Barriers factor of ISO 9001:2015 implementation in the manufacturing industry of Pakistan

The ISO 9001 certification increases the willingness of companies to satisfy customer needs and consumers may rely on reliability good quality products. ISO 9000 is one of the most successful projects that originated from the quality revolution of the 1980s. Quality techniques of ISO 9001: 2015 are known as highest standards in the world including Pakistan. Manufacturing industries play an important role in developing and increasing Gross Domestic Production in Pakistan. Pakistan's manufacturing industries have become very competitive and complex. It has been observed that Pakistan’s manufacturing industries are lacking the implementation of the ISO 9001:2015. The study aimed to identify the factors which hinder the implementation of ISO 9001 in the manufacturingindustry of Pakistan and to formulate solutions for the identified issues. A literature review was carried out and twenty-seven factors were found hindering the implementation of ISO 9001:2015 recorded from previous research. Based on the identified factors, a questionnaire was developed and used for further evaluation. The respondents for this survey were from the 239 top managerial post of the manufacturing industry as shown in Appendix-E. Statistical analysis was conducted by using mean value which resulted in eleven significant factors shortlisted. After identification of significant factors, semi-structured questionnaire was carried out among stakeholders having experience of more than 15 years in manufacturing industries for the recommendation of implementation of ISO 9001:2015. The results of semi-structured questionnaire helped recommendations for the implementation of ISO that is relevant to manufacturing industries in Pakistan. This research would be helpful for managerial staff to effectively implement the ISO 9001:2015 in the manufacturing industry of Pakistan

Oral cancer via the bargain bin : the role of smokeless tobacco in the etiology of oral cancer

Background: Oral cancer combined with the other cancers of the head and neck region constitute the sixth most common cancer in the world. Oral cancer is a major public health challenge in South Asia. Pakistan, India, Bangladesh and Sri Lanka have some of the highest incidence and prevalence rates of oral cancer in the world. Approximately 16,000 new cases of oral cancer are diagnosed each year in Pakistan and around 6,000 Pakistanis lose their lives to this malignancy every year. There is a disconnect between the research findings from the developed countries and the developing countries, with regards to the risk of oral cancer associated with smokeless tobacco use. Given the differences in the composition of the smokeless tobacco products used in different parts of the world, it is imperative that the health risks related with each of these products are assessed on an individual basis. Methods: A case-control study was carried out in the Khyber Pakhtunkhwa province of Pakistan from September 2014 until May 2015, to quantify the risk of oral cancer associated with the use of Naswar (smokeless tobacco). Additionally, three systematic reviews (including meta-analyses) of observational studies and two narrative reviews were carried out to address the secondary objectives of this dissertation. Results: We found an increased risk of oral cancer associated with the use of smokeless tobacco products in South Asia. The use of smokeless tobacco was also associated with an elevated risk of oral potentially malignant disorders. In Khyber Pakhtunkhwa, Pakistan, Ever-users of Naswar had a 21-fold increase in the risk of oral cancer compared to Never-users Odds ratio (OR) =21.2 (95% Confidence Interval (CI), (8.4-53.8) . An elevated risk of oral cancer associated with Naswar use was found among both women and men. The risk of oral cancer increased with the increasing frequency, total duration, and the intensity of Naswar use. 70% of the oral cancer burden of Khyber Pakhtunkhwa was attributable to Naswar. Discussion: The findings of the systematic reviews and the case-control study on Naswar are comparable to the existing literature. The results clearly demonstrate a high risk of oral cancer and related disorders, associated with the use of smokeless tobacco products like Naswar, Betel quid, and Gutkha. There is a lack of oral cancer research in Pakistan and the tobacco control policies of the country largely focus on tobacco smoking while neglecting smokeless tobacco. In order to tackle the growing burden of oral cancer in South Asia in general and Pakistan in particular, policies need to be in place to curb the use of smokeless tobacco products. These products need to be regulated and brought under the tobacco tax-net. Changes to the composition of these products, to make them less harmful to health, should also be looked into as an intervention

