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Extracting text out of PDF documents is never an easy task when a higher degree of accuracy and consistency are the two main criteria to be attained. Although, there exist a considerable number of such systems; however, most of them are falling short of offering desirable performance especially when academic literature is the concern. Researches, those involved heavily in text mining and project analyzing, need an accurate and consistent supporting tool for PDF-To-Text (PTT) conversion. Therefore, in this paper, we propose a Natural Language Processing based PDF-to-text (NLPDF) conversion system, which comprises of two major steps, namely (i) reads contents from the PDF and (ii) reconstruct the text. The performance of the proposed system is evaluated via four metrics, namely Precision, Recall, F -Measure (AF), and standard deviation, and compared with eight other similar benchmarked systems available in the market. The experimental results evidently demonstrate the effectiveness of the proposed system.

We introduce our efforts within the project ‘The science of deep specification’ to work out the key formal underpinnings of industrial-scale formal specifications of software and hardware components, anticipating a world where large verified systems are routinely built out of smaller verified components that are also used by many other projects. We identify an important class of specification that has already been used in a few experiments that connect strong component-correctness theorems across the work of different teams. To help popularize the unique advantages of that style, we dub itdeep specification, and we say that it encompasses specifications that arerich,two-sided,formalandlive(terms that we define in the article). Our core team is developing a proof-of-concept system (based on the Coq proof assistant) whose specification and verification work is divided across largely decoupled subteams at our four institutions, encompassing hardware microarchitecture, compilers, operating systems and applications, along with cross-cutting principles and tools for effective specification. We also aim to catalyse interest in the approach, not just by basic researchers but also by users in industry.This article is part of the themed issue ‘Verified trustworthy software systems’.

Paper production is a problem with significant importance for society; it is also a challenging topic for scientific investigation. This study is concerned with the simulation of the pressing section of a paper machine. A two-dimensional model is developed to account for the water flow within the pressing zone. A Richards-type equation is used to describe the flow in the unsaturated zone. The dynamic capillary pressure–saturation relation is adopted for the paper production process. The mathematical model accounts for the coexistence of saturated and unsaturated zones in a multilayer computational domain. The discretization is performed by the MPFA-O method. Numerical experiments are carried out for parameters that are typical of the production process. The static and dynamic capillary pressure–saturation relations are tested to evaluate the influence of the dynamic capillary effect.

Splicing the shredded paper means the technology that, according the paper, which has been shredded to design a particular algorithm to splice and recover the original paper. This paper introduced the algorithm of splicing the shredded paper based on the matching to texture feature. By means of this algorithm, we modeled for the problem of splicing the shredded paper and solved it. And, we used the algorithm to splice both pieces of English shredded paper and Chinese shredded paper. The recovered paper had proved the accuracy of the algorithm.

Malaysia is now moving towards becoming a developed nation, targeting on the high-income nation by 2020. In order to execute this intention, Malaysia needs to develop and strengthen the economic growth. Small and Medium Enterprises (SMEs) are acknowledged have a significant role in Malaysian economic growth and expected to contribute 41% of GDP by 2020. However, there are a few factors hinder SMEs to maximize their growth and it has been reported that SMEs contributions to the country’s economy are still comparatively low compared with the contributions of SMEs in many developed and developing countries. Innovation is one of the important factors to remaining competitive in this globalization world. Therefore, SMEs need to focus on innovation activities to increase contribution and remain competitive. Knowledge management is one of the most effective strategies that may help to stimulate innovations and enable innovation activities into the business. Hence, the main aim of this study is to investigate the role of innovation in the relationship between knowledge management practices and SMEs Performance. This study proposed to investigate innovation activities at SMEs manufacturing sector focusing in food and beverages industry. Specifically, innovation types that will be focused in this study are product, process and management innovation. The result hopefully will become an empirical evidence that confirmed innovation is crucial to increase SMEs competitive ability and increase organizational performance. In addition, the result also expectantly prove knowledge management practices have an impact on innovation. Lastly, this study will help Malaysian Government to strategies the policy to overcome difficulties and more importantly in ensuring the sustainability and competitiveness of Malaysian SMEs.

