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Ernesto Cuadros Vargas
Feb 1, 2019, 2:41:33 PM2/1/19
to Sociedad Peruana de Computacion, cs-...@googlegroups.com, cs-utec-faculty, cs-...@googlegroups.com, Ciencia de la Computacion UNSA, School of Computer Science-Professors, School of Computer Science, Maestria UCSP, EPIS UNSA
estimados,
Van algunos temas de tesis útiles para todos en la comunidad de la SPC.
Saludos
er
You have received this message because you subscribed to the ACM Computing Surveys (CSUR) Table of Contents Service within the ACM Digital Library.
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ACM Computing Surveys (CSUR) Volume 52 Issue 1, January 2019 (Issue-in-Progress)
http://dl.acm.org/citation.cfm?id=3309872
Brownout Approach for Adaptive Management of Resources and Applications in Cloud Computing Systems: A Taxonomy and Future Directions
http://dl.acm.org/citation.cfm?id=3234151
Minxian Xu, Rajkumar Buyya
Cloud computing has been regarded as an emerging approach to provisioning resources and managing applications. It provides attractive features, such as an on-demand model, scalability enhancement, and management cost reduction. However, cloud computing systems continue to face problems such as hardware failures, overloads caused by unexpected workloads, or the waste of energy due to inefficient resource utilization, which all result in resource shortages and application issues such as delays or saturation. A paradigm, the brownout, has been applied to handle these issues by adaptively activating or deactivating optional parts of applications or services to manage resource usage in cloud computing system.
A Survey on Bayesian Nonparametric Learning
http://dl.acm.org/citation.cfm?id=3291044
Junyu Xuan, Jie Lu, Guangquan Zhang
Bayesian (machine) learning has been playing a significant role in machine learning for a long time due to its particular ability to embrace uncertainty, encode prior knowledge, and endow interpretability. On the back of Bayesian learning’s great success, Bayesian nonparametric learning (BNL) has emerged as a force for further advances in this field due to its greater modelling flexibility and representation power. Instead of playing with the fixed-dimensional probabilistic distributions of Bayesian learning, BNL creates a new “game” with infinite-dimensional stochastic processes. BNL has long been recognised as a research subject in statistics, and, to date, several state-of-the-art pilot studies have demonstrated that BNL has a great deal of potential to solve real-world machine-learning tasks.
ACM Computing Surveys (CSUR) Volume 51 Issue 6, January 2019 (Issue-in-Progress)
http://dl.acm.org/citation.cfm?id=3303862
A Survey of Communication Performance Models for High-Performance Computing
http://dl.acm.org/citation.cfm?id=3284358
Juan A. Rico-Gallego, Juan C. Díaz-Martín, Ravi Reddy Manumachu, Alexey L. Lastovetsky
This survey aims to present the state of the art in analytic communication performance models, providing sufficiently detailed descriptions of particularly noteworthy efforts. Modeling the cost of communications in computer clusters is an important and challenging problem. It provides insights into the design of the communication pattern of parallel scientific applications and mathematical kernels and sets a clear ground for optimization of their deployment in the increasingly complex high-performance computing infrastructure. The survey provides background information on how different performance models represent the underlying platform and shows the evolution of these models over time from early clusters of single-core processors to present-day multi-core and heterogeneous platforms.
If you would like to unsubcribe or change your email address please go to http://dl.acm.org/toc_manage.cfm and sign in with your ACM Web Account.
To send comments about ACM's TOC Service, email: tocse...@acm.org
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From: <tocse...@acm.org>
Date: Fri, Jan 25, 2019 at 6:01 PM
Subject: TOC Service - ACM Computing Surveys (CSUR)
To: <ecua...@spc.org.pe>
From: <tocse...@acm.org>
Date: Fri, Jan 25, 2019 at 6:01 PM
Subject: TOC Service - ACM Computing Surveys (CSUR)
To: <ecua...@spc.org.pe>
You have received this message because you subscribed to the ACM Computing Surveys (CSUR) Table of Contents Service within the ACM Digital Library.
