Search results for: anchor nodes
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 722

Search results for: anchor nodes

212 Blockchain for Transport: Performance Simulations of Blockchain Network for Emission Monitoring Scenario

Authors: Dermot O'Brien, Vasileios Christaras, Georgios Fontaras, Igor Nai Fovino, Ioannis Kounelis

Abstract:

With the rise of the Internet of Things (IoT), 5G, and blockchain (BC) technologies, vehicles are becoming ever increasingly connected and are already transmitting substantial amounts of data to the original equipment manufacturers (OEMs) servers. This data could be used to help detect mileage fraud and enable more accurate vehicle emissions monitoring. This would not only help regulators but could enable applications such as permitting efficient drivers to pay less tax, geofencing for air quality improvement, as well as pollution tolling and trading platforms for transport-related businesses and EU citizens. Other applications could include traffic management and shared mobility systems. BC enables the transmission of data with additional security and removes single points of failure while maintaining data provenance, identity ownership, and the possibility to retain varying levels of privacy depending on the requirements of the applied use case. This research performs simulations of vehicles interacting with European member state authorities and European Commission BC nodes that are running hyperleger fabric and explores whether the technology is currently feasible for transport applications such as the emission monitoring use-case.

Keywords: future transportation systems, technological innovations, policy approaches for transportation future, economic and regulatory trends, blockchain

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211 Clinicopathological Findings of Partuberclosis in Camels: Possible Steps for Control Strategy

Authors: A. M. Almujalli, G. M. Al-Ghamdi

Abstract:

Mycobacterium avium subspecies paratuberculosis causes paratuberculosis, a chronic debilitating granulomatous enteritis, in camels as well as domestic and wild ruminants. The clinical manifestation of the disease in camel is not well characterized, therefore this study was aimed to investigate the clinical and pathological pictures of camels that are suffering from partuberculosis. Twelve young camels that were presented to the Veterinary Teaching Hospital, King Faisal University were investigated. Clinical and pathological examination were performed. The results revealed highly significant increase in creatinine, blood urea nitrogen, magnesium, AST and ALT in diseased camels, while glucose, total protein and albumin were highly significantly decreased in diseased camels when compared to healthy ones. Post-mortem testing indicated thickening, corrugation of the intestinal wall, folded mucosa, enlarged and oedemated ileocaecal and mesenteric lymph nodes. The microscopic findings detected short, blunt and distorted intestinal villi with hyperactive goblet cells of the villi and the crypts of lieberkuhn contained mucin droplets. The lamina propria was heavily infiltrated with mononuclear cells mostly macrophages. This clinical picture of paratuberculosis may be used to initiate control strategy to limit the spread of the disease in camel herds.

Keywords: camel, partuberclosis, control, Saudi Arabia

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210 Nature Manifestations: An Archetypal Analysis of Selected Nightwish Songs

Authors: Suzanne Strauss, Leandi Steenkamp

Abstract:

The Finnish symphonic metal band Nightwish is the brainchild of songwriter and lyricist TuomasHolopainen and the band recorded their first demonstration recording in 1996. The band has since produced nine full-length studio albums, the most recent being the 2020 album Human. :||: Nature., and has reached massive international success. The band is well known for songs about fantasy and escapism and employs many sonic, visual and branding tools and techniques to communicate these constructs to the audience. Among these, is the band’s creation of the so-called “Nightwish world and mythology” with a set of recurring characters and narratives which, in turn, creates a psychological anchor and safe space for Nightwish fans around the globe. Nature and the reverence of nature are central themes in Nightwish’s self-created mythology.Swiss psychologist Carl Jung’s theory of the collective unconscious identified a mysterious reservoir of psychological constructs common to all people, being derived from ancestral memory and experience, common to all humankind, and distinct from the individual’s personal unconscious. Furthermore, he defined archetypes as timeless collective patterns and images that springs forth from the collective unconscious. Archetypes can be actualized when they enter consciousness as images in interaction with the outside world. Archetypal patterns or images can manifest in different ways across world cultures, but follow common patterns, also known as archetypal themes and symbols. The Jungian approach to the psyche places great emphasis on nature, positing a direct link betweenthe concept of wholeness and responsible care for nature and the environment.In our proposed paper, we examine, by means of thematic content analysis, how Nightwish makes use of archetypal themes and symbols referring to nature and the environment in selected songs from their ninth full-length album Human. II Nature. Furthermore, we argue that the longing for and reverence of nature in selected Nightwish songs may serve as a type of “social intervention” and social critique on modern capitalist society. The type of social critique that the band offers is generally connoted intertextually and is not equally explicit in their songs. The band uses a unique combination of escapism, fantasy, and nature narratives to inspire a sense of wonder, enchantment, and magic in the listener. In this way, escapism, fantasy, and nature serve as postmodern frames of reference that aim to “re-enchant” the disenchanted and de-spiritualized. In this way, re-enchantment could also refer to spiritual and/or psychological healing and rebirth.

