Search results for: node points
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2885

Search results for: node points

2795 Self-Supervised Attributed Graph Clustering with Dual Contrastive Loss Constraints

Authors: Lijuan Zhou, Mengqi Wu, Changyong Niu

Abstract:

Attributed graph clustering can utilize the graph topology and node attributes to uncover hidden community structures and patterns in complex networks, aiding in the understanding and analysis of complex systems. Utilizing contrastive learning for attributed graph clustering can effectively exploit meaningful implicit relationships between data. However, existing attributed graph clustering methods based on contrastive learning suffer from the following drawbacks: 1) Complex data augmentation increases computational cost, and inappropriate data augmentation may lead to semantic drift. 2) The selection of positive and negative samples neglects the intrinsic cluster structure learned from graph topology and node attributes. Therefore, this paper proposes a method called self-supervised Attributed Graph Clustering with Dual Contrastive Loss constraints (AGC-DCL). Firstly, Siamese Multilayer Perceptron (MLP) encoders are employed to generate two views separately to avoid complex data augmentation. Secondly, the neighborhood contrastive loss is introduced to constrain node representation using local topological structure while effectively embedding attribute information through attribute reconstruction. Additionally, clustering-oriented contrastive loss is applied to fully utilize clustering information in global semantics for discriminative node representations, regarding the cluster centers from two views as negative samples to fully leverage effective clustering information from different views. Comparative clustering results with existing attributed graph clustering algorithms on six datasets demonstrate the superiority of the proposed method.

Keywords: attributed graph clustering, contrastive learning, clustering-oriented, self-supervised learning

Procedia PDF Downloads 53
2794 Quality of Service of Transportation Networks: A Hybrid Measurement of Travel Time and Reliability

Authors: Chin-Chia Jane

Abstract:

In a transportation network, travel time refers to the transmission time from source node to destination node, whereas reliability refers to the probability of a successful connection from source node to destination node. With an increasing emphasis on quality of service (QoS), both performance indexes are significant in the design and analysis of transportation systems. In this work, we extend the well-known flow network model for transportation networks so that travel time and reliability are integrated into the QoS measurement simultaneously. In the extended model, in addition to the general arc capacities, each intermediate node has a time weight which is the travel time for per unit of commodity going through the node. Meanwhile, arcs and nodes are treated as binary random variables that switch between operation and failure with associated probabilities. For pre-specified travel time limitation and demand requirement, the QoS of a transportation network is the probability that source can successfully transport the demand requirement to destination while the total transmission time is under the travel time limitation. This work is pioneering, since existing literatures that evaluate travel time reliability via a single optimization path, the proposed QoS focuses the performance of the whole network system. To compute the QoS of transportation networks, we first transfer the extended network model into an equivalent min-cost max-flow network model. In the transferred network, each arc has a new travel time weight which takes value 0. Each intermediate node is replaced by two nodes u and v, and an arc directed from u to v. The newly generated nodes u and v are perfect nodes. The new direct arc has three weights: travel time, capacity, and operation probability. Then the universal set of state vectors is recursively decomposed into disjoint subsets of reliable, unreliable, and stochastic vectors until no stochastic vector is left. The decomposition is made possible by applying existing efficient min-cost max-flow algorithm. Because the reliable subsets are disjoint, QoS can be obtained directly by summing the probabilities of these reliable subsets. Computational experiments are conducted on a benchmark network which has 11 nodes and 21 arcs. Five travel time limitations and five demand requirements are set to compute the QoS value. To make a comparison, we test the exhaustive complete enumeration method. Computational results reveal the proposed algorithm is much more efficient than the complete enumeration method. In this work, a transportation network is analyzed by an extended flow network model where each arc has a fixed capacity, each intermediate node has a time weight, and both arcs and nodes are independent binary random variables. The quality of service of the transportation network is an integration of customer demands, travel time, and the probability of connection. We present a decomposition algorithm to compute the QoS efficiently. Computational experiments conducted on a prototype network show that the proposed algorithm is superior to existing complete enumeration methods.

Keywords: quality of service, reliability, transportation network, travel time

Procedia PDF Downloads 221
2793 Angular-Coordinate Driven Radial Tree Drawing

Authors: Farshad Ghassemi Toosi, Nikola S. Nikolov

Abstract:

We present a visualization technique for radial drawing of trees consisting of two slightly different algorithms. Both of them make use of node-link diagrams for visual encoding. This visualization creates clear drawings without edge crossing. One of the algorithms is suitable for real-time visualization of large trees, as it requires minimal recalculation of the layout if leaves are inserted or removed from the tree; while the other algorithm makes better utilization of the drawing space. The algorithms are very similar and follow almost the same procedure but with different parameters. Both algorithms assign angular coordinates for all nodes which are then converted into 2D Cartesian coordinates for visualization. We present both algorithms and discuss how they compare to each other.

