Search results for: optimum weight vector.

Authors: Ling-fei Xu, Qi Zhao, Yan-ru Chen, Mu-chun Zhou, Meng Zhang, Shi-xue Xu

Abstract:

SVM ( Support Vector Machine ) is a new method in the artificial neural network ( ANN ). In the steel making, how to use computer to predict the end point of BOF accuracy is a great problem. A lot of method and theory have been claimed, but most of the results is not satisfied. Now the hot topic in the BOF end point predicting is to use optical way the predict the end point in the BOF. And we found that there exist some regular in the characteristic curve of the flame from the mouse of pudding. And we can use SVM to predict end point of the BOF, just single spectrum intensity should be required as the input parameter. Moreover, its compatibility for the input space is better than the BP network.

Keywords: SVM, predict, BOF, single spectrum intensity.

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Authors: Kalyan Kr. Mandal, Suresh Thokchom, Mithun Roy

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The present paper reports results of an experimental program conducted to study performance of fly ash based geopolymer pastes at elevated temperature. Three series of geopolymer pastes differing in Na2O content (8.5%, 10% and 11.5%) were manufactured by activating low calcium fly ash with a mixture of sodium hydroxide and sodium silicate solution. The paste specimens were subjected to temperatures as high as 900oC and the behaviour at elevated temperatures were investigated on the basis of physical appearance, weight losses, residual strength, shrinkage measurements and sorptivity tests at different temperatures. Scanning electron microscopy along with EDX and XRD tests were also conducted to examine microstructure and mineralogical changes during the thermal exposure. Specimens which were initially grey turned reddish accompanied by appearance of small cracks as the temperature increased to 900oC. Loss of weight was more in specimens manufactured with highest Na2O content. Geopolymer paste specimen containing minimum Na2O performed better than those with higher Na2O content in terms of residual compressive strength.

Keywords: Compressive strength, EDX, Elevated temperature, Fly ash, Geopolymer, Scanning electron microscopy, XRD

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning (ML) archetypal that could forecast the COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID-19 cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organization (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data are split into 8:2 ratio for training and testing purposes to forecast future new COVID-19 cases. Support Vector Machine (SVM), Random Forest (RF), and linear regression (LR) algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID-19 cases is evaluated. RF outperformed the other two ML algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n = 30. The mean square error obtained for RF is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis, RF algorithm can perform more effectively and efficiently in predicting the new COVID-19 cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest.

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Authors: M. Hussain, Aqsa Farooq

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Let G = (V,E) be a connected graph and distance between any two vertices a and b in G is a−b geodesic and is denoted by d(a, b). A set of vertices W resolves a graph G if each vertex is uniquely determined by its vector of distances to the vertices in W. A metric dimension of G is the minimum cardinality of a resolving set of G. In this paper line graph of honeycomb network has been derived and then we calculated the metric dimension on line graph of honeycomb network.

Keywords: Resolving set, metric dimension, honeycomb network, line graph.

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Authors: Nebi Gedik, Ayten Atasoy

Abstract:

This paper investigates successful sub-bands of wave atom transform via classification of mammograms, when the coefficients of sub-bands are used as features. A computer-aided diagnosis system is constructed by using wave atom transform, support vector machine and k-nearest neighbor classifiers. Two-class classification is studied in detail using two data sets, separately. The successful sub-bands are determined according to the accuracy rates, coefficient numbers, and sensitivity rates.

Keywords: Breast cancer, wave atom transform, SVM, k-NN.

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Authors: Kapse Swapnil, K. Shankar

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Aiming at optimizing the weight and deflection of cantilever beam subjected to maximum stress and maximum deflection, Multi-objective Particle Swarm Optimization (MOPSO) with Utopia Point based local search is implemented. Utopia point is used to govern the search towards the Pareto Optimal set. The elite candidates obtained during the iterations are stored in an archive according to non-dominated sorting and also the archive is truncated based on least crowding distance. Local search is also performed on elite candidates and the most diverse particle is selected as the global best. This method is implemented on standard test functions and it is observed that the improved algorithm gives better convergence and diversity as compared to NSGA-II in fewer iterations. Implementation on practical structural problem shows that in 5 to 6 iterations, the improved algorithm converges with better diversity as evident by the improvement of cantilever beam on an average of 0.78% and 9.28% in the weight and deflection respectively compared to NSGA-II.

