Optimality conditions for nonsmooth optimization problems via generalised derivatives
- Authors: Hassani, Sara
- Date: 2016
- Type: Text , Thesis , PhD
- Full Text:
- Description: Aquatic plants are integral components of freshwater ecosystems and provide essential ecosystem services. However, when invasive species establish in new aquatic environments, there are few natural checks and balances to inhibit their growth and spread. Overabundant aquatic vegetation can harm aquatic systems if left unchecked and negatively impact on agricultural productivity, social amenity and biodiversity values. Prevention and early intervention are recognised as the most cost effective means to manage invasive species that pose a biosecurity risk. This thesis contributes to the development of effective management strategies for one of the world’s most invasive aquatic plant species, known as alligator weed (Alternanthera philoxeroides (Mart.) Griseb.). It focusses on developing management strategies in an early stage of invasion, in order to achieve extirpation of this species from catchments and waterways. Developing effective detection and surveillance strategies are required for invasive aquatic plants, as a key impediment to achieving extirpation is the ability to detect infestations, so that control strategies can be enacted. This thesis investigates the effectiveness of aerial surveillance for detection of alligator weed at different spatial scales, using high altitude aerial imagery (orthophotos) and unmanned aerial vehicle (UAV) technology. An examination of the growth rate of alligator weed in Victoria, Australia, over a five year period, demonstrates the effective use of orthophotos to detect and monitor large infestations of aquatic alligator weed. The efficacy of unmanned aerial vehicle technology, including the use of automated algorithms, to detect patches of alligator weed growing in waterways is evaluated against current detection techniques. Effective management of invasive aquatic plants targeted for extirpation requires the coupling of effective detection and control efforts to prevent reproduction. To date, development of control strategies for aquatic alligator weed has been limited to evaluating the efficacy of short-term control at a local scale without regard to the effects of management strategies on dispersal of propagules throughout catchments. This thesis determines that viable alligator weed stem fragments are produced following herbicide application, which comprises extirpation efforts. This thesis has gone further than current practice in that it has evaluated the efficacy of current and novel control techniques, in both laboratory and field trials and has developed methods to manage viable fragment production post-herbicide application, to limit dispersal throughout catchments. In this respect, the application of the herbicides glyphosate, metsulfuron-methyl and imazapyr, and their effectiveness when incorporating surfactant systems and plant growth regulators, have been evaluated in field and laboratory studies to optimise control techniques for aquatic alligator weed. Results have shown that our approaches, when used in an early stage of invasion, are capable of eliminating patches of alligator weed in two to three years. Integral to the research is an experiment to determine the effect of herbicide treatments on the production of alligator weed stem fragments and their subsequent viability. Further investigation to determine the usefulness of commercially available plant growth regulators (PGRs) to reduce the number of viable propagules produced by alligator weed post-herbicide application was found to be ineffective. This thesis also evaluates the impact of herbicides and surfactant systems, on all key alligator weed response metrics in aquatic environments including; above ground biomass, below ground biomass and viable stem fragmentation. No previous studies have looked simultaneously at these three important measures for determining the efficacy of a particular control regime, and we have determined that this is essential for effective management of aquatic alligator weed in an early stage of invasion. The thesis has underscored the notion that development of more effective management strategies, based upon experimental trials, will result in an increased likelihood of eradicating invasive aquatic plants that pose a biosecurity risk, and thus move toward the mitigation of the threat that high-risk species pose to aquatic ecosystems. PLEASE NOTE: Portions of the full text have been removed due to copyright restrictions.
