Abstract: Demand on plant oils has increased to an enormous extent that is due to the change of human nutrition habits on the one hand, while on the other hand to the increase of raw material demand of some industrial sectors, just as to the increase of biofuel production. Besides the determining importance of sunflower in Hungary the production area, just as in part the average yield amount of rapeseed has increased among the produced oil crops. The variety/hybrid palette has changed significantly during the past decade. The available varieties’/hybrids’ palette has been extended to a significant extent. It is agreed that rapeseed production demands professionalism and local experience. Technological elements are successive; high yield amounts cannot be produced without system-based approach. The aim of the present work was to execute the complex study of one of the most critical production technology element of rapeseed production, that was sowing technology. Several sowing technology elements are studied in this research project that are the following: biological basis (the hybrid Arkaso is studied in this regard), sowing time (sowing time treatments were set so that they represent the wide period used in industrial practice: early, optimal and late sowing time) plant density (in this regard reaction of rare, optimal and too dense populations) were modelled. The multifactorial experimental system enables the single and complex evaluation of rapeseed sowing technology elements, just as their modelling using experimental result data. Yield quality and quantity have been determined as well in the present experiment, just as the interactions between these factors. The experiment was set up in four replications at the Látókép Plant Production Research Site of the University of Debrecen. Two different sowing times were sown in the first experimental year (2014), while three in the second (2015). Three different plant densities were set in both years: 200, 350 and 500 thousand plants ha-1. Uniform nutrient supply and a row spacing of 45 cm were applied. Winter wheat was used as pre-crop. Plant physiological measurements were executed in the populations of the Arkaso rapeseed hybrid that were: relative chlorophyll content analysis (SPAD) and leaf area index (LAI) measurement. Relative chlorophyll content (SPAD) and leaf area index (LAI) were monitored in 7 different measurement times.
Abstract: Because of the easy applying and not costing too much, ultrasonic pulse velocity (UPV) is one of the most used non-destructive techniques to determine concrete characteristics along with impact-echo, Schmidt rebound hammer (SRH) and pulse-echo. This article investigates the relationship between UPV and compressive strength of hybrid fiber reinforced concretes. Water/cement ratio (w/c) was kept at 0.4 for all concrete mixes. Compressive strength of concrete was targeted at 35 MPa. UPV testing and compressive strength tests were carried out at the curing age of 28 days. The UPV of concrete containing steel fibers has been found to be higher than plain concrete for all the testing groups. It is decided that there is not a certain relationship between fiber addition and strength.
Abstract: Large exhibition halls require a lot of energy to maintain comfortable atmosphere for the visitors viewing inside. One way of reducing the energy cost is to have thermal energy storage systems installed so that the thermal energy can be stored in the middle of night when the energy price is low and then used later when the price is high. To minimize the overall energy cost, however, we should be able to decide how much energy to save during which time period exactly. If we can foresee future energy load and the corresponding cost, we will be able to make such decisions reasonably. In this paper, we use machine learning technique to obtain models for predicting weather conditions and the number of visitors on hourly basis for the next day. Based on the energy load thus predicted, we build a cost-optimal daily operation plan for the thermal energy storage systems and cooling and heating facilities through simulation-based optimization.
Abstract: There are many articles that attempt to establish the role of different facial fragments in face recognition. Various approaches are used to estimate this role. Frequently, authors calculate the entropy corresponding to the fragment. This approach can only give approximate estimation. In this paper, we propose to use a more direct measure of the importance of different fragments for face recognition. We propose to select a recognition method and a face database and experimentally investigate the recognition rate using different fragments of faces. We present two such experiments in the paper. We selected the PCNC neural classifier as a method for face recognition and parts of the LFW (Labeled Faces in the Wild) face database as training and testing sets. The recognition rate of the best experiment is comparable with the recognition rate obtained using the whole face.
Abstract: When the Manning equation is used, a unique value of normal depth in the uniform flow exists for a given channel geometry, discharge, roughness, and slope. Depending on the value of normal depth relative to the critical depth, the flow type (supercritical or subcritical) for a given characteristic of channel conditions is determined whether or not flow is uniform. There is no general solution of Manning's equation for determining the flow depth for a given flow rate, because the area of cross section and the hydraulic radius produce a complicated function of depth. The familiar solution of normal depth for a rectangular channel involves 1) a trial-and-error solution; 2) constructing a non-dimensional graph; 3) preparing tables involving non-dimensional parameters. Author in this paper has derived semi-analytical solution to Manning's equation for determining the flow depth given the flow rate in rectangular open channel. The solution was derived by expressing Manning's equation in non-dimensional form, then expanding this form using Maclaurin's series. In order to simplify the solution, terms containing power up to 4 have been considered. The resulted equation is a quartic equation with a standard form, where its solution was obtained by resolving this into two quadratic factors. The proposed solution for Manning's equation is valid over a large range of parameters, and its maximum error is within -1.586%.
