Search results for: accurate planning of production

Authors: Christopher Viens, Bosko Gajic, Steve Krase

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Stick-Slip is a term that is often overused and commonly diagnosed from surface drilling parameters of torque and differential pressure, but the actual magnitude of the condition is rarely captured at the BHA level as the necessary measurements are seldom deployed. Deployment of an accurate stick-slip measurement downhole has led to an interesting discovery that goes against long held traditional drilling lore. A divide has been identified between stick-slip as independent bit and BHA conditions. This phenomenon in horizontal laterals is common, but few M/LWD systems have been able to capture it. Utilizing measurements of downhole RPM bore pressure, high-speed magnetometer data, bending moment, and continuous inclination, the wellbore spiraling phenomenon is able to be captured, quantified, and intimately tied back to systematic effects of BHA stalling and micro-sliding. An operator in the Permian Basin has identified that this phenomenon is contributing to increased tortuosity and drag. Utilizing downhole torque measurements the root causes of the stick-slip and spiraling phenomenon were identified and able to engineered out of the system.

Keywords: bending moment, downhole dynamics measurements, micro sliding, wellbore spiraling

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Authors: Devesh Motwani, Ranjana S. Baruah

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The prime incentive behind up gradation of heavy oil is to increase its API gravity for ease of transportation to refineries, thus expanding the market access of bitumen-based crude to the refineries. There has always been a demand for an integrated approach that aims at simplifying the upgrading scheme, making it adaptable to the production site in terms of economics, environment, and personnel safety. Recent advances in nanotechnology have facilitated the development of two lines of heavy oil upgrading processes that make use of nano-catalysts for producing upgraded oil: In Situ Upgrading and Field Upgrading. The In-Situ upgrading scheme makes use of Hot Fluid Injection (HFI) technique where heavy fractions separated from produced oil are injected into the formations to reintroduce heat into the reservoir along with suspended nano-catalysts and hydrogen. In the presence of hydrogen, catalytic exothermic hydro-processing reactions occur that produce light gases and volatile hydrocarbons which contribute to increased oil detachment from the rock resulting in enhanced recovery. In this way the process is a combination of enhanced heavy oil recovery along with up gradation that effectively handles the heat load within the reservoirs, reduces hydrocarbon waste generation and minimizes the need for diluents. By eliminating most of the residual oil, the Synthetic Crude Oil (SCO) is much easier to transport and more amenable for processing in refineries. For heavy oil reservoirs seriously impacted by the presence of aquifers, the nano-catalytic technology can still be implemented on field though with some additional investments and reduced synergies; however still significantly serving the purpose of production of transportable oil with substantial benefits with respect to both large scale upgrading, and known commercial field upgrading technologies currently on the market. The paper aims to delve deeper into the technology discussed, and the future compatibility.

Keywords: upgrading, synthetic crude oil, nano-catalytic technology, compatibility

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Authors: Anselm Ego Onyimonyi, Maduako Johnpaul O.

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The study was designed to investigate into the socio-ecological impact of migration of Fulani herders in Anambra state of Nigeria, through a climate justice lens. Nigeria is one of the world’s most densely populated countries with a population of over 284 million people, half of which are considered to be in abject poverty. There is no doubt that livestock production provides sustainable contributions to food security and poverty reduction to Nigeria economy, but not without some environmental implications like any other economic activities. Nigeria is recognized as being vulnerable to climate change. Climate change and global warming if left unchecked will cause adverse effects on livelihoods in Nigeria, such as livestock production, crop production, fisheries, forestry and post-harvest activities, because the rainfall regimes and patterns will be altered, floods which devastate farmlands would occur, increase in temperature and humidity which increases pest and disease would occur and other natural disasters like desertification, drought, floods, ocean and storm surges, which not only damage Nigerians’ livelihood but also cause harm to life and property, would occur. This and other climatic issue as it affects Fulani herdsmen was what this study investigated. In carrying out this research, a survey research design was adopted. A simple sampling technique was used. One local government area (LGA) was selected purposively from each of the four agricultural zone in the state based on its predominance of Fulani herders. For appropriate sampling, 25 respondents from each of the four Agricultural zones in the state were randomly selected making up the 100 respondent being sampled. Primary data were generated by using a set of structured 5-likert scale questionnaire. Data generated were analyzed using SPSS and the result presented using descriptive statistics. From the data analyzed, the study indentified; Unpredicted rainfall (mean = 3.56), Forest fire (mean = 4.63), Drying Water Source (mean = 3.99), Dwindling Grazing (mean 4.43), Desertification (mean = 4.44), Fertile land scarcity (mean = 3.42) as major factor predisposing Fulani herders to migrate southward while rejecting Natural inclination to migrate (mean = 2.38) and migration to cause trouble as a factor. On the reason why Fulani herders are trying to establish a permanent camp in Anambra state; Moderate temperature (mean= 3.60), Avoiding overgrazing (4.42), Search for fodder and water (mean = 4.81) and (mean = 4.70) respectively, Need for market (4.28), Favorable environment (mean = 3.99) and Access to fertile land (3.96) were identified. It was concluded that changing climatic variables necessitated the migration of herders from Northern Nigeria to areas in the South were the variables are most favorable to the herders and their animals.