- Description: Doctor of Philosophy
- Authors: Hassani, Sara
- Date: 2016
- Type: Text , Thesis , PhD
- Full Text:
- Description: Aquatic plants are integral components of freshwater ecosystems and provide essential ecosystem services. However, when invasive species establish in new aquatic environments, there are few natural checks and balances to inhibit their growth and spread. Overabundant aquatic vegetation can harm aquatic systems if left unchecked and negatively impact on agricultural productivity, social amenity and biodiversity values. Prevention and early intervention are recognised as the most cost effective means to manage invasive species that pose a biosecurity risk. This thesis contributes to the development of effective management strategies for one of the world’s most invasive aquatic plant species, known as alligator weed (Alternanthera philoxeroides (Mart.) Griseb.). It focusses on developing management strategies in an early stage of invasion, in order to achieve extirpation of this species from catchments and waterways. Developing effective detection and surveillance strategies are required for invasive aquatic plants, as a key impediment to achieving extirpation is the ability to detect infestations, so that control strategies can be enacted. This thesis investigates the effectiveness of aerial surveillance for detection of alligator weed at different spatial scales, using high altitude aerial imagery (orthophotos) and unmanned aerial vehicle (UAV) technology. An examination of the growth rate of alligator weed in Victoria, Australia, over a five year period, demonstrates the effective use of orthophotos to detect and monitor large infestations of aquatic alligator weed. The efficacy of unmanned aerial vehicle technology, including the use of automated algorithms, to detect patches of alligator weed growing in waterways is evaluated against current detection techniques. Effective management of invasive aquatic plants targeted for extirpation requires the coupling of effective detection and control efforts to prevent reproduction. To date, development of control strategies for aquatic alligator weed has been limited to evaluating the efficacy of short-term control at a local scale without regard to the effects of management strategies on dispersal of propagules throughout catchments. This thesis determines that viable alligator weed stem fragments are produced following herbicide application, which comprises extirpation efforts. This thesis has gone further than current practice in that it has evaluated the efficacy of current and novel control techniques, in both laboratory and field trials and has developed methods to manage viable fragment production post-herbicide application, to limit dispersal throughout catchments. In this respect, the application of the herbicides glyphosate, metsulfuron-methyl and imazapyr, and their effectiveness when incorporating surfactant systems and plant growth regulators, have been evaluated in field and laboratory studies to optimise control techniques for aquatic alligator weed. Results have shown that our approaches, when used in an early stage of invasion, are capable of eliminating patches of alligator weed in two to three years. Integral to the research is an experiment to determine the effect of herbicide treatments on the production of alligator weed stem fragments and their subsequent viability. Further investigation to determine the usefulness of commercially available plant growth regulators (PGRs) to reduce the number of viable propagules produced by alligator weed post-herbicide application was found to be ineffective. This thesis also evaluates the impact of herbicides and surfactant systems, on all key alligator weed response metrics in aquatic environments including; above ground biomass, below ground biomass and viable stem fragmentation. No previous studies have looked simultaneously at these three important measures for determining the efficacy of a particular control regime, and we have determined that this is essential for effective management of aquatic alligator weed in an early stage of invasion. The thesis has underscored the notion that development of more effective management strategies, based upon experimental trials, will result in an increased likelihood of eradicating invasive aquatic plants that pose a biosecurity risk, and thus move toward the mitigation of the threat that high-risk species pose to aquatic ecosystems. PLEASE NOTE: Portions of the full text have been removed due to copyright restrictions.
- Description: Doctor of Philosophy
Characterizations of minimal elements of topical functions on semimodules with applications
- Hassani, Sara, Mohebi, Hossein
- Authors: Hassani, Sara , Mohebi, Hossein
- Date: 2017
- Type: Text , Journal article
- Relation: Linear Algebra and Its Applications Vol. 520, no. (2017), p. 104-124
- Full Text:
- Reviewed:
- Description: In this paper, we first give characterizations of the superdifferential of extended valued topical functions defined on a semimodule with values in a semifield. Next, we characterize minimal elements of the upper support set of extended valued topical functions. Finally, as an application, we present a necessary and sufficient condition for global maximum of the difference of two strictly topical functions defined on a semimodule. (C) 2017 Elsevier Inc. All rights reserved.
- Authors: Hassani, Sara , Mohebi, Hossein
- Date: 2017
- Type: Text , Journal article
- Relation: Linear Algebra and Its Applications Vol. 520, no. (2017), p. 104-124
- Full Text:
- Reviewed:
- Description: In this paper, we first give characterizations of the superdifferential of extended valued topical functions defined on a semimodule with values in a semifield. Next, we characterize minimal elements of the upper support set of extended valued topical functions. Finally, as an application, we present a necessary and sufficient condition for global maximum of the difference of two strictly topical functions defined on a semimodule. (C) 2017 Elsevier Inc. All rights reserved.