Abstract: A compositional reservoir simulation model (CMG-GEM) was used for cyclic CO2 injection process in unconventional tight reservoir. Cyclic CO2 injection is an enhanced oil recovery process consisting of injection, shut-in, and production. The study of cyclic CO2 injection and hydrocarbon recovery in ultra-low permeability reservoirs is mainly a function of rock, fluid, and operational parameters. CMG-GEM was used to study several design parameters of cyclic CO2 injection process to distinguish the parameters with maximum effect on the oil recovery and to comprehend the behavior of cyclic CO2 injection in tight reservoir. On the other hand, permeability reduction induced by asphaltene precipitation is one of the major issues in the oil industry due to its plugging onto the porous media which reduces the oil productivity. In addition to asphaltene deposition, solubility of CO2 in the aquifer is one of the safest and permanent trapping techniques when considering CO2 storage mechanisms in geological formations. However, the effects of the above uncertain parameters on the process of CO2 enhanced oil recovery have not been understood systematically. Hence, it is absolutely necessary to study the most significant parameters which dominate the process. The main objective of this study is to improve techniques for designing cyclic CO2 injection process while considering the effects of asphaltene deposition and solubility of CO2 in the brine in order to prevent asphaltene precipitation, minimize CO2 emission, optimize cyclic CO2 injection, and maximize oil production.
Abstract: Without taking account of the attribute richness of POI (point of interest) data and spatial distribution limited by roads, a POI generalization method considering both attribute information and spatial distribution has been proposed against the existing point generalization algorithm merely focusing on overall information of point groups. Hierarchical characteristic of urban POI information expression has been firstly analyzed to point out the measurement feature of the corresponding hierarchy. On this basis, an urban POI generalizing strategy has been put forward: POIs urban road network have been divided into three distribution pattern; corresponding generalization methods have been proposed according to the characteristic of POI data in different distribution patterns. Experimental results showed that the method taking into account both attribute information and spatial distribution characteristics of POI can better implement urban POI generalization in the mapping presentation.
Abstract: The overvaluation of the use of automobile has detrimentally affected the importance of pedestrians within the city and consequently its public spaces. As a way of treating contemporary urban paradigms, Tactical Urbanism aims to recover and activate spaces through fast and easily-applied actions that demonstrate the possibility of large-scale and long-term changes in cities. Tactical interventions have represented an important practice of redefining public spaces and urban mobility. The concept of Active Transportation coheres with the idea of sustainable urban mobility, characterizing the means of transportation through human propulsion, such as walking and cycling. This paper aims to debate the potential of Tactical Urbanism in promoting Active Transportation by revealing opportunities of transformation in the urban space of contemporary cities through initiatives that promote the protection and valorization of the presence of pedestrians and cyclists in cities, and that subvert the importance of motorized vehicles. In this paper, we present the character of these actions in two different ways: when they are used as tests for permanent interventions and when they have pre-defined start and end periods. Using recent initiatives to illustrate, we aim to discuss the role of small-scale actions in promoting and incentivizing a more active, healthy, sustainable and responsive urban way of life, presenting how some of them have developed through public policies. For that, we will present some examples of tactical actions that illustrate the encouragement of Active Transportation and trials to balance the urban opportunities for pedestrians and cyclists. These include temporary closure of streets, the creation of new alternatives and more comfortable areas for walking and cycling, and the subversion of uses in public spaces where the usage of cars are predominant.
Abstract: A growing demand for sustainability makes sustainability as one of the significant debates of nowadays. Energy saving is one of the main criteria to be considered in the context of sustainability. Reducing energy use in buildings is one of the most important ways to reduce humans’ overall environmental impact. Taking this into consideration, study of different design strategies, which can assist in reducing energy use and subsequently improving the sustainability level of today's buildings would be an essential task. The sustainability level of a building is highly affected by the sustainability performance of its components. One of the main building components, which can have a great impact on energy saving and sustainability level of the building, is its facade. The aim of this study is to investigate on the role of facade in sustainability enhancement of the contemporary buildings of Iran. In this study, the concept of sustainability in architecture, the building facades, and their relationship to sustainability are explained briefly. Following that, a number of contemporary Iranian buildings are discussed and analyzed in terms of different design strategies used in their facades in accordance to the sustainability concepts. The methods used in this study are descriptive and analytic. The results of this paper would assist in generating a wider vision and a source of inspiration for the current designers to design and create environmental and sustainable buildings for the future.
