Search results for: soil classification

Authors: Mohammed Abaoli Abafogi, Sinem Satiroglu, M. Misir

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The current study has addressed the effect of Hazelnut (Corylus avellana) agroforestry on carbon sequestration. Eight sample plots were collected from Hazelnut (Corylus avellana) agroforestry using random sampling method. The diameter of all trees in each plot with ≥ 2cm at 1.3m DBH was measured by using a calliper. Average diameter, aboveground biomass, and carbon stock were calculated for each plot. Comparative data for natural forestland was used for C was taken from KTU, and the soil C was converted from the biomass conversion equation. Biomass carbon was significantly higher in the Natural forest (68.02Mgha⁻¹) than in the Hazelnut agroforestry (16.89Mgha⁻¹). SOC in Hazelnut agroforestry, Natural forest, and arable agricultural land were 7.70, 385.85, and 0.00 Mgha⁻¹ respectively. Biomass C, on average accounts for only 0.00% of the total C in arable agriculture, and 11.02% for the Hazelnut agroforestry while 88.05% for Natural forest. The result shows that the conversion of arable crop field to Hazelnut agroforestry can sequester a large amount of C in the soil as well as in the biomass than Arable agricultural lands.

Keywords: arable agriculture, biomass carbon, carbon sequestration, hazelnut (Corylus avellana) agroforestry, soil organic carbon

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Authors: Ahmed M. El-Tuhami, Ahmed A. Mohamed

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This paper studies the behavior of strip footing adjacent to slope crest and the effect of jet grouting under the footing. This problem is investigated numerically in the present study. Two dimensional plane strain program PLAXIS is used in this study. 15 nodes triangular element is used to idealize soil with hardening soil model. Five nodes isoperimetric beam element is used to idealize stripe footing. Interface element is used to represent the contact between beam element and soil. Two parameters were studied, the first is the foundation depth and the second is the Stripe footing distance from the slope crest. Settlement and horizontal displacement of strip footing were obtained and studied from the analyzed finite element model results. The reduction influence of jet grouting on footing displacement were studied and investigated. The results indicate that the inclusion of jet grouting under strip footing adjacent to slope crest has significant effect in improving the response of the strip footing and the slope.

Keywords: strip footing, jet grouting, slope, PLAXIS, relative distance

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Authors: Maher Z. Mohammed, Barry G. Clarke

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As an alternative to stone column in fine grained soils, it is possible to create stiffened columns of soils using electroosmosis (electroosmotic piles). This program of this research is to establish the effectiveness and efficiency of the process in different soils. The aim of this study is to assess the capability of electroosmosis treatment in a range of composite soils. The combined electroosmotic and preloading equipment developed by Nizar and Clarke (2013) was used with an octagonal array of anodes surrounding a single cathode in a nominal 250mm diameter 300mm deep cylinder of soil and 80mm anode to cathode distance. Copper coiled springs were used as electrodes to allow the soil to consolidate either due to an external vertical applied load or electroosmosis. The equipment was modified to allow the temperature to be monitored during the test. Electroosmotic tests were performed on China Clay Grade E kaolin and calcium bentonite (Bentonex CB) mixed with sand fraction C (BS 1881 part 131) at different ratios by weight; (0, 23, 33, 50 and 67%) subjected to applied voltages (5, 10, 15 and 20). The soil slurry was prepared by mixing the dry soil with water to 1.5 times the liquid limit of the soil mixture. The mineralogical and geotechnical properties of the tested soils were measured before the electroosmosis treatment began. In the electroosmosis cell tests, the settlement, expelled water, variation of electrical current and applied voltage, and the generated heat was monitored during the test time for 24 osmotic tests. Water content was measured at the end of each test. The electroosmotic tests are divided into three phases. In Phase 1, 15 kPa was applied to simulate a working platform and produce a uniform soil which had been deposited as a slurry. 50 kPa was used in Phase 3 to simulate a surcharge load. The electroosmotic treatment was only performed during Phase 2 where a constant voltage was applied through the electrodes in addition to the 15 kPa pressure. This phase was stopped when no further water was expelled from the cell, indicating the electroosmotic process had stopped due to either the degradation of the anode or the flow due to the hydraulic gradient exactly balanced the electroosmotic flow resulting in no flow. Control tests for each soil mixture were carried out to assess the behaviour of the soil samples subjected to only an increase of vertical pressure, which is 15kPa in Phase 1 and 50kPa in Phase 3. Analysis of the experimental results from this study showed a significant dewatering effect on the soil slurries. The water discharged by the electroosmotic treatment process decreased as the sand content increased. Soil temperature increased significantly when electrical power was applied and drops when applied DC power turned off or when the electrode degraded. The highest increase in temperature was found in pure clays at higher applied voltage after about 8 hours of electroosmosis test.

