ESS-Bilbao Initiative Workshop. Beam Dynamics Codes: Availability, Sophistica...ESS BILBAO
Beam Dynamics Codes: Availability, Sophistication, Limitations. P.N. Ostroumov and B. Mustapha Argonne National Laboratory, J.-P. Carneiro Fermi National Accelerator Laboratory
goGPS is open source software that improves the accuracy of low-cost GPS devices through real-time kinematic (RTK) positioning and Kalman filtering. It was initially developed through 2007-2009 at the Polytechnic of Milan and Osaka City University. The software provides sub-meter level positioning and is being ported from MATLAB to Java to manage it as a collaborative open source project. goGPS processing will also be offered as a web service to provide accurate positioning from raw GPS data. Future work includes expanding supported signals and sensors and developing hardware to run the software-defined radio front-end.
Ofdm sim-matlab-code-tutorial web for EE studentsMike Martin
This document describes an OFDM simulation using Matlab. It begins with an introduction to OFDM and its advantages for wireless communications. It then provides the mathematical equations for OFDM transmission and reception based on the DVB-T standard. The document outlines the steps to simulate OFDM transmission in Matlab, including generating OFDM symbols using an IFFT, adding a guard interval, pulse shaping, and upconverting to a carrier frequency. It also provides the equations and steps for simulating OFDM reception. Figures and tables are included to illustrate the simulation results and parameters.
1. The document discusses interference detection in combined GNSS receivers for civil aviation. It focuses on continuous wave interference that can affect signals like GPS L1 C/A and Galileo E1.
2. The receiver architecture includes detection functions to monitor performance levels and flag losses or recoveries of system components. This allows the receiver to switch between nominal, alternate and degraded modes of operation.
3. Interference detection algorithms need to meet civil aviation requirements for false alarms and missed detections. Continuous wave interference near code spectrum lines can cause larger errors, so detection of interference with power up to -155 dBW and a Doppler shift of 2 Hz/s is examined.
WE4.L09 - ORTHOGONAL POLARIMETRIC SAR PROCESSOR BASED ON SIGNAL AND INTERFERE...grssieee
The document presents new SAR subspace processors based on signal and interference subspace models. It introduces SAR subspace models that represent targets and interference as belonging to low-rank subspaces. It describes three SAR processors: SSDSAR uses only the signal subspace, OISDSAR removes interference in the orthogonal interference subspace, and OSISDSAR jointly uses both subspaces to better detect targets while reducing false alarms from interference. The models and processors are demonstrated on simulated forest penetration data, showing improved detection over conventional SAR and reduced false alarms compared to SSDSAR. Future work is outlined on theoretical analysis and evaluating performance on real data.
Tessellation adds geometric detail to 3D games by dynamically expanding coarse geometry on the GPU. It works by running a hull shader to generate control points, then using a fixed-function tessellator to divide patches into triangles based on tessellation factors. A domain shader then evaluates the final surface and positions vertices. Common tessellation schemes include PN triangles with cubic patches, Phong tessellation with quadratic interpolation, and approximating Catmull-Clark subdivision surfaces. Tessellation improves performance and scalability by storing less geometry and expanding it only where needed.
ESS-Bilbao Initiative Workshop. Beam Dynamics Codes: Availability, Sophistica...ESS BILBAO
Beam Dynamics Codes: Availability, Sophistication, Limitations. P.N. Ostroumov and B. Mustapha Argonne National Laboratory, J.-P. Carneiro Fermi National Accelerator Laboratory
goGPS is open source software that improves the accuracy of low-cost GPS devices through real-time kinematic (RTK) positioning and Kalman filtering. It was initially developed through 2007-2009 at the Polytechnic of Milan and Osaka City University. The software provides sub-meter level positioning and is being ported from MATLAB to Java to manage it as a collaborative open source project. goGPS processing will also be offered as a web service to provide accurate positioning from raw GPS data. Future work includes expanding supported signals and sensors and developing hardware to run the software-defined radio front-end.
Ofdm sim-matlab-code-tutorial web for EE studentsMike Martin
This document describes an OFDM simulation using Matlab. It begins with an introduction to OFDM and its advantages for wireless communications. It then provides the mathematical equations for OFDM transmission and reception based on the DVB-T standard. The document outlines the steps to simulate OFDM transmission in Matlab, including generating OFDM symbols using an IFFT, adding a guard interval, pulse shaping, and upconverting to a carrier frequency. It also provides the equations and steps for simulating OFDM reception. Figures and tables are included to illustrate the simulation results and parameters.