This paper presents a new method for calculating the insulation health index (HI) of oil-paper transformers rated under 110 kV to provide a snapshot of health condition using binary logistic regression. Oil breakdown voltage (BDV), total acidity of oil, 2-Furfuraldehyde content, and dissolved gas analysis (DGA) are singled out in this method as the input data for determining HI. A sample of transformers is used to test the proposed method. The results are compared with the results calculated for the same set of transformers using fuzzy logic. The comparison results show that the proposed method is reliable and effective in evaluating transformer health condition.

We consider a one-dimensional cutting stock problem (CSP) in which the stock widths are not used to fulfill the order but kept for use in the future for the industrial-use paper production. We present a new model based on the flexible stock allocation and trim loss control to determine the production quantity. We evaluate our approach using a real data and show that we are able to solve industrial-size problems, while also addressing common cutting considerations such as aggregation of orders, multiple stock widths, and cutting different patterns on the same machine. In addition, we compare our model with others, including trim loss minimization problem (TLMP) and cutting stock problem (CSP). The results show that the proposed model outperforms the other two models regarding total flexibility and trim loss ratio.

The enormous usage of mobile gadget in this era gives opportunity to use this facility to improve the communication between researchers or students for sharing scientific paper citation data. Users can access easily electronic scientific journal data using their mobile gadget via internet connection. This research proposes to build mobile client-server application based on Android Operating System. Mobile application also equipped with social network feature, where users can share paper citation through Facebook. The integration with social network improves paper dissemination and facilitates collaborative research works between communities or groups on social network.

Tourism is one of the National Key Economic Area (NKEAs) as initiatives to ensure sustainability of growth in Malaysia. One option to increase the national income is through promoting event tourism. Organizing events are highly resource intensive, and can have negative environmental consequences such as waste of water, energy and materials. Therefore, greening of events is critically important to ensure sustainability development in event management by making responsible decisions during planning, organization and implementation of an event. Sustainable event management is the process used to produce events with particular concern for environmental, economic and social issues. Identification of factors that increase the demand for sustainable events would greatly contribute to the country’s NKEAs to improve business services and generate the economy with event tourism. Thus, creating a competitive domestic economy as stated in the country’s Strategic Reform Initiatives (SRIs), by creating more green events using sustainability issues as the main attraction to increase the rate of attendance. The objective of this study is to identify the demand for green events to promote sustainable tourism.

The shift of traditional service perspective to a more transformative service orientation given the rise of customer citizenship behavior thought. This concept considers customers as the citizen instead of a mere service recipient. Derived from organizational citizenship behavior, customer citizenship behavior (CCB) phenomenon led significant research interest among academicians and practitioners in recent years. However, the effect of CCB in relation to online commerce community is yet to be tested. It is obvious that online commerce is spreading day-by-day which became another strong medium of marketing. Existing literature stressed on sharing of knowledge and information among online consumers. However, more importance should be given to understand consumer behavior like CCB. As such, it is utmost necessary to study the behavioral pattern of online commerce community. Furthermore, there is a dearth of study that investigated the elements of social capital (structural, cognitive and relational social capital) in relation to CCB. Such social capital also translates into firm value/profits through congenial customer citizenship behavior. Considering such gaps in the existing literature, the present study aims to propose a conceptual framework highlighting the antecedents and consequence of CCB in the context of online commerce community.

Toner-print removal from paper would allow paper to be re-used instead of being recycled, incinerated or disposed of in landfill. This could significantly reduce the environmental impact of paper production and use. Previous work on the subject has explored the applicability of ultraviolet, visible and infrared (IR) lasers under nanosecond pulses for toner removal. This article expands on this work by testing a wider range of ultrafast and long-pulsed lasers. Results from 10 distinct laser set-ups are used to propose an operating window for the toner-removal process. Colour analysis under the L * a * b * colour space, scanning electron microscope examination and attenuated total reflectance–Fourier transform IR spectroscopy measurements of the outcome show that, with the right laser, it is possible to remove toner from paper to enable its re-use. Theoretical models to predict the laser ablation of toner are discussed, and, while imperfect, provide sufficient evidence to support a physical explanation of toner ablation.