Keywords: electrokinetic treatment, electrical conductivity, electroosmotic consolidation, electroosmosis permeability ratio

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Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

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Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Bayesian network, classification, expert knowledge, structure learning, surface water analysis

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Authors: Hong Li, Tingxian Li, Xudong Wang, Weibo Yang

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Co-limitation of iron (Fe) deficiency in legume nitrogen fixation process is not well understood. Our objectives were to examine how peanut plants cope with Fe deficiency with the rhizobial inoculants and N-nutrient treatments. The study was conducted in the tropical Hainan Island during 2012-2013. The soil was strongly acidic (pH 4.6±0.7) and deficient in Fe (9.2±2.3 mg/kg). Peanut plants were intercropped with cassava. The inoculants and N treatments were arranged in a split-plot design with three blocks. Peanut root nodulation, stem allantoin, amino acids and plant N derived from fixation (P) reduced with declining soil Fe concentrations. The treatment interactions were significant on relative ureide % and peanut yields (P<0.05). Residual fixed N from peanut plants was beneficial to cassava plants. It was concluded that co-variance of Fe deficiency could influence peanut N fixation efficiency and rhizobia and N inputs could help improving peanut tolerance to Fe deficiency stress.

Keywords: amino acids, plant N derived from N fixation, root nodulation, soil Fe co-variance, stem ureide, peanuts, cassava

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Authors: Seonaid Hume, Gordon Dobie, Graeme West

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Detecting and localizing radioactive sources is a necessity for safe and secure decommissioning of nuclear facilities. An important aspect for the management of the sort-and-segregation process is establishing the spatial distributions and quantities of the waste radionuclides, their type, corresponding activity, and ultimately classification for disposal. The data received from surveys directly informs decommissioning plans, on-site incident management strategies, the approach needed for a new cell, as well as protecting the workforce and the public. Manual classification of nuclear waste from a nuclear cell is time-consuming, expensive, and requires significant expertise to make the classification judgment call. Also, in-cell decommissioning is still in its relative infancy, and few techniques are well-developed. As with any repetitive and routine tasks, there is the opportunity to improve the task of classifying nuclear waste using autonomous systems. Hence, this paper proposes a new framework for the automatic classification of nuclear waste. This framework consists of five main stages; 3D spatial mapping and object detection, object classification, radiological mapping, source localisation based on gathered evidence and finally, waste classification. The first stage of the framework, 3D visual mapping, involves object detection from point cloud data. A review of related applications in other industries is provided, and recommendations for approaches for waste classification are made. Object detection focusses initially on cylindrical objects since pipework is significant in nuclear cells and indeed any industrial site. The approach can be extended to other commonly occurring primitives such as spheres and cubes. This is in preparation of stage two, characterizing the point cloud data and estimating the dimensions, material, degradation, and mass of the objects detected in order to feature match them to an inventory of possible items found in that nuclear cell. Many items in nuclear cells are one-offs, have limited or poor drawings available, or have been modified since installation, and have complex interiors, which often and inadvertently pose difficulties when accessing certain zones and identifying waste remotely. Hence, this may require expert input to feature match objects. The third stage, radiological mapping, is similar in order to facilitate the characterization of the nuclear cell in terms of radiation fields, including the type of radiation, activity, and location within the nuclear cell. The fourth stage of the framework takes the visual map for stage 1, the object characterization from stage 2, and radiation map from stage 3 and fuses them together, providing a more detailed scene of the nuclear cell by identifying the location of radioactive materials in three dimensions. The last stage involves combining the evidence from the fused data sets to reveal the classification of the waste in Bq/kg, thus enabling better decision making and monitoring for in-cell decommissioning. The presentation of the framework is supported by representative case study data drawn from an application in decommissioning from a UK nuclear facility. This framework utilises recent advancements of the detection and mapping capabilities of complex radiation fields in three dimensions to make the process of classifying nuclear waste faster, more reliable, cost-effective and safer.

Keywords: nuclear decommissioning, radiation detection, object detection, waste classification

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Authors: Kamran Baksh Soomro, Amin Talei, Sina Alaghmand

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Due to the declining freshwater availability to agriculture in many areas, the utilization of saline irrigation requires more consideration. For this purpose, the effects of saline irrigation on the economics of crop yield and soil salinity should be understood. A two-year field experiment was carried out during 2017-18 with three replications to investigate the effect of saline groundwater on the economics of bitter gourd production and soil salinity status after harvesting the crop. Two irrigation treatments, i.e., fresh quality irrigation water (IT₁ EC 0.56 dS.m⁻¹ (control) and other is saline groundwater ( IT₂ EC 2.56 dS.m⁻¹) were used under drip system of irrigation. Cost-benefit analysis is often used to assess adaptation approaches. In this study, it has been observed that the salts under IT₁ (fresh quality water) and IT₂ (saline groundwater) did not accumulate in the wetted zone. However, the salts were observed deposited at wetted periphery under both the treatments after the crop end at all the three sampling depths under drip system of irrigation. Moreover, the costs and benefits associated with different irrigation treatments for two consecutive seasons for bitter-gourd cultivation were also investigated, and it was found that the average gross returns per hectare in season 1 were USD 5008.22 and 4454.78 under irrigation treatment IT₁ and IT₂ respectively. Whereas in season 2 the average gross returns per hectare were 3713.47 and 3140.51 under IT₁ and IT₂ respectively.