1. The document discusses interference detection in combined GNSS receivers for civil aviation. It focuses on continuous wave interference that can affect signals like GPS L1 C/A and Galileo E1.
2. The receiver architecture includes detection functions to monitor performance levels and flag losses or recoveries of system components. This allows the receiver to switch between nominal, alternate and degraded modes of operation.
3. Interference detection algorithms need to meet civil aviation requirements for false alarms and missed detections. Continuous wave interference near code spectrum lines can cause larger errors, so detection of interference with power up to -155 dBW and a Doppler shift of 2 Hz/s is examined.
WE4.L09 - ORTHOGONAL POLARIMETRIC SAR PROCESSOR BASED ON SIGNAL AND INTERFERE...grssieee
The document presents new SAR subspace processors based on signal and interference subspace models. It introduces SAR subspace models that represent targets and interference as belonging to low-rank subspaces. It describes three SAR processors: SSDSAR uses only the signal subspace, OISDSAR removes interference in the orthogonal interference subspace, and OSISDSAR jointly uses both subspaces to better detect targets while reducing false alarms from interference. The models and processors are demonstrated on simulated forest penetration data, showing improved detection over conventional SAR and reduced false alarms compared to SSDSAR. Future work is outlined on theoretical analysis and evaluating performance on real data.
Tessellation adds geometric detail to 3D games by dynamically expanding coarse geometry on the GPU. It works by running a hull shader to generate control points, then using a fixed-function tessellator to divide patches into triangles based on tessellation factors. A domain shader then evaluates the final surface and positions vertices. Common tessellation schemes include PN triangles with cubic patches, Phong tessellation with quadratic interpolation, and approximating Catmull-Clark subdivision surfaces. Tessellation improves performance and scalability by storing less geometry and expanding it only where needed.
A presentation on the selection criteria, testing + evaluation and successful, zero-downtime migration to MongoDB. Additionally details on Wordnik's speed and stability are covered as well as how NoSQL technologies have changed the way Wordnik scales.
This document provides summaries of several chess games played between various grandmasters in the ACP Cup 2013 rapid tournament. It includes the players, ratings and results for 15 different chess matches. The games are presented in a compact format with the moves listed sequentially.
Tactical motifs gives you the positions from the recent games where different tactical methods, deflection, decoy, annihilation of pawn structure, clearance, are applied. Study the position and find the best possible move.
Relational databases are being pushed beyond their limits because of the way we build and run applications today, coupled with growth in data sources and user loads. To address these challenges, many companies, such as MTV and Cisco have migrated successfully from relational databases to MongoDB.
Migrating from MySQL to MongoDB at WordnikTony Tam
Wordnik migrated their live application from MySQL to MongoDB to address scaling issues. They moved over 5 billion documents totaling over 1.2 TB of data with zero downtime. The migration involved setting up MongoDB infrastructure, designing the data model and software to match their existing object model, migrating the data, and optimizing performance of the new system. They achieved insert rates of over 100,000 documents per second during the migration process and saw read speeds increase to 250,000 documents per second after completing the move to MongoDB.
This very short document appears to be about a future-focused fish named "Futureled_Fish Rebel" and contains only a single line of text mentioning "The final week in photos." along with a series of repetitive symbols and the word "Fin". It does not provide much contextual information that can be summarized succinctly in 3 sentences or less.
The document discusses ant colony optimization (ACO) algorithms. It introduces ACO as a probabilistic metaheuristic technique inspired by the behavior of ants seeking paths between their colony and food sources. It outlines the ACO metaheuristic and describes key ACO algorithms like Ant System, Ant Colony System, and MAX-MIN Ant System. The document also covers applications of ACO, advantages like inherent parallelism and efficient solutions to problems like the traveling salesman problem, and disadvantages like difficulty analyzing ACO theoretically.