Keywords: socio-ecological, migration, fulani, climate, justice, lens

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Authors: Dmytro Symak

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Drying is a complex technologic, thermal and energy process. Energy cost of drying processes in many cases is the most costly stage of production, and can be over 50% of total costs. As we know, in Ukraine over 85% of Portland cement is produced moist, and the finished product energy costs make up to almost 60%. During the wet cement production, energy costs make up over 5500 kJ / kg of clinker, while during the dry only 3100 kJ / kg, that is, switching to a dry Portland cement will allow result into double cutting energy costs. Therefore, to study raw materials drying process in the manufacture of Portland cement is very actual task. The fine ferrous materials drying (small pyrites, red mud, clay Kyoko) is recommended to do by filtration method, that is one of the most intense. The essence of filtration method drying lies in heat agent filtering through a stationary layer of wet material, which is located on the perforated partition, in the "layer-dispersed material - perforated partition." For the optimum drying purposes, it is necessary to establish the dependence of pressure loss in the layer of dispersed material, and the values of heat and mass transfer, depending on the speed of the gas flow filtering. In our research, the experimentally determined pressure loss in the layer of dispersed material was generalized based on dimensionless complexes in the form and coefficients of heat exchange. We also determined the relation between the coefficients of mass and heat transfer. As a result of theoretic and experimental investigations, it was possible to develop a methodology for calculating the optimal parameters for the thermal agent and the main parameters for the filtration drying installation. The comparison of calculated by known operating expenses methods for the process of small pyrites drying in a rotating drum and filtration method shows to save up to 618 kWh per 1,000 kg of dry material and 700 kWh during filtration drying clay.

Keywords: drying, cement, heat and mass transfer, filtration method

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Authors: Alok Kumar, Raviraj Patil

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The ability to respond to an incident of a disastrous event in a vulnerable area is very crucial an aspect of emergency management. The ability to constantly predict the likelihood of an event along with its severity in an area and react to those significant events which are likely to have a high impact allows the authorities to respond by allocating resources optimally in a timely manner. It provides for measuring, monitoring, and modeling facilities that integrate underlying systems into one solution to improve operational efficiency, planning, and coordination. We were particularly involved in this innovative incubation work on the current state of research and development in collaboration. technologies & systems for a disaster.

Keywords: predictive analytics, advanced analytics, area flood likelihood model, area flood severity model, level of impact model, mortality score, economic loss score, resource allocation, crew allocation

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Authors: Hamdy M. Youssef, Eman A. Al-Lehaibi

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Due to many applications and problems in the fields of plasma physics, geophysics, and other many topics, the interaction between the strain field and the magnetic field has to be considered. Adomian introduced the decomposition method for solving linear and nonlinear functional equations. This method leads to accurate, computable, approximately convergent solutions of linear and nonlinear partial and ordinary differential equations even the equations with variable coefficients. This paper is dealing with a mathematical model of generalized thermoelasticity of a half-space conducting medium. A magnetic field with constant intensity acts normal to the bounding plane has been assumed. Adomian’s decomposition method has been used to solve the model when the bounding plane is taken to be traction free and thermally loaded by harmonic heating. The numerical results for the temperature increment, the stress, the strain, the displacement, the induced magnetic, and the electric fields have been represented in figures. The magnetic field, the relaxation time, and the angular thermal load have significant effects on all the studied fields.

Keywords: Adomian’s decomposition method, magneto-thermoelasticity, finite conductivity, iteration method, thermal load

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Authors: Muhammad Azam, Micheal Olaolu Arowolo, Fei He, Mihail Popescu, Dong Xu

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The number of biological papers is growing quickly, which means that the number of biological pathway figures in those papers is also increasing quickly. Each pathway figure shows extensive biological information, like the names of genes and how the genes are related. However, manually annotating pathway figures takes a lot of time and work. Even though using advanced image understanding models could speed up the process of curation, these models still need to be made more accurate. To improve gene name recognition from pathway figures, we applied a Siamese network to map image segments to a library of pictures containing known genes in a similar way to person recognition from photos in many photo applications. We used a triple loss function and a triplet spatial pyramid pooling network by combining the triplet convolution neural network and the spatial pyramid pooling (TSPP-Net). We compared VGG19 and VGG16 as the Siamese network model. VGG16 achieved better performance with an accuracy of 93%, which is much higher than OCR results.

Keywords: biological pathway, image understanding, gene name recognition, object detection, Siamese network, VGG

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Authors: Altaf H. Khan, Frank Stenger, Mohammed A. Hussein, Reaz A. Chaudhuri, Sameera Asif

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This paper discusses a novel approach to approximate quadrature integrals that arise in the estimation of likelihood parameters for the generalized linear mixed models (GLMM) as well as Bayesian methodology also requires computation of multidimensional integrals with respect to the posterior distributions in which computation are not only tedious and cumbersome rather in some situations impossible to find solutions because of singularities, irregular domains, etc. An attempt has been made in this work to apply Sinc function based quadrature rules to approximate intractable integrals, as there are several advantages of using Sinc based methods, for example: order of convergence is exponential, works very well in the neighborhood of singularities, in general quite stable and provide high accurate and double precisions estimates. The Sinc function based approach seems to be utilized first time in statistical domain to our knowledge, and it's viability and future scopes have been discussed to apply in the estimation of parameters for GLMM models as well as some other statistical areas.