An RSS feed for this Table of Contents Services is available - http://rss.acm.org/dl/J204.xml
ACM Computing Surveys (CSUR) Volume 52 Issue 1, January 2019 (Issue-in-Progress)
http://dl.acm.org/citation.cfm?id=3309872
Brownout Approach for Adaptive Management of Resources and Applications in Cloud Computing Systems: A Taxonomy and Future Directions
http://dl.acm.org/citation.cfm?id=3234151
Minxian Xu, Rajkumar Buyya
Cloud computing has been regarded as an emerging approach to provisioning resources and managing applications. It provides attractive features, such as an on-demand model, scalability enhancement, and management cost reduction. However, cloud computing systems continue to face problems such as hardware failures, overloads caused by unexpected workloads, or the waste of energy due to inefficient resource utilization, which all result in resource shortages and application issues such as delays or saturation. A paradigm, the brownout, has been applied to handle these issues by adaptively activating or deactivating optional parts of applications or services to manage resource usage in cloud computing system.
A Survey on Bayesian Nonparametric Learning
http://dl.acm.org/citation.cfm?id=3291044
Junyu Xuan, Jie Lu, Guangquan Zhang
Bayesian (machine) learning has been playing a significant role in machine learning for a long time due to its particular ability to embrace uncertainty, encode prior knowledge, and endow interpretability. On the back of Bayesian learning’s great success, Bayesian nonparametric learning (BNL) has emerged as a force for further advances in this field due to its greater modelling flexibility and representation power. Instead of playing with the fixed-dimensional probabilistic distributions of Bayesian learning, BNL creates a new “game” with infinite-dimensional stochastic processes. BNL has long been recognised as a research subject in statistics, and, to date, several state-of-the-art pilot studies have demonstrated that BNL has a great deal of potential to solve real-world machine-learning tasks.
ACM Computing Surveys (CSUR) Volume 51 Issue 6, January 2019 (Issue-in-Progress)
http://dl.acm.org/citation.cfm?id=3303862
A Survey of Communication Performance Models for High-Performance Computing
http://dl.acm.org/citation.cfm?id=3284358
Juan A. Rico-Gallego, Juan C. Díaz-Martín, Ravi Reddy Manumachu, Alexey L. Lastovetsky
This survey aims to present the state of the art in analytic communication performance models, providing sufficiently detailed descriptions of particularly noteworthy efforts. Modeling the cost of communications in computer clusters is an important and challenging problem. It provides insights into the design of the communication pattern of parallel scientific applications and mathematical kernels and sets a clear ground for optimization of their deployment in the increasingly complex high-performance computing infrastructure. The survey provides background information on how different performance models represent the underlying platform and shows the evolution of these models over time from early clusters of single-core processors to present-day multi-core and heterogeneous platforms.
If you would like to unsubcribe or change your email address please go to http://dl.acm.org/toc_manage.cfm and sign in with your ACM Web Account.
To send comments about ACM's TOC Service, email: tocse...@acm.org
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Ernesto Cuadros Vargas
Feb 1, 2019, 9:32:19 PM2/1/19
to Sociedad Peruana de Computacion, cs-utec-faculty, cs-...@googlegroups.com, Ciencia de la Computacion UNSA, School of Computer Science-Professors, School of Computer Science, cs-...@googlegroups.com, Maestria UCSP, EPIS UNSA
Estimados,
aqui va una lista extendida de temas de tesis para todos los niveles ...
Saludos
er
---------- Forwarded message ---------
From: <tocse...@acm.org>
Date: Mon, Jan 28, 2019 at 6:04 PM
Subject: TOC Service - ACM Computing Surveys (CSUR)
To: <ecua...@spc.org.pe>
From: <tocse...@acm.org>
Date: Mon, Jan 28, 2019 at 6:04 PM
Subject: TOC Service - ACM Computing Surveys (CSUR)
To: <ecua...@spc.org.pe>
You have received this message because you subscribed to the ACM Computing Surveys (CSUR) Table of Contents Service within the ACM Digital Library.