Keywords: archetypes, metal music, nature, Nightwish, social interventions

Procedia PDF Downloads 86
209 MhAGCN: Multi-Head Attention Graph Convolutional Network for Web Services Classification

Authors: Bing Li, Zhi Li, Yilong Yang

Abstract:

Web classification can promote the quality of service discovery and management in the service repository. It is widely used to locate developers desired services. Although traditional classification methods based on supervised learning models can achieve classification tasks, developers need to manually mark web services, and the quality of these tags may not be enough to establish an accurate classifier for service classification. With the doubling of the number of web services, the manual tagging method has become unrealistic. In recent years, the attention mechanism has made remarkable progress in the field of deep learning, and its huge potential has been fully demonstrated in various fields. This paper designs a multi-head attention graph convolutional network (MHAGCN) service classification method, which can assign different weights to the neighborhood nodes without complicated matrix operations or relying on understanding the entire graph structure. The framework combines the advantages of the attention mechanism and graph convolutional neural network. It can classify web services through automatic feature extraction. The comprehensive experimental results on a real dataset not only show the superior performance of the proposed model over the existing models but also demonstrate its potentially good interpretability for graph analysis.

Keywords: attention mechanism, graph convolutional network, interpretability, service classification, service discovery

Procedia PDF Downloads 112
208 Performance Evaluation of Distributed Deep Learning Frameworks in Cloud Environment

Authors: Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang

Abstract:

2016 has become the year of the Artificial Intelligence explosion. AI technologies are getting more and more matured that most world well-known tech giants are making large investment to increase the capabilities in AI. Machine learning is the science of getting computers to act without being explicitly programmed, and deep learning is a subset of machine learning that uses deep neural network to train a machine to learn  features directly from data. Deep learning realizes many machine learning applications which expand the field of AI. At the present time, deep learning frameworks have been widely deployed on servers for deep learning applications in both academia and industry. In training deep neural networks, there are many standard processes or algorithms, but the performance of different frameworks might be different. In this paper we evaluate the running performance of two state-of-the-art distributed deep learning frameworks that are running training calculation in parallel over multi GPU and multi nodes in our cloud environment. We evaluate the training performance of the frameworks with ResNet-50 convolutional neural network, and we analyze what factors that result in the performance among both distributed frameworks as well. Through the experimental analysis, we identify the overheads which could be further optimized. The main contribution is that the evaluation results provide further optimization directions in both performance tuning and algorithmic design.

Keywords: artificial intelligence, machine learning, deep learning, convolutional neural networks

Procedia PDF Downloads 177
207 Investigating Message Timing Side Channel Attacks on Networks on Chip with Ring Topology

Authors: Mark Davey

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Communications on a Network on Chip (NoC) produce timing information, i.e., network injection delays, packet traversal times, throughput metrics, and other attributes relating to the traffic being sent across the chip. The security requirements of a platform encompass each node to operate with confidentiality, integrity, and availability (ISO 27001). Inherently, a shared NoC interconnect is exposed to analysis of timing patterns created by contention for the network components, i.e., links and switches/routers. This phenomenon is defined as information leakage, which represents a ‘side channel’ of sensitive information that can be correlated to platform activity. The key algorithm presented in this paper evaluates how an adversary can control two platform neighbouring nodes of a target node to obtain sensitive information about communication with the target node. The actual information obtained is the period value of a periodic task communication. This enacts a breach of the expected confidentiality of a node operating in a multiprocessor platform. An experimental investigation of the side channel is undertaken to judge the level and significance of inferred information produced by access times to the NoC. Results are presented with a series of expanding task set scenarios to evaluate the efficacy of the side channel detection algorithm as the network load increases.

Keywords: embedded systems, multiprocessor, network on chip, side channel

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206 An Enhanced Hybrid Backoff Technique for Minimizing the Occurrence of Collision in Mobile Ad Hoc Networks

Authors: N. Sabiyath Fatima, R. K. Shanmugasundaram

Abstract:

In Mobile Ad-hoc Networks (MANETS), every node performs both as transmitter and receiver. The existing backoff models do not exactly forecast the performance of the wireless network. Also, the existing models experience elevated packet collisions. Every time a collision happens, the station’s contention window (CW) is doubled till it arrives at the utmost value. The main objective of this paper is to diminish collision by means of contention window Multiplicative Increase Decrease Backoff (CWMIDB) scheme. The intention of rising CW is to shrink the collision possibility by distributing the traffic into an outsized point in time. Within wireless Ad hoc networks, the CWMIDB algorithm dynamically controls the contention window of the nodes experiencing collisions. During packet communication, the backoff counter is evenly selected from the given choice of [0, CW-1]. At this point, CW is recognized as contention window and its significance lies on the amount of unsuccessful transmission that had happened for the packet. On the initial transmission endeavour, CW is put to least amount value (C min), if transmission effort fails, subsequently the value gets doubled, and once more the value is set to least amount on victorious broadcast. CWMIDB is simulated inside NS2 environment and its performance is compared with Binary Exponential Backoff Algorithm. The simulation results show improvement in transmission probability compared to that of the existing backoff algorithm.

Keywords: backoff, contention window, CWMIDB, MANET

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205 Blockchain-Based Approach on Security Enhancement of Distributed System in Healthcare Sector

Authors: Loong Qing Zhe, Foo Jing Heng

Abstract:

A variety of data files are now available on the internet due to the advancement of technology across the globe today. As more and more data are being uploaded on the internet, people are becoming more concerned that their private data, particularly medical health records, are being compromised and sold to others for money. Hence, the accessibility and confidentiality of patients' medical records have to be protected through electronic means. Blockchain technology is introduced to offer patients security against adversaries or unauthorised parties. In the blockchain network, only authorised personnel or organisations that have been validated as nodes may share information and data. For any change within the network, including adding a new block or modifying existing information about the block, a majority of two-thirds of the vote is required to confirm its legitimacy. Additionally, a consortium permission blockchain will connect all the entities within the same community. Consequently, all medical data in the network can be safely shared with all authorised entities. Also, synchronization can be performed within the cloud since the data is real-time. This paper discusses an efficient method for storing and sharing electronic health records (EHRs). It also examines the framework of roles within the blockchain and proposes a new approach to maintain EHRs with keyword indexes to search for patients' medical records while ensuring data privacy.