Keywords: Radial drawing, Visualization, Algorithm, Use of node-link diagrams

Procedia PDF Downloads 338
2792 Development of Modular Shortest Path Navigation System

Authors: Nalinee Sophatsathit

Abstract:

This paper presents a variation of navigation systems which tallies every node along the shortest path from start to destination nodes. The underlying technique rests on the well-established Dijkstra Algorithm. The ultimate goal is to serve as a user navigation guide that furnishes stop over cost of every node along this shortest path, whereby users can decide whether or not to visit any specific nodes. The output is an implementable module that can be further refined to run on the Internet and smartphone technology. This will benefit large organizations having physical installations spreaded over wide area such as hospitals, universities, etc. The savings on service personnel, let alone lost time and unproductive work, are attributive to innovative navigation system management.

Keywords: navigation systems, shortest path, smartphone technology, user navigation guide

Procedia PDF Downloads 338
2791 Graph Neural Network-Based Classification for Disease Prediction in Health Care Heterogeneous Data Structures of Electronic Health Record

Authors: Raghavi C. Janaswamy

Abstract:

In the healthcare sector, heterogenous data elements such as patients, diagnosis, symptoms, conditions, observation text from physician notes, and prescriptions form the essentials of the Electronic Health Record (EHR). The data in the form of clear text and images are stored or processed in a relational format in most systems. However, the intrinsic structure restrictions and complex joins of relational databases limit the widespread utility. In this regard, the design and development of realistic mapping and deep connections as real-time objects offer unparallel advantages. Herein, a graph neural network-based classification of EHR data has been developed. The patient conditions have been predicted as a node classification task using a graph-based open source EHR data, Synthea Database, stored in Tigergraph. The Synthea DB dataset is leveraged due to its closer representation of the real-time data and being voluminous. The graph model is built from the EHR heterogeneous data using python modules, namely, pyTigerGraph to get nodes and edges from the Tigergraph database, PyTorch to tensorize the nodes and edges, PyTorch-Geometric (PyG) to train the Graph Neural Network (GNN) and adopt the self-supervised learning techniques with the AutoEncoders to generate the node embeddings and eventually perform the node classifications using the node embeddings. The model predicts patient conditions ranging from common to rare situations. The outcome is deemed to open up opportunities for data querying toward better predictions and accuracy.

Keywords: electronic health record, graph neural network, heterogeneous data, prediction

Procedia PDF Downloads 86
2790 Emotion Detection in a General Human-Robot Interaction System Optimized for Embedded Platforms

Authors: Julio Vega

Abstract:

Expression recognition is a field of Artificial Intelligence whose main objectives are to recognize basic forms of affective expression that appear on people’s faces and contributing to behavioral studies. In this work, a ROS node has been developed that, based on Deep Learning techniques, is capable of detecting the facial expressions of the people that appear in the image. These algorithms were optimized so that they can be executed in real time on an embedded platform. The experiments were carried out in a PC with a USB camera and in a Raspberry Pi 4 with a PiCamera. The final results shows a plausible system, which is capable to work in real time even in an embedded platform.

Keywords: python, low-cost, raspberry pi, emotion detection, human-robot interaction, ROS node

Procedia PDF Downloads 129
2789 Cellular Components of the Hemal Node of Egyptian Cattle

Authors: Amira E. Derbalah, Doaa M. Zaghloul

Abstract:

10 clinically healthy hemal nodes were collected from male bulls aged 2-3 years. Light microscopy revealed a capsule of connective tissue consisted mainly of collagen fiber surrounding hemal node, numerous erythrocytes were found in wide subcapsular sinus under the capsule. The parenchyma of the hemal node was divided into cortex and medulla. Diffused lymphocytes, and lymphoid follicles, having germinal centers were the main components of the cortex, while in the medulla there was wide medullary sinus, diffused lymphocytes and few lymphoid nodules. The area occupied with lymph nodules was larger than that occupied with non-nodular structure of lymphoid cords and blood sinusoids. Electron microscopy revealed the cellular components of hemal node including elements of circulating erythrocytes intermingled with lymphocytes, plasma cells, mast cells, reticular cells, macrophages, megakaryocytes and endothelial cells lining the blood sinuses. The lymphocytes were somewhat triangular in shape with cytoplasmic processes extending between adjacent erythrocytes. Nuclei were triangular to oval in shape, lightly stained with clear nuclear membrane indentation and clear nucleoli. The reticular cells were elongated in shape with cytoplasmic processes extending between adjacent lymphocytes, rough endoplasmic reticulum, ribosomes and few lysosomes were seen in their cytoplasm. Nucleus was elongated in shape with less condensed chromatin. Plasma cells were oval to irregular in shape with numerous dilated rough endoplasmic reticulum containing electron lucent material occupying the whole cytoplasm and few mitochondria were found. Nuclei were centrally located and oval in shape with heterochromatin emarginated and often clumped near the nuclear membrane. Occasionally megakaryocytes and mast cells were seen among lymphocytes. Megakaryocytes had multilobulated nucleus and free ribosomes often appearing as small aggregates in their cytoplasm, while mast cell had their characteristic electron dense granule in the cytoplasm, few electron lucent granules were found also, we conclude that, the main function of the hemal node of cattle is proliferation of lymphocytes. No role for plasma cell in erythrophagocytosis could be suggested.