An RSS feed for this Table of Contents Services is available - http://rss.acm.org/dl/J204.xml
ACM Computing Surveys (CSUR) Volume 51 Issue 6, January 2019 (Issue-in-Progress)
http://dl.acm.org/citation.cfm?id=3303862
http://dl.acm.org/citation.cfm?id=3303862
Towards the Decentralised Cloud: Survey on Approaches and Challenges for Mobile, Ad hoc, and Edge Computing
http://dl.acm.org/citation.cfm?id=3243929
Ana Juan Ferrer, Joan Manuel Marquès, Josep Jorba
Cloud computing emerged as a centralised paradigm that made “infinite” computing resources available on demand. Nevertheless, the ever-increasing computing capacities present on smart connected things and devices calls for the decentralisation of Cloud computing to avoid unnecessary latencies and fully exploit accessible computing capacities at the edges of the network. Whilst these decentralised Cloud models represent a significant breakthrough from a Cloud perspective, they are rooted in existing research areas such as Mobile Cloud Computing, Mobile Ad hoc Computing, and Edge computing. This article analyses the pre-existing works to determine their role in Decentralised Cloud and future computing development.
“Dave...I can assure you ...that it’s going to be all right ...” A Definition, Case for, and Survey of Algorithmic Assurances in Human-Autonomy Trust Relationships
http://dl.acm.org/citation.cfm?id=3267338
Brett W. Israelsen, Nisar R. Ahmed
People who design, use, and are affected by autonomous artificially intelligent agents want to be able to trust such agents—that is, to know that these agents will perform correctly, to understand the reasoning behind their actions, and to know how to use them appropriately. Many techniques have been devised to assess and influence human trust in artificially intelligent agents. However, these approaches are typically ad hoc and have not been formally related to each other or to formal trust models. This article presents a survey of algorithmic assurances, i.e., programmed components of agent operation that are expressly designed to calibrate user trust in artificially intelligent agents.
A Survey of On-Chip Optical Interconnects
http://dl.acm.org/citation.cfm?id=3267934
Janibul Bashir, Eldhose Peter, Smruti R. Sarangi
Numerous challenges present themselves when scaling traditional on-chip electrical networks to large manycore processors. Some of these challenges include high latency, limitations on bandwidth, and power consumption. Researchers have therefore been looking for alternatives. As a result, on-chip nanophotonics has emerged as a strong substitute for traditional electrical NoCs. As of 2017, on-chip optical networks have moved out of textbooks and found commercial applicability in short-haul networks such as links between servers on the same rack or between two components on the motherboard. It is widely acknowledged that in the near future, optical technologies will move beyond research prototypes and find their way into the chip.
A Survey of Communication Protocols for Internet of Things and Related Challenges of Fog and Cloud Computing Integration
http://dl.acm.org/citation.cfm?id=3292674
Jasenka Dizdarević, Francisco Carpio, Admela Jukan, Xavi Masip-Bruin
The fast increment in the number of IoT (Internet of Things) devices is accelerating the research on new solutions to make cloud services scalable. In this context, the novel concept of fog computing as well as the combined fog-to-cloud computing paradigm is becoming essential to decentralize the cloud, while bringing the services closer to the end-system. This article surveys e application layer communication protocols to fulfill the IoT communication requirements, and their potential for implementation in fog- and cloud-based IoT systems. To this end, the article first briefly presents potential protocol candidates, including request-reply and publish-subscribe protocols. After that, the article surveys these protocols based on their main characteristics, as well as the main performance issues, including latency, energy consumption, and network throughput.
A Perspective Analysis of Handwritten Signature Technology
http://dl.acm.org/citation.cfm?id=3274658
Moises Diaz, Miguel A. Ferrer, Donato Impedovo, Muhammad Imran Malik, Giuseppe Pirlo, Réjean Plamondon
Handwritten signatures are biometric traits at the center of debate in the scientific community. Over the last 40 years, the interest in signature studies has grown steadily, having as its main reference the application of automatic signature verification, as previously published reviews in 1989, 2000, and 2008 bear witness. Ever since, and over the last 10 years, the application of handwritten signature technology has strongly evolved and much research has focused on the possibility of applying systems based on handwritten signature analysis and processing to a multitude of new fields. After several years of haphazard growth of this research area, it is time to assess its current developments for their applicability in order to draw a structured way forward.
