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Ubiquitous Computing Communication

Ubiquitous Computing Communication

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Ubiquitous Computing Communication refers to the study and design of systems that enable seamless interaction and data exchange among interconnected devices in everyday environments. It emphasizes the integration of computing technology into daily life, allowing for continuous connectivity and communication without the need for explicit user intervention.
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Ubiquitous Computing Communication refers to the study and design of systems that enable seamless interaction and data exchange among interconnected devices in everyday environments. It emphasizes the integration of computing technology into daily life, allowing for continuous connectivity and communication without the need for explicit user intervention.

Key research themes

1. How can infrastructure architectures enhance seamless automatic configuration and context-awareness in ubiquitous computing?

This research area focuses on designing and implementing software infrastructures and middleware systems that support automatic configuration, dynamic adaptation, and context-aware interactions in ubiquitous computing environments. These infrastructures aim to reduce user overhead in managing heterogeneous and mobile devices, enable smooth task migration across locations, and provide high utility by learning user intents and environmental context. This is critical because ubiquitous computing ecosystems are characterized by dynamic resource availability, diverse device capabilities, and the need for minimizing user intervention while maximizing system utility.

The Aura software architecture : an infrastructure for ubiquitous computing
by David Garlan

2023

Key finding: The Aura infrastructure autonomously handles task migration and environment reconfiguration as users move between locations in a ubiquitous computing environment. It exploits lightweight user task and context models to... Read more
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System Support for Rapid Ubiquitous Computing Application Development and Evaluation
by Roy Campbell

2022, System Support for …

Key finding: This work documents the iterative design and deployment of a system infrastructure that manages physically bounded ubiquitous computing environments, supporting multi-device integration, application migration, and coordinated... Read more
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A Peer-to-Peer Based Infrastructure for Context Distribution in Mobile and Ubiquitous Environments
by George A . Papadopoulos

2024, Lecture Notes in Computer Science

Key finding: This paper proposes a decentralized peer-to-peer architecture for scalable and robust context information distribution among heterogeneous devices in mobile and ubiquitous environments. By categorizing sensor nodes,... Read more
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Systems directions for pervasive computing
by Ben Hendrickson

2024, Proceedings Eighth Workshop on Hot Topics in Operating Systems

Key finding: The paper critiques existing distributed computing technologies as insufficient for pervasive computing due to the tight encapsulation of data and functionality, lack of continuous resource acquisition, and the absence of a... Read more
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A personal agent supporting ubiquitous interaction
by Sebastiano Pizzutilo

2023, dagli Oggetti agli Agenti

Key finding: The D-Me multiagent system introduces personal agents that leverage context-awareness for proactive task execution and information presentation in ubiquitous environments. The agent models user activities, intents, and... Read more
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2. What role does context-awareness and multimodal interaction play in enabling human-centric ubiquitous communication?

This theme explores how context-aware systems and intimate, seamless human-computer interactions can be designed to better integrate computing into everyday life. Research in this space examines context capturing, interpretation, and dynamic adaptation to user location, activity, and preferences. Studies investigate how multimodal input/output (such as wearable computing, visual markers, speech, and augmented reality) and intimate computing paradigms can be leveraged to support emotional, social, and cognitive aspects of human communication within ubiquitous environments. This focus is crucial as it addresses usability, acceptability, and the enhancement of natural communication in ubicomp.

UBIQUITOUS COMPUTING: DEFINING AN HCI RESEARCH AGENDA FOR AN EMERGING INTERACTION PARADIGM
by PRASANNAJIT DASH

2022, IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308

Key finding: This paper introduces a taxonomy for ubicomp applications based on user mobility and interaction transparency, defining the scope of HCI challenges in ubiquitous computing. It reveals that increasing interaction... Read more
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Intimate ubiquitous computing
by Tim Brooke

2021

Key finding: Through a workshop and theoretical discourse, this work critically examines the notion of intimacy within ubiquitous computing, conceptualizing intimacy beyond sexual connotations as cognitive, emotional, and physical... Read more
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A Ubiquitous Computing Environment Composed by Cooperation between Visual Markers and Event-Driven Compact Devices
by Tsutomu Terada

2021

Key finding: The paper presents an approach integrating dynamic visual markers (VCC markers) with event-driven ubiquitous chips that collect sensor data and control actuators to provide context-aware information in wearable augmented... Read more
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Augment-able reality: situated communication through physical and digital spaces
by Jun Rekimoto

2024, Digest of Papers. Second International Symposium on Wearable Computers (Cat. No.98EX215)

Key finding: This work extends augmented reality systems by enabling bidirectional dynamic attachment of digital notes (voice, pictures) to physical locations or objects using wearable computers. Contextual tags such as location and... Read more
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Instant Messaging as a Platform for the Realisation of a true Ubiquitous Computing Environment
by Sven van der Meer

2015

Key finding: This paper demonstrates an instant messaging (IM) based platform (IMPRUVE) to support human-centric ubiquitous communication, leveraging pervasive wireless standards and commercial IM technology. It uses IM bots and services... Read more
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3. How can computational methods like signal processing and security mechanisms support the development of robust, context-aware and mobile ubiquitous systems?