Keywords: generalized linear mixed model, likelihood parameters, qudarature, Sinc function

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Authors: Chaoran Liu

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Bioactive polysaccharides and polysaccharide-protein complex derived from mushrooms and fungi have a wide range of immunomodulatory activity with low side-effects and have therefore the potential to be developed as an adjuvant in cancer therapies. Mushrooms sclerotium is rich in polysaccharides and the polysaccharides isolated from the sclerotium of Polyporus rhinocerus have shown potent in vivo and in vitro immunomodulatory effects. Macrophages are considered to be an important component of the innate immune response against bacterial infection and cancer. To better understanding the immunomodulatory effects and its underlying mechanisms of sclerotial water-soluble polysaccharides extracted from P. rhinocerus on macrophages, the objectives of this study are to purify the water-soluble novel sclerotial polysaccharides and to characterize the structure and properties as well as to study the detailed molecular mechanisms of the in vitro immunomodulating effects in murine macrophages. The hot water-soluble fraction PRW from the sclerotium of P. rhinocerus was obtained using solvent extraction. PRW was further fractionated by membrane ultrafiltration to a give a fraction (PRW1) with molecular mass less than 50 kDa. PRW1 was characterized to be a polysaccharide-protein complex composed of 45.7% polysaccharide and 44.2% protein. The chemical structure of the carbohydrate moiety of PRW1 was elucidated by GC and FTIR to be mainly beta-D-glucan with trace amount of galactose and mannose. The immunomodulatory effects of PRW1 on murine RAW 264.7 macrophages were demonstrated in terms of the increase in nitric oxide production and cytokine production. Mechanistically, PRW1 initiates ERK phosphorylation to activate macrophages within 15 min and significantly improves the expression level of inducible NOS (iNOS) from 6 h after treatment. In summary, this study indicates that PRW1 is a potent immunomodulatory agent for macrophages and suggests that mushroom sclerotia from Polyporus rhinocerus requires for further investigation in cancer research.

Keywords: Polyporus rhinocerus, mushroom sclerotia, Polysaccharide-Protein Complex, macrophage activation

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Authors: Anung Style Bukhori, Ani Dijah Rahajoe

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Poverty poses a significant challenge in Indonesia, requiring an effective analytical approach to understand and address this issue. In this research, we applied the Naïve Bayes classification method to examine and classify poverty data in Indonesia. The main focus is on classifying data using RapidMiner, a powerful data analysis platform. The analysis process involves data splitting to train and test the classification model. First, we collected and prepared a poverty dataset that includes various factors such as education, employment, and health..The experimental results indicate that the Naïve Bayes classification model can provide accurate predictions regarding the risk of poverty. The use of RapidMiner in the analysis process offers flexibility and efficiency in evaluating the model's performance. The classification produces several values to serve as the standard for classifying poverty data in Indonesia using Naive Bayes. The accuracy result obtained is 40.26%, with a moderate recall result of 35.94%, a high recall result of 63.16%, and a low recall result of 38.03%. The precision for the moderate class is 58.97%, for the high class is 17.39%, and for the low class is 58.70%. These results can be seen from the graph below.

Keywords: poverty, classification, naïve bayes, Indonesia

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Authors: I. Stathopoulos, V. Syrgiamiotis, E. Karavasilis, A. Ploussi, I. Nikas, C. Hatzigiorgi, K. Platoni, E. P. Efstathopoulos

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Introduction: Brain and central nervous system (CNS) tumors form the second most common group of cancer in children, accounting for 30% of all childhood cancers. MRI is the key imaging technique used for the visualization and management of pediatric brain tumors. Initial characterization of tumors from MRI scans is usually performed via a radiologist’s visual assessment. However, different brain tumor types do not always demonstrate clear differences in visual appearance. Using only conventional MRI to provide a definite diagnosis could potentially lead to inaccurate results, and so histopathological examination of biopsy samples is currently considered to be the gold standard for obtaining definite diagnoses. Machine learning is defined as the study of computational algorithms that can use, complex or not, mathematical relationships and patterns from empirical and scientific data to make reliable decisions. Concerning the above, machine learning techniques could provide effective and accurate ways to automate and speed up the analysis and diagnosis for medical images. Machine learning applications in radiology are or could potentially be useful in practice for medical image segmentation and registration, computer-aided detection and diagnosis systems for CT, MR or radiography images and functional MR (fMRI) images for brain activity analysis and neurological disease diagnosis. Purpose: The objective of this study is to provide an automated tool, which may assist in the imaging evaluation and classification of brain neoplasms in pediatric patients by determining the glioma type, grade and differentiating between different brain tissue types. Moreover, a future purpose is to present an alternative way of quick and accurate diagnosis in order to save time and resources in the daily medical workflow. Materials and Methods: A cohort, of 80 pediatric patients with a diagnosis of posterior fossa tumor, was used: 20 ependymomas, 20 astrocytomas, 20 medulloblastomas and 20 healthy children. The MR sequences used, for every single patient, were the following: axial T1-weighted (T1), axial T2-weighted (T2), FluidAttenuated Inversion Recovery (FLAIR), axial diffusion weighted images (DWI), axial contrast-enhanced T1-weighted (T1ce). From every sequence only a principal slice was used that manually traced by two expert radiologists. Image acquisition was carried out on a GE HDxt 1.5-T scanner. The images were preprocessed following a number of steps including noise reduction, bias-field correction, thresholding, coregistration of all sequences (T1, T2, T1ce, FLAIR, DWI), skull stripping, and histogram matching. A large number of features for investigation were chosen, which included age, tumor shape characteristics, image intensity characteristics and texture features. After selecting the features for achieving the highest accuracy using the least number of variables, four machine learning classification algorithms were used: k-Nearest Neighbour, Support-Vector Machines, C4.5 Decision Tree and Convolutional Neural Network. The machine learning schemes and the image analysis are implemented in the WEKA platform and MatLab platform respectively. Results-Conclusions: The results and the accuracy of images classification for each type of glioma by the four different algorithms are still on process.

