An ambipolar polymer additive for enhanced open circuit voltage in a bulk heterojunction solar cells

Open circuit voltage (V_OC) of organic bulk heterojunction solar cell is extended by the addition of a 20 wt % of F8TBT, an ambipolar polymer in the active layer matrixes (P3HT:PCBM) and then spin casted (1000 rpm/30 s) in the optimized devices on the PEDOT:PSS layer of the ITO glass. A substantial increase in the open circuit voltage from approximately 0.61–0.88 V (44.26%) has been observed with slight increase in efficiency up to 1.91% in the fabricated devices. However, further increment of F8TBT content to 40 wt % reduces the photovoltaic efficiency and affects the J_SC values remarkably, possibly due the excess amount of resistance developed. The enhancement of V_OC is attributed to the ambipolar nature of F8TBT polymer which facilitates the generated electron and hole transfer at the respective electrodes, enhanced π–π* conjugation in polymer matrix, a superior nanoscale separation, and better molecular conformation at the film interface, thus giving an ample opportunities to explore the impact of blending of materials rather than depositing a thin buffer layer by expensive vapor phase technologies. The details of electrical and microstructure characterization of the film were analyzed by AFM, SEM, UV–Vis, J–V characteristics, and EQE techniques. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43042.     

Identifying high perceived value practices of CMMI level 2: An empirical study

ObjectiveIn this paper, we present findings from an empirical study that was aimed at identifying the relative “perceived value” of CMMI level 2 specific practices based on the perceptions and experiences of practitioners of small and medium size companies. The objective of this study is to identify the extent to which a particular CMMI practice is used in order to develop a finer-grained framework, which encompasses the notion of perceived value within specific practices.MethodWe used face-to-face questionnaire based survey sessions as the main approach to collecting data from 46 software development practitioners from Malaysia and Vietnam. We asked practitioners to choose and rank CMMI level 2 practices against the five types of assessments (high, medium, low, zero or do not know). From this, we have proposed the notion of ‘perceived value’ associated with each practice.ResultsWe have identified three ‘requirements management’ practices as having a ‘high perceived value’. The results also reveal the similarities and differences in the perceptions of Malaysian and Vietnamese practitioners with regard to the relative values of different practices of CMMI level 2 process areas.ConclusionsSmall and medium size companies should not be seen as being “at fault” for not adopting CMMI – instead the Software Process Improvement (SPI) implementation approaches and its transition mechanisms should be improved. We argue that research into “tailoring” existing process capability maturity models may address some of the issues of small and medium size companies.     

Statistically correlated multi-task learning for autonomous driving

Neural Computing and Applications - Autonomous driving research is an emerging area in the machine learning domain. Most existing methods perform single-task learning, while multi-task learning...     

Sulphur dioxide loadings over megacity Lahore (Pakistan) and adjoining region of Indo-Gangetic Basin

This article presents spatial and temporal variations of planetary boundary layer (PBL) sulphur dioxide (SO₂) over megacity Lahore and adjoining region, a typical representative area in the Indo-Gangetic Basin (IGB) largely influenced by transported volcanic SO₂ from Africa, Middle East, and southern Europe, by using data retrieved from satellite-based Ozone Monitoring Instrument (OMI) during October 2004–September 2015. We find a positive trend of 2.4% per year (slope 0.01 ± 0.005 with y-intercept 0.35 ± 0.03 Dobson Unit (DU), correlation coefficient r = 0.55 and 2-tailed p-value at 0.1) of OMI-SO₂ column with the average value of 0.4 ± 0.05 DU. Strong seasonality of OMI-SO₂ column is observed over the region linked with local meteorology, patterns of anthropogenic emissions, crop residue burning, and vegetation cover. There exists a seasonal high value in winter 0.56 ± 0.24 DU with a peak in December 0.67 ± 0.26 DU. The seasonal lowest value is observed to be 0.29 ± 0.11 DU in wet summer with minimum value in July 0.25 ± 0.06 DU. High growth rates of OMI-SO₂ column over the study region have been observed in January, June, October, and December ranging from 5.7% to 11.6% per year. Satellite data show elevated OMI-SO₂ columns in 2007, 2008, 2011, and 2012 largely contributed by trans-boundary volcanic SO₂. A detailed analysis of volcanic SO₂ transported from Africa and Middle East (Jabal Al-Tair, Dalaffilla, and Nabro volcanoes) over the study area is presented. Air mass trajectories suggest the presence of long-range transported volcanic SO₂ at high altitude levels over Lahore and IGB region during the volcanic episodes. The SO₂ enhancements in PBL during winter season are generally due to significant vertical downdraft of high-altitude volcanic SO₂. For the first time, we present significant influence of volcanic SO₂ from southern Europe (Mt. Etna volcano) reaching over the study area. Daily mean OMI-SO₂ levels up to 21.4, 10.0, 5.6, and 2.4 DU have been noticed due to the eruptions from Dalaffilla, Mt. Etna, Nabro, and Jabal Al-Tair volcanoes, respectively.     