Nonsmooth optimization models and algorithms for data clustering and visualization
- Authors: Mohebi, Ehsan
- Date: 2015
- Type: Text , Thesis
- Full Text:
- Description: Cluster analysis deals with the problem of organization of a collection of patterns into clusters based on a similarity measure. Various distance functions can be used to define this measure. Clustering problems with the similarity measure defined by the squared Euclidean distance have been studied extensively over the last five decades. However, problems with other Minkowski norms have attracted significantly less attention. The use of different similarity measures may help to identify different cluster structures of a data set. This in turn may help to significantly improve the decision making process. High dimensional data visualization is another important task in the field of data mining and pattern recognition. To date, the principal component analysis and the self-organizing maps techniques have been used to solve such problems. In this thesis we develop algorithms for solving clustering problems in large data sets using various similarity measures. Such similarity measures are based on the squared L
- Description: Doctor of Philosophy
- Authors: Mohebi, Ehsan
- Date: 2015
- Type: Text , Thesis
- Full Text:
- Description: Cluster analysis deals with the problem of organization of a collection of patterns into clusters based on a similarity measure. Various distance functions can be used to define this measure. Clustering problems with the similarity measure defined by the squared Euclidean distance have been studied extensively over the last five decades. However, problems with other Minkowski norms have attracted significantly less attention. The use of different similarity measures may help to identify different cluster structures of a data set. This in turn may help to significantly improve the decision making process. High dimensional data visualization is another important task in the field of data mining and pattern recognition. To date, the principal component analysis and the self-organizing maps techniques have been used to solve such problems. In this thesis we develop algorithms for solving clustering problems in large data sets using various similarity measures. Such similarity measures are based on the squared L
- Description: Doctor of Philosophy
A fault-tolerant cascaded switched-capacitor multilevel inverter for domestic applications in smart grids
- Akbari, Ehsan, Teimouri, Ali, Saki, Mojtaba, Rezaei, Mohammad, Hu, Jiefeng, Band, Shahab, Pai, Hao-Ting, Mosavi, Amir
- Authors: Akbari, Ehsan , Teimouri, Ali , Saki, Mojtaba , Rezaei, Mohammad , Hu, Jiefeng , Band, Shahab , Pai, Hao-Ting , Mosavi, Amir
- Date: 2022
- Type: Text , Journal article
- Relation: IEEE Access Vol. 10, no. (2022), p. 110590-110602
- Full Text:
- Reviewed:
- Description: Cascaded multilevel inverters (MLIs) generate an output voltage using series-connected power modules that employ standard configurations of low-voltage components. Each module may employ one or more switched capacitors to double or quadruple its input voltage. The higher number of switched capacitors and semiconductor switches in MLIs compared to conventional two-level inverters has led to concerns about overall system reliability. A fault-tolerant design can mitigate this reliability issue. If one part of the system fails, the MLI can continue its planned operation at a reduced level rather than the entire system failing, which makes the fault tolerance of the MLI particularly important. In this paper, a novel fault location technique is presented that leads to a significant reduction in fault location detection time based on the reliability priority of the components of the proposed fault-tolerant switched capacitor cascaded MLI (CSCMLI). The main contribution of this paper is to reduce the number of MLI switches under fault conditions while operating at lower levels. The fault-tolerant inverter requires fewer switches at higher reliability, and the comparison with similar MLIs shows a faster dynamic response of fault detection and reduced fault location detection time. The experimental results confirm the effectiveness of the presented methods applied in the CSCMLI. Also, all experimental data including processor code, schematic, PCB, and video of CSCMLI operation are attached. © 2013 IEEE.
- Authors: Akbari, Ehsan , Teimouri, Ali , Saki, Mojtaba , Rezaei, Mohammad , Hu, Jiefeng , Band, Shahab , Pai, Hao-Ting , Mosavi, Amir
- Date: 2022
- Type: Text , Journal article
- Relation: IEEE Access Vol. 10, no. (2022), p. 110590-110602
- Full Text:
- Reviewed:
- Description: Cascaded multilevel inverters (MLIs) generate an output voltage using series-connected power modules that employ standard configurations of low-voltage components. Each module may employ one or more switched capacitors to double or quadruple its input voltage. The higher number of switched capacitors and semiconductor switches in MLIs compared to conventional two-level inverters has led to concerns about overall system reliability. A fault-tolerant design can mitigate this reliability issue. If one part of the system fails, the MLI can continue its planned operation at a reduced level rather than the entire system failing, which makes the fault tolerance of the MLI particularly important. In this paper, a novel fault location technique is presented that leads to a significant reduction in fault location detection time based on the reliability priority of the components of the proposed fault-tolerant switched capacitor cascaded MLI (CSCMLI). The main contribution of this paper is to reduce the number of MLI switches under fault conditions while operating at lower levels. The fault-tolerant inverter requires fewer switches at higher reliability, and the comparison with similar MLIs shows a faster dynamic response of fault detection and reduced fault location detection time. The experimental results confirm the effectiveness of the presented methods applied in the CSCMLI. Also, all experimental data including processor code, schematic, PCB, and video of CSCMLI operation are attached. © 2013 IEEE.
