compared the results with k-means. Our clustering results show that PDM2 has perfromed overally the best. This confirms our retrieval results and identifies PDM2 as a suitable dissimilarity measure for image retrieval and clustering.
- Description: Doctor of Philosophy
Ahliat va Masir (roots and routes) : Narratives of identity and adaptation from Persian Baha'i refugees in Australia
- Authors: Williams, Ruth
- Date: 2008
- Type: Text , Thesis , PhD
- Full Text:
- Description: This study aims to discover what oral history narratives reveal about the post-migration renegotiation of identity for seven Persian Baha'i refugees and to assess the ensuing impact on their adaptation to Australia.
- Description: Doctor of Philosophy
- Authors: Williams, Ruth
- Date: 2008
- Type: Text , Thesis , PhD
- Full Text:
- Description: This study aims to discover what oral history narratives reveal about the post-migration renegotiation of identity for seven Persian Baha'i refugees and to assess the ensuing impact on their adaptation to Australia.
- Description: Doctor of Philosophy
- 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.
Using activity theory to understand the impact of social networking sites and apps use by Saudi postgraduate students
- Alghamdi, Abdulelah, Plunkett, Margaret
- Authors: Alghamdi, Abdulelah , Plunkett, Margaret
- Date: 2022
- Type: Text , Journal article
- Relation: Behaviour and Information Technology Vol. 41, no. 6 (2022), p. 1298-1312
- Full Text:
- Reviewed:
- Description: Social networking sites and apps (SNSAs) are being used more frequently across the world and yet the nature of this online environment and associated interactions are not fully understood. With no restrictions for SNSAs use related to specific geographical regions, language, age, gender, educational level, or any other factors, it is important to find a concept to describe and explain the components of this online environment and their relationships. This paper describes the environment of SNSAs use by Saudi postgraduate students from the perspective of second-generation activity theory (AT). The findings supported the theoretical framework of AT as a useful lens in understanding SNSAs use from the perspective of students, particularly in a cultural environment where physical communication has restrictions based on gender. A similar AT model can be drawn for the use of SNSAs, taking the perspective of different groups of academic users. The flexibility of the AT model appears at the level of SNSAs as technical and physical tools, and at the level of users’ community, which was managed by the explicit and implicit rules relating to communication. This feature reveals the way in which this extended framework can be used to indicate pertinent features of SNSAs. © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
- Authors: Alghamdi, Abdulelah , Plunkett, Margaret
- Date: 2022
- Type: Text , Journal article
- Relation: Behaviour and Information Technology Vol. 41, no. 6 (2022), p. 1298-1312
- Full Text:
- Reviewed:
- Description: Social networking sites and apps (SNSAs) are being used more frequently across the world and yet the nature of this online environment and associated interactions are not fully understood. With no restrictions for SNSAs use related to specific geographical regions, language, age, gender, educational level, or any other factors, it is important to find a concept to describe and explain the components of this online environment and their relationships. This paper describes the environment of SNSAs use by Saudi postgraduate students from the perspective of second-generation activity theory (AT). The findings supported the theoretical framework of AT as a useful lens in understanding SNSAs use from the perspective of students, particularly in a cultural environment where physical communication has restrictions based on gender. A similar AT model can be drawn for the use of SNSAs, taking the perspective of different groups of academic users. The flexibility of the AT model appears at the level of SNSAs as technical and physical tools, and at the level of users’ community, which was managed by the explicit and implicit rules relating to communication. This feature reveals the way in which this extended framework can be used to indicate pertinent features of SNSAs. © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
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.
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
Performance assessment of a solar dryer system using small parabolic dish and alumina/oil nanofluid : simulation and experimental study
- Arkian, Amir, Najafi, Gholamhassan, Gorjian, Shiva, Loni, Reyhaneh, Bellos, Evangelos, Yusaf, Talal
- Authors: Arkian, Amir , Najafi, Gholamhassan , Gorjian, Shiva , Loni, Reyhaneh , Bellos, Evangelos , Yusaf, Talal
- Date: 2019
- Type: Text , Journal article
- Relation: Energies Vol. 12, no. 24 (Dec 2019), p. 22
- Full Text:
- Reviewed:
- Description: In this study, a small dish concentrator with a cylindrical cavity receiver was experimentally investigated as the heat source of a dryer. The system was examined for operation with pure thermal oil and Al2O3/oil nanofluid as the working fluids in the solar system. Moreover, the design, the development, and the evaluation of the dried mint plant are presented in this work. Also, the solar dryer system was simulated by the SolidWorks and ANSYS CFX software. On the other side, the color histogram of the wet and dried mint samples based on the RGB method was considered. The results revealed that the different temperatures of the solar working fluids at the inlet and outlet of the cavity receiver showed similar trend data compared to the variation of the solar radiation during the experimental test. Moreover, it is found that the cavity heat gain and thermal efficiency of the solar system was improved by using the nanofluid as the solar working fluid. Furthermore, the required time for mint drying had decreased by increasing the drying temperature and increasing air speed. The highest drying time was measured equal to 320 min for the condition of the air speed equal to 0.5 m/s and the drying temperature of 30 degrees C. A good agreement was observed between the calculated numerical results and measured experimental data. Finally, based on the color histogram of the wet and dried mint samples, it was concluded that intensity amount of the red color of the mint increased with the drying process compared to intensity amount of the red color of the wet mint sample.