Statistical analysis of various data for the papers published in Journal of Shanghai University (English Edition) from 1997 to 2004 was made. The issues examined include numbers of published papers, disciplinary distribution, constituents of authors, proportions of collaborated papers contributed by multiple authors and papers based on cooperation between different institutions, publishing retardation, and citation of references. Suggestions are made for further improving the quality of the Journal.

Since its coming of age in the mid 1960s, continuum biomechanics has contributed much to our understanding of human health as well as to disease, injury, and their treatment. Nevertheless, biomechanics has yet to reach its full potential as a consistent contributor to the improvement of health–care delivery. Because of the inherent complexities of the microstructure and biomechanical behaviour of biological cells and tissues, there is a need for new theoretical frameworks to guide the design and interpretation of new classes of experiments. Because of continued advances in experimental technology, and the associated rapid increase in information on molecular and cellular contributions to behaviour at tissue and organ levels, there is a pressing need for mathematical models to synthesize and predict observations across multiple length– and time–scales. And because of the complex geometries and loading conditions, there is a need for new computational approaches to solve the boundaryand initial–value problems of clinical, industrial, and academic importance. Clearly, much remains to be done. The purpose of this paper is twofold: to review a few of the many achievements in the biomechanics of soft tissues and the tools that allowed them, but, more importantly, to identify some of the open problems that merit increased attention from those in applied mechanics, biomechanics, mathematics and mechanobiology.

This paper analyzed the drying process of the household gas clothes dryer (GCD) based on the principle of heat and mass transfer. The drying models in three scenarios were established: natural gas burned in combustion chamber, ambient air mixed with exhausted gas in hot gas duct, and clothes were dried in the drying drum. The simulation of the drying process was performed on MATLAB software. And the effectiveness of the drying model was verified by comparison with experiment results. The effects of gas flow rate, dry mass of clothes, ambient temperature, ambient humidity, textile type, and moisture extraction rate (MER) on the performance of dryers were studied. This paper provided a theoretical basis for the design and optimization of GCDs. It was found that the drying time of the gas clothes dryer was mostly affected by the gas flow and dry mass of clothes, and the specific moisture extraction rate (SMER) was mostly affected by the ambient temperature and relative humidity. The nylon clothes have the fastest MER and the smallest SMER. Moreover, reducing operating time in falling-rate drying period can improve energy efficiency.

COVID-19 pandemic has affected all aspects of people's lives and disrupted the economy. Forecasting the number of cases infected with this virus can help authorities make accurate decisions on the interventions that must be implemented to control the pandemic. Investigation of the studies on COVID-19 forecasting indicates that various techniques such as statistical, mathematical, and machine and deep learning have been utilized. Although deep learning models have shown promising results in this context, their performance can be improved using auxiliary features. Therefore, in this study, we propose two hybrid deep learning methods that utilize the statistical features as auxiliary inputs and associate them with their main input. Specifically, we design a hybrid method of the multihead attention mechanism and the statistical features (ATT_FE) and a combined method of convolutional neural network and the statistical features (CNN_FE) and apply them to COVID-19 data of 10 countries with the highest number of confirmed cases. The results of experiments indicate that the hybrid models outperform their conventional counterparts in terms of performance measures. The experiments also demonstrate the superiority of the hybrid ATT_FE method over the long short-term memory model.

Funder: Prince of Wales Global Sustainability Fellowship Programme, Woody biomass could potentially become a viable raw material for the future sustainable chemical industry. For this, a suitable regulatory framework must exist, that would create favourable economic conditions for wood biorefineries. Such policies must be developed on the basis of scientific evidence—in this case, data supporting the environmental advantages of the bio-based feedstocks to the chemical industry. The most suitable methodology for comprehensive evaluation of environmental performance of technologies is life cycle assessment (LCA). In this review, the available LCA studies of woody biomass fractionation and conversion to bulk chemical feedstocks are critically evaluated. It has been revealed that the majority of the openly available studies do not contain transparent inventory data and, therefore, cannot be verified or re-used; studies containing inventory data are reported in this review. The lack of inventory data also prevents comparison between studies of the same processes performed with different evaluation methods or using different system boundaries. Recommendations are proposed on how to overcome issues of commercial data sensitivity by using black-box modelling when reporting environmental information. From several comparable LCA studies, it has been concluded that today the most environmentally favourable technology for wood biomass fractionation is organosolv. This article is part of the theme issue ‘Bio-derived and bioinspired sustainable advanced materials for emerging technologies (part 1)’.