Keywords: image classification, machine learning algorithms, pediatric MRI, pediatric oncology

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Authors: Faiqa Jalal

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The purpose of the following research paper is to discuss the differentiating meanings of culture and how popular culture has maintained a great impact on intercultural and international behavior. The following discussion leads to the notion of communicating cultural impact on behavior through advertising and sub-cultural theory in advertising. Although towards the end of the research, the complexities that develop through the above discussion, lead to the solution that ‘advertising gives meaning to the otherwise meaningless and identical objects through linking them to our basic needs’. In today’s fast paced digital world, it is difficult to define culture, literally, since its meaning tends to shift through series of different perceptions such as ‘how’ and ‘why’ it should be used. This notion can be taken towards another notion of popular culture. It is dependent on ‘attitudes, ideas, images, perspectives and other phenomena within the mainstream of a given culture’. Since popular culture is influenced by mass media, it has a way of influencing an individual’s attitude towards certain topics. For example, tattoos are a form of human decorations, that have historic significance, and a huge spectrum of meanings. Advertising is one aspect of marketing that has evolved from the time when it was ‘production oriented’, up till the time it started using different mediums to make its impact more effective. However, this impact has confused us between our needs and desires. The focus in this paper is ‘we consume to acquire a sense of social identity and status, not just for the sake of consumption’. Every culture owns different expressions, which are then used by advertisers to create its impact on the behavior of people sub-culturally and globally, as culture grows through social interaction. Advertisers furthermore play a smart role in highlighting quality of life ranging from ‘survival to well-being’. Hence, this research paper concludes by highlighting that culture is considered as a ‘basic root’ of any community that also provides solution to certain problems; however, advertisers play their part in manipulating society’s literacy and beliefs by rationalizing how relevant certain products/brands are to their beliefs.

Keywords: mass media, popular culture, production oriented, sub-culture

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Authors: Dharmendra Pratap

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Large Cardamom (Amomum subulatum), family Zingiberaceae is an aromatic spice crop and has rich medicinal value. Large Cardamom is as synonymous to Sikkim as Tea is to Darjeeling. Since Sikkim alone contributes up to 88% of India's large cardamom production which is the world leader by producing over 50% of the global yield. However, the production of large cardamom has declined almost to half since last two decade. The economic losses have been attributed to two viral diseases namely, chirke and Foorkey. Chirke disease is characterized by light and dark green streaks on leaves. The affected leaves exhibit streak mosaic, which gradually coalesce, turn brown and eventually dry up. Excessive sprouting and formation of bushy dwarf clumps at the base of mother plants that gradually die characterize the foorkey disease. In our surveys in Sikkim–Darjeeling hill area during 2012-14, 40-45% of plants were found to be affected with foorkey disease and 10-15% with chirke. Mechanical and aphid transmission study showed banana as an alternate host for both the disease. For molecular identification, total genomic DNA and RNA was isolated from the infected leaf tissues and subjected to Rolling circle amplification (RCA) and RT-PCR respectively. The DNA concatamers produced in the RCA reaction were monomerized by different restriction enzymes and the bands corresponding to ~1 kb genomes were purified and cloned in the respective sites. The nucleotide sequencing results revealed the association of Nanovirus with the foorkey disease of large cardamom. DNA1 showed 74% identity with Replicase gene of FBNYV, DNA2 showed 77% identity with the NSP gene of BBTV and DNA3 showed 74% identity with CP gene of BBTV. The finding suggests the presence of a new species of nanovirus associated with foorkey disease of large cardamom in Sikkim and Darjeeling hills. The details of their epidemiology and other factors would be discussed.

Keywords: RCA, nanovirus, large cardamom, molecular virology and microbiology

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Authors: Mohamed A. Abou-Shouk, Mahamoud M. Hewedi

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This study extends technology acceptance model (TAM) to investigate the antecedents and consequences of social media adoption by tourists and travel agents. It compares their perceptions on social media adoption and its consequences. Online survey was addressed to tourists and travel agents for data collection purposes. Structural equation modelling was employed for analysis purposes. The findings revealed that the majority of tourists and travel agents involved in the study believe in the usefulness of social media adoption for travel planning and marketing purposes. They agree that adopting social media could change the attitude of tourists towards specific destination or attraction and influence their purchasing decisions. This study contributes to knowledge by extending TAM and provides some managerial implication to marketers.

Keywords: TAM, social media, travel and tourism, travel agents

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Authors: Daina Jonkus, Solvita Petrovska, Dace Smiltina, Lasma Cielava

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The beta-lactoglobulin and kappa-casein are milk proteins which are important for milk composition. Cows with beta-lactoglobulin and kappa-casein gene BB genotypes have highest milk crude protein and fat content. The aim of the study was to determinate the frequencies of milk protein gene polymorphisms in local Latvian Brown (LB) cows breed and analyze the influence of beta-lactoglobulin and kappa-casein genotypes to milk productivity traits. 102 cows’ genotypes of milk protein genes were detected using Polymerase Chain Reaction and Restriction Fragment Length Polymorphism (PCR-RFLP) and electrophoresis on 3% agarose gel. For beta-lactoglobulin were observed 2 types of alleles A and B and for kappa-casein 3 types: A, B and E. Highest frequency in beta-lactoglobulin gene was observed for B allele – 0.926. Molecular analysis of beta-lactoglobulin gene shows 86.3% of individuals are homozygous by B allele and animals are with genotypes BB and 12.7% of individuals are heterozygous with genotypes AB. The highest milk yield 4711.7 kg was for 1st lactation cows with AB genotypes, whereas the highest milk protein content (3.35%) and fat content (4.46 %) was for BB genotypes. Analysis of the kappa-casein locus showed a prevalence of the A allele – 0.750. The genetic variant of B was characterized by a low frequency – 0.240. Moreover, the frequency of E occurred in the LB cows’ population with very low frequency – 0.010. 54.9 % of cows are homozygous with genotypes AA, and only 4.9 % are homozygous with genotypes BB. 32.8 % of individuals are heterozygous with genotypes AB, and 2.0 % are with AE. The highest milk productivity was for 1st lactation cows with AB genotypes: milk yield 4620.3 kg, milk protein content 3.39% and fat content 4.53 %. According to the results, in local Latvian brown there are only 2.9% of cows are with BB-BB genotypes, which is related to milk coagulation ability and affected cheese production yield. Acknowledgment: the investigation is supported by VPP 2014-2017 AgroBioRes Project No. 3 LIVESTOCK.

