Search results for: time truncated experiment

Authors: Shahin A. Abdel-Naby, James P. Colgan, Michael S. Pindzola

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A time-dependent close-coupling method is developed to calculate a total, double and triple autoionization rates for hollow atomic ions of four-electron systems. This work was motivated by recent observations of the four-electron Auger process in near K-edge photoionization of C+ ions. The time-dependent close-coupled equations are solved using lattice techniques to obtain a discrete representation of radial wave functions and all operators on a four-dimensional grid with uniform spacing. Initial excited states are obtained by relaxation of the Schrodinger equation in imaginary time using a Schmidt orthogonalization method involving interior subshells. The radial wave function grids are partitioned over the cores on a massively parallel computer, which is essential due to the large memory requirements needed to store the coupled-wave functions and the long run times needed to reach the convergence of the ionization process. Total, double, and triple autoionization rates are obtained by the propagation of the time-dependent close-coupled equations in real-time using integration over bound and continuum single-particle states. These states are generated by matrix diagonalization of one-electron Hamiltonians. The total autoionization rates for each L excited state is found to be slightly above the single autoionization rate for the excited configuration using configuration-average distorted-wave theory. As expected, we find the double and triple autoionization rates to be much smaller than the total autoionization rates. Future work can be extended to study electron-impact triple ionization of atoms or ions. The work was supported in part by grants from the American University of Sharjah and the US Department of Energy. Computational work was carried out at the National Energy Research Scientific Computing Center (NERSC) in Berkeley, California, USA.

Keywords: hollow atoms, autoionization, auger rates, time-dependent close-coupling method

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Authors: Asghar Abbas, Rao Zahid Abbas, Muhammad Asif Raza, Kashif Hussain

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In the current experiment, in vitro anticoccidial potential of Vitis venifera (grape seed) extract was evaluated. For this purpose, an in vitro sporulation inhibition assay was used. Collected oocysts of different Eimeria species of chicken were exposed to six different concentrations (w/v) of Vitis venifera extract (TAE) in 10% dimethylsulphoxide solution (DMSO). Dimethylsulphoxide (DMSO) and potassium dichromate solution (K₂Cr₂O₇) served as control groups. Results of the study revealed that Vitis venifera extract (TAE) showed an inhibitory effect on sporulation (%) and damage (%) of Eimeria oocysts in a dose-dependent manner as compared to both control groups. Vitis venifera extract also damaged the morphology of oocysts in terms of shape, size, and number of sporocysts.

Keywords: Vitis venifera, in vitro, Eimeria, oocysts

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Authors: Jing Hu, Dong Yang

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With the increasingly difficult development and operating environment of exploration, there are many new challenges and difficulties in developing and exploiting oil and gas resources. These include the ability to dynamically monitor wells and provide data and assurance for the completion and production of high-cost and complex wells. A key technology in providing these assurances and maximizing oilfield profitability is real-time permanent reservoir monitoring. The emergence of optical fiber sensing systems has gradually begun to replace traditional electronic systems. Traditional temperature sensors can only achieve single-point temperature monitoring, but fiber optic sensing systems based on the Bragg grating principle have a high level of reliability, accuracy, stability, and resolution, enabling cost-effective monitoring, which can be done in real-time, anytime, and without well intervention. Continuous data acquisition is performed along the entire wellbore. The integrated package with the downhole pressure gauge, packer, and surface system can also realize real-time dynamic monitoring of the pressure in some sections of the downhole, avoiding oil well intervention and eliminating the production delay and operational risks of conventional surveys. Real-time information obtained through permanent optical fibers can also provide critical reservoir monitoring data for production and recovery optimization.

Keywords: PDHM, optical fiber, coiled tubing, photoelectric composite cable, digital-oilfield

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Authors: S. Hellam, Y. Oulahrir, F. El Mounchid, A. Sadiq, S. Mbarki

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In this paper, we propose a method for three-dimensional (3-D)-model indexing based on defining a new descriptor, which we call new descriptor using spherical harmonics. The purpose of the method is to minimize, the processing time on the database of objects models and the searching time of similar objects to request object. Firstly we start by defining the new descriptor using a new division of 3-D object in a sphere. Then we define a new distance which will be used in the search for similar objects in the database.

