Top PDF Cognitive Edge Computing based Resource Allocation Framework for Internet of Things

Cognitive Edge Computing based Resource Allocation Framework for Internet of Things

Cognitive Edge Computing based Resource Allocation Framework for Internet of Things

In any network of connected devices, processing capacity and latency have always been major concerns for researchers and practitioners. The number of connected devices are ex- pected to grow exponentially in the next coming decades, creating a new paradigm shift; where the aforementioned concerns will become major optimization criteria. Due to the growing demands for resources, depending on the enterprise cloud, is no longer a feasible solution. Edge Computing is a promising paradigm is this context, and complies with future developments such as 5G technologies. The framework proposed in this paper intended to integrate the advancement of edge computing resource requirement schemes as well as the resource allocation schemes found in the literature for enterprise cloud; to attain a universal resource allocation framework for IoT . The assumption has taken into consider- ation that the enterprise cloud operating system supports bi- directional resource sharing from local processing platform with heterogeneous device properties. To obtain the proposed resource allocation framework to be more cost-effective, auc- tion mode of resource sharing agreement will be considered for future works, alongside investigating the feasibility of a unified operating system compatible with cloud resource sharing within heterogeneous computing devices.
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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

The proliferation of smart Internet of Things (IoT) devices in our homes provides a level of convenience in our day-to-day activities but also raises key privacy concerns. There is an implicit concern among users that these devices storing important confidential information about the user (identity, credit-card details, family profile, house information) could someday go rogue leading to a doomsday question for user privacy. The general concern that, as technology gets smarter by the day, the level of privacy gets weaker, is already being reflected among users’ opinions today. With the array of smart sensors, assistants and perhaps robots invading the smart home consumer market, majority of users are already raising concerns on the need for constant monitoring (audio, video, indirect sensing) of the users. In a couple of recent patents [32], Google imagines devices that would get a lot more intrusive than what’s already available out there. We believe that it is only a matter of time before current day smart home technology deployments potentially hit the tipping point for privacy intrusion.
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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

What could be the mechanistic basis for a boost in RdRP activity when only one P-XD subunit is able to interact with L? A previous study considered that negotiation of the encapsidated template by paramyxovirus polymerases might depend on continuous structural rearrangements within the RdRP complex, possibly including the repetitive dissolution and reassembly of P:L interaction [117]. Based on our identification of a bipartite P:L interface and the trans- complementation data, we propose that the newly discovered P-XD:L interface periodically resolves and reforms. In wild type P tetramers, all four P-XDs are L binding-competent. Iterative separation of P-XD from L creates an opportunity for competition between the individual P-XDs to reengage with L and/or need for rearrangement within the P-L hetero-oligomer every time a physically different P-XD than before is successful. Delegating L binding to a designated P-XD monomer as in our mixed P tetramers eliminates internal competition and associated rearrangements of the complex, unleashing maximal polymerase processivity. This conclusion is consistent with the mathematical description of our experimental data and provides ready explanations for why a bipartite P:L interface may have evolved – two distinct contact zones allow temporary separation of only the P-XD:L interface without presumably catastrophic full separation of P from L – and why the trans-complementation pair depicted in Figure 20B-4 is bio-inactive. If P-XD indeed transiently separates from and rebinds to L as the polymerase advances along the template, the single (L + MoRE + ) P-XD monomer present in every RdRP complex that can
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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

socioeconomic or geographical differences between population groups (HHS, 2016). Lack of access to care is the major factor and the leading cause of healthcare disparities in the under- served population; these barriers prevent people from getting quality healthcare services (AHRQ, 2011). In fact, the burden of health disparities not only affect individuals, but the society as a whole; the joint center for political and economic studies estimates medical care expenditures associated with health disparities, costs at $229.4 billion for direct medical care expenditures and $1 trillion for the indirect costs of disparities (HHS, 2016). Financial cost may be part of the deterrent factors for many in getting medical checkups, but for many people in rural areas, MHCs tend to be the only and more feasible resource (McCoy, Williams, Atkinson, & Rubens, 2016; Rodriguez, Appelt, Young, & Fox, 2007). MHC offers a cost-effective option in
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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

