Search results for: tomato yield prediction

Authors: Amin Nezarat, Naeime Seifadini

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Trip mode selection is a behavioral characteristic of passengers with immense importance for travel demand analysis, transportation planning, and traffic management. Identification of trip mode distribution will allow transportation authorities to adopt appropriate strategies to reduce travel time, traffic and air pollution. The majority of existing trip mode inference models operate based on human selected features and traditional machine learning algorithms. However, human selected features are sensitive to changes in traffic and environmental conditions and susceptible to personal biases, which can make them inefficient. One way to overcome these problems is to use neural networks capable of extracting high-level features from raw input. In this study, the convolutional neural network (CNN) architecture is used to predict the trip mode distribution based on raw GPS trajectory data. The key innovation of this paper is the design of the layout of the input layer of CNN as well as normalization operation, in a way that is not only compatible with the CNN architecture but can also represent the fundamental features of motion including speed, acceleration, jerk, and Bearing rate. The highest prediction accuracy achieved with the proposed configuration for the convolutional neural network with batch normalization is 85.26%.

Keywords: predicting, deep learning, neural network, urban trip

Procedia PDF Downloads 138

Authors: Jun-ya Nagase, Toshiyuki Satoh, Norihiko Saga, Koichi Suzumori

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In recent years, Japanese society has been aging, engendering a labour shortage of young workers. Robots are therefore expected to perform tasks such as rehabilitation, nursing elderly people, and day-to-day work support for elderly people. The pneumatic balloon actuator is a rubber artificial muscle developed for use in a robot hand in such environments. This actuator has a long stroke, and a high power-to-weight ratio compared with the present pneumatic artificial muscle. Moreover, the dynamic characteristics of this actuator resemble those of human muscle. This study evaluated characteristics of force control of balloon actuator using a predictive functional control (PFC) system with disturbance observer. The predictive functional control is a model-based predictive control (MPC) scheme that predicts the future outputs of the actual plants over the prediction horizon and computes the control effort over the control horizon at every sampling instance. For this study, a 1-link finger system using a pneumatic balloon actuator is developed. Then experiments of PFC control with disturbance observer are performed. These experiments demonstrate the feasibility of its control of a pneumatic balloon actuator for a robot hand.

Keywords: disturbance observer, pneumatic balloon, predictive functional control, rubber artificial muscle

Procedia PDF Downloads 453

Authors: H. Mahdavinezhad, M. Labbaf, H. R. Tavakoli

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In recent decades, the study and control of the destructive effects of explosive vibration in construction projects has received more attention, and several experimental equations in the field of vibration prediction as well as allowable vibration limit for various structures are presented. Researchers have developed a number of experimental equations to estimate the peak particle velocity (PPV), in which the experimental constants must be obtained at the site of the explosion by fitting the data from experimental explosions. In this study, the most important of these equations was evaluated for strong massive conglomerates around Dez Dam by collecting data on explosions, including 30 particle velocities, 27 displacements, 27 vibration frequencies and 27 acceleration of earth vibration at different distances; they were recorded in the form of two types of detonation systems, NUNEL and electric. Analysis showed that the data from the explosion had the best correlation with the cube root of the explosive, R2=0.8636, but overall the correlation coefficients are not much different. To estimate the vibration in this project, data regression was performed in the other formats, which resulted in the presentation of new equation with R2=0.904 correlation coefficient. Finally according to the importance of the studied structures in order to ensure maximum non damage to adjacent structures for each diagram, a range of application was defined so that for distances 0 to 70 meters from blast site, exponent n=0.33 and for distances more than 70 m, n =0.66 was suggested.

Keywords: blasting, blast-induced vibration, empirical equations, PPV, tunnel

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Authors: Rajai Al-Rousan

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This paper presents a proposed analytical model for predicting the shear strength of reinforced concrete beams strengthened with CFRP composites as external reinforcement. The proposed analytical model can predict the shear contribution of CFRP composites of RC beams with an acceptable coefficient of correlation with the tested results. Based on the comparison of the proposed model with the published well-known models (ACI model, Triantafillou model, and Colotti model), the ACI model had a wider range of 0.16 to 10.08 for the ratio between tested and predicted ultimate shears at failure. Also, an acceptable range of 0.27 to 2.78 for the ratio between tested and predicted ultimate shears by the Triantafillou model. Finally, the best prediction (the ratio between the tested and predicted ones) of the ultimate shear capacity is observed by using Colotti model with a range of 0.20 to 1.78. Thus, the contribution of the CFRP composites as external reinforcement can be predicted with high accuracy by using the proposed analytical model.

