EAI Endorsed Transactions on Self-Adaptive Systems

Temporarily closed open access journal abstracted/indexed in DBLP, CrossRef, EBSCO Discovery Services, and WorldCat. It focuses on artificial intelligence including smart manufacturing, smart cities and smart medical services and more, with no publishing fees.

Editor(s)-in-Chief: Emil Vassev

Aims & Scope
Editorial Board
Special Issues

A large class of software-intensive systems, including those for industrial automation, consumer electronics, airplanes, automobiles, medical devices, and civic infrastructure, must interact with the physical world. More advanced systems, such as unmanned autonomous systems, don’t just interact but also perceive important structural and dynamic aspects of their operational environment.

To become interactive, an autonomous system must be aware of its physical environment and whereabouts, as well as its current internal status. This ability helps software-intensive systems sense, draw inferences, and react by exhibiting self-adaptation. As software is used for more pervasive and critical applications, support for self-adaptation is increasingly seen as necessary in avoiding costly disruptions for repair, maintenance and evolution of systems.

A common understanding about the process of self-adaptation is the ability of a system to autonomously monitor its behavior and eventually modify the same according to changes in the operational environment or in the system itself. A good example of self-adaptive systems can be addressed to contemporary robotics systems that rely on the most recent advances in automation and robotic technologies to promote autonomy and self-adaptation to robotized systems.

The paradigm of self-adaptive systems is closely related to AI, which makes the research and development of such systems extremely challenging and demanding new approaches that can efficiently tackle the problems of expressing autonomy requirements, designing and implementing self-adaptive features, and efficiently testing self-adaptive behavior.

AI for wireless communications
AI for signal processing
AI for image processing
AI for medical/biological analysis, visualization and diagnosis
AI for robotics
AI for audio, language and speech processing
AI for big data mining and analysis
AI for emotion analysis
AI for self-piloting automobile
Applications in neuroscience
Computer imaging, vision and graphics
Machine learning
Deep learning
Deep reinforcement learning
Pattern recognition
Automated reasoning and inference
Natural language processing
Knowledge and data engineering

Special Issues Editor: Jorge De-j. Lozoya-santos (University of Monterrey, Mexico)

Bashar Nuseibeh (The Open University, UK and Lero, the Irish Software Engineering Research Center, University of Limerick)

Christopher Rouff (Johns Hopkins Applied Physics Laboratory)

Danny Weyns (Linnaeus University)

Diana Spears (Swarmotics LLC, Laramie, Wyoming, USA)

Franco Zambonelli (UNIMORE, Italy)

Genaina Rodrigues (University of Brasilia)

Giacomo Cabri (UNIMORE, Italy)

Imrich Chlamtac (CREATE-NET Research Consortium, University of Trento, Italy)

James Windsor (ESTEC, European Space Agency, Netherlands)

Michael O'Neill (UCD, Ireland)

Mike Hinchey (Lero, the Irish Software Engineering Research Center, University of Limerick)

Richard Antony (University of Greenwich)

Simon Dobson (University of St Andrews)

Recently Published
Most Popular

Intelligence of reconstructed biomolecular motor system
Appears in:
sas 16(8): e4

Authors:
Daisuke Inoue, Arif Rashedul Kabir, Akira Kakugo

Published:
24th May 2016

Abstract:
Collective motion is a fascinating example of coordinated behavior of self-propelled objects, which is often associated with the formation of large scale patterns. Nowadays, in vitro gliding assay is being considered a model system to experimentally investigate various aspects of group behavior and…Collective motion is a fascinating example of coordinated behavior of self-propelled objects, which is often associated with the formation of large scale patterns. Nowadays, in vitro gliding assay is being considered a model system to experimentally investigate various aspects of group behavior and pattern formation by self-propelled objects. In this work, we have demonstrated the collective motion of kinesin driven microtubules by regulating mutual interaction among the gliding microtubules, by employing depletion force among them. Proper regulation of the mutual interaction among the gliding microtubules through employment of the depletion force was found to allow the exhibition of collective motion and stream pattern formation by microtubules. We also discuss how collectively moving microtubule on kinesin coated elastomer substrate response to external stimuli such as mechanical stresses.
more »
Gliding Movements of Microtubule Driven by Kinesin Motors under External Force: Steering and Detachment
Appears in:
sas 16(8): e3