Cloud Brokerage: A Systematic Survey
http://dl.acm.org/citation.cfm?id=3274657
Abdessalam Elhabbash, Faiza Samreen, James Hadley, Yehia Elkhatib
Background—The proliferation of cloud services has opened a space for cloud brokerage services. Brokers intermediate between cloud customers and providers to assist the customer in selecting the most suitable service, helping to manage the dimensionality, heterogeneity, and uncertainty associated with cloud services. Objective—Unlike other surveys, this survey focuses on the customer perspective. The survey systematically analyses the literature to identify and classify approaches to realise cloud brokerage, presenting an understanding of the state-of-the-art and a novel taxonomy to characterise cloud brokers. Method—A systematic literature survey was conducted to compile studies related to cloud brokerage and explore how cloud brokers are engineered.
Recent Developments in Cartesian Genetic Programming and its Variants
http://dl.acm.org/citation.cfm?id=3275518
Abdul Manazir, Khalid Raza
Cartesian Genetic Programming (CGP) is a variant of Genetic Programming with several advantages. During the last one and a half decades, CGP has been further extended to several other forms with lots of promising advantages and applications. This article formally discusses the classical form of CGP and its six different variants proposed so far, which include Embedded CGP, Self-Modifying CGP, Recurrent CGP, Mixed-Type CGP, Balanced CGP, and Differential CGP. Also, this article makes a comparison among these variants in terms of population representations, various constraints in representation, operators and functions applied, and algorithms used.
Parallel Computing of Support Vector Machines: A Survey
http://dl.acm.org/citation.cfm?id=3280989
Shirin Tavara
The immense amount of data created by digitalization requires parallel computing for machine-learning methods. While there are many parallel implementations for support vector machines (SVMs), there is no clear suggestion for every application scenario. Many factor—including optimization algorithm, problem size and dimension, kernel function, parallel programming stack, and hardware architecture—impact the efficiency of implementations. It is up to the user to balance trade-offs, particularly between computation time and classification accuracy. In this survey, we review the state-of-the-art implementations of SVMs, their pros and cons, and suggest possible avenues for future research.
Synthesis of Facial Expressions in Photographs: Characteristics, Approaches, and Challenges
http://dl.acm.org/citation.cfm?id=3292652
Rafael Luiz Testa, Cléber Gimenez Corrêa, Ariane Machado-Lima, Fátima L. S. Nunes
The synthesis of facial expressions has applicationsin areas such as interactive games, biometrics systems, and training of people with disorders, among others. Although this is an area relatively well explored in the literature, there are no recent studies proposing to systematize an overview of research in the area. This systematic review analyzes the approaches to the synthesis of facial expressions in photographs, as well as important aspects of the synthesis process, such as preprocessing techniques, databases, and evaluation metrics. Forty-eight studies from three different scientific databases were analyzed. From these studies, we established an overview of the process, including all the stages used to synthesize expressions in facial images.
Linked Vocabulary Recommendation Tools for Internet of Things: A Survey
http://dl.acm.org/citation.cfm?id=3284316
Niklas Kolbe, Sylvain Kubler, Jérémy Robert, Yves Le Traon, Arkady Zaslavsky
The Semantic Web emerged with the vision of eased integration of heterogeneous, distributed data on the Web. The approach fundamentally relies on the linkage between and reuse of previously published vocabularies to facilitate semantic interoperability. In recent years, the Semantic Web has been perceived as a potential enabling technology to overcome interoperability issues in the Internet of Things (IoT), especially for service discovery and composition. Despite the importance of making vocabulary terms discoverable and selecting the most suitable ones in forthcoming IoT applications, no state-of-the-art survey of tools achieving such recommendation tasks exists to date. This survey covers this gap by specifying an extensive evaluation framework and assessing linked vocabulary recommendation tools.