Keywords: predicting, shear capacity, reinforced concrete, beams, strengthened, externally, CFRP composites

Procedia PDF Downloads 229

Authors: Adam Kok Wey Leong

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The comparison between the Western ways of war and Eastern ways of war has raised contemporary debates on the validity of these arguments. The Western way of war is popularly propounded by Victor Davis Hanson as originating from the Greek hoplite tactics, direct military maneuvers, democratic principles and social freedom and cohesion that has continued to yield military success for the Western powers for centuries. On the other hand, the Eastern way of war has been deemed as relying on indirect tactics, deception, and ruses. This often accepted notion of the divide between Western and Eastern style does not sustain in view of the available classical strategic texts from both sides from the same period that has proposed similar principles of warfare. This paper analyses the similarities between classical strategic texts on war from the Eastern perspective namely Sun Tzu’s Art of War with a similar temporal strategic text from the West which is Sextus Iuluis Frontinus’s Stratagematon, and deduces answers to this core research question - Does the hypothesis of the existence of distinctive Western and Eastern ways of warfare stands? The main thesis advanced by this research is that ways of warfare share universal principles, and it transcends cultural and spatial boundaries. Warfare is a human endeavour, and the same moral actions guide humans from different geo-cultural spheres in warfare’s objectives, which are winning over an enemy in the most economical way and serve as a mean to an end.

Keywords: ways of warfare, strategic culture, strategy, Sun Tzu, frontinus

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Authors: Srinivasan Chandrasekaran, R. Nagavinothini

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Offshore platforms for ultra-deep waters are form-dominant by design; hybrid systems with large flexibility in horizontal plane and high rigidity in vertical plane are preferred due to functional complexities. Offshore triceratops is relatively a new-generation offshore platform, whose deck is partially isolated from the supporting buoyant legs by ball joints. They allow transfer of partial displacements of buoyant legs to the deck but restrain transfer of rotational response. Buoyant legs are in turn taut-moored to the sea bed using pre-tension tethers. Present study will discuss detailed dynamic analysis and preliminary design of the chosen geometric, which is necessary as a proof of validation for such design applications. A detailed numeric analysis of triceratops at 2400 m water depth under random waves is presented. Preliminary design confirms member-level design requirements under various modes of failure. Tether configuration, proposed in the study confirms no pull-out of tethers as stress variation is comparatively lesser than the yield value. Presented study shall aid offshore engineers and contractors to understand suitability of triceratops, in terms of design and dynamic response behaviour.

Keywords: offshore structures, triceratops, random waves, buoyant legs, preliminary design, dynamic analysis

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Authors: Sihem Benmimoune, Abdelbaki Lemgharbi, Ahmed Ait Yahia, Abdelkrim Kameli

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Our study is based on chemical and phytochemical characterization of Artemisia absinthium L and in vitro tests to demonstrate the biological activities of essential oil and natural extract. A qualitative and quantitative comparison of the essential oil extracted by two extraction procedures was performed by analysis of CG/SM and the yield calculation. The method of hydrodistillation has a chemical composition and provides oil content than the best training water vapor. These oils are composed mainly of thujone followed chamazulene and ρ-cymene. The antimicrobial activity of wormwood oil was tested in vitro by two methods (agar diffusion and microdilution) on four plant pathogenic fungi (Aspergillus sp, Botrytis cinerea, Fusarium culmorum and Helminthosporium sp). The study of the antifungal effect showed that this oil has an inhibitory effect counterpart the microorganisms tested in particular the strain Botrytis cinerea. Otherwise, this activity depends on the nature of the oil and the germ itself. The antioxidant activity in vitro was studied with the DPPH method. The activity test shows that the oil and extract of Artemisia absinthium have a very low antioxidant capacity compared to the antioxidants used as a reference. The extract has a potentially high antiradical power not from its oil. The quantitative determinations of phenolic compounds by the Folin-Ciocalteu revealed that absinthe is low in total polyphenols and tannins.

Keywords: artemisia absinthium, biological activities, essential oil, extraction processes

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Authors: Y. K. Leong, J. C. W. Lan, H. S. Loh, P. L. Show

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Being biodegradable, non-toxic, renewable and have similar or better properties as commercial plastics, polyhydroxy alkanoates (PHAs) can be a potential game changer in the polymer industry. PHAs are the biodegradable polymer produced by bacteria, which are in interest as a sustainable alternative to petrochemical-derived plastics; however, its commercial value has significantly limited by high production and recovery cost of PHA. Aqueous two-phase system (ATPS) offers different chemical and physical environments, which contains about 80-90% water delivers an excellent environment for partitioning of cells, cell organelles and biologically active substances. Extractive bioconversion via ATPS allows the integration of PHA upstream fermentation and downstream purification process, which reduces production steps and time, thus lead to cost reduction. The ability of Ralstonia eutropha to grow under different ATPS conditions was investigated for its potential to be used in a bioconversion system. Changes in tie-line length (TLL) and a volume ratio (Vr) were shown to have an effect on PHA partition coefficient. High PHA recovery yield of 65% with a relatively high purity of 73% was obtained in PEG 6000/Sodium sulphate system with 42.6 wt/wt % TLL and 1.25 Vr. Extractive bioconversion via ATPS is an attractive approach for the combination of PHA production and recovery process.