The document discusses ant colony optimization (ACO), which is an algorithm inspired by the behavior of ants seeking paths between their colony and food sources. It was originally applied to solve the traveling salesman problem. The algorithm works by "ants" probabilistically constructing solutions and adjusting pheromone trails that guide future ants towards better solutions. Over time, the pheromone trails reinforce shorter solution paths through positive feedback. The document provides examples of how ACO can be applied to problems like routing in networks and scheduling. It also discusses extensions of the basic ACO approach.
The document discusses ant colony optimization (ACO), which is a metaheuristic algorithm inspired by the behavior of real ant colonies. It describes how real ants deposit pheromone trails to communicate indirectly and find the shortest path between their colony and food sources. The algorithm works by "artificial ants" probabilistically building solutions to optimization problems and adjusting pheromone levels based on solution quality, similar to how real ants reinforce shorter paths. It provides examples of how ACO has been applied to problems like the traveling salesman problem and discusses some extensions to the basic ACO algorithm.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
This document presents a path planning algorithm called Ant Colony Robot Path Planning (ARPP) that is based on Ant Colony Optimization (ACO) techniques. The ARPP algorithm uses artificial ants to find optimal paths for a warehouse material handling robot to navigate between locations, avoiding obstacles. The algorithm models the environment as a visibility graph and applies ACO concepts like pheromone deposition and evaporation to guide the ants toward shorter paths. Simulation results on a sample visibility graph show that after 100 iterations, the ARPP approach consistently finds the shortest path of 33 units in length. The algorithm provides an effective method for mobile robot path planning in complex warehouse environments.
Swarm Intelligence Technique ACO and Traveling Salesman ProblemIRJET Journal
The document discusses the ant colony optimization (ACO) algorithm, a swarm intelligence technique inspired by ant behavior, and its application to the traveling salesman problem (TSP). ACO mimics how ants deposit and follow pheromone trails to probabilistically determine paths, and it has been shown to find good solutions to TSP. The paper also reviews the ACO algorithm and describes how it can be applied to find the shortest tour between cities in TSP.
Zone based ant colony routing in manet by kumar bharagava (comp.sc. engg)kumar65
Zone based ant colony routing is proposed as a routing algorithm for mobile ad hoc networks (MANETs). The algorithm divides the network into zones defined by routers. It is based on the ant colony optimization metaheuristic, which models the food searching behavior of real ants. Ants probabilistically establish paths between nodes by adjusting pheromone values on edges. The algorithm supports features important for MANETs like distributed operation, adaptation to dynamic topology, and multipath routing. It has low overhead since routing information is not directly exchanged between nodes.
Zone based ant colony routing in manet by kumar bharagava (comp.sc. engg)kumar65
The document proposes a zone-based ant colony routing algorithm for mobile ad-hoc networks (MANETs). It divides the network into zones for improved routing. The algorithm is based on the food searching behavior of ants, which optimally find shortest paths. Ants probabilistically establish paths between zones by adjusting pheromone values on network edges. This approach is well-suited for MANETs due to its adaptation to dynamic topology changes and support for multiple paths.
This document describes Ant Colony Optimization, an algorithm inspired by ant behavior that can be applied to routing protocols in wired and wireless networks. It discusses how biological ants are able to find the shortest path between their nest and a food source by leaving pheromone trails. The algorithm is implemented in Java and demonstrated on sample networks, showing convergence on optimal paths. Examples are given of how it has been adapted to routing protocols and been shown to outperform protocols like OSPF and RIP in terms of efficiency and scalability. Results of tests on different networks found that ant-based routing algorithms delivered packets with less overhead compared to protocols like DSR and AODV.
The document discusses ant colony optimization, an algorithm inspired by ant behavior, and its application to routing protocols in wired and wireless networks. It explains how biological ants are able to find the shortest path to food sources using pheromone trails, and how this concept was adapted into an algorithm where simulated ants leave virtual pheromone trails to probabilistically find optimal paths. The algorithm is demonstrated through simulations where "ant agents" explore networks and progressively reinforce shorter routing paths between nodes. Research examples show the ant colony approach can find higher quality routes with lower overhead compared to traditional routing protocols like OSPF.
i. The document describes an ant colony optimization (ACO) based routing algorithm for mobile ad hoc networks (MANETs). ACO algorithms are inspired by how real ants find the shortest path between their colony and food sources.