Authors:
Takahiro Nitta, Kouki Kawauchi

Published:
24th May 2016

Abstract:
Kinesin and microtubule have been utilized for applications, such as molecular communication. In this paper, we describe a computer simulation which reproduced movements of microtubules gliding over kinesin-coated glass surfaces under external force. The simulation qualitatively reproduced experime…Kinesin and microtubule have been utilized for applications, such as molecular communication. In this paper, we describe a computer simulation which reproduced movements of microtubules gliding over kinesin-coated glass surfaces under external force. The simulation qualitatively reproduced experimental results of microtubule movements under external force. This simulation would enable understanding of details of the gliding movements of microtubules under external force.
more »
Microtubule Motional Diffusion Coefficient in Motility Assays is Determined by Heterogeneity in Motor Stiffness
Appears in:
sas 16(8): e2

Authors:
Henri Palacci, Ofer Idan, Megan Armstrong, Takahiro Nitta, Henry Hess

Published:
24th May 2016

Abstract:
In the past twenty years, our ability to manipulate and engineer devices at the nano-scale has grown exponentially. As the fabrication of autonomous systems at these scales becomes a reality, the observation of biological structures can help us understand general design principles at the nano-scale…In the past twenty years, our ability to manipulate and engineer devices at the nano-scale has grown exponentially. As the fabrication of autonomous systems at these scales becomes a reality, the observation of biological structures can help us understand general design principles at the nano-scale. The gliding motility assay is an excellent model system for the observation of collective behavior of coupled motors. Indeed, hundreds of surface-adhered kinesin motors propel one microtubule filament. Filament motion has been observed using fluorescence microscopy, revealing fluctuations in gliding velocity. We here theoretically characterize the motional diffusion coefficients through the heterogeneity factor proposed by Sekimoto and Tawada, and use a Brownian dynamics simulation of kinesin head diffusion under an anharmonic potential to determine a theoretical value of 0.3 for this heterogeneity factor.
more »
Capacity of Multilayer Diffusion-based Molecular Communication (DBMC) Channel
Appears in:
sas 16(8): e1

Authors:
Saizalmursidi Md Mustam, Sharifah Kamilah Syed Yusof, Suleiman Zubair

Published:
24th May 2016

Abstract:
In diffusion-based molecular communication (DBMC) system, information is encoded in the variation of molecules such as amounts, time shifts, or different molecule types, at a transmitter nanomachine (TN). These molecules are then released and propagated through a channel towards a receiver nanomach…In diffusion-based molecular communication (DBMC) system, information is encoded in the variation of molecules such as amounts, time shifts, or different molecule types, at a transmitter nanomachine (TN). These molecules are then released and propagated through a channel towards a receiver nanomachine (RN). One of the most important performance matrices in evaluating this system from an information theory perspective is channel capacity. This paper provides a derivation of capacity expression for multilayer DBMC channel in which the propagation of molecules from the TN to the RN through multiple channels follows the Brownian motion and modeled by Fick's equations. The Fourier transforms is employed to convert time to frequency domain functions. The results show that the maximum capacity can be obtained by increasing both the bandwidth and the average transmitted power, and decreasing the TN-RN distance.
more »
A topological approach for multivariate time series characterization: the epileptic brain
Appears in:
sas 16(7): e5