grades has been shown by other researchers. For example, Jewell and Malecki (2005) found that certain CBM scores were strong predictors of qualitative measures of writing for second-grade students, but not for fourth- and sixth-grade students. Similarly, Parker, Tindal, and Hasbrouck (1991) found that certain CBM scores were suitable as screening measures for struggling writers in fourth grade, but not in the second and third grades. Taken together, the results of these studies indicate that what we know about writers in one grade may not apply to writers in another grade. Accordingly, what we know about first graders, who are also young, beginning writers, does not apply to kindergarten students. However, based on the results of the present study, a qualitative and productivity scoring system appear to be sufficient for measuring kindergarten writing. Furthermore, these measures are easy and quick to administer and score, which is an important consideration for school-based research and in-classroom assessment. These measures appear to measure the components of writing that have previously been identified as important. Therefore, instructional attention to these important aspects of writing (productivity and quality, including accuracy and macro-organization) may be important for facilitating writing in emerging writers in kindergarten.
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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

Participants were randomized to one of two interventions. The MBAT intervention group had 33 participants partake while the “iQuit” Mindfully group had 38 participants. The MBAT intervention involved eight weekly 2-hour in-person group treatment sessions, nicotine patch therapy, and self-help materials. The aims of MBAT were to: (a) become more aware of thoughts, feelings, and sensations from moment to moment, (b) develop a different way of relating to thoughts, feelings, and sensations, and (c) increase the ability to disengage attention and choose skillful responses to any thoughts, feelings, or situations that arise (Vidrine et al., 2016). MBAT is intended to serve as a primary treatment approach and incorporates meditation practice later within each treatment session. Participants in the iQuit Mindfully condition similarly received the MBAT intervention and also received text messages throughout the day, which remind participants to practice mindfulness. These texts also reminded participants of their personal reasons to quit as well as specific strategies to aid in cessation (ex: reminders to get rid of cues to smoke, reach out for social support, and to use cognitive behavioral strategies taught in MBAT). Participants were also able to text specified words to request help. For example, they may text CRAVE, STRESS, or SLIP at any point to received additional support through text messages for coping with cravings, stress, or smoking lapses, respectively.
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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

LOCALIZED EXPRESSION OF PYROPTOSIS-ASSOCIATED MOLECULES IN THE RETINA FOLLOWING MCMV INFECTION OF MAIDS-10 MICE As addressed before, apoptosis and necroptosis were not the only programme[r]

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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

conditions and known error modes which aims to make these limitations more transparent. There may be an ethical requirement to reveal such limitations, with the potential for future legal requirements to provide them. Past empirical research into explanations in AI has found mixed outcomes for explanations. However, deep learning systems may commit errors that can be readily detected when partnered with a human and explanation may be more valuable than has been identified in research on other types of AI systems. Further, there is relatively little known about how people process agent explanations regardless of type of system, with past research focused on trust, preference, and compliance. A social cognition framework was employed to focus on how explanations are processed by participants performing the task. An experiment was conducted where three types of explanations were manipulated between conditions. Participants were randomly selected into one of five conditions: A “black box” condition with no
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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

Cognitive: children will start recognizing the function of objects; retelling stories from picture books; engaging in pretend play; drawing people with more recognizable parts; differentiating between real and make-believe; and becoming capable of anticipating what will happen next. Communication: children will be able to answer questions about a story they were told; use regular past tense form; demonstrate emotions by using facial expressions and body language; generate more complex sentences; have an improved understanding of time concepts; give more than two descriptive words that characterize an object; and participate in group discussions. Social-Emotional: children will start sharing toys with others; participate in group games and activities; volunteer for tasks and show pride in accomplishment; talk about their feelings; offer to help others; and have the appropriate responses to social situations.
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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

En conséquence, ces esclaves ne sont pas nés d'Afrique mais de l'océan Glissant.Cette théorie de Glissant nous permettra d’analyser le trope de la mer dans Des pieds mon pied, et son imp[r]

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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