Multispectral Palmprint Encoding and Recognition

Palmprints are emerging as a new entity in multi-modal biometrics for human identification and verification. Multispectral palmprint images captured in the visible and infrared spectrum not only contain the wrinkles and ridge structure of a palm, but also the underlying pattern of veins; making them a highly discriminating biometric identifier. In this paper, we propose a feature encoding scheme for robust and highly accurate representation and matching of multispectral palmprints. To facilitate compact storage of the feature, we design a binary hash table structure that allows for efficient matching in large databases. Comprehensive experiments for both identification and verification scenarios are performed on two public datasets -- one captured with a contact-based sensor (PolyU dataset), and the other with a contact-free sensor (CASIA dataset). Recognition results in various experimental setups show that the proposed method consistently outperforms existing state-of-the-art methods. Error rates achieved by our method (0.003% on PolyU and 0.2% on CASIA) are the lowest reported in literature on both dataset and clearly indicate the viability of palmprint as a reliable and promising biometric. All source codes are publicly available.Comment: Preliminary version of this manuscript was published in ICCV 2011. Z. Khan A. Mian and Y. Hu, "Contour Code: Robust and Efficient Multispectral Palmprint Encoding for Human Recognition", International Conference on Computer Vision, 2011. MATLAB Code available: https://sites.google.com/site/zohaibnet/Home/code

Multiphysics Modelling of Energy Storage Devices Using Pore Scale Approaches

The advancement in high-resolution X-ray tomography image acquisition techniques has enabled imaged-based modelling of pore-scale transport processes to better understand structural performance relationship in porous media. The porous components in electrochemical energy storage devices such as lithium-ion batteries, fuel cell and redox flow batteries are subject to intense research to maximize performance and hence reduce the cost of energy storage systems. The image-based pore-scale modelling approaches such as direct numerical simulation (DNS) are, however, very computationally expensive and it gets infeasible to simulate a representative element volume of porous structure on a standard workstation or laptop machine. Pore network modelling (PNM) approach has been previously used to simulate large size porous domains of fuel cell and redox flow batteries at substantially lower computational cost, however, its application in lithium-ion batteries has not been attempted due to the multiphysics and transient nature of transport mechanism involved during charging and discharging process. Lithium-ion batteries are considered as the top candidate for electrochemical energy storage, so modelling their structure-performance relationship at less computational cost will enable development of efficient numerical pore network modelling framework. Therefore, this thesis aims towards developing pore network modelling framework for lithium-ion batteries to study the impact of microstructure on multiphysics transport processes occurring inside battery electrodes. The development of lithium-ion battery pore network model requires enhancements in the current implementation of pore network modelling algorithms. For example, current pore network extraction algorithms only extract a single phase from a tomography image (usually the pores). On the other hand, lithium-ion battery electrodes contain three phases, namely active material (e.g. NMC), carbon binder, and electrolyte filled void phase. To resolve this issue, multiphase pore network extraction algorithms were developed that connect any two phases via interconnections. This allowed investigating inter- and intra-phase transport processes between phases which are common in lithium-ion battery. The extraction algorithms were tested on random sphere packings and three-phase lithium-ion battery cathode and found to agree well with experimental data and DNS model. Computational performance of PNM model was also compared with other modelling approaches and found to give appreciable performance gain on large size porous domains, while yielding similar or equivalent results.Although modelling of transport process using the PNM approach is computationally efficient, extracting pore networks from tomography images is a computationally expensive task. Also, image resolution plays a vital role to determine the relative accuracy of extracted geometrical properties and hence simulation accuracy. To remove these bottlenecks, an efficient, parallelized network extraction technique was developed that enabled pore network extraction from massive size images. A geometric domain decomposition technique was adopted to reduce the computational cost of extraction. The network extraction was observed 7 times faster and consumed 50% less RAM when used in parallel and serial mode respectively. Finally, a case study was performed to reduce the effect of resolution during pore network extraction. This enabled more reliable extracted pore networks for pore network modelling studies. Finally, pore network modelling of lithium-ion batteries cathodes was performed to study galvanostatic discharge behaviour of half-cells. A massive reduction in computational cost was observed when compared with DNS approach. The structural features of two electrodes were investigated to understand the performance-structural relationship. Also, particle-to-particle and pore-to-pore analysis was performed to analyze the state of lithiation, solid-phase potential distribution and lithium-ion concentration distribution, electrolyte phase potential distribution in solid and electrolyte phase respectively. The study enabled modelling of large size lithium-ion electrodes to analyze the impact of internal microstructure on the overall performance of the cell. The presented work in this thesis is focused on developing, validating, and applying a pore network modelling framework for lithium-ion battery discharge. It has enabled the study of structural performance relationship of battery electrodes on a particle to particle basis without estimating effective transport properties using empirical or experimental data. The excellent computational performance of PNMs has allowed multiphysics modelling on standard workstation or laptop with minimal computational resources. Although developed for lithium-ion battery cathodes the developed framework can be used for any anode structure or study thermal performance-structure relationship as well

