Robust Framework to Combine Diverse Classifiers Assigning Distributed Confidence to Individual Classifiers at Class Level

We have presented a classification framework that combines multiple heterogeneous classifiers in the presence of class label noise. An extension of m-Mediods based modeling is presented that generates model of various classes whilst identifying and filtering noisy training data. This noise free data is further used to learn model for other classifiers such as GMM and SVM. A weight learning method is then introduced to learn weights on each class for different classifiers to construct an ensemble. For this purpose, we applied genetic algorithm to search for an optimal weight vector on which classifier ensemble is expected to give the best accuracy. The proposed approach is evaluated on variety of real life datasets. It is also compared with existing standard ensemble techniques such as Adaboost, Bagging, and Random Subspace Methods. Experimental results show the superiority of proposed ensemble method as compared to its competitors, especially in the presence of class label noise and imbalance classes

AN ASSESSMENT OF SEVERITY LEVEL OF LIVER CIRRHOSIS AND ITS ASSOCIATION WITH PROLONGED QTC INTERVAL

Objective: The primary aim of the research was to find the connection of extended QTC period with the intensity of liver cirrhosis. Material and Methods: The research was performed at Sir Ganga Ram Hospital, Lahore from February to September 2018. Total numbers of patients selected for research are ninety-seven. Results: The number of male and female patients was fifty-three (54.60%) and forty-four (45.40%) respectively. Whereas the average age and time period of the disease are 47.55±10.88 years &1.799±2.131 years respectively. With respect to MELD score, a number of patients (67.01%) was displayed with the temperate disease. Results had displayed extended QTC period (˃450msec) in (54.64%) cases, whereas (45.36%) patients displayed nil QTC period extension, liver cirrhosis intensity was expressively connected with (P-value ˂ 0.001) with extended QTC period. Conclusion: Commonness of extended QTC period in patients of liver cirrhosis was comparatively high and substantially linked with disease intensity. Keywords: Model for End-Stage Liver Disease (MELD), International Normalized Ratio (INR)

Effect of Climate Change on Wheat Productivity

Climate is the average of weather situation in a particular area, which affects all parts of ecosystem. Due to industrialization and urbanization, forests are cutting down and converted into living societies. This change in ecosystem disturbs the balance of ecosystem from decomposers to producers and consumers. Important part of ecosystem is plants (producers) that are energy providers. This alteration affects productivity and sustainability of plants. Wheat is staple food, which is highly affected by temperature and CO2 elevation. It not only affects wheat yield but also make wheat vulnerable to several diseases. High temperature causes a high rate of transpiration, which causes drought that ultimately leads to low productivity. A model was designed on drought conditions and result showed that global warming causes serious drought in 60% of wheat-growing areas of the world. Currently, drought affects 15% of wheat productivity. It was predicted that every 2°C shift of temperature can cause severe water shortage in the coming 20 to 30 years. Water shortage at milking and grain filling stage will affect yield. This chapter includes factors affecting climate, impact on wheat growth, yield, and elevation of carbon dioxide, impact on disease severity, prediction model for temperature rise, and CO2 curve in 2050

Leveraging Ethereum platform for development of efficient tractability system in pharmaceutical supply chain

Consumer knowledge of the goods produced or processed by the numerous suppliers and processors is still relatively low due to the growing complexity of the structure of pharmaceutical supply chains. Information asymmetry in the pharmaceutical sector has an effect on welfare, sustainability, and health. (1) Background: In this respect, we wanted to develop a productive structure for a pharmaceutical supply chain that satisfies the consumer information needs and fosters consumer confidence in the pharmacy goods they buy. By using blockchain technology, the main goals were to develop and implement a pharmaceutical supply chain. (2) Objectives: The main objectives of this work were to leverage an Ethereum platform for the development of a tractability system in a pharmaceutical supply chain environment and to analyze the efficiency of MSMAChain with respect to the cost and execution of transactions based on our designed smart contracts. (3) Results: This research looked into a variety of issues related to the value, viability, and effects of blockchain technology for use in supply chain applications. The methods and creations in this environment were monitored and researched. It is vital to identify a number of crucial subjects including future research areas, in order to achieve the widespread acceptance of the supply chain traceability provided by blockchain technology. (4) Conclusions: MSMAChain, an Ethereum blockchain-based approach, leverages smart contracts and decentralized off-chain storage for efficient product traceability in terms of the cost and execution of transaction for a health care supply chain

The Prevalence, Severity and the Contributive Organizational Factors of Burnout Syndrome among Pakistani Physiotherapists