This theme deals with the application of specific computational techniques such as multiwavelet transforms for multilingual information retrieval and the use of advanced public key cryptography tailored for resource-constrained mobile devices and payment systems. It also includes investigations into efficient cryptanalysis methods of RSA schemes in the context of mobile security. These computational underpinnings are critical enablers for robust, private, and efficient information exchange and intelligent data retrieval in ubiquitous computing settings where devices are heterogeneous, contexts are dynamic, and security and efficiency are paramount.

A novel multilingual web information retrieval method using multiwavelet transform
by shawki al-dubaee

2024, Ubiquitous Computing

Key finding: The paper presents a novel information retrieval approach that applies multiwavelet transforms for feature extraction across multiple languages while addressing language-specific script, word order, and font challenges.... Read more
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Public Key Cryptography for Mobile Payment
by Sattar Aboud

2021, Ubiquitous Computing and Communication Journal

Key finding: The study analyzes elliptic curve public key encryption as an efficient alternative to traditional RSA encryption for mobile payment security, highlighting its lower key size, faster computation, and reduced power... Read more
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Efficient Method for Breaking RSA Scheme
by Sattar Aboud

2021, Ubiquitous Computing and Communication Journal

Key finding: The paper proposes a novel algorithm that can efficiently attack RSA encryption by recovering the private key and factoring the modulus from the public key, especially effective when the public exponent e is small, a common... Read more
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Related Topics

  • 3D User Interfaces
  • Marshall McLuhan: Understanding Media. The Extensions of Man
  • Natural User Interfaces
  • Gesture Recognition
  • Tangible User Interfaces
  • Interactive and Digital Media
  • Human Computer Interaction
  • Artificial Intelligence
  • Computer Science
  • Education

    • All papers in Ubiquitous Computing Communication

    Evaluating Process Capability Indices of a Manufacturing Process 107 2 Process Capability Indices
    by Kayode Adekeye

    2025

    The effectiveness of a manufacturing product produced depends on whether the specified standards by the management / production engineers are met or not. It is possible that a process will be stable but will not meet the specification set... more
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    A novel multilingual web information retrieval method using multiwavelet transform
    by shawki al-dubaee

    2024, Ubiquitous Computing

    This paper presents a novel approach based on multiwavelet transform in Web information retrieval. The influence multiwavelet transform on feature extraction and information retrieval ability of calibration model and solve problem of... more
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    The Normal Probability Plot as a Tool for Understanding Data: A Shape Analysis from the Perspective of Skewness, Kurtosis, and Variability
    by Gregory Boylan

    2024, Quality and Reliability Engineering International

    Continuous quality improvement is an effort to improve the quality of products, processes, or services. A program intended to effectively implement such efforts begins with the collection and analysis of data. The primary purpose of the... more
    Figure 1. Portrayal of (a) positive and (b) negative skewness Although the estimators for sample skewness and kurtosis are biased and therefore tend to underestimate the true values for the population, the consideration of these moments is necessary, as no probability distribution could technically be described as Gaussian normal unless both equal 0. Figure 2(a) depicts several examples of distributions exhibiting varying degrees of kurtosis where J, N, and U denote Johnson, nor- mal, and uniform distributions, respectively. It is important to note that, in each case, the distributions with positive or negative kur- tosis cross the normal curve twice on each side of the mean, which is a common trait of distributions with excess kurtosis. For distributions with excess positive kurtosis, such as the Johnson (0,1,0,10), this results in a pattern of higher-lower-higher probabilities on each side relative to each crossing point. For example, consider the J(0,1,0,10) relative to the N(0,1) in Figure 2(a). For values near the mean, the probabilities are higher for the J(0,1,0,10) distribution. Moving left or right from the mean, the densities cross and the relationship shifts to lower probabilities for the J(0,1,0,10) and then shifts back to higher probabilities, moving further to the left or right. For distributions with negative excess kurtosis, such as the uniform, the pattern becomes lower-higher-lower. This is a very important distinction, as when they cross only once, this is indicative of changes in variability vice kurtosis. The example of the normal distributions with different variances in Figure 2(b) depicts this.
    Figure 2. Graphical representations of (a) distributions possessing varying degrees of excess kurtosis relative to a N(0,1) and (b) three normal distributions with differen’ variances and zero excess kurtosis
    Figure 3. Normal probability plot for the base case of data sampled from a SN(5, 2, 0) The plots in Figure 6 impart several interesting observations. As expected, the positive skew incorporated in the base case in Figure 6(a) evinces the characteristic concavity previously described in Section 3.2.1, along with a shortening and thinning of the left tail coupled with a corresponding elongation of the right tail. Beyond this, the plots clearly show that changes in variability have a much
    Figure 4. Normal probability plots showing the effect of varying degrees of positive skewness
    Figure 5. Normal probability plots showing the effect of varying degrees of negative skewness Figures 6(b), (c), and (d) depict plots in which we sequentially reduce the variance from 2 to 0.5, 0.4, and finally to 0.125. In contrast to the examples with increasing variability, here we observe that the distribution shortens in both tails as the bulk of the values push in toward the mean of 5. We also note that the variance reduction begins to offset the skewness, inducing a degree of symmetry
    Figure 6. Normal probability plots showing the impact of decreasing and increasing variability
    describe kurtosis presented in Section 2.2 is scaled with respect to the variance and therefore is not affected by it. That is, kurtosis serves to describe the shape of a distribution irrespective of the variance. Despite this, the plots portray a clear relationship. Thus, the deeper implication appears to be that the kurtosis existed from the start but was masked by the variability.
    Figure 8. Normal probability plots showing the effects of decreased and increased levels of excess kurtosis
    demonstration of these effects, showing both the narrowing of the peak in the distribution coupled with a nearly twofold increase in its height. The sample statistics for Figures 12(c) and (d) certainly show the effects on excess kurtosis, but they also show a clear impact on the asymmetry, as the negative skewness increases by a factor of 3 in each case. This is further evidenced by the continued albeit slight leftward shift in the mean.
    Figure 10. Effects of changing variability on negative excess kurtosis
    Figure 11. Overlays of the density plots from Figures 10(b) and (c), revealing (a) increased peakedness and(b) heaviness in the tails typically indicate the presence of either positive or negative asymmetry or skewness, respectively. Moreover, the nature of the tails provides a hint of how variability affects the data. That is, whereas the nature of the curve can impart knowledge as to skewness about the mean, the nature of the tails can impart knowledge about the degree of variability present in the data. The plots in Figures 6(c), (e), and (g) serve as a good example of this, showing a clear elongation of the right tail in the face of increasing variability. However, the nature of the concave or convex curve may also reveal the presence of kurtosis in the data, suggesting a combined effect of dis- tribution characteristics at work within the data. The probability plot in Figure 11(e) provides a stark example of this, depicting the convex curve illustrative of negative asymmetry about the mean, but also a significant degree of positive excess kurtosis suggested by the dense, near-vertical curve in the immediate proximity of the mean.
    Figure 12. Normal probability and density plots portraying the effects of decreasing variability in the presence of non-zero skewness and kurtosi:
    about the mean. Obviously, as the variance approaches 0, we would expect to observe a straight line, perpendicular to the x axis, situ- ated at the mean. The plots are clearly trending this way, as shown by Figure 6(f). Despite the evolving symmetry, reducing the var- iance exacerbates the departure from normality, as demonstrated by the density plot in Figure 7, which is associated with the probability plot in Figure 6(f).
    Table IV. Simulation results showing the effects of decreasing variability on kurtosis
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    A power transformation for non-normal processes capability estimation
    by Goran Turk

