1,430 research outputs found

    Anaerobic Fluidized Bed Treatment of Palm Oil Mill Effluent

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    A 2 m³ pilot scale anaerobic fluidized bed reactor (APBR) was designed, constructed and operated to study its ability to treat high-strength industrial wastewater, at ambient temperature. Besides performance evaluation, kinetic coefficients of three models were determined. Reactor response to pH shock load was also carried out. An early start-up of 17 days was experienced with diluted palm oil mill etlluent (POME) of 2000 mg/l COD. The hydraulic retention time (HRT) was reduced step wise from 24 hr to 4 hr which resulted in volumetric loading rates of 4.0 kgCOD/m³.d to 13.8 kgCOD/m³.d respectively. Maximum COD removal efficiencies achieved at those loading rates were between 65% and 85%. BOD and TSS removal rates were varied in the range of 64% - 91 % and 68% - 89% respectively. The raw substrate was rich in nitrogen nutrients and 17% to 55% of total nitrogen could be removed. Optimum HRT for the COD removal was found to be 1 2 hour, which was much less than that of conventional tank digester system. Reactor performance was found to be a function of loading rate, which decreased steadily with the increased loading rates. The AFBR exhibited low sludge production with sludge volume indices (SVI) of between 11 l/mg and 35 l/mg. General kinetic coefficients for Monod, Contois and Chen & Hashimoto's models were b = 0.23, Y = 0.79, µm = 4.63 and K = 2.47. Specific coefficients for Monod's model were k = 1 .22 and K. = 577, and for Contois' model, B = 0.05 and µm = 0.86. The pilot plant exhibited good buffering ability when pH shock load of 5.0 was imposed on the AFBR

    Machining Strategies Exploring Reduction in Energy Consumption

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    The main aim of this thesis is to explore machining strategies, analyzing energy consumption using Design of Experiments (DOE) at the material removal rate (MRR), compare to cutting geometrical trajectories according to CNC parameters such as spindle RPM, feed rate, depth of cut per pass and total depth of cut. Spindle RPM, depth of cut per pass, and feed rate are selected as the main three factors and each factor has two levels: low-level (-) and high-level (+). These experiments have been performed at an end-milling machine by using a concept of a constant volume of material removal processes in the circular and linear geometrical slots in pine wood blocks. Standard energy logger equipment has used to measure energy consumption during end-milling operation. Different statistical analysis, such as ANOVA, regression line, and cause & effect diagram have used to show different energy consumption results in the material removal process. At the end the of data analysis, it is found that a significant amount of electricity demand is associated with machining pre-cutting & post-cutting stage and this significant amount of electricity demand is defined as peripheral energy. This peripheral energy is not involved in the actual performance of material removal process in the end-milling process. In the [Figure 11] end-milling process has been involved with pine wood blocks at constant volume of material removal (2.8 cubic inch) process. Results can be varied using of hard material removal process, such as steel & aluminum metals

    Shrimp-prawn farming in Bangladesh : impacts on livelihoods, food and nutritional security