Pulp washing process has the features of multivariate, time delay, nonlinearity. Considering the difficulties of modeling and optimal control in pulp washing process, a data-driven operational-pattern optimization method is proposed to model and optimize the pulp washing process in this paper. The most important quality indexes of pulp washing performance are residual soda in the washed pulp and Baume degree of extracted black liquor. Considering the difficulties of modeling, online measurement of these indexes, two-step neural networks, and multivariate logistic regression are used to establish the prediction models of residual soda and Baume degree. The mathematical model of the washing process can be identified, and the indexes can meet the production requirements. In the target of better product quality, low cost, and low energy consumption, a multiobjective problems is solved by ant colony optimization algorithm based on the optimized operational-pattern database. It shows that the theoretical analyses are correct and the practical applications are feasible, optimization control system has been designed for the pulp washing process, and the practical results show that pulp production increased by 20% and water consumption decreased by nearly 30%. This method is effective in the pulp washing process.

Utilization of coal as a source of electrical energy in the power plant in Indonesia was increased significantly every year, but it can damage the environment if the excessive use of it is not anticipated. This study was conducted by analyzing the potential energy of the corn cobs (CC) in every province. The conducted study is on energy content and ash content of CC. The study shows the potential of the electric energy of CC is available only in 12 provinces that enable for the operation of the power plant with a capacity of 10 MW. However, the waste CC is highly feasible to use as fuel in the power plant because it has a calorific value of about 16.92 MJ/kg which is greater than the calorific value of rice husk around 13.44 MJ/kg and rice straw around 12.56 MJ/kg, and has a ashes around 2.14 % which is very small compared to ashes of rice husk and rice straw which are 19.11% and 18.51%, respectively. The study results are expected to contribute to reducing the use of coal at the power plant.

This paper discusses the science–policy interface, emphasizing the role of evidence and scientific assessments. It then presents the key findings from the UK National Ecosystem Assessment (NEA), which provided much of the evidence for the Natural Environment White Paper for England as a case study. It also influenced the development of the biodiversity strategy for England. The NEA demonstrates the importance of a multi-disciplinary team of experts to prepare and peer review assessments and the importance of input from funding agencies and relevant stakeholder groups in co-designing and reviewing. Much of the text and all of the figures in the NEA section are taken from the Synthesis Report of the NEA, which I drafted as co-chair of the NEA. 1

This paper describes the history and science behind the development of modern flat-panel displays, and assesses future trends. Electronic displays are an important feature of modern life. For many years the cathode ray tube, an engineering marvel, was universal, but its shape was cumbersome and its operating voltage too high. The need for a flat-panel display, working at a low voltage, became imperative, and much research has been applied to this need. Any versatile flat-panel display will exploit an electro-optical effect, a transparent conductor and an addressing system to deliver data locally. The first need is to convert an electrical signal into a visible change. Two methods are available, the first giving emission of light, the second modulating ambient illumination. The most useful light-emitting media are semiconductors, historically exploiting III–V or II–VI compounds, but more recently organic or polymer semiconductors. Another possible effect uses gas plasma discharges. The modulating, or subtractive, effects that have been studied include liquid crystals, electrophoresis, electrowetting and electrochromism. A transparent conductor makes it possible to apply a voltage to an extended area while observing the results. The design is a compromise, since the free electrons that carry current also absorb light. The first materials used were metals, but some semiconductors, when heavily doped, give a better balance, with high transmission for a low resistance. Delivering data unambiguously to a million or so picture elements across the display area is no easy task. The preferred solution is an amorphous silicon thin-film transistor deposited at each cross-point in an X – Y matrix. Success in these endeavours has led to many applications for flat-panel displays, including television, flexible displays, electronic paper, electronic books and advertising signs.

