The second class is new and is closely related to the Compton camera imaging principles and invertible under special conditions . As they are poised to play a major role in future designs of biomedical imaging systems , we present an account of their most important properties which may be relevant for active researchers in the field . Over the past 2 decades , hyperspectral imaging technologies have been adapted to address the need for molecule-specific identification in the biomedical imaging field . Applications have ranged from single-cell microscopy to whole-animal in vivo imaging and from basic research to clinical systems . There is a common belief that the successful training of deep neural networks requires many annotated training samples , which are often expensive and difficult to obtain especially in the biomedical imaging field . While it is often easy for researchers to use data augmentation to expand the size of training sets , constructing and generating generic augmented data that is able to teach the network the desired invariance and robustness properties using traditional data augmentation techniques is challenging in practice . The emergence of PLM for biomedical imaging lifecycle management highlights the needs for management and analysis of heterogeneous , complex and multidimensional data in PLM systems . Data provenance in biomedical imaging domain is complex , notably provenance of processing data , and to ensure full traceability in a purpose of reuse , processing operations must be integrated to PLM systems and processing provenance must be easily analyzable by users . The DIMP ( Data Integrated Management and Processing ) method was designed for this objective : it allows user to launch easily processing chains from PLM systems and ensures a full management of provenance . In the context of biomedical imaging analysis and computer-assisted diagnosis , segmentation analysis is an intense field of research and development . The most difficult part of medical image analysis is the automated localization and delineation of structures of interest . Biomedical imaging analysis typically comprises a variety of complex tasks requiring sophisticated algorithms and visualising high dimensional data . The successful integration and deployment of the enabling software to clinical ( research ) partners , for rigorous evaluation and testing , is a crucial step to facilitate adoption of research innovations within medical settings . Deep learning has gained tremendous attention on CAD ( Computer-aided Diagnosing ) application , particularly biomedical imaging analysis . We analyze three large-scale publicly available CXR ( Chest X-ray ) datasets and find that vanilla training of deep models on diagnosing common Thorax Diseases are subject to dataset bias , leading to severe performance degradation when evaluated on unseen test set . In this talk , I will first review my research work on spline and wavlelet based signal processing theory and algorithms and then present their applications to two biomedical imaging modalities , i.e. , tagged MRI image analysis and genomic imaging . In the first application , spline approximations are used to rapid and accurate computation of displacement field from tagged MRI image sequences for heart disease diagnosis . The overall goal of this issue is to promote research and development of biomedical imaging by publishing high-quality research articles in this rapidly growing interdisciplinary field . Due to the time limit , this special issue mainly focused on 4 kinds of biomedical imaging modalities : CT , MRI , ultrasound , and fluorescence imaging ; several biomedical image processing methods were also involved . Each paper published in this special issue was reviewed by at least two reviewers and revised according to reviewer 's comments . The design , development , and implementation of ultrahigh resolution OCT systems in both laboratory and clinical experiments has been pursued in this work . Biomedical imaging studies in the areas of arthroscopy , cardiology , and endoscopy have been investigated with ultrahigh resolution capability achieved through the use of broadband femtosecond oscillators such as Ti : Sapphire and Cr : Forsterite light sources . OCT image resolutions of 1 - 5um in tissue have been realized , an order of magnitude greater than conventional MRI or ultrasound resolutions . A common problem in many biomedical imaging studies is that of finding a correspondence between two plane curves which aligns their shapes . A mathematical formulation and solutions to this problem is proposed in this paper . Image segmentation is a fundamental issue in biomedical imaging area . This can be exploited in the images to evaluate therapeutic effect or evolution of the disease . Current input , voltage output analog integrators are important electronic components for photo-current measurement applications such as diffuse light tomography and spectroscopy applications . In this work , current input , analog voltage output integrator has been designed and simulations have been tested for biomedical imaging purpose . Researchers want to know photon accumulations in different phantom layers for photon measurement applications , especially for diffuse optical tomography ( DOT ) devices . Then , we repeatedly build PA images around a special target to yield the best focused result by dynamically updating the acoustic speeds in a different medium of the target . With these correct acoustic propagation velocities in the according mediums , we can effectively optimize the PA image quality as the experiments proved , which might benefit future research in biomedical imaging science . Increasingly emerging technologies in micro-electromechanical systems and wireless communications allows a mobile wireless sensor networks ( MWSN ) to be a more and more powerful mean in many applications such as habitat and environmental monitoring , traffic observing , battlefield surveillance , smart homes and smart cities . Nevertheless , due to sensor battery constraints , energy-efficiently operating a MWSN is paramount importance in those applications ; and a plethora of approaches have been proposed to elongate the network longevity at most possible . Simulations aid in many scientific and industrial applications . A general ambition for these simulations is to keep the time-to-solution as small as possible while maintaining a desired accuracy . The physical and optical characteristics of both the single wall carbon nanotubes dispersions and the deposited films were studied using