    2023, Research Square (Research Square)

    Process capability estimation depends on the underlying data distribution. If data is not normally distributed, other techniques for capability estimation should be taken into consideration. In this paper, we propose modified power... more
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    Supplementary document for Large-scale, cell-resolution volumetric analysis allows layer-specific investigation of human brain cytoarchitecture - 5159214.pdf
    by Mattia Neri

    2023

    Fig. S1. Picture of various samples before (PBS) and after (TDE) the clearing protocol. Acronym: HME (Hemimegalencephaly), FCD (Focal cortical dysplasia). SWITCH/TDE sample clearing. To demonstrate the widespread applicability of the SWITCH/TDE protocol different samples were cleared. Supplementary figure S1 shows 4 autoptic pieces from healthy subjects and 5 blocks from diseased patients of various ages, kept in formalin for different amounts of time before and after the clearing procedure.
    Fig. S2. Representative two-photon images of tissue stained with anti-NeuN antibody (in red) and DAPI (in green) at different temperatures and incubation times. Scale bar = 50 um. Background (S/B) analysis was performed with Fiji (http://fiji.sc/Fiji) to assess the best contrast: mean intensity of 10 square of 25px were analyzed for each condition, media and standard deviation were then calculated using OriginPro 9.0 (OriginLab Corporation). The protocol with the highest signal amplification corresponds to 4°C of incubation temperature and 24 hours of incubation time of the primary antibody.
    Fig. S3. First row: a representative middle plane (~ 200 um) of the mesoscopic reconstruction of the four analyzed human brain specimens obtained with TPFM. Scale bar = 1mm. Bottom rows: magnified insets of each specimen showing the native resolution of the acquisition. Images were selected from the top, middle plane and bottom of the stacks indicated with a white box in the first row. Scale bar = 50 tm.
    The three methods struggle to generalize with respect to brightness and contrast variability, yielding to generally poor segmentation results in challenging imaging conditions like the ones that characterize the initial part of our dataset (Fig. S4, 40 um). Subpar detection performance is observed even in the other parts of the dataset, with many medium and low- intensity objects being completely lost in segmentation (Fig. S4, 200 and 400 ym).
    Fig. S5. The CNN architecture. Block scheme of the architecture of the CNN with 3 convolutional layers and 3 Fully Connected layers.
    Fig. S6. (a) Neuronal segmentation workflow of the 2.5D approach. (b) A representative image undergoing the CNN analysis. From the native image to cells contour segmentation. Scale bar = 100 pm
    Fig. S7. 3D representation of the neurons of a stack manually annotated by the operator (in blue), automatically identified by the 2.5D approach (in red), and the superposition of the two. 2.5D statistical assessment. The statistical assessment of the 2.5D performance wa: determined by analyzing four representative stacks of 100 x 100 x 100 um’, one for eack specimen and a representative stack of 100 x 100 x 450 um’ to determine the accuracy along the full depth. Each stack was independently manually annotated by an operator anc automatically segmented by the 2.5D approach. The manual segmentation has_ beer performed on LAIRA® (https://laira.bioretics.com) and stored in the Ximage open-source format (https://github.com/bioretics/ximage). LAIRA® is available free of charge in tria mode. Supplementary Figure S7 shows the comparison between the manual annotations anc the automatic reconstruction for one of these sub-volumes.
    Fig. S8. The figure shows the 10 selected lines used for the analysis for specimens 1, 2, and 3 drown on top of the maps of figure 5d. Depth accuracy quantification. To describe the variability of the 2.5D along with depth, we plotted the z-profiles across the cortex along 10 different lines that were drawn orthogonally to the cortical layers in specimens 1, 2, and 3 using Fiji. To avoid the distribution artifacts introduced by the imaging (e.g alteration of the surface and the bottom of the sample due to the fact that the tissue is not completely flat), for each sample we selected the middle planes (6 depth=200um) that present intact surfaces. Supplementary Figures S8 shows for each specimen the 10 selected lines. Then, we calculated and plotted the mean value and the one standard deviation of each profile along Z (Supplementary Figures S9, S10, $11). The stability of the profile along with the cortical depth and the stack depth proves that the 2.5D evaluation is stable between different samples, in various regions of the cortex, and along with the stack depth.
    Fig. S9. Plots of cortical depth profiles (i.e. along Z) are shown together with the mean value and the one standard deviation for each of the 10 lines of specimen 1 showed in Fig $7.
    Fig. S10. Plots of cortical depth profiles (i.e. along Z) are shown together with the mean value and the one standard deviation for each of the 10 lines of specimen 2 showed in Fig S7
    Fig. S11. Plots of cortical depth profiles (i.e. along Z) are shown together with the mean value and the one standard deviation for each of the 10 lines of specimen 3 showed in Fig S7
    Fig. S12. Layer masks (L1 red, L2 white, L3 blue, L4 green, L5 light blue, L6 yellow) of the middle plane of samples 1,2, and 3. Grey matter mask (in grey) is shown for sample 4. Manual segmentation of the grey matter. In order to identify the different layers of the grey matter of the cortex, we manually segmented the cell and mean volume distribution maps using the software Fiji (Supplementary figure S12). Big blood vessels, tissue holes/breakages, and imaging artifacts were not reckoned drawing the masks. Sample 4 shows a disruption of the structural organization of the cortex, making layer classification impossible, only grey matter were segmented. The total volume for each mask was obtained performing this operation for all the z-plane of the sample.
    The network parameters are as follows: Optimizer hyper-parameters are as follows:
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    Smart Environments as Agents Workspaces
    by Andrea Omicini