Keywords: 3D indexation, spherical harmonic, similarity of 3D objects, measurement similarity

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Authors: Violina R. Angelova, Vanja I. Akova, Stefan V. Krustev, Krasimir I. Ivanov

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A field study was conducted to evaluate the efficacy of safflower plant for phytoremediation of contaminated soils. The experiment was performed on an agricultural fields contaminated by the Non-Ferrous-Metal Works near Plovdiv, Bulgaria. The concentrations of Pb, Zn and Cd in safflower (roots, stems, leaves and seeds), safflower oil and meal were determined. A correlation was found between the quantity of the mobile forms and the uptake of Pb, Zn and Cd by the safflower seeds. Safflower is a plant which is tolerant to heavy metals and can be grown on contaminated soils, and which can be referred to the hyperaccumulators of cadmium and the accumulators of lead and zinc, and can be successfully used in the phytoremediation of heavy metal contaminated soils. The processing of seeds to oil and using the obtained oil for nutritional purposes will greatly reduce the cost of phytoremediation. The possibility of further industrial processing will make safflower economically interesting crops for farmers of phytoremediation technology.

Keywords: heavy metals, phytoremediation, polluted soils, safflower

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Authors: Matthias Walluch, José Alberto Rodríguez, Christopher Giehl, Gunther Arnold, Daniela Ehgartner

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Dynamic mechanical analysis (DMA) is a powerful method to characterize viscoelastic properties and phase transitions for a wide range of materials. It is often used to characterize polymers and their temperature-dependent behavior, including thermal transitions like the glass transition temperature Tg, via determination of storage and loss moduli in tension (Young’s modulus, E) and shear or torsion (shear modulus, G) or other testing modes. While production and application temperatures for polymers are often limited to several hundred degrees, material properties of glasses usually require characterization at temperatures exceeding 600 °C. This contribution highlights a high temperature setup for rotational and oscillatory rheometry as well as for DMA in different modes. The implemented standard convection oven enables the characterization of glass in different loading modes at temperatures up to 950 °C. Three-point bending, tension and torsional measurements on different glasses, with E and G moduli as a function of frequency and temperature, are presented. Additional tests include superimposing several frequencies in a single temperature sweep (“multiwave”). This type of test results in a considerable reduction of the experiment time and allows to evaluate structural changes of the material and their frequency dependence. Furthermore, DMA in torsion and tension was performed to determine the complex Poisson’s ratio as a function of frequency and temperature within a single test definition. Tests were performed in a frequency range from 0.1 to 10 Hz and temperatures up to the glass transition. While variations in the frequency did not reveal significant changes of the complex Poisson’s ratio of the glass, a monotonic increase of this parameter was observed when increasing the temperature. This contribution outlines the possibilities of DMA in bending, tension and torsion for an extended temperature range. It allows the precise mechanical characterization of material behavior from room temperature up to the glass transition and the softening temperature interval. Compared to other thermo-analytical methods, like Dynamic Scanning Calorimetry (DSC) where mechanical stress is neglected, the frequency-dependence links measurement results (e.g. relaxation times) to real applications

Keywords: dynamic mechanical analysis, oscillatory rheometry, Poisson's ratio, solid glass, viscoelasticity

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Authors: Oral Lacin, Turan Calban, Fatih Sevim, Taner Celik

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In this study, Pb²⁺ uptake by the hydroxyapatite nanopowders (n-Hap) from aqueous solutions was investigated by using batch adsorption techniques. The adsorption equilibrium studies were carried out as a function of contact time, adsorbent dosage, pH, temperature, and initial Pb²⁺ concentration. The results showed that the equilibrium time of adsorption was achieved within 60 min, and the effective pH was selected to be 5 (natural pH). The maximum adsorption capacity of Pb²⁺ on n-Hap was found as 565 mg.g^-1. It is believed that the results obtained for adsorption may provide a background for the detailed mechanism investigations and the pilot and industrial scale applications.

Keywords: nanopowders, hydroxyapatite, heavy metals, adsorption

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Authors: Aleksandar Dedic, Dusko Salemovic, Milorad Danilovic, Radomir Kuzmanovic

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This paper takes into consideration the influence of bonding energy of water on energy demand of vacuum wood drying using the specific method of obtaining sorption isotherms. The experiment was carried out on oak wood at vacuum pressures of: 0.7 bar, 0.5bar and 0.3bar. The experimental work was done to determine a mathematical equation between the moisture content and energy of water-bonding. This equation helps in finding the average amount of energy of water-bonding necessary in calculation of energy consumption by use of the equation of heat balance in real drying chambers. It is concluded that the energy of water-bonding is large enough to be included into consideration. This energy increases at lower values of moisture content, when drying process approaches to the end, and its average values are lower on lower pressure.