Keywords: Utopia point, multi-objective particle swarm optimization, local search, cantilever beam.

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Authors: A. A. Najm, M. R. Haj Seyed Hadi, F. Fazeli, M. Taghi Darzi, R. Shamorady

Abstract:

Cattle manure and mineral fertilizers are two source of Nitrogen, which can affect the growth and quantity of potato. In this research the effects of the use of cattle manure (5, 10, 15 and 20 ton ha-1), Nitrogen fertilizer (50, 100 and 150 kg N ha-1) and their interaction on potato growth were evaluated during field experiments in 2008 with the help of Randomized Complete Block (RCB) with the factorial arrangement of three experimental replications in Iran. At the 75 th day after emergence, dry weight of Shoots, leaf area index (LAI) and plant height were recorded. Results showed that, dry weight of Shoots, LAI and plant height increased linearly and very significantly in response to the application of manure and Nitrogen fertilizer. While the interaction between manure and Nitrogen fertilizer just on the LAI and plant height was significant, somehow the maximum amount of plant height( 73 cm) was obtained by using 150 kg Nitrogen + 15 tons of manure per hectare, and maximum LAI ( 5.36) was obtained by using 150 kg Nitrogen + 20 tons of manure per hectare. Also in this experiment maximum tuber yield (36.8 tons ha-1) was obtained by the utilization of 150 kg Nitrogen per hectare + 20 tons manure.

Keywords: Solanum tuberosum, LAI, cattle manure, mineral fertilizer, integrated management.

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Authors: E. Dolatdar, S. Soleymani, B. Mozafari

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Power loss reduction is one of the main targets in power industry and so in this paper, the problem of finding the optimal configuration of a radial distribution system for loss reduction is considered. Optimal reconfiguration involves the selection of the best set of branches to be opened ,one each from each loop, for reducing resistive line losses , and reliving overloads on feeders by shifting the load to adjacent feeders. However ,since there are many candidate switching combinations in the system ,the feeder reconfiguration is a complicated problem. In this paper a new approach is proposed based on a simple optimum loss calculation by determining optimal trees of the given network. From graph theory a distribution network can be represented with a graph that consists a set of nodes and branches. In fact this problem can be viewed as a problem of determining an optimal tree of the graph which simultaneously ensure radial structure of each candidate topology .In this method the refined genetic algorithm is also set up and some improvements of algorithm are made on chromosome coding. In this paper an implementation of the algorithm presented by [7] is applied by modifying in load flow program and a comparison of this method with the proposed method is employed. In [7] an algorithm is proposed that the choice of the switches to be opened is based on simple heuristic rules. This algorithm reduce the number of load flow runs and also reduce the switching combinations to a fewer number and gives the optimum solution. To demonstrate the validity of these methods computer simulations with PSAT and MATLAB programs are carried out on 33-bus test system. The results show that the performance of the proposed method is better than [7] method and also other methods.

Keywords: Distribution System, Reconfiguration, Loss Reduction , Graph Theory , Optimization , Genetic Algorithm

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Authors: Salem Alsanusi

Abstract:

A self-compacting concrete (SCC) is the one that can be placed in the form and can go through obstructions by its own weight and without the need of vibration. Since its first development in Japan in 1988, SCC has gained wider acceptance in Japan, Europe and USA due to its inherent distinct advantages. Although there are visible signs of its gradual acceptance in the North Africa through its limited use in construction, Libya has yet to explore the feasibility and applicability of SCC in new construction. The contributing factors to this reluctance appear to be lack of any supportive evidence of its suitability with local aggregates and the harsh environmental conditions. The primary aim of this study is to explore the feasibility of using SCC made with local aggregates of Eastern Province of Libya by examining its basic properties characteristics. This research consists of: (i) Development of a suitable mix for SCC such as the effect of water to cement ratio, limestone and silica fume that would satisfy the requirements of the plastic state; (ii) Casting of concrete samples and testing them for compressive strength and unit weight. Local aggregates, cement, admixtures and industrial waste materials were used in this research. The significance of this research lies in its attempt to provide some performance data of SCC made in the Eastern Province of Libya so as to draw attention to the possible use of SCC.