ii. In the algorithm, artificial "ants" are generated at nodes and collect information about path lengths and quality as they travel between nodes. They deposit and follow "pheromone trails" to probabilistically route along better paths. This allows the protocol to discover paths and adapt to dynamic topologies.
iii. The algorithm is analyzed in simulation. Results show it constructs probabilistic routing tables where better paths have higher pheromone values and are preferred. It can find next
Ant colony optimization based routing algorithm in various wireless sensor ne...Editor Jacotech
Wireless Sensor Network has several issues and challenges due to limited battery backup, limited computation capability, and limited computation capability. These issues and challenges must be taken care while designing the algorithms to increase the Network lifetime of WSN. Routing, the act of moving information across an internet world from a source to a destination is one of the vital issue associated with Wireless Sensor Network. The Ant Colony Optimization (ACO) algorithm is a probabilistic technique for solving computational problems that can be used to find optimal paths through graphs. The short route will be increasingly enhanced therefore become more attractive. The foraging behavior and optimal route finding capability of ants can be the inspiration for ACO based algorithm in WSN. The nature of ants is to wander randomly in search of food from their nest. While moving, ants lay down a pheromone trail on the ground. This chemical pheromone has the ability to evaporate with the time. Ants have the ability to smell pheromone. When selecting their path, they tend to select, probably the paths that has strong pheromone concentrations. As soon as an ant finds a food source, carries some of it back to the nest. While returning, the quantity of chemical pheromone that an ant lay down on the ground may depend on the quantity and quality of the food. The pheromone trails will lead other ants towards the food source. The path which has the strongest pheromone concentration is followed by the ant which is the shortest paths between their nest and food source. This paper surveys the ACO based routing in various Networking domains like Wireless Sensor Networks and Mobile Ad Hoc Networks.
A NOVEL ANT COLONY ALGORITHM FOR MULTICAST ROUTING IN WIRELESS AD HOC NETWORKS cscpconf
The Steiner tree is the underlying model for multicast communication. This paper presents a
novel ant colony algorithm guided by problem relaxation for unconstrained Steiner tree in static
wireless ad hoc networks. The framework of the proposed algorithm is based on ant colony
system (ACS). In the first step, the ants probabilistically construct the path from the source tothe terminal nodes. These paths are then merged together to generate a Steiner tree rooted at the source. The problem is relaxed to incorporate the structural information into the heuristic value for the selection of nodes. The effectiveness of the algorithm is tested on the benchmark problems of the OR-library. Simulation results show that our algorithm can find optimal Steiner tree with high success rate.
The document discusses ant colony optimization (ACO), which is an algorithm inspired by how ants find food. It describes how ants deposit pheromones to mark shorter paths, reinforcing them. The ACO algorithm simulates this process, with "ants" probabilistically building solutions and updating pheromones. It provides pseudocode and discusses applications to problems like the traveling salesman problem. ACO shows good performance on distributed, combinatorial optimization problems.
Security Mechanisms for Organic Mesh Networks - CAST Security Award 2007Kalman Graffi
The document proposes security frameworks for organic mesh networks. It discusses challenges around node authentication, secure routing, and misbehavior detection in networks without a trusted third party. The contribution includes a bootstrapping mechanism for node authentication, the AntSec secure routing protocol, the WatchAnt one-hop misbehavior detector, and a reputation management system. Simulation results show AntSec improves throughput over traditional protocols and WatchAnt quickly and robustly detects misbehavior.
Ant Colony Optimization for Optimal Low-Pass State Variable Filter Sizing IJECEIAES
In analog filter design, discrete components values such as resistors (R) and capacitors (C) are selected from the series following constant values chosen. Exhaustive search on all possible combinations for an optimized design is not feasible. In this paper, we present an application of the Ant Colony Optimization technique (ACO) in order to selected optimal values of resistors and capacitors from different manufactured series to satisfy the filter design criteria. Three variants of the Ant Colony Optimization are applied, namely, the AS (Ant System), the MMAS (Min-Max AS) and the ACS (Ant Colony System), for the optimal sizing of the Low-Pass State Variable Filter. SPICE simulations are used to validate the obtained results/performances which are compared with already published works.
A presentation on the selection criteria, testing + evaluation and successful, zero-downtime migration to MongoDB. Additionally details on Wordnik's speed and stability are covered as well as how NoSQL technologies have changed the way Wordnik scales.