Keywords: bonding energy, drying, isosters, oak, vacuum

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Authors: Nassima Noufail, Sara Bouhali

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In this work, we develop a semi-supervised solution for the purpose of action detection in videos and propose an efficient algorithm for video segmentation. The approach is divided into video segmentation, feature extraction, and classification. In the first part, a video is segmented into clips, and we used the K-means algorithm for this segmentation; our goal is to find groups based on similarity in the video. The application of k-means clustering into all the frames is time-consuming; therefore, we started by the identification of transition frames where the scene in the video changes significantly, and then we applied K-means clustering into these transition frames. We used two image filters, the gaussian filter and the Laplacian of Gaussian. Each filter extracts a set of features from the frames. The Gaussian filter blurs the image and omits the higher frequencies, and the Laplacian of gaussian detects regions of rapid intensity changes; we then used this vector of filter responses as an input to our k-means algorithm. The output is a set of cluster centers. Each video frame pixel is then mapped to the nearest cluster center and painted with a corresponding color to form a visual map. The resulting visual map had similar pixels grouped. We then computed a cluster score indicating how clusters are near each other and plotted a signal representing frame number vs. clustering score. Our hypothesis was that the evolution of the signal would not change if semantically related events were happening in the scene. We marked the breakpoints at which the root mean square level of the signal changes significantly, and each breakpoint is an indication of the beginning of a new video segment. In the second part, for each segment from part 1, we randomly selected a 16-frame clip, then we extracted spatiotemporal features using convolutional 3D network C3D for every 16 frames using a pre-trained model. The C3D final output is a 512-feature vector dimension; hence we used principal component analysis (PCA) for dimensionality reduction. The final part is the classification. The C3D feature vectors are used as input to a multi-class linear support vector machine (SVM) for the training model, and we used a multi-classifier to detect the action. We evaluated our experiment on the UCF101 dataset, which consists of 101 human action categories, and we achieved an accuracy that outperforms the state of art by 1.2%.

Keywords: video segmentation, action detection, classification, Kmeans, C3D

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Authors: Abhishek Jha, Manoj Kumar

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This paper proposes a new type of two wheels differential type odometry to estimate the next position and orientation of mobile robots. The proposed odometry is composed for two independent wheels with respective encoders. The two wheels rotate independently, and the change is determined by the difference in the velocity of the two wheels. Angular velocities of the two wheels are measured by rotary encoders. A mathematical model is proposed for the mobile robots to precisely move towards the goal. Using measured values of the two encoders, the current displacement vector of a mobile robot is calculated by kinematics of the mathematical model. Using the displacement vector, the next position and orientation of the mobile robot are estimated by proposed odometry. Result of simulator experiment by the developed odometry is shown.

Keywords: mobile robot, odometry, unicycle, differential type, encoders, infrared range sensors, kinematic model

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Authors: YuLung Wu, YuTien Wu, ShuMey Yu

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Game-based learning can enhance the learning motivation of students and provide a means for them to learn through playing games. This study used augmented reality technology to develop an interactive card game as a game-based teaching aid for delivering elementary school science course content with the aim of enhancing student learning processes and outcomes. Through playing the proposed card game, students can familiarize themselves with appearance, features, and foraging behaviors of insects. The system records the actions of students, enabling teachers to determine their students’ learning progress. In this study, 37 students participated in an assessment experiment and provided feedback through questionnaires. Their responses indicated that they were significantly more motivated to learn after playing the game, and their feedback was mostly positive.

Keywords: game-based learning, learning motivation, teaching aid, augmented reality

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Authors: Nitin Lahkar, Rishiraj Goswami

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“Oil Well Logging” or the practice of making a detailed record (a well log) of the geologic formations penetrated by a borehole is an important practice in the Oil and Gas industry. Although a lot of research has been undertaken in this field, some basic limitations still exist. One of the main arenas or venues where plethora of problems arises is in logistically challenged areas. Accessibility and availability of efficient manpower, resources and technology is very time consuming, restricted and often costly in these areas. So, in this regard, the main challenge is to decrease the Non Productive Time (NPT) involved in the conventional logging process. The thought for the solution to this problem has given rise to a revolutionary concept called the “Robotic Logging Technology”. Robotic logging technology promises the advent of successful logging in all kinds of wells and trajectories. It consists of a wireless logging tool controlled from the surface. This eliminates the need for the logging truck to be summoned which in turn saves precious rig time. The robotic logging tool here, is designed such that it can move inside the well by different proposed mechanisms and models listed in the full paper as TYPE A, TYPE B and TYPE C. These types are classified on the basis of their operational technology, movement and conditions/wells in which the tool is to be used. Thus, depending on subsurface conditions, energy sources available and convenience the TYPE of Robotic model will be selected. Advantages over Conventional Logging Techniques: Reduction in Non-Productive time, lesser energy requirements, very fast action as compared to all other forms of logging, can perform well in all kinds of well trajectories (vertical/horizontal/inclined).