Keywords: healthcare sectors, distributed system, blockchain, electronic health records (EHR)

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204 Revitalization Strategy of Beijing-Tianjin-Hebei Rural Areas Organized by Production-Living-Ecology Spatial Network at Township Level

Authors: Liuhui Zhu, Peng Zeng

Abstract:

The rural revitalization strategy means to take the country and the city on the same level, and achieve urban-rural integration and comprehensive development of rural areas. Beijing-Tianjin-Hebei rural areas have always been the weak links in the region, with prominently uneven development between urban and rural areas. The rural areas need to join the overall regional synergy. Based on the analysis of the characteristics and problems of rural development in the region from the perspective of production-living-ecology space, the paper proposes the township as the basic unit for rural revitalization according to the overall requirements of the rural revitalization strategy. The basic unit helps to realize resource arrangement, functional organization, and collaborative governance organized by the production-living-ecology spatial network. The paper summarizes the planning strategies for the basic unit. Through spatial cognition and spatial reconstruction, the three space is networked through the base, nodes, and connections to improve the comprehensive value of rural areas and achieve the multiple goals of rural revitalization.

Keywords: rural revitalization, Beijing-Tianjin-Hebei region, township level, production-living-ecology spatial network

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203 Turbulent Channel Flow Synthesis using Generative Adversarial Networks

Authors: John M. Lyne, K. Andrea Scott

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In fluid dynamics, direct numerical simulations (DNS) of turbulent flows require large amounts of nodes to appropriately resolve all scales of energy transfer. Due to the size of these databases, sharing these datasets amongst the academic community is a challenge. Recent work has been done to investigate the use of super-resolution to enable database sharing, where a low-resolution flow field is super-resolved to high resolutions using a neural network. Recently, Generative Adversarial Networks (GAN) have grown in popularity with impressive results in the generation of faces, landscapes, and more. This work investigates the generation of unique high-resolution channel flow velocity fields from a low-dimensional latent space using a GAN. The training objective of the GAN is to generate samples in which the distribution of the generated samplesis ideally indistinguishable from the distribution of the training data. In this study, the network is trained using samples drawn from a statistically stationary channel flow at a Reynolds number of 560. Results show that the turbulent statistics and energy spectra of the generated flow fields are within reasonable agreement with those of the DNS data, demonstrating that GANscan produce the intricate multi-scale phenomena of turbulence.

Keywords: computational fluid dynamics, channel flow, turbulence, generative adversarial network

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202 Study of the Facilities in the Cultural and Ecotourism Route in the Area of Om Nont Canal, Nonthaburi Provice, Thailand

Authors: Supattra Suanlim

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Nonthaburi province is one of the provinces in the central region of Thailand. There is the Chao Phraya River, which is a large and important river of Thailand passing through the province. With the way of life and social changes since the past. There is a digging canal called Lat canal or Om canal, communities along the canal have dense settlements. Important in life and culture. This research has 3 objectives as follows. 1.To explore cultural and ecotourism attractions in the Om Nont canal area. 2.To explore the facilities in the Om Nont canal tourist attraction. To suggest facilities for tourist attractions in the Om Nont canal, Nonthaburi, Thailand. This research is a qualitative research, using research methods by collecting data and surveying tourist attractions by water traffic. The results of the research can be concluded that There are 21 tourist attractions that have the potential to welcome tourists who want to travel cultural. 16 temples or places of worship, 2 government offices, 1 market, 2 landmarks. Each should be improved to increase the potential of the paths. There should be improvements in the road landscape that is a connection to water traffic. Districts should have signage and signage installation within tourist sites and have guidelines for architectural improvements. And the Nodes should improve the public space of the community. Such as the Nonthaburi pier area to have the idea of designing a tourist center Provide information in both Thai and English.

Keywords: Community, Cultural, Ecotourism, Facility

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201 Graph Cuts Segmentation Approach Using a Patch-Based Similarity Measure Applied for Interactive CT Lung Image Segmentation

Authors: Aicha Majda, Abdelhamid El Hassani

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Lung CT image segmentation is a prerequisite in lung CT image analysis. Most of the conventional methods need a post-processing to deal with the abnormal lung CT scans such as lung nodules or other lesions. The simplest similarity measure in the standard Graph Cuts Algorithm consists of directly comparing the pixel values of the two neighboring regions, which is not accurate because this kind of metrics is extremely sensitive to minor transformations such as noise or other artifacts problems. In this work, we propose an improved version of the standard graph cuts algorithm based on the Patch-Based similarity metric. The boundary penalty term in the graph cut algorithm is defined Based on Patch-Based similarity measurement instead of the simple intensity measurement in the standard method. The weights between each pixel and its neighboring pixels are Based on the obtained new term. The graph is then created using theses weights between its nodes. Finally, the segmentation is completed with the minimum cut/Max-Flow algorithm. Experimental results show that the proposed method is very accurate and efficient, and can directly provide explicit lung regions without any post-processing operations compared to the standard method.