Keywords: Silica fume, self compacting concrete, workability, coarse and fine aggregate.

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Authors: Javad Taherahmadi, Mohammad Jafarian, Mohammad Naser Asefi

Abstract:

The global capacity of wind power has dramatically increased in recent years. Therefore, improving the technology of wind turbines to take different advantages of this enormous potential in the power grid, could be interesting subject for scientists. The doubly-fed induction generator (DFIG) wind turbine is a popular system due to its many advantages such as the improved power quality, high energy efficiency and controllability, etc. With an increase in wind power penetration in the network and with regard to the flexible control of wind turbines, the use of wind turbine systems to improve the dynamic stability of power systems has been of significance importance for researchers. Subsynchronous oscillations are one of the important issues in the stability of power systems. Damping subsynchronous oscillations by using wind turbines has been studied in various research efforts, mainly by adding an auxiliary control loop to the control structure of the wind turbine. In most of the studies, this control loop is composed of linear blocks. In this paper, simple adaptive control is used for this purpose. In order to use an adaptive controller, the convergence of the controller should be verified. Since adaptive control parameters tend to optimum values in order to obtain optimum control performance, using this controller will help the wind turbines to have positive contribution in damping the network subsynchronous oscillations at different wind speeds and system operating points. In this paper, the application of simple adaptive control in DFIG wind turbine systems to improve the dynamic stability of power systems is studied and the essential condition for using this controller is considered. It is also shown that this controller has an insignificant effect on the dynamic stability of the wind turbine, itself.

Keywords: Almost strictly positive real, doubly-fed induction generator, simple adaptive control, subsynchronous oscillations, wind turbine.

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Authors: Zia Amjad, Salem S. Alghamdi

Abstract:

The study was conducted at the student educational farm at the College of Food and Agriculture in the Kingdom of Saudi Arabia. The aim of study was to characterize 154 Vicia faba L. accessions using agro-morphological traits based on The International Union for the Protection of New Varieties of Plants (UPOV) and The International Board for Plant Genetic Resources (IBPGR) descriptors. This research is significant as it contributes to the understanding of the genetic diversity and potential yield of V. faba in Saudi Arabia. In the study, 24 agro-morphological characters including 11 quantitative and 13 qualitative were observed for genetic variation. All the results were analyzed using multivariate analysis i.e., principal component analysis (PCA). First, six principal components (PC) had eigenvalues greater than one; accounted for 72% of available V. faba genetic diversity. However, first three components revealed more than 10% of genetic diversity each i.e., 22.36%, 15.86% and 10.89% respectively. PCA distributed the V. faba accessions into different groups based on their performance for the characters under observation. PC-1, which represented 22.36% of the genetic diversity, was positively associated with stipule spot pigmentation, intensity of streaks, pod degree of curvature and to some extent with 100 seed weight. PC-2 covered 15.86 of the genetic diversity and showed positive association for average seed weight per plant, pod length, number of seeds per plant, 100 seed weight, stipule spot pigmentation, intensity of streaks (same as in PC-1) and to some extent for pod degree of curvature and number of pods per plant. PC-3 revealed 10.89% of genetic diversity and expressed positive association for number of pods per plant and number of leaflets per plant. This study contributes to the understanding of the genetic diversity and potential yield of V. faba in the Kingdom of Saudi Arabia. By establishing a core collection of V. faba, the research provides a valuable resource for future conservation and utilization of this crop worldwide.

Keywords: Agro-morphological characterization, genetic diversity, core collection, PCA, Vicia faba L.