In recent years, modeling and recognizing driver behavior have become crucial to understanding intelligence transport systems, human-vehicle systems, and intelligent vehicle systems. A wide range of both mathematical identification methods and modeling methods of driver behavior are presented from the control point of view in this paper based on the driving data, such as the brake/throttle pedal position and the steering wheel angle, among others. Subsequently, the driver’s characteristics derived from the driver model are embedded into the advanced driver assistance systems, and the evaluation and verification of vehicle systems based on the driver model are described.

Many food processing wastes were generated from traditional operation such as the peeling and coring of fruit. Unwanted material are discarded while primary food are used for further processing. Food processing operation also uses enormous quantities of water which are consequently discharge as a polluted effluent. The waste are contain high concentration of biodegradable organic material and suspended solid. As a result it has a high BOD and extremes of pH conditions. The solid waste from pineapple canning process was estimated about 40–50% from fresh fruit as pineapple peals and cores. Analysis of sugar indicates that liquid waste contains mainly sucrose, glucose and fructose. The waste contains very little nitrogen and soluble protein and elements such as Fe, Ca, Mn, Zn, Cu, Cd, Na and K, and potassium is the highest elements. The sugar content in solid waste was glucose and fructose of 8.24 and 12.17%, no sucrose on this waste. The moisture, nitrogen total, ash, lipid and phosphorus content were 87.5, 0.83, 4.0, 0.15 and 1.0%, respectively.

Utilization of cassava processing waste as animal feed is an attempt waste management. These efforts also support the provision of alternative feed for ruminants on zero waste management system of livestock. Feed processing technology in this study is used to evaluate proximate composition, palatability and feed consumption of cassava peel on local goat. The benefits of this research to provide information about the acceptability of processing cassava peel on local goat. Goats were grouped by weight. Processing cassava peel was used in this study by the ammoniation (T1), fermentation (T2) and the combination of amoniation and fermentation/(amofer (T3). Randomized block design (RBD) in 3 treatments with control (T0, T1, T2, T3) was used to analyze the data. Duncan test was used for further analyse. The results showed that amofer treatment can improve the palatability of cassava peel’s consumption on a local goat. Amofer processing capable to develop proximate composition of cassava peel’s quality compared to ammoniation and fermentation processing. The conclusion recommended amofer processing technology should be used to increase the quality of cassava peel as feed for the livestock. Keywords: Amofer, Palatability, Cassava Peel Processing, Feed Technology, Waste Management.

This position paper observes how different technical and normative conceptions of privacy have evolved in parallel and describes the practical challenges that these divergent approaches pose. Notably, past technologies relied on intuitive, heuristic understandings of privacy that have since been shown not to satisfy expectations for privacy protection. With computations ubiquitously integrated in almost every aspect of our lives, it is increasingly important to ensure that privacy technologies provide protection that is in line with relevant social norms and normative expectations. Similarly, it is also important to examine social norms and normative expectations with respect to the evolving scientific study of privacy. To this end, we argue for a rigorous analysis of the mapping from normative to technical concepts of privacy and vice versa. We review the landscape of normative and technical definitions of privacy and discuss specific examples of gaps between definitions that are relevant in the context of privacy in statistical computation. We then identify opportunities for overcoming their differences in the design of new approaches to protecting privacy in accordance with both technical and normative standards. This article is part of a discussion meeting issue ‘The growing ubiquity of algorithms in society: implications, impacts and innovations’.

The study of composting technique becomes relevant to management of organic waste generated in an undertaking agricultural research. Therefore, this paper aimed to evaluate the efficiency of stabilization of organic matter in two composting systems: controlled (plowings and irrigations fortnightly) and natural. It has been tested two piles (controlled and natural) during 120 days in four treatments: soy straw (T1), wheat straw (T2), tree pruning (T3), mixture of soy and wheat straw and tree pruning (T4) with organic residues from the recycling program + soybeans. There was monitoring of temperature, moisture, pH, electrical conductivity (EC), C, N, C/N ratio and reduction of mass and volume. In the controlled treatments, the thermophilic phase was lower, the moisture was in the ideal ratio for the process (with lower values in the natural treatments), and there was a decrease of 3-4 times of the values of EC and the higher reductions of mass and volume. In all treatments, the values of pH were neutral and the C/N ratio declined 37-50%, assuming final values of matured composts. It has been concluded that regardless of mixtures of waste, the controlled treatments, in the period of 120 days, were more efficient in stabilize the organic material.