- Authors: Mestrom, Sanne
- Date: 2012
- Type: Text , Visual art work
- Full Text:
Importance of environmental flows in the Wimmera catchment, Southeast Australia
- Atazadeh, Ehsan, Barton, Andrew, Razeghi, Jafar
- Authors: Atazadeh, Ehsan , Barton, Andrew , Razeghi, Jafar
- Date: 2021
- Type: Text , Journal article
- Relation: Limnological Review Vol. 20, no. 4 (2021), p. 185-198
- Full Text:
- Reviewed:
- Description: In this paper the environment, climate, vegetation, indigenous and European settlement history, stream flow patterns, water quality and water resources development in western Victoria, Australia are studied. The last part of the paper focuses on the MacKenzie River, a tributary of the Wimmera River located on the northern slopes of the Grampians Ranges in western Victoria, Australia. Water release along the MacKenzie River was regulated to improve water quality, stream condition and river health especially in the downstream reaches. The upstream section tends to receive water most days of the year due to releases to secure the requirements of water supply for the city of Horsham and its recreational and conservation values, which is diverted into Mt Zero Channel. Below this the middle and downstream sections receive a more intermittent supply. Annually, a total of 10,000 dam3 of water is released from Wartook Reservoir into the MacKenzie River. Of this volume, only about 4,000 dam3 was released explicitly for environmental purposes. The remaining 6,000 dam3 was released to meet consumptive demands and to transfer water to downstream reservoirs. The empirical data and models showed the lower reaches of the river to be in poor condition under low flows, but this condition improved under flows of 35 dam3 per day, as indicated. The results are presented to tailor discharge and duration of the river flows by amalgamation of consumptive and environmental flows to improve the condition of the stream, thereby supplementing the flows dedicated to environmental outcomes. Ultimately the findings can be used by management to configure consumptive flows that would enhance the ecological condition of the MacKenzie River. © 2020 Ehsan Atazadeh et al., published by Sciendo 2020.
- Authors: Atazadeh, Ehsan , Barton, Andrew , Razeghi, Jafar
- Date: 2021
- Type: Text , Journal article
- Relation: Limnological Review Vol. 20, no. 4 (2021), p. 185-198
- Full Text:
- Reviewed:
- Description: In this paper the environment, climate, vegetation, indigenous and European settlement history, stream flow patterns, water quality and water resources development in western Victoria, Australia are studied. The last part of the paper focuses on the MacKenzie River, a tributary of the Wimmera River located on the northern slopes of the Grampians Ranges in western Victoria, Australia. Water release along the MacKenzie River was regulated to improve water quality, stream condition and river health especially in the downstream reaches. The upstream section tends to receive water most days of the year due to releases to secure the requirements of water supply for the city of Horsham and its recreational and conservation values, which is diverted into Mt Zero Channel. Below this the middle and downstream sections receive a more intermittent supply. Annually, a total of 10,000 dam3 of water is released from Wartook Reservoir into the MacKenzie River. Of this volume, only about 4,000 dam3 was released explicitly for environmental purposes. The remaining 6,000 dam3 was released to meet consumptive demands and to transfer water to downstream reservoirs. The empirical data and models showed the lower reaches of the river to be in poor condition under low flows, but this condition improved under flows of 35 dam3 per day, as indicated. The results are presented to tailor discharge and duration of the river flows by amalgamation of consumptive and environmental flows to improve the condition of the stream, thereby supplementing the flows dedicated to environmental outcomes. Ultimately the findings can be used by management to configure consumptive flows that would enhance the ecological condition of the MacKenzie River. © 2020 Ehsan Atazadeh et al., published by Sciendo 2020.
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.
Zero duality gap conditions via abstract convexity
- Bui, Hoa, Burachik, Regina, Kruger, Alexander, Yost, David
- Authors: Bui, Hoa , Burachik, Regina , Kruger, Alexander , Yost, David
- Date: 2022
- Type: Journal article
- Relation: Optimization Vol. 71, no. 4 (2022), p. 811-847
- Relation: https://purl.org/au-research/grants/arc/DP160100854
- Full Text:
- Reviewed:
- Description: Using tools provided by the theory of abstract convexity, we extend conditions for zero duality gap to the context of non-convex and nonsmooth optimization. Mimicking the classical setting, an abstract convex function is the upper envelope of a family of abstract affine functions (being conventional vertical translations of the abstract linear functions). We establish new conditions for zero duality gap under no topological assumptions on the space of abstract linear functions. In particular, we prove that the zero duality gap property can be fully characterized in terms of an inclusion involving (abstract) (Formula presented.) -subdifferentials. This result is new even for the classical convex setting. Endowing the space of abstract linear functions with the topology of pointwise convergence, we extend several fundamental facts of functional/convex analysis. This includes (i) the classical Banach–Alaoglu–Bourbaki theorem (ii) the subdifferential sum rule, and (iii) a constraint qualification for zero duality gap which extends a fact established by Borwein, Burachik and Yao (2014) for the conventional convex case. As an application, we show with a specific example how our results can be exploited to show zero duality for a family of non-convex, non-differentiable problems. © 2021 Informa UK Limited, trading as Taylor & Francis Group.
