Communication Steps Research Articles

Asynchronous Byzantine reliable broadcast with a message adversary

This paper considers the problem of reliable broadcast in asynchronous authenticated systems, in which n processes communicate using signed messages and up to t processes may behave arbitrarily (Byzantine processes). In addition, for each message m broadcast by a correct (i.e., non-Byzantine) process, a message adversary may prevent up to d correct processes from receiving m. (This message adversary captures network failures such as transient disconnections, silent churn, or message losses.) Considering such a “double” adversarial context and assuming n>3t+2d, a reliable broadcast algorithm is presented. Interestingly, when there is no message adversary (i.e., d=0), the algorithm terminates in two communication steps (so, in this case, this algorithm is optimal in terms of both Byzantine tolerance and time efficiency). It is then shown that the condition n>3t+2d is necessary for implementing reliable broadcast in the presence of both Byzantine processes and a message adversary (whether the underlying system is enriched with signatures or not).

Mathematical modeling for further improving task scheduling on Big Data systems

In the big data era which we have entered, the development of smart scheduler has become a necessity. A Distributed Stream Processing System (DSPS) has the role of assigning processing tasks to the available resources (dynamically or not) and route streaming data between them. Smart and efficient task scheduling can reduce latencies and eliminate network congestions. The most commonly used scheduler is the default Storm scheduler, which has proven to have certain disadvantages, like the inability to handle system changes in a dynamic environment. In such cases, rescheduling is necessary. This paper is an extension of a previous work on dynamic task scheduling. In such a scenario, some type of rescheduling is necessary to have the system working in the most efficient way. In this paper, we extend our previous works Souravlas and Anastasiadou (Appl Sci 10(14):4796, 2020); Souravlas et al. (Appl Sci 11(1):61, 2021) and present a mathematical model that offers better balance and produces fewer communication steps. The scheduler is based on the idea of generating larger sets of communication steps among the system nodes, which we call superclasses. Our experiments have shown that this scheme achieves better balancing and reduces the overall latency.

Abstract P3165: Spectrin-based Regulation Of Exosome Secretion In Cardiac Fibroblasts

Cardiac fibroblasts (CFs) not only modulate the extracellular matrix under physiological conditions, but also have the ability to sense local injury and respond with a phenotypic change and increased paracrine communication to distal cells. While a myriad of studies have focused on identifying the paracrine signals involved in recruitment and activation of CFs, the manner by which CF paracrine communication networks are tuned in response to chronic stress remains unclear. Previously, our lab found that stress-induced loss of the cytoskeletal protein, β IV -spectrin, regulates the CF phenotype and fibrosis. Therefore, we hypothesized that degradation of β IV -spectrin is a critical step in stress-induced communication involved in recruitment of distal CFs. In this study, we first collected conditioned media from WT and β IV -spectrin deficient (qv 4J ) CFs to test the effects on quiescent WT CFs. We found that the CFs treated with qv 4J -conditioned media showed increased proliferation and compaction rates, as well as altered gene expression in the recipient cells compared to those treated with WT-conditioned media. To further explore the role of β IV -spectrin in paracrine signaling, we isolated exosomes from WT- and qv 4J -conditioned media. We found that loss of β IV -spectrin in CFs resulted in an increased concentration of exosomes in conditioned media, that also induced increased proliferation in quiescent CFs. Furthermore, we found that genetic mice expressing degradation-resistant β IV -spectrin ( qv 3J mice) showed impaired CF recruitment and activation following myocardial infarction (MI) together with increased mortality and impaired fibrotic remodeling compared to WT. Finally, we demonstrate that exosomes from a WT-MI heart can improve fibrotic remodeling in qv 3J mice following MI. Our work identifies a novel role of the spectrin-based pathway in facilitating long-range communication in response to chronic stress.

PERCEPTION OF HUMAN EXPRESSION, AGE AND GENDER RELATED VARIATIONS OF EMOTIONRECOGNITION BASED ON LIVE CAMERA IMAGES IN DEEP LEARNING USING PYTHON

Now-a-days online marketing is rapidly increasing. As a growth, we capture the customer images through web camera. Depending on their age, gender and expression of mood easily continue our product marketing in online. Automated face detection methods are substantial for facial identification, head position analysis, and human-computer communication. Face detection is a method for detecting and analyzing a human face in a webcam image. Identifying gender and oldness has now established itself as a key step in numerous human-machine communications. It can be used in advertising, security, and all other areas where gender and age recognition help them better to do the task given to them. Gender, oldness and mood of user forecast is the initial tool for any system which utilize it to scale their performance through personalized communication with the user of certain age and gender and mood of customers to improve our business online itself with high preference.