This document provides summaries of several chess games played between various grandmasters in the ACP Cup 2013 rapid tournament. It includes the players, ratings and results for 15 different chess matches. The games are presented in a compact format with the moves listed sequentially.
Tactical motifs gives you the positions from the recent games where different tactical methods, deflection, decoy, annihilation of pawn structure, clearance, are applied. Study the position and find the best possible move.
Relational databases are being pushed beyond their limits because of the way we build and run applications today, coupled with growth in data sources and user loads. To address these challenges, many companies, such as MTV and Cisco have migrated successfully from relational databases to MongoDB.
Migrating from MySQL to MongoDB at WordnikTony Tam
Wordnik migrated their live application from MySQL to MongoDB to address scaling issues. They moved over 5 billion documents totaling over 1.2 TB of data with zero downtime. The migration involved setting up MongoDB infrastructure, designing the data model and software to match their existing object model, migrating the data, and optimizing performance of the new system. They achieved insert rates of over 100,000 documents per second during the migration process and saw read speeds increase to 250,000 documents per second after completing the move to MongoDB.
This very short document appears to be about a future-focused fish named "Futureled_Fish Rebel" and contains only a single line of text mentioning "The final week in photos." along with a series of repetitive symbols and the word "Fin". It does not provide much contextual information that can be summarized succinctly in 3 sentences or less.
The document discusses ant colony optimization (ACO) algorithms. It introduces ACO as a probabilistic metaheuristic technique inspired by the behavior of ants seeking paths between their colony and food sources. It outlines the ACO metaheuristic and describes key ACO algorithms like Ant System, Ant Colony System, and MAX-MIN Ant System. The document also covers applications of ACO, advantages like inherent parallelism and efficient solutions to problems like the traveling salesman problem, and disadvantages like difficulty analyzing ACO theoretically.
The document discusses ant colony optimization (ACO), which is an algorithm inspired by the behavior of ants seeking paths between their colony and food sources. It was originally applied to solve the traveling salesman problem. The algorithm works by "ants" probabilistically constructing solutions and adjusting pheromone trails that guide future ants towards better solutions. Over time, the pheromone trails reinforce shorter solution paths through positive feedback. The document provides examples of how ACO can be applied to problems like routing in networks and scheduling. It also discusses extensions of the basic ACO approach.
The document discusses ant colony optimization (ACO), which is a metaheuristic algorithm inspired by the behavior of real ant colonies. It describes how real ants deposit pheromone trails to communicate indirectly and find the shortest path between their colony and food sources. The algorithm works by "artificial ants" probabilistically building solutions to optimization problems and adjusting pheromone levels based on solution quality, similar to how real ants reinforce shorter paths. It provides examples of how ACO has been applied to problems like the traveling salesman problem and discusses some extensions to the basic ACO algorithm.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
This document presents a path planning algorithm called Ant Colony Robot Path Planning (ARPP) that is based on Ant Colony Optimization (ACO) techniques. The ARPP algorithm uses artificial ants to find optimal paths for a warehouse material handling robot to navigate between locations, avoiding obstacles. The algorithm models the environment as a visibility graph and applies ACO concepts like pheromone deposition and evaporation to guide the ants toward shorter paths. Simulation results on a sample visibility graph show that after 100 iterations, the ARPP approach consistently finds the shortest path of 33 units in length. The algorithm provides an effective method for mobile robot path planning in complex warehouse environments.
Swarm Intelligence Technique ACO and Traveling Salesman ProblemIRJET Journal
The document discusses the ant colony optimization (ACO) algorithm, a swarm intelligence technique inspired by ant behavior, and its application to the traveling salesman problem (TSP). ACO mimics how ants deposit and follow pheromone trails to probabilistically determine paths, and it has been shown to find good solutions to TSP. The paper also reviews the ACO algorithm and describes how it can be applied to find the shortest tour between cities in TSP.
Zone based ant colony routing in manet by kumar bharagava (comp.sc. engg)kumar65
Zone based ant colony routing is proposed as a routing algorithm for mobile ad hoc networks (MANETs). The algorithm divides the network into zones defined by routers. It is based on the ant colony optimization metaheuristic, which models the food searching behavior of real ants. Ants probabilistically establish paths between nodes by adjusting pheromone values on edges. The algorithm supports features important for MANETs like distributed operation, adaptation to dynamic topology, and multipath routing. It has low overhead since routing information is not directly exchanged between nodes.