- Authors: Bui, Hoa , Burachik, Regina , Kruger, Alexander , Yost, David
- Date: 2022
- Type: Journal article
- Relation: Optimization Vol. 71, no. 4 (2022), p. 811-847
- Relation: https://purl.org/au-research/grants/arc/DP160100854
- Full Text:
- Reviewed:
- Description: Using tools provided by the theory of abstract convexity, we extend conditions for zero duality gap to the context of non-convex and nonsmooth optimization. Mimicking the classical setting, an abstract convex function is the upper envelope of a family of abstract affine functions (being conventional vertical translations of the abstract linear functions). We establish new conditions for zero duality gap under no topological assumptions on the space of abstract linear functions. In particular, we prove that the zero duality gap property can be fully characterized in terms of an inclusion involving (abstract) (Formula presented.) -subdifferentials. This result is new even for the classical convex setting. Endowing the space of abstract linear functions with the topology of pointwise convergence, we extend several fundamental facts of functional/convex analysis. This includes (i) the classical Banach–Alaoglu–Bourbaki theorem (ii) the subdifferential sum rule, and (iii) a constraint qualification for zero duality gap which extends a fact established by Borwein, Burachik and Yao (2014) for the conventional convex case. As an application, we show with a specific example how our results can be exploited to show zero duality for a family of non-convex, non-differentiable problems. © 2021 Informa UK Limited, trading as Taylor & Francis Group.
Extremality and stationarity of collections of sets : metric, slope and normal cone characterisations
- Bui, Hoa
- Authors: Bui, Hoa
- Date: 2019
- Type: Text , Thesis , PhD
- Full Text:
- Description: Variational analysis, a relatively new area of research in mathematics, has become one of the most powerful tools in nonsmooth optimisation and neighbouring areas. The extremal principle, a tool to substitute the conventional separation theorem in the general nonconvex environment, is a fundamental result in variational analysis. There have seen many attempts to generalise the conventional extremal principle in order to tackle certain optimisation models. Models involving collections of sets, initiated by the extremal principle, have proved their usefulness in analysis and optimisation, with non-intersection properties (or their absence) being at the core of many applications: recall the ubiquitous convex separation theorem, extremal principle, Dubovitskii Milyutin formalism and various transversality/regularity properties. We study elementary nonintersection properties of collections of sets, making the core of the conventional definitions of extremality and stationarity. In the setting of general Banach/Asplund spaces, we establish nonlinear primal (slope) and linear/nonlinear dual (generalised separation) characterisations of these non-intersection properties. We establish a series of consequences of our main results covering all known formulations of extremality/ stationarity and generalised separability properties. This research develops a universal theory, unifying all the current extensions of the extremal principle, providing new results and better understanding for the exquisite theory of variational analysis. This new study also results in direct solutions for many open questions and new future research directions in the fields of variational analysis and optimisation. Some new nonlinear characterisations of the conventional extremality/stationarity properties are obtained. For the first time, the intrinsic transversality property is characterised in primal space without involving normal cones. This characterisation brings a new perspective on intrinsic transversality. In the process, we thoroughly expose and classify all quantitative geometric and metric characterisations of transversality properties of collections of sets and regularity properties of set-valued mappings.