Keywords: aqueous two-phase system, extractive bioconversion, polyhydroxy alkanoates, purification

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Authors: Ahsan Abdullah, Ahmed A. S. Bakshwain

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Livestock is one of the fastest-growing sectors in agriculture. If carefully managed, have potential opportunities for economic growth, food sovereignty and food security. In this study we mainly analyse and compare long-term i.e. for year 2030 climate variability impact on predicted productivity of meat i.e. beef, mutton and poultry for the Kingdom of Saudi Arabia w.r.t three factors i.e. i) climatic-change vulnerability ii) CO2 fertilization and iii) water scarcity and compare the results with two countries of the region i.e. Iraq and Yemen. We do the analysis using data from diverse sources, which was extracted, transformed and integrated before usage. The collective impact of the three factors had an overall negative effect on the production of meat for all the three countries, with adverse impact on Iraq. High similarity was found between CO2 fertilization (effecting animal fodder) and water scarcity i.e. higher than that between production of beef and mutton for the three countries considered. Overall, the three factors do not seem to be favorable for the three Middle-East countries considered. This points to possibility of a vegetarian year 2030 based on dependency on indigenous live-stock population.

Keywords: prediction, animal-source foods, pastures, CO2 fertilization, climatic-change vulnerability, water scarcity

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Authors: Galal H. Senussi, Muamar Benisa, Sanja Vasin

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In our business field today, one of the most important issues for any enterprises is cost minimization and profit maximization. Second issue is how to develop a strong and capable model that is able to give us desired forecasting of these two issues. Many researches deal with these issues using different methods. In this study, we developed a model for multi-criteria production program optimization, integrated with Artificial Neural Network. The prediction of the production cost and profit per unit of a product, dealing with two obverse functions at same time can be extremely difficult, especially if there is a great amount of conflict information about production parameters. Feed-Forward Neural Networks are suitable for generalization, which means that the network will generate a proper output as a result to input it has never seen. Therefore, with small set of examples the network will adjust its weight coefficients so the input will generate a proper output. This essential characteristic is of the most important abilities enabling this network to be used in variety of problems spreading from engineering to finance etc. From our results as we will see later, Feed-Forward Neural Networks has a strong ability and capability to map inputs into desired outputs.

Keywords: project profitability, multi-objective optimization, genetic algorithm, Pareto set, neural networks

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Authors: Adrian-Gabriel Chifu, Sebastien Fournier

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One of the challenges of natural language understanding is to deal with the subjectivity of sentences, which may express opinions and emotions that add layers of complexity and nuance. Sentiment analysis is a field that aims to extract and analyze these subjective elements from text, and it can be applied at different levels of granularity, such as document, paragraph, sentence, or aspect. Aspect-based sentiment analysis is a well-studied topic with many available data sets and models. However, there is no clear definition of what makes a sentence difficult for aspect-based sentiment analysis. In this paper, we explore this question by conducting an experiment with three data sets: ”Laptops”, ”Restaurants”, and ”MTSC” (Multi-Target-dependent Sentiment Classification), and a merged version of these three datasets. We study the impact of domain diversity and syntactic diversity on difficulty. We use a combination of classifiers to identify the most difficult sentences and analyze their characteristics. We employ two ways of defining sentence difficulty. The first one is binary and labels a sentence as difficult if the classifiers fail to correctly predict the sentiment polarity. The second one is a six-level scale based on how many of the top five best-performing classifiers can correctly predict the sentiment polarity. We also define 9 linguistic features that, combined, aim at estimating the difficulty at sentence level.

Keywords: sentiment analysis, difficulty, classification, machine learning

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Authors: Tasir Khan, Yejuan Wang

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The study of extreme rainfall events is very important for flood management in river basins and the design of water conservancy infrastructure. Evaluation of quantiles of annual maximum rainfall (AMRF) is required in different environmental fields, agriculture operations, renewable energy sources, climatology, and the design of different structures. Therefore, the annual maximum rainfall (AMRF) was performed at different stations in Pakistan. Multiple probability distributions, log normal (LN), generalized extreme value (GEV), Gumbel (max), and Pearson type3 (P3) were used to find out the most appropriate distributions in different stations. The L moments method was used to evaluate the distribution parameters. Anderson darling test, Kolmogorov- Smirnov test, and chi-square test showed that two distributions, namely GUM (max) and LN, were the best appropriate distributions. The quantile estimate of a multi-parameter PD offers extreme rainfall through a specific location and is therefore important for decision-makers and planners who design and construct different structures. This result provides an indication of these multi-parameter distribution consequences for the study of sites and peak flow prediction and the design of hydrological maps. Therefore, this discovery can support hydraulic structure and flood management.