Zone based ant colony routing in manet by kumar bharagava (comp.sc. engg)kumar65
The document proposes a zone-based ant colony routing algorithm for mobile ad-hoc networks (MANETs). It divides the network into zones for improved routing. The algorithm is based on the food searching behavior of ants, which optimally find shortest paths. Ants probabilistically establish paths between zones by adjusting pheromone values on network edges. This approach is well-suited for MANETs due to its adaptation to dynamic topology changes and support for multiple paths.
This document describes Ant Colony Optimization, an algorithm inspired by ant behavior that can be applied to routing protocols in wired and wireless networks. It discusses how biological ants are able to find the shortest path between their nest and a food source by leaving pheromone trails. The algorithm is implemented in Java and demonstrated on sample networks, showing convergence on optimal paths. Examples are given of how it has been adapted to routing protocols and been shown to outperform protocols like OSPF and RIP in terms of efficiency and scalability. Results of tests on different networks found that ant-based routing algorithms delivered packets with less overhead compared to protocols like DSR and AODV.
The document discusses ant colony optimization, an algorithm inspired by ant behavior, and its application to routing protocols in wired and wireless networks. It explains how biological ants are able to find the shortest path to food sources using pheromone trails, and how this concept was adapted into an algorithm where simulated ants leave virtual pheromone trails to probabilistically find optimal paths. The algorithm is demonstrated through simulations where "ant agents" explore networks and progressively reinforce shorter routing paths between nodes. Research examples show the ant colony approach can find higher quality routes with lower overhead compared to traditional routing protocols like OSPF.
i. The document describes an ant colony optimization (ACO) based routing algorithm for mobile ad hoc networks (MANETs). ACO algorithms are inspired by how real ants find the shortest path between their colony and food sources.
ii. In the algorithm, artificial "ants" are generated at nodes and collect information about path lengths and quality as they travel between nodes. They deposit and follow "pheromone trails" to probabilistically route along better paths. This allows the protocol to discover paths and adapt to dynamic topologies.
iii. The algorithm is analyzed in simulation. Results show it constructs probabilistic routing tables where better paths have higher pheromone values and are preferred. It can find next
Ant colony optimization based routing algorithm in various wireless sensor ne...Editor Jacotech
Wireless Sensor Network has several issues and challenges due to limited battery backup, limited computation capability, and limited computation capability. These issues and challenges must be taken care while designing the algorithms to increase the Network lifetime of WSN. Routing, the act of moving information across an internet world from a source to a destination is one of the vital issue associated with Wireless Sensor Network. The Ant Colony Optimization (ACO) algorithm is a probabilistic technique for solving computational problems that can be used to find optimal paths through graphs. The short route will be increasingly enhanced therefore become more attractive. The foraging behavior and optimal route finding capability of ants can be the inspiration for ACO based algorithm in WSN. The nature of ants is to wander randomly in search of food from their nest. While moving, ants lay down a pheromone trail on the ground. This chemical pheromone has the ability to evaporate with the time. Ants have the ability to smell pheromone. When selecting their path, they tend to select, probably the paths that has strong pheromone concentrations. As soon as an ant finds a food source, carries some of it back to the nest. While returning, the quantity of chemical pheromone that an ant lay down on the ground may depend on the quantity and quality of the food. The pheromone trails will lead other ants towards the food source. The path which has the strongest pheromone concentration is followed by the ant which is the shortest paths between their nest and food source. This paper surveys the ACO based routing in various Networking domains like Wireless Sensor Networks and Mobile Ad Hoc Networks.
A NOVEL ANT COLONY ALGORITHM FOR MULTICAST ROUTING IN WIRELESS AD HOC NETWORKS cscpconf
The Steiner tree is the underlying model for multicast communication. This paper presents a
novel ant colony algorithm guided by problem relaxation for unconstrained Steiner tree in static
wireless ad hoc networks. The framework of the proposed algorithm is based on ant colony
system (ACS). In the first step, the ants probabilistically construct the path from the source tothe terminal nodes. These paths are then merged together to generate a Steiner tree rooted at the source. The problem is relaxed to incorporate the structural information into the heuristic value for the selection of nodes. The effectiveness of the algorithm is tested on the benchmark problems of the OR-library. Simulation results show that our algorithm can find optimal Steiner tree with high success rate.