- Description: Doctor of Philosophy
- Authors: Bui, Hoa
- Date: 2019
- Type: Text , Thesis , PhD
- Full Text:
- Description: Variational analysis, a relatively new area of research in mathematics, has become one of the most powerful tools in nonsmooth optimisation and neighbouring areas. The extremal principle, a tool to substitute the conventional separation theorem in the general nonconvex environment, is a fundamental result in variational analysis. There have seen many attempts to generalise the conventional extremal principle in order to tackle certain optimisation models. Models involving collections of sets, initiated by the extremal principle, have proved their usefulness in analysis and optimisation, with non-intersection properties (or their absence) being at the core of many applications: recall the ubiquitous convex separation theorem, extremal principle, Dubovitskii Milyutin formalism and various transversality/regularity properties. We study elementary nonintersection properties of collections of sets, making the core of the conventional definitions of extremality and stationarity. In the setting of general Banach/Asplund spaces, we establish nonlinear primal (slope) and linear/nonlinear dual (generalised separation) characterisations of these non-intersection properties. We establish a series of consequences of our main results covering all known formulations of extremality/ stationarity and generalised separability properties. This research develops a universal theory, unifying all the current extensions of the extremal principle, providing new results and better understanding for the exquisite theory of variational analysis. This new study also results in direct solutions for many open questions and new future research directions in the fields of variational analysis and optimisation. Some new nonlinear characterisations of the conventional extremality/stationarity properties are obtained. For the first time, the intrinsic transversality property is characterised in primal space without involving normal cones. This characterisation brings a new perspective on intrinsic transversality. In the process, we thoroughly expose and classify all quantitative geometric and metric characterisations of transversality properties of collections of sets and regularity properties of set-valued mappings.
- Description: Doctor of Philosophy
Intelligent packaging in meat industry : An overview of existing solutions
- Mohebi, Ehsan, Marquez, Leorey
- Authors: Mohebi, Ehsan , Marquez, Leorey
- Date: 2015
- Type: Text , Journal article
- Relation: Journal of Food Science and Technology-Mysore Vol. 52, no. 7 (2015), p. 3947-3964
- Full Text:
- Reviewed:
- Description: Traditional packaging systems are refused since these systems do not provide any information about the quality of food products to the consumers and manufacturers at any stage of supply chain. The essence of a new technology to monitor the food spoilage from farm to fork is emerged to reduce hazards such as food borne diseases. Moreover, the food quality monitoring systems clarify the main factors in food wastage during supply chain. Intelligent packaging is employed to provide information about the history of food handling and storage to enhance food products quality and meet consumer satisfactions. Meat is one of the most perishable foods which causes sever illnesses in the case of spoilage. Variety of indicators and sensors have been proposed to warn about meat spoilage in meat industry. In this paper an overview of proposed approaches as well as commercial technologies to monitor the quality of meat during storage and transportation is presented. Furthermore, the existing technologies are compared in the sense of advantages and disadvantages in meat packaging applications.
- Authors: Mohebi, Ehsan , Marquez, Leorey
- Date: 2015
- Type: Text , Journal article
- Relation: Journal of Food Science and Technology-Mysore Vol. 52, no. 7 (2015), p. 3947-3964
- Full Text:
- Reviewed:
- Description: Traditional packaging systems are refused since these systems do not provide any information about the quality of food products to the consumers and manufacturers at any stage of supply chain. The essence of a new technology to monitor the food spoilage from farm to fork is emerged to reduce hazards such as food borne diseases. Moreover, the food quality monitoring systems clarify the main factors in food wastage during supply chain. Intelligent packaging is employed to provide information about the history of food handling and storage to enhance food products quality and meet consumer satisfactions. Meat is one of the most perishable foods which causes sever illnesses in the case of spoilage. Variety of indicators and sensors have been proposed to warn about meat spoilage in meat industry. In this paper an overview of proposed approaches as well as commercial technologies to monitor the quality of meat during storage and transportation is presented. Furthermore, the existing technologies are compared in the sense of advantages and disadvantages in meat packaging applications.
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
Best approximation by downward sets with applications
- Rubinov, Alex, Mohebi, Hossein
- Authors: Rubinov, Alex , Mohebi, Hossein
- Date: 2006
- Type: Text , Journal article
- Relation: Analysis in Theory and Applications Vol. 22, no. 1 (2006), p. 20-40
- Full Text:
- Reviewed:
- Description: We develop a theory of downward sets for a class of normed ordered spaces. We study best approximation in a normed ordered space X by elements of downward sets, and give necessary and sufficient conditions for any element of best approximation by a closed downward subset of X. We also characterize strictly downward subsets of X, and prove that a downward subset of X is strictly downward if and only if each its boundary point is Chebyshev. The results obtained are used for examination of some Chebyshev pairs (W,x), where x E X and W is a closed downward subset of X.