The aim of this interdisciplinary approach is to provide innovative solutions to environmental problems, in particular, improving the treatment of textile industrial effluents and finding a use for the residual biomass generated from palm tree (Bactris gasipaes) extraction. Three types of white-rot fungi were cultivated applying different strategies for the decolorization the textile effluents: i) solid-state fermentation (SSF), ii) submerged fermentation (SF), and iii) adsorption. In all cases, it was used the peach-palm residue. In the SSF strategy, the decolorization process and laccase production were enhanced by increasing the concentration of final effluent. Even though the highest decolorization percentage (80%) was attained after 10 days of fermentation with G. lucidum EF 31 applied in the treatment of a final effluent, no significant differences were found in relation to the other two fungi. The decolorization efficiency obtained in the SF was lower compared with SSF, however, the presence of final effluent in the SF process improved the laccase activity. It was noted that the addition of peach-palm residue in this system provides a habitat for the fungus as well as a suitable source material for laccase production with the consequent decolorization of the effluent., This research was supported by the Brazilian Ministry of Science, Technology and Innovation (MCTI) (Grant 402593/2013-8). The authors are grateful to the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Capes) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for scholarships. The author L. B. B. Tavares is the holder of a CNPq fellowship.

Frying oil is one of the major environmental problems in urban centers, causing blockage of sewer pipes and pollution of rivers. Producing biodiesel with frying oil is an alternative to reduce the environmental impacts generated in the undue discarding of the same. Because it has high calorific power, great availability, low emission of pollutants when burned, besides being renewable, which guarantees its uninterrupted supply. This study evaluated the use of diesel blends with biodiesel from frying oil, in proportions varied by 10% for each treatment, ranging from B0 with 0% to B100 with 100% biodiesel, at room temperature and after heating at an average temperature of 50.63°C. The blends were evaluated through measurements of density, viscosity, calorific power and fuel consumption, which were useful for determining the power supplied. Without preheating, there was a gradual increase in fuel consumption, when the percentage of biodiesel in blends increased. However, preheating resulted in a decrease in consumption. Thus, without preheating, there was a low decrease of the power supplied by biodiesel compared to diesel oil. With preheating, this reduction was significantly higher .

Organic chemicals discharged in urban wastewater from industrial and domestic sources, or those entering through atmospheric deposition onto paved areas via surface run-off, are predominantly lipophilic in nature and therefore become concentrated in sewage sludge, with potential implications for the agricultural use of sludge as a soil improver. Biodegradation occurs to varying degrees during wastewater and sludge treatment processes. However, residues will probably still be present in the resulting sludge and can vary from trace values of several micrograms per kilogram up to approximately 1 per cent in the dry solids for certain bulk chemicals, such as linear alkylbenzene sulphonate, which is widely used as a surfactant in detergent formulations. However, the review of the scientific literature on the potential environmental and health impacts of organic contaminants (OCs) in sludge indicates that the presence of a compound in sludge, or of seemingly large amounts of certain compounds used in bulk volumes domestically and by industry, does not necessarily constitute a hazard when the material is recycled to farmland. Furthermore, the chemical quality of sludge is continually improving and concentrations of potentially harmful and persistent organic compounds have declined to background values. Thus, recycling sewage sludge on farmland is not constrained by concentrations of OCs found in contemporary sewage sludges. A number of issues, while unlikely to be significant for agricultural utilization, require further investigation and include: (i) the impacts of chlorinated paraffins on the food chain and human health, (ii) the risk assessment of the plasticizer di(2-ethylhexyl)phthalate, a bulk chemical present in large amounts in sludge, (iii) the microbiological risk assessment of antibiotic-resistant micro-organisms in sewage sludge and sludge-amended agricultural soil, and (iv) the potential significance of personal-care products (e.g. triclosan), pharmaceuticals and endocrine-disrupting compounds in sludge on soil quality and human health.