Post-Quantum Lattice-Based Cryptography Implementations: A Survey
http://dl.acm.org/citation.cfm?id=3292548
Hamid Nejatollahi, Nikil Dutt, Sandip Ray, Francesco Regazzoni, Indranil Banerjee, Rosario Cammarota
The advent of quantum computing threatens to break many classical cryptographic schemes, leading to innovations in public key cryptography that focus on post-quantum cryptography primitives and protocols resistant to quantum computing threats. Lattice-based cryptography is a promising post-quantum cryptography family, both in terms of foundational properties as well as in its application to both traditional and emerging security problems such as encryption, digital signature, key exchange, and homomorphic encryption. While such techniques provide guarantees, in theory, their realization on contemporary computing platforms requires careful design choices and tradeoffs to manage both the diversity of computing platforms (e.g., high-performance to resource constrained), as well as the agility for deployment in the face of emerging and changing standards.
Demystifying Arm TrustZone: A Comprehensive Survey
http://dl.acm.org/citation.cfm?id=3291047
Sandro Pinto, Nuno Santos
The world is undergoing an unprecedented technological transformation, evolving into a state where ubiquitous Internet-enabled “things” will be able to generate and share large amounts of security- and privacy-sensitive data. To cope with the security threats that are thus foreseeable, system designers can find in Arm TrustZone hardware technology a most valuable resource. TrustZone is a System-on-Chip and CPU system-wide security solution, available on today’s Arm application processors and present in the new generation Arm microcontrollers, which are expected to dominate the market of smart “things.” Although this technology has remained relatively underground since its inception in 2004, over the past years, numerous initiatives have significantly advanced the state of the art involving Arm TrustZone.
A Survey on Agent-based Simulation Using Hardware Accelerators
http://dl.acm.org/citation.cfm?id=3291048
Jiajian Xiao, Philipp Andelfinger, David Eckhoff, Wentong Cai, Alois Knoll
Due to decelerating gains in single-core CPU performance, computationally expensive simulations are increasingly executed on highly parallel hardware platforms. Agent-based simulations, where simulated entities act with a certain degree of autonomy, frequently provide ample opportunities for parallelisation. Thus, a vast variety of approaches proposed in the literature demonstrated considerable performance gains using hardware platforms such as many-core CPUs and GPUs, merged CPU-GPU chips as well as Field Programmable Gate Arrays. Typically, a combination of techniques is required to achieve high performance for a given simulation model, putting substantial burden on modellers. To the best of our knowledge, no systematic overview of techniques for agent-based simulations on hardware accelerators has been given in the literature.
http://dl.acm.org/citation.cfm?id=3243929
Ana Juan Ferrer, Joan Manuel Marquès, Josep Jorba
Cloud computing emerged as a centralised paradigm that made “infinite” computing resources available on demand. Nevertheless, the ever-increasing computing capacities present on smart connected things and devices calls for the decentralisation of Cloud computing to avoid unnecessary latencies and fully exploit accessible computing capacities at the edges of the network. Whilst these decentralised Cloud models represent a significant breakthrough from a Cloud perspective, they are rooted in existing research areas such as Mobile Cloud Computing, Mobile Ad hoc Computing, and Edge computing. This article analyses the pre-existing works to determine their role in Decentralised Cloud and future computing development.
“Dave...I can assure you ...that it’s going to be all right ...” A Definition, Case for, and Survey of Algorithmic Assurances in Human-Autonomy Trust Relationships
http://dl.acm.org/citation.cfm?id=3267338
Brett W. Israelsen, Nisar R. Ahmed
People who design, use, and are affected by autonomous artificially intelligent agents want to be able to trust such agents—that is, to know that these agents will perform correctly, to understand the reasoning behind their actions, and to know how to use them appropriately. Many techniques have been devised to assess and influence human trust in artificially intelligent agents. However, these approaches are typically ad hoc and have not been formally related to each other or to formal trust models. This article presents a survey of algorithmic assurances, i.e., programmed components of agent operation that are expressly designed to calibrate user trust in artificially intelligent agents.
A Survey of On-Chip Optical Interconnects
http://dl.acm.org/citation.cfm?id=3267934
Janibul Bashir, Eldhose Peter, Smruti R. Sarangi
Numerous challenges present themselves when scaling traditional on-chip electrical networks to large manycore processors. Some of these challenges include high latency, limitations on bandwidth, and power consumption. Researchers have therefore been looking for alternatives. As a result, on-chip nanophotonics has emerged as a strong substitute for traditional electrical NoCs. As of 2017, on-chip optical networks have moved out of textbooks and found commercial applicability in short-haul networks such as links between servers on the same rack or between two components on the motherboard. It is widely acknowledged that in the near future, optical technologies will move beyond research prototypes and find their way into the chip.