Keywords: graph cuts, lung CT scan, lung parenchyma segmentation, patch-based similarity metric

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200 An Approach of Node Model TCnNet: Trellis Coded Nanonetworks on Graphene Composite Substrate

Authors: Diogo Ferreira Lima Filho, José Roberto Amazonas

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Nanotechnology opens the door to new paradigms that introduces a variety of novel tools enabling a plethora of potential applications in the biomedical, industrial, environmental, and military fields. This work proposes an integrated node model by applying the same concepts of TCNet to networks of nanodevices where the nodes are cooperatively interconnected with a low-complexity Mealy Machine (MM) topology integrating in the same electronic system the modules necessary for independent operation in wireless sensor networks (WSNs), consisting of Rectennas (RF to DC power converters), Code Generators based on Finite State Machine (FSM) & Trellis Decoder and On-chip Transmit/Receive with autonomy in terms of energy sources applying the Energy Harvesting technique. This approach considers the use of a Graphene Composite Substrate (GCS) for the integrated electronic circuits meeting the following characteristics: mechanical flexibility, miniaturization, and optical transparency, besides being ecological. In addition, graphene consists of a layer of carbon atoms with the configuration of a honeycomb crystal lattice, which has attracted the attention of the scientific community due to its unique Electrical Characteristics.

Keywords: composite substrate, energy harvesting, finite state machine, graphene, nanotechnology, rectennas, wireless sensor networks

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199 Wireless Sensor Network for Forest Fire Detection and Localization

Authors: Tarek Dandashi

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WSNs may provide a fast and reliable solution for the early detection of environment events like forest fires. This is crucial for alerting and calling for fire brigade intervention. Sensor nodes communicate sensor data to a host station, which enables a global analysis and the generation of a reliable decision on a potential fire and its location. A WSN with TinyOS and nesC for the capturing and transmission of a variety of sensor information with controlled source, data rates, duration, and the records/displaying activity traces is presented. We propose a similarity distance (SD) between the distribution of currently sensed data and that of a reference. At any given time, a fire causes diverging opinions in the reported data, which alters the usual data distribution. Basically, SD consists of a metric on the Cumulative Distribution Function (CDF). SD is designed to be invariant versus day-to-day changes of temperature, changes due to the surrounding environment, and normal changes in weather, which preserve the data locality. Evaluation shows that SD sensitivity is quadratic versus an increase in sensor node temperature for a group of sensors of different sizes and neighborhood. Simulation of fire spreading when ignition is placed at random locations with some wind speed shows that SD takes a few minutes to reliably detect fires and locate them. We also discuss the case of false negative and false positive and their impact on the decision reliability.

Keywords: forest fire, WSN, wireless sensor network, algortihm

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198 Autonomous Kuka Youbot Navigation Based on Machine Learning and Path Planning

Authors: Carlos Gordon, Patricio Encalada, Henry Lema, Diego Leon, Dennis Chicaiza

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The following work presents a proposal of autonomous navigation of mobile robots implemented in an omnidirectional robot Kuka Youbot. We have been able to perform the integration of robotic operative system (ROS) and machine learning algorithms. ROS mainly provides two distributions; ROS hydro and ROS Kinect. ROS hydro allows managing the nodes of odometry, kinematics, and path planning with statistical and probabilistic, global and local algorithms based on Adaptive Monte Carlo Localization (AMCL) and Dijkstra. Meanwhile, ROS Kinect is responsible for the detection block of dynamic objects which can be in the points of the planned trajectory obstructing the path of Kuka Youbot. The detection is managed by artificial vision module under a trained neural network based on the single shot multibox detector system (SSD), where the main dynamic objects for detection are human beings and domestic animals among other objects. When the objects are detected, the system modifies the trajectory or wait for the decision of the dynamic obstacle. Finally, the obstacles are skipped from the planned trajectory, and the Kuka Youbot can reach its goal thanks to the machine learning algorithms.

Keywords: autonomous navigation, machine learning, path planning, robotic operative system, open source computer vision library

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197 Graph Neural Networks and Rotary Position Embedding for Voice Activity Detection

Authors: YingWei Tan, XueFeng Ding

Abstract:

Attention-based voice activity detection models have gained significant attention in recent years due to their fast training speed and ability to capture a wide contextual range. The inclusion of multi-head style and position embedding in the attention architecture are crucial. Having multiple attention heads allows for differential focus on different parts of the sequence, while position embedding provides guidance for modeling dependencies between elements at various positions in the input sequence. In this work, we propose an approach by considering each head as a node, enabling the application of graph neural networks (GNN) to identify correlations among the different nodes. In addition, we adopt an implementation named rotary position embedding (RoPE), which encodes absolute positional information into the input sequence by a rotation matrix, and naturally incorporates explicit relative position information into a self-attention module. We evaluate the effectiveness of our method on a synthetic dataset, and the results demonstrate its superiority over the baseline CRNN in scenarios with low signal-to-noise ratio and noise, while also exhibiting robustness across different noise types. In summary, our proposed framework effectively combines the strengths of CNN and RNN (LSTM), and further enhances detection performance through the integration of graph neural networks and rotary position embedding.