- Authors: Arkian, Amir , Najafi, Gholamhassan , Gorjian, Shiva , Loni, Reyhaneh , Bellos, Evangelos , Yusaf, Talal
- Date: 2019
- Type: Text , Journal article
- Relation: Energies Vol. 12, no. 24 (Dec 2019), p. 22
- Full Text:
- Reviewed:
- Description: In this study, a small dish concentrator with a cylindrical cavity receiver was experimentally investigated as the heat source of a dryer. The system was examined for operation with pure thermal oil and Al2O3/oil nanofluid as the working fluids in the solar system. Moreover, the design, the development, and the evaluation of the dried mint plant are presented in this work. Also, the solar dryer system was simulated by the SolidWorks and ANSYS CFX software. On the other side, the color histogram of the wet and dried mint samples based on the RGB method was considered. The results revealed that the different temperatures of the solar working fluids at the inlet and outlet of the cavity receiver showed similar trend data compared to the variation of the solar radiation during the experimental test. Moreover, it is found that the cavity heat gain and thermal efficiency of the solar system was improved by using the nanofluid as the solar working fluid. Furthermore, the required time for mint drying had decreased by increasing the drying temperature and increasing air speed. The highest drying time was measured equal to 320 min for the condition of the air speed equal to 0.5 m/s and the drying temperature of 30 degrees C. A good agreement was observed between the calculated numerical results and measured experimental data. Finally, based on the color histogram of the wet and dried mint samples, it was concluded that intensity amount of the red color of the mint increased with the drying process compared to intensity amount of the red color of the wet mint sample.
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).
Divergent SATB1 expression across human life span and tissue compartments
- Nüssing, Simone, Koay, Hui-Fern, Sant, Sneha, Loudovaris, Thomas, Mannering, Stuart, Lappas, Martha, d′Udekem, Yves, Konstantinov, Igor, Berzins, Stuart, Rimmelzwaan, Guus, Turner, Stephen, Clemens, Bridie, Godfrey, Dale, Nguyen, Thi, Kedzierska, Katherine
- Authors: Nüssing, Simone , Koay, Hui-Fern , Sant, Sneha , Loudovaris, Thomas , Mannering, Stuart , Lappas, Martha , d′Udekem, Yves , Konstantinov, Igor , Berzins, Stuart , Rimmelzwaan, Guus , Turner, Stephen , Clemens, Bridie , Godfrey, Dale , Nguyen, Thi , Kedzierska, Katherine
- Date: 2019
- Type: Text , Journal article
- Relation: Immunology and Cell Biology Vol. 97, no. (2019), p. 498-511
- Full Text:
- Reviewed:
- Description: Special AT-rich binding protein-1 (SATB1) is a global chromatin organizer capable of activating or repressing gene transcription in mice and humans. The role of SATB1 is pivotal for T-cell development, with SATB1-knockout mice being neonatally lethal, although the exact mechanism is unknown. Moreover, SATB1 is dysregulated in T-cell lymphoma and proposed to suppress transcription of the Pdcd1 gene, encoding the immune checkpoint programmed cell death protein 1 (PD-1). Thus, SATB1 expression in T-cell subsets across different tissue compartments in humans is of potential importance for targeting PD-1. Here, we comprehensively analyzed SATB1 expression across different human tissues and immune compartments by flow cytometry and correlated this with PD-1 expression. We investigated SATB1 protein levels in pediatric and adult donors and assessed expression dynamics of this chromatin organizer across different immune cell subsets in human organs, as well as in antigen-specific T cells directed against acute and chronic viral infections. Our data demonstrate that SATB1 expression in humans is the highest in T-cell progenitors in the thymus, and then becomes downregulated in mature T cells in the periphery. Importantly, SATB1 expression in peripheral mature T cells is not static and follows fine-tuned expression dynamics, which appear to be tissue- and antigen-dependent. Furthermore, SATB1 expression negatively correlates with PD-1 expression in virus-specific CD8 + T cells. Our study has implications for understanding the role of SATB1 in human health and disease and suggests an approach for modulating PD-1 in T cells, highly relevant to human malignancies or chronic viral infections.