a variety of methods . These single wall carbon nanotubes based near-infrared sensors shows excellent sensitivity up to 7.2 % at 1.5 mW/mm2 laser light illumination and can be used , for instance , for a variety of scientific and industrial applications . This algorithm for line integral convolution enables the interactive post-processing of flow fields on partitioned and distributed unstructured grids . The methods introduced in this thesis are evaluated using several large-scale simulation datasets from different fields of engineering in scientific and industrial applications . Numerische Simulationen und deren Auswertung gewinnen in Produktdesign und Produktoptimierung They are also valuable in extending the software 's working life . FOCUS is an ESPRIT-2 project whose goal is to develop generic tools and techniques for constructing and maintaining KBFEs for open user systems ( e.g. libraries , reusable software components ) and closed user systems ( e.g. free-standing software , packages ) for industrial and scientific applications . The participating partners are drawn from both industrial and academic institutions , providing a wide crosssection of software researchers , producers and users , and , although there are substantial research objectives , the project has taken a pragmatic approach , with the commercialisation of products developed playing a prominent role . In many scientific , industrial and commercial applications , it is often necessary to analyze large data sets over geographically distributed sites . An appropriate distributed and parallel system is needed to store and manage the large data sets . Computational resources available from cluster configurations are cost effective components to improve several classes of applications in many organizations . Scientific , industrial and commercial applications are more relying on cluster performance . OSCAR is a useful open software approach to manage cluster of workstations . The availability of commodity parallel computers , ubiquitous networks , maturing Grid middleware , and portal frameworks is fostering the development and deployment of large scale simulation and data analysis solutions in many areas . This topic highlights recent progress in applications of high performance parallel and Grid computing , with an emphasis on successes , advances , and lessons learned in the development and implementation of novel scientific , engineering and industrial applications . Today 's large computational solutions often operate in complex information and computation environments where efficient data access and management can be as important as computational methods and performance , so the technical approaches in this topic span high performance parallel computing , Grid computation and data access , and the associated problem-solving environments that compose and manage advanced solutions . They are also used in general purpose computing to solve problems that can benefit from massive parallel processing . There are numerous reports confirming the effectiveness of GPU in science and industrial applications . However , there are several issues related with GPU usage as a databases coprocessor that must be considered . The projection of high-dimensional data by linear or nonlinear techniques is a well established technique in pattern recognition and other scientific and industrial application fields . Commonly , methods affiliated to multidimensional-scaling , projection pursuit or Sammons nonlinear distance preserving mapping are applied , based on gradient descent techniques . The purpose of this paper is to evaluate the potential of the Institute as a multifunctional information center that widely uses modern information and communications technologies and electronic information resources . Promising approaches are considered to deeper processing of information , multivariate analysis of collected data , and the possibility of establishing the actual types of information products and services that are focused on decision support in scientific , technical , and industrial applications , and , indirectly , in the economy as a whole . The whole genome DNA microarrays make it possible to monitor the expression of nearly all the genes in an organism and have been widely used in scientific and industrial fields . The challenges no longer lie in obtaining the data , but rather in interpreting the results to reveal the mechanisms of biological significance . Sensor networks have significantly reduced the costs of data gathering in the environment . Real-time sensor data are being used for scientific and industrial purposes such as calibration of forecast modeling , environmental monitoring and decision-making processes in business impacted by environmental changes . Many scientific and industrial tasks in the domain of microand nano-technology require micro-/ nano-operations such as pick-and-place , assembly , feeding and so on , combined with large up to several centimetres robotized manipulations ( for some field robotics and medical robotics ) . Such complex tasks need one large-range robot and one or more low-range manipulators with high precision . Data processing for scientific and industrial tasks often involves accurate extraction of theoretical model parameters from empirical data , and requires automated estimation methods that are robust in the presence of " noisy " ( i.e. , contaminated ) data . Robust estimation is thus an important statistical tool that is frequently applied in numerous fields of science and engineering ( e.g. , automated manufacturing , robotic navigation , image processing , and computer vision ) . In this paper , the approach to the development of deductive assistance based on the current state of the System for Automated Deduction , SAD , is described briefly . The SAD may be considered as a three-dimensional " shell " for deductive assistance in a formal natural language environment when solving a number of scientific and industrial tasks requiring automated theorem proving , verification of formal texts , construction of knowledge bases for formalized theories , integration of symbolic calculation with deduction , and so on Nowadays plasma has become of great importance in both scientific and industrial areas since nanostructures , used for creating small computational processing devices , are produced by pulse lasers . The Simulation of phenomena such as plasma consumes a big amount of CPUs execution time . Accurately predicting the dynamics of particulate materials is of importance to numerous scientific and