Keywords: ground-water, soil salinity, drip irrigation, wetted zone, wetted periphery, cost benefit analysis

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Authors: Maryam Salehi, Gholamreza Bonyadinejad

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The application of agricultural plastic products like mulch, greenhouse covers, and silage films is increasing due to their economic benefits in providing an early and better-quality harvest. In 2015, the 4 million tons (valued a 10.6 million USD) global market for agricultural plastic films was estimated to grow by 5.6% per year through 2030. Despite the short-term benefits provided by plastic products, their long-term sustainability issues and negative impacts on soil health are not well understood. After their removal from the field, some plastic residuals remain in the soil. Plastic residuals in farmlands may fragment to small particles called microplastics (d<5mm). The microplastics' exposure to solar radiation could alter their surface chemistry and make them susceptible to fragmentation. Thus, this study examined the photodegradation of low density polyethylene as the model microplastics that are released to the agriculture farmland. The variation of plastic’s surface chemistry, morphology, and bulk characteristics were studied after accelerated UV-A radiation experiments and sampling from an agricultural field. The Attenuated Total Reflectance Fourier Transform Spectroscopy (ATR-FTIR) and X-ray Photoelectron Spectroscopy (XPS) demonstrated the formation of oxidized surface functional groups onto the microplastics surface due to the photodegradation. The Differential Scanning Calorimetry (DSC) analysis revealed an increased crystallinity for the photodegraded microplastics compared to the new samples. The gel permeation chromatography (GPC) demonstrated the reduced molecular weight for the polymer due to the photodegradation. This study provides an important opportunity to advance understanding of soil pollution. Understanding the plastic residuals’ variations as they are left in the soil is providing a critical piece of information to better estimate the microplastics' impacts on environmental biodiversity, ecosystem sustainability, and food safety.

Keywords: soil health, plastic pollution, sustainability, photodegradation

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Authors: Hasan Basri Jumin

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Protoplasts isolated from embryogenic callus of Murraya paniculata (L. Jack.) were cultured in MT (Murashige and Tucker, 1969) basal medium containing 5% sucrose supplemented with kinetin, malt extract (ME) and 0.6 M sorbitol. About 85% of the surviving protoplasts formed a cell wall within 6 d of culture and the first cell division was observed 7 days after isolation. The highest plating effi¬ciency was obtained on MT basal medium containing 5% sucrose supplemented with 0.01 mg 1-1 kinetin 600 mg 1-1 ME, MT basal medium containing 5% sucrose and supplemented with 0.01 mg 1-1 Indole-acetic-acid (IAA) was found to be a medium suitable for the development somatic embryos into heart-shaped somatic embryos. The highest percentage of shoot formation was obtained using 0.1 mg 1-1 Indole-acitic-acid (IAA) 0..1 mg 1-1 gibberellic acid (GA3). In this investigation 40 plants were survived and grew normally in the soil. After two months maitained in the soil plants formed flower and flower developed into fruits on the soil treated with BA.

Keywords: gibberellic-acid, indole-acetic-acid, protoplast, precocious-flowering, somatic-embryo

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Authors: Gonca Z. Tuncbilek

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Architectural research tends to define architecture in terms of its permanence. In this study, the term ‘temporality’ and its use in architectural discourse is re-visited. The definition, proposition, and efficacy of the temporality occur both in architecture and in its related knowledge. The temporary architecture not only fulfills the requirement of the architectural programs, but also plays a significant role in generating an environment of architectural discourse. In recent decades, there is a great interest on the temporary architectural practices regarding to the installations, exhibition spaces, pavilions, and expositions; inviting the architects to experience and think about architecture. The temporary architecture has a significant role among the architecture, the architect, and the architectural discourse. Experiencing the contemporary materials, methods and technique; they have proposed the possibilities of the future architecture. These structures give opportunities to the architects to a wide-ranging variety of freedoms to experience the ‘new’ in architecture. In addition to this experimentation, they can be considered as an agent to redefine and reform the boundaries of the architectural discipline itself. Although the definition of architecture is re-analyzed in terms of its temporality rather than its permanence; architecture, in reality, still relies on historically codified types and principles of the formation. The concept of type can be considered for several different sciences, and there is a tendency to organize and understand the world in terms of classification in many different cultures and places. ‘Type’ is used as a classification tool with/without the scope of the critical invention. This study considers theories of type, putting forward epistemological and discursive arguments related to the form of architecture, being related to historical and formal disciplinary knowledge in architecture. This study has been to emphasize the importance of the temporality in architecture as a creative tool to reveal the position within the architectural discourse. The temporary architecture offers ‘new’ opportunities in the architectural field to be analyzed. In brief, temporary structures allow the architect freedoms to the experimentation in architecture. While redefining the architecture in terms of temporality, architecture still relies on historically codified types (pavilions, exhibitions, expositions, and installations). The notion of architectural types and its varying interpretations are analyzed based on the texts of architectural theorists since the Age of Enlightenment. Investigating the classification of type in architecture particularly temporary architecture, it is necessary to return to the discussion of the origin of the knowledge and its classification.