Keywords: beta-lactoglobulin, cows, genotype frequencies, kappa-casein

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Authors: Md. Z. Alam, Amal A. Elgharbawy, Muhammad Moniruzzaman, Nassereldeen A. Kabbashi, Parveen Jamal

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The enzymatic hydrolysis of lignocellulosic biomass is one of the obstacles in the process of sugar production, due to the presence of lignin that protects the cellulose molecules against cellulases. Although the pretreatment of lignocellulose in ionic liquid (IL) system has been receiving a lot of interest; however, it requires IL removal with an anti-solvent in order to proceed with the enzymatic hydrolysis. At this point, introducing a compatible cellulase enzyme seems more efficient in this process. A cellulase enzyme that was produced by Trichoderma reesei on palm kernel cake (PKC) exhibited a promising stability in several ILs. The enzyme called PKC-Cel was tested for its optimum pH and temperature as well as its molecular weight. One among evaluated ILs, 1,3-diethylimidazolium dimethyl phosphate [DEMIM] DMP was applied in this study. Evaluation of six factors was executed in Stat-Ease Design Expert V.9, definitive screening design, which are IL/ buffer ratio, temperature, hydrolysis retention time, biomass loading, cellulase loading and empty fruit bunches (EFB) particle size. According to the obtained data, IL-enzyme system shows the highest sugar concentration at 70 °C, 27 hours, 10% IL-buffer, 35% biomass loading, 60 Units/g cellulase and 200 μm particle size. As concluded from the obtained data, not only the PKC-Cel was stable in the presence of the IL, also it was actually stable at a higher temperature than its optimum one. The reducing sugar obtained was 53.468±4.58 g/L which was equivalent to 0.3055 g reducing sugar/g EFB. This approach opens an insight for more studies in order to understand the actual effect of ILs on cellulases and their interactions in the aqueous system. It could also benefit in an efficient production of bioethanol from lignocellulosic biomass.

Keywords: cellulase, hydrolysis, lignocellulose, pretreatment

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Authors: Firas M. Tuaimah, Huda M. Abdul Abbas

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Accurate Short Term Load Forecasting (STLF) is essential for a variety of decision making processes. However, forecasting accuracy can drop due to the presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. Interval Type 2 Fuzzy Logic System (IT2 FLS), with additional degrees of freedom, gives an excellent tool for handling uncertainties and it improved the prediction accuracy. The training data used in this study covers the period from January 1, 2012 to February 1, 2012 for winter season and the period from July 1, 2012 to August 1, 2012 for summer season. The actual load forecasting period starts from January 22, till 28, 2012 for winter model and from July 22 till 28, 2012 for summer model. The real data for Iraqi power system which belongs to the Ministry of Electricity.

Keywords: short term load forecasting, prediction interval, type 2 fuzzy logic systems, electric, computer systems engineering

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Authors: Dawit Abay Tesfamariam

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Ethiopia’s Climate- Resilient Green Economy (ECRGE) strategy focuses mainly on generating and proper utilization of renewable energy (RE). Nonetheless, the current electricity generation of the country is dominated by hydropower. The data collected in 2016 by Ethiopian Electric Power (EEP) indicates that the intermittent RE sources from solar and wind energy were only 8 %. On the other hand, the EEP electricity generation plan in 2030 indicates that 36.1 % of the energy generation share will be covered by solar and wind sources. Thus, a case study was initiated to model and compute the balance and consumption of electricity in three different scenarios: 2016, 2025, and 2030 using the EnergyPLAN Model (EPM). Initially, the model was validated using the 2016 annual power-generated data to conduct the EnergyPLAN (EP) analysis for two predictive scenarios. The EP simulation analysis using EPM for 2016 showed that there was no significant excess power generated. Thus, the EPM was applied to analyze the role of energy storage in RE in Ethiopian grid systems. The results of the EP simulation analysis showed there will be excess production of 402 /7963 MW average and maximum, respectively, in 2025. The excess power was in the three rainy months of the year (June, July, and August). The outcome of the model also showed that in the dry seasons of the year, there would be excess power production in the country. Consequently, based on the validated outcomes of EP indicates, there is a good reason to think about other alternatives for the utilization of excess energy and storage of RE. Thus, from the scenarios and model results obtained, it is realistic to infer that if the excess power is utilized with a storage system, it can stabilize the grid system and be exported to support the economy. Therefore, researchers must continue to upgrade the current and upcoming storage system to synchronize with potentials that can be generated from renewable energy.