Keywords: voice activity detection, CRNN, graph neural networks, rotary position embedding

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196 Bitcoin, Blockchain and Smart Contract: Attacks and Mitigations

Authors: Mohamed Rasslan, Doaa Abdelrahman, Mahmoud M. Nasreldin, Ghada Farouk, Heba K. Aslan

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Blockchain is a distributed database that endorses transparency while bitcoin is a decentralized cryptocurrency (electronic cash) that endorses anonymity and is powered by blockchain technology. Smart contracts are programs that are stored on a blockchain. Smart contracts are executed when predetermined conditions are fulfilled. Smart contracts automate the agreement execution in order to make sure that all participants immediate-synchronism of the outcome-certainty, without any intermediary's involvement or time loss. Currently, the Bitcoin market worth billions of dollars. Bitcoin could be transferred from one purchaser to another without the need for an intermediary bank. Network nodes through cryptography verify bitcoin transactions, which are registered in a public-book called “blockchain”. Bitcoin could be replaced by other coins, merchandise, and services. Rapid growing of the bitcoin market-value, encourages its counterparts to make use of its weaknesses and exploit vulnerabilities for profit. Moreover, it motivates scientists to define known vulnerabilities, offer countermeasures, and predict future threats. In his paper, we study blockchain technology and bitcoin from the attacker’s point of view. Furthermore, mitigations for the attacks are suggested, and contemporary security solutions are discussed. Finally, research methods that achieve strict security and privacy protocol are elaborated.

Keywords: Cryptocurrencies, Blockchain, Bitcoin, Smart Contracts, Peer-to-Peer Network, Security Issues, Privacy Techniques

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195 Merging Appeal to Ignorance, Composition, and Division Argument Schemes with Bayesian Networks

Authors: Kong Ngai Pei

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The argument scheme approach to argumentation has two components. One is to identify the recurrent patterns of inferences used in everyday discourse. The second is to devise critical questions to evaluate the inferences in these patterns. Although this approach is intuitive and contains many insightful ideas, it has been noted to be not free of problems. One is that due to its disavowing the probability calculus, it cannot give the exact strength of an inference. In order to tackle this problem, thereby paving the way to a more complete normative account of argument strength, it has been proposed, the most promising way is to combine the scheme-based approach with Bayesian networks (BNs). This paper pursues this line of thought, attempting to combine three common schemes, Appeal to Ignorance, Composition, and Division, with BNs. In the first part, it is argued that most (if not all) formulations of the critical questions corresponding to these schemes in the current argumentation literature are incomplete and not very informative. To remedy these flaws, more thorough and precise formulations of these questions are provided. In the second part, how to use graphical idioms (e.g. measurement and synthesis idioms) to translate the schemes as well as their corresponding critical questions to graphical structure of BNs, and how to define probability tables of the nodes using functions of various sorts are shown. In the final part, it is argued that many misuses of these schemes, traditionally called fallacies with the same names as the schemes, can indeed be adequately accounted for by the BN models proposed in this paper.

Keywords: appeal to ignorance, argument schemes, Bayesian networks, composition, division

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194 Arthroscopic Superior Capsular Reconstruction Using the Long Head of the Biceps Tendon (LHBT)

Authors: Ho Sy Nam, Tang Ha Nam Anh

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Background: Rotator cuff tears are a common problem in the aging population. The prevalence of massive rotator cuff tears varies in some studies from 10% to 40%. Of irreparable rotator cuff tears (IRCTs), which are mostly associated with massive tear size, 79% are estimated to have recurrent tears after surgical repair. Recent studies have shown that superior capsule reconstruction (SCR) in massive rotator cuff tears can be an efficient technique with optimistic clinical scores and preservation of stable glenohumeral stability. Superior capsule reconstruction techniques most commonly use either fascia lata autograft or dermal allograft, both of which have their own benefits and drawbacks (such as the potential for donor site issues, allergic reactions, and high cost). We propose a simple technique for superior capsule reconstruction that involves using the long head of the biceps tendon as a local autograft; therefore, the comorbidities related to graft harvesting are eliminated. The long head of the biceps tendon proximal portion is relocated to the footprint and secured as the SCR, serving to both stabilize the glenohumeral joint and maintain vascular supply to aid healing. Objective: The purpose of this study is to assess the clinical outcomes of patients with large to massive RCTs treated by SCR using LHBT. Materials and methods: A study was performed of consecutive patients with large to massive RCTs who were treated by SCR using LHBT between January 2022 and December 2022. We use one double-loaded suture anchor to secure the long head of the biceps to the middle of the footprint. Two more anchors are used to repair the rotator cuff using a single-row technique, which is placed anteriorly and posteriorly on the lateral side of the previously transposed LHBT. Results: The 3 men and 5 women had an average age of 61.25 years (range 48 to 76 years) at the time of surgery. The average follow-up was 8.2 months (6 to 10 months) after surgery. The average preoperative ASES was 45.8, and the average postoperative ASES was 85.83. The average postoperative UCLA score was 29.12. VAS score was improved from 5.9 to 1.12. The mean preoperative ROM of forward flexion and external rotation of the shoulder was 720 ± 160 and 280 ± 80, respectively. The mean postoperative ROM of forward flexion and external rotation were 1310 ± 220 and 630 ± 60, respectively. There were no cases of progression of osteoarthritis or rotator cuff muscle atrophy. Conclusion: SCR using LHBT is considered a treatment option for patients with large or massive RC tears. It can restore superior glenohumeral stability and function of the shoulder joint and can be an effective procedure for selected patients, helping to avoid progression to cuff tear arthropathy.