Abstract: With the increasing of the penetration of renewable energy in power system, the whole inertia of the power system is declining, which will endanger the frequency stability of the power system. In order to enhance the inertia, virtual synchronous generator (VSG) has been proposed. In addition, the motor-generator pair (MGP) system is proposed to enhance grid inertia. Both of them need additional equipment to provide instantaneous energy, so the economic problem should be considered. In this paper, the basic working principle of MGP system and VSG are introduced firstly. Then, the technical characteristics and economic investment of MGP/VSG are compared by calculation and simulation. The results show that the MGP system can provide same inertia with less cost than VSG.
Abstract: In recent years, the combined economic and emission power dispatch is one of the main problems of electrical power system. It aims to schedule the power generation of generators in order to minimize cost production and emission of harmful gases caused by fossil-fueled thermal units such as CO, CO2, NOx, and SO2. To solve this complicated multi-objective problem, an improved version of the particle swarm optimization technique that includes non-dominated sorting concept has been proposed. Valve point loading effects and system losses have been considered. The three-unit and ten-unit benchmark systems have been used to show the effectiveness of the suggested optimization technique for solving this kind of nonconvex problem. The simulation results have been compared with those obtained using genetic algorithm based method. Comparison results show that the proposed approach can provide a higher quality solution with better performance.
Abstract: In the continuous interaction between the past and the present that historiography is, each time when history gets re/written, a new representation emerges. This new representation is a reflection of the earlier archives and their interpretations, fragmented remembrances of the past, as well as the reactions to the present. Memory, or lack thereof, and stereotyping generally play a major role in this representation. William Dalrymple’s Nine Lives: In Search of the Sacred in Modern India (2009) is one such written account that sets out to narrate the representations of religion and culture of India and contemporary reactions to it. Dalrymple’s nine saints belong to different castes, sects, religions, and regions. By dealing with their religions and expressions of those religions, and through the lived mysticism of these nine individuals, the book engages with some important issues like class, caste and gender in the contexts provided by historical as well as present India. The paper studies the development of religion and accompanied feeling of religiosity in modern as well as historical contexts through a study of these elements in the book. Since, the language used in creation of texts and the literary texts thus produced create a new reality that questions the stereotypes of the past, and in turn often end up creating new stereotypes or stereotypical representations at times, the paper seeks to actively engage with the text in order to identify and study such stereotypes, along with their changing representations. Through a detailed examination of the book, the paper seeks to unravel whether some socio-cultural stereotypes existed earlier, and whether there is development of new stereotypes from Dalrymple’s point of view as an outsider writing on issues that are deeply rooted in the cultural milieu of the country. For this analysis, the paper takes help from the psycho-literary theories of stereotyping and representation.
Abstract: Alkaline niobate (Na0.5K0.5)NbO3 ceramic system has attracted major attention in view of its potential for replacing the highly toxic but superior lead zirconate titanate (PZT) system for piezoelectric applications. Recently, a more detailed study of this system reveals that the ferroelectric and piezoelectric properties are optimized in the Li- and V-modified system having the composition (K0.485Na0.5Li0.015)(Nb0.98V0.02)O3. In the present work, we further study the pyroelectric behaviour of this composition along with another doped with Mn4+. So, (K0.485Na0.5Li0.015)(Nb0.98V0.02)O3 + x MnO2 (x = 0, and 0.01 wt. %) ceramic compositions were synthesized by conventional ceramic processing route. X-ray diffraction study reveals that both the undoped and Mn4+-doped ceramic samples prepared crystallize into a perovskite structure having orthorhombic symmetry. Dielectric study indicates that Mn4+ doping has little effect on both the Curie temperature (Tc) and tetragonal-orthorhombic phase transition temperature (Tot). The bulk density, room-temperature dielectric constant (εRT), and room-c The room-temperature coercive field (Ec) is observed to be lower in Mn4+ doped sample. The detailed analysis of the P-E hysteresis loops over the range of temperature from about room temperature to Tot points out that enhanced ferroelectric properties exist in this temperature range with better thermal stability for the Mn4+ doped ceramic. The study reveals that small traces of Mn4+ can modify (K0.485Na0.5Li0.015)(Nb0.98V0.02)O3 system so as to improve its ferroelectric properties with good thermal stability over a wide range of temperature.
Abstract: The purpose of this paper was separation and study of the part of structure regime, which directly affects the process of desertification. A simple scheme was prepared for the assessment of desertification process; surface air temperature and precipitation for the years of 1936-2009 were analyzed. The map of distribution of the Desertification Contributing Coefficient in the territory of Georgia was compiled. The simple scheme for identification of the intensity of the desertification contributing process has been developed and the illustrative example of its practical application for the territory of Georgia has been conducted.
