Algorithmic Implementation of Load Balancing �in Wireless LAN

Intra domain traffic engineering (TE) has become an indispensable tool for Internet Service Providers (ISPs) to optimize network performance and utilize network resources efficiently. Various explicit routing TE methods were recently proposed and have been able to achieve high network performance. However, explicit routing has high complexity and requires Large Ternary Content Addressable Memories (TCAMs) in the routers. Moreover, it is costly to deploy explicit routing in IP networks. In this project, we present an approach, called Generalized Destination-Based Multipath Routing (GDMR), to achieve the high performance as explicit routing. The main contribution of this project is to enhance an arbitrary explicit routing can be converted to a loop-free destination-based routing without any performance penalty for a given traffic matrix. We present a systematic approach including a heuristic algorithm to realize GDMR. Extensive evaluation demonstrates the effectiveness and robustness of GDMR

Algorithmic Implementation of Load Balancing –in Wireless LAN

Intra domain traffic engineering (TE) has become an indispensable tool for Internet service providers (ISPs) to Optimize network performance and utilize network resources efficiently . Various explicitrouting TE methods were recently proposed and have been able to achieve high network performance. However, explicit routing has high complexity and requires large ternary content addressable memories (TCAMs) in the routers. Moreover, it is costly to deploy explicit routing in IP networks. In this paper, we present an approach, called generalized destination-based multipath routing (GDMR), to achieve the same high performance as explicit routing. The main contribution of this paper is that we prove that an arbitrary explicit routing can be converted to a loop-free destination-based routing without any performance penalty for a given traffic matrix. We present a systematic approach including a heuristic algorithm to realize GDMR. Extensive evaluation demonstrates the effectiveness and robustness of GDMR

A Review Paper on Classification of Stem Cell Transplant to Identify the High Survival Rate

A patient undergoing hematopoietic stem cell transplant faces various risk factors and has become the standard of care for congenital or acquired disorders of the hematopoietic system or with chemo-sensitive, radiosensitive or immunosensitive malignancies. Analyzing and classifying the data from past transplant can enhance the understanding of the factors leading to highest survival rates among the patients. Over the last few decades there has been tremendous use of technology in this field. Stem cell transplant remains a dangerous procedure as it requires significant infrastructure and a network of specialists from all fields of medicine. In this paper, we are using a classification algorithm known as Support Vector Machine to classify the patients who have undergone stem cell transplant with high odds of survival. We are also keeping track of information about the donors within the family and outside the family which has a direct impact in the prioritization of resources. Classification of this information is useful to create the need for a global perspective for all cell, tissue, and organ transplants and to reveal statistical structure with potential implications in evidence-based prioritization of resources. Machine-learning techniques proved useful in analyzing the correct data from various datasets as this techniques were previously been considered too complex to analyze. DOI: 10.17762/ijritcc2321-8169.16043

A Study to Assess Knowledge, Attitude and Practice Regarding Tuberculosis among Tuberculosis Patients at Health Centre Nadiad

Tuberculosis is well known contagious infection that spreads though the inhalation of droplet produced by the coughs or sneezes of and infected person. TB usually affect the lungs (pulmonary TB) but can also affect multiple other organs Aims: To Assess the level of Knowledge, Attitude, and Practice among Tuberculosis Patients.  Methodology: A quantitative study was conducted among 100 tuberculosis patients of selected health center Nadiad city by using purposive sampling technique. Data were obtained using knowledge questionnaire (19), Likert’s attitude scale (10) and practice questionnaire (10) with interview technique. Descriptive statics were used to analyze the demographic data.  Result :In this study total 100 tuberculosis patients are participated the result revealed than 14(14%) tuberculosis patients have good knowledge, 66(66%) tuberculosis patients have average knowledge, and 20(20%) tuberculosis patients have poor knowledge, about attitude the shoes that 21(21%) tuberculosis patients have favorable attitude,3(3%) tuberculosis patients have unfavorable attitude and 76(76%) patients have Moderate attitude about practice shows that 20(20%) tuberculosis patients have good practices, 1(1%) tuberculosis patients have poor practices and 79(79%) average practice. The finding tuberculosis patient having good knowledge, Moderate attitudes, and average practice. Conclusion: In this study, the knowledge of patients about TB were found within a low level of perception. Therefore, implementation of health education and awareness program are required to reduce the prevalence of TB

Racial discrepancies in interpregnancy intervals and postpartum contraception receipt in Centering Pregnancy prenatal care

Non-Hispanic black women are disproportionately affected by higher rates of shorter interpregnancy intervals. The purpose of this study is to identify whether the Centering Pregnancy model of group prenatal care (GPC) can reduce this health disparity by increasing postpartum contraception receipt. This retrospective chart analysis measures consistency in contraception intent versus actual postpartum receipt in populations of women who received either individual or GPC. The main predictors were: race, insurance type (public or private), marital status, and type of prenatal care. The main outcomes were: type of contraception received, consistency with contraception intent, and presence of a short interpregnancy interval. Of the limited sample population analyzed (n=37), a distribution test found that only 10% of GPC patients (n=10) received a different contraception, compared to 48% of non-GPC patients (n=13). Non-Hispanic black patients overall (n=7) were 20% more likely than White patients (n=12) to receive a different contraception than intended prepartum. Correlation between contraception consistency and variables race (-0.3895) and GPC participation (0.2828) is low, while insignificant for insurance and marital status (\u3c0.06). Due to lack of Ob/Gyn patient follow up in chart documentation, interpregnancy intervals could not be addressed in this research. Data collection is still in progress. These results suggest that (1) non-Hispanic black women are unable to receive the contraception requested during prenatal care and (2) GPC may be an appropriate intervention in increasing autonomy over contraception receipt. To evaluate racial disparities in these outcomes, an additional comparison must be made between non-Hispanic black women who attended GPC and those who did not