Keywords: superior capsule reconstruction, large or massive rotator cuff tears, the long head of the biceps, stabilize the glenohumeral joint

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193 Resource Sharing Issues of Distributed Systems Influences on Healthcare Sector Concurrent Environment

Authors: Soo Hong Da, Ng Zheng Yao, Burra Venkata Durga Kumar

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The Healthcare sector is a business that consists of providing medical services, manufacturing medical equipment and drugs as well as providing medical insurance to the public. Most of the time, the data stored in the healthcare database is to be related to patient’s information which is required to be accurate when it is accessed by authorized stakeholders. In distributed systems, one important issue is concurrency in the system as it ensures the shared resources to be synchronized and remains consistent through multiple read and write operations by multiple clients. The problems of concurrency in the healthcare sector are who gets the access and how the shared data is synchronized and remains consistent when there are two or more stakeholders attempting to the shared data simultaneously. In this paper, a framework that is beneficial to distributed healthcare sector concurrent environment is proposed. In the proposed framework, four different level nodes of the database, which are national center, regional center, referral center, and local center are explained. Moreover, the frame synchronization is not symmetrical. There are two synchronization techniques, which are complete and partial synchronization operation are explained. Furthermore, when there are multiple clients accessed at the same time, synchronization types are also discussed with cases at different levels and priorities to ensure data is synchronized throughout the processes.

Keywords: resources, healthcare, concurrency, synchronization, stakeholders, database

Procedia PDF Downloads 126
192 Development and Power Characterization of an IoT Network for Agricultural Imaging Applications

Authors: Jacob Wahl, Jane Zhang

Abstract:

This paper describes the development and characterization of a prototype IoT network for use with agricultural imaging and monitoring applications. The sensor and gateway nodes are designed using the ESP32 SoC with integrated Bluetooth Low Energy 4.2 and Wi-Fi. A development board, the Arducam IoTai ESP32, is used for prototyping, testing, and power measurements. Google’s Firebase is used as the cloud storage site for image data collected by the sensor. The sensor node captures images using the OV2640 2MP camera module and transmits the image data to the gateway via Bluetooth Low Energy. The gateway then uploads the collected images to Firebase via a known nearby Wi-Fi network connection. This image data can then be processed and analyzed by computer vision and machine learning pipelines to assess crop growth or other needs. The sensor node achieves a wireless transmission data throughput of 220kbps while consuming 150mA of current; the sensor sleeps at 162µA. The sensor node device lifetime is estimated to be 682 days on a 6600mAh LiPo battery while acquiring five images per day based on the development board power measurements. This network can be utilized by any application that requires high data rates, low power consumption, short-range communication, and large amounts of data to be transmitted at low-frequency intervals.

Keywords: Bluetooth low energy, ESP32, firebase cloud, IoT, smart farming

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191 Overview of Multi-Chip Alternatives for 2.5 and 3D Integrated Circuit Packagings

Authors: Ching-Feng Chen, Ching-Chih Tsai

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With the size of the transistor gradually approaching the physical limit, it challenges the persistence of Moore’s Law due to the development of the high numerical aperture (high-NA) lithography equipment and other issues such as short channel effects. In the context of the ever-increasing technical requirements of portable devices and high-performance computing, relying on the law continuation to enhance the chip density will no longer support the prospects of the electronics industry. Weighing the chip’s power consumption-performance-area-cost-cycle time to market (PPACC) is an updated benchmark to drive the evolution of the advanced wafer nanometer (nm). The advent of two and half- and three-dimensional (2.5 and 3D)- Very-Large-Scale Integration (VLSI) packaging based on Through Silicon Via (TSV) technology has updated the traditional die assembly methods and provided the solution. This overview investigates the up-to-date and cutting-edge packaging technologies for 2.5D and 3D integrated circuits (ICs) based on the updated transistor structure and technology nodes. The author concludes that multi-chip solutions for 2.5D and 3D IC packagings are feasible to prolong Moore’s Law.

Keywords: moore’s law, high numerical aperture, power consumption-performance-area-cost-cycle time to market, 2.5 and 3D- very-large-scale integration, packaging, through silicon via

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190 Robot Operating System-Based SLAM for a Gazebo-Simulated Turtlebot2 in 2d Indoor Environment with Cartographer Algorithm

Authors: Wilayat Ali, Li Sheng, Waleed Ahmed

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The ability of the robot to make simultaneously map of the environment and localize itself with respect to that environment is the most important element of mobile robots. To solve SLAM many algorithms could be utilized to build up the SLAM process and SLAM is a developing area in Robotics research. Robot Operating System (ROS) is one of the frameworks which provide multiple algorithm nodes to work with and provide a transmission layer to robots. Manyof these algorithms extensively in use are Hector SLAM, Gmapping and Cartographer SLAM. This paper describes a ROS-based Simultaneous localization and mapping (SLAM) library Google Cartographer mapping, which is open-source algorithm. The algorithm was applied to create a map using laser and pose data from 2d Lidar that was placed on a mobile robot. The model robot uses the gazebo package and simulated in Rviz. Our research work's primary goal is to obtain mapping through Cartographer SLAM algorithm in a static indoor environment. From our research, it is shown that for indoor environments cartographer is an applicable algorithm to generate 2d maps with LIDAR placed on mobile robot because it uses both odometry and poses estimation. The algorithm has been evaluated and maps are constructed against the SLAM algorithms presented by Turtlebot2 in the static indoor environment.