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Authors: S. M. Al-Salem, G.A. Leeke, H. J. Karam, R. Al-Enzi, A. T. Al-Dhafeeri, J. Wang

Abstract:

Thermogravimetry has been popularized as a thermal characterization technique since the 1950s. It aims at investigating the weight loss against both reaction time and temperature, whilst being able to characterize the evolved gases from the volatile components of the organic material being tested using an appropriate hyphenated analytical technique. In an effort to characterize and identify the reclaimed waste from an unsanitary landfill site, this approach was initiated. Solid waste (SW) reclaimed from an active landfill site in the State of Kuwait was collected and prepared for characterization in accordance with international protocols. The SW was segregated and its major components were identified after washing and air drying. Shredding and cryomilling was conducted on the plastic solid waste (PSW) component to yield a material that is representative for further testing and characterization. The material was subjected to five heating rates (b) with minimal repeatable weight for high accuracy thermogravimetric analysis (TGA) following the recommendation of the International Confederation for Thermal Analysis and Calorimetry (ICTAC). The TGA yielded thermograms that showed an off-set from typical behavior of commercial grade resin which was attributed to contact of material with soil and thermal/photo-degradation.

Keywords: Polymer, TGA, Pollution, Landfill, Waste, Plastic.

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Authors: A. Ghasemipanah, R. Ziaie Moayed, H. Niroumand

Abstract:

Improving the geotechnical properties of soil has always been one of the issues in geotechnical engineering. Traditional materials have been used to improve and stabilize soils to date, each with its own advantages and disadvantages. Although the soil stabilization by adding materials such as cement, lime, bitumen, etc. is one of the effective methods to improve the geotechnical properties of soil, but nanoparticles are one of the newest additives which can improve the loose soils. This research is intended to study the effect of adding nanobentonite on soil engineering properties, especially the unconfined compression strength and maximum dry unit weight, using clayey soil with low liquid limit (CL) from Kerman (Iran). Nanobentonite was mixed with soil in three different percentages (i.e. 3, 5, 7% by weight of the parent soil) with different curing time (1, 7 and 28 days). The unconfined compression strength, liquid and plastic limits and plasticity index of treated specimens were measured by unconfined compression and Atterberg limits test. It was found that increase in nanobentonite content resulted in increase in the unconfined compression strength, liquid and plastic limits of the clayey soil and reduce in plasticity index.

Keywords: Nanobentonite particles, clayey soil, unconfined compression stress, soil improvement.

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Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

Abstract:

Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: Metagenomics, phenotype prediction, deep learning, embeddings, multiple instance learning.

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Authors: Pravin Gaikwad, Prakash Mahanwar

Abstract:

The main objective of incorporating natural fibers such as Henequen microfibers (NF) into the High Density Polyethylene (HDPE) polymer matrix is to reduce the cost and to enhance the mechanical as well as other properties. The Henequen microfibers were chopped manually to 5-7mm in length and added into the polymer matrix at the optimized concentration of 8 wt %. In order to facilitate the link between Henequen microfibers (NF) and HDPE matrix, coupling agent such as Glycidoxy (Epoxy) Functional Methoxy Silane (GPTS) at various concentrations from 0.1%, 0.3%, 0.5%, 0.7%, 0.9% and 1% by weight to the total fibers were added. The tensile strength of the composite increased marginally while % elongation at break of the composites decreased with increase in silane loading by wt %. Tensile modulus and stiffness observed increased at 0.9 wt % GPTS loading. Flexural as well as impact strength of the composite decreased with increase in GPTS loading by weight %. Dielectric strength of the composite also found increased marginally up to 0.5wt % silane loading and thereafter remained constant. 

Keywords: Henequen microfibers (NF), polymer composites, HDPE, coupling agent, GPTS

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Authors: Howaidi M. Al-Otaibi, Abdulrahman S. Al-Suhaibani, Hamad A. Alsoliman

Abstract:

Fibers are extensively used in civil engineering applications for many years. In this study, empty fruit bunch of date palm trees were used to produce cellulose fiber that were used as additives in the asphalt binder. Two sizes (coarse and fine) of cellulose fibers were pre-blended in PG64-22 binder with various contents of 1.5%, 3%, 4.5%, 6%, and 7.5% by weight of asphalt binder. The physical and rheological properties of fiber modified asphalt binders were tested by using conventional tests such as penetration, softening point and viscosity; and SHRP test such as dynamic shear rheometer. The results indicated that the fiber modified asphalt binders were higher in softening point, viscosity, and complex shear modulus, and lower in penetration compared to pure asphalt. The fiber modified binders showed an improvement in rheological properties since it was possible to raise the control binder (pure asphalt) PG from 64 to 70 by adding 6% (by weight) of either fine or coarse fibers. Such improvement in stiffness of fiber modified binder is expected to improve pavement resistance to rutting.