The document discusses ant colony optimization (ACO), which is an algorithm inspired by how ants find food. It describes how ants deposit pheromones to mark shorter paths, reinforcing them. The ACO algorithm simulates this process, with "ants" probabilistically building solutions and updating pheromones. It provides pseudocode and discusses applications to problems like the traveling salesman problem. ACO shows good performance on distributed, combinatorial optimization problems.
Security Mechanisms for Organic Mesh Networks - CAST Security Award 2007Kalman Graffi
The document proposes security frameworks for organic mesh networks. It discusses challenges around node authentication, secure routing, and misbehavior detection in networks without a trusted third party. The contribution includes a bootstrapping mechanism for node authentication, the AntSec secure routing protocol, the WatchAnt one-hop misbehavior detector, and a reputation management system. Simulation results show AntSec improves throughput over traditional protocols and WatchAnt quickly and robustly detects misbehavior.
Ant Colony Optimization for Optimal Low-Pass State Variable Filter Sizing IJECEIAES
In analog filter design, discrete components values such as resistors (R) and capacitors (C) are selected from the series following constant values chosen. Exhaustive search on all possible combinations for an optimized design is not feasible. In this paper, we present an application of the Ant Colony Optimization technique (ACO) in order to selected optimal values of resistors and capacitors from different manufactured series to satisfy the filter design criteria. Three variants of the Ant Colony Optimization are applied, namely, the AS (Ant System), the MMAS (Min-Max AS) and the ACS (Ant Colony System), for the optimal sizing of the Low-Pass State Variable Filter. SPICE simulations are used to validate the obtained results/performances which are compared with already published works.
The document discusses the Telecommunications Technical Interest Group (TIG) at Georgia Tech, which focuses on digital communications. It provides an overview of undergraduate and graduate coursework in physical layer communications and networking. Examples are also given of research conducted at Georgia Tech on topics such as optical data storage, satellite communications using adaptive antennas, and high-speed wireless network prototypes.
AN EFFICIENT ANT BASED QOS AWARE INTELLIGENT TEMPORALLY ORDERED ROUTING ALGOR...IJCNCJournal
This document summarizes an ant-based routing algorithm for mobile ad hoc networks that aims to improve network lifetime, reduce packet loss, and decrease average end-to-end delay. It combines aspects of Ant Colony Optimization and the Temporally Ordered Routing Algorithm (TORA). The algorithm is designed to find multiple paths between sources and destinations in the network while satisfying quality of service constraints like delay, bandwidth, energy consumption, and data rate. It is claimed to be suitable for real-time and multimedia applications in mobile ad hoc networks.
An adaptative nature inspired algorithm explained, concretely implemented, and applied to routing protocols in wired and wireless networks. The document discusses how ant colony optimization algorithms can be applied to routing by simulating how ants leave pheromone trails to find the shortest path between their nest and food sources. It provides examples of how ant colony algorithms have been implemented in routing protocols like ABC for wired networks, AntNet for MANETs, and ARA and AntHocNet for wireless ad hoc networks. Evaluation results show these ant-inspired routing protocols can find paths more efficiently than traditional routing protocols like OSPF and perform better than protocols like AODV for packet delivery in mobile wireless networks.
This document summarizes ant colony optimization algorithms for solving the traveling salesman problem. It first discusses how real ant behavior inspired the development of artificial ant colony algorithms. It then reviews different ant colony optimization algorithms for the traveling salesman problem, including the ant system, elitist ant system, rank-based ant system, min-max ant system, and ant colony system algorithms. Finally, it briefly discusses parallel implementations of ant colony algorithms.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...Zilliz
Join us to introduce Milvus Lite, a vector database that can run on notebooks and laptops, share the same API with Milvus, and integrate with every popular GenAI framework. This webinar is perfect for developers seeking easy-to-use, well-integrated vector databases for their GenAI apps.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
20 Comprehensive Checklist of Designing and Developing a WebsitePixlogix Infotech
Dive into the world of Website Designing and Developing with Pixlogix! Looking to create a stunning online presence? Look no further! Our comprehensive checklist covers everything you need to know to craft a website that stands out. From user-friendly design to seamless functionality, we've got you covered. Don't miss out on this invaluable resource! Check out our checklist now at Pixlogix and start your journey towards a captivating online presence today.