Shifting the narrative from living at risk to living with risk: validating and pilot-testing a clinical decision support tool: a mixed methods study

BackgroundWhen there are safety concerns, healthcare professionals (HCPs) may disregard older adults’ wishes to return or remain at home. A paradigm shift is needed for HCPs to move from labelling older adults as living at risk to helping them live with risk. The Living with Risk: Decision Support Tool (LwR:DST) was developed to support older adults and HCPs with difficult decision-making regarding living with risk. The study objectives were to: (1) validate, and (2) pilot-test the LwR:DST in hospital and community settings.MethodsThe study was conducted across Canada during the pandemic. The LwR:DST’s content was validated with quantitative and qualitative data by: (1) 71 HCPs from hospital and community settings using the Delphi method, and (2) 17 older adults and caregivers using focus groups. HCPs provided feedback on the LwR:DST’s content, format and instruction manual while older adults provided feedback on the LwR:DST’s communication step. The revised LwR:DST was pilot-tested by 14 HCPs in one hospital and one community setting, and 17 older adults and caregivers described their experience of HCPs using this approach with them. Descriptive and thematic analysis were performed.ResultsThe LwR:DST underwent two iterations incorporating qualitative and quantitative data provided by HCPs, older adults and caregivers. The quantitative Delphi method data validated the content and the process of the LwR:DST, while the qualitative data provided practical improvements. The pilot-testing results suggest that using the LwR:DST broadens HCPs’ clinical thinking, structures their decision-making, improves their communication and increases their competence and comfort with risk assessment and management. Our findings also suggest that the LwR:DST improves older adults’ healthcare experience by feeling heard, understood and involved.ConclusionsThis revised LwR:DST should help HCPs systematically identify frail older adults’ risks when they remain at or return home and find acceptable ways to mitigate these risks. The LwR:DST induces a paradigm shift by acknowledging that risks are inherent in everyday living and that risk-taking has positive and negative consequences. The challenges involved in integrating the LwR:DST into practice, i.e., when, how and with whom to use it, will be addressed in future research.

Solving 3-SAT in distributed P systems with string objects

In this study, string rewriting P systems with communication by request is used in solving the satisfiability problem, or SAT. The family of solutions using this class of rewriting P system is shown to be uniform, in terms of the number of clauses and variables of the input boolean formula. This rewriting P system is then used as components for the construction of a distributed P system solving SAT. It is shown in this work that encoding the truth assignment for the communication steps only require a polynomial number of rules to implement, but requires an exponential-sized set of inter-component communication rules to achieve a low communication cost.

Komunikasi Positif Dalam Pengasuhan Anak Usia Dini

The purpose of this study is to recommend readers to change their parenting communication style from traditional communication style to positive communication. Qualitative research methods with a library study approach. Data collection techniques with documentation. Data reduction processing techniques, presentation and conclusion. The results of the study show: positive communication steps in early childhood care are obtained: (1) leaving traditional communication styles: by changing the message of communication to children. (2) use the message "I" to convey thoughts and feelings: serves to convey facts (3) reads children's body language: understands children's movements (4) becomes an active listener: respects children's opinions and words. (5). Change negative language to positive language: to change a child's bad habits.

A novel method for studying intercellular networks: quantifying cellular cooperativity and inferring the extracellular signals driving it

Abstract Objective: Develop an integrated experimental-computational approach to determine the functional role played by different cell subsets and extracellular communication signals in shaping the behavior of intercellular networks. Methods: We present a microwell-based experimental system, that allows isolating and culturing small groups (up to a few dozens) of cells over extended periods of time, while monitoring their interactions and states using fluorescence microscopy. In parallel, we present a computational framework that uses the data generated by this system for estimating the degree of intercellular cooperativity associated with observed behaviors of the interacting cells, and for inferring the contribution of measured extracellular signals in shaping these behaviors. Results: We used our approach to study the differentiation of mouse Th17 cells. We show that this process requires a relatively large number (> 10) of intermediate intercellular communication steps, in which information processing is carried out by a relatively small percentage (10–20%) of the interacting cells. We correctly predict a correlation between the time in which communication signals are expressed during differentiation, and the degree of intercellular cooperativity associated with their production. Furthermore, we show that we can accurately predict cell-level behaviors. In addition, we correctly identify previously-known effects of cytokines on cell survival, and further predict novel relations, which we validate experimentally. Conclusions: We present a new and general approach for the study of collective cellular behaviors, identifying the key cell subsets and extracellular communication signals driving them. This work was supported in part by National Human Genome Research Institute Centers of Excellence in Genomics Science P50 HG006193 (N.H.), by National Institutes of Health Grants P01 AI045757 and DP3 DK09768101 (J.C.L.) and by the U. S. Army Research Office through the Institute for Soldier Nanotechnologies, under contract number W911NF-13-D-0001 (J.C.L.). This work was also supported in part by the Koch Institute Support (core) Grant P30-CA14051 from the National Cancer Institute. J.C.L. is a Camille Dreyfus Teacher-Scholar.