Keywords: classification of architecture, exhibition design, pavilion design, temporary architecture

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Authors: Bunjirtluk Jintaridth

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Utilization of silicon for sustainable rice cultivation in acid sulfate soils was studied for 2 years. The study was conducted on Rungsit soils in Amphoe Tanyaburi, Pathumtani Province. The objectives of this study were to assess the effect of high quality organic fertilizer in combination with silicon and chemical fertilizer on rice yield, chemical soil properties after using soil amendments, and also to assess the economic return. A Randomized Complete Block Design (RCBD) with 10 treatments and 3 replications were employed. The treatments were as follows: 1) control 2) chemical fertilizer (recommended by Land Development Department, LDD 3) silicon 312 kg/ha 4) high quality organic fertilizer at 1875 kg/ha (the recommendation rate by LDD) 5) silicon 156 kg/ha in combination with high quality organic fertilizer 1875 kg/ha 6) silicon at the 312 kg/ha in combination with high quality organic fertilizer 1875 kg/ha 7) silicon 156 kg/ha in combination with chemical fertilizer 8) silicon at the 312 kg/ha in combination with chemical fertilizer 9) silicon 156 kg/ha in combination with ½ chemical fertilizer rate, and 10) silicon 312 kg/ha in combination with ½ chemical fertilizer rate. The results of 2 years indicated the treatment tended to increase soil pH (from 5.1 to 4.7-5.5), percentage of organic matter (from 2.43 to 2.54 - 2.94%); avail. P (from 7.5 to 7-21 mg kg-1 P; ext. K (from 616 to 451-572 mg kg-1 K), ext Ca (from 1962 to 2042.3-4339.7 mg kg-1 Ca); ext Mg (from 1586 to 808.7-900 mg kg-1 Mg); but decrease the ext. Al (from 2.56 to 0.89-2.54 cmol kg-1 Al. Two years average of rice yield, the highest yield was obtained from silicon 156 kg/ha application in combination with high quality organic fertilizer 300 kg/rai (3770 kg/ha), or using silicon at the 312 kg/ha combination with high quality organic fertilizer 300 kg/rai. (3,750 kg/ha). It was noted that chemical fertilizer application with 156 and 312 kg/ha silicon gave only 3,260 และ 3,133 kg/ha, respectively. On the other hand, half rate of chemical fertilizer with 156 and 312 kg/ha with silicon gave the yield of 2,934 และ 3,218 kg/ha, respectively. While high quality organic fertilizer only can produce 3,318 kg/ha as compare to rice yield of 2,812 kg/ha from control. It was noted that the highest economic return was obtained from chemical fertilizer treated plots (886 dollars/ha). Silicon application at the rate of 156 kg/ha in combination with high quality organic fertilizer 1875 kg/ha gave the economic return of 846 dollars/ha, while 312 kg/ha of silicon with chemical fertilizer gave the lowest economic return (697 dollars/ha).

Keywords: rice, high quality organic fertilizer, acid sulfate soil, silicon

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Authors: Violina R. Angelova, Sava G. Tabakov, Aleksander B. Peltekov, Krasimir I. Ivanov

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A field study was conducted to evaluate the chemical composition and quality of the Aronia fruits, as well as the possibilities of Aronia cultivation on soils contaminated with heavy metals. The experiment was performed on an agricultural field contaminated by the Non-Ferrous-Metal Works (NFMW) near Plovdiv, Bulgaria. The study included four varieties of Aronia; Aron variety, Hugin variety, Viking variety and Nero variety. The Aronia was cultivated according to the conventional technology on areas at a different distance from the source of pollution NFMW- Plovdiv (1 km, 3.5 km, and 15 km). The concentrations of macroelements, microelements, and heavy metals in Aronia fruits were determined. The dry matter content, ash, sugars, proteins, and fats were also determined. Aronia is a crop that is tolerant to heavy metals and can successfully be grown on soils contaminated with heavy metals. The increased content of heavy metals in the soil leads to less absorption of the nutrients (Ca, Mg and P) in the fruit of the Aronia. Soil pollution with heavy metals does not affect the quality of the Aronia fruit varieties.

Keywords: aronia, chemical composition, fruits, quality

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Authors: J. O. Akinyele, R. W. Salim, K. O. Oikelome, O. T. Olateju

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Rice Husk (RH) is the major byproduct in the processing of paddy rice. The management of this waste has become a big challenge to some of the rice producers, some of these wastes are left in open dumps while some are burn in the open space, and these two actions have been contributing to environmental pollution. This study evaluates an alternative waste management of this agricultural product for use as a civil engineering material. The RH was burn in a controlled environment to form Rice Husk Ash (RHA). The RHA was mix with lateritic clay at 0, 2, 4, 6, 8, and 10% proportion by weight. Chemical test was conducted on the open burn and controlled burn RHA with the lateritic clay. Physical test such as particle size distribution, Atterberg limits test, and density test were carried out on the mix material. The chemical composition obtained for the RHA showed that the total percentage compositions of Fe2O3, SiO2 and Al2O3 were found to be above 70% (class “F” pozzolan) which qualifies it as a very good pozzolan. The coefficient of uniformity (Cu) was 8 and coefficient of curvature (Cc) was 2 for the soil sample. The Plasticity Index (PI) for the 0, 2, 4, 6, 8. 10% was 21.0, 18.8, 16.7, 14.4, 12.4 and 10.7 respectively. The work concluded that RHA can be effectively used in hydraulic barriers and as a stabilizing agent in soil stabilization.