    2023, Ubiquitous Computing and Communication Journal, Special Issue-CPE

    The pervasive computing scenario provides a diffused presence of technological appliances distributed in the environment and interacting by means of wired or wireless networks. These computational units should be able to fruitfully... more
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    Analysis of Wireless Sensor Networks Deployments Using Vertical Variance Trimming and the Analytic Hierarchy Process
    by Carlos Andres Avellaneda Otero

    2023, International Journal of Ad hoc, Sensor & Ubiquitous Computing

    Due to reliance on stochastic deployment, delivery of large-scale WSN presents a major problem in the application of Wireless Sensor Networks (WSN) technology. When deployed in a stochastic manner, the WSN has the utmost challenge of... more
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    Enhancement of Data Aggregation Grid based Coverage Ratio using Overlap Sensing Ratio with Awgn Channel in Heterogeneous WSNs
    by ELISHA GEORGE

    2023, International Journal of Computer Applications

    Heterogeneous wireless sensor network (H-WSN) consists of sensor nodes with different ability, such as different computing power and sensing range. In this Research paper, the improved-enhance coverage overlapping sensing ratio (I-ECOSR)... more
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    On the expected parts per million nonconforming levels obtained from estimated process capability indices
    by Banu Ozkaya

    2023, Quality Engineering

    Process capability indices (PCIs) and parts per million (PPM) nonconforming (NC) levels are widely used in quality improvement programs for quantifying the capability of a process to meet specification requirements. Calculation of PCIs... more
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    Deployment Techniques in Wireless Sensor Networks, Coverage and Connectivity: A Survey
    by Mostafa Elhosseini

    2023, IEEE Access

    Wireless sensor networks (WSNs) have gained wide attention from researchers in the last few years because it has a vital role in countless applications. The main function of WSN is to process extracted data and to transmit it to remote... more
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    A Novel Multilingual Web Information Retrieval Method Using Multiwavelet Transform
    by Saif Rakib

    2023, Ubiquitous Computing and Communication ( …

    This paper presents a novel approach based on multiwavelet transform in Web information retrieval. The influence multiwavelet transform on feature extraction and information retrieval ability of calibration model and solve problem of... more
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    Adaptive Video Streaming Through Server Driven Rate Control In Manets
    by vijay babu

    2023, International Journal Of Engineering And Computer Science

    The IEEE 802.11standard is developed and gained unprecedented popularity for its simple and cost-effective wireless technology to provide best effort services. But, it has to address serious challenges concerned to multimedia services.... more
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    Deployment Techniques in Wireless Sensor Networks, Coverage and Connectivity: A Survey
    by Mostafa Elhosseini

    2023, IEEE Access

    Wireless sensor networks (WSNs) have gained wide attention from researchers in the last few years because it has a vital role in countless applications. The main function of WSN is to process extracted data and to transmit it to remote... more
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    Deployment Techniques in Wireless Sensor Networks, Coverage and Connectivity: A Survey
    by Hesham Arafat Ali