Keywords: cattle, electron microscopy, hemal node, histology, immune system

Procedia PDF Downloads 402
2788 Fuzzy Rules Based Improved BEENISH Protocol for Wireless Sensor Networks

Authors: Rishabh Sharma

Abstract:

The main design parameter of WSN (wireless sensor network) is the energy consumption. To compensate this parameter, hierarchical clustering is a technique that assists in extending duration of the networks life by efficiently consuming the energy. This paper focuses on dealing with the WSNs and the FIS (fuzzy interface system) which are deployed to enhance the BEENISH protocol. The node energy, mobility, pause time and density are considered for the selection of CH (cluster head). The simulation outcomes exhibited that the projected system outperforms the traditional system with regard to the energy utilization and number of packets transmitted to sink.

Keywords: wireless sensor network, sink, sensor node, routing protocol, fuzzy rule, fuzzy inference system

Procedia PDF Downloads 104
2787 Lies of Police Interrogators in the Ultimatum Game

Authors: Eitan Elaad

Abstract:

The present study's purpose was to examine lyingand pretend fairness by police interrogators in sharing situations. Forty police officers and 40 laypeople from the community, all males, self-assessed their lie-telling ability, rated the frequency of their lies, evaluated the acceptability of lying, and indicated using rational and intuitive thinking while lying. Next, according to the ultimatum game procedure, participants were asked to share 100 points with a virtual target, either a male police interrogator or a male layman. Participantsallocated points to the target person bearing in mind that the other person must accept their offer. Participants' goal was to retain as many points as possible, and to this end, they could tell the target person that fewer than 100 points were available for distribution. The difference between the available 100 points and the sum of points designated for sharing defines lying. The ratio of offered and designated points defines pretend fairness. Results indicate that those police officers lied more than laypeople. Similar results emergedeven when the target person was a police interrogator. However, police interrogators presented higher pretend fairness than laypeople. The higher pretend fairness may be in line with interrogation tactics of persuasion used in the criminal interrogation. Higher-lying frequency reported by police interrogators compared with laypeople support the present results. Finally, lie acceptability predicted lying in the ultimatum game. Specifically, participants who rated lying as more acceptable tended to lie more than low acceptability raters.

Keywords: lying, police interrogators, lie acceptability, ultimatum game, pretend fairness

Procedia PDF Downloads 153
2786 Digimesh Wireless Sensor Network-Based Real-Time Monitoring of ECG Signal

Authors: Sahraoui Halima, Dahani Ameur, Tigrine Abedelkader

Abstract:

DigiMesh technology represents a pioneering advancement in wireless networking, offering cost-effective and energy-efficient capabilities. Its inherent simplicity and adaptability facilitate the seamless transfer of data between network nodes, extending the range and ensuring robust connectivity through autonomous self-healing mechanisms. In light of these advantages, this study introduces a medical platform harnessed with DigiMesh wireless network technology characterized by low power consumption, immunity to interference, and user-friendly operation. The primary application of this platform is the real-time, long-distance monitoring of Electrocardiogram (ECG) signals, with the added capacity for simultaneous monitoring of ECG signals from multiple patients. The experimental setup comprises key components such as Raspberry Pi, E-Health Sensor Shield, and Xbee DigiMesh modules. The platform is composed of multiple ECG acquisition devices labeled as Sensor Node 1 and Sensor Node 2, with a Raspberry Pi serving as the central hub (Sink Node). Two communication approaches are proposed: Single-hop and multi-hop. In the Single-hop approach, ECG signals are directly transmitted from a sensor node to the sink node through the XBee3 DigiMesh RF Module, establishing peer-to-peer connections. This approach was tested in the first experiment to assess the feasibility of deploying wireless sensor networks (WSN). In the multi-hop approach, two sensor nodes communicate with the server (Sink Node) in a star configuration. This setup was tested in the second experiment. The primary objective of this research is to evaluate the performance of both Single-hop and multi-hop approaches in diverse scenarios, including open areas and obstructed environments. Experimental results indicate the DigiMesh network's effectiveness in Single-hop mode, with reliable communication over distances of approximately 300 meters in open areas. In the multi-hop configuration, the network demonstrated robust performance across approximately three floors, even in the presence of obstacles, without the need for additional router devices. This study offers valuable insights into the capabilities of DigiMesh wireless technology for real-time ECG monitoring in healthcare applications, demonstrating its potential for use in diverse medical scenarios.

