Search results for: soil texture prediction

Authors: M. Hassani, Y. Hassani, N. Ajudanioskooei, N. N. Benvid

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Laser Forming process as a non-contact thermal forming process is widely used to forming and bending of metallic and non-metallic sheets. In this process, according to laser irradiation along a specific path, sheet is bent. One of the most important output parameters in laser forming is bending angle that depends on process parameters such as physical and mechanical properties of materials, laser power, laser travel speed and the number of scan passes. In this paper, Artificial Neural Network and Fuzzy Logic System were used to predict of bending angle in laser forming process. Inputs to these models were laser travel speed and laser power. The comparison between artificial neural network and fuzzy logic models with experimental results has been shown both of these models have high ability to prediction of bending angles with minimum errors.

Keywords: artificial neural network, bending angle, fuzzy logic, laser forming

Procedia PDF Downloads 601

Authors: Dona Grace Jeyaseeli

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Water quality conditions in a pond are controlled by both natural processes and human influences. Natural factors such as the source of the pond water and the types of rock and soil in the pond watershed will influence some water quality characteristics. These factors are difficult to control but usually cause few problems. Instead, most serious water quality problems originate from land uses or other activities near or in the pond. The effects of these activities can often be minimized through proper management and early detection of problems through testing. In the present study a survey of three ponds in Coimbatore city, Tamilnadu, India were analyzed and found that water quality problems in their ponds, ranging from muddy water to fish kills. Unfortunately, most pond owners have never tested their ponds, and water quality problems are usually only detected after they cause a problem. Hence the present study discusses some common water quality parameters that may cause problems in ponds and how to detect through testing for better management of pond.

Keywords: water quality, pond, test, problem

Procedia PDF Downloads 512

Authors: Ekatereine Abashidze, Nino Nazarashvili, Dali Gaganidze, Oleg Gorgadze, Mariam Aznarashvili, Eter Gvritishvili

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Potato is one of the leading agricultural crops in Georgia. Georgia produces early and late potato varieties in almost all regions. Potato production is equal to 25,000 ha and its average yield is 20-25 t/ha. Among the plant pests that limit potato production and quality, the potato cyst nematodes (Globodera pallida (Stone) Behrens and Globodera rostochiensis (Wollenveber) Behrens) are harmful around the world. PCN is among the most difficult plant pests to control. Cysts protected by a durable wall can survive for over 30 years . Control of PCN (G. pallida and G. rostochiensis) is regulated by Council Directive 2007/33/EE C. There was no legislative regulation of these pests in Georgia before 2016. By Resolution #302 from July 1, 2016, developed within the action plan of the DCFTA (Deep and Comprehensive Free Trade Area) the Government of Georgia established control over potato cyst nematodes. The Agreement about the legal acts approximation to EU legislation concerns the approval of rules of PCN control and research of these pests. Taking into consideration the above mentioned, it is necessary to study PCN (G. pallida and G. rostochiensis) in the potato-growing areas of Georgia. The aim of this research is to conduct survey of potato cyst nematodes (Globodera rostochiensis and G. pallida) in two geographically distinct regions of Georgia - Samtskhe - Javakheti and Svanetii and to identify the species G. Rostochiensis and G. Pallida by the morphological - morphometric and molecular methods. Soil samples were taken in each village, in a zig-zag pattern on the potato fields of the private sector, using the Metlitsky method. Samples were taken also from infested potato plant roots. To extract nematode cysts from soil samples Fanwick can be used according to standard methods by EPPO. Cysts were measured under a stereoscopic microscope (Leica M50). Identification of the nematod species was carried out according to morphological and morphometric characteristics of the cysts and larvae using appropriate protocols EPPO. For molecular identification, a multiplex PCR test was performed by the universal ITS5 and cyst nematodes’ (G. pallida, G. rostochiensis) specific primers. To identify the species of potato cyst nematodes (PCN) in two regions (Samtskhe-Javakheti and Svaneti) were taken 200 samples, among them: 80 samples in Samtskhe-Javakheti region and 120 in Svaneti region. Cysts of Globiodera spp. were revealed in 50 samples obtained from Samtskhe-Javakheti and 80 samples from Svaneti regions. Morphological, morphometric and molecular analysis of two forms of PCN found in investigated regions of Georgia shows that one form of PCN belongs to G. rostoshiensi; the second form is the different species of Globodera sp.t is the subject of future research. Despite the different geographic locations, larvae and cysts of G. rostoshiensi were found in both regions. But cysts and larvae of G. pallida were not reported. Acknowledgement: The research has been supported by the Shota Rustaveli National Scientific Foundation of Georgia: Project # FR17_235.