    2023, IEEE Access

    Wireless sensor networks (WSNs) have gained wide attention from researchers in the last few years because it has a vital role in countless applications. The main function of WSN is to process extracted data and to transmit it to remote... more
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    Windows Implementation of PgRouting to find Shortest Path using Dijkstra's Algorithm for Varanasi Road Network
    by Kumari Pritee

    2023

    Many route mapping were done with the help of API of Google maps but does not provide geospatial Routing functionality like overlay, interpolation etc. This project aims to find the shortest path between two or more points by using... more
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    Mobility Aware Routing in VANET
    by Mehul Kapadiya

    2023

    VANET, Vehicular Ad-hoc Network is very emerging area of research. There are lots of applications like; Message Transmission, for example – Infotainment (Information + Entertainment), Emergency Safety Messages, convenience messages,... more
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    New Variable Step-Size NLMS Algorithm for Adaptive Noise Cancellation
    by Khaled Shehata

    2022, International Journal of Sciences: Basic and Applied Research

    Numerous Variable Step-Size Normalized Least Mean Square (VSS-NLMS) algorithms have been proposed to solve the problems of fast convergence rate and low value of steady-state misadjustment in the past three decades. In this paper we... more
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    Delay efficient Layer by Layer Angle Based Flooding Protocol (L2-ABF) for Underwater Wireless Sensor Networks
    by Dr. Tariq Ali

    2022

    The advancement of acoustic modem technology in providing better data rates and more reliable underwater wireless communications has motivated many researchers to create various algorithms to support such technology in a better way. These... more
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    Deployment Techniques in Wireless Sensor Networks, Coverage and Connectivity: A Survey
    by Bharat Gupta

    2022, IEEE Access

    Wireless sensor networks (WSNs) have gained wide attention from researchers in the last few years because it has a vital role in countless applications. The main function of WSN is to process extracted data and to transmit it to remote... more
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    Conversation Monitoring via Low-cost Speaker Diarization using Wearable Wireless Sensors
    by ChaiYong Lim

    2022, Journal of Emerging Technologies in Web Intelligence

    This paper presents speaker diarization mechanisms using low-cost and low-resolution wearable wireless sensors. Speaker diarization is used for identifying speaking sequence and duration for all individuals engaged in a conversation... more
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    Delay efficient Layer by Layer Angle Based Flooding Protocol (L2-ABF) for Underwater Wireless Sensor Networks
    by Ibrahima Faye

    2022

    The advancement of acoustic modem technology in providing better data rates and more reliable underwater wireless communications has motivated many researchers to create various algorithms to support such technology in a better way. These... more
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    Multivariate nonnormal process capability analysis
    by Shafiq Ahmad

    2022, The International Journal of Advanced Manufacturing Technology

    There is a great deal of interest in the manufacturing industry for quantitative measures of process performance with multiple quality characteristics. Unfortunately, multivariate process capability indices that are currently employed,... more
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    Measuring Process Capability for Bivariate Non-Normal Process Using the Bivariate Burr Distribution
    by Shafiq Ahmad

    2022

    As is well known, process capability analysis for more than one quality variables is a complicated and sometimes contentious area with several quality measures vying for recognition. When these variables exhibit non-normal... more
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    Enhancing Route lifetime in Vehicular Ad Hoc ‎Networks Based on Skellam Distribution Model
    by Mohammed A L I Tawfeeq

    2022, International Journal of Communication Networks and Information Security (IJCNIS)

    The emergence of smart cities and the need to use intelligent transportation systems has led to an increased reliance on vehicle ad hoc networks (VANET). The topology of VANET is highly dynamic, which results in a short effective routing... more
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    Programming Distributed Multi-Agent Systems in simpAL
    by Alessandro Ricci

    2022

    Abstract—Distribution is one of the essential features characterizing multi-agent systems (MASs), giving developers the opportunity to seamlessly conceive and then engineer a physically distributed application as a MAS spread among... more
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    Smart Environments as Agents Workspaces
    by Alessandro Ricci

    2022, Ubiquitous Computing and Communication Journal, Special Issue-CPE

    The pervasive computing scenario provides a diffused presence of technological appliances distributed in the environment and interacting by means of wired or wireless networks. These computational units should be able to fruitfully... more
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    A Pilot Study of Anabolic Steroids in Elderly Patients With Hip Fractures
    by Peter Wing

    2022, Journal of the American Geriatrics Society

    The characteristics of nodes moving arbitrarily and the network topology changing frequently lead to AODV routing protocol, which uses minimum hop-count as the metric for route selection, facing intermittent connectivity frequently which... more
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    Non-normal Capability Indices for the Weibull and Lognormal Distributions
    by Piña Monarrez

    2022

    Because the normal process capability indices (PCIs) C p , C pu , C pl , and C pk represent the times that the process standard deviation is within the specification limits; then, based on and by using the direct relations among the... more
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    Modification of Clements’ Method for Assessing the Capability of a Non-Normal Process with an Application
    by Giray genç