Keywords: rice husk ash, pozzolans, paddy rice, lateritic clay

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Authors: Ebrahim Taherzadeh, Helmi Z. M. Shafri, Kaveh Shahi

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One of the most important tasks in urban area remote sensing is detection of impervious surface (IS), such as building roof and roads. However, detection of IS in heterogeneous areas still remains as one of the most challenging works. In this study, detection of concrete roof using an object-oriented approach was proposed. A new rule-based classification was developed to detect concrete roof tile. The proposed rule-based classification was applied to WorldView-2 image. Results showed that the proposed rule has good potential to predict concrete roof material from WorldView-2 images with 85% accuracy.

Keywords: object-based, roof material, concrete tile, WorldView-2

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Authors: Yahaya Abdullahi, Ben Coetzee, Linda Van Den Berg

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The study aimed at establishing the global positioning system (GPS) determined singles match characteristics that act as predictors of successful and less-successful male singles badminton players’ group classification. Twenty-two (22) male single players (aged: 23.39 ± 3.92 years; body stature: 177.11 ± 3.06cm; body mass: 83.46 ± 14.59kg) who represented 10 African countries participated in the study. Players were categorised as successful and less-successful players according to the results of five championships’ of the 2014/2015 season. GPS units (MinimaxX V4.0), Polar Heart Rate Transmitter Belts and digital video cameras were used to collect match data. GPS-related variables were corrected for match duration and independent t-tests, a cluster analysis and a binary forward stepwise logistic regression were calculated. A Receiver Operating Characteristic Curve (ROC) was used to determine the validity of the group classification model. High-intensity accelerations per second were identified as the only GPS-determined variable that showed a significant difference between groups. Furthermore, only high-intensity accelerations per second (p=0.03) and low-intensity efforts per second (p=0.04) were identified as significant predictors of group classification with 76.88% of players that could be classified back into their original groups by making use of the GPS-based logistic regression formula. The ROC showed a value of 0.87. The identification of the last-mentioned GPS-related variables for the attainment of badminton performances, emphasizes the importance of using badminton drills and conditioning techniques to not only improve players’ physical fitness levels but also their abilities to accelerate at high intensities.

Keywords: badminton, global positioning system, match analysis, inertial movement analysis, intensity, effort

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Authors: Federico Valenzuela-Beltran, Sonia E. Ruiz, Alfredo Reyes-Salazar, Juan Bojorquez

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A reliability-based methodology which uses structural demand hazard curves to consider the increment of the ductility demands of structures with tilting is proposed. The approach considers the effect of two orthogonal components of the ground motions as well as the influence of soil-structure interaction. The approach involves the calculation of ductility demand hazard curves for symmetric systems and, alternatively, for systems with different degrees of asymmetry. To get this objective, demand hazard curves corresponding to different global ductility demands of the systems are calculated. Next, Uniform Exceedance Rate Spectra (UERS) are developed for a specific mean annual rate of exceedance value. Ratios between UERS corresponding to asymmetric and to symmetric systems located in soft soil of the valley of Mexico are obtained. Results indicate that the ductility demands corresponding to tilted structures may be several times higher than those corresponding to symmetric structures, depending on several factors such as tilting angle and vibration period of structure and soil.

Keywords: asymmetric yielding, seismic performance, structural reliability, tilted structures

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Authors: Feda Negesse

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One of the most important indicators of research quality is a good data - collection instrument that can yield reliable and valid data. The Swadesh wordlist has been used for more than half a century for collecting data in comparative and historical linguistics though arbitrariness is observed in its application and size. This research compare s the classification results of the 100 Swadesh wordlist with those of its subsets to determine if reducing the size of the wordlist impact s its effectiveness. In the comparison, the 100, 50 and 40 wordlists were used to compute lexical distances of 29 Cushitic and Semitic languages spoken in Ethiopia and neighbouring countries. Gabmap, a based application, was employed to compute the lexical distances and to divide the languages into related clusters. The study shows that the subsets are not as effective as the 100 wordlist in clustering languages into smaller subgroups but they are equally effective in di viding languages into bigger groups such as subfamilies. It is noted that the subsets may lead to an erroneous classification whereby unrelated languages by chance form a cluster which is not attested by a comparative study. The chance to get a wrong result is higher when the subsets are used to classify languages which are not closely related. Though a further study is still needed to settle the issues around the size of the Swadesh wordlist, this study indicates that the 50 and 40 wordlists cannot be recommended as reliable substitute s for the 100 wordlist under all circumstances. The choice seems to be determined by the objective of a researcher and the degree of affiliation among the languages to be classified.