Keywords: robotic logging technology, innovation, geology, geophysics

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Authors: Pramod Kumar, A. V. N. Swamy, C. V. Sowjanya, C. V. Ramachandra Murthy

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Biosorption is one of the effective methods for the removal of heavy metal ions from aqueous solutions. Results are presented showing the sorption of Pb(II) from solutions by biomass of commonly available marine algae Chlorella sp. The ability of marine algae Chlorella pyrenoidosa to remove heavy metal ion (Pb(II)) from aqueous solutions has been studied in this work. The biosorption properties of the biosorbent like equilibrium agitation time, optimum pH, temperature and initial solute concentration were investigated on metal uptake by showing respective profiles. The maximum metal uptake was found to be 10.27 mg/g. To achieve this metal uptake, the optimum conditions were found to be 30 min as equilibrium agitation time, 4.6 as optimum pH, 60 ppm of initial solute concentration. Lead concentration is determined by atomic absorption spectrometer. The process was found to be well fitted for pseudo-second order kinetics.

Keywords: biosorption, heavy metal ions, agitation time, metal uptake, aqueous solution

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Authors: Susanne Fridsten, Kristina Hellman, Anders Sundin, Lennart Blomqvist

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Background: Patients diagnosed with locally advanced cervical carcinoma are treated with definitive concomitant chemo-radiotherapy. Treatment failure occurs in 30-50% of patients with very poor prognoses. The treatment is standardized with risk for both over-and undertreatment. Consequently, there is a great need for biomarkers able to predict therapy outcomes to allow for individualized treatment. Aim: To explore the role of T2- and diffusion-weighted magnetic resonance imaging (MRI) for early prediction of therapy outcome and the optimal time point for assessment. Methods: A pilot study including 15 patients with cervical carcinoma stage IIB-IIIB (FIGO 2009) undergoing definitive chemoradiotherapy. All patients underwent MRI four times, at baseline, 3 weeks, 5 weeks, and 12 weeks after treatment started. Tumour size, size change (∆size), visibility on diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) and change of ADC (∆ADC) at the different time points were recorded. Results: 7/15 patients relapsed during the study period, referred to as "poor prognosis", PP, and the remaining eight patients are referred to "good prognosis", GP. The tumor size was larger at all time points for PP than for GP. The ∆size between any of the four-time points was the same for PP and GP patients. The sensitivity and specificity to predict prognostic group depending on a remaining tumor on DWI were highest at 5 weeks and 83% (5/6) and 63% (5/8), respectively. The combination of tumor size at baseline and remaining tumor on DWI at 5 weeks in ROC analysis reached an area under the curve (AUC) of 0.83. After 12 weeks, no remaining tumor was seen on DWI among patients with GP, as opposed to 2/7 PP patients. Adding ADC to the tumor size measurements did not improve the predictive value at any time point. Conclusion: A large tumor at baseline MRI combined with a remaining tumor on DWI at 5 weeks predicted a poor prognosis.

Keywords: chemoradiotherapy, diffusion-weighted imaging, magnetic resonance imaging, uterine cervical carcinoma

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Authors: Hilary Rutto

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Leaching with acids are the most commonly reagents used to remove copper ions from its copper ores. It is important that the process conditions are optimized to improve the leaching efficiency. In the present study the effects of pH, oxidizing agent (hydrogen peroxide), stirring speed, solid to liquid ratio and acid concentration on the leaching of copper ions from it ore were investigated using a pH Stat apparatus. Copper ions were analyzed at the end of each experiment using Atomic Absorption (AAS) machine. Results showed that leaching efficiency improved with an increase in acid concentration, stirring speed, oxidizing agent, pH and decreased with an increase in the solid to liquid ratio.

Keywords: leaching, copper, oxidizing agent, pH stat apparatus

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Authors: D. Artamonov, A. Tsibulnikova, I. Samusev, V. Bryukhanov, A. Kozhevnikov

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The synthesis and luminescent properties of Yb₂O₃, Nd₂O₃@Bi₂O₃ complex with upconversion generation are discussed in this work. The obtained samples were measured in the visible region of the spectrum under excitation with a wavelength of 980 nm. The studies showed that the obtained complexes have a high degree of stability and intense luminescence in the wavelength range of 400-750 nm. Consideration of the time dependence of the intensity of the upconversion luminescence allowed us to conclude that the enhancement of the intensity occurs in the time interval from 5 to 30 min, followed by the appearance of a stationary mode.