Keywords: RAMSE, multiple frequency analysis, annual maximum rainfall, L-moments

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Authors: Nanxi Miao, Junjie Wang

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The discovery of 2D materials with distinct compositions and properties has been a research aim since the report of graphene. One of the latest members of the 2D material family is MXene, which is produced from the topochemical deintercalation of the A layer from a laminate MAX phase. Recently, analogous 2D MBenes (transitional metal borides) have been predicted by theoretical calculations as excellent alternatives in applications such as metal-ion batteries, magnetic devices, and catalysts. However, the practical applications of two-dimensional (2D) transition-metal borides (MBenes) have been severely hindered by the lack of accessible MBenes because of the difficulties in the selective etching of traditional ternary MAB phases with orthorhombic symmetry (ort-MAB). Here, we discover a family of ternary hexagonal MAB (h-MAB) phases and 2D hexagonal MBenes (h-MBenes) by ab initio predictions and experiments. Calculations suggest that the ternary h-MAB phases are more suitable precursors for MBenes than the ort-MAB phases. Based on the prediction, we report the experimental synthesis of h-MBene HfBO by selective removal of in from h-MAB Hf2InB2. The synthesized 2D HfBO delivered a specific capacity of 420 mAh g-1 as an anode material in lithium-ion batteries, demonstrating the potential for energy-storage applications. The discovery of this h-MBene HfBO added a new member to the growing family of 2D materials and provided opportunities for a wide range of novel applications.

Keywords: 2D materials, DFT calculations, high-throughput screening, lithium-ion batteries

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Authors: Rouaz Idriss, Bourahla Nour-Eddine, Kahlouche Farah, Rafa Sid Ali

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The stability of structures made of light-gauge steel depends highly on the contribution of Shear Wall Panel (SWP) systems under horizontal forces due to wind or earthquake loads. Steel plate sheathing is often used with these panels made of cold formed steel (CFS) to improve its shear strength. In order to predict the shear strength resistance, two methods are presented in this paper. In the first method, the steel plate sheathing is modeled with plats strip taking into account only the tension and compression force due to the horizontal load, where both track and stud are modeled according to the geometrical and mechanical characteristics of the specimen used in the experiments. The theoretical background and empirical formulations of this method are presented in this paper. However, the second method is based on a micro modeling of the cold formed steel Shear Wall Panel “CFS-SWP” using Abaqus software. A nonlinear analysis was carried out with an in-plan monotonic load. Finally, the comparison between these two methods shows that the micro modeling with Abaqus gives better prediction of shear resistance of SWP than strips method. However, the latter is easier and less time consuming than the micro modeling method.

Keywords: cold formed steel 'CFS', shear wall panel, strip method, finite elements

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Authors: Nweke Kingsley

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From the times of ancient Greece to modern times, democratic elections have been associated with a higher number of participants. Sequel to this, politicians globally and incumbent governments appear concerned with understanding the personality traits that may assure them of unflinching support by electorates. The study examined how openness to experience predicted electoral behaviour among senior non-teaching employees of Nnamdi Azikiwe University Awka. One hundred and thirty-three non-teaching employees who volunteered were randomly selected for the study. Two instruments were used for data collection: The Electoral Behaviour Scale, and the Openness to Experience dimension of the Personality Trait Inventory. A correlational design was adopted for the study, and the data generated were statistically analyzed using Pearson Product Moment and linear regression statistics. Results revealed that Openness to Experience positively and significantly predicted Electoral Behaviour among senior non-teaching employees of Nnamdi Azikiwe University, Awka. It was recommended that politicians and stakeholders hold town hall meetings and seminars to increase awareness of the electoral perception of electorates with the Openness to Experience trait as this will increase their support and yield successive results during elections.