Keywords: cyst nematode, globodera rostochiensis, globodera pallida, morphologic-morphometric measurement

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Authors: Gurjinder Singh Randhawa, Jonny Garg, Sukhraj Singh, Gurmeet Singh Cheema

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A major problem related to the use of rotavator is wear of rotavator blades due to abrasion by soil hard particles, as it seriously affects tillage quality and agricultural production economy. The objective of this study was to increase the wear resistance by covering the rotavator blades with two different hard facing electrodes. These blades are generally produced from low carbon or low alloy steel. During the field work i.e. preparing land for the cultivation these blades are subjected to severe wear conditions. Comparative wear tests on a regular rotavator blade and two kinds of hardfacing with electrodes were conducted in the field. These two different hardfacing electrodes, which are designated HARD ALLOY-400 and HARD ALLOY-650, were used for hardfacing. The wear rate in the field tests was found to be significantly different statistically. When the cost is taken into consideration; HARD ALLOY-650 and HARD ALLOY-400 have been found to be the best hardfacing electrodes.

Keywords: hardfacing, rotavator blades, hard alloy-400, abrasive wear

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Authors: Jarek Krajewski, David Daxberger

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We propose a stress detection method based on an RGB camera using heart rate detection, also known as Photoplethysmography Imaging (PPGI). This technique focuses on the measurement of the small changes in skin colour caused by blood perfusion. A stationary lab setting with simulated video conferences is chosen using constant light conditions and a sampling rate of 30 fps. The ground truth measurement of heart rate is conducted with a common PPG system. The proposed approach for pulse peak detection is based on a machine learning-based approach, applying brute force feature extraction for the prediction of heart rate pulses. The statistical analysis showed good agreement (correlation r = .79, p<0.05) between the reference heart rate system and the proposed method. Based on these findings, the proposed method could provide a reliable, low-cost, and contactless way of measuring HR parameters in daily-life environments.

Keywords: heart rate, PPGI, machine learning, brute force feature extraction

Procedia PDF Downloads 125

Authors: Murad Almadani, Khalil Abu-Hantash, Xinyu Wang, Herbert Jelinek, Kinda Khalaf

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Gait analysis is used by healthcare professionals as a tool to gain a better understanding of the movement impairment and track progress. In most circumstances, monitoring patients in their real-life environments with low-cost equipment such as cameras and wearable sensors is more important. Inertial sensors, on the other hand, cannot provide enough information on angular dynamics. This research offers a method for tracking 2D joint coordinates using cutting-edge vision algorithms and a single RGB camera. We provide an end-to-end comprehensive deep learning pipeline for marker-less gait parameter estimation, which, to our knowledge, has never been done before. To make our pipeline function in real-time for real-world applications, we leverage the AlphaPose human posture prediction model and a deep learning transformer. We tested our approach on the well-known GPJATK dataset, which produces promising results.

Keywords: gait analysis, human pose estimation, deep learning, real time gait estimation, AlphaPose, transformer

Procedia PDF Downloads 121

Authors: Hadi Farhadian, Homayoon Katibeh

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Groundwater inflow to the tunnels is one of the most important problems in tunneling operation. The objective of this study is the investigation of model dimension effects on tunnel inflow assessment in discontinuous rock masses using numerical modeling. In the numerical simulation, the model dimension has an important role in prediction of water inflow rate. When the model dimension is very small, due to low distance to the tunnel border, the model boundary conditions affect the estimated amount of groundwater flow into the tunnel and results show a very high inflow to tunnel. Hence, in this study, the two-dimensional universal distinct element code (UDEC) used and the impact of different model parameters, such as tunnel radius, joint spacing, horizontal and vertical model domain extent has been evaluated. Results show that the model domain extent is a function of the most significant parameters, which are tunnel radius and joint spacing.