Keywords: lasers, luminescence, upconversion photonics, rare earth metals

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Authors: Jens Ehm

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Manufacturing in supply chains requires an efficient organisation of production and transport processes in order to guarantee the supply of all partners within the chain with the material that is needed for the reliable fulfilment of tasks. If one partner is not able to supply products for a certain period, these products might be missing as the working material for the customer to perform the next manufacturing step, potentially as supply for further manufacturing steps. This way, local disruptions can influence the whole supply chain. In order to avoid material shortages, an efficient scheduling of tasks is necessary. However, the occurrence of unexpected disruptions cannot be eliminated, so that a modification of the schedule should be arranged as fast as possible. This paper discusses the challenges for the implementation of real-time scheduling and control methods and presents a graph-based approach that enables the integrated scheduling of production and transport processes for multiple supply chain partners and offers the potential for quick adaptations to parts of the initial schedule.

Keywords: production, logistics, integrated scheduling, real-time scheduling

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Authors: Orose Rugchati, Sarawut Wattanawongpitak

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The Chainat 1 variety (CN1) of rice, which generally has high amylose starch, is distributed in the lower part of Northern Thailand. CN1 rice starch can be used in both food and non-food products. In this research, the CN1 rice starch from the wet-milling process was prepared by Pre-Gelatinization (Heat-Moisture Treatments, HMT) under different conditions: percentage of moisture contents (20% and 30%) and duration time in minutes (0, 30, 60, and 90) at a specific temperature 110°C. The physicochemical characteristics of CN1 rice starch modification, such as amylose content, viscosity, swelling, and solubility property, were evaluated and compared with native CN1 rice starch. The results showed that modification CN1 rice starch tends to have some characteristics better than native starch. The appearance color and starch granule of modified CN1 by HMT have more effective characteristics than native starch when increased duration time. The duration time and moisture content are significant factors to the CN1 starch characteristic by HMT. Moreover, physical modification of CN1 starch by HMT can be described as a modified rice starch providing in many applications and the advantage of biodegradability development.

Keywords: physicochemical characteristics, physical modification, pre-gelatinization, Heat-Moisture Treatments, rice starch, Chainat 1 variety (CN1)

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Authors: J. Winkler, S. Chovancová

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The article deals with the relation between rainfall in selected months and subsequent weed infestation of spring barley. The field experiment was performed at Mendel University agricultural enterprise in Žabčice, Czech Republic. Weed infestation was measured in spring barley vegetation in years 2004 to 2012. Barley was grown in three tillage variants: conventional tillage technology (CT), minimization tillage technology (MT), and no tillage (NT). Precipitation was recorded in one-day intervals. Monthly precipitation was calculated from the measured values in the months of October through to April. The technique of canonical correspondence analysis was applied for further statistical processing. 41 different species of weeds were found in the course of the 9-year monitoring period. The results clearly show that precipitation affects the incidence of most weed species in the selected months, but acts differently in the monitored variants of tillage technologies.

Keywords: weeds, precipitation, tillage, weed infestation forecast

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Authors: Tejush Badal, Sanaa Alwidian

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Class diagrams are useful tools within the Unified Modelling Language (UML) to model and visualize the relationships between, and properties of objects within a system. As a system evolves over time and space (e.g., products), a series of models with several commonalities and variabilities create what is known as a model family. In circumstances where there are several versions of a model, examining each model individually, becomes expensive in terms of computation resources. To avoid performing redundant operations, this paper proposes an approach for representing a family of class diagrams into Union Models to represent model families using a single generic model. The paper aims to analyze and reason about a family of class diagrams using union models as opposed to individual analysis of each member model in the family. The union algorithm provides a holistic view of the model family, where the latter cannot be otherwise obtained from an individual analysis approach, this in turn, enhances the analysis performed in terms of speeding up the time needed to analyze a family of models together as opposed to analyzing individual models, one model at a time.

Keywords: analysis, class diagram, model family, unified modeling language, union model

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Authors: Asghar Ebrahimzadeh, Sattar Malekian, Mohammad Ali Aazami, Mohammad Bagher Hassanpouraghdam

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Roses are of main ornamental flowers worldwide. Rosa damascena Mill., besides being an ornamental plant, has major pharmaceutical, cosmetic and fragrance applications. Traditional propagation methods of the plant are using suckers, cutting and grafting. In the present experiment, we used the different explants (leaf section, petioles and nodal cutting) for the optimization of this high-valued ornamental from a native clonal plant. Diverse explants were acquired from mature plants during the growing season and were planted on MS medium supplemented with different hormonal combinations. 70% alcohol and sodium hypochloride were utilized for the surface sterilization. For proliferation, BAP and BA (1-5 mg L-1) and NAA (1-2 mg L-1) were tested. The highest proliferation rate was afforded from MS medium supplemented with 1.5 mg L-1 BA and 5 mg L-1 BAP. Callogenesis from leaf samples and petioles was the best with 1/2 MS medium enriched with 1mg L-1 BAP and 4 mg L-1 2,4-D. Rooting was occurred with the highest frequency in a medium containing 0.1 mg L-1 IBA.