    2022, Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering

    In many industries process capability studies are conducted in order to determine the capability of the process to produce acceptable products and it is one of the important activities of statistical process control. In order to express... more
    Figure 1. (a) Histogram of pocket bottom flatness data (b) Normal probability plot of pocket bottom flatness data Initially the histogram and normal probability plot for the flatness data are obtained and given in Figure 1.
    Tablel. MSE of the estimator of Cpu for Weibull distribution with different shape parameters when different pairs of skewness and kurtosis estimators are used in the estimation of Cpu by Clements’ method. According to Table 1, for small values of skewness and kurtosis, using traditional estimators (sk -Kr,) in the estimation of Cpu results in larger MSE as compared to the use of other estimators of skewness and kurtosis. Especially, using sk3 or Sk, in combination with Kr, in the estimation of Cy, by Clements’ method might be preferred by the practitioners since their corresponding MSE is considerably less than the MSE of Gon which is obtained by traditional estimators.
    Aytacgoglu and Geng / Eskisehir Tech. Univ. J. of Sci. and Technology A — Appl. Sci. and Eng. 20 (4) — 2015 When we examine Table 2, for small values of skewness and kurtosis, generally using sk4 and kr, pair in the estimation of Cpu by Clement’s method results in smaller MSE as compared to the use of other estimators of skewness and kurtosis. As skewness and kurtosis of the data get larger MSE values become very large, especially when sk,-kr, , sk,-kr3, and sk,-kr, pairs are used in the estimation of Cpu. Therefore, if the data has large skewness and kurtosis, instead of these pairs, traditional estimators of
    Table 5. Calculated values of L,, U, and M for pocket bottom flatness data. Aytagoglu and Geng / Eskigehir Tech. Univ. J. of Sci. and Technology A — Appl. Sci. and Eng. 20 (4) — 2015
    In Table 6, Cpu is estimated by using all possible estimators of skewness and kurtosis given in this study. When the histogram and the estimates of skewness and kurtosis of pocket bottom flatness data are examined, we see that the skewness of the flatness data is not so large and the kurtosis estimates fluctuate around 0. In the previous section, simulation results showed us that if the skewness and kurtosis are not so large, instead of using traditional estimators of them it is better to use Ska» ks, or Sky = kr, pair in the estimation of Cpu. Therefore, Cpu values that are estimated by using these pairs are given in bold in Table 6. Assessing the process capability with the C,. values estimated by the use of the traditional estimators (sk,-kr,) may mislead the practitioner about the capability of the process. C,u for the flatness data which is estimated by the traditional estimators of skewness and kurtosis is smaller than the Cpu estimated by using sk3 - kr) or Sk4 - kr, pair, and smaller Cy is the indication of less capable process. In that case a practitioner may take an action although it is not actually needed. Table 6. Estimated C,,, values for pocket bottom flatness data.
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    AD HOC WIRELESS INTERNET
    by Prof. Dr.J.R. Arun kumar

    2022

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    Evaluating Process Capability Indices of a Manufacturing Process 107 2 Process Capability Indices
    by Kayode Adekeye

    2022

    The effectiveness of a manufacturing product produced depends on whether the specified standards by the management / production engineers are met or not. It is possible that a process will be stable but will not meet the specification set... more
    The process capability indices for the weigh conditions that were used in this study as ref of Cofta tablet are very close under the two ected in Table 1. This may be due to the fact that the distribution of the data is not far from normal distribution. However, the parts per million defects for the non-normal based indi based indices. The results for the thickness s capable and not well centered since the C, and indices show appreciable gain in the par The confidence interval for the C, and C,, w ces show an appreciable gain over the normal hows that the process for the thickness is not C,, are not equal. Also the non-normal based s per million defects. ere also determined for the purpose of future management of the weight and thickness of and Cpk for the thickness are not capa he tablet process. However, the obtained Cp ble of producing according to the specifications. Hence. the confidence intervals obtained based on the computed values can not be used for
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    Link Quality and MAC-Overhead aware Predictive Preemptive Routing Protocol for Mobile Ad hoc Network
    by Kamel Mohamed Faraoun

    2022, ArXiv

    In Ad Hoc networks, route failure may occur due to less received power, mobility, congestion and node failures. Many approaches have been proposed in literature to solve this problem, where a node predicts pre-emptively the route failure... more
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    Modelling of Non-Normal Neonatal Weight Data to Estimate Mortality Rate of Newborn Babies
    by Mali Abdollahian

    2022

    Neonatal Mortality Rate (NMR) can be defined as the number of newborn deaths’ aged 0 to 28 days. The most significant factor influenced NMR is low birth weight of newborn babies approximately 48%, followed by asphyxia 37% and sepsis... more
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    Reliable Routing in Vehicular Ad Hoc Networks
    by Nathalie Mitton

    2021, Distributed Computing Systems …

    One of the notoriously difficult problems in vehicular ad-hoc networks (VANET) is to ensure that established routing paths do not break before the end of data transmission. This is a difficult problem because the network topology is... more
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    An efficient routing protocol for connecting vehicular networks to the Internet
    by Ritesh Patel

    2021, Pervasive and Mobile Computing

    Vehicular ad hoc networks (VANETs) enable vehicles to communicate with each other (V2V) as well as with roadside infrastructure units (V2I). These units provide different services such as driver information systems and Internet access.... more
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    A Load Aware Routing Protocol for Mobile Ad hoc Networks
    by Hesham Elmahdy

    2021

    The Ad hoc On-Demand Distance Vector (AODV) routing protocol is an efficient Mobile Ad hoc NETworks (MANETs) routing protocol. It uses hop count as a metric for the path selection. AODV does not support Quality of Service (QoS) and... more
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    Deployment Scheme in Wireless Sensor Network: A Review
    by Devendra Prasad