Keywords: electoral-behaviour, employees, non-teaching, openness-to-experience

Procedia PDF Downloads 63

Authors: Mohd Radzi Hilmi, Mohd Zulfaezal Che Azemin, Khairidzan Mohd Kamal, Azrin Esmady Ariffin, Mohd Izzuddin Mohd Tamrin, Norfazrina Abdul Gaffur, Tengku Mohd Tengku Sembok

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Purpose: The purpose of this study is to predict optical quality changes after pterygium surgery using tissue redness grading. Methods: Sixty-eight primary pterygium participants were selected from patients who visited an ophthalmology clinic. We developed a semi-automated computer program to measure the pterygium fibrovascular redness from digital pterygium images. The outcome of this software is a continuous scale grading of 1 (minimum redness) to 3 (maximum redness). The region of interest (ROI) was selected manually using the software. Reliability was determined by repeat grading of all 68 images and its association with contrast sensitivity function (CSF) and visual acuity (VA) was examined. Results: The mean and standard deviation of redness of the pterygium fibrovascular images was 1.88 ± 0.55. Intra- and inter-grader reliability estimates were high with intraclass correlation ranging from 0.97 to 0.98. The new grading was positively associated with CSF (p<0.01) and VA (p<0.01). The redness grading was able to predict 25% and 23% of the variance in the CSF and the VA respectively. Conclusions: The new grading of pterygium fibrovascular redness can be reliably measured from digital images and show a good correlation with CSF and VA. The redness grading can be used in addition to the existing pterygium grading.

Keywords: contrast sensitivity, pterygium, redness, visual acuity

Procedia PDF Downloads 515

Authors: M. R. Noor El-Din, Marwa R. Mishrif, R. E. Morsi, E. A. El-Sharaky, M. E. Haseeb, Rania T. M. Ghanem

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This paper studies the physical and rheological behaviours of water/in/diesel fuel nanoemulsions prepared by modified low energy method. Twenty of water/in/diesel fuel nanoemulsions were prepared using mixed nonionic surfactants of sorbitan monooleate and polyoxyethylene sorbitan trioleate (MTS) at Hydrophilic-Lipophilic Balance (HLB) value of 10 and a working temperature of 20°C. The influence of the prepared nanoemulsions on the physical properties such as kinematic viscosity, density, and calorific value was studied. Also, nanoemulsion systems were subjected to rheological evaluation. The effect of water loading percentage (5, 6, 7, 8, 9 and 10 wt.%) on rheology was assessed at temperatures range from 20 to 60°C with temperature interval of 10 for time lapse 0, 1, 2 and 3 months, respectively. Results show that all of the sets nanoemulsions exhibited a Newtonian flow character of low-shear viscosity in the range of 132 up to 191 1/s, and followed by a shear-thinning region with yield value (Non-Newtonian behaviour) at high shear rate for all water ratios (5 to 10 wt.%) and at all test temperatures (20 to 60°C) for time ageing up to 3 months. Also, the viscosity/temperature relationship of all nanoemulsions fitted well Arrhenius equation with high correlation coefficients that ascertain their Newtonian behavior.

Keywords: alternative fuel, nanoemulsion, surfactant, diesel fuel

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Authors: Tieling Xing, Jinqiu Yang, Guoqiang Chen

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It is environmentally friendly to use horseradish peroxidase (HRP) instead of the traditional transition metal catalyst for the catalyst of atom transfer radical polymerization (ATRP). Silk fabrics were successfully grafted with hydroxyl-containing acrylate monomer to improve its crease resistance by HRP-catalyzed ATRP method. Taking grafting yield as the evaluation index, single factor tests revealed that the optimum grafting reaction condition was as follow: monomer mass fraction 120-210%(o.w.f), HRP concentration 360-480U/mL, molar ratio of HRP to NaAsc 1:150, reaction temperature 50-60℃, reaction time 24h. Raman spectra showed hydroxyl-containing acrylate monomer were successfully grafted on silk fabrics. SEM figures indicated the surface of grafted silk became rougher, and graft copolymer was distributed evenly on the surface of silk fiber. The crease-resistant recovery property of grafted silk fabric was greatly improved, especially in wet crease recovery angle. The result showed hydroxyl-containing acrylate monomer can be successfully grafted onto silk fabric based on HRP-catalyzed ATRP method.

Keywords: atom transfer radical polymerization, catalysis, horseradish peroxidase, hydroxyl-containing acrylate monomer

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Authors: Rafia Rafique, Mutmina Zainab

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The present study investigated the relationship between fear of negative evaluation (FNE), social support and well-being in people with Vitiligo. It was hypothesized that low level of FNE and greater social support is likely to predict well-being. It was also hypothesized that social support is likely to moderate the relationship between FNE and well-being. Correlational research design was used for the present study. Non-probability purposive sampling technique was used to collect a sample (N=122) of people with Vitiligo. Hierarchical Moderated Regression analysis was used to test prediction and moderation. Brief Fear of Negative Evaluation Scale, Multidimensional Scale of Perceived Social Support (MSPSS) and Mental Health Continuum-Short form (MHC-SF) were used to evaluate the study variables. Fear of negative evaluation negatively predicted well-being (emotional and psychological). Social support from significant others and friends predicted social well-being. Social Support from family predicted emotional and psychological well-being. It was found that social support from significant others moderated the relationship between FNE and emotional well-being and social support from family moderated the relationship between FNE and social well-being. Dermatologists treating people with Vitiligo need to educate them and their families about the buffering role of social support (family and significant others). Future studies need to focus on other important mediating factors that can possibly explain the relationship between fear of negative evaluation and wellbeing.