A reinforcement-learning-based model for resilient load balancing in Hyperledger Fabric

Blockchain with its numerous advantages is often considered a foundational technology with the potential to revolutionize a wide range of application domains, including enterprise applications. These enterprise applications must meet several important criteria, including scalability, performance, and privacy. Enterprise blockchain applications are frequently constructed on private blockchain platforms to satisfy these criteria. Hyperledger Fabric is one of the most popular platforms within this domain. In any privacy blockchain system, including Fabric, every organisation needs to utilise a peer node (or peer nodes) to connect to the blockchain platform. Due to the ever-increasing size of blockchain and the need to support a large user base, the monitoring and the management of different resources of such peer nodes can be crucial for a successful deployment of such blockchain platforms. Unfortunately, little attention has been paid to this issue. In this work, we propose the first-ever solution to this significant problem by proposing an intelligent control system based on reinforcement learning for distributing the resources of Hyperledger Fabric. We present the architecture, discuss the protocol flows, outline the data collection methods, analyse the results and consider the potential applications of the proposed approach

On correlation functions of Wilson loops, local and non-local operators

We discuss and extend recent conjectures relating partial null limits of correlation functions of local gauge invariant operators and the expectation value of null polygonal Wilson loops and local gauge invariant operators. We point out that a particular partial null limit provides a strategy for the calculation of the anomalous dimension of short twist-two operators at weak and strong coupling.Comment: 29 pages, 8 figure

On Feynman rules for Mellin amplitudes in AdS/CFT

The computation of CFT correlation functions via Witten diagrams in AdS space can be simplified via the Mellin transform. Recently a set of Feynman rules for tree-level Mellin space amplitudes has been proposed for scalar theories. In this note we derive these rules by explicitly evaluating all of the relevant Witten diagram integrals for the scalar phi^n theory. We also check that the rules reduce to the usual Feynman rules in the flat space limit.Comment: minor corrections, published versio

Effectiveness of early intervention programs for parents of preterm infants: a meta-review of systematic reviews

Background: Various intervention programs exist for parents of preterm babies and some systematic reviews (SRs) have synthesised the evidence of their effectiveness. These reviews are, however, limited to specific interventions, components, or outcomes, and a comprehensive evidence base is lacking. The aim of this meta-review was to appraise and meta-synthesise the evidence from existing SRs to provide a comprehensive evidence base on the effectiveness of interventions for parents of preterm infants on parental and infant outcomes. Methods: We conducted a comprehensive search of the following databases to identify relevant SRs: Cochrane library, Web of science, EMBASE, CINAHL, British Nursing Index, PsycINFO, Medline, ScienceDirect, Scopus, IBSS, DOAJ, ERIC, EPPI-Centre, PROSPERO, WHO Library. Additional searches were conducted using authors’ institutional libraries, Google Scholar, and the reference lists of identified reviews. Identified articles were screened in two stages against an inclusion criteria with titles and abstracts screened first followed by full-text screening. Selected SRs were appraised using the AMSTAR tool. Extracted data using a predesigned tool were synthesised narratively examining the direction of impact on outcomes. Results: We found 11 SRs eligible for inclusion that synthesised a total of 343 quantitative primary studies. The average quality of the SRs was ‘medium’. Thirty four interventions were reported across the SRs with considerable heterogeneity in the structural framework and the targeted outcomes that included maternal-infant dyadic, maternal/parental, and infant outcomes. Among all interventions, Kangaroo Care (KC) showed the most frequent positive impact across outcomes (n = 19) followed by Mother Infant Transaction Program (MITP) (n = 14). Other interventions with most consistent positive impact on infant outcomes were Modified-Mother Infant Transaction Program (M-MITP) (n = 6), Infant Health and Development Program (IHDP) (n = 5) and Creating Opportunities for Parent Empowerment (COPE) (n = 5). Overall, interventions with both home and facility based components showed the most frequent positive impact across outcomes. Conclusions: Neonatal care policy and planning for preterm babies should consider the implementation of interventions with most positive impact on outcomes. The heterogeneity in interventions and outcomes calls for the development and implementation of an integrated program for parents of preterm infants with a clearly defined global set of parental and infant outcomes

An Ultrasonic Based System to Measure Inter Spinous Process Distance in Humans: A Pilot Study

ABSTRACT The objective of this research project was to develop an ultrasonic based testing system and evaluate its application on human volunteers to locate and assess the distance between adjacent lumbar vertebrae. Tests were performed on ten volunteers aged between 19 and 29 years old during two sessions. The participants were asked to lie face down on a table with lower back section uncovered while the tests were executed. A computer controlled ultrasonic system was designed for this application. A single element 3.5 MHz immersion transducer held by a customized assembly was used to propagate and receive the ultrasonic signals. The transducer was moved along the assembly to fully scan at least two contiguous spinous processes. A Lab view based program was designed to generate a twodimensional image (B-scan) that display the shape and position of the bone tips as well as the distance between them. The standard deviation obtained from the measurements of the distance between the tips of the spinous processes of human subjects, in a given session ranged from 0.1-0.48mm. The difference between two sessions had a mean of 0.85-0.95 mm and a standard deviation of 0.87-1.03mm with reliability coefficients greater than 0.95. The study demonstrated the viability of utilizing ultrasound to precisely measure the distance between spinous processes of adjacent lumbar vertebrae