Development and Evaluation of a Child Neurology Resident Curriculum for Communication Around Serious Illness

Background: Communication around serious illness is a core competency for all residencies. One-fifth of neurology residencies have no curriculum. Published curricula use didactics or role-play to assess confidence performing this skill without evaluation in clinical settings. The SPIKES mnemonic (Setting, Perception, Invitation, Knowledge, Empathy, Strategy/Summary) outlines 6 evidence-based steps for communication around serious illness. It is unknown whether child neurology residents can incorporate SPIKES into communication around serious illness in clinical settings. Objective: To develop and evaluate a curriculum on communication around serious illness using SPIKES for child neurology residents that shows long-term skill retention in clinical settings at a single institution. Methods: In 2019, we created a pre-post survey and skills checklist based on SPIKES, with 20 total including 10 core skills. Faculty observed residents' (n = 7) communication with families and completed both preintervention and postintervention checklists for comparison. Residents underwent training in SPIKES during a 2-hour session using didactic and coached role-play. Results: All (n = 7) residents completed preintervention surveys, 4 of 6 completed postintervention. All (n = 6) participated in the training session. Following the training, 75% of residents reported improved confidence in use of SPIKES, though 50% were still unsure about appropriately responding to emotions. There was improvement in all SPIKES skills, with significant improvement in 6 of 20 skills up to 1 year following training. Conclusion: This is the first evaluation of the implementation of a communication around serious illness curriculum for child neurology residents. We identified improved comfort with SPIKES after training. Successful acquisition and utilization of this framework in our program suggests it could be incorporated into any residency program.

DNA Reaction Network Mimicking the Basic Steps of Synaptic Communication

Comprehensive SummaryBiological systems use intricate networks of chemical reactions to exchange information. How to simulate complex systems with simple strand‐displacement reactions is crucial to broaden the application scenario of the DNA reaction network. Here, we report the artificial DNA reaction network to mimic the operation and function of biological information transfer via strand‐displacement reaction. DNA is used as simple artificial analogs to schematize structures and transmit information. Using chemical synapses in neural networks as an example, we show that the proposed network enables core functions of biological systems, such as the long‐term potential of synapses, which underpin learning and memory. Also, we performed the simple “silicon mimetic” to link electronic circuits to chemical network‐based biological structures. As such, synaptic communication simulated by the DNA reaction network provides a complete demonstration for designing artificial reaction networks based on the essence of information interaction.

Communication and Raising Citizen's Consciousness of Climate Change Challenges and Adaptation in Nigeria

The global impact of climate change remains a grave concern to every nation, from severe droughts in East Africa to wildfires in Australia and extreme floods and landslides in India, Nepal and Bangladesh, and, recently, the devastating floods witnessed in Nigeria, climate change challenges continue to escalate. Climate change is driving people out of their homes and ushering in a world of poverty. Extant literature avers that at the centre of mitigating the adverse effects of climate change and stimulating the desired action is communication. Consequently, this paper seeks to interrogate the centrality of communication as a tool in the hands of policymakers, the media and international donor agencies in stimulating public consciousness in Nigeria towards climate change challenges and adaptation. Leveraging a quantitative and exploratory approach and using surveys with structured and unstructured questionnaire questions, the study exposed gaps in citizens' knowledge of the causes of climate change and revealed the level of awareness of climate change challenges, people's attitudes to climate change, sources of information, and desired medium of communication among the Nigerian public. The study highlights the interplay between the contents of climate change communication and actionable steps that are easy to be understood and relatively simple to be followed by the citizens. Finally, the paper contends that much more needs to be done in sensitising citizens on climate change while suggesting a combination of alternative communication strategies that promise to stimulate citizens' awareness of climate change challenges and adaptation in Nigeria.