Keywords: Cellulose date palm fiber, fiber modified asphalt, physical properties, rheological properties.

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Authors: Rujira Kongnuy

Abstract:

Leptospirosis is recognized as an important zoonosis in tropical regions well as an important animal disease with substantial loss in production. In this study, the model for the transmission of the Leptospirosis disease to human population are discussed. Model is described the vector population dynamics and the Leptospirosis transmission to the human population are discussed. Local analysis of equilibria are given. We confirm the results by using numerical results.

Keywords: Eigenvalues, Leptospirosis, Local Stability, Numerical Result

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Authors: C. Ardil

Abstract:

Unmanned combat aircraft (UCA) are expanding significantly in several defense industries, along with artificial intelligence improvements in highly precise technology. UCA is crucial in military settings for targeting enemy elements, and objects. UCA is also utilized for highly precise reconnaissance and surveillance tasks. To select the best alternative for critical missions, a methodical and effective strategy for UCA selection is required. Multiple criteria decision-making (MCDM) methodologies are ideally equipped to handle the complexity of alternative aircraft selection. To analyze UCA alternatives for the selection process, an integrated methodology built on the objective criteria weights and preference analysis for reference ideal solution (PARIS). First, the weights of essential elements are determined using the average weight (AW), standard deviation (SW) and entropy weight (EW) approach. The weights of the evaluation criteria affect the decision-making process. The aircraft choices in the decision problem are then ranked using objective criteria weights along with the PARIS technique. The validation and sensitivity analysis of the proposed MCDM approach are discussed.

Keywords: unmanned combat aircraft (UCA), multiple criteria decision making, MCDM, PARIS

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Authors: W. A. Hamd Alla, E. M. Shalaby, R. A. Dawood, A. A. Zohry

Abstract:

A field experiment was carried out at Arab El- Awammer Research Station, Agric. Res. Center. Assiut Governorate during summer seasons of 2013 and 2014. The present study assessed the effect of cowpea with maize intercropping on yield and its components. The experiment comprised of three treatments (sole cowpea, sole maize and cowpea-maize intercrop). The experimental design was a randomized complete block with four replications. Results indicated that intercropped maize plants with cowpea, exhibited greater potentiality and resulted in higher values of most of the studied criteria viz., plant height, number of ears/plant, number of rows/ear, number of grains/row, grains weight/ear, 100–grain weight and straw and grain yields. Fresh and dry forage yields of cowpea were lower in intercropping with maize than sole. Furthermore, the combined of the two seasons revealed that the total Land Equivalent Ratio (LER) between cowpea and maize was 1.65. The Aggressivity (A) maize was 0.45 and cowpea was -0.45. This showed that maize was the dominant crop, whereas cowpea was the dominated. The Competitive Ratio (CR) indicated that maize more competitive than cowpea, maize was 1.75 and cowpea was 0.57. The Actual Yield Loss (AYL) maize was 0.05 and cowpea was -0.40. The Monetary Advantage Index (MAI) was 2360.80.

Keywords: Intercropping, cowpea, maize, land equivalent ratio (LER).