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    The overarching aim of this research was to improve understanding of the synergies and trade-offs between economic and domestic food security benefits associated export-oriented shrimp and prawn aquaculture in a fragile developing country environmental context. The research scope covers the entire ‘seafood system’ incorporating production, distribution, trading and consumption in the south-west coastal region under greater Khulna District, Bangladesh. The primary research objective was to understand causal factors in variation of seafood nutritional quality and health outcomes, exploring correlations with seafood consumption across a range of agro-ecological, aquatic farming systems and socio-economic conditions. The study also focused on differences in intra-household allocation with a special focus on adolescent girls, being amongst the most vulnerable members of society. These objectives necessitated a highly inter-disciplinary approach to understand complex interactions between biophysical aspects (e.g. where and which species are most effective in supplying essential nutrients) and the social norms of food allocation. Fieldwork was conducted in Satkhira, Khulna, and Bagerhat Districts of Khulna Province over 17 months during 2012 to 2015. Four villages across a peak-annual surface water salinity gradient; high saline (>10 ppt), medium saline (>5<10 ppt), low saline (<5 ppt) and freshwater (<0.5 ppt) were selected for case-studies. The thesis begins with a literature review of the evolution of shrimp and prawn farming in Bangladesh and the wider region and identification of knowledge gaps. Research resolved from district to community to household level. Key informant (KI) interviews were used to establish well-being criteria (based on a range of 5 social and economic assets) at community level. In each community a census of households (n=1082 households) were derived from the same interviews and KIs asked to ranked households on the established well-being criteria. Results were validated through a short interview of all the identified households (HH). This sample-frame provided the based for two concurrent survey efforts. Stratified-random selection of 160 HH on two well-being categories (better-off and worse-off) for ‘farm level’ analysis using a semi-structured questionnaire. Key topics included inputs/outputs characteristics, economic benefits and the fate of farmed products were evaluated. Another 240 households with single adolescent girls were selected from the same frame, again with randomized-stratified sampling based on well-being categories for ‘intra-household’ analysis. This resulted in selection of 60 HH per community consisting of 30 ‘better-off’ and 30 worse-off households (further analysis was conducted on a range of secondary sampling outcomes based on livelihood options, intra-household food distribution and aquatic farming assets). A 24-hour food recall method, food frequency questionnaire, food photography and measuring cup sets were used to estimate individual members’ food consumption at the household level. Anthropometric measures (stunting, wasting, BMI, MUAC) and biomarkers (omega-3 index in RBC and LC n-3 PUFA/LC PUFA in whole blood cell) were used to assess food security outcomes of adolescent girls (n=200 subject). In an entirely separate effort, samples of shrimp/prawn and fish polyculture species (57 species and 9 by-products, 1 live feed; n=672) were collected from the major agro-ecologies (four saline gradients; HS, MS, LS and FW) and culture systems (extensive, semi-intensive, intensive, organic and pocket gher). At least 3 sites from each saline gradient (3×4=12 sites) were selected for sampling and pooled samples to represent all the culture system in the region. The major macro and micronutrients of the collected species were analysed and these datasets were used to know the nutritional distribution among the family members in household level study. Two aggregate indices of wealth (or well-being) and aquaculture were developed based on a range of quantitative (ordinal and interval) measures. Principle Component Analysis (PCA) was used to understand how aquaculture influences on wealth gain. Wealth index of the same social well-being did not differ among the agro-ecologies. However, the aquaculture index was varied in agro-ecologies. Most of the households (60-80%) were involved directly in aquaculture however, a majority portion of the households was worse-off (48-64%). Both HS and LS area had more livelihood options due to their proximity to mangrove forest Sundarbans and city amenities, respectively compared to MS and FW area. Ownership of the land did not influence any involvement in aquaculture and yields but he willingness and risk-absorbing capacity of the farmers were the main factor to get involve in aqauculture. In aquatic farming system the importance of export-oriented shellfish yield gradually decreased from HS to FW area (55-20% by volume). The intentional stocking of finfish and PLs were common across the saline areas however the wild caught juveniles and hatchery originated fingerlings were usual in higher and lower saline areas, respectively. The low priced tilapia took the place of wild recruited mangrove fishes in MS area. Diseases, especially the devastating white spot virus (WSSV), frequency were higher in higher saline areas. The indicators like wild recruitment, salinity, water productivity and water management also a vital factor to gain yield. The integration of aquatic and terrestrial crops (rice and dyke crop) in the lower saline areas provide higher yield compared to higher saline areas. However, the net economic returns were largely determined by the aquatic products. The income of ghers in FW and MS area was sensitive to the lower prices of freshwater finfish and tilapia. The protein content in shellfish was higher than the other finfish, however, lower in other essential nutrients. Species living in the higher saline areas contained higher total n-3 PUFA (in weight) and LC n-3 PUFA/LC-PUFA compared to the same species living in lower saline areas. Small Indigenous Species (SIS) and Self-Recruiting Species (SRS) were proven to provide higher micronutrients and total n-3 PUFA than larger fish. Seafood that destined for the international markets contained less n-3 PUFA and micronutrients in comparison to the domestically consumed fish. Customary intra-household food distribution disparity (mainly fish) still exists at household levels where females, especially adolescent girls, were deprived. Fish consumption (>77 g /capita/day) and fish originated protein supply (>25% of total protein intake) was higher than the other part of Bangladesh. The protein consumption of adolescents was 2-3 times higher than the Recommended Nutritional Intake (RNI). However, the energy intake was lower than the required level. High protein, low energy consumption was not reflected in body mass. Micronutrients (zinc) consumption was above the RNI level. However, iron and calcium consumption was less than the RNI. The n-3 PUFA in RBC of adolescent girls accurately reflected their access to, and availability of, oily fish. In the omega-3 index (n-3 PUFA in red blood cell) both HS and MS areas, adolescent females were in the intermediate stage (4-8%), and rest of the two areas were in the undesirable stage (<4%). The n-3 LC-PUFA was around 20-30% of total LC-PUFA content in whole blood and gradually decreased from higher saline to lower saline areas. The thesis concludes that the gher based aquatic animal farming in S-W Bangladesh is a dynamic system operated by both rich and poor. The salinity level and the presence of mangrove forest make the farming system dynamic. The holistic scenario suggested aquaculture in ghers is a family driven small scale polyculture where varieties of aquatic foods are produced both for global and local value chain. Higher amounts of valued products (both in terms of nutrition and price), less disease susceptibility, more alternative livelihood options both in HS and LS were found in better position than the other two sites, however the nutritional content of fish and its manifestation in adolescents strongly mirrors agro-ecologies irrespective of social position of households. The thesis provides an important, grounded importance of the system and the linkage of the community people for livelihoods, food production and food security. The dynamic systems were understood and effective messages formulated for the policy makers. In doing so, the thesis contributes to an understanding of how small-scale polyculture equally benefited local food security and macroeconomic growth of a developing country

    Effect of Grain Size and Interface Engineering on the Photovoltaic Performance and Stability of Perovskite Solar Cells