Tung’s fruits (Aleurites fordii) produce oil of great applicability in the market of painting and covering due to its drying characteristics. Tung’s oil may be an alternative for the production of new biofuels. In this study, it was evaluated the energetic potential of the fruit, oil and biodiesel obtained from the Tung. The average yielding of the extracted seed oil was 50.6%, a value similar to those presented in literature. Moreover, its density presented a value of 931.5 g L-1 and its acid index, 4.5 mg KOH g-1. In the last step of this study, biodiesel was produced by basic methyl route using potassium hydroxide. The specific mass of the produced biodiesel was 909.2 kg m-3 at 20°C; its acid index was 0.473 mg KOH g-1 and its flash point was 178°C. The values of heating values in natura and the low level of ashes in the residual biomass makes the Tung’s fruits a promising renewable clean source of energy of second generation fuel.

Com a realização deste trabalho, objetivou-se avaliar a eficiência do sistema alagado construído, cultivado com aveia preta forrageira (Avena strigosa Schreb), no tratamento de esgoto domestico, efluente de um tanque séptico, com ênfase na remoção de matéria carbonácea, nutrientes (N, P e K) e sódio. O experimento foi conduzido em quatro Sistemas Alagados Construídos (SACs) de escoamento subsuperficial horizontal para tratamento secundário/terciário de esgoto doméstico. Os SACs 1, 2, 3 e 4 receberam, respectivamente, taxas de carregamento orgânico (TCO) de 100; 200; 400 e 600 kg ha -1 dia -1 de DBO. A eficiência média na remoção de DBO, DQO, nitrogênio total, fósforo, sódio e potássio, foram, respectivamente, de 69,5; 70,2; 17,8; 26,2; 14,9 e 16,6%. A baixa eficiência na remoção de nutrientes (N, P e K) foi devida à alta TCO aplicada que proporcionou, também, grande aporte de nutrientes ao sistema. A eficiência de remoção de sódio foi baixa por ser um íon de grande solubilidade e devido à baixa absorção pelas plantas. No geral, menores TCOs proporcionaram maiores remoções de poluente do esgoto doméstico. The objective of the present work was to evaluate the efficiency of a constructed wetland system cultivated with black oat (Avena strigosa Schreb) for the treatment of domestic sewage effluent from a septic tank, with emphasis on removal of carbonaceous matter, nutrients (N, P and K) and sodium. The experiment was conducted in four constructed wetland system (CWS) with horizontal subsurface flow for secondary/tertiary treatment domestic sewage. The CWS 1, 2, 3 and 4 received, respectively, organic load rates (OLR) of 100, 200, 400 and 600 kg ha-1 day-1 of BOD. Average efficiencies for removal of BOD, COD, total nitrogen, phosphorus, sodium and potassium were, respectively, 69.5, 70.2, 17.8, 26.2, 14.9 and 16.6%. Low efficiency in the removal of nutrients (N, P and K) was due a high OLR applied which provided also a large input of nutrients to the system. Sodium removal efficiency was low because it is a highly soluble ion and is poorly absorbed by plants. In general, lower OLR result in greater pollutant removals from the domestic sewage.

This test was conducted to evaluate the performance of an agricultural tractor using a mixture of biodiesel and petroleum diesel. The experiment was conducted at FCAV-Unesp, Jaboticabal, using a 4x2 AFWD tractor with 73.6 kW (100 hp @ 2,300 rpm) of power in the motor, pulling a disk harrow. The biodiesel used was of the ethyl type, filtered, and produced from residual soybean oil. The experimental design was completed randomized in factorial scheme (4x5), with 20 treatments and 4 repetitions, in which 5 ratios of biodiesel and petroleum diesel mixtures were combined (0 and 100%, 25 and 75%, 50 and 50%, 75 and 25% and 100 and 0%), with 4 displacement runs. The analyzed variables were traction bar power, engine rotation and displacement speed. The results evidenced that the mixture ratio (biodiesel and petroleum diesel) did not compromise tractor performance until the limit of 50%.

Cross-flow microfiltration is an attractive alternative method for fluid clarification and sterilization in the brewing industries. The advantages are: elimination of filter aids, reduced beer losses and better product quality. The performance is still limited in flux terms due to membrane fouling. This work aimed to study the mechanism of fouling in beer microfiltration by means of calculating resistances. The experiments were conducted in batch with raw beer, in a cross flow ultrafiltration pilot unit. The membranes were tubular ceramics, with mean pore diameter of 0.2; 0.3; 0.4; 0.6 and 0.8 m and the pressures work were from 1.0 to 4.0 bar, at a temperature of 6±1oC. From the model of resistances in series, the values obtained were of membrane intrinsic resistance, resistances due to polarization of concentration and colmatage.