- Description: C1
- Description: 2003001535
- Authors: Rubinov, Alex , Mohebi, Hossein
- Date: 2006
- Type: Text , Journal article
- Relation: Analysis in Theory and Applications Vol. 22, no. 1 (2006), p. 20-40
- Full Text:
- Reviewed:
- Description: We develop a theory of downward sets for a class of normed ordered spaces. We study best approximation in a normed ordered space X by elements of downward sets, and give necessary and sufficient conditions for any element of best approximation by a closed downward subset of X. We also characterize strictly downward subsets of X, and prove that a downward subset of X is strictly downward if and only if each its boundary point is Chebyshev. The results obtained are used for examination of some Chebyshev pairs (W,x), where x E X and W is a closed downward subset of X.
- Description: C1
- Description: 2003001535
Mapping geographical inequalities in childhood diarrhoeal morbidity and mortality in low-income and middle-income countries, 2000-17 : analysis for the global burden of disease study 2017
- Reiner, Robert, Wiens, Kirsten, Deshpande, Aniruddha, Baumann, Mathew, Rahman, Muhammad Aziz
- Authors: Reiner, Robert , Wiens, Kirsten , Deshpande, Aniruddha , Baumann, Mathew , Rahman, Muhammad Aziz
- Date: 2020
- Type: Text , Journal article
- Relation: The Lancet Vol. 395, no. 10239 (2020), p. 1779-1801
- Full Text:
- Reviewed:
- Description: Background Across low-income and middle-income countries (LMICs), one in ten deaths in children younger than 5 years is attributable to diarrhoea. The substantial between-country variation in both diarrhoea incidence and mortality is attributable to interventions that protect children, prevent infection, and treat disease. Identifying subnational regions with the highest burden and mapping associated risk factors can aid in reducing preventable childhood diarrhoea. Methods We used Bayesian model-based geostatistics and a geolocated dataset comprising 15 072 746 children younger than 5 years from 466 surveys in 94 LMICs, in combination with findings of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, to estimate posterior distributions of diarrhoea prevalence, incidence, and mortality from 2000 to 2017. From these data, we estimated the burden of diarrhoea at varying subnational levels (termed units) by spatially aggregating draws, and we investigated the drivers of subnational patterns by creating aggregated risk factor estimates. Findings The greatest declines in diarrhoeal mortality were seen in south and southeast Asia and South America, where 54·0% (95% uncertainty interval [UI] 38·1-65·8), 17·4% (7·7-28·4), and 59·5% (34·2-86·9) of units, respectively, recorded decreases in deaths from diarrhoea greater than 10%. Although children in much of Africa remain at high risk of death due to diarrhoea, regions with the most deaths were outside Africa, with the highest mortality units located in Pakistan. Indonesia showed the greatest within-country geographical inequality; some regions had mortality rates nearly four times the average country rate. Reductions in mortality were correlated to improvements in water, sanitation, and hygiene (WASH) or reductions in child growth failure (CGF). Similarly, most high-risk areas had poor WASH, high CGF, or low oral rehydration therapy coverage. Interpretation By co-analysing geospatial trends in diarrhoeal burden and its key risk factors, we could assess candidate drivers of subnational death reduction. Further, by doing a counterfactual analysis of the remaining disease burden using key risk factors, we identified potential intervention strategies for vulnerable populations. In view of the demands for limited resources in LMICs, accurately quantifying the burden of diarrhoea and its drivers is important for precision public health. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. ***Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Rahman” is provided in this record***
- Description: C A T Antonio reports grants and personal fees from Johnson & Johnson (Philippines), outside the submitted work. S J Dunachie reports grants from The Fleming Fund at UK Department of Health & Social Care, during the conduct of the study. M Jakovljevic reports grants from Ministry of Education Science and Technological Development of The Republic of Serbia, outside the submitted work. J J Jó
- Authors: Reiner, Robert , Wiens, Kirsten , Deshpande, Aniruddha , Baumann, Mathew , Rahman, Muhammad Aziz
- Date: 2020
- Type: Text , Journal article
- Relation: The Lancet Vol. 395, no. 10239 (2020), p. 1779-1801
- Full Text:
- Reviewed:
- Description: Background Across low-income and middle-income countries (LMICs), one in ten deaths in children younger than 5 years is attributable to diarrhoea. The substantial between-country variation in both diarrhoea incidence and mortality is attributable to interventions that protect children, prevent infection, and treat disease. Identifying subnational regions with the highest burden and mapping associated risk factors can aid in reducing preventable childhood diarrhoea. Methods We used Bayesian model-based geostatistics and a geolocated dataset comprising 15 072 746 children younger than 5 years from 466 surveys in 94 LMICs, in combination with findings of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, to estimate posterior distributions of diarrhoea prevalence, incidence, and mortality from 2000 to 2017. From these data, we estimated the burden of diarrhoea at varying subnational levels (termed units) by spatially aggregating draws, and we investigated the drivers of subnational patterns by creating aggregated risk factor estimates. Findings The greatest declines in diarrhoeal mortality were seen in south and southeast Asia and South America, where 54·0% (95% uncertainty interval [UI] 38·1-65·8), 17·4% (7·7-28·4), and 59·5% (34·2-86·9) of units, respectively, recorded decreases in deaths from diarrhoea greater than 10%. Although children in much of Africa remain at high risk of death due to diarrhoea, regions with the most deaths were outside Africa, with the highest mortality units located in Pakistan. Indonesia showed the greatest within-country geographical inequality; some regions had mortality rates nearly four times the average country rate. Reductions in mortality were correlated to improvements in water, sanitation, and hygiene (WASH) or reductions in child growth failure (CGF). Similarly, most high-risk areas had poor WASH, high CGF, or low oral rehydration therapy coverage. Interpretation By co-analysing geospatial trends in diarrhoeal burden and its key risk factors, we could assess candidate drivers of subnational death reduction. Further, by doing a counterfactual analysis of the remaining disease burden using key risk factors, we identified potential intervention strategies for vulnerable populations. In view of the demands for limited resources in LMICs, accurately quantifying the burden of diarrhoea and its drivers is important for precision public health. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. ***Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Rahman” is provided in this record***
- Description: C A T Antonio reports grants and personal fees from Johnson & Johnson (Philippines), outside the submitted work. S J Dunachie reports grants from The Fleming Fund at UK Department of Health & Social Care, during the conduct of the study. M Jakovljevic reports grants from Ministry of Education Science and Technological Development of The Republic of Serbia, outside the submitted work. J J Jó
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).
A simulated annealing-based maximum-margin clustering algorithm
- Seifollahi, Sattar, Bagirov, Adil, Borzeshi, Ehsan, Piccardi, Massimo
- Authors: Seifollahi, Sattar , Bagirov, Adil , Borzeshi, Ehsan , Piccardi, Massimo
- Date: 2019
- Type: Text , Journal article
- Relation: Computational Intelligence Vol. 35, no. 1 (2019), p. 23-41
- Full Text:
- Reviewed:
- Description: Maximum-margin clustering is an extension of the support vector machine (SVM) to clustering. It partitions a set of unlabeled data into multiple groups by finding hyperplanes with the largest margins. Although existing algorithms have shown promising results, there is no guarantee of convergence of these algorithms to global solutions due to the nonconvexity of the optimization problem. In this paper, we propose a simulated annealing-based algorithm that is able to mitigate the issue of local minima in the maximum-margin clustering problem. The novelty of our algorithm is twofold, ie, (i) it comprises a comprehensive cluster modification scheme based on simulated annealing, and (ii) it introduces a new approach based on the combination of k-means++ and SVM at each step of the annealing process. More precisely, k-means++ is initially applied to extract subsets of the data points. Then, an unsupervised SVM is applied to improve the clustering results. Experimental results on various benchmark data sets (of up to over a million points) give evidence that the proposed algorithm is more effective at solving the clustering problem than a number of popular clustering algorithms.
- Authors: Seifollahi, Sattar , Bagirov, Adil , Borzeshi, Ehsan , Piccardi, Massimo
- Date: 2019
- Type: Text , Journal article
- Relation: Computational Intelligence Vol. 35, no. 1 (2019), p. 23-41
- Full Text:
- Reviewed:
- Description: Maximum-margin clustering is an extension of the support vector machine (SVM) to clustering. It partitions a set of unlabeled data into multiple groups by finding hyperplanes with the largest margins. Although existing algorithms have shown promising results, there is no guarantee of convergence of these algorithms to global solutions due to the nonconvexity of the optimization problem. In this paper, we propose a simulated annealing-based algorithm that is able to mitigate the issue of local minima in the maximum-margin clustering problem. The novelty of our algorithm is twofold, ie, (i) it comprises a comprehensive cluster modification scheme based on simulated annealing, and (ii) it introduces a new approach based on the combination of k-means++ and SVM at each step of the annealing process. More precisely, k-means++ is initially applied to extract subsets of the data points. Then, an unsupervised SVM is applied to improve the clustering results. Experimental results on various benchmark data sets (of up to over a million points) give evidence that the proposed algorithm is more effective at solving the clustering problem than a number of popular clustering algorithms.
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