Keywords: fear of negative evaluation, hierarchical moderated regression, vitiligo, well-being

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Authors: Shafiullah Soomro

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Active contour is one of the image segmentation techniques and its goal is to capture required object boundaries within an image. In this paper, we propose a novel image segmentation method by using an active contour method based on anisotropic diffusion feature enhancement technique. The traditional active contour methods use only pixel information to perform segmentation, which produces inaccurate results when an image has some noise or complex background. We use Perona and Malik diffusion scheme for feature enhancement, which sharpens the object boundaries and blurs the background variations. Our main contribution is the formulation of a new SPF (signed pressure force) function, which uses global intensity information across the regions. By minimizing an energy function using partial differential framework the proposed method captures semantically meaningful boundaries instead of catching uninterested regions. Finally, we use a Gaussian kernel which eliminates the problem of reinitialization in level set function. We use several synthetic and real images from different modalities to validate the performance of the proposed method. In the experimental section, we have found the proposed method performance is better qualitatively and quantitatively and yield results with higher accuracy compared to other state-of-the-art methods.

Keywords: active contours, anisotropic diffusion, level-set, partial differential equations

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Authors: Urvee B. Trivedi, U. D. Dalal

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As wireless communication services grow quickly; the seriousness of spectrum utilization has been on the rise gradually. An emerging technology, cognitive radio has come out to solve today’s spectrum scarcity problem. To support the spectrum reuse functionality, secondary users are required to sense the radio frequency environment, and once the primary users are found to be active, the secondary users are required to vacate the channel within a certain amount of time. Therefore, spectrum sensing is of significant importance. Once sensing is done, different prediction rules apply to classify the traffic pattern of primary user. Primary user follows two types of traffic patterns: periodic and stochastic ON-OFF patterns. A cognitive radio can learn the patterns in different channels over time. Two types of classification methods are discussed in this paper, by considering edge detection and by using autocorrelation function. Edge detection method has a high accuracy but it cannot tolerate sensing errors. Autocorrelation-based classification is applicable in the real environment as it can tolerate some amount of sensing errors.

Keywords: cognitive radio (CR), probability of detection (PD), probability of false alarm (PF), primary user (PU), secondary user (SU), fast Fourier transform (FFT), signal to noise ratio (SNR)

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Authors: Muhammad Naeem Mushtaq, Muhammad Arshad, Shahid Majeed

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Maize is known as queen of cereals because of its highest genetic yield potential and multipurpose characteristics in human being and animal diet. Maize crop visited by many major, minor, visitors and sporadic insect pests. This study was conducted during 2014 to evaluate the richness and evenness of these insect pests and their interaction with metrological conditions at University of Agriculture, Faisalabad. In this experiment, two localities were selected; one was treated with pesticide and second was untreated. Maize field visited by many insect pests. Those insect pests were collected by using three collection method: sweep net, pitfall trap and plant inspection. The data was collected weekly interval from August to October and statistically analyzed by using Shannon Index which showed the results of insect pest richness and evenness. The value of Shannon Index was higher with the increase in number of species and abundance of insects. Camponotus nearcticus was most abundant in sweep net and pitfall trap method while Rhopalosiphum maidis was abundant in plant inspection method. Temperature was negatively co-relate with the insect population in all three collection methods while the relative humidity and rainfall had varying results.

Keywords: abundance, evenness, maize, richness

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Authors: Churamani Pokhrel, C. B. Jha, S. R. Niraula, P. R. Pokharel

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Human identification is one of the most challenging subjects that man has confronted. The determination of adult sex and stature are two of the four key factors (sex, stature, age, and race) in identification of an individual. Craniofacial and odontometric parameters are important tools for forensic anthropologists when it is not possible to apply advanced techniques for identification purposes. The present study provides anthropometric correlation of the parameters with stature and gender and also devises regression formulae for reconstruction of stature. A total of 312 Nepalese students with equal distribution of sex i.e., 156 male and 156 female students of age 18-35 years were taken for the study. Total of 10 parameters were measured (age, sex, stature, head circumference, head length, head breadth, facial height, bi-zygomatic width, mesio-distal canine width and inter-canine distance of both maxilla and mandible). Co-relation and regression analysis was done to find the association between the parameters. All parameters were found to be greater in males than females and each was found to be statistically significant. Out of total 312 samples, the best regressor for the determination of stature was head circumference and mandibular inter-canine width and that for gender was head circumference and right mandibular teeth. The accuracy of prediction was 83%. Regression equations and analysis generated from craniofacial and odontometric parameters can be a supplementary approach for the estimation of stature and gender when extremities are not available.