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Authors: Anuoluwapo S. Taiwo, David S. Ayre, Morteza Khorami, Sameer S. Rahatekar

Abstract:

This investigation aims to characterize the effect of corncob (CC), an agricultural waste, for potential use as a filler material, reducing cement in natural fibre-reinforced cement composite boards used for building applications in low-cost housing estates in developing countries. The CC is readily and abundantly available in many West African States. However, this agricultural waste product has not been put to any effective use. Hence, the objective of the current research is to convert this massive agro-waste resource into a potential material for use as filler materials reducing cement contents in fibre-cement board production. Kraft pulp fibre-reinforced cement composite boards were developed with the incorporation of the CC powder at varying percentages of 1-4% as filler materials to reduce the cement content, using a laboratory-simulated vacuum de-watering process. The mechanical properties of the developed cement boards were characterized through a three-point bending test, while the fractured morphology of the cement boards was examined through a Scanning Electron Microscope (SEM). Results revealed that the flexural strength of the composite board improved significantly with an optimum enhancement of 39% when compared to the reference sample without CC replacement, however, the flexural behaviour (ductility) of the composite board was slightly affected by the addition of the CC powder at higher percentage. SEM observation of the fractured surfaces revealed good bonding at the fibre-matrix interface as well as a ductile-to-brittle fracture mechanism. Overall, the composite board incorporated with 2% CC powder as filler materials had the optimum properties, satisfying the minimum requirements of relevant standards for fibre cement flat sheets.

Keywords: Kraft pulp fibre, fibre-cement board, agricultural waste, sustainability, building applications.

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Authors: Mohammad Abdallah

Abstract:

Due to the constant increase in terrorist attacks, the research and engineering communities have given significant attention to building performance under explosions. This paper presents a methodology for studying and simulating the dynamic responses of steel structures during external detonations, particularly for accurately investigating the impact of incrementing charge weight on the members total behavior, resistance and failure. Prediction damage method was introduced to evaluate the damage level of the steel members based on five scenarios of explosions. Johnson–Cook strength and failure model have been used as well as ABAQUS finite element code to simulate the explicit dynamic analysis, and antecedent field tests were used to verify the acceptance and accuracy of the proposed material strength and failure model. Based on the structural response, evaluation criteria such as deflection, vertical displacement, drift index, and damage level; the obtained results show the vulnerability of steel columns and un-braced steel frames which are designed and optimized to carry dead and live load to resist and endure blast loading.

Keywords: Steel structure, blast load, terrorist attacks, charge weight, damage level.

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Authors: A. Kistaubayeva, I. Savitskaya, D. Ibrayeva, M. Abdulzhanova, N. Voronova

Abstract:

36 strains of sulfur-oxidizing bacteria were isolated in Southern Kazakhstan soda-saline soils and identified. Screening of strains according bio-oxidation (destruction thiosulfate to sulfate) and enzymatic (Thiosulfate dehydrogenises and thiosulfate reductase) activity was conducted. There were selected modes of aeration and culture conditions (pH, temperature), which provide optimum harvest cells. These strains can be used in bio-melioration technology.

Keywords: Elemental sulfur, oxidation activity, Тhiobacilli, fertilizers, heterotrophic S-oxidizers.

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Authors: S. Hasan, I. Beshara

Abstract:

Infrastructure maintenance is a great challenge facing sustainable development of infrastructure assets due to the high cost of passive implementation of a sustainable maintenance plan. An assessment model of sustainable maintenance for highway infrastructure projects in Egypt is developed in this paper. It helps in improving the implementation of sustainable maintenance criteria. Thus, this paper has applied the analytical hierarchy processes (AHP) to rank and explore the weight of 26 assessment indicators using three hierarchy levels containing the main sustainable categories and subcategories with related indicators. Overall combined weight of each indicator for sustainable maintenance evaluation has been calculated to sum up to a sustainable maintenance performance index (SMI). The results show that the factor "Preventive maintenance cost" has the highest relative contribution factor among others (13.5%), while two factors of environmental performance have the least weights (0.7%). The developed model aims to provide decision makers with information about current maintenance performance and support them in the decision-making process regarding future directions of maintenance activities. It can be used as an assessment performance tool during the operation and maintenance stage. The developed indicators can be considered during designing the maintenance plan. Practices for successful implementation of the model are also presented.

Keywords: Analytical Hierarchy Process, AHP, assessment performance model, KPIs for sustainable maintenance, sustainable maintenance index.

