communication demands
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2022 ◽  
Vol 18 (2) ◽  
pp. 1-22
Author(s):  
João Paulo Cardoso de Lima ◽  
Marcelo Brandalero ◽  
Michael Hübner ◽  
Luigi Carro

Accelerating finite-state automata benefits several emerging application domains that are built on pattern matching. In-memory architectures, such as the Automata Processor (AP), are efficient to speed them up, at least for outperforming traditional von-Neumann architectures. In spite of the AP’s massive parallelism, current APs suffer from poor memory density, inefficient routing architectures, and limited capabilities. Although these limitations can be lessened by emerging memory technologies, its architecture is still the major source of huge communication demands and lack of scalability. To address these issues, we present STAP , a Scalable TCAM-based architecture for Automata Processing . STAP adopts a reconfigurable array of processing elements, which are based on memristive Ternary CAMs (TCAMs), to efficiently implement Non-deterministic finite automata (NFAs) through proper encoding and mapping methods. The CAD tool for STAP integrates the design flow of automata applications, a specific mapping algorithm, and place and route tools for connecting processing elements by RRAM-based programmable interconnects. Results showed 1.47× higher throughput when processing 16-bit input symbols, and improvements of 3.9× and 25× on state and routing densities over the state-of-the-art AP, while preserving 10 4 programming cycles.


2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Pengfei Wang ◽  
Chi Lin ◽  
Zhen Yu ◽  
Leyou Yang ◽  
Qiang Zhang

The rapidly increasing number of smart devices deployed in the Industrial Internet of Things (IIoT) environment has been witnessed. To improve communication efficiency, edge computing-enabled Industrial Internet of Things (E-IIoT) has gained attention recently. Nevertheless, E-IIoT still cannot conquer the rapidly increasing communication demands when hundreds of millions of IIoT devices are connected at the same time. Considering the future 6G environment where smart network-in-box (NIB) nodes are everywhere (e.g., deployed in vehicles, buses, backpacks, etc.), we propose a crowdsourcing-based recruitment framework, leveraging the power of the crowd to provide extra communication resources and enhance the communication capabilities. We creatively treat NIB nodes as edge layer devices, and CrowdBox is devised using a Stackelberg game where the E-IIoT system is the leader, and the NIB nodes are the followers. CrowdBox can calculate the optimal reward to reach the unique Stackelberg equilibrium where the utility of E-IIoT can be maximized while none of the NIB nodes can improve its utility by deviating from its strategy. Finally, we evaluate the performance of CrowdBox with extensive simulations with various settings, and it shows that CrowdBox outperforms the compared algorithms in improving system utility and attracting more NIB nodes.


2021 ◽  
Author(s):  
S. Sudhakar ◽  
A. Akashwar ◽  
M. Ajay Someshwar ◽  
T. Dhaneshguru ◽  
M. Prem Kumar

The growing network traffic rate in wireless communication demands extended network capacity. Current crypto core methodologies are already reaching the maximum achievable network capacity limits. The combination of AES with other crypto cores and inventing new optimization models have emerged. In this paper, some of the prominent issues related to the existing AES core system, namely, lack of data rate, design complexity, reliability, and discriminative properties. In addition to that, this work also proposes a biometric key generation for AES core that constitutes simpler arithmetic such as substitution, modulo operation, and cyclic shifting for diffusion and confusion metrics which explore cipher transformation level. It is proved that in AES as compared to all other functions S-Box component directly influences the overall system performance both in terms of power consumption overhead, security measures, and path delay, etc.


PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258575
Author(s):  
Caroline Jagoe ◽  
Caitlin McDonald ◽  
Minerva Rivas ◽  
Nora Groce

Introduction An estimated 1 billion people with disabilities live in low and middle income countries, a population that includes people with communication disabilities (PwCD). PwCD are a heterogenous group with a wide range of abilities who may be underrepresented in research due to the communication demands involved in research participation. Methods A critical analysis of 145 studies from a previously published systematic review was undertaken with the aim of documenting the opportunities for direct participation of PwCD in research on poverty and disability in low- and middle- income countries. Results The key finding was the high risk of underrepresentation of PwCD in research on poverty and disability in LMICs, despite low rates of explicit exclusion (n = 8; 5.5%). A total of 366 uses of data collection tools were analysed (255 unique tools). The majority of data collection tools had high communication demands (92.9%), including those measuring disability (88.6%) and those assessing poverty (100%). Only 22 studies (15.2%) specifically included PwCD. A subset of these studies (n = 14) presented disaggregated data in a way that allowed for analysis of outcomes for PwCD, suggesting a clear intersection between poverty and communication disability, with findings related to general poverty indicators, reduced access to education, low levels of employment, and additional expenditure. Conclusions The findings suggest a systematic underrepresentation of PwCD in research on poverty and disability with substantial implications for future policy and program planning, directly affecting the availability and provision of services and resources for this population. A failure to provide adequate opportunity for participation of PwCD in research risks leaving those with communication disabilities behind in the pursuit of global poverty eradication.