Keywords: classification, Cushitic, Swadesh, wordlist

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Authors: Karim Kootahi, Seyed Abolhasan Naeini

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The soil-water characteristic curve (SWCC), which represents the relationship between suction and water content (or degree of saturation), is an important property of unsaturated soils. The conventional method for determining SWCC is through specialized testing procedures. Since these procedures require specialized unsaturated soil testing apparatus and lengthy testing programs, several index properties-based correlations have been developed for estimating the SWCC of fine-grained soils. There are, however, considerable inconsistencies among the published correlations and there is no validation study on the predictive ability of existing correlations. In the present study, all existing index properties-based correlations are evaluated using a high quality worldwide database. The performances of existing correlations are assessed both graphically and quantitatively using statistical measures. The results of the validation indicate that most of the existing correlations provide unacceptable estimates of degree of saturation but the most recent model appears to be promising.

Keywords: SWCC, correlations, index properties, validation

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Authors: Baha Eddine Aissou, Aichouche Belhadj Aissa

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Light detection and ranging (LiDAR) is an active remote sensing technology used for several applications. Airborne LiDAR is becoming an important technology for the acquisition of a highly accurate dense point cloud. A classification of airborne laser scanning (ALS) point cloud is a very important task that still remains a real challenge for many scientists. Support vector machine (SVM) is one of the most used statistical learning algorithms based on kernels. SVM is a non-parametric method, and it is recommended to be used in cases where the data distribution cannot be well modeled by a standard parametric probability density function. Using a kernel, it performs a robust non-linear classification of samples. Often, the data are rarely linearly separable. SVMs are able to map the data into a higher-dimensional space to become linearly separable, which allows performing all the computations in the original space. This is one of the main reasons that SVMs are well suited for high-dimensional classification problems. Only a few training samples, called support vectors, are required. SVM has also shown its potential to cope with uncertainty in data caused by noise and fluctuation, and it is computationally efficient as compared to several other methods. Such properties are particularly suited for remote sensing classification problems and explain their recent adoption. In this poster, the SVM classification of ALS LiDAR data is proposed. Firstly, connected component analysis is applied for clustering the point cloud. Secondly, the resulting clusters are incorporated in the SVM classifier. Radial basic function (RFB) kernel is used due to the few numbers of parameters (C and γ) that needs to be chosen, which decreases the computation time. In order to optimize the classification rates, the parameters selection is explored. It consists to find the parameters (C and γ) leading to the best overall accuracy using grid search and 5-fold cross-validation. The exploited LiDAR point cloud is provided by the German Society for Photogrammetry, Remote Sensing, and Geoinformation. The ALS data used is characterized by a low density (4-6 points/m²) and is covering an urban area located in residential parts of the city Vaihingen in southern Germany. The class ground and three other classes belonging to roof superstructures are considered, i.e., a total of 4 classes. The training and test sets are selected randomly several times. The obtained results demonstrated that a parameters selection can orient the selection in a restricted interval of (C and γ) that can be further explored but does not systematically lead to the optimal rates. The SVM classifier with hyper-parameters is compared with the most used classifiers in literature for LiDAR data, random forest, AdaBoost, and decision tree. The comparison showed the superiority of the SVM classifier using parameters selection for LiDAR data compared to other classifiers.

Keywords: classification, airborne LiDAR, parameters selection, support vector machine

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Authors: Kaitlyn O'Mara, Michele Burford

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Estuaries and coastal bays can receive large quantities of sediment from surrounding catchments during flooding or high flow periods. Large river systems that feed freshwater into estuaries can flow through several catchments of varying geology. Human modification of catchments for agriculture, industry and urban use can contaminate soils with excess nutrients, trace metals and other pollutants. Land clearing, especially clearing of riparian vegetation, can accelerate erosion, mobilising, transporting and depositing soil particles into rivers, estuaries and coastal bays. In this study, a flood simulation experiment was used to study the flux of nutrients between soil particles and water during this erosion, transport and deposition process. Granite, sedimentary and basalt surface soils (as well as sub-soils of granite and sedimentary) were collected from eroding areas surrounding the Brisbane River, Australia. The <63 µm size fraction of each soil type was tumbled in freshwater for 3 days, to simulation flood erosion and transport, followed by stationary exposure to seawater for 4 weeks, to simulate deposition into estuaries. Filtered water samples were taken at multiple time points throughout the experiment and analysed for water nutrient concentrations. The highest rates of nutrient release occurred during the first hour of exposure to freshwater and seawater, indicating a chemical reaction with seawater that may act to release some nutrient particles that remain bound to the soil during turbulent freshwater transport. Although released at a slower rate than the first hour, all of the surface soil types showed continual ammonia, nitrite and nitrate release over the 4-week seawater exposure, suggesting that these soils may provide ongoing supply of these nutrients to estuarine waters after deposition. Basalt surface soil released the highest concentrations of phosphates and dissolved organic phosphorus. Basalt soils are found in much of the agricultural land surrounding the Brisbane River and contributed largely to the 2011 Brisbane River flood plume deposit in Moreton Bay, suggesting these soils may be a source of phosphate enrichment in the bay. The results of this study suggest that erosion of catchment soils during storm and flood events may be a source of nutrient supply in receiving waterways, both freshwater and marine, and that the amount of nutrient release following these events may be affected by the type of soil deposited. For example, flooding in different catchments of a river system over time may result in different algal and food web responses in receiving estuaries.