industrial areas with applications ranging across particle scales from powder flow to ore crushing . Computational discrete element simulations is a viable option to aid in the understanding of particulate dynamics and design of devices such as mixers , silos and ball mills , as laboratory scale tests comes at a significant cost . An error less than 0.005 % was obtained for these values during conversion time of 100 μs ( 40 clock cycles ) . The results obtained make it possible to manufacture analog-to-digital functional converters with increased accuracy and speed , applicable for various industrial and scientific tasks . A special feature is the possibility of user 's choice of the required accuracy and speed , even before the start of conversion . Three-dimensional ( 3-D ) image segmentation is one of the most demanding tasks in image processing . The applications comprise industrial and scientific tasks . Due to the high data volume , advanced algorithms can not be processed on standard hardware in real time . 3D image segmentation is one of the most demanding tasks in image processing . The applications comprise industrial and scientific tasks . Due to the high data volume advanced algorithms can not be processed on standard hardware in real time . Simulation of Mobile Ad-hoc NETworks ( MANETs ) , designed for civil and or military use is particularly challenging , due to high number of nodes , different mobility and channel models and different types of traffic and QoS requirements , and led to the design of several network simulators . Among them , OMNeT++ , OPNET and ns-3 are arguably the most popular ones for scientific and industrial activities . Each of the above simulators is characterized by specific advantages and drawbacks , as well as different available models . Autonomous systems like self-driving cars , unmanned aerial and marine vehicles , smart robots etc . , are rapidly emerging in scientific and industrial sectors for mission-critical applications , in recent times . Critical systems are developed using component-based software engineering paradigm by most of the software developers . Abstract We study non-preemptive scheduling problems where heterogeneous projects stochastically arrive over time . The projects include precedence-constrained tasks that require multiple resources . Consequently , a new iteration was launched until obtaining the best multi- tenant software scheduling results . The results from experiments show that performances of this proposed method for multi- tenant scheduling are superior to traditional methods at run time , the efficiency of the resource utilization and the number of users . This method has strong capabilities for multi- tenant software scheduling and provides a scientific basis for the multi- tenant software scheduling optimization . Since its introduction , it has been deployed in production and extended to support use cases beyond large-scale batch processing . The tutorial will present the active research and development supporting such heterogeneous workloads , with particular attention to multi-tenant scheduling . Topics include security , resource isolation , protocols , and preemption . This book comprehensively illustrates quality-ware scheduling in key-value stores . In addition , it provides scheduling strategies and a prototype framework of quality-aware scheduler as well as a demonstration of online applications . Additionally , we provide evidence for the practical relevance of these theoretical findings through extensive numerical experiments . Finally , we present a case study in which the benefits of offering assortments in stages are explored and exploited within the context of dynamically scheduling restaurant reservations . For this purpose , we make use of historical reservation data from a fine-dining Michelin starred restaurant to build a realistic simulation of their booking process . We propose a set of scheduling procedures for dealing with the sporadic task scheduling in a dynamic periodic system . For this we mean a system in which periodic tasks change their parameters dynamically ( at run-time ) , in an unpredictable way . How Long Does a Bit Live in a Computer?.- Approximation Algorithms for the Traveling Purchaser Problem and Its Variants in Network Design.- The Impact of Knowledge on Broadcasting Time in Radio Networks.- Multipacket Routing on 2-D Meshes and Its Application to Fault-Tolerant Routing.- IP Address LookupMade Fast and Simple.- On-Line Load Balancing in a Hierarchical Server Topology.- Provably Good and Practical Strategies for Non-uniform Data Management in Networks.- Approximation Algorithms for Restoration Capacity Planning.- Efficient Algorithms for Integer Programs with Two Variables per Constraint.- Convex Quadratic Programming Relaxations for Network Scheduling Problems.- Resource-Constrained Project Scheduling : Computing Lower Bounds by Solving Minimum Cut Problems.- Approximation Schemes for Scheduling on Uniformly Related and Identical Parallel Machines.- Off-Line Temporary Tasks Assignment.- Load Balancing Using Bisectors - A Tight Average-Case Analysis.- Based on the CGLP formulation , we present a mixed-integer formulation that determines if such an equivalence exists and we report computational results on several instances where many cuts from elementary t-branch disjunctions are not equivalent to cuts from t rows of the simplex tableau . The last area is an emergent scheduling application , in which we study a last-mile passenger transportation service using autonomous vehicles . Our contribution consists of an approach to solve this optimization problem within the required time frame . Currently , academia and technology corporations are leading the way in research and implementation , working in distinct fields such as natural language processing and object recognition . There has been enormous progress , as AI , supported by deep learning [ 1 ] , is very good at completing a discrete task such as scheduling an appointment [ 2 ] . But it ’s not capable of completing a more general intellectual task , such as knowing how and when to reschedule the appointment in the event of more urgent matters . A DMC model demonstrates the impact of task allocation on ASP M-P architectures . Five application-specific heuristics and four static-labelling schemes are developed for scheduling console taskforces on M-Ps . An integrated research framework and DCS engine enable scheduling strategies to be analysed with regard to the DMC problem domain . Examples of applications enabled by this technology include