    2021, International Journal of Computer Applications

    Nowadays Wireless sensor networks (WSNs) being applied in many different civilian applications like vehicle tracking, habitat monitoring, forest surveillance, earthquake observation, biomedical or health care requests and building... more
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    Providing Reliability and QoS in Multi-Hop Wireless Networks: The ADHOCSYS Approach
    by Nikos Fragoulis

    2021, Proceedings of the 3rd International ICST Conference on Mobile Multimedia Communications

    Multi-hop wireless networks appear as a promising means for providing broadband Internet access in rural and mountain regions. Reliability and QoS are among others two important aspects in such context. This paper presents a pragmatic... more
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    Delay efficient Layer by Layer Angle Based Flooding Protocol (L2-ABF) for Underwater Wireless Sensor Networks
    by Dr. Tariq Ali

    2021

    The advancement of acoustic modem technology in providing better data rates and more reliable underwater wireless communications has motivated many researchers to create various algorithms to support such technology in a better way. These... more
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    A New Multivariate Process Capability Index Under Both Unilateral and Bilateral Quality Characteristics
    by Amirhossein Amiri

    2021, Quality and Reliability Engineering International

    Process capability indices (PCIs) are used in statistical process control to evaluate the capability of the processes in satisfying the customer's needs. In the past two decades varieties of PCI are introduced by researchers to analyze... more
    One of the problems with the NMPCV is that it is too sensitive to the angle between the large axis of the process region ellipsoic and the horizontal axis. This angle completely depends on the variance-covariance structure. As an example, for two processes with equa variation and different correlation between quality characteristics, NMC,,,, may compute two values with large difference (see Figures 2¢ and 2b). As shown in Figures 2a and 2b, two processes with equal variation but different correlation between quality characteristic:
    Figure 1. Example of the modified tolerance region (extracted from Shahriari and Abdollahzadeh"*)
    Figure 2. (a and b) Two processes with the same variation but different correlations between quality characteristics where PV is the P value of hypothesis test Ho: = flo against Hy : 4 jlo, which is computed by using Hotelling T* test statistic and
    Figure 3. Two process with different variations, which are completely within the modified tolerance region
    Figure 4. Situation of the PR and the modified tolerance region respect to each other In the mentioned situations, the first component of the proposed index accounts for the process variation and the second com- ponent is the inverse of distance between the process mean and the target. Using this component, we can distinguish between two processes with equal first component but different distance between target and process mean.
    Figure 7. (a) A bivariate quality characteristic with bilateral specification limits. (b) A bivariate quality characteristic with both unilateral and bilateral specification limit: Figure 6. Unilateral quality characteristic without values greater than the process mean
    Figure 5. A unilateral quality characteristic (with LSL)
    2.2.2. Proposed index “onsider the PR shown in Figure 8 by color black. The PR can be located anywhere, even out of the tolerance region. However, it is lesired that the PR lies in the modified tolerance region. To develop the PCI, we computed the CV and the NCV regions of modified tolerance and PR and considered as variation measures. By using computed regions value (see Appendix A), the proposed index is computed as follows: where 4 is a constant value and will be discussed in Section 2.3. The first component of the proposed index does not distinguis between processes A and B, as shown in Figure 9. However, the second component, which we call location part, can identify the mor capable process. It is obvious that process B is more capable because Y> is the smaller and better quality characteristic. The location part can be computed by Equation (15)as follows:
    Figure 9. Effect of location part on the proposed index
    where D;; and Diz are the D;- and D>-type distance for the ith quality characteristic, respectively. 2.3. Discussion about the process capability sensitivity parameter (A)
    Equation (14) can be easily rewritten as a general equation for multivariate case,
    Figure 11. Tolerance region, which is not within the modified tolerance region (bilateral case)
    Figure 12. (a) Capable process when the PR is equal to the modified tolerance region. (b) Capable process with a correlation between quality characteristic In this section, similar to Pearn et al.7*, a confidence interval for the first component of the proposed index is developed, assuming the sensitivity parameter of the proposed PCI (A) is equal to zero. In Section 2.3, we discussed the sensitivity parameter and recommended the value of 0.27 for this parameter. However, as explained in the Section 2.3, when the correlation between quality characteristics
    Figure 13. Tolerance region, which is not within the modified tolerance region (unilateral case)
    where Fy(z =f fy(y)dy; thus, a 100(1 — «)% confidence interval for the first component of MPCycy can be obtained as increases, it is desired to use the smaller value of the sensitivity parameter. Hence, assuming A=0, the first component of the proposed index is ee. Note that PR volume follows a chi-square distribution with v degrees of freedom. Hence, a 100(1 — «)% confidence interval for the first component of MPCycy can be established as follows:
    Figure 15. Values of NMPCV and MPCycy for the first example Figure 14. Graphical representation of the six processes for the first example
    4. Numerical examples for unilateral situation In this section, we investigate the performance of the proposed index in the unilateral cases through two examples which are real cases. 4.1. Example 4
    Figure 18. (a) Relationship between the tolerance region and the modified tolerance region for example 4. (b-c) PR and the modified tolerance region for processes o example 4 tae a, Dee The results of the index in Table V considering Figures , 18a-18c show the effectiveness of the proposed index in measuring the ‘apability of the processes. Note that because two processes are completely in the modified tolerance region, the first component of oroposed index only consider the variation of processes and distance from target is measured with the second component. To com- ute the proposed index, 2 =0.27/4 = 0.0675 is used because two quality characteristics are unilateral, and there is one corner in the nodified tolerance region.
    4.2. Example 5
    Figure A1. Tolerance and PRs for a unilateral process To compute CV and NCV regions for the proposed index, we used integral. Consider a unilateral process, which is depicted in Figure Al. Firct. we divided CV reaion in two narts from nrocess mean of Y. (Figure A171).
    Table I. The characteristics of processes for example 1
    3.2. Example 2
    A biological reduction of the ethyl 4-chloro acetoacetate process for the production of optically pure compound is applied to demon- strate the effectiveness of the proposed index.*”° S-4-chloro-3-hydroxybutyric acid ethyl ester (or S-CHBE) can be used to synthesize various optically active compounds such as antihypertensive drugs and antibiotics. The compound can be produced by adding ethyl 4-chloro acetoacetate to baker's yeast. The reaction produces S-CHBE with a small amount of enzymes in the yeast cell.
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    On Call Admission Control in W-Cdma Networks Supporting Handoff Traffic
    by Michael D. Logothetis