Abstract: Test data compression is an efficient method for reducing the test application cost. The problem of reducing test data has been addressed by researchers in three different aspects: Test Data Compression, Built-in-Self-Test (BIST) and Test set compaction. The latter two methods are capable of enhancing fault coverage with cost of hardware overhead. The drawback of the conventional methods is that they are capable of reducing the test storage and test power but when test data have redundant length of runs, no additional compression method is followed. This paper presents a modified Run Length Coding (RLC) technique with Multilevel Selective Huffman Coding (MLSHC) technique to reduce test data volume, test pattern delivery time and power dissipation in scan test applications where redundant length of runs is encountered then the preceding run symbol is replaced with tiny codeword. Experimental results show that the presented method not only improves the test data compression but also reduces the overall test data volume compared to recent schemes. Experiments for the six largest ISCAS-98 benchmarks show that our method outperforms most known techniques.
Abstract: Clustering is a well known data mining technique used in pattern recognition and information retrieval. The initial dataset to be clustered can either contain categorical or numeric data. Each type of data has its own specific clustering algorithm. In this context, two algorithms are proposed: the k-means for clustering numeric datasets and the k-modes for categorical datasets. The main encountered problem in data mining applications is clustering categorical dataset so relevant in the datasets. One main issue to achieve the clustering process on categorical values is to transform the categorical attributes into numeric measures and directly apply the k-means algorithm instead the k-modes. In this paper, it is proposed to experiment an approach based on the previous issue by transforming the categorical values into numeric ones using the relative frequency of each modality in the attributes. The proposed approach is compared with a previously method based on transforming the categorical datasets into binary values. The scalability and accuracy of the two methods are experimented. The obtained results show that our proposed method outperforms the binary method in all cases.
Abstract: The increasing amount of collected data has limited the performance of the current analyzing algorithms. Thus, developing new cost-effective algorithms in terms of complexity, scalability, and accuracy raised significant interests. In this paper, a modified effective k-means based algorithm is developed and experimented. The new algorithm aims to reduce the computational load without significantly affecting the quality of the clusterings. The algorithm uses the City Block distance and a new stop criterion to guarantee the convergence. Conducted experiments on a real data set show its high performance when compared with the original k-means version.
Abstract: Climate change projections based on the emission of greenhouse effect gases suggest an increase in the concentration of atmospheric carbon dioxide, in up to 750 ppm. In this scenario, we have significant changes in plant development, and consequently, in agricultural systems. This study aims to evaluate the interaction between culture (Glycine max) and weed (Amaranthus viridis and Euphorbia heterophylla) in two conditions of CO2, 400 and 800 ppm. The results showed that the coexistence of culture with both weed species resulted in a mutual loss, with decrease in dry mass productivity of culture + weeds, in both conditions of CO2. However, when the culture is grown in association with E. heterophylla, total dry mass of culture + weed was smaller at 800 ppm. Soybean was more aggressive in comparison to the A. viridis in both the concentrations of CO2, but not in relation to the E. heterophylla.
Abstract: Mobile localization has attracted a great deal of attention recently due to the introduction of wireless networks. Although several localization algorithms and systems have been implemented and discussed in the literature, very few researchers have exploited the gap that exists between indoor localization, tracking, external storage of location information and outdoor localization for the purpose of digital forensics during and after a disaster. The contribution of this paper lies in the implementation of a robust system that is capable of locating, tracking mobile device users and store location information for both indoor and partially outdoor the cloud. The system can be used during disaster to track and locate mobile phone users. The developed system is a mobile application built based on Android, Hypertext Preprocessor (PHP), Cascading Style Sheets (CSS), JavaScript and MATLAB for the Android mobile users. Using Waterfall model of software development, we have implemented a three level system that is able to track, locate and store mobile device information in secure database (cloud) on almost a real time basis. The outcome of the study showed that the developed system is efficient with regard to the tracking and locating mobile devices. The system is also flexible, i.e. can be used in any building with fewer adjustments. Finally, the system is accurate for both indoor and outdoor in terms of locating and tracking mobile devices.
Abstract: Causal relation identification is a crucial task in information extraction and knowledge discovery. In this work, we present two approaches to causal relation identification. The first is a classification model trained on a set of knowledge-based features. The second is a deep learning based approach training a model using convolutional neural networks to classify causal relations. We experiment with several different convolutional neural networks (CNN) models based on previous work on relation extraction as well as our own research. Our models are able to identify both explicit and implicit causal relations as well as the direction of the causal relation. The results of our experiments show a higher accuracy than previously achieved for causal relation identification tasks.