Defect Analysis of a Non-Iterative Co-Simulation

This article presents an analysis of co-simulation defects for a system of coupled ordinary differential equations. The research builds on the theorem that the co-simulation error is bounded if the co-simulation defect is bounded. The co-simulation defect can be divided into integration, output, and connection defects, all of which can be controlled. This article proves that the output and connection defect can be controlled by the co-simulation master by varying the communication step size. A non-iterative co-simulation method with variable communication step size is presented to demonstrate the applicability of the presented research. The orders of the interpolation polynomials used in the co-simulation method are varied in the experimental analysis. The experimental analysis shows how each component of a co-simulation defect affects the co-simulation error. The analysis presented is used to verify the applicability of the proposed approach and to provide guidelines for the configuration of the co-simulation.

Parents' experience of the communication process of positivity at newborn screening for metabolic diseases: A qualitative study.

The process of receiving a communication of positivity for metabolic diseases at expanded newborn screening (ENBS) is extremely articulated, involves a variety of actors (parents, maternal and child departments, clinical centres and laboratories) and is open to a variety of outcomes from false positive to true positive cases. Receiving communication of positivity can be highly stressful for parents and requires an adequate communication process to give clear and reliable information without causing excessive worry. This qualitative study describes the parents' experience of receiving a communication of positivity to metabolic diseases at ENBS, and their assessment of the quality of the communication process and steps, with the main aim to identify the process' strengths and weaknesses and to advance tailored recommendations to improve the communication process. Fourteen in-depth, semi-structured phone interviews were conducted with parents whose children resulted positive to the ENBS. As part of the ENBS communication process, parents received a first phone call communication of positivity and a second in-person communication at metabolic clinical centres (MCC). The framework analysis method was used to organize the data and identify emerging themes. Parents were largely dissatisfied with the quality and depth of the information received and with the way the healthcare staff delivered the first communication phone call, which failed to create a caring, empathic and safe setting. Many parents tried to reduce the uncertainty by searching online information or consulting with other providers. Nevertheless, the majority of parents described the in-person visit at MCC as clear, welcoming and reassuring. More efforts are needed to improve the quality of the communication process of the ENBS. Guidelines, recommendations and standard scripts to communicate positivity are needed along with programmes and educational resources to train tailored communication skills.

MANAJEMEN KOMUNIKASI BENCANA DALAM PENCEGAHAN KEBAKARAN LAHAN GAMBUT DI SUMATERA SELATAN

The communication process to prevent repeated land fires is carried out by conveying information about the impact of fires and their prevention. The disaster communication process and prevention scheme have been planned. However, peatland fires in South Sumatra are still recurring, so it is necessary to review the disaster communication steps that have been taken. Disaster communication management is always needed both in emergency and post-disaster conditions. This study aims to evaluate and describe disaster communication management in preventing peatland fires in South Sumatra. This study uses a qualitative method with an evaluative study approach. Collecting data was done using interviews, observations, and documentation studies. Data analysis in this study used an interactive analysis model. The results of this study indicate that the elements of disaster communication management used in efforts to prevent peatland fires in South Sumatra consist of planning, organizing, implementing, and evaluating.

A Compact Filtering Antenna With Step and Continuous Tuning Modes for WiMAX Cognitive Radio Communication

A Compact Filtering Antenna With Step and Continuous Tuning Modes for WiMAX Cognitive Radio Communication

Finite-Time Consensus Dual Algorithm for Distributed Optimization over Digraphs

In this paper, we solve the convex distributed optimization problems, which include unconstrained optimization and a special constrained problem commonly known as a resource allocation problem, over a network of agents among which the communication can be represented by directed graphs (digraphs), by using the finite-time consensus-based and dual-based first-order gradient descent (GD) techniques. The key point is that a special consensus matrix is utilized for problem reformulation to make our dual-based algorithm suitable for digraphs. By the property of distributed finite-time exact (not approximate) consensus, the classical centralized optimization techniques (e.g., Nesterov accelerated GD) can be embedded into our dual-based algorithm conveniently, which means our distributed algorithm can inherit performance of classical centralized algorithms that has been proved to have optimal convergence performance. As a result, our proposed algorithm has faster convergence rate related to the optimization iteration number compared with other distributed optimization algorithms in literature. Since there are finite consensus communication steps inside each consensus process, when the time needed to communicate values between two neighbors is less than a threshold of the time needed to perform local computations, our proposed algorithm is also faster related to the time, as demonstrated in the simulations.