- Authors: Nüssing, Simone , Koay, Hui-Fern , Sant, Sneha , Loudovaris, Thomas , Mannering, Stuart , Lappas, Martha , d′Udekem, Yves , Konstantinov, Igor , Berzins, Stuart , Rimmelzwaan, Guus , Turner, Stephen , Clemens, Bridie , Godfrey, Dale , Nguyen, Thi , Kedzierska, Katherine
- Date: 2019
- Type: Text , Journal article
- Relation: Immunology and Cell Biology Vol. 97, no. (2019), p. 498-511
- Full Text:
- Reviewed:
- Description: Special AT-rich binding protein-1 (SATB1) is a global chromatin organizer capable of activating or repressing gene transcription in mice and humans. The role of SATB1 is pivotal for T-cell development, with SATB1-knockout mice being neonatally lethal, although the exact mechanism is unknown. Moreover, SATB1 is dysregulated in T-cell lymphoma and proposed to suppress transcription of the Pdcd1 gene, encoding the immune checkpoint programmed cell death protein 1 (PD-1). Thus, SATB1 expression in T-cell subsets across different tissue compartments in humans is of potential importance for targeting PD-1. Here, we comprehensively analyzed SATB1 expression across different human tissues and immune compartments by flow cytometry and correlated this with PD-1 expression. We investigated SATB1 protein levels in pediatric and adult donors and assessed expression dynamics of this chromatin organizer across different immune cell subsets in human organs, as well as in antigen-specific T cells directed against acute and chronic viral infections. Our data demonstrate that SATB1 expression in humans is the highest in T-cell progenitors in the thymus, and then becomes downregulated in mature T cells in the periphery. Importantly, SATB1 expression in peripheral mature T cells is not static and follows fine-tuned expression dynamics, which appear to be tissue- and antigen-dependent. Furthermore, SATB1 expression negatively correlates with PD-1 expression in virus-specific CD8 + T cells. Our study has implications for understanding the role of SATB1 in human health and disease and suggests an approach for modulating PD-1 in T cells, highly relevant to human malignancies or chronic viral infections.
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
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- 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.
Study on the tribological characteristics of plant oil-based bio-lubricant with automotive liner-piston ring materials
- Shahabuddin, M., Mofijur, M., Rizwanul Fattah, I. M., Kalam, M. A., Masjuki, H. H., Chowdhury, M. A., Hossain, N.
- Authors: Shahabuddin, M. , Mofijur, M. , Rizwanul Fattah, I. M. , Kalam, M. A. , Masjuki, H. H. , Chowdhury, M. A. , Hossain, N.
- Date: 2022
- Type: Text , Journal article
- Relation: Current Research in Green and Sustainable Chemistry Vol. 5, no. (2022), p.
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- Description: The development of bio-lubricant is an immerging area of research considering the rapid depletion of petroleum reserve and environmental concern. This study aims to develop non-edible jatropha oil-based bio-lubricant and investigate the tribological properties considering commonly used piston ring-cylinder liner materials of stainless steel and cast iron due to their interaction under lubricated conditions in an internal combustion engine. The bio-lubricant was prepared by blending different percentages of vegetable oil with commercial lubricants. The tribological test was carried out using a Reo-Bicerihigh-frequency reciprocating rig (HFRR) for the duration of 6 h under standard operating conditions. Different properties of bio-lubricants were measured before and after the HFRR test using various analytical instruments. The morphology of the worn material surfaces was examined via Hitachi S-4700 FE-SEM cold field emission high resolution scanning electron microscopy (SEM). The result showed that addition of vegetable oil lubricant up to 7.5% concentration can be compared with commercial lubricant in case of wear rate and coefficient of wear as weight loss reduced significantly. Minimum change in viscosity was observed at the addition of 7.5% bio-lubricant. Surface morphology analysis confirmed less damage of metal surface when tribological analysis were performed at mixed lubricated condition. © 2022 The Authors
- Authors: Shahabuddin, M. , Mofijur, M. , Rizwanul Fattah, I. M. , Kalam, M. A. , Masjuki, H. H. , Chowdhury, M. A. , Hossain, N.
- Date: 2022
- Type: Text , Journal article
- Relation: Current Research in Green and Sustainable Chemistry Vol. 5, no. (2022), p.
- Full Text:
- Reviewed:
- Description: The development of bio-lubricant is an immerging area of research considering the rapid depletion of petroleum reserve and environmental concern. This study aims to develop non-edible jatropha oil-based bio-lubricant and investigate the tribological properties considering commonly used piston ring-cylinder liner materials of stainless steel and cast iron due to their interaction under lubricated conditions in an internal combustion engine. The bio-lubricant was prepared by blending different percentages of vegetable oil with commercial lubricants. The tribological test was carried out using a Reo-Bicerihigh-frequency reciprocating rig (HFRR) for the duration of 6 h under standard operating conditions. Different properties of bio-lubricants were measured before and after the HFRR test using various analytical instruments. The morphology of the worn material surfaces was examined via Hitachi S-4700 FE-SEM cold field emission high resolution scanning electron microscopy (SEM). The result showed that addition of vegetable oil lubricant up to 7.5% concentration can be compared with commercial lubricant in case of wear rate and coefficient of wear as weight loss reduced significantly. Minimum change in viscosity was observed at the addition of 7.5% bio-lubricant. Surface morphology analysis confirmed less damage of metal surface when tribological analysis were performed at mixed lubricated condition. © 2022 The Authors
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
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
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- 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
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- 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.