Keywords: DigiMesh protocol, ECG signal, real-time monitoring, medical platform

Procedia PDF Downloads 79
2785 GRCNN: Graph Recognition Convolutional Neural Network for Synthesizing Programs from Flow Charts

Authors: Lin Cheng, Zijiang Yang

Abstract:

Program synthesis is the task to automatically generate programs based on user specification. In this paper, we present a framework that synthesizes programs from flow charts that serve as accurate and intuitive specification. In order doing so, we propose a deep neural network called GRCNN that recognizes graph structure from its image. GRCNN is trained end-to-end, which can predict edge and node information of the flow chart simultaneously. Experiments show that the accuracy rate to synthesize a program is 66.4%, and the accuracy rates to recognize edge and node are 94.1% and 67.9%, respectively. On average, it takes about 60 milliseconds to synthesize a program.

Keywords: program synthesis, flow chart, specification, graph recognition, CNN

Procedia PDF Downloads 119
2784 Eliminating Cutter-Path Deviation For Five-Axis Nc Machining

Authors: Alan C. Lin, Tsong Der Lin

Abstract:

This study proposes a deviation control method to add interpolation points to numerical control (NC) codes of five-axis machining in order to achieve the required machining accuracy. Specific research issues include: (1) converting machining data between the CL (cutter location) domain and the NC domain, (2) calculating the deviation between the deviated path and the linear path, (3) finding interpolation points, and (4) determining tool orientations for the interpolation points. System implementation with practical examples will also be included to highlight the applicability of the proposed methodology.

Keywords: CAD/CAM, cutter path, five-axis machining, numerical control

Procedia PDF Downloads 424
2783 Research on Resilience-Oriented Disintegration in System-of-System

Authors: Hang Yang, Jiahao Liu, Jichao Li, Kewei Yang, Minghao Li, Bingfeng Ge

Abstract:

The system-of-systems (SoS) are utilized to characterize networks formed by integrating individual complex systems that demonstrate interdependence and interconnectedness. Research on the disintegration issue in SoS is significant in improving network survivability, maintaining network security, and optimizing SoS architecture. Accordingly, this study proposes an integrated framework called resilience-oriented disintegration in SoS (SoSRD), for modeling and solving the issue of SoS disintegration. Firstly, a SoS disintegration index (SoSDI) is presented to evaluate the disintegration effect of SoS. This index provides a practical description of the disintegration process and is the first integration of the network disintegration model and resilience models. Subsequently, we propose a resilience-oriented disintegration method based on reinforcement learning (RDRL) to enhance the efficiency of SoS disintegration. This method is not restricted by the problem scenario as well as considering the coexistence of disintegration (node/link removal) and recovery (node/link addition) during the process of SoS disintegration. Finally, the effectiveness and superiority of the proposed SoSRD are demonstrated through a case study. We demonstrate that our proposed framework outperforms existing indexes and methods in both node and link disintegration scenarios, providing a fresh perspective on network disintegration. The findings provide crucial insights into dismantling harmful SoS and designing a more resilient SoS.

Keywords: system-of-systems, disintegration index, resilience, reinforcement learning

Procedia PDF Downloads 14
2782 Lies and Pretended Fairness of Police Officers in Sharing

Authors: Eitan Elaad

Abstract:

The current study aimed to examine lying and pretended fairness by police personnel in sharing situations. Forty Israeli police officers and 40 laypeople from the community, all males, self-assessed their lie-telling ability, rated the frequency of their lies, evaluated the acceptability of lying, and indicated using rational and intuitive thinking while lying. Next, according to the ultimatum game procedure, participants were asked to share 100 points with an imagined target, either a male policeman or a male non-policeman. Participants allocated points to the target person bearing in mind that the other person must accept or reject their offer. Participants' goal was to retain as many points as possible, and to this end, they could tell the target person that fewer than 100 points were available for distribution. We defined concealment or lying as the difference between the available 100 points and the sum of points designated for sharing. Results indicated that police officers lied less to their fellow police targets than non-police targets, whereas laypeople lied less to non-police targets than imagined police targets. The ratio between the points offered to the imagined target person and the points endowed by the participant as available for sharing defined pretended fairness.Enhanced pretended fairness indicates higher motivation to display fair sharing even if the fair sharing is fictitious. Police officers presented higher pretended fairness to police targets than laypeople, whereas laypeople set off more fairness to non-police targets than police officers. We discussed the results concerning occupation solidarity and loyalty among police personnel. Specifically, police work involves uncertainty, danger and risk, coercive authority, and the use of force, which isolates the police from the community and dictates strong bonds of solidarity between police personnel. No wonder police officers shared more points (lied less) to fellow police targets than non-police targets. On the other hand, police legitimacy or the belief that the police are acting honestly in the best interest of the citizens constitutes citizens' attitudes toward the police. The relatively low number of points shared for distribution by laypeople to police targets indicates difficulties with the legitimacy of the Israeli police.