A Survey of Communication Protocols for Internet of Things and Related Challenges of Fog and Cloud Computing Integration
http://dl.acm.org/citation.cfm?id=3292674
Jasenka Dizdarević, Francisco Carpio, Admela Jukan, Xavi Masip-Bruin
The fast increment in the number of IoT (Internet of Things) devices is accelerating the research on new solutions to make cloud services scalable. In this context, the novel concept of fog computing as well as the combined fog-to-cloud computing paradigm is becoming essential to decentralize the cloud, while bringing the services closer to the end-system. This article surveys e application layer communication protocols to fulfill the IoT communication requirements, and their potential for implementation in fog- and cloud-based IoT systems. To this end, the article first briefly presents potential protocol candidates, including request-reply and publish-subscribe protocols. After that, the article surveys these protocols based on their main characteristics, as well as the main performance issues, including latency, energy consumption, and network throughput.
A Perspective Analysis of Handwritten Signature Technology
http://dl.acm.org/citation.cfm?id=3274658
Moises Diaz, Miguel A. Ferrer, Donato Impedovo, Muhammad Imran Malik, Giuseppe Pirlo, Réjean Plamondon
Handwritten signatures are biometric traits at the center of debate in the scientific community. Over the last 40 years, the interest in signature studies has grown steadily, having as its main reference the application of automatic signature verification, as previously published reviews in 1989, 2000, and 2008 bear witness. Ever since, and over the last 10 years, the application of handwritten signature technology has strongly evolved and much research has focused on the possibility of applying systems based on handwritten signature analysis and processing to a multitude of new fields. After several years of haphazard growth of this research area, it is time to assess its current developments for their applicability in order to draw a structured way forward.
Cloud Brokerage: A Systematic Survey
http://dl.acm.org/citation.cfm?id=3274657
Abdessalam Elhabbash, Faiza Samreen, James Hadley, Yehia Elkhatib
Background—The proliferation of cloud services has opened a space for cloud brokerage services. Brokers intermediate between cloud customers and providers to assist the customer in selecting the most suitable service, helping to manage the dimensionality, heterogeneity, and uncertainty associated with cloud services. Objective—Unlike other surveys, this survey focuses on the customer perspective. The survey systematically analyses the literature to identify and classify approaches to realise cloud brokerage, presenting an understanding of the state-of-the-art and a novel taxonomy to characterise cloud brokers. Method—A systematic literature survey was conducted to compile studies related to cloud brokerage and explore how cloud brokers are engineered.
Recent Developments in Cartesian Genetic Programming and its Variants
http://dl.acm.org/citation.cfm?id=3275518
Abdul Manazir, Khalid Raza
Cartesian Genetic Programming (CGP) is a variant of Genetic Programming with several advantages. During the last one and a half decades, CGP has been further extended to several other forms with lots of promising advantages and applications. This article formally discusses the classical form of CGP and its six different variants proposed so far, which include Embedded CGP, Self-Modifying CGP, Recurrent CGP, Mixed-Type CGP, Balanced CGP, and Differential CGP. Also, this article makes a comparison among these variants in terms of population representations, various constraints in representation, operators and functions applied, and algorithms used.
Parallel Computing of Support Vector Machines: A Survey
http://dl.acm.org/citation.cfm?id=3280989
Shirin Tavara
The immense amount of data created by digitalization requires parallel computing for machine-learning methods. While there are many parallel implementations for support vector machines (SVMs), there is no clear suggestion for every application scenario. Many factor—including optimization algorithm, problem size and dimension, kernel function, parallel programming stack, and hardware architecture—impact the efficiency of implementations. It is up to the user to balance trade-offs, particularly between computation time and classification accuracy. In this survey, we review the state-of-the-art implementations of SVMs, their pros and cons, and suggest possible avenues for future research.