Background: This is fast age where many underlying health issues go unaddressed in race of progress such as Burnout. This state of mental illness due to chronic stress that may be comprised of emotional exhaustion, personal accomplishment and depersonalization. This is thought to be associated with occupation and organizational parameters. This can put physiotherapist compromised health, social and family life, dealing with patients and low performance at work. Objective: To determine burnout level and its severity among physical therapists and associated organizational factors Material and method: Cross sectional survey was conducted in sample of convenience comprising 120 physiotherapists. The participants were of both gender and age above 25 years. The data was collected by using Maslach Burnout Inventory Scale and data analysis was executed using SPSS version 20. Continuous variables including age, total scores were analyzed for mean and standard deviation, while frequency percentages were calculated against categorical variables. Results: Results of the study demonstrated that mean+SD score for emotional exhaustion was 16.55+ 5.07, mean+SD score for personal accomplishment was 44.73+1.54 and mean+SD score for depersonalization was 0.75+0.93. Conclusion: The study concluded that physiotherapists demonstrated mild to moderate level of burnout. Burnout symptoms apparently found significantly associated with high working hours, private sector, female gender and less physical activity.           &nbsp

IEEE Access special section editorial: scalable deep learning for big data

Deep learning (DL) has emerged as a key application exploiting the increasing computational power in systems such as GPUs, multicore processors, Systems-on-Chip (SoC), and distributed clusters. It has also attracted much attention in discovering correlation patterns in data in an unsupervised manner and has been applied in various domains including speech recognition, image classification, natural language processing, and computer vision. Unlike traditional machine learning (ML) approaches, DL also enables dynamic discovery of features from data. In addition, now, a number of commercial vendors also offer accelerators for deep learning systems (such as Nvidia, Intel, and Huawei)

Resilience and its associated factors in head and neck cancer patients in Pakistan: An analytical cross-sectional study

Introduction: The study aimed to assess resilience and its associated factors in head and neck cancer patients, post-treatment in a low middle income country (LMIC) such as Pakistan.Methods: An analytical cross-sectional study was conducted from November 2019 to May 2020 among head and neck cancer patients aged at least 18 years at the largest private tertiary care hospital, in Karachi, Pakistan. Information regarding their resilience scores was collected through Wagnild and Young\u27s Resilience scale that comprises of 14 items (RS-14). Moreover, depression and anxiety were also assessed via Hospital Anxiety and Depression Scale (HADS) and social support was assessed by Enriched Social Support Instrument (ESSI).Results: The data was analyzed by linear regression modeling. Unadjusted and adjusted beta coefficients with 95% CI were reported. A total of 250 head and neck cancer patients were recruited, 79% of them were males. Mean age of the patients was 51.59 years with 93% having high social support and only 8% having severe depression and 3% having severe anxiety. After adjusting for the covariates in multivariable analysis resilience was associated with severe depression (- 17[- 20.98,-12.93]) or borderline depression (- 4[- 8.41,-0.39]), severe anxiety (- 11 [- 17.88,-4.18]), low social support (- 6[- 9.62,-1.71]), having family members of \u3e 6 in the household (- 2[- 4.31,-0.29), smokeless tobacco users post- treatment (10[5.79, 14.45]), and those who underwent tracheotomy (- 4[- 7.67,-0.21]). There was a significant interaction between education and role in the family (decision maker).Conclusion: In Pakistan, a South Asian LMIC, collectivist culture prevails, family ties are greatly promoted thus resilience and social support is highly prevalent in head and neck cancer patients resulting in lower prevalence of depression and anxiety. Our study highlights that higher resilience is prevalent among small families less than six members, as the welfare of the individual is prioritized over multiple needs of the family. Formal Education and role in household/decision making power are effect modifiers in our study, demonstrating its protective effect on the mental health of head and neck cancer patients. High resilience scores were reported among current smokeless tobacco users as compared to quitters post treatment. Resilience-building interventions should be formulated to aid head and neck cancer patients to cope with the disease and its sequel

A review of virtual reality applications in an educational domain

The use of virtual reality (VR) applications has grown tremendously in recent years. This paper focuses on the review of existing virtual reality applications in higher educational institutions. The VR applications are still not widely used although it helps students learn and enhances their performance. Moreover, some factors that lead to the limited use of virtual reality are lack of communication, delay in technology development, weak acquisition of knowledge, etc. This paper provides a comprehensive overview of virtual reality applications in educational institutions. The reviewed articles are taken from databases such as Science Direct, Ebscohost, and Scopus. Furthermore, the reviewed eighteen articles are published between 2016 and 2021. The study analyzed the reviewed articles based on different factors such as fields, purpose, targets, methods, citations, factors, and limitations. The findings revealed that virtual reality applications could play an essential role in the education domain. The reviewed articles highlighted the significant contribution of virtual reality applications in the education domain and their impact on the students’ performance. Moreover, the study revealed the critical factors used in VR environments, such as ease of use, efficiency, interactive environments, effectiveness, and learning environments