Keywords: lying, fairness, police solidarity, police legitimacy, sharing, ultimatum game

Procedia PDF Downloads 114
2781 A Decentralized Application for Secure Data Handling of Wireless Networks Using Ethereum Smart Contracts

Authors: Midhun Xavier

Abstract:

This paper introduces a method to verify multi-agent systems in industrial control systems using blockchain technology. The proposed solution enables to record and verify each process that occurs while generating a customized product using Ethereum-based smart contracts. Node-Red software agents are developed with the help of semantic web technologies, and these software agents interact with IEC 61499 function blocks to execute the processes. The agent associated with each mechatronic component and its controller can communicate with the blockchain to record various events that occur during each process, and the latter smart contract helps to verify these process orders of the customized product.

Keywords: blockchain, Ethereum, node-red, IEC 61499, multi-agent system, MQTT

Procedia PDF Downloads 94
2780 An Internet of Things Based Home Automation Based on Raspberry Pi and Node JS Server

Authors: Ahmed Khattab, Bassem Shetta

Abstract:

Today, there are many branches of technology, one of them is the internet of things. In this paper, it's focused specifically on automating all the home appliances through E-mail using Node JS server, the server side stores, and processes this data. The server side contains user interface and notification system functionalities which is operated by Raspberry Pi. It will present the security requirements for the smart home. In this application, the privilege of home control including special persons to use it, using the hardware appliances through mobiles and tablets is achieved. The proposed application delivers high quality of service, long lifetime, low maintenance, fast deployment, and low power requirements with low cost needed for development.

Keywords: Raspberry Pi, E-mail, home automation, temperature sensor, PIR sensor, actuators, relay

Procedia PDF Downloads 262
2779 Large-Scale Simulations of Turbulence Using Discontinuous Spectral Element Method

Authors: A. Peyvan, D. Li, J. Komperda, F. Mashayek

Abstract:

Turbulence can be observed in a variety fluid motions in nature and industrial applications. Recent investment in high-speed aircraft and propulsion systems has revitalized fundamental research on turbulent flows. In these systems, capturing chaotic fluid structures with different length and time scales is accomplished through the Direct Numerical Simulation (DNS) approach since it accurately simulates flows down to smallest dissipative scales, i.e., Kolmogorov’s scales. The discontinuous spectral element method (DSEM) is a high-order technique that uses spectral functions for approximating the solution. The DSEM code has been developed by our research group over the course of more than two decades. Recently, the code has been improved to run large cases in the order of billions of solution points. Running big simulations requires a considerable amount of RAM. Therefore, the DSEM code must be highly parallelized and able to start on multiple computational nodes on an HPC cluster with distributed memory. However, some pre-processing procedures, such as determining global element information, creating a global face list, and assigning global partitioning and element connection information of the domain for communication, must be done sequentially with a single processing core. A separate code has been written to perform the pre-processing procedures on a local machine. It stores the minimum amount of information that is required for the DSEM code to start in parallel, extracted from the mesh file, into text files (pre-files). It packs integer type information with a Stream Binary format in pre-files that are portable between machines. The files are generated to ensure fast read performance on different file-systems, such as Lustre and General Parallel File System (GPFS). A new subroutine has been added to the DSEM code to read the startup files using parallel MPI I/O, for Lustre, in a way that each MPI rank acquires its information from the file in parallel. In case of GPFS, in each computational node, a single MPI rank reads data from the file, which is specifically generated for the computational node, and send them to other ranks on the node using point to point non-blocking MPI communication. This way, communication takes place locally on each node and signals do not cross the switches of the cluster. The read subroutine has been tested on Argonne National Laboratory’s Mira (GPFS), National Center for Supercomputing Application’s Blue Waters (Lustre), San Diego Supercomputer Center’s Comet (Lustre), and UIC’s Extreme (Lustre). The tests showed that one file per node is suited for GPFS and parallel MPI I/O is the best choice for Lustre file system. The DSEM code relies on heavily optimized linear algebra operation such as matrix-matrix and matrix-vector products for calculation of the solution in every time-step. For this, the code can either make use of its matrix math library, BLAS, Intel MKL, or ATLAS. This fact and the discontinuous nature of the method makes the DSEM code run efficiently in parallel. The results of weak scaling tests performed on Blue Waters showed a scalable and efficient performance of the code in parallel computing.