Keywords: renewable energy, power, storage, wind, energy plan

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Authors: Janusz Bedkowski, Grzegorz Kisala, Michal Wlasiuk, Piotr Pokorski

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Ground-truth data is essential for VO (Visual Odometry) and SLAM (Simultaneous Localization and Mapping) quantitative evaluation using e.g. ATE (Absolute Trajectory Error) and RPE (Relative Pose Error). Many open-access data sets provide raw and ground-truth data for benchmark purposes. The issue appears when one would like to validate Visual Odometry and/or SLAM approaches on data captured using the device for which the algorithm is targeted for example mobile phone and disseminate data for other researchers. For this reason, we propose an open source, open hardware groundtruth system that provides an accurate and precise trajectory with a 3D point cloud. It is based on LiDAR Livox Mid-360 with a non-repetitive scanning pattern, on-board Raspberry Pi 4B computer, battery and software for off-line calculations (camera to LiDAR calibration, LiDAR odometry, SLAM, georeferencing). We show how this system can be used for the evaluation of various the state of the art algorithms (Stella SLAM, ORB SLAM3, DSO) in typical indoor monocular VO/SLAM.

Keywords: SLAM, ground truth, navigation, LiDAR, visual odometry, mapping

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Authors: Camila Penido Gomes

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Over the past decade, an emerging body of research has been pointing to artificial intelligence´s great potential to improve the use of open data, increase transparency and curb corruption in the public sector. Nonetheless, studies on this subject are scant and usually lack evidence to validate AI-based technologies´ effectiveness in addressing corruption, especially in developing countries. Aiming to fill this void in the literature, this paper sets out to examine how AI has been deployed by civil society to improve the use of open data and prevent congresspeople from misusing public resources in Brazil. Building on the current debates and carrying out a systematic literature review and extensive document analyses, this research reveals that AI should not be deployed as one silver bullet to fight corruption. Instead, this technology is more powerful when adopted by a multidisciplinary team as a civic tool in conjunction with other strategies. This study makes considerable contributions, bringing to the forefront discussion a more accurate understanding of the factors that play a decisive role in the successful implementation of AI-based technologies in anti-corruption efforts.

Keywords: artificial intelligence, civil society organization, corruption, open data, transparency

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Authors: Fauzi Jarushi, Sinan Mohsin AlKaabi

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The Standard Penetration Test (SPT) is the most common insitu test for soil investigations. On the other hand, the Cone Penetration Test (CPT) is considered one of the best investigation tools. Due to the fast and accurate results that can be obtained it complaints the SPT in many applications like field explorations, design parameters, and quality control assessments. Many soil index and engineering properties have been correlated to both of SPT and CPT. Various foundation design methods were developed based on the outcome of these tests. Therefore it is vital to correlate these tests to each other so that either one of the tests can be used in the absence of the other, especially for preliminary evaluation and design purposes. The primary purpose of this study was to investigate the relationships between the SPT and CPT for different types of soil in Florida. Data for this research were collected from number of projects sponsored by the Florida Department of Transportation (FDOT), six sites served as the subject of SPT-CPT correlations. The correlations were established between the cone resistance (qc) and the SPT blows (i.e., N) for various soils. A positive linear relationship was found between fs and N for various soils. In general, qc versus N showed higher correlation coefficients than fs versus N. qc/N ratios were developed for different soil types and compared to literature values, the results of this research revealed higher ratios than literature values.

Keywords: in situ tests, correlation, SPT, CPT

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Authors: Reza Zakerinejad

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Gully erosion is a serious problem that threading the sustainability of agricultural area and rangeland and water in a large part of Iran. This type of water erosion is the main source of sedimentation in many catchment areas in the north of Iran. Since in many national assessment approaches just qualitative models were applied the aim of this study is to predict the spatial distribution of gully erosion processes by means of detail terrain analysis and GIS -based logistic regression in the loess deposition in a case study in the Golestan Province. This study the DEM with 25 meter result ion from ASTER data has been used. The Landsat ETM data have been used to mapping of land use. The TreeNet model as a stochastic modeling was applied to prediction the susceptible area for gully erosion. In this model ROC we have set 20 % of data as learning and 20 % as learning data. Therefore, applying the GIS and satellite image analysis techniques has been used to derive the input information for these stochastic models. The result of this study showed a high accurate map of potential for gully erosion.

Keywords: TreeNet model, terrain analysis, Golestan Province, Iran

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Authors: Ghaleb Y. Abbasi, Israa Abu Rumman

Abstract:

This paper modeled sales history archived from 2012 to 2015 bulked in monthly bins for five products for a medical supply company in Jordan. The sales forecasts and extracted consistent patterns in the sales demand history from the Enterprise Resource Planning (ERP) system were used to predict future forecasting and generate sales demand forecasting using time series analysis statistical technique called Auto Regressive Integrated Moving Average (ARIMA). This was used to model and estimate realistic sales demand patterns and predict future forecasting to decide the best models for five products. Analysis revealed that the current replenishment system indicated inventory overstocking.

Keywords: ARIMA models, sales demand forecasting, time series, R code

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Authors: Rabia Shabbir, Sheikh Saeed Ahmad, Amna Butt

Abstract:

Rapid land use changes have taken place in Islamabad, the capital city of Pakistan, over the past decades due to accelerated urbanization and industrialization. In this study, land use changes in the metropolitan area of Islamabad was observed by the combined use of GIS and satellite remote sensing for a time period of 15 years. High-resolution Google Earth images were downloaded from 2000-2015, and object-based classification method was used for accurate classification using eCognition software. The information regarding urban settlements, industrial area, barren land, agricultural area, vegetation, water, and transportation infrastructure was extracted. The results showed that the city experienced a spatial expansion, rapid urban growth, land use change and expanding transportation infrastructure. The study concluded the integration of GIS and remote sensing as an effective approach for analyzing the spatial pattern of urban growth and land use change.