Keywords: craniofacial, gender, odontometric, stature

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Authors: Ahmet Kayabasi, Ali Akdagli

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In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated with the help of IE3D™ based on method of moment (MoM). The ANN, ANFIS and SVM models for computing the resonant frequency were then built by considering the simulation data. 124 simulated ACMAs were utilized for training and the remaining 20 ACMAs were used for testing the ANN, ANFIS and SVM models. The performance of the ANN, ANFIS and SVM models are compared in the training and test process. The average percentage errors (APE) regarding the computed resonant frequencies for training of the ANN, ANFIS and SVM were obtained as 0.457%, 0.399% and 0.600%, respectively. The constructed models were then tested and APE values as 0.601% for ANN, 0.744% for ANFIS and 0.623% for SVM were achieved. The results obtained here show that ANN, ANFIS and SVM methods can be successfully applied to compute the resonant frequency of ACMAs, since they are useful and versatile methods that yield accurate results.

Keywords: a-shaped compact microstrip antenna, artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), support vector machine (SVM)

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Authors: Mahtab Davari, Charles Edward Okon, Somayeh Aghanavesi

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Every institute of learning is usually interested in the performance of enrolled students. The level of these performances determines the approach an institute of study may adopt in rendering academic services. The focus of this paper is to evaluate students' academic performance in given courses of study using machine learning methods. This study evaluated various supervised machine learning classification algorithms such as Logistic Regression (LR), Support Vector Machine, Random Forest, Decision Tree, K-Nearest Neighbors, Linear Discriminant Analysis, and Quadratic Discriminant Analysis, using selected features to predict study performance. The accuracy, precision, recall, and F1 score obtained from a 5-Fold Cross-Validation were used to determine the best classification algorithm to predict students’ performances. SVM (using a linear kernel), LDA, and LR were identified as the best-performing machine learning methods. Also, using the LR model, this study identified students' educational habits such as reading and paying attention in class as strong determinants for a student to have an above-average performance. Other important features include the academic history of the student and work. Demographic factors such as age, gender, high school graduation, etc., had no significant effect on a student's performance.

Keywords: student performance, supervised machine learning, classification, cross-validation, prediction

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Authors: Leila Momenzadeh, Alexander V. Evteev, Elena V. Levchenko, Tanvir Ahmed, Irina Belova, Graeme Murch

Abstract:

In this work, the phonon thermal conductivity of f.c.c. Al is investigated in detail in the temperature range 100 – 900 K within the framework of equilibrium molecular dynamics simulations making use of the Green-Kubo formalism and one of the most reliable embedded-atom method potentials. It is found that the heat current auto-correlation function of the f.c.c. Al model demonstrates a two-stage temporal decay similar to the previously observed for f.c.c Cu model. After the first stage of decay, the heat current auto-correlation function of the f.c.c. Al model demonstrates a peak in the temperature range 100-800 K. The intensity of the peak decreases as the temperature increases. At 900 K, it transforms to a shoulder. To describe the observed two-stage decay of the heat current auto-correlation function of the f.c.c. Al model, we employ decomposition model recently developed for phonon-mediated thermal transport in a monoatomic lattice. We found that the electronic contribution to the total thermal conductivity of f.c.c. Al dominates over the whole studied temperature range. However, the phonon contribution to the total thermal conductivity of f.c.c. Al increases as temperature decreases. It is about 1.05% at 900 K and about 12.5% at 100 K.

Keywords: aluminum, gGreen-Kubo formalism, molecular dynamics, phonon thermal conductivity

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Authors: Innocent Pangapanga, Eric Mungatana

Abstract:

Fall armyworm (FAW) (Spodoptera frugiperda), an invasive lepidopteran pest, has caused substantial yield loss since its first detection in September 2016, thereby threatening the farm productivity food security and poverty reduction initiatives in Malawi. Several stakeholders, including households, have adopted chemical pesticides to control FAW without accounting for its costs on welfare, health and the environment. Thus, this study has used panel data endogenous switching regression model to investigate the impact of FAW and the integrated pest management (IPM) –related practices on-farm productivity and food security. The study finds that FAW substantively reduces farm productivity by seven (7) percent and influences the adoption of IPM –related practices, namely, intercropping, mulching, and agroforestry, by 6 percent, ceteris paribus. Interestingly, multiple adoptions of the IPM -related practices noticeably increase farm productivity by 21 percent. After accounting for potential endogeneity through the endogenous switching regression model, the IPM practices further demonstrate tenfold more improvement on food security, implying the role of the IPM –related practices in containing the effect of FAW at the household level.