Keywords: computational fluid dynamics, direct numerical simulation, spectral element, turbulent flow

Procedia PDF Downloads 133
2778 A Firefly Based Optimization Technique for Optimal Planning of Voltage Controlled Distributed Generators

Authors: M. M. Othman, Walid El-Khattam, Y. G. Hegazy, A. Y. Abdelaziz

Abstract:

This paper presents a method for finding the optimal location and capacity of dispatchable DGs connected to the distribution feeders for optimal planning for a specified power loss 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 node in case of reactive power limit violation. The proposed algorithm is implemented in MATLAB and tested on the IEEE 37-nodes feeder. The results that are validated by comparing it with results obtained from other competing methods show the effectiveness, accuracy and speed of the proposed method.

Keywords: distributed generators, firefly technique, optimization, power loss

Procedia PDF Downloads 533
2777 Fusion of MOLA-based DEMs and HiRISE Images for Large-Scale Mars Mapping

Authors: Ahmed F. Elaksher, Islam Omar

Abstract:

In this project, we used MOLA-based DEMs to orthorectify HiRISE optical images. The MOLA data was interpolated using the kriging interpolation technique. Corresponding tie points were then digitized from both datasets. These points were employed in co-registering both datasets using GIS analysis tools. Different transformation models, including the affine and projective transformation models, were used with different sets and distributions of tie points. Additionally, we evaluated the use of the MOLA elevations in co-registering the MOLA and HiRISE datasets. The planimetric RMSEs achieved for each model are reported. Results suggested the use of 3D-2D transformation models.

Keywords: photogrammetry, Mars, MOLA, HiRISE

Procedia PDF Downloads 77
2776 Optimal Sortation Strategy for a Distribution Network in an E-Commerce Supply Chain

Authors: Pankhuri Dagaonkar, Charumani Singh, Poornima Krothapalli, Krishna Karthik

Abstract:

The backbone of any retail e-commerce success story is a unique design of supply chain network, providing the business an unparalleled speed and scalability. Primary goal of the supply chain strategy is to meet customer expectation by offering fastest deliveries while keeping the cost minimal. Meeting this objective at the large market that India provides is the problem statement that we have targeted here. There are many models and optimization techniques focused on network design to identify the ideal facility location and size, optimizing cost and speed. In this paper we are presenting a tactical approach to optimize cost of an existing network for a predefined speed. We have considered both forward and reverse logistics of a retail e-commerce supply chain consisting of multiple fulfillment (warehouse) and delivery centers, which are connected via sortation nodes. The mathematical model presented here determines if the shipment from a node should get sorted directly for the last mile delivery center or it should travel as consolidated package to another node for further sortation (resort). The objective function minimizes the total cost by varying the resort percentages between nodes and provides the optimal resource allocation and number of sorts at each node.

Keywords: distribution strategy, mathematical model, network design, supply chain management

Procedia PDF Downloads 297
2775 Optimal Price Points in Differential Pricing

Authors: Katerina Kormusheva

Abstract:

Pricing plays a pivotal role in the marketing discipline as it directly influences consumer perceptions, purchase decisions, and overall market positioning of a product or service. This paper seeks to expand current knowledge in the area of discriminatory and differential pricing, a main area of marketing research. The methodology includes developing a framework and a model for determining how many price points to implement in differential pricing. We focus on choosing the levels of differentiation, derive a function form of the model framework proposed, and lastly, test it empirically with data from a large-scale marketing pricing experiment of services in telecommunications.

Keywords: marketing, differential pricing, price points, optimization

Procedia PDF Downloads 93
2774 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

Procedia PDF Downloads 138
2773 Approximation of Intersection Curves of Two Parametric Surfaces

Authors: Misbah Irshad, Faiza Sarfraz

Abstract:

The problem of approximating surface to surface intersection is considered to be very important in computer aided geometric design and computer aided manufacturing. Although it is a complex problem to handle, its continuous need in the industry makes it an active topic in research. A technique for approximating intersection curves of two parametric surfaces is proposed, which extracts boundary points and turning points from a sequence of intersection points and interpolate them with the help of rational cubic spline functions. The proposed approach is demonstrated with the help of examples and analyzed by calculating error.