In this paper, we consider the propagation of waves in an open waveguide in ℝ$^{2}$ where the index of refraction is a local perturbation of a function which is periodic along the axis of the waveguide (which we choose to be the x$_{1}$ axis) and equal to one for |x$_{2}$| > h$_{0}$ for some h$_{0}$ > 0. Motivated by the limiting absorption principle (proven in an earlier paper by the author), we formulate a radiation condition which allows the existence of propagating modes and prove uniqueness, existence, and stability of a solution under the assumption that no bound states exist. In the second part, we determine the order of decay of the radiating part of the solution in the direction of the layer and in the direction orthogonal to it. Finally, we show that it satisfies the classical Sommerfeld radiation condition and allows the definition of a far field pattern.

In this paper, we address the issues of the trade-off between QoS and QoE with an analytical analysis based on mathematical modeling under a unified normalization measurement. We model through computation the awareness of QoS and QoE with a strategy of quality-aware QoE-QoS coordination. A balanced coordination is proposed using modeling correlations between user experience and service performance. The main contributions of this paper include three main parts. First, a comprehensive mapping is modeled in a close form to illustrate the analytic correlations between QoS, QoE, and data communication. Second, an analytical method to analyze and coordinate the nonlinear trade-off between QoE and QoS is proposed based on the theoretical proof with discussions on necessary-sufficient conditions. Third, an algorithmic framework is provided to perform QoE-QoS coordination based on quality-awareness computing with a test proof. An assessment model for user experience quantification is built with the mean opinion score (MOS) test. Quality-aware QoE and QoS models are built based on the subspace learning strategy. Simulations are given to prove the feasibility and effectiveness of the proposed method. The results show that the operations with the proposed solution can be obtained analytically with balanced efficiency in both user experience performance and network performance.

The precision of traditional deformation resistance model is limited, which leads to the inaccuracy of the existing rolling force model. In this paper, the back propagation (BP) neural network model was established according to the industrial big data to accurately predict the deformation resistance. Then, a new rolling force model was established by using the BP neural network model. During the establishment of the neural network model, the data set of deformation resistance was established, which was calculated back from the actual rolling force data. Based on the data set after normalization, the BP neural network model of deformation resistance was established through the optimization of algorithm and network structure. It is shown that both the prediction accuracy of the neural network model on the training set and the test set are high, indicating that the generalization ability of the model is strong. The neural network model of the deformation resistance is compared with the theoretical one, and the maximum error is only 3.96%. Furthermore, by comparison with the traditional rolling force model, it is found that the prediction accuracy of the rolling force model imbedding with the present neural network model is improved obviously. The maximum error of the present rolling force model is just 3.86%. The research in this paper provides a new way to improve the prediction accuracy of rolling force model.

As the essential content of intelligent animal husbandry, identifying each livestock is the only way to achieve modern and refined scientific husbandry. This paper proposes a sheep face recognition method based on European spatial metrics and realizes noncontact sheep identity recognition by training the network using sheep face image samples in the natural environment. The SheepBase data set was first proposed in this process, which contains 6559 images of Inner Mongolia fine-wool sheep and Sunite sheep. To enhance the diversity of the data, the sheep face images were data-enhanced. Secondly, to solve the problems of more redundant information in the sheep face image and the poor posture and angle of the sheep face, we propose the sheep face detection and correction (SheepFaceRepair) method. This method aims to detect the sheep face area in the image to be recognized and align the sheep face area. On this basis, we offer an open sheep facial recognition network (SheepFaceNet) based on the European spatial metric. This method incorporates the biological identity information features of the sheep face to achieve sheep identity. We also tested the effectiveness of this method in the SheepBase data set. The experimental results show that the method proposed in this paper is much higher than the other methods, and the precision of recognition reaches 89.12%. In addition, we found that integrating the biometrics of the sheep face can effectively improve the network’s recognition capacity.