Search results for: distributed ontologies

Authors: Fisayo G. Ojo, Shamala K. Subramaniam, Zuriati Ahmad Zukarnain

Abstract:

As technology is advancing and wireless applications are becoming dependable sources, while the physical layer of the applications are been embedded into tiny layer, so the more the problem on energy efficiency and consumption. This paper reviews works done in recent years in wireless applications and distributed computing, we discovered that applications are becoming dependable, and resource allocation sharing with other applications in distributed computing. Applications embedded in distributed system are suffering from power stability and efficiency. In the reviews, we also prove that discrete event simulation has been left behind untouched and not been adapted into distributed system as a simulation technique in scheduling of each event that took place in the development of distributed computing applications. We shed more lights on some researcher proposed techniques and results in our reviews to prove the unsatisfactory results, and to show that more work still have to be done on issues of energy efficiency in wireless applications, and congestion in distributed computing.

Keywords: discrete event simulation (DES), distributed computing, energy efficiency (EE), internet of things (IOT), quality of service (QOS), user equipment (UE), wireless mesh network (WMN), wireless sensor network (wsn), worldwide interoperability for microwave access x (WiMAX)

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Authors: Anubhav Shrivastava Shivarudraswamy, Bhat Lakshya

Abstract:

Distributed generation has indeed become a major area of interest in recent years. Distributed generation can address a large number of loads in a power line and hence has better efficiency over the conventional methods. However, there are certain drawbacks associated with it, an increase in voltage being the major one. This paper addresses the voltage control at the buses for an IEEE 30 bus system by regulating reactive power. For carrying out the analysis, the suitable location for placing distributed generators (DG) is identified through load flow analysis and seeing where the voltage profile is dipping. MATLAB programming is used to regulate the voltage at all buses within +/- 5% of the base value even after the introduction of DGs. Three methods for regulation of voltage are discussed. A sensitivity based analysis is then carried out to determine the priority among the various methods listed in the paper.

Keywords: distributed generators, distributed system, reactive power, voltage control, sensitivity analysis

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Authors: Lai Junzhe, Wang Lihao, Burra Venkata Durga Kumar

Abstract:

In recent years, due to today's global technological advances, big data and artificial intelligence technologies have been widely used in various industries and fields, playing an important role in reducing costs and increasing efficiency. Among them, artificial intelligence has derived another branch in its own continuous progress and the continuous development of computer personnel, namely distributed artificial intelligence computing systems. Distributed AI is a method for solving complex learning, decision-making, and planning problems, characterized by the ability to take advantage of large-scale computation and the spatial distribution of resources, and accordingly, it can handle problems with large data sets. Nowadays, distributed AI is widely used in military, medical, and human daily life and brings great convenience and efficient operation to life. In this paper, we will discuss three areas of distributed AI computing systems in vision processing, blockchain, and smart home to introduce the performance of distributed systems and the role of AI in distributed systems.

Keywords: distributed system, artificial intelligence, blockchain, IoT, visual information processing, smart home

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Authors: Sabrina Azzi, Michal Iglewski, Véronique Nabelsi

Abstract:

Diagnosis error problem is frequent and one of the most important safety problems today. One of the main objectives of our work is to propose an ontological representation that takes into account the diagnostic criteria in order to improve the diagnostic. We choose pneumonia disease since it is one of the frequent diseases affected by diagnosis errors and have harmful effects on patients. To achieve our aim, we use a semi-automated method to integrate diverse knowledge sources that include publically available pneumonia disease guidelines from international repositories, biomedical ontologies and electronic health records. We follow the principles of the Open Biomedical Ontologies (OBO) Foundry. The resulting ontology covers symptoms and signs, all the types of pneumonia, antecedents, pathogens, and diagnostic testing. The first evaluation results show that most of the terms are covered by the ontology. This work is still in progress and represents a first and major step toward a development of a diagnosis decision support system for pneumonia.