Analysis of teacher instructional communication barriers

During the Covid-19 pandemic, education in Indonesia was held using the blended learning method, or a combination of online and offline education and learning patterns. This condition creates obstacles for teachers in the Districts of Kebon Jeruk and Grogol Petamburan in the process of effective learning communication. This study aims to identify barriers to teacher instructional communication in two sub-districts during the Covid19 pandemic. Empirically this research was conducted so that pedagogic competence in terms of teacher instructional communication can create a climate of Active, Innovative, Creative, Effective, and Fun Learning (PAIKEM). The discussion in this study uses the Shannon Weaver communication model. This study uses qualitative and descriptive methods with a case study approach. Data collection was also carried out by observing the teachers of SDN Duri Kepa 03 Kebon Jeruk District and Al Chasanah Junior High School, Grogol Petamburan District, West Jakarta while teaching offline and online. This study uses purposive sampling, ie from the beginning, the sample has been determined with specific considerations, namely those who are considered to have the ability and competence to provide maximum data. The results showed that the steps in instructional communication could overcome the communication barriers. The conclusion of this study is that by identifying communication disorders that occur and carrying out 10 steps of instructional communication, then pedagogic competence in terms of aspects of teacher instructional communication during the Covid-19 pandemic can be overcome.

Dual-Language Detection using Machine Learning

There are number of languages around the world and knowing all the languages is very difficult for any person. At the same time, unawareness about the language will hinder communication. Language identification is the process where the identifying the language(s) in text form is performed based on the writing style and looking at the unique diacritics of each language. When a multitude of languages are spoken in any circumstances, the first step in communication is the identification of the language. There are several techniques used for language detection like machine learning and deep learning. These are used in detecting languages like German. In India, numerous languages are spoken by the people and thus we propose to develop a model that detects two languages: Kannada and Devanagari/Sanskrit. In this study, Support Vector Machines classifiers were used, for classification and an accuracy of 99% was achieved.

CEMDA

People use smartphones to do many tasks: view email attachments, read social media posts, create and edit photographs, and forward files. The user's perspective on actions performed when creating, viewing, and modifying files (her mental model ) reflects the visible clicks and swipes performed. At the file system and OS, however, such actions are less clear. A single click can lead to a flurry of hundreds of file system reads and writes, system calls, and communication steps. While individual apps can use analytics to record in-app user actions, common patterns such as download-read-forward cross app boundaries and become difficult to discover. That lack leads to inefficiencies in on-device file management and backup. To better enable apps and devices to discover the user's mental model, we present CEMDA, an Android app that automatically detects the user's mental model by applying the theories of file lifecycle events and complex events. CEMDA detects over 10 high level user stories in 4 categories of user actions (create, access, share, modify) while operating completely in user space and without OS modification. CEMDA successfully detects user actions in cross-app actions across popular messaging and productivity apps (e.g., WhatsApp, Adobe Reader) with 75%-100% success while consuming minimal battery and memory.

FedPCC: Parallelism of Communication and Computation for Federated Learning in Wireless Networks

The advances of both computation and communication technologies facilitate the exploitation of massive data generated by mobile devices. It is attractive to leverage these data and computation resources to train high-performance machine learning (ML) models. In traditional ML methods, all data are uploaded to servers for model training, which incur issues of large overhead and privacy concerns. Federated learning (FL) was proposed to address these issues. In this paper, we propose FedPCC, an efficient approach based on the parallelism of communication and computation among devices for FL in wireless networks. FedPCC considers the difference in communication and computation capabilities between different devices and optimizes the training schedule for devices selected in each round. Instead of dividing an FL training round into separate communication and computation steps, FedPCC protocol arranges devices to download the global model sequentially and then start local model training immediately once finishing downloading, which allows better utilization of communication and computation resources. Specifically, we formulate an optimization problem to minimize the time for each training round and propose an algorithm to solve the problem based on the trade-off of devices’ communication and computation capabilities. FedPCC uses a heuristic algorithm to make slow devices start relatively earlier, which can shorten the time in one training round, thus reducing the entire training time. We conduct extensive experiments to demonstrate that the proposed protocol outperforms the existing protocols under different system settings.