Keywords: SLAM, ROS, navigation, localization and mapping, gazebo, Rviz, Turtlebot2, slam algorithms, 2d indoor environment, cartographer

Procedia PDF Downloads 114
189 Energy Efficient Clustering with Reliable and Load-Balanced Multipath Routing for Wireless Sensor Networks

Authors: Alamgir Naushad, Ghulam Abbas, Shehzad Ali Shah, Ziaul Haq Abbas

Abstract:

Unlike conventional networks, it is particularly challenging to manage resources efficiently in Wireless Sensor Networks (WSNs) due to their inherent characteristics, such as dynamic network topology and limited bandwidth and battery power. To ensure energy efficiency, this paper presents a routing protocol for WSNs, namely, Enhanced Hybrid Multipath Routing (EHMR), which employs hierarchical clustering and proposes a next hop selection mechanism between nodes according to a maximum residual energy metric together with a minimum hop count. Load-balancing of data traffic over multiple paths is achieved for a better packet delivery ratio and low latency rate. Reliability is ensured in terms of higher data rate and lower end-to-end delay. EHMR also enhances the fast-failure recovery mechanism to recover a failed path. Simulation results demonstrate that EHMR achieves a higher packet delivery ratio, reduced energy consumption per-packet delivery, lower end-to-end latency, and reduced effect of data rate on packet delivery ratio when compared with eminent WSN routing protocols.

Keywords: energy efficiency, load-balancing, hierarchical clustering, multipath routing, wireless sensor networks

Procedia PDF Downloads 51
188 Weighted Data Replication Strategy for Data Grid Considering Economic Approach

Authors: N. Mansouri, A. Asadi

Abstract:

Data Grid is a geographically distributed environment that deals with data intensive application in scientific and enterprise computing. Data replication is a common method used to achieve efficient and fault-tolerant data access in Grids. In this paper, a dynamic data replication strategy, called Enhanced Latest Access Largest Weight (ELALW) is proposed. This strategy is an enhanced version of Latest Access Largest Weight strategy. However, replication should be used wisely because the storage capacity of each Grid site is limited. Thus, it is important to design an effective strategy for the replication replacement task. ELALW replaces replicas based on the number of requests in future, the size of the replica, and the number of copies of the file. It also improves access latency by selecting the best replica when various sites hold replicas. The proposed replica selection selects the best replica location from among the many replicas based on response time that can be determined by considering the data transfer time, the storage access latency, the replica requests that waiting in the storage queue and the distance between nodes. Simulation results utilizing the OptorSim show our replication strategy achieve better performance overall than other strategies in terms of job execution time, effective network usage and storage resource usage.

Keywords: data grid, data replication, simulation, replica selection, replica placement

Procedia PDF Downloads 237
187 Pulsed Laser Single Event Transients in 0.18 μM Partially-Depleted Silicon-On-Insulator Device

Authors: MeiBo, ZhaoXing, LuoLei, YuQingkui, TangMin, HanZhengsheng

Abstract:

The Single Event Transients (SETs) were investigated on 0.18μm PDSOI transistors and 100 series CMOS inverter chain using pulse laser. The effect of different laser energy and device bias for waveform on SET was characterized experimentally, as well as the generation and propagation of SET in inverter chain. In this paper, the effects of struck transistors type and struck locations on SETs were investigated. The results showed that when irradiate NMOSFETs from 100th to 2nd stages, the SET pulse width measured at the output terminal increased from 287.4 ps to 472.9 ps; and when irradiate PMOSFETs from 99th to 1st stages, the SET pulse width increased from 287.4 ps to 472.9 ps. When struck locations were close to the output of the chain, the SET pulse was narrow; however, when struck nodes were close to the input, the SET pulse was broadening. SET pulses were progressively broadened up when propagating along inverter chains. The SET pulse broadening is independent of the type of struck transistors. Through analysis, history effect induced threshold voltage hysteresis in PDSOI is the reason of pulse broadening. The positive pulse observed by oscilloscope, contrary to the expected results, is because of charging and discharging of capacitor.

Keywords: single event transients, pulse laser, partially-depleted silicon-on-insulator, propagation-induced pulse broadening effect

Procedia PDF Downloads 387
186 Comparative Analysis of Classification Methods in Determining Non-Active Student Characteristics in Indonesia Open University

Authors: Dewi Juliah Ratnaningsih, Imas Sukaesih Sitanggang

Abstract:

Classification is one of data mining techniques that aims to discover a model from training data that distinguishes records into the appropriate category or class. Data mining classification methods can be applied in education, for example, to determine the classification of non-active students in Indonesia Open University. This paper presents a comparison of three methods of classification: Naïve Bayes, Bagging, and C.45. The criteria used to evaluate the performance of three methods of classification are stratified cross-validation, confusion matrix, the value of the area under the ROC Curve (AUC), Recall, Precision, and F-measure. The data used for this paper are from the non-active Indonesia Open University students in registration period of 2004.1 to 2012.2. Target analysis requires that non-active students were divided into 3 groups: C1, C2, and C3. Data analyzed are as many as 4173 students. Results of the study show: (1) Bagging method gave a high degree of classification accuracy than Naïve Bayes and C.45, (2) the Bagging classification accuracy rate is 82.99 %, while the Naïve Bayes and C.45 are 80.04 % and 82.74 % respectively, (3) the result of Bagging classification tree method has a large number of nodes, so it is quite difficult in decision making, (4) classification of non-active Indonesia Open University student characteristics uses algorithms C.45, (5) based on the algorithm C.45, there are 5 interesting rules which can describe the characteristics of non-active Indonesia Open University students.