interactive ads , interactive access to sports statistics during sports events , and interactive access to supplementary information during talk shows , news programs , documentaries , etc . This paper describes the basic technology for such enhanced DTV programming , and analyzes the architectural and scheduling issues that arise in connection with inserting data into the digital broadcast stream to support it . The primary focus is on so-called ATVEF ( Advanced Television Enhancement Forum ) applications in the context of the ATSC digital television standards , but most of the analysis applies equally well to other forms of enhanced DTV programming where data must be coordinated with the audio-video . Distributed data mining(DDM ) is widely used in industrial , scientific and commercial applications to analyze large datasets maintained over geographically distributed sites , which makes DDM a major research issue on(today 's ) data mining field . This paper discusses the disadvantages of existing DDM systems , puts forward a service-oriented architecture for DDM on the grid and describe the process of mining under this framework . Micro/nano positioning technologies have been attractive for decades in industrial and scientific applications fields . The actuators have inherent hysteresis that can cause system unexpected behave in some extend . Abstract X-ray micro computed tomography ( microCT ) is a high resolution non-destructive materials imaging technology and is emerging as a powerful tool for industrial and scientific research applications . The aim of this review paper is to present the capabilities and potential of this technique within an African context . This topic aims at the development , implementation and experience of real industrial , engineering and scientific applications on parallel and distributed systems . The robot has a payload area to allow the integration of different equipment depending on the devices and systems . Its flexibility , easy operation and openness makes the SPARUS II AUV a multipurpose platform that can adapt to industrial , scientific and academic applications . Five units were developed in 2014 , and different teams used and adapted the platform for different applications . The totality of the results presented in this thesis represent a significant addition to the open source data pool and have advanced the state of the art in the understanding of dynamic signatures from rotating cylinders . The results are shown to have relevance to a variety of defence and industrial scientific applications and will therefore be of interest to a wide audience . Finally a new Doppler-surface mapping ( D-map ) methodology is given that provides a mechanism to discriminate between targets with differing electrical ( material ) properties or surface roughness characteristics . CajAstur and the Foundation for the Advancement of Soft Computing , through the European Centre for Soft Computing , announce the Sixth edition of their International Prize for Soft Computing . The CAJASTUR " MAMDANI PRIZE ' ' FOR SOFT COMPUTING is meant to distinguish a person or group of persons for the realization of a relevant scientific or industrial application , meaning an original contribution in the area of Soft Computing . Modern parallel file system architectures however , span a large and complex design space . As a result , IT architects are faced with a challenge when deciding on the most appropriate parallel file system for a specific scientific or industrial application in a large-scale computing installation . Typically , the right choice depends on the characteristics of the application as well as the design assumptions built into a parallel file system .
The second class is new and is closely related to the Compton camera imaging principles and invertible under special conditions . As they are poised to play a major role in future designs of biomedical imaging systems , we present an account of their most important properties which may be relevant for active researchers in the field .
Over the past 2 decades , hyperspectral imaging technologies have been adapted to address the need for molecule-specific identification in the biomedical imaging field . Applications have ranged from single-cell microscopy to whole-animal in vivo imaging and from basic research to clinical systems .
There is a common belief that the successful training of deep neural networks requires many annotated training samples , which are often expensive and difficult to obtain especially in the biomedical imaging field . While it is often easy for researchers to use data augmentation to expand the size of training sets , constructing and generating generic augmented data that is able to teach the network the desired invariance and robustness properties using traditional data augmentation techniques is challenging in practice .
The emergence of PLM for biomedical imaging lifecycle management highlights the needs for management and analysis of heterogeneous , complex and multidimensional data in PLM systems . Data provenance in biomedical imaging domain is complex , notably provenance of processing data , and to ensure full traceability in a purpose of reuse , processing operations must be integrated to PLM systems and processing provenance must be easily analyzable by users . The DIMP ( Data Integrated Management and Processing ) method was designed for this objective : it allows user to launch easily processing chains from PLM systems and ensures a full management of provenance .
In the context of biomedical imaging analysis and computer-assisted diagnosis , segmentation analysis is an intense field of research and development . The most difficult part of medical image analysis is the automated localization and delineation of structures of interest .
Biomedical imaging analysis typically comprises a variety of complex tasks requiring sophisticated algorithms and visualising high dimensional data . The successful integration and deployment of the enabling software to clinical ( research ) partners , for rigorous evaluation and testing , is a crucial step to facilitate adoption of research innovations within medical settings .
Deep learning has gained tremendous attention on CAD ( Computer-aided Diagnosing ) application , particularly biomedical imaging analysis . We analyze three large-scale publicly available CXR ( Chest X-ray ) datasets and find that vanilla training of deep models on diagnosing common Thorax Diseases are subject to dataset bias , leading to severe performance degradation when evaluated on unseen test set .