Keywords: approximation, parametric surface, spline function, surface intersection

Procedia PDF Downloads 270
2772 Biocompatible Chitosan Nanoparticles as an Efficient Delivery Vehicle for Mycobacterium Tuberculosis Lipids to Induce Potent Cytokines and Antibody Response through Activation of γδ T-Cells in Mice

Authors: Ishani Das, Avinash Padhi, Sitabja Mukherjee, Santosh Kar, Avinash Sonawane

Abstract:

Activation of cell mediated and humoral immune responses to Mycobacterium tuberculosis (Mtb) are critical for protection. Herein, we show that mice immunized with Mtb lipid bound chitosan nanoparticles(NPs) induce secretion of prominent Th1 and Th2 cytokines in lymph node and spleen cells, and also induced significantly higher levels of IgG, IgG1, IgG2 and IgM in comparison to control mice measured by ELISA. Furthermore, significantly enhanced γδ-T cell activation was observed in lymph node cells isolated from mice immunized with Mtb lipid coated chitosan-NPs as compared to mice immunized with chitosan-NPs alone or Mtb lipid liposomes through flow cytometric analysis. Also, it was observed that in comparison to CD8+ cells, significantly higher CD4+ cells were present in both the lymph node and spleen cells isolated from mice immunized with Mtb lipid coated chitosan NP. In conclusion, this study represents a promising new strategy for efficient delivery of Mtb lipids using chitosan NPs to trigger enhanced cell mediated and antibody response against Mtb lipids.

Keywords: antibody response, chitosan nanoparticles, cytokines, mycobacterium tuberculosis lipids

Procedia PDF Downloads 280
2771 Comparison of Sports Massage and Stretching along the Cold on Pain Intensity in Elite Female Volleyball Players with Trigger Points in Shoulder Girdle Region

Authors: Sahar Mohammadyari Ghareh Bolagh, Behnaz Seyedi Aghdam, Jalal Shamlou

Abstract:

This study was done to compare the effects of sports massage and stretching along the cold on pain intensity in elite female volleyball players with trigger points in shoulder girdle region. This study was conducted on 32 female volleyball players with latent trigger points in shoulder girdle region. Patients were randomly assigned to three groups: sports massage (n=11) stretching along the cold (n=11) and control group (n=10). One session treatment program during 15 minutes was performed. Pain intensity with VAS + algometer was assessed before and after intervention and improved in both of massage and cold groups. After treatment there were no significant difference between two treatment groups (P < 0. 050). Results of present research showed sports massage and stretching along the cold were effective on pain intensity of myofascial trigger points.

Keywords: sports massage، stretching along the cold، pain intensity، trigger points, elite, volleyball players, shoulder girdle region

Procedia PDF Downloads 370
2770 A Comparison of Design and Off-Design Performances of a Centrifugal Compressor

Authors: Zeynep Aytaç, Nuri Yücel

Abstract:

Today, as the need for high efficiency and fuel-efficient engines have increased, centrifugal compressor designs are expected to be high-efficient and have high-pressure ratios than ever. The present study represents a design methodology of centrifugal compressor placed in a mini jet engine for the design and off-design points with the utilization of computational fluid dynamics (CFD) and compares the performance characteristics at the mentioned two points. Although the compressor is expected to provide the required specifications at the design point, it is known that it is important for the design to deliver the required parameters at the off-design point also as it will not operate at the design point always. It was observed that the obtained mass flow rate, pressure ratio, and efficiency values are within the limits of the design specifications for the design and off-design points. Despite having different design inputs for the mentioned two points, they reveal similar flow characteristics in the general frame.

Keywords: centrifugal compressor, computational fluid dynamics, design point, off-design point

Procedia PDF Downloads 144
2769 Optimized Cluster Head Selection Algorithm Based on LEACH Protocol for Wireless Sensor Networks

Authors: Wided Abidi, Tahar Ezzedine

Abstract:

Low-Energy Adaptive Clustering Hierarchy (LEACH) has been considered as one of the effective hierarchical routing algorithms that optimize energy and prolong the lifetime of network. Since the selection of Cluster Head (CH) in LEACH is carried out randomly, in this paper, we propose an approach of electing CH based on LEACH protocol. In other words, we present a formula for calculating the threshold responsible for CH election. In fact, we adopt three principle criteria: the remaining energy of node, the number of neighbors within cluster range and the distance between node and CH. Simulation results show that our proposed approach beats LEACH protocol in regards of prolonging the lifetime of network and saving residual energy.