Authors:
Emanuela Merelli, Marco Piangerelli, Matteo Rucco, Daniele Toller

Published:
24th May 2016

Abstract:
In this paper we propose a methodology based on Topogical Data Analysis (TDA) for capturing when a complex system, represented by a multivariate time series, changes its internal organization. The modification of the inner organization among the entities belonging to a complex system can induce …In this paper we propose a methodology based on Topogical
Data Analysis (TDA) for capturing when a complex system,
represented by a multivariate time series, changes its internal organization. The modification of the inner organization
among the entities belonging to a complex system can induce
a phase transition of the entire system. In order to identify
these reorganizations, we designed a new methodology that
is based on the representation of time series by simplicial
complexes. The topologization of multivariate time series
successfully pinpoints out when a complex system evolves.
Simplicial complexes are characterized by persistent homology techniques, such as the clique weight rank persistent
homology and the topological invariants are used for computing a new entropy measure, the so-called weighted per-
sistent entropy. With respect to the global invariants, e.g.
the Betti numbers, the entropy takes into account also the
topological noise and then it captures when a phase transition happens in a system. In order to verify the reliability of the methodology, we have analyzed the EEG signals of PhysioNet database and we have found numerical evidences that
the methodology is able to detect the transition between the pre-ictal and ictal states.
more »
On the Computational Complexity of Software (Re)Modularization: Elaborations and Opportunities
Appears in:
sas 16(7): e4

Author:
Todd Wareham

Published:
24th May 2016

Abstract:
Software system modularization and remodularization are key challenges in software engineering. All previous research has assumed that these problems are computationally intractable and hence focused on heuristic methods such as hill-climbing, evolutionary algorithms, and simulated annealing …Software system modularization and remodularization are key challenges in software
engineering. All previous research has assumed that these problems are
computationally intractable and hence focused on heuristic methods such as
hill-climbing, evolutionary algorithms, and simulated annealing that are fast but
do not guarantee to produce solutions of optimal or even near-optimal quality.
However, this intractability has never been formally established. In this paper,
we give the first proofs of the $NP$-hardness of software modularization and
remodularization relative to several models of module-internal connectivity. We
also review three popular algorithmic approaches for producing provably optimal or
near-optimal solutions efficiently and both discuss the applicability of these
approaches in and list results in the literature relevant to
practical software modularization and remodularization.
more »
Optimal topology of gene-regulatory networks: role of the average shortest path
Appears in:
sas 16(7): e3

Authors:
Ahmed Abdelzaher, Thang Dinh, Michael Mayo, Preetam Ghosh

Published:
24th May 2016

Abstract:
Gene regulatory networks (GRNs) possess an important structural property; they are sparse and resilient, with a robust topology that affords protection against random "attacks" (e.g., gene deletions). However, such networks exhibit optimal or near-optimal topological features not present in other …Gene regulatory networks (GRNs) possess an important structural property; they are sparse and resilient, with a robust topology that affords protection against random "attacks" (e.g., gene deletions). However, such networks exhibit optimal
or near-optimal topological features not present in other
scale-free networks. This paper utilizes an integer linear program formulation to gauge the exact structural optimality of scale-free networks measured using the average shortest path between transcription factors and the regulated
genes of a gene-regulatory network sampled from the
Escherichia coli bacterium. While randomly generated versions of these networks show several cases for improvement, few subnetworks sampled from Escherichia coli's transcriptional network show optimized solutions that differ substantially from their original topology. We therefore conclude that sampled transcriptional subnetworks from Escherichia
coli exhibit an "optimal" topology not present in alternative networks. Because these analyses do not consider the biology of expression dynamics and are based on topology alone, other communication systems, such as wireless networks,
may benefit from a more detailed examination of the
role in which the average shortest path affects system function, such as with noise or other signaling disruptions.
more »
A Population Based ACO Algorithm for the Combined Tours TSP Problem
Appears in:
sas 16(7): e2