In this talk , I will first review my research work on spline and wavlelet based signal processing theory and algorithms and then present their applications to two biomedical imaging modalities , i.e. , tagged MRI image analysis and genomic imaging . In the first application , spline approximations are used to rapid and accurate computation of displacement field from tagged MRI image sequences for heart disease diagnosis .
The overall goal of this issue is to promote research and development of biomedical imaging by publishing high-quality research articles in this rapidly growing interdisciplinary field . Due to the time limit , this special issue mainly focused on 4 kinds of biomedical imaging modalities : CT , MRI , ultrasound , and fluorescence imaging ; several biomedical image processing methods were also involved . Each paper published in this special issue was reviewed by at least two reviewers and revised according to reviewer 's comments .
The design , development , and implementation of ultrahigh resolution OCT systems in both laboratory and clinical experiments has been pursued in this work . Biomedical imaging studies in the areas of arthroscopy , cardiology , and endoscopy have been investigated with ultrahigh resolution capability achieved through the use of broadband femtosecond oscillators such as Ti : Sapphire and Cr : Forsterite light sources . OCT image resolutions of 1 - 5um in tissue have been realized , an order of magnitude greater than conventional MRI or ultrasound resolutions .
A common problem in many biomedical imaging studies is that of finding a correspondence between two plane curves which aligns their shapes . A mathematical formulation and solutions to this problem is proposed in this paper .
Image segmentation is a fundamental issue in biomedical imaging area . This can be exploited in the images to evaluate therapeutic effect or evolution of the disease .
Current input , voltage output analog integrators are important electronic components for photo-current measurement applications such as diffuse light tomography and spectroscopy applications . In this work , current input , analog voltage output integrator has been designed and simulations have been tested for biomedical imaging purpose . Researchers want to know photon accumulations in different phantom layers for photon measurement applications , especially for diffuse optical tomography ( DOT ) devices .
Then , we repeatedly build PA images around a special target to yield the best focused result by dynamically updating the acoustic speeds in a different medium of the target . With these correct acoustic propagation velocities in the according mediums , we can effectively optimize the PA image quality as the experiments proved , which might benefit future research in biomedical imaging science .
Increasingly emerging technologies in micro-electromechanical systems and wireless communications allows a mobile wireless sensor networks ( MWSN ) to be a more and more powerful mean in many applications such as habitat and environmental monitoring , traffic observing , battlefield surveillance , smart homes and smart cities . Nevertheless , due to sensor battery constraints , energy-efficiently operating a MWSN is paramount importance in those applications ; and a plethora of approaches have been proposed to elongate the network longevity at most possible .
Simulations aid in many scientific and industrial applications . A general ambition for these simulations is to keep the time-to-solution as small as possible while maintaining a desired accuracy .
The physical and optical characteristics of both the single wall carbon nanotubes dispersions and the deposited films were studied using a variety of methods . These single wall carbon nanotubes based near-infrared sensors shows excellent sensitivity up to 7.2 % at 1.5 mW/mm2 laser light illumination and can be used , for instance , for a variety of scientific and industrial applications .
This algorithm for line integral convolution enables the interactive post-processing of flow fields on partitioned and distributed unstructured grids . The methods introduced in this thesis are evaluated using several large-scale simulation datasets from different fields of engineering in scientific and industrial applications . Numerische Simulationen und deren Auswertung gewinnen in Produktdesign und Produktoptimierung
They are also valuable in extending the software 's working life . FOCUS is an ESPRIT-2 project whose goal is to develop generic tools and techniques for constructing and maintaining KBFEs for open user systems ( e.g. libraries , reusable software components ) and closed user systems ( e.g. free-standing software , packages ) for industrial and scientific applications . The participating partners are drawn from both industrial and academic institutions , providing a wide crosssection of software researchers , producers and users , and , although there are substantial research objectives , the project has taken a pragmatic approach , with the commercialisation of products developed playing a prominent role .
In many scientific , industrial and commercial applications , it is often necessary to analyze large data sets over geographically distributed sites . An appropriate distributed and parallel system is needed to store and manage the large data sets .
Computational resources available from cluster configurations are cost effective components to improve several classes of applications in many organizations . Scientific , industrial and commercial applications are more relying on cluster performance . OSCAR is a useful open software approach to manage cluster of workstations .
The availability of commodity parallel computers , ubiquitous networks , maturing Grid middleware , and portal frameworks is fostering the development and deployment of large scale simulation and data analysis solutions in many areas . This topic highlights recent progress in applications of high performance parallel and Grid computing , with an emphasis on successes , advances , and lessons learned in the development and implementation of novel scientific , engineering and industrial applications . Today 's large computational solutions often operate in complex information and computation environments where efficient data access and management can be as important as computational methods and performance , so the technical approaches in this topic span high performance parallel computing , Grid computation and data access , and the associated problem-solving environments that compose and manage advanced solutions .