Keywords: Clinical decision support system, Diagnostic errors, Ontology, Pneumonia

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Authors: Aliyu Isah Agaie, Masrah Azrifah Azmi Murad, Nurfadhlina Mohd Sharef, Aida Mustapha

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Natural Language Interfaces typically support a restricted language and also have scopes and limitations that naïve users are unaware of, resulting in errors when the users attempt to retrieve information from ontologies. To overcome this challenge, an auto-suggest feature is introduced into the querying process where users are guided through the querying process using interactive query construction system. Guiding users to formulate their queries, while providing them with an unconstrained (or almost unconstrained) way to query the ontology results in better interpretation of the query and ultimately lead to an effective search. The approach described in this paper is unobtrusive and subtly guides the users, so that they have a choice of either selecting from the suggestion list or typing in full. The user is not coerced into accepting system suggestions and can express himself using fragments or full sentences.

Keywords: auto-suggest, expressiveness, habitability, natural language interface, query interpretation, user guidance

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Authors: Karima Qayumi, Alex Norta

Abstract:

The rapid generation of high volume and a broad variety of data from the application of new technologies pose challenges for the generation of business-intelligence. Most organizations and business owners need to extract data from multiple sources and apply analytical methods for the purposes of developing their business. Therefore, the recently decentralized data management environment is relying on a distributed computing paradigm. While data are stored in highly distributed systems, the implementation of distributed data-mining techniques is a challenge. The aim of this technique is to gather knowledge from every domain and all the datasets stemming from distributed resources. As agent technologies offer significant contributions for managing the complexity of distributed systems, we consider this for next-generation data-mining processes. To demonstrate agent-based business intelligence operations, we use agent-oriented modeling techniques to develop a new artifact for mining massive datasets.

Keywords: agent-oriented modeling (AOM), business intelligence model (BIM), distributed data mining (DDM), multi-agent system (MAS)

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Authors: Byung Ho Jung, Ji Eun Shin, Dong Hoon Lim

Abstract:

Rhipe that integrates R and Hadoop environment made it possible to process and analyze massive amounts of data using a distributed processing environment. In this paper, we implemented multiple regression analysis using Rhipe with various data sizes of actual data. Experimental results for comparing the performance of our Rhipe with stats and biglm packages available on bigmemory, showed that our Rhipe was more fast than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases. We also compared the computing speeds of pseudo-distributed and fully-distributed modes for configuring Hadoop cluster. The results showed that fully-distributed mode was faster than pseudo-distributed mode, and computing speeds of fully-distributed mode were faster as the number of data nodes increases.

Keywords: big data, Hadoop, Parallel regression analysis, R, Rhipe

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Authors: Ishak Suleiman, Ahmad Kamsani Samingan, Yeoh Chun Yeow, Abdul Aziz Bin Abdul Rahman

Abstract:

In this paper, we evaluate the benefits of distributed 4x4 MIMO LTE downlink systems compared to that of the co-located 4x4 MIMO LTE downlink system. The performance evaluation was carried out experimentally by using Wireless Open-Access Research Platform (WARP), where the comparison between the 4x4 MIMO LTE transmission downlink system in distributed and co-located techniques was examined. The measured Error Vector Magnitude (EVM) results showed that the distributed technique achieved better system performance compared to the co-located arrangement.

Keywords: multiple-input-multiple-output (MIMO), distributed MIMO, co-located MIMO, LTE

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Authors: Lakshya Bhat, Anubhav Shrivastava, Shivarudraswamy

Abstract:

There has been a formidable interest in the area of Distributed Generation in recent times. A wide number of loads are addressed by Distributed Generators and have better efficiency too. The major disadvantage in Distributed Generation is voltage control- is highlighted in this paper. The paper addresses voltage control at buses in IEEE 14 Bus system by regulating reactive power. An analysis is carried out by selecting the most optimum location in placing the Distributed Generators through load flow analysis and seeing where the voltage profile rises. Matlab programming is used for simulation of voltage profile in the respective buses after introduction of DG’s. A tolerance limit of +/-5% of the base value has to be maintained.To maintain the tolerance limit , 3 methods are used. Sensitivity analysis of 3 methods for voltage control is carried out to determine the priority among the methods.