2021 ◽  
pp. 089331892110413
Author(s):  
Sarah E. Riforgiate ◽  
Satoris S. Howes ◽  
Mathias J. Simmons

Emotional labor research largely focuses on client-facing occupations. However, employees across occupations engage in emotional labor when they perceive that specific types of emotional communication are required to align with organizational expectations. The current two-week daily survey study of 42 employees was conducted at a small website development company to examine relationships between employees’ emotional labor, physical health, and psychological well-being. Results indicated that daily emotional labor surface acting was significantly negatively related to daily psychological well-being and daily physical health. However, daily emotional labor deep acting was not significantly related to daily psychological well-being or daily physical health. After aggregating emotional labor across days, results revealed a significant positive relationship between emotional labor and burnout. This study enhances organizational awareness of the relationship between emotional communication expectations and employees’ psychological and physical health. Research-driven practices are detailed to ameliorate the negative side effects of emotional labor communication demands.


2021 ◽  
pp. 875529302110266
Author(s):  
Hesam Talebiyan ◽  
Kanoknart Leelardcharoen ◽  
Leonardo Dueñas-Osorio ◽  
Barry J Goodno ◽  
James I Craig

This article quantifies the seismic performance of interdependent electric power and telecommunication systems, while also identifying variables with the highest impact on design. We introduce interdependent power and telecommunication models, which probabilistically simulate the physical dependency of telecommunication systems on power via interdependent adjacency and coupling strength, while a topology observability analysis quantifies the cyber dependency of the power system on telecommunications. We also use new functionality-based performance measures, including data congestion in telecommunications and partial observability in power systems, given communication demands upsurging after earthquakes. As an application, our methodology assesses the performance of stylized power and telecommunication systems in Shelby County, TN. Results show that neglecting retrials, congestion, and power interdependency lead to significant overestimation of the performance of telecommunication systems, particularly at low-to-medium hazard levels. Sensitivity results also reveal that decreasing the strength of coupling across systems is one of the most effective ways to improve the seismic performance of evolving cyber-physical systems, particularly when increasing observability in the power system through telecommunication end offices with richer data flow pathways.


Author(s):  
Yegnanarayanan Venkatraman ◽  
◽  
Narayanaa Y Krithicaa ◽  
Valentina E. Balas ◽  
Marius M. Balas ◽  
...  

Notice that the synapsis of brain is a form of communication. As communication demands connectivity, it is not a surprise that "graph theory" is a fastest growing area of research in the life sciences. It attempts to explain the connections and communication between networks of neurons. Alzheimer’s disease (AD) progression in brain is due to a deposition and development of amyloid plaque and the loss of communication between nerve cells. Graph/network theory can provide incredible insights into the incorrect wiring leading to memory loss in a progressive manner. Network in AD is slanted towards investigating the intricate patterns of interconnections found in the pathogenesis of brain. Here, we see how the notions of graph/network theory can be prudently exploited to comprehend the Alzheimer’s disease. We begin with introducing concepts of graph/network theory as a model for specific genetic hubs of the brain regions and cellular signalling. We begin with a brief introduction of prevalence and causes of AD followed by outlining its genetic and signalling pathogenesis. We then present some of the network-applied outcome in assessing the disease-signalling interactions, signal transduction of protein-protein interaction, disturbed genetics and signalling pathways as compelling targets of pathogenesis of the disease.