Keywords: flood, nitrogen, nutrient, phosphorus, sediment, soil

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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: Amna Shoaib, Sidrah Hanif, Rashid Mehmood

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Current research work was carried out to check influence of farmyard manure (FYM) in Lycopersicon esculentum L. against Fusarium oxysporum f. sp. lycopersici (FO) in copper polluted soil. Silt-loam soil naturally enriched with 70 ppm of Cu was inoculated with 1 x 106 spore suspensions of FO and incorporated with 0%, 1%, 1.5% or 2% FYM. The multilateral interaction of host-pathogen-metal-organic amendment was assessed in terms of morphology, growth, yield, physiology, biochemistry and metal uptake in tomato plant after 30 and 60 days of sowing. When soil was inoculated with FO, plant growth and biomass were significantly increased during vegetative stage, while declining during flowering stage with substantial increase in productivity over control. Infected plants exhibited late wilting and disease severity was found on 26-50% of plant during reproductive stage. Incorporation of up to 1% FYM suppressed disease severity, improved plant growth and biomass, while it decreased yield. Rest of manure doses was found ineffective in suppressing disease. Content of total chlorophyll, sugar and protein were significantly declined in FO inoculated plants and incorporation of FYM caused significant reduction or no influence on sugar and chlorophyll content, and no pronounced difference among different FYM doses were observed. On the other hand, proline, peroxidase, catalase and nitrate reductase activity were found to be increased in infected plants and incorporation of 1-2% FYM further enhanced the activity of these enzymes. Tomato plant uptake of 30-40% of copper naturally present in the soil and incorporation of 1-2% FYM markedly decreased plant uptake of metal by 15-30%, while increased Cu retention in soil. Present study concludes that lower dose (1%) of FYM could be used to manage disease, increase growth and biomass, while being ineffective for yield and productivity in Cu-polluted soil. Altered physiology/biochemistry of plant in response to any treatment could be served as basis for resistant against pathogen and metal homeostasis in plants.

Keywords: Lycopersicon esculentum, copper, Fusarium wilt, farm yard manure

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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: Abubakar Aminu

Abstract:

Sand dunes, as a major product of desertification, is well known to affect soil resources, water resources and vegetation, especially in arid and semi-arid region; this scenario disrupt the livelihood security of people in the affected areas. The research assessed the episode of sand dune accumulation on water resources, soil and vegetation in Gada local government of Sokoto State, Nigeria. In this paper, both qualitative and quantitative methods were used to generate data which was analyzed and discussed. The finding of the paper shows that livelihood was affected by accumulations of sand dunes as water resources and soils were affected negatively thereby reducing crop yields and making livestock domestication a very difficult and expensive task; the finding also shows that 60% of the respondents agreed to planting of trees as the major solution to combat sand dunes accumulation. However, the soil parameters tested indicated low Organic carbon, low Nitrogen, low Potassium, Calcium and Phosphorus but higher values were recorded in Sodium and Cation exchange capacity which served as evidence of the high or strong aridity nature of the soil in the area. In line with the above, the researcher recommended a massive tree planting campaign to curtail desertification as well as using organic manures for higher agricultural yield and as such, improvement in livelihood security.

Keywords: soils, vegetatio, water, desertification

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Authors: Girish J. Showkatramani, Arthi M. Krishna, Sashi Nareddi, Naresh Nula, Aaron Pepe, Glen Brown, Greg Gabel, Chris Doninger

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Trademark examination and approval is a complex process that involves analysis and review of the design components of the marks such as the visual representation as well as the textual data associated with marks such as marks' description. Currently, the process of identifying marks with similar visual representation is done manually in United States Patent and Trademark Office (USPTO) and takes a considerable amount of time. Moreover, the accuracy of these searches depends heavily on the experts determining the trademark design codes used to catalog the visual design codes in the mark. In this study, we explore several methods to automate trademark design code classification. Based on recent successes of convolutional neural networks in image classification, we have used several different convolutional neural networks such as Google’s Inception v3, Inception-ResNet-v2, and Xception net. The study also looks into other techniques to augment the results from CNNs such as using Open Source Computer Vision Library (OpenCV) to pre-process the images. This paper reports the results of the various models trained on year of annotated trademark images.

Keywords: trademark design code, convolutional neural networks, trademark image classification, trademark image search, Inception-ResNet-v2

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Authors: Nwanneka Mmonwuba

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Solid waste disposal to the environment was investigated by analyzing the quality characteristics of waste, air quality, and heavy metal concentration in the soil. The characteristics of waste were analyzed by enumerating the number of houses, hostels, hotels, markets, schools, and industries with the type of waste being discharged or deposited into the dump site. The percentage of waste was estimated with organic ranking first for both wet and dry seasons, 54% and 44%, respectively. The ambient air quality was analyzed using the crown gas monitor analyzer. The analysis showed that the mean concentration of NO₂, SO₂, and Co is 0.74, 0.37, and 47.35 ppm for the wet season and 0.47, 0.35, and 37.65 ppm for the dry season, respectively, and do not conform with the USEPA standard. The chemical analysis of the groundwater sample indicates alkalinity ranging from 7.38 to 9.11. the heavy metals concentration in the soil of cadmium, iron, copper, calcium, and potassium with 0.053, 0.722, 0227, 21.3, and 9.019, respectively, obtained from 0.3 m at the subsurface failed to conform to the NRC (2013) standard. Iron consent in the soil can be corrected using ascorbic acid and soda ash. The permanent reduction of effects is to try relocating people who live very close to the dumpsite, or the dumpsite should be sited elsewhere and replaced with a sanitary landfill.