Keywords: Rosa damascene, micropropagation, petiole, IBA, BAP

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Authors: Simon Keller, Rainer Mueller

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Continuous range queries are a common means to handle mobile clients in high-density areas. Most existing approaches focus on settings in which the range queries for location-based services are more or less static, whereas the mobile clients in the ranges move. We focus on a category called dynamic real-time range queries (DRRQ), assuming that both, clients requested by the query and the inquirers, are mobile. In consequence, the query parameters and the query results continuously change. This leads to two requirements: the ability to deal with an arbitrarily high number of mobile nodes (scalability) and the real-time delivery of range query results. In this paper, we present the highly decentralized solution adaptive quad streaming (AQS) for the requirements of DRRQs. AQS approximates the query results in favor of a controlled real-time delivery and guaranteed scalability. While prior works commonly optimize data structures on the involved servers, we use AQS to focus on a highly distributed cell structure without data structures automatically adapting to changing client distributions. Instead of the commonly used request-response approach, we apply a lightweight streaming method in which no bidirectional communication and no storage or maintenance of queries are required at all.

Keywords: approximation of client distributions, continuous spatial range queries, mobile objects, streaming-based decentralization in spatial mobile environments

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Authors: Taisiia Gorshkova

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Since the 1980s, spatial correlation models have been used more often to model regional indicators. An increasingly popular method for studying regional indicators is modeling taking into account spatial relationships between objects that are part of the same economic zone. In 2000s the new class of model – spatial vector autoregressions was developed. The main difference between standard and spatial vector autoregressions is that in the spatial VAR (SpVAR), the values of indicators at time t may depend on the values of explanatory variables at the same time t in neighboring regions and on the values of explanatory variables at time t-k in neighboring regions. Thus, VAR is a special case of SpVAR in the absence of spatial lags, and the spatial panel data model is a special case of spatial VAR in the absence of time lags. Two specifications of SpVAR were applied to Russian regional data for 2000-2017. The values of GRP and regional CPI are used as endogenous variables. The lags of GRP, CPI and the unemployment rate were used as explanatory variables. For comparison purposes, the standard VAR without spatial correlation was used as “naïve” model. In the first specification of SpVAR the unemployment rate and the values of depending variables, GRP and CPI, in neighboring regions at the same moment of time t were included in equations for GRP and CPI respectively. To account for the values of indicators in neighboring regions, the adjacency weight matrix is used, in which regions with a common sea or land border are assigned a value of 1, and the rest - 0. In the second specification the values of depending variables in neighboring regions at the moment of time t were replaced by these values in the previous time moment t-1. According to the results obtained, when inflation and GRP of neighbors are added into the model both inflation and GRP are significantly affected by their previous values, and inflation is also positively affected by an increase in unemployment in the previous period and negatively affected by an increase in GRP in the previous period, which corresponds to economic theory. GRP is not affected by either the inflation lag or the unemployment lag. When the model takes into account lagged values of GRP and inflation in neighboring regions, the results of inflation modeling are practically unchanged: all indicators except the unemployment lag are significant at a 5% significance level. For GRP, in turn, GRP lags in neighboring regions also become significant at a 5% significance level. For both spatial and “naïve” VARs the RMSE were calculated. The minimum RMSE are obtained via SpVAR with lagged explanatory variables. Thus, according to the results of the study, it can be concluded that SpVARs can accurately model both the actual values of macro indicators (particularly CPI and GRP) and the general situation in the regions

Keywords: forecasting, regional data, spatial econometrics, vector autoregression

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Authors: Dong Wu, Michael Grenn

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Managing software projects effectively is crucial for meeting deadlines, ensuring quality, and managing resources well. Traditional methods often struggle with predicting project timelines accurately due to uncertain schedules and complex data. This study addresses these challenges by combining time prediction algorithms with Large Language Models (LLMs). It makes use of real-world software project data to construct and validate a model. The model takes detailed project progress data such as task completion dynamic, team Interaction and development metrics as its input and outputs predictions of project timelines. To evaluate the effectiveness of this model, a comprehensive methodology is employed, involving simulations and practical applications in a variety of real-world software project scenarios. This multifaceted evaluation strategy is designed to validate the model's significant role in enhancing forecast accuracy and elevating overall management efficiency, particularly in complex software project environments. The results indicate that the integration of time prediction algorithms with LLMs has the potential to optimize software project progress management. These quantitative results suggest the effectiveness of the method in practical applications. In conclusion, this study demonstrates that integrating time prediction algorithms with LLMs can significantly improve the predictive accuracy and efficiency of software project management. This offers an advanced project management tool for the industry, with the potential to improve operational efficiency, optimize resource allocation, and ensure timely project completion.