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    Organic-inorganic halide perovskite solar cells (PSCs) have grown rapidly in recent years due to their outstanding optoelectronic properties, high efficiency, and low-cost. However, this emerging solar cell technology is experiencing some challenges such as defects, hysteresis, and long-term stability, which need to be addressed in order to make it commercially available. This dissertation aims to assist in overcoming some of the barriers and is therefore important to the field of perovskite solar cells. Initially, this dissertation focuses on investigating the role of grain interiors (GIs) and grain boundaries (GBs) of perovskite film using chemically, spatially, and temporally resolved measurements at the nanoscale level. It is shown that, the GBs are defective with deeper defect levels and are unfavorable to the high performance of perovskite solar cells. Therefore, larger grain perovskite film can be considered as a plausible solution for better quality perovskite films. This work leads to a novel deconvoluted PL approach to determine the charge carrier dynamics of the GI and the GB of the perovskite film. We have quantitatively demonstrated that the charge carrier dynamics of the GI and GB can be analyzed from the ordered and disordered phase of the asymmetric PL spectrum observed in the perovskite film. This deconvoluted PL approach is simple, rapid, non-destructive, and requires no sample preparation compared with the currently available nanoscale characterization measurements. Subsequently, this dissertation describes the interface defect passivation between perovskite and the electron transport layer (ETL). To address this, a novel thin film of PCBM/carbon was introduced as ETL in the device architecture, which reduces the interface defects and increases the conductivity compared with that of the competitive ETL of PCBM/C60. Moreover, carbon is abundant in nature and the use of carbon in perovskite solar cells will reduce the manufacturing cost. Finally, the limitation of the air instability of perovskite film is investigated. For that, an in-depth study of degradation pathways of the perovskite film in air was performed using optical, crystallographic, morphological, and mechanical measurements. Based on this study, we suggest the modification of perovskite device architecture to improve the stability of perovskite solar cells in air

    AI-enabled modeling and monitoring of data-rich advanced manufacturing systems

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    The infrastructure of cyber-physical systems (CPS) is based on a meta-concept of cybermanufacturing systems (CMS) that synchronizes the Industrial Internet of Things (IIoTs), Cloud Computing, Industrial Control Systems (ICSs), and Big Data analytics in manufacturing operations. Artificial Intelligence (AI) can be incorporated to make intelligent decisions in the day-to-day operations of CMS. Cyberattack spaces in AI-based cybermanufacturing operations pose significant challenges, including unauthorized modification of systems, loss of historical data, destructive malware, software malfunctioning, etc. However, a cybersecurity framework can be implemented to prevent unauthorized access, theft, damage, or other harmful attacks on electronic equipment, networks, and sensitive data. The five main cybersecurity framework steps are divided into procedures and countermeasure efforts, including identifying, protecting, detecting, responding, and recovering. Given the major challenges in AI-enabled cybermanufacturing systems, three research objectives are proposed in this dissertation by incorporating cybersecurity frameworks. The first research aims to detect the in-situ additive manufacturing (AM) process authentication problem using high-volume video streaming data. A side-channel monitoring approach based on an in-situ optical imaging system is established, and a tensor-based layer-wise texture descriptor is constructed to describe the observed printing path. Subsequently, multilinear principal component analysis (MPCA) is leveraged to reduce the dimension of the tensor-based texture descriptor, and low-dimensional features can be extracted for detecting attack-induced alterations. The second research work seeks to address the high-volume data stream problems in multi-channel sensor fusion for diverse bearing fault diagnosis. This second approach proposes a new multi-channel sensor fusion method by integrating acoustics and vibration signals with different sampling rates and limited training data. The frequency-domain tensor is decomposed by MPCA, resulting in low-dimensional process features for diverse bearing fault diagnosis by incorporating a Neural Network classifier. By linking the second proposed method, the third research endeavor is aligned to recovery systems of multi-channel sensing signals when a substantial amount of missing data exists due to sensor malfunction or transmission issues. This study has leveraged a fully Bayesian CANDECOMP/PARAFAC (FBCP) factorization method that enables to capture of multi-linear interaction (channels × signals) among latent factors of sensor signals and imputes missing entries based on observed signals

    Multiclass Classification of Risk Factors for Cervical Cancer Using Artificial Neural Networks

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    World Health Organization statistics show that cervical cancer is the fourth most frequent cancer in women with an estimated 530,000 new cases in 2012. Cervical cancer diagnosis typically involves liquid-based cytology (LBC) followed by a pathologist review. The accuracy of decision is therefore highly influenced by the expert’s skills and experience, resulting in relatively high false positive and/or false negative rates. Moreover, given the fact that the data being analyzed is highly dimensional, same reviewer’s decision is inherently affected by inconsistencies in interpreting the data. In this study, we use an Artificial Neural Network based model that aims to considerably reduce experts’ inconsistencies in predicting cervical cancer. We rely on standard machine learning techniques to train the neural network using six experts’ predictions for cervical cancer (based on analysis of more than sixty parameters/risk factors) and we produce a model where the unanimous decision is predicted with very good accuracy
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