Keywords: solid waste, groundwater, disposal, dumpsite

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Authors: Arturo Maldonado

Abstract:

In the iron ore mining industry, the intact strength of rock units is defined using the uniaxial compressive strength (UCS). This parameter is very important for the classification of shale materials, allowing the split between rock and cohesive soils based on the magnitude of UCS. For this research, it is assumed that UCS less than or equal to 1 MPa is representative of soils. Several researchers have anticipated that the magnitude of UCS reduces with weathering progression, also since UCS is a directional property, its magnitude depends upon the rock fabric orientation. Thus, the paper presents how the UCS of shales is affected by both weathering grade and bedding orientation. The mineralogy of shales has been defined using Hyper-spectral and chemical assays to define the mineral constituents of shale and other non-shale materials. Geological classification tools have been used to define distinct lithological types, and in this manner, the author uses mineralogical datasets to recognize and isolate shales from other rock types and develop tertiary plots for fresh and weathered shales. The mineralogical classification of shales has reduced the contamination of lithology types and facilitated the study of the physical factors affecting the intact strength of shales, like anisotropic strength due to bedding orientation. The analysis of mineralogical characteristics of shales is perhaps the most important contribution of this paper to other researchers who may wish to explore similar methods.

Keywords: rock mechanics, mineralogy, shales, weathering, anisotropy

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Authors: Emily Arangote

Abstract:

This paper defined the association between the indigenous knowledge, cultural practices and the ecosystem its implication to the environmental education to the farmers. Farmers recognize the need for sustainability of the ecosystem they inhabit. The cultural practices of farmers on use of indigenous pest control, use of insect-repellant plants, soil management practices that suppress diseases and harmful pests and conserve soil moisture are deemed to be ecologically-friendly. Indigenous plant materials that were more drought- and pest-resistant were grown. Crop rotation was implemented with various crop seeds to increase their disease resistance. Multi-cropping, planting of perennial crops, categorization of soil and planting of appropriate crops, planting of appropriate and leguminous crops, alloting land as watershed, and preserving traditional palay seed varieties were found to be beneficial in preserving the environment. The study also found that indigenous knowledge about crops are still relevant and useful to the current generation. This ensured the sustainability of our environment and incumbent on policy makers and educators to support and preserve for generations yet to come.

Keywords: cultural practices, ecosystem, environmental education, indigenous knowledge

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Authors: Carlos Tarmeño Noriega, Igor Aguilar Alonso

Abstract:

Fungal diseases are common in vineyards; they cause a decrease in the quality of the products that can be sold, generating distrust of the customer towards the seller when buying fruit. Currently, technology allows the classification of fruits according to their characteristics thanks to artificial intelligence. This study proposes the implementation of a control system that allows the identification of the main fungal diseases present in the Italia grape, making use of a convolutional neural network (CNN), OpenCV, and TensorFlow. The methodology used was based on a collection of 20 articles referring to the proposed research on quality control, classification, and recognition of fruits through artificial vision techniques.

Keywords: computer vision, convolutional neural networks, quality control, fruit market, OpenCV, TensorFlow

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Authors: Sanjeev Mukherjee, Satyendra Mittal

Abstract:

This paper presents the experimental investigations on the behaviour of a group of single, double and triple helical screw anchors embedded vertically at the same level in sand. The tests were carried out on one, two, three and four numbers of anchors in sand for different depths of embedment keeping shallow and deep mode of behaviour in mind. The testing program included 48 tests conducted on three model anchors installed in sand whose density kept constant throughout the tests. It was observed that the ultimate pullout load varied significantly with the installation depth of the anchor and the number of anchors. The apparent coefficient of friction (f*) between anchor and soil was also calculated based on the test results. It was found that the apparent coefficient of friction varies between 1.02 and 4.76 for 1, 2, 3, and 4 numbers of single, double and triple helical screw anchors. Plate load tests conducted on model soil showed that the value of ф increases from 35o for virgin soil to 48o for soil with four double screw helical anchors. The graphs of ultimate pullout capacity of a group of two, three and four no. of anchors with respect to one anchor were plotted and design equations have been proposed correlating them. Based on these findings, it has been concluded that the load-displacement relationships for all groups can be reduced to a common curve. A 3-D finite element model, PLAXIS, was used to confirm the results obtained from laboratory tests and the agreement is excellent.

Keywords: apparent coefficient of friction, helical screw anchor, installation depth, plate load test

Procedia PDF Downloads 555