Authors:
Martin Clauss, Lydia Lotzmann, Martin Middendorf

Published:
24th May 2016

Abstract:
In this paper we apply a Population based Ant Colony Optimization(PACO) algorithm for solving the following new version of the Traveling Salesperson problem that is called the Combined Tours TSP (CT-TSP). Given are a set of cities, for each pair of cities a cost function and an integer k. The aim i…In this paper we apply a Population based Ant Colony Optimization(PACO) algorithm for solving the following new version of the Traveling Salesperson problem that is called the Combined Tours TSP (CT-TSP). Given are a set of cities, for each pair of cities a cost function and an integer k. The aim is to find a set of k (cyclic) tours, i.e., each city is contained exactly once in each tour and each tour returns to its origin city, which have minimum total costs. In this paper the case of finding two tours is studied where the costs of one tour depends on the other tour. Each pair of cities has a distance and a weight which influence the costs of the tours. The weight is used to define if it is advantageous or disadvantageous when the corresponding pair of cities is contained, i.e., neighbouring, in both tours. Different heuristics that the ants of the PACO use for the construction of the tours are compared experimentally. One result is that it is (often) advantageous when the heuristic for the second tour is different from the heuristic for the first tour such that the former heuristic uses knowledge about the first tour.
more »
Optimization of Aircraft Landing Route and Order: An approach of Hierarchical Evolutionary Computation
Appears in:
sas 16(6): e5

Authors:
Akinori Murata, Masaya Nakata, Hiroyuki Sato, Tim Kovacs, Keiki Takadama

Published:
24th May 2016

Abstract:
This paper focuses on the aircraft landing optimization problem where both the landing routes and the landing order of aircrafts should be optimized to minimize an occupancy time of airport , and proposes its optimization method which is robust to dynamical situations such as weather condition cha… This paper focuses on the aircraft landing optimization problem where both the landing routes and the landing order of aircrafts should be optimized to minimize an occupancy time of airport , and proposes its optimization method which is robust to dynamical situations such as weather condition change and other aircrafts’ landing routes change. As a difficulty of this optimization problem, appropriate landing routes of aircrafts change depending on such an environment change. To tackle this problem, this paper proposes the hierarchical evolutionary computation to solve the aircraft landing optimization problem. Specifically, our method firstly generates candidates of main landing route of all aircrafts with their own additional sub-routes, which can be applied into the main routes depending on the current environmental situation. Secondly, our method evolves the good combination of landing routes (including their sub-routes) of all aircrafts to minimize an occupancy time of airport. Through the intensive experiment on a benchmark problem, the following implications have been found: (1) our method successfully generates robust landing routes including some sub-routes，which are flexible depending on environmental situations; and (2) Our method can finds an adequate landing order which contributes to reducing the occupancy time.
more »
Automatic Regulator for Supplemental Oxygen Therapy
Appears in:
sas 16(6): e4

Authors:
Vian Abraham, Yasameen Al Mharib, Brian Donnel, Xiaobin Le, Joseph Santacroce, Douglas Dow

Published:
24th May 2016

Abstract:
Living tissues require a sufficient supply of oxygen for survival. An insufficient supply of oxygen may result from impairments of the respiration or oxygen transport systems, such as lung disease, heart disease, and anemia. Supplemental oxygen therapy increases the oxygen content in the lungs and …Living tissues require a sufficient supply of oxygen for survival. An insufficient supply of oxygen may result from impairments of the respiration or oxygen transport systems, such as lung disease, heart disease, and anemia. Supplemental oxygen therapy increases the oxygen content in the lungs and blood oxygen saturation. The control of the oxygen flow is typically adjusted manually. This manual adjustment increases the risk for a mismatch between the oxygen flow rate and oxygen consumption that may change with physiological activity. An insufficient supply of oxygen increases the risk for cell damage and hypoxia. An excessive supply of oxygen risks oxygen toxicity and rapid depletion of the oxygen supply. This paper develops and tests the regulation of gas flow intake based on input of patient oxygen blood saturation. During testing of the prototype, gas pressure was regulated based on input oxygen blood saturation values, indicating control of gas flow. Further development and testing would be required for closed loop control of the system. Such a system would contribute toward improving the match of oxygen flow to physiological demands, and contribute to improving the health of many patients.
more »

A Framework for System Event Classification and Prediction by Means of Machine Learning
Appears in:
sas 15(3): e3

Authors:
Teerat Pitakrat, Jonas Grunert, Oliver Kabierschke, Fabian Keller, Andre van Hoorn