Keywords: software project management, time prediction algorithms, large language models (LLMS), forecast accuracy, project progress prediction

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Authors: Haitham A. Hussein, Rozi Abdullah, Issa Saket, Md. Azlin

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The gravitational effect has been extensively applied to separate oil from water in water and wastewater treatment systems. The maximum oil globules removal efficiency is improved by obtaining the best flow uniformity in separator tanks. This study used 2D computational fluid dynamics (CFD) to investigate the effect of different inlet baffle positions inside the separator tank. Laboratory experiment has been conducted, and the measured velocity fields which were by Nortek Acoustic Doppler Velocimeter (ADV) are used to verify the CFD model. Computational investigation results indicated that the construction of an inlet baffle in a suitable location provides the minimum recirculation zone volume, creates the best flow uniformity, and dissipates kinetic energy in the oil and water separator tank. Useful formulas were predicted to design the oil and water separator tanks geometry based on an experimental model.

Keywords: oil/water separator tanks, inlet baffles, CFD, VOF

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Authors: Jaemin Kim, Ilsun Pang, Yongrae Cho, Kwanghun Kim, Sungsun Baik

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Manufacturing cost reduction is becoming more important due to excessive oversupply of Single crystalline ingot in recent solar market. Many companies are carrying out extensive research to grow more than one Single crystalline ingot in one batch to reduce manufacturing cost. However what most companies are finding difficult in this process is the effect on ingot due to increasing levels of impurities. Every ingot leaves a certain amount of melt after it is fully grown. This is the impurity that lowers the ingot quality. This impurity increase in the batch after second, third and more are grown subsequently in one batch. In order to solve this problem, the experiment to remove the residual melt in high temperature of hot zone was performed and succeeded. Theoretical average metal concentration of second ingot by new method was calculated and compared to it by conventional method.

Keywords: single crystal, solar cell, metal impurity, Ingot

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Authors: Magigi Wakuru, Gaudensi Kapinga

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This study examines land use changes and its implications on livelihood activities of peri-urban settlements in Msaranga, Moshi Municipality. Specifically; it analyses the historical development of the settlement, socioeconomic characteristics and land use changes over time. Likely, find out existing livelihood activities and how have been changing over time in the context of urbanization, and lastly highlights land use change implications on livelihood activities to residents. Interviews, observations, documentary reviews and mapping were data collection tools employed. The study shows that housing, urban agriculture, roads infrastructure, recreational, open spaces and institutions are some land use types existing in the settlement. On-farm and off-farm livelihood activities have been identified livelihood activities in the settlement. These include crop cultivation, livestock keeping, trading and formal employment and have been changing over time. However, urbanisation observed to be a catalyst of change and affect livelihood activities over time. Resorting to off-farm livelihoods activities including engaging in retail business and seeking employment in formal and informal sector are some copying strategies documented. The study wind up by pointing roles of different actors and issues of particular attention to different stakeholders towards reducing impact of land use changes on livelihood strategies in the settlement. Likely, unresolved issues for future research and policy development agenda are highlighted in this study. The study concludes that the impact of land use changes on livelihood activities need collaborative effort of different stakeholders, policy enforcement as well as public private partnership in issues based implementation in cities like Moshi where land use is rapidly changing over time within urban planning cycles due to increasing population demand in cities of Sub-Saharan Africa.

Keywords: land use, land use changes, livelihood activities, peri-urban settlement, Moshi, Tanzania

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Authors: Abdorreza Rabiee, Shahla Mohammad Hoseini Mirzaei

Abstract:

The advantages of distributed generations (DGs) based on renewable energy sources (RESs) leads to high penetration level of DGs in distribution network. With incorporation of DGs in distribution systems, the system reliability and security, as well as voltage profile, is improved. However, the protection of such systems is still challenging. In this paper, at first, the related papers are reviewed and then a practical scheme is proposed for coordination of OCRs in distribution system with DGs. The coordination problem is formulated as a nonlinear programming (NLP) optimization problem with the object function of minimizing total operating time of OCRs. The proposed method is studied based on a simple test system. The optimization problem is solved by General Algebraic Modeling System (GAMS) to calculate the optimal time dial setting (TDS) and also pickup current setting of OCRs. The results show the effectiveness of the proposed method and its applicability.