Keywords: comparative analysis, data mining, clasiffication, Bagging, Naïve Bayes, C.45, non-active students, Indonesia Open University

Procedia PDF Downloads 292
185 Redefining Intellectual Humility in Indian Context: An Experimental Investigation

Authors: Jayashree And Gajjam

Abstract:

Intellectual humility (IH) is defined as a virtuous mean between intellectual arrogance and intellectual self-diffidence by the ‘Doxastic Account of IH’ studied, researched and developed by western scholars not earlier than 2015 at the University of Edinburgh. Ancient Indian philosophical texts or the Upanisads written in the Sanskrit language during the later Vedic period (circa 600-300 BCE) have long addressed the virtue of being humble in several stories and narratives. The current research paper questions and revisits these character traits in an Indian context following an experimental method. Based on the subjective reports of more than 400 Indian teenagers and adults, it argues that while a few traits of IH (such as trustworthiness, respectfulness, intelligence, politeness, etc.) are panhuman and pancultural, a few are not. Some attributes of IH (such as proper pride, open-mindedness, awareness of own strength, etc.) may be taken for arrogance by the Indian population, while other qualities of Intellectual Diffidence such as agreeableness, surrendering can be regarded as the characteristic of IH. The paper then gives the reasoning for this discrepancy that can be traced back to the ancient Indian (Upaniṣadic) teachings that are still prevalent in many Indian families and still anchor their views on IH. The name Upanisad itself means ‘sitting down near’ (to the Guru to gain the Supreme knowledge of the Self and the Universe and setting to rest ignorance) which is equivalent to the three traits among the BIG SEVEN characterized as IH by the western scholars viz. ‘being a good listener’, ‘curious to learn’, and ‘respect to other’s opinion’. The story of Satyakama Jabala (Chandogya Upanisad 4.4-8) who seeks the truth for several years even from the bull, the fire, the swan and waterfowl, suggests nothing but the ‘need for cognition’ or ‘desire for knowledge’. Nachiketa (Katha Upanisad), a boy with a pure mind and heart, follows his father’s words and offers himself to Yama (the God of Death) where after waiting for Yama for three days and nights, he seeks the knowledge of the mysteries of life and death. Although the main aim of these Upaniṣadic stories is to give the knowledge of life and death, the Supreme reality which can be identical with traits such as ‘curious to learn’, one cannot deny that they have a lot more to offer than mere information about true knowledge e.g., ‘politeness’, ‘good listener’, ‘awareness of own limitations’, etc. The possible future scope of this research includes (1) finding other socio-cultural factors that affect the ideas on IH such as age, gender, caste, type of education, highest qualification, place of residence and source of income, etc. which may be predominant in current Indian society despite our great teachings of the Upaniṣads, and (2) to devise different measures to impart IH in Indian children, teenagers, and younger adults for the harmonious future. The current experimental research can be considered as the first step towards these goals.

Keywords: ethics and virtue epistemology, Indian philosophy, intellectual humility, upaniṣadic texts in ancient India

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184 DG Allocation to Reduce Production Cost by Reducing Losses in Radial Distribution Systems Using Fuzzy

Authors: G. V. Siva Krishna Rao, B. Srinivasa Rao

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Electrical energy is vital in every aspect of day-to-day life. Keen interest is taken on all possible sources of energy from which it can be generated and this led to the encouragement of generating electrical power using renewable energy resources such as solar, tidal waves and wind energy. Due to the increasing interest on renewable sources in recent times, the studies on integration of distributed generation to the power grid have rapidly increased. Distributed Generation (DG) is a promising solution to many power system problems such as voltage regulation, power loss and reduction in operational cost, etc. To reduce production cost, it is important to minimize the losses by determining the location and size of local generators to be placed in the radial distribution systems. In this paper, reduction of production cost by optimal size of DG unit operated at optimal power factor is dealt. The optimal size of the DG unit is calculated analytically using approximate reasoning suitable nodes and DG placement to minimize production cost with minimum loss is determined by fuzzy technique. Total Cost of Power generation is compared with and without DG unit for 1 year duration. The suggested method is programmed under MATLAB software and is tested on IEEE 33 bus system and the results are presented.

Keywords: distributed generation, operational cost, exact loss formula, optimum size, optimum location

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183 Finite Element Analysis of Steel-Concrete Composite Structures Considering Bond-Slip Effect

Authors: WonHo Lee, Hyo-Gyoung Kwak

Abstract:

A numerical model considering slip behavior of steel-concrete composite structure is introduced. This model is based on a linear bond stress-slip relation along the interface. Single node was considered at the interface of steel and concrete member in finite element analysis, and it improves analytical problems of model that takes double nodes at the interface by adopting spring elements to simulate the partial interaction. The slip behavior is simulated by modifying material properties of steel element contacting concrete according to the derived formulation. Decreased elastic modulus simulates the slip occurrence at the interface and decreased yield strength simulates drop in load capacity of the structure. The model is verified by comparing numerical analysis applying this model with experimental studies. Acknowledgment—This research was supported by a grant(13SCIPA01) from Smart Civil Infrastructure Research Program funded by Ministry of Land, Infrastructure and Transport(MOLIT) of Korea government and Korea Agency for Infrastructure Technology Advancement(KAIA) and financially supported by Korea Ministry of Land, Infrastructure and Transport(MOLIT) as U-City Master and Doctor Course Grant Program.

Keywords: bond-slip, composite structure, partial interaction, steel-concrete structure

Procedia PDF Downloads 159