Keywords: distributed generators, distributed system, reactive power, voltage control, sensitivity analysis

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Authors: Shivarudraswamy, Anubhav Shrivastava, Lakshya Bhat

Abstract:

Distributed generation has indeed become a major area of interest in recent years. Distributed Generation can address large number of loads in a power line and hence has better efficiency over the conventional methods. However there are certain drawbacks associated with it, increase in voltage being the major one. This paper addresses the voltage control at the buses for an IEEE 30 bus system by regulating reactive power. For carrying out the analysis, the suitable location for placing distributed generators (DG) is identified through load flow analysis and seeing where the voltage profile is dipping. MATLAB programming is used to regulate the voltage at all buses within +/-5% of the base value even after the introduction of DG’s. Three methods for regulation of voltage are discussed. A sensitivity based analysis is later carried out to determine the priority among the various methods listed in the paper.

Keywords: distributed generators, distributed system, reactive power, voltage control

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Authors: Saeid Jalilzadeh, Majid Pakdel

Abstract:

The customer demand for better power quality and higher reliability has forced the power industry to use distributed generations (DGs) such as wind power and photo voltaic arrays. Islanding is a phenomenon occurs when a power grid becomes electrically isolated from the power system and the distribution system is energized by distributed generators. It is necessary to disconnect all distributed generators immediately after islanding occurrence. Therefore a DG system should have the capability to detect islanding phenomena. In this paper, a novel micro controller based relay for anti-islanding protection of a typical DG system is proposed. The simulation results using Proteus software verify the proper operation and effectiveness of the proposed protective relay.

Keywords: islanding, distributed generation (DG), protective relay, micro controller, proteus software

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Authors: Mohamed Haffar, Ramdane Djebarni, Russell Evans

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Despite a growth in literature on distributed leadership, the majority of studies are centred on large public organisations particularly within the health and education sectors. The purpose of this study is to fill the gap in the literature by exploring employee experiences of distributed leadership within two commercial consultancy SME businesses in the UK and USA. The aim of the study informed an exploratory method of research to gather qualitative data drawn from semi-structured interviews involving a sample of employees in each organisation. A series of broad, open questions were used to explore the employees’ experiences; evidence of distributed leadership; and extant barriers and practices in each organisation. Whilst some of our findings aligned with patterns and practices in the existing literature, it importantly discovered some emergent themes that have not previously been recognised in the previous studies. Our investigation identified that whilst distributed leadership was in evidence in both organisations, the interviewees’ experience reported that it was sporadic and inconsistent. Moreover, non-client focused projects were reported to be less important and distributed leadership was found to be inconsistent or non-existent.

Keywords: consultancy, distributed leadership, owner-manager, SME, entrepreneur

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Authors: Tarek Kandil, Ameen Ali

Abstract:

Distributed generation (DG) has recently gained a lot of momentum in power industry due to market deregulation and environmental concerns. One of the most technical challenges facing DGs is islanding of distributed generators. The current industry practice is to disconnect all distributed generators immediately after the occurrence of islands within 200 to 350 ms after loss of main supply. To achieve such goal, each DG must be equipped with an islanding detection device. Frequency relays are one of the most commonly used loss of mains detection method. However, distribution utilities may be faced with concerns related to false operation of these frequency relays due to improper settings. The commercially available frequency relays are considering standard tight setting. This paper investigates some factors related to relays internal algorithm that contribute to their different operating responses. Further, the relay operation in the presence of multiple distributed at the same network is analyzed. Finally, the relay setting can be accurately determined based on these investigation and analysis.

Keywords: frequency relay, distributed generation, islanding detection, relay setting

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Authors: Toshiya Kawato, Shin-ichi Motomura, Masayuki Higashino, Takao Kawamura

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Storage for storing data is indispensable. If a storage capacity becomes insufficient, we can increase its capacity by adding new disks. It is, however, difficult to add a new disk when a budget is not enough. On the other hand, there are many unused idle resources such as used personal computers despite those use value. In order to solve those problems, used personal computers can be reused as storage. In this paper, we attempt to reuse used-PCs as a distributed storage. First, we list up the characteristics of used-PCs and design a storage system that utilizes its characteristics. Next, we experimentally implement an auto-construction system that automatically constructs a distributed storage environment in used-PCs.