Keywords: hunger, invasive fall army worms, integrated pest management practices, farm productivity, endogenous switching regression

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Authors: Zainal Arifin, Mohammad Saeri

Abstract:

The purpose of this study is to determine the efficiency of irrigation use on the growth and yield of two varieties of rice. Water management research on rainfed lowland rice was carried out in dry season (DS I) 2016 in an area of 10,000 m2 in Bunbarat Village, Rubaru Subdistrict, Sumenep Regency. The research was randomized block design factorial with 8 treatments and repeated 3 times, ie Factor I (varieties): (a) Inpago 9, and (b) Sidenuk; factor II (irrigation): (a) Alternate Wetting and Drying, (b) intermittent, (c) submerged, and (d) inundated. The results showed that dominant weed species such as purslane (Portulaca oleraceae L.) and barnyard grass (Echinochloa crusgalli) were mostly found in rice cultivation with Alternate Wetting and Drying, intermittent and submerged irrigation treatment, while the lowest was inundated irrigation. The use of Sidenuk variety with Alternate Wetting and Drying irrigation yielded 5.7 t/ha dry grain harvest (dgh) and was not significantly different from the inundated watering using the Sidenuk variety (6.2 t/ha dgh). With Alternate Wetting and Drying irrigation technique, water use is more efficient as much as 1,503 m3/ha so as to produce 1 kg of grain, it needs 459 liters of water compared to inundated irrigation (665 liters/kg of grain). Results of analysis of rice farming Sidenuk variety with Alternate Wetting and Drying irrigation has the highest B/C ratio (2.56) so that economically feasible.

Keywords: water management, varieties, rice, dry season, rainfed lowland

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Authors: Murast Dicleli, Ali SalemMilani

Abstract:

In this paper, a summary of analytical and experimental studies into the behavior of a new hysteretic damper, designed for seismic protection of structures is presented. The Multi-directional Torsional Hysteretic Damper (MRSD) is a patented invention in which a symmetrical arrangement of identical cylindrical steel cores is so configured as to yield in torsion while the structure experiences planar movements due to earthquake shakings. The new device has certain desirable properties. Notably, it is characterized by a variable and controllable-via-design post-elastic stiffness. The mentioned property is a result of MRSD’s kinematic configuration which produces this geometric hardening, rather than being a secondary large-displacement effect. Additionally, the new system is capable of reaching high force and displacement capacities, shows high levels of damping, and very stable cyclic response. The device has gone through many stages of design refinement, multiple prototype verification tests and development of design guide-lines and computer codes to facilitate its implementation in practice. Practicality of the new device, as offspring of an academic sphere, is assured through extensive collaboration with industry in its final design stages, prototyping and verification test programs.

Keywords: seismic, isolation, damper, adaptive stiffness

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Authors: Niranjan Koirala, Sumangala Darsandhari, Hye Jin Jung, Jae Kyung Sohng

Abstract:

Sakuranetin, an antifungal agent and genkwanin, an anti-inflammatory agent, are flavonoids with several potential pharmaceutical applications. To produce such valuable flavonoids in large quantity, an Escherichia coli cell factory has been created. E. coli harboring O-methyltransferase (SaOMT2) derived from Streptomyces avermitilis was employed for regiospecific methylation of naringenin and apigenin. In order to increase the production via biotransformation, metK gene was overexpressed and the conditions were optimized. The maximum yield of sakuranetin and genkwanin under optimized conditions was 197 µM and 170 µM respectively when 200 µM of naringenin and apigenin were supplemented in the separate cultures. Furthermore, sakuranetin was purified in large scale and used as a substrate for in vitro glycosylation by YjiC to produce glucose and galactose derivatives of sakuranetin for improved solubility. We also found that unlike naringenin, sakuranetin effectively inhibits α-melanocyte stimulating hormone (α-MSH)-stimulated melanogenesis in B16F10 melanoma cells. In addition, genkwanin more potently inhibited angiogenesis than apigenin. Based on our findings, we speculate that these compounds warrant further investigation in vivo as potential new therapeutic anti-carcinogenic, anti-melanogenic and anti-angiogenic agents.

Keywords: anti-carcinogenic, anti-melanogenic, glycosylation, methylation

Procedia PDF Downloads 610