Keywords: distributed generation, DG, distribution network, over current relay, OCR, protection coordination, pickup current, time dial setting, TDS

Procedia PDF Downloads 120

Authors: C. P. Mallapur, U. K. Hulihalli, D. N. Kambrekar

Abstract:

Maize (Zea mays L.) an important cereal crop in the world has diversified uses including human consumption, animal feed, and industrial uses. A major constraint in low productivity of maize in India is undoubtedly insect pests particularly two species of stem borers, Chilo partellus (Swinhoe) and Sesamia inferens (Walker). The stem borers cause varying level of yield losses in different agro-climate regions (25.7 to 80.4%) resulting in a huge economic loss to the farmers. Although these pests are rather difficult to manage, efforts have been made to combat the menace by using effective insecticides. However, efforts have been made in the present study to integrate various possible approaches for sustainable management of these borers. Two field experiments were conducted separately during 2016-17 at Main Agricultural Research Station, University of Agricultural Sciences, Dharwad, Karnataka, India. In the first experiment, six treatments were randomized in RBD. The insect eggs at pinhead stage (@ 40 eggs/plant) were stapled to the under surface of leaves covering 15-20 % of plants in each plot after 15 days of sowing. The second experiment was planned with nine treatments replicated thrice. The border crop with NB -21 grass was planted all around the plots in the specific treatments while, cowpea intercrop (@6:1-row proportion) was sown along with the main crop and later, the insecticidal spray with chlorantraniliprole and nimbecidine was taken upon need basis in the specific treatments. The results indicated that the leaf injury and dead heart incidence were relatively more in the treatments T₂ and T₄ wherein, no insect control measures were made after the insect release (58.30 & 40.0 % leaf injury and 33.42 and 25.74% dead heart). On the contrary, these treatments recorded higher stem tunneling (32.4 and 24.8%) and resulted in lower grain yield (17.49 and 26.79 q/ha) compared to 29.04, 32.68, 40.93 and 46.38 q/ha recorded in T₁, T₃, T₅ and T₆ treatments, respectively. A maximum yield loss of 28.89 percent was noticed in T₂ followed by 19.59 percent in T₄ where no sprays were imposed. The data on integrated management trial revealed the lowest stem borer damage (19.28% leaf injury and 1.21% dead heart) in T₅ (seed treatment with thiamethoxam 70FS @ 8ml/kg seed + cow intercrop along with nimbecidine 0.03EC @ 5.0 ml/l and chlorantraniliprole 18.5SC spray @ 0.2 ml/l). The next best treatment was T₆ (ST+ NB-21 borer with nimbecidine and chlorantraniliprole spray) with 21.3 and 1.99 percent leaf injury and dead heart incidence, respectively. These treatments resulted in highest grain yield (77.71 and 75.53 q/ha in T₅ and T₆, respectively) compared to the standard check, T₁ (ST+ chlorantraniliprole spray) wherein, 27.63 percent leaf injury and 3.68 percent dead heart were noticed with 60.14 q/ha grain yield. The stem borers can cause yield loss up to 25-30 percent in maize which can be well tackled by seed treatment with thiamethoxam 70FS @ 8ml/kg seed and sowing the crop along with cowpea as intercrop (6:1 row proportion) or NB-21 grass as border crop followed by application of nimbecidine 0.03EC @ 5.0 ml/l and chlorantraniliprole 18.5SC @ 0.2 ml/l on need basis.

Keywords: Maize stem borers, Chilo partellus, Sesamia inferens, crop loss, integrated management

Procedia PDF Downloads 160

Authors: Golnar Behzadi, Michael O'Sullivan, Tava Olsen, Abraham Zhang

Abstract:

By definition, increasing supply chain resilience improves the supply chain’s ability to return to normal, or to an even more desirable situation, quickly and efficiently after being hit by a disruption. This is especially critical in agribusiness supply chains where the products are perishable and have a short life-cycle. In this paper, we propose a resilience metric to capture and improve the recovery process in terms of both performance and time, of an agribusiness supply chain following either supply or demand-side disruption. We build a model that determines optimal supply chain recovery planning decisions and selects the best resilient strategies that minimize the loss of profit during the recovery time window. The model is formulated as a two-stage stochastic mixed-integer linear programming problem and solved with a branch-and-cut algorithm. The results show that the optimal recovery schedule is highly dependent on the duration of the time-window allowed for recovery. In addition, the profit loss during recovery is reduced by utilizing the proposed resilient actions.

Keywords: agribusiness supply chain, recovery, resilience metric, risk management

Procedia PDF Downloads 378