Synthesis of Facial Expressions in Photographs: Characteristics, Approaches, and Challenges
http://dl.acm.org/citation.cfm?id=3292652
Rafael Luiz Testa, Cléber Gimenez Corrêa, Ariane Machado-Lima, Fátima L. S. Nunes
The synthesis of facial expressions has applicationsin areas such as interactive games, biometrics systems, and training of people with disorders, among others. Although this is an area relatively well explored in the literature, there are no recent studies proposing to systematize an overview of research in the area. This systematic review analyzes the approaches to the synthesis of facial expressions in photographs, as well as important aspects of the synthesis process, such as preprocessing techniques, databases, and evaluation metrics. Forty-eight studies from three different scientific databases were analyzed. From these studies, we established an overview of the process, including all the stages used to synthesize expressions in facial images.
Linked Vocabulary Recommendation Tools for Internet of Things: A Survey
http://dl.acm.org/citation.cfm?id=3284316
Niklas Kolbe, Sylvain Kubler, Jérémy Robert, Yves Le Traon, Arkady Zaslavsky
The Semantic Web emerged with the vision of eased integration of heterogeneous, distributed data on the Web. The approach fundamentally relies on the linkage between and reuse of previously published vocabularies to facilitate semantic interoperability. In recent years, the Semantic Web has been perceived as a potential enabling technology to overcome interoperability issues in the Internet of Things (IoT), especially for service discovery and composition. Despite the importance of making vocabulary terms discoverable and selecting the most suitable ones in forthcoming IoT applications, no state-of-the-art survey of tools achieving such recommendation tasks exists to date. This survey covers this gap by specifying an extensive evaluation framework and assessing linked vocabulary recommendation tools.
Post-Quantum Lattice-Based Cryptography Implementations: A Survey
http://dl.acm.org/citation.cfm?id=3292548
Hamid Nejatollahi, Nikil Dutt, Sandip Ray, Francesco Regazzoni, Indranil Banerjee, Rosario Cammarota
The advent of quantum computing threatens to break many classical cryptographic schemes, leading to innovations in public key cryptography that focus on post-quantum cryptography primitives and protocols resistant to quantum computing threats. Lattice-based cryptography is a promising post-quantum cryptography family, both in terms of foundational properties as well as in its application to both traditional and emerging security problems such as encryption, digital signature, key exchange, and homomorphic encryption. While such techniques provide guarantees, in theory, their realization on contemporary computing platforms requires careful design choices and tradeoffs to manage both the diversity of computing platforms (e.g., high-performance to resource constrained), as well as the agility for deployment in the face of emerging and changing standards.
Demystifying Arm TrustZone: A Comprehensive Survey
http://dl.acm.org/citation.cfm?id=3291047
Sandro Pinto, Nuno Santos
The world is undergoing an unprecedented technological transformation, evolving into a state where ubiquitous Internet-enabled “things” will be able to generate and share large amounts of security- and privacy-sensitive data. To cope with the security threats that are thus foreseeable, system designers can find in Arm TrustZone hardware technology a most valuable resource. TrustZone is a System-on-Chip and CPU system-wide security solution, available on today’s Arm application processors and present in the new generation Arm microcontrollers, which are expected to dominate the market of smart “things.” Although this technology has remained relatively underground since its inception in 2004, over the past years, numerous initiatives have significantly advanced the state of the art involving Arm TrustZone.
A Survey on Agent-based Simulation Using Hardware Accelerators
http://dl.acm.org/citation.cfm?id=3291048
Jiajian Xiao, Philipp Andelfinger, David Eckhoff, Wentong Cai, Alois Knoll
Due to decelerating gains in single-core CPU performance, computationally expensive simulations are increasingly executed on highly parallel hardware platforms. Agent-based simulations, where simulated entities act with a certain degree of autonomy, frequently provide ample opportunities for parallelisation. Thus, a vast variety of approaches proposed in the literature demonstrated considerable performance gains using hardware platforms such as many-core CPUs and GPUs, merged CPU-GPU chips as well as Field Programmable Gate Arrays. Typically, a combination of techniques is required to achieve high performance for a given simulation model, putting substantial burden on modellers. To the best of our knowledge, no systematic overview of techniques for agent-based simulations on hardware accelerators has been given in the literature.