WT mice, but not in Tlr4-/- mice. If anything, there was a trend toward LPS increasing time spent in the center zone in Tlr4-/- mice, suggesting that LPS may interact with other innate immune receptors to decrease anxiety. TLR4 antagonists, however, did not directly block the effects of LPS gavage on behavior. It is unlikely that this is due to ineffective dosage, as we chose dosages of antagonists based on the literature (Sorge et al., 2011; Wu et al., 2012; Corrigan et al., 2015; Li et al., 2015a), and (+)-naloxone affected behavior regardless of LPS treatment in this study. Measurement of cytokines suggests that LPS acted primarily at the level of the gut, as we did not find elevation of inflammatory markers in serum but did find a significant elevation of IL-6 expression in the gut. If so, it may be that the TLR4 antagonists did not intervene effectively at the site of action of the LPS. Orally-administered LPS likely interacts with TLR4 present on the apical surface of intestinal epithelial cells. It is plausible that our antagonists, when injected intraperitoneally, do not have sufficient access to these receptors.
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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

An ethnoscape by Appadurai’s (1990) definition is a landscape of persons who shift throughout the world, this can constitute as a tourist, immigrant, refugee, exile, and guest worker. However, Appadurai notes that movement and migration is not limited to a physical shift, but can also mean imagining or envisioning moving, leaving, or migrating to another place. Thinking about a place, city, or space, of new horizons and futures, is not solely based in fantasy but a practical and realistic process based on changes in society, such as policies on immigration, involuntary migration, political strife, and more. Although imagined worlds and communities seem speculative, they are very much practical and necessary. The utilization of Twitter by second-generation East African women offer new insight on the diasporic production of the global order, but more so, whether these practices of the imaginary through discursive means on the web provide the agency that Appadurai speaks of. The effectiveness of Twitter as a site for cultural productions of identity and homeplace will unveil whether speculative and imagined worlds constitute as new realities for second-generation East African women.
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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

understand that RLC is important but that general comprehension must be obtained first. If the students do not understand what is going on, they cannot make the relevant STEAM connections. I used student participation in the discussions surrounding the artworks as a clear indicator of understanding. If half of the students showed visual or verbal understanding I noted it as a medium level of comprehension. I also noted less than half of the students showing visual or verbal understanding as low student comprehension. More than half of the students showing visual or verbal understandings was recorded as a high level of comprehension. I shared my knowledge of nonverbal comprehension assessment with the High museum coordinators. We agreed on some strategies that could be implemented into the museum tours. Docents would use some strategies with students who were non verbal based on visual responses. Docents would also sometimes base student levels of understanding and participation on the sketching activities previously mentioned. Additionally, I observed docents offering a non verbal student a paper and clipboard to draw on and respond with several times even if there was not a specific drawing activity. The docents used the thumbs strategy to ask for understanding as well which I noted as effective and inclusive.
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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

prostaglandin cervical ripening than dinoprostone in women with a high BMI and that mechanical cervical ripening may work better than pharmacological cervical ripening. The time to birth was longer for women who were induced and women who had a higher BMI, but there is little literature regarding the time to birth in women with a high BMI. What is known about labor induction with cervical ripening among women with a high BMI has been largely based on the retrospective analysis of cohort studies. While there are a few studies with large sample sizes, these existing studies do not appropriately control for parity, which plays a significant role in labor induction outcomes regardless of obesity category. A multiparous woman with a previous vaginal birth has a higher chance at a subsequent vaginal birth than a nulliparous woman who has not yet had a vaginal birth. Little is known regarding whether a woman’s BMI affects labor induction
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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

Topics included history of birth control method use, experience with formal or informal sex education, identification with a community of IUD users, political beliefs and concerns, curre[r]

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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

departments. Without this information, HBCU administrators will only have one side of the big picture of college athletics, and not fully understand where their institutions are in financial comparison to other NCAA member institutions. The NCAA is made up of 1,117-member institutions, and research into what sets HBCU athletic departments apart from the rest of the membership can help identify possible solutions to the growing financial disparity in college athletics. Recent research has found HBCUs spend less annually on operating expenses, head coach salaries, recruiting, and athletic aid when compared to their peer institutions. Additionally, these institutions fall short in the race for revenue and report significantly less earnings than their peers (Elliott, Kellison, & Cianfrone, Research in progress). This financial picture indicates research is needed to have a better understanding of the fiscal, budget, and revenue-based challenges faced by both HBCUs and PWI athletic departments.
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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