Downloads:
2309

Abstract:
During operation, software systems produce large amounts of log events, comprising notifications of different severity from various hardware and software components. These data include important information that helps to diagnose problems in the system, e.g., post-mortem root cause analysis. Manual…During operation, software systems produce large amounts of log events, comprising notifications of different severity from various hardware and software components. These data include important information that helps to diagnose problems in the system, e.g., post-mortem root cause analysis. Manual processing of system logs after a problem occurred is a common practice. However, it is time-consuming and error-prone. Moreover, this way, problems are diagnosed after they occurred—even though the data may already include symptoms of upcoming problems.
To address these challenges, we developed the SCAPE approach for automatic system event classification and prediction, employing machine learning techniques. This paper introduces SCAPE, including a brief description of the proof-of-concept implementation. SCAPE is part of our Hora framework for online failure prediction in component-based software systems. The experimental evaluation, using a publicly available supercomputer event log, demonstrates SCAPE’s high classification accuracy and first results on applying the prediction to a real world data set.
more »
A topological approach for multivariate time series characterization: the epileptic brain
Appears in:
sas 16(7): e5

Authors:
Emanuela Merelli, Marco Piangerelli, Matteo Rucco, Daniele Toller

Downloads:
2055

Abstract:
In this paper we propose a methodology based on Topogical Data Analysis (TDA) for capturing when a complex system, represented by a multivariate time series, changes its internal organization. The modification of the inner organization among the entities belonging to a complex system can induce …In this paper we propose a methodology based on Topogical
Data Analysis (TDA) for capturing when a complex system,
represented by a multivariate time series, changes its internal organization. The modification of the inner organization
among the entities belonging to a complex system can induce
a phase transition of the entire system. In order to identify
these reorganizations, we designed a new methodology that
is based on the representation of time series by simplicial
complexes. The topologization of multivariate time series
successfully pinpoints out when a complex system evolves.
Simplicial complexes are characterized by persistent homology techniques, such as the clique weight rank persistent
homology and the topological invariants are used for computing a new entropy measure, the so-called weighted per-
sistent entropy. With respect to the global invariants, e.g.
the Betti numbers, the entropy takes into account also the
topological noise and then it captures when a phase transition happens in a system. In order to verify the reliability of the methodology, we have analyzed the EEG signals of PhysioNet database and we have found numerical evidences that
the methodology is able to detect the transition between the pre-ictal and ictal states.
more »
The Development of Intelligent Service System for Machine Tool Industry
Appears in:
sas 15(4): e4

Authors:
Yueh-Ling Lin, Chih-Chieh Lin, Hung-Sheng Chiu

Downloads:
2045

Abstract:
Developing efficient services for Taiwan’s machine-tool industry is important because of the intelligent service enhancement for industrial networks and systems integration. The purpose of this study is to provide innovative service via remote cloud computing for machine tool solutions. The intelli…Developing efficient services for Taiwan’s machine-tool industry is important because of the intelligent service enhancement for industrial networks and systems integration. The purpose of this study is to provide innovative service via remote cloud computing for machine tool solutions. The intelligent system integrates both hardware and software functions of machine tools. A platform was developed for machinery information convergence and intelligent service system. To complete the standards for the proposed system, the Taiwan Machine Tool Connect (TMTC) standard was developed to provide over 80% data acquisition support for current CNC machines and PLC controllers. Compare the TMTC standard with the MTConnect standard, the TMTC can provide faster and lower traffic on multi-trip data exchange to accelerate the interpretation and increase 50% transmission speed. The proposed system was demonstrated by applying it to the aerospace and automotive industries. The system performance was verified by proximal system functional test, platform verification, work and service process feasibility assessment, and key performance evaluation for machine tool solutions. The results successfully connect 302 machines with ServBox to achieve real-time machine monitoring and enhance productivity. Finally, the proposed system can provide machinery data analysis, intelligent service, and applications for machine tool solutions and increase production values for Taiwan’s machine-tool industry.
more »
Ascending and Descending Walking Recognition using Smartphone
Appears in:
sas 16(6): e1