Keywords: land use change, urban growth, Islamabad, object-based classification, Google Earth, remote sensing, GIS

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Authors: Thembelihle Portia Lubisi, Malusi Ntandoyenkosi Mkhize, Jonas Kalebe Johakimu

Abstract:

Fertilizers play an important role in maintaining the productivity and quality of plants. Inorganic fertilizers (containing nitrogen, phosphorus, and potassium) are largely used in South Africa as they are considered inexpensive and highly productive. When applied, a portion of the excess fertilizer will be retained in the soil, a portion enters water streams due to surface runoff or the irrigation system adopted. Excess nutrient from the fertilizers entering the water stream eventually results harmful algal blooms (HABs) in freshwater systems, which not only disrupt wildlife but can also produce toxins harmful to humans. Use of agro-chemicals such as pesticides and herbicides has been associated with increased antimicrobial resistance (AMR) in humans as the plants are consumed by humans. This resistance of bacterial poses a threat as it prevents the Health sector from being able to treat infectious disease. Archaeological studies have found that pyrolysis liquids were already used in the time of the Neanderthal as a biocide and plant protection product. Pyrolysis is thermal degradation process of plant biomass or organic material under anaerobic conditions leading to production of char, bio-oils and syn gases. Bio-oil constituents can be categorized as water soluble (wood vinegar) and water insoluble fractions (tar and light oils). Wood vinegar (pyro-ligneous acid) is said to contain contains highly oxygenated compounds including acids, alcohols, aldehydes, ketones, phenols, esters, furans, and other multifunctional compounds with various molecular weights and compositions depending on the biomass material derived from and pyrolysis operating conditions. Various researchers have found the wood vinegar to be efficient in the eradication of termites, effective in plant protection and plant growth, has antibacterial characteristics and was found effective in inhibiting the micro-organisms such as candida yeast, E-coli, etc. This study investigated characterisation of South African forestry product processing waste with intention of evaluating the potential of using the respective biomass waste as feedstock for boil oil production via pyrolysis process. Ability to use biomass waste materials in production of wood-vinegar has advantages that it does not only allows for reduction of environmental pollution and landfill requirement, but it also does not negatively affect food security. The biomass wastes investigated were from the popular tree types in KZN, which are, pine saw dust (PSD), pine bark (PB), eucalyptus saw dust (ESD) and eucalyptus bark (EB). Furthermore, the research investigates the possibility of mixing the different wastes with an aim to lessen the cost of raw material separation prior to feeding into pyrolysis process and mixing also increases the amount of biomass material available for beneficiation. A 50/50 mixture of PSD and ESD (EPSD) and mixture containing pine saw dust; eucalyptus saw dust, pine bark and eucalyptus bark (EPSDB). Characterisation of the biomass waste will look at analysis such as proximate (volatiles, ash, fixed carbon), ultimate (carbon, hydrogen, nitrogen, oxygen, sulphur), high heating value, structural (cellulose, hemicellulose and lignin) and thermogravimetric analysis.

Keywords: characterisation, biomass waste, saw dust, wood waste

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Authors: Aghbalou Nihad, Charki Abderafi, Saida Rahali, Reklaoui Kamal

Abstract:

Maximize the benefit from the wind energy potential is the most interest of the wind power stakeholders. As a result, the wind tower size is radically increasing. Nevertheless, choosing an appropriate wind turbine for a selected site require an accurate estimate of vertical wind profile. It is also imperative from cost and maintenance strategy point of view. Then, installing tall towers or even more expensive devices such as LIDAR or SODAR raises the costs of a wind power project. Various models were developed coming within this framework. However, they suffer from complexity, generalization and lacks accuracy. In this work, we aim to investigate the ability of neural network trained using the Bayesian Regularization technique to estimate wind speed profile up to height of 100 m based on knowledge of wind speed lower heights. Results show that the proposed approach can achieve satisfactory predictions and proof the suitability of the proposed method for generating wind speed profile and probability distributions based on knowledge of wind speed at lower heights.

Keywords: bayesian regularization, neural network, wind shear, accuracy

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Authors: Samuel Ahamefula

Abstract:

Turbulent motion is a highly nonlinear and complex phenomenon, and its modelling is still very challenging. In this study, we developed a hybrid computational approach to accurately simulate fluid turbulence phenomenon. The focus is coupling and transitioning between Direct Numerical Simulation (DNS) and Large Eddy Simulating Wall Models (LES-WM) regions. In the framework, high-order fidelity fluid dynamical methods are utilized to simulate the unsteady compressible Navier-Stokes equations in the Eulerian format on the unstructured moving grids. The coupling and transitioning of DNS and LES-WM are conducted through the linearly staggered Dirichlet-Neumann coupling scheme. The high-fidelity framework is verified and validated based on namely, DNS ability for capture full range of turbulent scales, giving accurate results and LES-WM efficiency in simulating near-wall turbulent boundary layer by using wall models.

Keywords: computational methods, turbulence modelling, turbulence entropy, navier-stokes equations

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Authors: A. A. Saki, Y. Karimi, H. J. Najafabadi, P. Zamani, Z. Mostafaie

Abstract:

The restaurant residuals reasons such as competition between human and animal consumption of cereals, increasing environmental pollution and the high cost of production of livestock products is important. Therefore, in this restaurant residuals have a high nutritional value (protein and high energy) that it is possible can replace some of the poultry diets are especially Japanese quail. Today, the challenges of processing and consumption of these lesions occurring in modern industry would be confronting. Increasing costs, pressures, and problems associated with waste excretion, the need for re-evaluation and utilization of waste to livestock and poultry feed fortifies. This study aimed to investigate the effects of different levels of restaurant residuals on performance of 300 layer Japanese quails. This experiment included 5 treatments, 4 replicates, and 15 quails in each from 10 to 18 weeks age in a completely randomized design (CRD). The treatments consist of basal diet including corn and soybean meal (without residual restaurants), and treatments 2, 3, 4 and 5, includes a basal diet containing 5, 10, 15 and 20% of restaurant residuals, respectively. There were no significant effect of restaurant residuals levels on body weight (BW), feed conversion ratio (FCR), percentage of egg production (EP), egg mass (EM) between treatments (P > 0/05). However, feed intake (FI) of 5% restaurant residual was significantly higher than 20% treatment (P < 0/05). Egg weight (EW) was also higher by receiving 20% restaurant residuals compared with 10% in this respect (P < 0/05). Yolk weight (YW) of treatments containing 10 and 20% of the residual restaurant were significantly higher than control (P < 0/05). Eggs white weight (EWW) of 20 and 5% restaurants residual treatments were significantly increased compared by 10% (P < 0/05). Furthermore, EW, egg weight to shell surface area and egg surface area in 20% treatment were significantly higher than control and 10% treatment (P < 0/05). The overall results of this study have shown that restaurant residuals for laying quail diets in levels of 10 and 15 percent could be replaced with a part of the quail ration without any adverse effect.

Keywords: by-product, laying quail, performance, restaurant residuals

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Authors: Pilly Kagosi, Cherestino Balama

Abstract:

Beekeeping plays major role in improving biodiversity, increasing household income, and crop production through pollination. Tobacco farming is also the main source of household income for smallholder farmers. In Kigoma, production of Tobacco has increased and is perceived to threaten honey quality. The study explored the perception of the community on quality of honey in tobacco and non tobacco growing areas. The study was conducted in Kigoma Region, Tanzania. District and Villages were purposively sampled based on large numbers of people dealing with beekeeping activities and tobacco farming. Socioeconomic data were collected and analysed using Statistical Package for Social Sciences and content analysis. The perception of stakeholders on honey quality was analysed using Likert scale. Majority of the respondents agreed that tobacco farming greatly affects honey quality because honey from beehives near tobacco farms test bitter and sometimes irritating, which was associated with nicotine content and agrochemicals applied to tobacco crops. Though they cannot differentiate honey bitterness from agrochemicals and bee fodders. Furthermore, it was revealed that chemicals applied to tobacco and vegetables have negative effect on the bees and honey quality. Respondents believe that setting bee hives near tobacco farms might contaminate honey and therefore affect its quality. Beekeepers are not aware of the nicotine content from other bee fodders like miombo of which do not have any effect on human beings. Actually, tobacco farming does not affect beekeeping activities in issue of quality when farmers follow proper management of tobacco flowers and proper handling of honey. Though, big challenge in tobacco farming is chemically applied to the crops and harvest bee fodders for curing tobacco. The study recommends training to community on proper management of tobacco and proper handling of bee products.

Keywords: community, honey, perceptions, tobacco

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Authors: Sachin B. Patil, Narendra M. Kanhe

Abstract:

A typical cane molasses based distillery generates 15 L of waste water per liter of alcohol production. Distillery waste with COD of over 1,00,000 mg/l and BOD of over 30,000 mg/l ranks high amongst the pollutants produced by industries both in magnitude and strength. Treatment and safe disposal of this waste is a challenging task since long. The high strength of waste water renders aerobic treatment very expensive and physico-chemical processes have met with little success. Thermophilic anaerobic treatment of distillery waste may provide high degree of treatment and better recovery of biogas. It may prove more feasible in most part of tropical country like India, where temperature is suitable for thermophilic micro-organisms. Researchers have reviled that, at thermophilic conditions due to increased destruction rate of organic matter and pathogens, higher digestion rate can be achieved. Literature review reveals that the variety of anaerobic reactors including anaerobic lagoon, conventional digester, anaerobic filter, two staged fixed film reactors, sludge bed and granular bed reactors have been studied, but little attempts have been made to evaluate the usefulness of thermophilic anaerobic treatment for treating distillery waste. The present study has been carried out, to study feasibility of thermophilic anaerobic digestion to facilitate the design of full scale reactor. A pilot scale anaerobic fixed film fixed bed reactor (AFFFB) of capacity 25m3 was designed, fabricated, installed and commissioned for thermophilic (55-65°C) anaerobic digestion at a constant pH of 6.5-7.5, because these temperature and pH ranges are considered to be optimum for biogas recovery from distillery wastewater. In these conditions, working of the reactor was studied, for different hydraulic retention times (HRT) (0.25days to 12days) and variable organic loading rates (361.46 to 7.96 Kg COD/m3d). The parameters such as flow rate and temperature, various chemical parameters such as pH, chemical oxygen demands (COD), biogas quantity, and biogas composition were regularly monitored. It was observed that, with the increase in OLR, the biogas production was increased, but the specific biogas yield decreased. Similarly, with the increase in HRT, the biogas production got decrease, but the specific biogas yield was increased. This may also be due to the predominant activity of acid producers to methane producers at the higher substrate loading rates. From the present investigation, it can be concluded that for thermophilic conditions the highest COD removal percentage was obtained at an HRT of 08 days, thereafter it tends to decrease from 8 to 12 days HRT. There is a little difference between COD removal efficiency of 8 days HRT (74.03%) and 5 day HRT (78.06%), therefore it would not be feasible to increase the reactor size by 1.5 times for mere 4 percent more efficiency. Hence, 5 days HRT is considered to be optimum, at which the biogas yield was 98 m3/day and specific biogas yield was 0.385 CH4 m3/Kg CODr.

Keywords: spent wash, anaerobic digestion, biomass, biogas

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