Keywords: water inflow, tunnel, discontinues rock, numerical simulation

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Authors: Douglas E. Mainhart, Alejandro Fierro-Cabo, Bradley Christoffersen, Charlotte Reemts

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Semi-arid ecosystems across the globe have faced land conversion for agriculture and resource extraction activities, posing a threat to the important ecosystem services they provide. Revegetation-centered restoration efforts in these regions face low success rates due to limited soil water availability and high temperatures leading to elevated seedling mortality after planting. Typical methods to alleviate these stresses require costly post-planting interventions aimed at improving soil moisture status. We set out to evaluate the efficacy of applying in-nursery treatments to address transplant shock. Four native Tamaulipan thornscrub species were compared. Three treatments were applied: elevated CO2, drought hardening (four-week exposure each), and antitranspirant foliar spray (the day prior to planting). Our goal was to answer two primary questions: (1) Do treatments improve survival and growth of seedlings in the early period post-planting? (2) If so, what underlying physiological changes are associated with this improved performance? To this end, we measured leaf gas exchange (stomatal conductance, light saturated photosynthetic rate, water use efficiency), leaf morphology (specific leaf area), and osmolality before and upon the conclusion of treatments. A subset of seedlings from all treatments have been planted, which will be monitored in coming months for in-field survival and growth.First month field survival for all treatment groups were high due to ample rainfall following planting (>85%). Growth data was unreliable due to high herbivory (68% of all sampled plants). While elevated CO2 had infrequent or no detectable influence on all aspects of leaf gas exchange, drought hardening reduced stomatal conductance in three of the four species measured without negatively impacting photosynthesis. Both CO2 and drought hardening elevated leaf osmolality in two species. Antitranspirant application significantly reduced conductance in all species for up to four days and reduced photosynthesis in two species. Antitranspirants also increased the variability of water use efficiency compared to controls. Collectively, these results suggest that antitranspirants and drought hardening are viable treatments for reducing short-term water loss during the transplant shock period. Elevated CO2, while not effective at reducing water loss, may be useful for promoting more favorable water status via osmotic adjustment. These practices could improve restoration outcomes in Tamaulipan thornscrub and other semi-arid systems. Further research should focus on evaluating combinations of these treatments and their species-specific viability.

Keywords: conservation, drought conditioning, semi-arid restoration, plant physiology

Procedia PDF Downloads 86

Authors: H. Zidoum, A. AlShareedah, S. Al Sawafi, A. Al-Ansari, B. Al Lawati

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Systemic lupus erythematosus (SLE) is an autoimmune disease with genetic and environmental components. SLE is characterized by a wide variability of clinical manifestations and a course frequently subject to unpredictable flares. Despite recent progress in classification tools, the early diagnosis of SLE is still an unmet need for many patients. This study proposes an interpretable disease classification model that combines the high and efficient predictive performance of CatBoost and the model-agnostic interpretation tools of Shapley Additive exPlanations (SHAP). The CatBoost model was trained on a local cohort of 219 Omani patients with SLE as well as other control diseases. Furthermore, the SHAP library was used to generate individual explanations of the model's decisions as well as rank clinical features by contribution. Overall, we achieved an AUC score of 0.945, F1-score of 0.92 and identified four clinical features (alopecia, renal disorders, cutaneous lupus, and hemolytic anemia) along with the patient's age that was shown to have the greatest contribution on the prediction.

Keywords: feature selection, classification, systemic lupus erythematosus, model interpretation, SHAP, Catboost

Procedia PDF Downloads 86

Authors: Sinan Bilgen, Bekir Ozer Ay, Nilay Sezer Uzol

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After decades of conventional shapes, irregular forms with complex geometries are getting more popular for form generation of tall buildings all over the world. This trend has recently brought out diverse building forms such as twisting tall buildings. This study investigates both the aerodynamic and design features of twisting tall buildings through comparative analyses. Since twisting a tall building give rise to additional complexities related with the form and structural system, lateral load effects become of greater importance on these buildings. The aim of this study is to analyze the inherent characteristics of these iconic forms by comparing the wind loads on twisting tall buildings with those on their prismatic twins. Through a case study research, aerodynamic analyses of an existing twisting tall building and its prismatic counterpart were performed and the results have been compared. The prismatic twin of the original building were generated by removing the progressive rotation of its floors with the same plan area and story height. Performance-based measures under investigation have been evaluated in conjunction with the architectural design. Aerodynamic effects have been analyzed by both wind tunnel tests and computational methods. High frequency base balance tests and pressure measurements on 3D models were performed to evaluate wind load effects on a global and local scale. Comparisons of flat and real surface models were conducted to further evaluate the effects of the twisting form without façade texture contribution. Comparisons highlighted that, the twisting form under investigation shows better aerodynamic behavior both for along wind but particularly for across wind direction. Compared to the prismatic counterpart; twisting model is superior on reducing vortex-shedding dynamic response by disorganizing the wind vortices. Consequently, despite the difficulties arisen from inherent complexity of twisted forms, they could still be feasible and viable with their attractive images in the realm of tall buildings.