Compliance of smokeless tobacco supply chain actors and products with tobacco control laws in Bangladesh, India and Pakistan: Protocol for a multicentre sequential mixed-methods study

Introduction: South Asia is home to more than 300 million smokeless tobacco (ST) users. Bangladesh, India and Pakistan as signatories to the Framework Convention for Tobacco Control (FCTC) have developed policies aimed at curbing the use of tobacco. The objective of this study is to assess the compliance of ST point-of-sale (POS) vendors and the supply chain with the articles of the FCTC and specifically with national tobacco control laws. We also aim to assess disparities in compliance with tobacco control laws between ST and smoked tobacco products.Methods and analysis: The study will be carried out at two sites each in Bangladesh, India and Pakistan. We will conduct a sequential mixed-methods study with five components: (1) mapping of ST POS, (2) analyses of ST samples packaging, (3) observation, (4) survey interviews of POS and (5) in-depth interviews with wholesale dealers/suppliers/manufacturers of ST. We aim to conduct at least 300 POS survey interviews and observations, and 6-10 in-depth interviews in each of the three countries. Data collection will be done by trained data collectors. The main statistical analysis will report the frequencies and proportions of shops that comply with the FCTC and local tobacco control policies, and provide a 95% CI of these estimates. The qualitative in-depth interview data will be analysed using the framework approach. The findings will be connected, each component informing the focus and/or design of the next component.Ethics and dissemination: Ethical approvals for the study have been received from the Health Sciences Research Governance Committee at the University of York, UK. In-country approvals were taken from the National Bioethics Committee in Pakistan, the Bangladesh Medical Research Council and the Indian Medical Research Council. Our results will be disseminated via scientific conferences, peer-reviewed research publications and press releases

A featureless approach for object detection and tracking in dynamic environments

One of the challenging problems in mobile robotics is mapping a dynamic environment for navigating robots. In order to disambiguate multiple moving obstacles, state-of-art techniques often solve some form of dynamic SLAM (Simultaneous Localization and Mapping) problem. Unfortunately, their higher computational complexity press the need for simpler and more efficient approaches suitable for real-time embedded systems. In this paper, we present a ROS-based efficient algorithm for constructing dynamic maps, which exploits the spatial-temporal locality for detecting and tracking moving objects without relying on prior knowledge of their geometrical features. A two-prong contribution of this work is as follows: first, an efficient scheme for decoding sensory data into an estimated time-varying object boundary that ultimately decides its orientation and trajectory based on the iteratively updated robot Field of View (FoV); second, lower time-complexity of updating the dynamic environment through manipulating spatial-temporal locality available in the object motion profile. Unlike existing approaches, the snapshots of the environment remain constant in the number of moving objects. We validate the efficacy of our algorithm on both V-Rep simulations and real-life experiments with a wide array of dynamic environments. We show that the algorithm accurately detects and tracks objects with a high probability as long as sensor noise is low and the speed of moving objects remains within acceptable limits

Future of Oral Proteomics

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