An image composition algorithm for handling global visual effects

Image composition is widely used in television and film industry to create synthetic visual effects. It requires seamless integration of different parts of two or more images into a single image. Existing image composition techniques only change the local contents of the resulting image while in many cases local changes may also require some global effects as well. For example, if the image of sun from one image is transferred to another image, the global brightness pattern should also be transferred. Unfortunately existing techniques cannot handle global effects of local content manipulations. This paper describes a novel image composition technique which captures global effects associated with a specific local content from one image and incorporates in the second image. In our proposed technique, all images are transformed to the frequency domain. The composite image is created in frequency domain by mixing different frequencies from multiple images and then transformed back to the spatial domain. We have experimented the proposed technique to shift the image of sun along with its global brightness pattern, the global effects of rain and also for transferring global texture pattern from one image to the other. In most of the cases the results produced by our algorithm appear far close to real images than state of the art existing image composition techniques.     

Eliciting information about organizational culture via laddering

Abstract. Eliciting information about organizational culture is an important part of system analysis and design. However, eliciting knowledge of this sort is difficult. Laddering is an established technique that is particularly suitable for eliciting information about goals and for eliciting explanations, which are important issues when investigating organizational culture. This paper describes the method, its strengths and limitations, its use in several case studies and its relation to other elicitation techniques. Recommendations for further work are given.     

Big Data Analytics in Healthcare——A Systematic Literature Review and Roadmap for Practical Implementation

The advent of healthcare information management systems(HIMSs)continues to produce large volumes of healthcare data for patient care and compliance and regulatory requirements at a global scale.Analysis of this big data allows for boundless potential outcomes for discovering knowledge.Big data analytics(BDA)in healthcare can,for instance,help determine causes of diseases,generate effective diagnoses,enhance Qo S guarantees by increasing efficiency of the healthcare delivery and effectiveness and viability of treatments,generate accurate predictions of readmissions,enhance clinical care,and pinpoint opportunities for cost savings.However,BDA implementations in any domain are generally complicated and resource-intensive with a high failure rate and no roadmap or success strategies to guide the practitioners.In this paper,we present a comprehensive roadmap to derive insights from BDA in the healthcare(patient care)domain,based on the results of a systematic literature review.We initially determine big data characteristics for healthcare and then review BDA applications to healthcare in academic research focusing particularly on No SQL databases.We also identify the limitations and challenges of these applications and justify the potential of No SQL databases to address these challenges and further enhance BDA healthcare research.We then propose and describe a state-of-the-art BDA architecture called Med-BDA for healthcare domain which solves all current BDA challenges and is based on the latest zeta big data paradigm.We also present success strategies to ensure the working of Med-BDA along with outlining the major benefits of BDA applications to healthcare.Finally,we compare our work with other related literature reviews across twelve hallmark features to justify the novelty and importance of our work.The aforementioned contributions of our work are collectively unique and clearly present a roadmap for clinical administrators,practitioners and professionals to successfully implement BDA initiatives in their organizations.     

Benchmarking performance of machine and deep learning-based methodologies for Urdu text document classification

Neural Computing and Applications - In order to provide benchmark performance for Urdu text document classification, the contribution of this paper is manifold. First, it provides a publicly...