They are also used in general purpose computing to solve problems that can benefit from massive parallel processing . There are numerous reports confirming the effectiveness of GPU in science and industrial applications . However , there are several issues related with GPU usage as a databases coprocessor that must be considered .
The projection of high-dimensional data by linear or nonlinear techniques is a well established technique in pattern recognition and other scientific and industrial application fields . Commonly , methods affiliated to multidimensional-scaling , projection pursuit or Sammons nonlinear distance preserving mapping are applied , based on gradient descent techniques .
The purpose of this paper is to evaluate the potential of the Institute as a multifunctional information center that widely uses modern information and communications technologies and electronic information resources . Promising approaches are considered to deeper processing of information , multivariate analysis of collected data , and the possibility of establishing the actual types of information products and services that are focused on decision support in scientific , technical , and industrial applications , and , indirectly , in the economy as a whole .
The whole genome DNA microarrays make it possible to monitor the expression of nearly all the genes in an organism and have been widely used in scientific and industrial fields . The challenges no longer lie in obtaining the data , but rather in interpreting the results to reveal the mechanisms of biological significance .
Sensor networks have significantly reduced the costs of data gathering in the environment . Real-time sensor data are being used for scientific and industrial purposes such as calibration of forecast modeling , environmental monitoring and decision-making processes in business impacted by environmental changes .
Many scientific and industrial tasks in the domain of microand nano-technology require micro-/ nano-operations such as pick-and-place , assembly , feeding and so on , combined with large up to several centimetres robotized manipulations ( for some field robotics and medical robotics ) . Such complex tasks need one large-range robot and one or more low-range manipulators with high precision .
Data processing for scientific and industrial tasks often involves accurate extraction of theoretical model parameters from empirical data , and requires automated estimation methods that are robust in the presence of " noisy " ( i.e. , contaminated ) data . Robust estimation is thus an important statistical tool that is frequently applied in numerous fields of science and engineering ( e.g. , automated manufacturing , robotic navigation , image processing , and computer vision ) .
In this paper , the approach to the development of deductive assistance based on the current state of the System for Automated Deduction , SAD , is described briefly . The SAD may be considered as a three-dimensional " shell " for deductive assistance in a formal natural language environment when solving a number of scientific and industrial tasks requiring automated theorem proving , verification of formal texts , construction of knowledge bases for formalized theories , integration of symbolic calculation with deduction , and so on
Nowadays plasma has become of great importance in both scientific and industrial areas since nanostructures , used for creating small computational processing devices , are produced by pulse lasers . The Simulation of phenomena such as plasma consumes a big amount of CPUs execution time .
Accurately predicting the dynamics of particulate materials is of importance to numerous scientific and industrial areas with applications ranging across particle scales from powder flow to ore crushing . Computational discrete element simulations is a viable option to aid in the understanding of particulate dynamics and design of devices such as mixers , silos and ball mills , as laboratory scale tests comes at a significant cost .
An error less than 0.005 % was obtained for these values during conversion time of 100 μs ( 40 clock cycles ) . The results obtained make it possible to manufacture analog-to-digital functional converters with increased accuracy and speed , applicable for various industrial and scientific tasks . A special feature is the possibility of user 's choice of the required accuracy and speed , even before the start of conversion .
Three-dimensional ( 3-D ) image segmentation is one of the most demanding tasks in image processing . The applications comprise industrial and scientific tasks . Due to the high data volume , advanced algorithms can not be processed on standard hardware in real time .
3D image segmentation is one of the most demanding tasks in image processing . The applications comprise industrial and scientific tasks . Due to the high data volume advanced algorithms can not be processed on standard hardware in real time .
Simulation of Mobile Ad-hoc NETworks ( MANETs ) , designed for civil and or military use is particularly challenging , due to high number of nodes , different mobility and channel models and different types of traffic and QoS requirements , and led to the design of several network simulators . Among them , OMNeT++ , OPNET and ns-3 are arguably the most popular ones for scientific and industrial activities . Each of the above simulators is characterized by specific advantages and drawbacks , as well as different available models .
Autonomous systems like self-driving cars , unmanned aerial and marine vehicles , smart robots etc . , are rapidly emerging in scientific and industrial sectors for mission-critical applications , in recent times . Critical systems are developed using component-based software engineering paradigm by most of the software developers .
Abstract We study non-preemptive scheduling problems where heterogeneous projects stochastically arrive over time . The projects include precedence-constrained tasks that require multiple resources .
Consequently , a new iteration was launched until obtaining the best multi- tenant software scheduling results . The results from experiments show that performances of this proposed method for multi- tenant scheduling are superior to traditional methods at run time , the efficiency of the resource utilization and the number of users . This method has strong capabilities for multi- tenant software scheduling and provides a scientific basis for the multi- tenant software scheduling optimization .