Keywords: wireless sensors networks, LEACH protocol, cluster head election, energy efficiency

Procedia PDF Downloads 329
2768 Exploring the Connectedness of Ad Hoc Mesh Networks in Rural Areas

Authors: Ibrahim Obeidat

Abstract:

Reaching a fully-connected network of mobile nodes in rural areas got a great attention between network researchers. This attention rose due to the complexity and high costs while setting up the needed infrastructures for these networks, in addition to the low transmission range these nodes has. Terranet technology, as an example, employs ad-hoc mesh network where each node has a transmission range not exceed one kilometer, this means that every two nodes are able to communicate with each other if they are just one kilometer far from each other, otherwise a third-party will play the role of the “relay”. In Terranet, and as an idea to reduce network setup cost, every node in the network will be considered as a router that is responsible of forwarding data between other nodes which result in a decentralized collaborative environment. Most researches on Terranet presents the idea of how to encourage mobile nodes to become more cooperative by letting their devices in “ON” state as long as possible while accepting to play the role of relay (router). This research presents the issue of finding the percentage of nodes in ad-hoc mesh network within rural areas that should play the role of relay at every time slot, relating to what is the actual area coverage of nodes in order to have the network reach the fully-connectivity. Far from our knowledge, till now there is no current researches discussed this issue. The research is done by making an implementation that depends on building adjacency matrix as an indicator to the connectivity between network members. This matrix is continually updated until each value in it refers to the number of hubs that should be followed to reach from one node to another. After repeating the algorithm on different area sizes, different coverage percentages for each size, and different relay percentages for several times, results extracted shows that for area coverage less than 5% we need to have 40% of the nodes to be relays, where 10% percentage is enough for areas with node coverage greater than 5%.

Keywords: ad-hoc mesh networks, network connectivity, mobile ad-hoc networks, Terranet, adjacency matrix, simulator, wireless sensor networks, peer to peer networks, vehicular Ad hoc networks, relay

Procedia PDF Downloads 282
2767 X-Corner Detection for Camera Calibration Using Saddle Points

Authors: Abdulrahman S. Alturki, John S. Loomis

Abstract:

This paper discusses a corner detection algorithm for camera calibration. Calibration is a necessary step in many computer vision and image processing applications. Robust corner detection for an image of a checkerboard is required to determine intrinsic and extrinsic parameters. In this paper, an algorithm for fully automatic and robust X-corner detection is presented. Checkerboard corner points are automatically found in each image without user interaction or any prior information regarding the number of rows or columns. The approach represents each X-corner with a quadratic fitting function. Using the fact that the X-corners are saddle points, the coefficients in the fitting function are used to identify each corner location. The automation of this process greatly simplifies calibration. Our method is robust against noise and different camera orientations. Experimental analysis shows the accuracy of our method using actual images acquired at different camera locations and orientations.

Keywords: camera calibration, corner detector, edge detector, saddle points

Procedia PDF Downloads 406
2766 Structural Invertibility and Optimal Sensor Node Placement for Error and Input Reconstruction in Dynamic Systems

Authors: Maik Kschischo, Dominik Kahl, Philipp Wendland, Andreas Weber

Abstract:

Understanding and modelling of real-world complex dynamic systems in biology, engineering and other fields is often made difficult by incomplete knowledge about the interactions between systems states and by unknown disturbances to the system. In fact, most real-world dynamic networks are open systems receiving unknown inputs from their environment. To understand a system and to estimate the state dynamics, these inputs need to be reconstructed from output measurements. Reconstructing the input of a dynamic system from its measured outputs is an ill-posed problem if only a limited number of states is directly measurable. A first requirement for solving this problem is the invertibility of the input-output map. In our work, we exploit the fact that invertibility of a dynamic system is a structural property, which depends only on the network topology. Therefore, it is possible to check for invertibility using a structural invertibility algorithm which counts the number of node disjoint paths linking inputs and outputs. The algorithm is efficient enough, even for large networks up to a million nodes. To understand structural features influencing the invertibility of a complex dynamic network, we analyze synthetic and real networks using the structural invertibility algorithm. We find that invertibility largely depends on the degree distribution and that dense random networks are easier to invert than sparse inhomogeneous networks. We show that real networks are often very difficult to invert unless the sensor nodes are carefully chosen. To overcome this problem, we present a sensor node placement algorithm to achieve invertibility with a minimum set of measured states. This greedy algorithm is very fast and also guaranteed to find an optimal sensor node-set if it exists. Our results provide a practical approach to experimental design for open, dynamic systems. Since invertibility is a necessary condition for unknown input observers and data assimilation filters to work, it can be used as a preprocessing step to check, whether these input reconstruction algorithms can be successful. If not, we can suggest additional measurements providing sufficient information for input reconstruction. Invertibility is also important for systems design and model building. Dynamic models are always incomplete, and synthetic systems act in an environment, where they receive inputs or even attack signals from their exterior. Being able to monitor these inputs is an important design requirement, which can be achieved by our algorithms for invertibility analysis and sensor node placement.

Keywords: data-driven dynamic systems, inversion of dynamic systems, observability, experimental design, sensor node placement

Procedia PDF Downloads 150