Keywords: distributed storage, used personal computer, idle resource, auto construction

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Authors: Andrew Hall, Paul Clarkson

Abstract:

Climate change is predicted to increase the number of extreme weather events intensifying the strain on Railway Earthworks. This paper describes the use of Distributed Rayleigh Sensing to monitor low frequency activity on a vulnerable earthworks sectionprone to landslides alongside a railway line in Northern Spain. The vulnerable slope is instrumented with conventional slope stability sensors allowing an assessment to be conducted of the application of Distributed Rayleigh Sensing as an earthwork condition monitoring tool to enhance the resilience of railway networks.

Keywords: condition monitoring, railway earthworks, distributed rayleigh sensing, climate change

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Authors: Benhamouda Sara, Guezouli Larbi

Abstract:

Nowadays, the dissemination of information touches the distributed world, where selecting the relevant servers to a user request is an important problem in distributed information retrieval. During the last decade, several research studies on this issue have been launched to find optimal solutions and many approaches of collection selection have been proposed. In this paper, we propose a new collection selection approach that takes into consideration the number of documents in a collection that contains terms of the query and the weights of those terms in these documents. We tested our method and our studies show that this technique can compete with other state-of-the-art algorithms that we choose to test the performance of our approach.

Keywords: distributed information retrieval, relevance, server selection, collection selection

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Authors: Wu You, Burra Venkata Durga Kumar

Abstract:

This study examines the promising potential of integrating Blockchain and Artificial Intelligence (AI) technologies to scalability in Distributed Systems within the field of supply chain finance. The finance industry is continually confronted with scalability challenges in its Distributed Systems, particularly within the supply chain finance sector, impacting efficiency and security. Blockchain, with its inherent attributes of high scalability and secure distributed ledger system, coupled with AI's strengths in optimizing data processing and decision-making, holds the key to innovating the industry's approach to these issues. This study elucidates the synergistic interplay between Blockchain and AI, detailing how their fusion can drive a significant transformation in the supply chain finance sector's Distributed Systems. It offers specific use-cases within this field to illustrate the practical implications and potential benefits of this technological convergence. The study also discusses future possibilities and current challenges in implementing this groundbreaking approach within the context of supply chain finance. It concludes that the intersection of Blockchain and AI could ignite a new epoch of enhanced efficiency, security, and transparency in the Distributed Systems of supply chain finance within the financial industry.

Keywords: blockchain, artificial intelligence (AI), scaled distributed systems, supply chain finance, efficiency and security

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Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a distributed hybrid algorithm is proposed for solving the job shop scheduling problem. The suggested method executes different artificial neural networks, heuristics and meta-heuristics simultaneously on more than one machine. The neural networks are used to control the constraints of the problem while the meta-heuristics search the global space and the heuristics are used to prevent the premature convergence. To attain an efficient distributed intelligent method for solving big and distributed job shop scheduling problems, Apache Spark and Hadoop frameworks are used. In the algorithm implementation and design steps, new approaches are applied. Comparison between the proposed algorithm and other efficient algorithms from the literature shows its efficiency, which is able to solve large size problems in short time.

Keywords: distributed algorithms, Apache Spark, Hadoop, job shop scheduling, neural network

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Authors: Fatéma Zahra Benchara, Mohamed Youssfi, Omar Bouattane, Hassan Ouajji, Mohamed Ouadi Bensalah

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In this paper, we propose a new distributed environment for High Performance Computing (HPC) based on mobile agents. It allows us to perform parallel programs execution as distributed one over a flexible grid constituted by a cooperative mobile agent team works. The distributed program to be performed is encapsulated on team leader agent which deploys its team workers as Agent Virtual Processing Unit (AVPU). Each AVPU is asked to perform its assigned tasks and provides the computational results which make the data and team works tasks management difficult for the team leader agent and that influence the performance computing. In this work we focused on the implementation of the Mobile Provider Agent (MPA) in order to manage the distribution of data and instructions and to ensure a load balancing model. It grants also some interesting mechanisms to manage the others computing challenges thanks to the mobile agents several skills.