Since its introduction , it has been deployed in production and extended to support use cases beyond large-scale batch processing . The tutorial will present the active research and development supporting such heterogeneous workloads , with particular attention to multi-tenant scheduling . Topics include security , resource isolation , protocols , and preemption .
This book comprehensively illustrates quality-ware scheduling in key-value stores . In addition , it provides scheduling strategies and a prototype framework of quality-aware scheduler as well as a demonstration of online applications .
Additionally , we provide evidence for the practical relevance of these theoretical findings through extensive numerical experiments . Finally , we present a case study in which the benefits of offering assortments in stages are explored and exploited within the context of dynamically scheduling restaurant reservations . For this purpose , we make use of historical reservation data from a fine-dining Michelin starred restaurant to build a realistic simulation of their booking process .
We propose a set of scheduling procedures for dealing with the sporadic task scheduling in a dynamic periodic system . For this we mean a system in which periodic tasks change their parameters dynamically ( at run-time ) , in an unpredictable way .
How Long Does a Bit Live in a Computer?.- Approximation Algorithms for the Traveling Purchaser Problem and Its Variants in Network Design.- The Impact of Knowledge on Broadcasting Time in Radio Networks.- Multipacket Routing on 2-D Meshes and Its Application to Fault-Tolerant Routing.- IP Address LookupMade Fast and Simple.- On-Line Load Balancing in a Hierarchical Server Topology.- Provably Good and Practical Strategies for Non-uniform Data Management in Networks.- Approximation Algorithms for Restoration Capacity Planning.- Efficient Algorithms for Integer Programs with Two Variables per Constraint.- Convex Quadratic Programming Relaxations for Network Scheduling Problems.- Resource-Constrained Project Scheduling : Computing Lower Bounds by Solving Minimum Cut Problems.- Approximation Schemes for Scheduling on Uniformly Related and Identical Parallel Machines.- Off-Line Temporary Tasks Assignment.- Load Balancing Using Bisectors - A Tight Average-Case Analysis.-
Based on the CGLP formulation , we present a mixed-integer formulation that determines if such an equivalence exists and we report computational results on several instances where many cuts from elementary t-branch disjunctions are not equivalent to cuts from t rows of the simplex tableau . The last area is an emergent scheduling application , in which we study a last-mile passenger transportation service using autonomous vehicles . Our contribution consists of an approach to solve this optimization problem within the required time frame .
Currently , academia and technology corporations are leading the way in research and implementation , working in distinct fields such as natural language processing and object recognition . There has been enormous progress , as AI , supported by deep learning [ 1 ] , is very good at completing a discrete task such as scheduling an appointment [ 2 ] . But it ’s not capable of completing a more general intellectual task , such as knowing how and when to reschedule the appointment in the event of more urgent matters .
A DMC model demonstrates the impact of task allocation on ASP M-P architectures . Five application-specific heuristics and four static-labelling schemes are developed for scheduling console taskforces on M-Ps . An integrated research framework and DCS engine enable scheduling strategies to be analysed with regard to the DMC problem domain .
Examples of applications enabled by this technology include interactive ads , interactive access to sports statistics during sports events , and interactive access to supplementary information during talk shows , news programs , documentaries , etc . This paper describes the basic technology for such enhanced DTV programming , and analyzes the architectural and scheduling issues that arise in connection with inserting data into the digital broadcast stream to support it . The primary focus is on so-called ATVEF ( Advanced Television Enhancement Forum ) applications in the context of the ATSC digital television standards , but most of the analysis applies equally well to other forms of enhanced DTV programming where data must be coordinated with the audio-video .
Distributed data mining(DDM ) is widely used in industrial , scientific and commercial applications to analyze large datasets maintained over geographically distributed sites , which makes DDM a major research issue on(today 's ) data mining field . This paper discusses the disadvantages of existing DDM systems , puts forward a service-oriented architecture for DDM on the grid and describe the process of mining under this framework .
Micro/nano positioning technologies have been attractive for decades in industrial and scientific applications fields . The actuators have inherent hysteresis that can cause system unexpected behave in some extend .
Abstract X-ray micro computed tomography ( microCT ) is a high resolution non-destructive materials imaging technology and is emerging as a powerful tool for industrial and scientific research applications . The aim of this review paper is to present the capabilities and potential of this technique within an African context .
This topic aims at the development , implementation and experience of real industrial , engineering and scientific applications on parallel and distributed systems .
The robot has a payload area to allow the integration of different equipment depending on the devices and systems . Its flexibility , easy operation and openness makes the SPARUS II AUV a multipurpose platform that can adapt to industrial , scientific and academic applications . Five units were developed in 2014 , and different teams used and adapted the platform for different applications .
The totality of the results presented in this thesis represent a significant addition to the open source data pool and have advanced the state of the art in the understanding of dynamic signatures from rotating cylinders . The results are shown to have relevance to a variety of defence and industrial scientific applications and will therefore be of interest to a wide audience . Finally a new Doppler-surface mapping ( D-map ) methodology is given that provides a mechanism to discriminate between targets with differing electrical ( material ) properties or surface roughness characteristics .