    2021

    In this paper, we evaluate a Call Admission Control (CAC) scheme suitable for W-CDMA networks accommodating multiple service-classes. In such networks, the distinction between new and handoff traffic is very important. A simple CAC scheme... more
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    On Call Admission Control in W-Cdma Networks Supporting Handoff Traffic
    by Michael D. Logothetis

    2021, ubicc.org

    In this paper, we evaluate a Call Admission Control (CAC) scheme suitable for W-CDMA networks accommodating multiple service-classes. In such networks, the distinction between new and handoff traffic is very important. A simple CAC scheme... more
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    Process capability estimation for non-normal quality charactersitics using Clement, Burr and Box--Cox methods
    by Dr. Shafiq Ahmad

    2021, ANZIAM Journal

    In today's competitive business environment, it is becoming more crucial than ever to assess precisely process losses due to non-compliance to customer specifications. To assess these losses, industry is widely using process capability... more
    FIGURE 1: Box plot of estimated C,,, values with target Cp, = 0.5, 1.0,1. and 2.0 for Weibull distribution.
    FIGURE 2: Box plot of estimated Cy, values with target Cy, = 0.5, 1.0, 1. and 2.0 for Gamma distribution.
    FIGURE 4: Histogram of data from a semiconductor industry.
    FIGURE 5: Histogram of measurement data from a computer manufacturing process.
    TABLE 1: PCI calculations using Burr Percentile Method.
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    Broadcast Control-Based Routing Protocol for Internet Access in VANETS
    by Jawad Drissi

    2021, 2011 7th International Wireless Communications and Mobile Computing Conference

    In the last few years, extensive research has been performed to extend Internet connectivity to VANETS. Indeed, several routing protocols have been proposed to determine routes between vehicles and gateways (e.g., Road Side Units: RSUs).... more
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    Adding gateway mode for R-AODV routing protocol in hybrid ad hoc network
    by Fitri Winda Sari

    2021, TENCON 2011-2011 …

    In mobile ad hoc networks (MANET), routing protocol plays the most important role. For more than one decade, Ad hoc On-demand Distance Vector (AODV) routing protocol becomes attention and research focus on MANET widely. A lot of protocols... more
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    Adding gateway mode for R-AODV routing protocol in hybrid ad hoc network
    by Fitri Winda Sari

    2021, TENCON 2011-2011 …

    In mobile ad hoc networks (MANET), routing protocol plays the most important role. For more than one decade, Ad hoc On-demand Distance Vector (AODV) routing protocol becomes attention and research focus on MANET widely. A lot of protocols... more
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    Mitigation of Channel Diversity and Indoor Channel Modeling for Remote Patient Monitoring Systems
    by Amit Sehgal (SET Professor)

    2021

    The continuously increasing demand for better healthcare services has added another application to the sphere of remote monitoring services. This extension to e-Health and Telecare services is known as Remote Patient Monitoring (RPM). The... more
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    A Multi-Layer Cooperation Framework for QoS-Aware Internet Access in Vanets
    by Antonella Molinaro

    2021, Ubiquitous Computing and Communication Journal

    A VANET is composed of vehicles, equipped with short range wireless communication capabilities, which cooperate to form a temporary distributed network enabling communications with other vehicles or road infrastructure nodes, located in... more
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    A Load Aware Routing Protocol for Mobile Ad hoc Networks
    by Hesham Elmahdy

    2021

    Ad hoc On-Demand Distance Vector (AODV) routing protocol is an efficient Mobile Ad hoc NETworks (MANETs) routing protocol. It uses hop count as a metric for the path selection. AODV does not support Quality of Service (QoS) and neither... more
    descriptionView Paperarrow_downwardDownload
    A Load Aware Routing Protocol for Mobile Ad hoc Networks
    by Hesham Elmahdy

    2021

    The Ad hoc On-Demand Distance Vector (AODV) routing protocol is an efficient Mobile Ad hoc NETworks (MANETs) routing protocol. It uses hop count as a metric for the path selection. AODV does not support Quality of Service (QoS) and... more
    descriptionView Paperarrow_downwardDownload
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