First, Benoit emphasizes the importance of audience analysis for a successful image repair effort, arguing that “understanding the accusations expressed to the audience…may provide insights into potential image repair messages” (2014, p. 30). However, it needs attention here that rather than explicitly referring to the audience’s actual perceptions, Benoit suggests understanding the rhetor’s perceptions of the audience’s accusations, an argument that first appears in his first elucidation of the image repair theory in 1995. Benoit differentiates these two versions of perceptions, noting that they “may or may not correspond” (p. 82). While he admits the differences, Benoit insists analyzing the rhetor’s perceptions of the audience’s reaction to attacks since “[they] are all the rhetor has available to prompt and guide image restoration efforts” (p. 82). Benoit’s excuse is no longer valid in the context of social media and Internet where the audiences’ perceptions can be instantaneously available for the interested parties. Benoit details audience analysis in his 2008 book Persuasive Messages, but unfortunately, he just suggests not only focuses on factors of audience’s size, homogeneity, history with the persuader but also on their knowledge about, interest in, and attitude toward the persuasive messages without offering an empirical basis. The purpose of conducting audience analysis, however, is not for the stakeholders’ good but for the accused organizations. Benoit also
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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

The integrated theory of health behavior change (ITHBC; Ryan, 2009) was the theoretical framework to guide this pilot study. A variety of theoretical categories exists in the discipline of nursing to frame research. These include grand and middle range theories (Peterson & Bredow, 2017). Grand theories are described as broad, abstract theories that provide information about nursing’s mission and goals (Meleis, 1997). Grand theories guide nursing practice by providing a framework for education that helps with the foundation of nursing practice (McKenna, 1997). In contrast, middle range theories are described as less abstract, with a more narrow focus, and are applicable to nursing practice (Meleis, 1997; Peterson & Bredow, 2017). The ITHBC is a middle range theory that predicts that health behavior change and the management of chronic conditions is a dynamic process that requires desire, motivation, and self-reflection to change behaviors (see Figure 1). Each of the interrelated concepts of the overall health ITHBC leads to proximal (engagement in self-management behaviors) and distal
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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

A total of 24 samples were retrieved from KAP-01 for charcoal and fungi taxa analysis. Sampling intervals were done at varying intervals while paying acute attention to core sediments that displayed significant changes in sediment composition based on LOI data. Each sample vial was spiked with two tablets of Lycopodium spores before the chemical treatment to determine the accuracy and variability of the fungal spore results (Meng, 1994). All samples were prepared and treated with KOH, HF, HCl, acetolysis, sieved for fine concentrations, and suspended in silicon oil following the standard method of pollen processing (Faegri, Kaland, & Krzywinski, 1989). Fungal spores samples were then mounted on slides for identification and counting. Identification of fungal spores and microscopic charcoal was performed using Olympus BX 43 microscope at 60X magnification.
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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

(1990) argued that “information-rich cases” are important to learn about issues of central significance to the purpose of the research and used the term “purposeful sampling” (p.169). A purposeful sampling can be used to yield the richest information about the phenomena in the study, thus, researchers emphasize the importance of determining suitable criteria for choosing who is to be studied (Mason, 2002; Merriam, 2002; Patton, 1990). Sample units are then chosen based on how well they represent particular features or characteristics that the researcher can explore to understand themes and questions that they are pursuing in the study (Ritchie et al. 2013). Thus, the number of participants for this study was ideally between 3-5. Participants were ideally in high school or recently graduated. Participants who had been in the US fewer than 5 years, and possibly ones who are currently taking an ESL course in a university or a public school to understand their language proficiency were recruited. This particular age group of participants was ideal because they had high access to mobile devices in everyday life based on the literature review. Further, identifying the number of years each had been in the US enabled me to understand their language development and types of apps they might use to learn language. The participants’ social markers (e.g., gender, nationality, and native language) varied. Inclusion criteria for participants in this study were as follows: a) ELs who have access to mobile devices such as smartphones and use them to learn language; b) ELs who are aged between 13 to 21; c) ELs whose native language is other than English and d) ELs who came to the US less than 5 years ago. For the participants who are native Korean speakers, the interviews were conducted in Korean upon their request.
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