CajAstur and the Foundation for the Advancement of Soft Computing , through the European Centre for Soft Computing , announce the Sixth edition of their International Prize for Soft Computing . The CAJASTUR " MAMDANI PRIZE ' ' FOR SOFT COMPUTING is meant to distinguish a person or group of persons for the realization of a relevant scientific or industrial application , meaning an original contribution in the area of Soft Computing .
Modern parallel file system architectures however , span a large and complex design space . As a result , IT architects are faced with a challenge when deciding on the most appropriate parallel file system for a specific scientific or industrial application in a large-scale computing installation . Typically , the right choice depends on the characteristics of the application as well as the design assumptions built into a parallel file system .
The Mathematical Foundations of 3D Compton Scatter Emission Imaging Comparing methods for analysis of biomedical hyperspectral image data Learning Data Augmentation for Brain Tumor Segmentation with Coarse-to-Fine Generative Adversarial Networks Processing and Visual Analyze of Heterogeneous and Multidimensional Data in Biomedical PLM Context A Review of Algorithms for Segmentation of Retinal Image Data Using Optical Coherence Tomography A lightweight rapid application development framework for biomedical image analysis Mitigating the Effect of Dataset Bias on Training Deep Models for Chest X-rays ECE590 Graduate Seminar Mathematical Methods in Biomedical Imaging 2014 Minimally invasive diagnostic imaging using high resolution Optical Coherence Tomography Shape-based nonrigid correspondence with application to heart motion analysis SEGMENTATION BY ACTIVE CONTOURS AND LEVEL SETS AND ITS APPLICATION IN MEDICAL IMAGES Integrator with p-channel depletion MOS switch Adaptive speed of sound correction with photoacoustic tomography for imaging quality optimization Mobility based network lifetime in wireless sensor networks: A review Numerical Investigation of Parallel-in-Time Methods for Dominantly Hyperbolic Equations Single-wall carbon nanotubes based near-infrared sensors on flexible substrate Interactive parallel post-processing of simulation results on unstructured grids Using the FOCUS architecture for developing knowledge-based front ends: a KBFE for forecasting Distributed Data Mining Based on Knowledge Grid A Middleware for OSCAR and Wireless Sensor Network Environments Topic 16 Applications of High-Performance and Grid Computing Query Optimization in Heterogeneous CPU/GPU Environment for Time Series Databases Improvement of non-linear mapping computation for dimensionality reduction in data visualization and classification A new conceptual basis for the development of the information activities of the All-Russian Institute for Scientific and Technical Information of the Russian Academy of Sciences Framework for Knowledge-Based Integrative Analysis of Microarray Data Keynote Speech: Technological Breakthroughs in Environmental Sensor Networks Hydro-MiNa Robot Technology for Micro- and Nano- Manipulation in Manufacturing of Micro-Products Computationally efficient algorithms for robust estimation The SAD System in Three Dimensions Semi-Lagrangian implementation method using GPU BlazeDEM3D-GPU A Large Scale DEM simulation code for GPUs Development of algorithms for improving the accuracy and performance speed of a functional analog­to­digital converter FPGA-Based Real-Time Image Segmentation for Medical Systems and Data Processing FPGA based real-time image segmentation for medical systems and data processing A novel architecture for a framework to support the storage of network simulation data into distributed storages for remote access Dynamic Software Component Authentication for Autonomous Systems using Slack space Approximate policy iteration for dynamic resource-constrained project scheduling Simulation on Multi-tenant Software Ooptimization Scheduling under Cloud Computing Environment Blind men and an elephant coalescing open-source, academic, and industrial perspectives on BigData Quality-aware Scheduling for Key-value Data Stores Improved Approximation Schemes for MNL-Driven Sequential Assortment Optimization On-line sporadic task scheduling in hard real-time systems Algorithms - ESA'99: 7th Annual European Symposium, Prague, Czech Republic, July 16-18, 1999 Proceedings Essays on Postoptimality, Lift-and-Project, and Scheduling Design and fiction: imagining civic AI Digital mixing consoles : parallel architectures and taskforce scheduling strategies Serving up Data for Enhanced DTV Programs Distributed Data Mining on the Grid Simulation and Experiment Based on FSMLC Method with EUPI Hysteresis Compensation for a Piezo-Driven Micro Position Stage Advancing X-ray micro computed tomography in Africa: Going far, together High-Performance Computing and Applications - Introduction Testing SPARUS II AUV, an open platform for industrial, scientific and academic applications Doppler signatures from canonical rotating targets CajAstur "Mamdani" Prize for Soft Computing A Comparative Experimental Study of Parallel File Systems for Large-Scale Data Processing
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PLM ICECS SSD HPCS Euro-Par HIS IJCBS APWeb Workshops SYNASC SimuTools ICDE RTS LASCO
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