Authors:
Sang Vu, Khoa Truong, Shiro Yano, Toshiyuki Kondo

Downloads:
1979

Abstract:
In the recent decades, activity recognition for human behavior monitoring has been one of the major interesting research subjects. This paper investigates fractal dimension (FD) as an effective feature for human activity recognition. The target activities are descending and ascending stairs, which …In the recent decades, activity recognition for human behavior monitoring has been one of the major interesting research subjects. This paper investigates fractal dimension (FD) as an effective feature for human activity recognition. The target activities are descending and ascending stairs, which are performed by six male participants. To testify the validity of feature, the classification methods are k-nearest neighbors (kNN) and support vector machine (SVM). The best result achieved in this results is using SVM classifier and obtaining 95.30% for walking downstairs and 88.56% for walking upstairs with window of 4s and equalized data. Another aim of this paper is to examine the impact of database on the classification results. The finding in the paper provides evidence that the classification accuracy is affected insignificantly by the ratio of descending and ascending data.
more »
Evaluating Unsupervised Fault Detection in Self-Healing Systems Using Stochastic Primitives
Appears in:
sas 15(1): e3

Authors:
Chris Schneider, Adam Barker, Simon Dobson

Downloads:
1767

Abstract:
Autonomous fault detection represents one approach for reducing operational costs in large-scale computing environments. However, little empirical evidence exists regarding the implementation or comparison of such methodologies, or offers proof that such approaches reduce costs. This paper compares…Autonomous fault detection represents one approach for reducing operational costs in large-scale computing environments. However, little empirical evidence exists regarding the implementation or comparison of such methodologies, or offers proof that such approaches reduce costs. This paper compares the effectiveness of several types of stochastic primitives using unsupervised learning to heuristically determine the root causes of faults. The results suggest that self-healing systems frameworks leveraging these techniques can reliably and autonomously determine the source of an anomaly within as little as five minutes. This finding lays the foundation for determining the potential these approaches have for reducing operational costs and ultimately concludes with new avenues for exploring anomaly prediction.
more »
Docking autonomous robots in passive docks with Infrared sensors and QR codes
Appears in:
sas 15(2): e2

Authors:
Roberto Quilez, Adriaan Zeeman, Nathalie Mitton, Julien Vandaele

Downloads:
1670

Abstract:
In this paper, we describe an inexpensive and easy to deploy docking solution in passive charging docks for autonomous mobile robots. The objective is to achieve long-term autonomous robots within an experiment test-bed. We propose to combine the use of QR codes as landmarks and Infrared distan…In this paper, we describe an inexpensive and
easy to deploy docking solution in passive charging docks for
autonomous mobile robots. The objective is to achieve long-term
autonomous robots within an experiment test-bed. We propose to
combine the use of QR codes as landmarks and Infrared distance
sensors. The relative size of the lateral edges of the visual pattern
is used to position the robot in relation with the dock. Infrared
distance sensors are then used to perform different approaching
strategies depending on the distance. Experiments show that the
proposed solution is fully operational and robust. Not to rely
exclusively on visual pattern recognition avoids potential errors
induced by camera calibration. Additionally, as a positive side
effect, the use of Infrared sensors allows the robot to avoid
obstacles while docking. The finality of such an approach is
to integrate these robots into the FIT IoT Lab experimental
testbed which allows any experimenter to book wireless resources
such as wireless sensors remotely and to test their own code.
Wifibots holding wireless sensors will be integrated as additional
reservable resources of the platform to enlarge the set of possible
experimentations with mobile entities.
more »
A Tool for Visualizing Buffer Overflow with Detecting Return Address Overwriting
Appears in:
sas 16(5): e5