A Survey of Communication Performance Models for High-Performance Computing
http://dl.acm.org/citation.cfm?id=3284358
Juan A. Rico-Gallego, Juan C. Díaz-Martín, Ravi Reddy Manumachu, Alexey L. Lastovetsky
This survey aims to present the state of the art in analytic communication performance models, providing sufficiently detailed descriptions of particularly noteworthy efforts. Modeling the cost of communications in computer clusters is an important and challenging problem. It provides insights into the design of the communication pattern of parallel scientific applications and mathematical kernels and sets a clear ground for optimization of their deployment in the increasingly complex high-performance computing infrastructure. The survey provides background information on how different performance models represent the underlying platform and shows the evolution of these models over time from early clusters of single-core processors to present-day multi-core and heterogeneous platforms.
ACM Computing Surveys (CSUR) Volume 52 Issue 1, January 2019 (Issue-in-Progress)
http://dl.acm.org/citation.cfm?id=3309872
Brownout Approach for Adaptive Management of Resources and Applications in Cloud Computing Systems: A Taxonomy and Future Directions
http://dl.acm.org/citation.cfm?id=3234151
Minxian Xu, Rajkumar Buyya
Cloud computing has been regarded as an emerging approach to provisioning resources and managing applications. It provides attractive features, such as an on-demand model, scalability enhancement, and management cost reduction. However, cloud computing systems continue to face problems such as hardware failures, overloads caused by unexpected workloads, or the waste of energy due to inefficient resource utilization, which all result in resource shortages and application issues such as delays or saturation. A paradigm, the brownout, has been applied to handle these issues by adaptively activating or deactivating optional parts of applications or services to manage resource usage in cloud computing system.
A Survey on Bayesian Nonparametric Learning
http://dl.acm.org/citation.cfm?id=3291044
Junyu Xuan, Jie Lu, Guangquan Zhang
Bayesian (machine) learning has been playing a significant role in machine learning for a long time due to its particular ability to embrace uncertainty, encode prior knowledge, and endow interpretability. On the back of Bayesian learning’s great success, Bayesian nonparametric learning (BNL) has emerged as a force for further advances in this field due to its greater modelling flexibility and representation power. Instead of playing with the fixed-dimensional probabilistic distributions of Bayesian learning, BNL creates a new “game” with infinite-dimensional stochastic processes. BNL has long been recognised as a research subject in statistics, and, to date, several state-of-the-art pilot studies have demonstrated that BNL has a great deal of potential to solve real-world machine-learning tasks.
http://dl.acm.org/citation.cfm?id=3309872
Brownout Approach for Adaptive Management of Resources and Applications in Cloud Computing Systems: A Taxonomy and Future Directions
http://dl.acm.org/citation.cfm?id=3234151
Minxian Xu, Rajkumar Buyya
Cloud computing has been regarded as an emerging approach to provisioning resources and managing applications. It provides attractive features, such as an on-demand model, scalability enhancement, and management cost reduction. However, cloud computing systems continue to face problems such as hardware failures, overloads caused by unexpected workloads, or the waste of energy due to inefficient resource utilization, which all result in resource shortages and application issues such as delays or saturation. A paradigm, the brownout, has been applied to handle these issues by adaptively activating or deactivating optional parts of applications or services to manage resource usage in cloud computing system.
A Survey on Bayesian Nonparametric Learning
http://dl.acm.org/citation.cfm?id=3291044
Junyu Xuan, Jie Lu, Guangquan Zhang
Bayesian (machine) learning has been playing a significant role in machine learning for a long time due to its particular ability to embrace uncertainty, encode prior knowledge, and endow interpretability. On the back of Bayesian learning’s great success, Bayesian nonparametric learning (BNL) has emerged as a force for further advances in this field due to its greater modelling flexibility and representation power. Instead of playing with the fixed-dimensional probabilistic distributions of Bayesian learning, BNL creates a new “game” with infinite-dimensional stochastic processes. BNL has long been recognised as a research subject in statistics, and, to date, several state-of-the-art pilot studies have demonstrated that BNL has a great deal of potential to solve real-world machine-learning tasks.
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