Keywords: image processing, distributed environment, mobile agents, parallel and distributed computing

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Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

Abstract:

As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling, and proposes the challenges and improvement directions for DRL-based resource scheduling algorithms.

Keywords: resource scheduling, deep reinforcement learning, distributed system, artificial intelligence

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Authors: Joon-Hoon Park

Abstract:

In this paper the rationalized Haar transform is applied for distributed parameter system identification and estimation. A distributed parameter system is a dynamical and mathematical model described by a partial differential equation. And system identification concerns the problem of determining mathematical models from observed data. The Haar function has some disadvantages of calculation because it contains irrational numbers, for these reasons the rationalized Haar function that has only rational numbers. The algorithm adopted in this paper is based on the transform and operational matrix of the rationalized Haar function. This approach provides more convenient and efficient computational results.

Keywords: distributed parameter system, rationalized Haar transform, operational matrix, system identification

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Authors: Mahmoud M. Othman, Y. G. Hegazy, A. Y. Abdelaziz

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This paper proposes a novel heuristic algorithm that aims to determine the best size and location of distributed generators in unbalanced distribution networks. The proposed heuristic algorithm can deal with the planning cases where power loss is to be optimized without violating the system practical constraints. The distributed generation units in the proposed algorithm is modeled as voltage controlled node with the flexibility to be converted to constant power factor node in case of reactive power limit violation. The proposed algorithm is implemented in MATLAB and tested on the IEEE 37 -node feeder. The results obtained show the effectiveness of the proposed algorithm.

Keywords: distributed generation, heuristic approach, optimization, planning

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Authors: Larbi Guezouli, Imane Azzouz

Abstract:

This work is located in the domain of distributed information retrieval ‘DIR’. A simplified view of the DIR requires a multi-search in a set of collections, which forces the system to analyze results found in these collections, and merge results back before sending them to the user in a single list. Our work is to find a fusion method based on the relevance score of each result received from collections and the relevance of the local search engine of each collection.

Keywords: information retrieval, distributed IR systems, merging results, datamining

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Authors: Pawel Sowa, Joachim Bargiel, Bogdan Mol, Katarzyna Luszcz

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The article raises the issue of the development of local renewable energy sources and the production of distributed energy in context of improving the reliability of the Polish Power System and the beneficial impact on local and national energy security. The paper refers to the current problems of local governments in the process of investment in the area of distributed energy projects, and discusses the issues of the future role and cooperation within the local power plants and distributed energy. Attention is paid to the local communities the chance to raise their own resources and management of energy fuels (biomass, wind, gas mining) and improving the local energy balance. The material presented takes the issue of the development of the energy potential of municipalities and future cooperation with professional energy. As an example, practical solutions used in one of the communes in Silesia.

Keywords: distributed generation, mini centers energy, renewable energy sources, reliability of supply of rural commune

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Authors: Can Zhang, Qun Li, Yonglin Lei, Zhi Zhu, Dong Guo

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Aiming at the problem of factor screen in distributed collaborative navigation of dense UAV swarm, an efficient distributed collaborative navigation factor screen method is proposed. The method considered the balance between computing load and positioning accuracy. The proposed algorithm utilized the factor graph model to implement a distributed collaborative navigation algorithm. The GNSS information of the UAV itself and the ranging information between the UAVs are used as the positioning factors. In this distributed scheme, a local factor graph is established for each UAV. The positioning factors of nodes with good geometric position distribution and small variance are selected to participate in the navigation calculation. To demonstrate and verify the proposed methods, the simulation and experiments in different scenarios are performed in this research. Simulation results show that the proposed scheme achieves a good balance between the computing load and positioning accuracy in the distributed cooperative navigation calculation of UAV swarm. This proposed algorithm has important theoretical and practical value for both industry and academic areas.