20 Comprehensive Checklist of Designing and Developing a Website
TEI 4
1. Bahan Presentasi Teknik Elektro dan Informatika Lanjut 1 dan 2
Multi-Agent Intrusion Detection System in Industrial Network using Ant Colony
Clustering Approach and Unsupervised Feature Extraction
Oleh : Chi-Ho Tsang and Sam Kwong
Company
LOGO
4. Inside Monitor Agent (M)
Raw network packets Feature type
Packet capture engine
captured from subnets construction
Pre-processed data
sent to communication
PCA dimensionality
ICA feature extraction module of its
reduction
associiated Decission
Agent
6. Evolving ACO-MH
• Deneubourg
• Dorigo dkk
dkk • Dorigo dkk
Binary • Goss dkk • Addition of
Bridge SACO • Double Ant System
heuristic
Experiment • Path Bridge (AS)
information
Selection Experiment
(β)
Process
• Maniezo & Ant • Gambardella
Colorni, 1999 & Dorigo
Modified Colony Max-Min
• Ellitis AS • 4 difference
AS System aspects from
AS
• Use only α (ACS) AS
Fast Ant
Ant-Q System Antabu
(FANT)
AS-
Fundamentals of Computational Swarm Intelligence Rank
ANTS
Andries P. Engelbrecht
Wiley & Sons @2005
8. Binary Bridge Experiment
The probability of the next ant to choose path A
at time step t + 1 is given as,
where c quantifies the degree of attraction of an
unexplored branch, α is the bias to using
pheromone deposits in the decision process
This algorithm is executed at each point where
the ant needs to make a decision.
Goss et al. extended the it is assumed that ants deposit the same amount of pheromone
binary bridge experiment and that pheromone does not evaporate
11. SACO - Transition Probability
If ant k is currently located at node i, it selects the next node j ∈ Nki , based on the
transition probability:
ij is pheromone concentration associtated with edge (i,j)
A number of ants, k = 1, . . . , nk, are placed on the source node.
Nki is the set of feasible nodes connected to node i, with respect to ant k.
α is a positive constant used to amplify the influence of pheromone concentrations.
12. SACO – Amount of deposit pheromone
After a complete path from the origin node to the destination node is accomplished,
and all loops have been removed, each ant retraces its path to the source node
deterministically, and deposits a pheromone amount,
to each link, (i, j), of the corresponding path; Lk(t) is the length of the path
constructed by ant k at time step t.
That is,
(17.4)
Where nk is the number of ants
13. SACO – evaporation of pheromone intensities
Ants rapidly converge to a solution, and that little time is spent exploring alternative
paths.
To explore more, and to prevent premature convergence, pheromone intensities on
links are allowed to “evaporate” at each iteration of the algorithm before being
reinforced on the basis of the newly constructed paths.
For each link, (i, j), let
with ρ ∈ [0, 1].
The constant, ρ, specifies the rate at which pheromones evaporate.
The large values of ρ, pheromone evaporates rapidly, while small values of ρ result
in slower evaporation rates.
The more pheromones evaporate, the more random the search becomes, facilitating
better exploration. For ρ = 1, the search is completely random.
15. AS – Adding the heuristic
(17.6)
ij = aposteriori effectiveness of the move from i to j (pheromone intensity)
exploration
ηij = apriori effectiveness of the move from i to j (desirability/attractiveness/visibility)
exploitation
k
, defines the set of feasible nodes for ant k when located on node i.
i
To prevent loops, Nki may include all nodes not yet visited by ant k.
For this purpose, a tabu list is usually maintained for each ant.
As an ant visits a new node, that node is added to the ant’s tabu list. Nodes in
the tabu list are removed from Nki , ensuring that no node is visited more than
once.
16. AS – Modified
Maniezzo and Colorni:
Pheromone evaporation: (17.5)
After completion of a path by each ant, the pheromone on each link is updated as
with (17.10)
the amount of pheromone deposited by ant k on link (i, j) and k at time step t.
(17.14)