Author(s):  
Rafael Stahl ◽  
Alexander Hoffman ◽  
Daniel Mueller-Gritschneder ◽  
Andreas Gerstlauer ◽  
Ulf Schlichtmann

AbstractPerforming inference of Convolutional Neural Networks (CNNs) on Internet of Things (IoT) edge devices ensures both privacy of input data and possible run time reductions when compared to a cloud solution. As most edge devices are memory- and compute-constrained, they cannot store and execute complex CNNs. Partitioning and distributing layer information across multiple edge devices to reduce the amount of computation and data on each device presents a solution to this problem. In this article, we propose DeeperThings, an approach that supports a full distribution of CNN inference tasks by partitioning fully-connected as well as both feature- and weight-intensive convolutional layers. Additionally, we jointly optimize memory, computation and communication demands. This is achieved using techniques to combine both feature and weight partitioning with a communication-aware layer fusion method, enabling holistic optimization across layers. For a given number of edge devices, the schemes are applied jointly using Integer Linear Programming (ILP) formulations to minimize data exchanged between devices, to optimize run times and to find the entire model’s minimal memory footprint. Experimental results from a real-world hardware setup running four different CNN models confirm that the scheme is able to evenly balance the memory footprint between devices. For six devices on 100 Mbit/s connections the integration of layer fusion additionally leads to a reduction of communication demands by up to 28.8%. This results in run time speed-up of the inference task by up to 1.52x compared to layer partitioning without fusing.


2021 ◽  
Author(s):  
Monika Molnar ◽  
Kai Ian Leung ◽  
Jodee Santos Herrera ◽  
Marcel Giezen

Aims and ObjectivesThis study was designed to assess whether bilingual caregivers, compared to monolingual caregivers, modify their nonverbal gestures to match the increased communicative and/or cognitive-linguistic demands of bilingual language contexts - as would be predicted based on the Facilitative Strategy Hypothesis.MethodologyWe recorded the rate of representational and beat gestures in monolingual and bilingual caregivers when they retold a cartoon story to their child or to an adult, in a monolingual and a bilingual context (‘synonym’ context for monolingual caregivers).Data and AnalysisWe calculated the frequency of all gestures, representational gestures, and beat gestures for each addressee (adult-directed vs. toddler-directed) and linguistic context (monolingual vs. bilingual/synonym), separately for the monolingual and the bilingual caregivers. Using ANOVA, we contrasted monolingual vs. bilingual caregivers’ gesture frequency for each gesture type separately - based on addressee and linguistic context. Findings/ConclusionsBilingual caregivers gesture more than monolingual caregivers, irrespective of addressee and language context. Furthermore, we found evidence in support of the Facilitative Strategy hypothesis across both monolingual and bilingual caregivers, as all caregivers increased the rate of their representational gestures in the child-directed re-telling. However, we found no clear patterns showing that bilingual caregivers, compared to monolingual caregivers, adjust their gestures when the communication demands from their child’s perspective are presumably high (i.e., the child is listening to a story in two languages). In summary, both monolingual and bilingual caregivers similarly adjust their gestures to aid their child’s comprehension, and bilinguals generally gesture more than monolinguals.OriginalityTo our knowledge, this is the first study of gesture use in child-directed communication in monolingual and bilingual caregivers.Significance/ImplicationsIndependent of their monolingual or bilingual status, caregivers adjust their child-directed multimodal communication strategies (specifically gestures) when interacting with their children.


Author(s):  
Sabah Uddin Saqib ◽  
Khawaja Muhammad Inam Pal

Abstract Introduction: The majority of cancer patients’ relatives in developing countries, especially in Pakistan prefers and demand, and in most times impose a “do not tell approach”, while counselling for patients disease. Thus, the aim of the current study is to first assess patients’ understanding about his or her disease and see preferences regarding the manner in which physicians’ deliver news about cancer diagnosis and its management plan. Material and methods: This was a cross-sectional qualitative study. Patients were approached and interviewed while having their regular follow-up. An immediate relative of the patient was also included in the study to see family perception regarding disease after their consent. This study enrolled 55 patients with 6 different types of cancers. Results: This study shows that 35 (65.5%) patients did not know stage at diagnosis while 40 (72.7%) patients did not know the current stage of their disease. In 22 (40%) cases, patient’s family knew diagnosis ahead of patient and 19 (86.3%) families asked clinicians to hide diagnosis news from the patient. This study demonstrates, specialist oncologist for breaking news, family counseling, helping patient to figure out how to tell diagnosis to others, telling news directly to the patient and the effects of cancer on daily life are preferred area to communicate on first visit. Conclusion:  Disclosing cancer news is always an unfavorable experience not only for patient and family but also clinician as well. In our population both patient understanding and communication demands improvements. Continuous...


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