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Authors: Mohammed T. Hayajneh, Adel Mahmood Hassan, Moath AL-Qudah

Abstract:

Burnishing is increasingly used as a finishing operation to improve surface roughness and surface hardness. This can be achieved by applying a hard ball or roller onto metallic surfaces under pressure, in order to achieve many advantages in the metallic surface. In the present work, the feed rate, speed and force have been considered as the basic burnishing parameters to study the surface roughness and surface hardness of metallic matrix composites. The considered metal matrix composites were made from Aluminum-Magnesium-Graphite with five different weight percentage of graphite. Both effects of burnishing parameters mentioned above and the graphite percentage on the surface hardness and surface roughness of the metallic matrix composites were studied. The results of this investigation showed that the surface hardness of the metallic composites increases with the increase of the burnishing force and decreases with the increase in the burnishing feed rate and burnishing speed. The surface roughness of the metallic composites decreases with the increasing of the burnishing force, feed rate, and speed to certain values, then it starts to increase. On the other hand, the increase in the weight percentage of the graphite in the considered composites causes a decrease in the surface hardness and an increase in the surface roughness.

Keywords: Burnishing process, Al-Mg-Graphite composites, Surface hardness, Surface roughness.

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Authors: M.Mirzakhani, M.R.Ardakani , A.Aeene Band , A.H. Shirani Rad, F.Rejali

Abstract:

In order to evaluate the Effects of dual inoculation of Azotobacter and Mycorrhiza with Nitrogen and Phosphorus levels on yield and yield components of spring safflower, this study was carried out in field of Farahan university in Markazi province in 2007. A factorial in a randomized complete block design with three replications was used inoculation of Azotobacter (with inoculation and without inoculation) and Mycorrhiza (with inoculation and without inoculation ) with Nitrogen and Phosphorus levels [F0= N0+ P0 (kg.ha-1), F1= N50+ P25(kg.ha-1), F2= N100+ P50(kg.ha-1) and F3= N150+ P75 (kg.ha-1)] on spring safflower (cultivar IL-111). In this study characteristics such as: Harvest index, Hectolitre weight, Root dry weight, Seed yield, Mycorrhizal Colonization Root, Number of days to maturity were assessed. Results indicated that treatment (A0M1F3) with grain yield (1556 kg.ha-1) and treatment (A0M1F0) with grain yield (918 kg.ha-1) were significantly superior to the other treatments and according to calculated, inoculation seeds in plantig date with Azotobacter and Mycorrhiza to cause increase grain yield about 5/38 percentage. we can by inoculation safflower seeds with Azotobacter and Mycorrhiza too easily at the time sowing date. The purpose of this research, study and evaluation the role of biological fixation N and P, to provide for feeds plants.

Keywords: Spring safflower, grain yield, inoculation, Azotobacter and Mycorrhiza.

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Authors: Maliheh Raji, Hossein Abolghasemi, Jaber Safdari, Ali Kargari

Abstract:

Samarium as a rare-earth element is playing a growing important role in high technology. Traditional methods for extraction of rare earth metals such as ion exchange and solvent extraction have disadvantages of high investment and high energy consumption. Emulsion liquid membrane (ELM) as an improved solvent extraction technique is an effective transport method for separation of various compounds from aqueous solutions. In this work, the extraction of samarium from aqueous solutions by ELM was investigated using response surface methodology (RSM). The organic membrane phase of the ELM was a nanofluid consisted of multiwalled carbon nanotubes (MWCNT), Span80 as surfactant, Cyanex 272 as mobile carrier, and kerosene as base fluid. 1 M nitric acid solution was used as internal aqueous phase. The effects of the important process parameters on samarium extraction were investigated, and the values of these parameters were optimized using the Central Composition Design (CCD) of RSM. These parameters were the concentration of MWCNT in nanofluid, the carrier concentration, and the volume ratio of organic membrane phase to internal phase (Roi). The three-dimensional (3D) response surfaces of samarium extraction efficiency were obtained to visualize the individual and interactive effects of the process variables. A regression model for % extraction was developed, and its adequacy was evaluated. The result shows that % extraction improves by using MWCNT nanofluid in organic membrane phase and extraction efficiency of 98.92% can be achieved under the optimum conditions. In addition, demulsification was successfully performed and the recycled membrane phase was proved to be effective in the optimum condition.