Keywords: screen method, cooperative positioning system, UAV swarm, factor graph, cooperative navigation

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Authors: Akash Amalan, Rui Wang, Yanqi Qiao, Emmanouil Panaousis, Kaitai Liang

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Federated learning is an emerging concept in the domain of distributed machine learning. This concept has enabled General Adversarial Networks (GANs) to benefit from the rich distributed training data while preserving privacy. However, in a non-IID setting, current federated GAN architectures are unstable, struggling to learn the distinct features, and vulnerable to mode collapse. In this paper, we propose an architecture MULTI-FLGAN to solve the problem of low-quality images, mode collapse, and instability for non-IID datasets. Our results show that MULTI-FLGAN is four times as stable and performant (i.e., high inception score) on average over 20 clients compared to baseline FLGAN.

Keywords: federated learning, generative adversarial network, inference attack, non-IID data distribution

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Authors: Arun Sanjel, Greg Speegle

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Every second, massive amounts of data are generated, and Data Intensive Scalable Computing (DISC) frameworks have evolved into effective tools for analyzing such massive amounts of data. Since the underlying architecture of these distributed computing platforms is often new to users, building a DISC application can often be time-consuming and prone to errors. The automated conversion of a sequential program to a DISC program will consequently significantly improve productivity. However, synthesizing a user’s intended program from an input specification is complex, with several important applications, such as distributed program synthesizing and code refactoring. Existing works such as Tyro and Casper rely entirely on deductive synthesis techniques or similar program synthesis approaches. Our approach is to develop a data-driven synthesis technique to identify sequential components and translate them to equivalent distributed operations. We emphasize using reinforcement learning and unit testing as feedback mechanisms to achieve our objectives.

Keywords: program synthesis, distributed computing, reinforcement learning, unit testing, DISC

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Authors: Abdulrahman M. Qahtani, Gary. B. Wills, Andy. M. Gravell

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Communicating and managing customers’ requirements in software development projects play a vital role in the software development process. While it is difficult to do so locally, it is even more difficult to communicate these requirements over distributed boundaries and to convey them to multiple distribution customers. This paper discusses the communication of multiple distribution customers’ requirements in the context of customised software products. The main purpose is to understand the challenges of communicating and managing customisation requirements across distributed boundaries. We propose a model for Communicating Customisation Requirements of Multi-Clients in a Distributed Domain (CCRD). Thereafter, we evaluate that model by presenting the findings of a case study conducted with a company with customisation projects for 18 distributed customers. Then, we compare the outputs of the real case process and the outputs of the CCRD model using simulation methods. Our conjecture is that the CCRD model can reduce the challenge of communication requirements over distributed organisational boundaries, and the delay in decision making and in the entire customisation process time.

Keywords: customisation software products, global software engineering, local decision making, requirement engineering, simulation model

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Authors: Edafe Lucky Okotie, Emmanuel Osawaru Omosigho

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This paper examines the impacts of the introduction of distributed energy generation (DEG) technology into the Nigerian power system as an alternative means of energy generation at distribution ends using Otovwodo 15 MVA, 33/11kV injection substation as a case study. The overall idea is to increase the generated energy in the system, improve the voltage profile and reduce system losses. A photovoltaic-based distributed energy generator (PV-DEG) was considered and was optimally placed in the network using Genetic Algorithm (GA) in Mat. Lab/Simulink environment. The results of simulation obtained shows that the dynamic performance of the network was optimized with DEG-grid integration.

Keywords: distributed energy generation (DEG), genetic algorithm (GA), power quality, total load demand, voltage profile

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Authors: Thomas Smith

Abstract:

Many hackers worldwide would agree that, had it not been for linear-time theory, the refinement of Byzantine fault tolerance might never have occurred. After years of significant research into extreme programming, we validate the refinement of simulated annealing. Maw, our new framework for unstable theory, is the solution to all of these issues.

Keywords: distributed, software engineering, DNS, DHCP

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