Author:
Isao Sasano

Downloads:
1639

Abstract:
Buffer overflow is a serious problem when the software is run as a server on the internet. Especially when the return addresses are overwritten intentionally, the control flow may be changed as the attacker intends. Although there have been proposed several ways to protect attacks that utilize the …Buffer overflow is a serious problem when the software is run as a server on the internet. Especially when the return addresses are overwritten intentionally, the control flow may be changed as the attacker intends. Although there have been proposed several ways to protect attacks that utilize the buffer overflow, the number of the errors owing to the buffer overflow have been increasing gradually. This paper presents a tool that visualizes the buffer overflow when executing
programs in C language, especially when the return
addresses are overwritten. The functionality is mainly targeted at beginners of C programming who do not recognize the attacks, which we expect makes the number of errors decrease in the future.
more »
Intelligence of reconstructed biomolecular motor system
Appears in:
sas 16(8): e4

Authors:
Daisuke Inoue, Arif Rashedul Kabir, Akira Kakugo

Downloads:
1373

Abstract:
Collective motion is a fascinating example of coordinated behavior of self-propelled objects, which is often associated with the formation of large scale patterns. Nowadays, in vitro gliding assay is being considered a model system to experimentally investigate various aspects of group behavior and…Collective motion is a fascinating example of coordinated behavior of self-propelled objects, which is often associated with the formation of large scale patterns. Nowadays, in vitro gliding assay is being considered a model system to experimentally investigate various aspects of group behavior and pattern formation by self-propelled objects. In this work, we have demonstrated the collective motion of kinesin driven microtubules by regulating mutual interaction among the gliding microtubules, by employing depletion force among them. Proper regulation of the mutual interaction among the gliding microtubules through employment of the depletion force was found to allow the exhibition of collective motion and stream pattern formation by microtubules. We also discuss how collectively moving microtubule on kinesin coated elastomer substrate response to external stimuli such as mechanical stresses.
more »
Infrared dynamic hand gesture recognition based on Gabor feature and sparse representation
Appears in:
sas 15(4): e1

Authors:
Lei Shang, Zhi Liu, Haixia Zhang

Downloads:
1337

Abstract:
Dynamic hand gesture recognition is a subject which has been investigated almost from the beginning of using terminals to interact with the computer central unit. We present a method for dynamic hand gesture recognition with image source acquired by a single IR camera. First of all, the hand images…Dynamic hand gesture recognition is a subject which has been investigated almost from the beginning of using terminals to interact with the computer central unit. We present a method for dynamic hand gesture recognition with image source acquired by a single IR camera. First of all, the hand images are captured by one infrared camera, which are light independent, and not be limited by skin color. Second, due to the dynamic hand gesture sets contain more than one frame, the data dimension is very large and the adjacent frames have limited difference. We use the twofold selections to choose the key frames from the gesture image sets. The Gabor feature is used to describe the locality variation. And the Sparse representation based classification (SRC) is used for recognition. Experimental results on dynamic hand gesture images with variations of rotation and translation demonstrate the good performance of our method.
more »
Using Joint Particle Swarm Optimization and Genetic Algorithm for Resource Allocation in TD-LTE Systems
Appears in:
sas 15(2): e4

Authors:
Jianbo Du, Liqiang Zhao, Jie Xin, Jen-Ming Wu, Jie Zeng

Downloads:
1327

Abstract:
This paper presents a joint radio resource allocation scheme in LTE/LTE-A systems. In order to maximize system throughput while satisfying the minimum user rate requirement, the resource allocation is modeled as a convex optimization with constraints in this paper, which is proved to be NP-hard. He…This paper presents a joint radio resource allocation scheme in LTE/LTE-A systems. In order to maximize system throughput while satisfying the minimum user rate requirement, the resource allocation is modeled as a convex optimization with constraints in this paper, which is proved to be NP-hard. Hence, a heuristic approach based on joint Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) is proposed. The proposed method exploits the benefits of GA and PSO so that it could avoid the low speed problem of genetic algorithm and the local optimum trap concern in particle swarm optimization algorithm. Simulation results show that the proposed algorithm can overcome the disadvantages of genetic algorithm and particle swarm optimization algorithm, and achieve better performance, e.g., a faster convergence and global optimum.
more »

Publisher: EAI
ISSN: 2410-4051
Number of Volumes: 2

Last Published: 2016-12-28