Keywords: Cyanex 272, emulsion liquid membrane, multiwalled carbon nanotubes, nanofluid, response surface methodology, Samarium.

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Authors: Raquel Vianna Duarte Cardoso, Eduarda Lobato Faria, José Jorge Boueri

Abstract:

Rapid urbanization has transformed the global landscape, presenting significant challenges to public health. This article delves into the impact of urbanization on the spread of infectious diseases in cities and identifies crucial strategies to enhance urban community resilience. Massive urbanization over recent decades has created conducive environments for the rapid spread of diseases due to population density, mobility, and unequal living conditions. Urbanization has been observed to increase exposure to pathogens and foster conditions conducive to disease outbreaks, including seasonal flu, vector-borne diseases, and respiratory infections. In order to tackle these issues, a range of cross-disciplinary approaches are suggested. These encompass the enhancement of urban healthcare infrastructure, emphasizing the need for robust investments in hospitals, clinics, and healthcare systems to keep pace with the burgeoning healthcare requirements in urban environments. Moreover, the establishment of disease monitoring and surveillance mechanisms is indispensable, as it allows for the timely detection of outbreaks, enabling swift responses. Additionally, community engagement and education play a pivotal role in advocating for personal hygiene, vaccination, and preventive measures, thus playing a pivotal role in diminishing disease transmission. Lastly, the promotion of sustainable urban planning, which includes the creation of cities with green spaces, access to clean water, and proper sanitation, can significantly mitigate the risks associated with waterborne and vector-borne diseases. The article is based on the analysis of scientific literature, and it offers a comprehensive insight into the complexities of the relationship between urbanization and health. It places a strong emphasis on the urgent need for integrated approaches to improve urban resilience in the face of health challenges.

Keywords: Infectious diseases dissemination, public health, urbanization impacts, urban resilience.

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Authors: A. Sopharak, B. Uyyanonvara, S. Barman

Abstract:

Diabetic retinopathy is characterized by the development of retinal microaneurysms. The damage can be prevented if disease is treated in its early stages. In this paper, we are comparing Support Vector Machine (SVM) and Naïve Bayes (NB) classifiers for automatic microaneurysm detection in images acquired through non-dilated pupils. The Nearest Neighbor classifier is used as a baseline for comparison. Detected microaneurysms are validated with expert ophthalmologists’ hand-drawn ground-truths. The sensitivity, specificity, precision and accuracy of each method are also compared.

Keywords: Diabetic retinopathy, microaneurysm, Naïve Bayes classifier, SVM classifier.

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Authors: M. Toghyani, A. Ghasemi, S. A. Tabeidian

Abstract:

The present study was carried out to evaluate the effect of different levels of dietary seed and extract of Harmal (Peganum harmala L.) on immunity of broiler chicks. A total of 350 one-day old broiler chicks (Ross 308) were randomly allocated to five dietary treatments with four replicates pen of 14 birds each. Dietary treatments consisted of control, 1 and 2 g/kg Harmal seed in diet, 100 and 200 mg/L Harmal seed extract in water. Broilers received dietary treatments from 1 to 42 d. Two birds from each pen were randomly weighed and sacrificed at 42 d of age, the relative weight of lymphoid organs (bursa of Fabercius and spleen) to live weight were calculated. Antibody titers against Newcastle and influenza viruses and sheep red blood cell were measured at 30 d of age. Results showed that the relative weights of lymphoid organs were not affected by dietary treatments. Furthermore, antibody titer against Newcastle and influenza viruses as well as sheep red blood cell antigen were significantly (P<0.05) enhanced by feeding Harmal seed and extract. In conclusion, the results indicated that dietary inclusion of Harmal seed and extract enhanced immunological responses in broiler chicks.

Keywords: Broiler chicks, Harmal, immunity.

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Authors: Yanting Cao, Kazumitsu Nawata

Abstract:

As smartphones are continually upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described more refined, complex and detailed. In this context, we analyzed a set of experimental data, obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model become extremely challenging. After a series of feature selection and parameters adjustments, a well-performed SVM classifier has been trained. 

Keywords: smart sensors, human activity recognition, artificial intelligence, SVM

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