Keywords: aerodynamic tests, motivation for twisting, tall buildings, twisted forms, wind excitation

Procedia PDF Downloads 237

Authors: Duncan Oteki, Andebut Yeneneh, Daba Gedafa, Nabil Suleiman

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Most agencies lack the equipment required to measure the dynamic modulus (|E*|) of asphalt mixtures, necessitating the need to use predictive models. This study compared measured |E*| values for nine North Dakota asphalt mixes using the original Witczak, modified Witczak, and Hirsch models. The influence of temperature on the |E*| models was investigated, and Pavement ME simulations were conducted using measured |E*| and predictions from the most accurate |E*| model. The results revealed that the original Witczak model yielded the lowest Se/Sy and highest R² values, indicating the lowest bias and highest accuracy, while the poorest overall performance was exhibited by the Hirsch model. Using predicted |E*| as inputs in the Pavement ME generated conservative distress predictions compared to using measured |E*|. The original Witczak model was recommended for predicting |E*| for low-reliability pavements in North Dakota.

Keywords: asphalt mixture, binder, dynamic modulus, MEPDG, pavement ME, performance, prediction

Procedia PDF Downloads 51

Authors: Dana Kristalova

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This article deals with geographical conditions in terrain and their effect on the movement of vehicles, their effect on speed and safety of movement of people and vehicles. Finding of the optimal routes outside the communication is studied in the army environment, but it occur in civilian as well, primarily in crisis situation, or by the provision of assistance when natural disasters such as floods, fires, storms, etc. have happened. These movements require the optimization of routes when effects of geographical factors should be included. The most important factor is surface of the terrain. It is based on several geographical factors as are slopes, soil conditions, micro-relief, a type of surface and meteorological conditions. Their mutual impact has been given by coefficient of deceleration. This coefficient can be used for commander´s decision. New approaches and methods of terrain testing, mathematical computing, mathematical statistics or cartometric investigation are necessary parts of this evaluation.

Keywords: surface of a terrain, movement of vehicles, geographical factor, optimization of routes

Procedia PDF Downloads 466

Authors: Sudhir Kumar Tiwari

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The paper demonstrates a methodology that can be used at an early design stage of any conventional aircraft. This research activity assesses the feasibility derivation of methodology for aircraft loads estimation during the various phases of design for a transport category aircraft by utilizing potential of using commercial finite element analysis software, which may drive significant time saving. Early Design phase have limited data and quick changing configuration results in handling of large number of load cases. It is useful to idealize the aircraft as a connection of beams, which can be very accurately modelled using finite element analysis (beam elements). This research explores the correct approach towards idealizing an aircraft using beam elements. FEM Techniques like inertia relief were studied for implementation during course of work. The correct boundary condition technique envisaged for generation of shear force, bending moment and torque diagrams for the aircraft. The possible applications of this approach are the aircraft design process, which have been investigated.

Keywords: multi-disciplinary optimization, aircraft load, finite element analysis, stick model

Procedia PDF Downloads 356

Authors: Xiaocong He

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Self-pierce riveting (SPR) is a new high-speed mechanical fastening technique which is suitable for point joining dissimilar sheet materials, as well as coated and pre-painted sheet materials. Mechanical structures assembled by SPR are expected to possess a high damping capacity. In this study, experimental measurement techniques were proposed for the prediction of vibration behavior of single-lap cantilevered SPR beams. The dynamic test software and the data acquisition hardware were used in the experimental measurement of the dynamic response of the single-lap cantilevered SPR beams. Free and forced vibration behavior of the single-lap cantilevered SPR beams was measured using the LMS CADA-X experimental modal analysis software and the LMS-DIFA Scadas II data acquisition hardware. The frequency response functions of the SPR beams of different rivet number were compared. The main goal of the paper is to provide a basic measuring method for further research on vibration based non-destructive damage detection in single-lap cantilevered SPR beams.

Keywords: self-piercing riveting, dynamic response, experimental measurement, frequency response functions

Procedia PDF Downloads 432

Authors: Saima Nazir, Mustansar Ali Ghazanfar, Sanay Muhammad Umar Saeed, Muhammad Awais Azam, Saad Ali Alahmari

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Terrorism is an important and challenging concern. The entire world is threatened by only few sophisticated terrorist groups and especially in Gulf Region and Pakistan, it has become extremely destructive phenomena in recent years. Predicting the pattern of attack type, attack group and target type is an intricate task. This study offers new insight on terrorist group’s attack type and its chosen target. This research paper proposes a framework for prediction of terrorist attacks using the historical data and making an association between terrorist group, their attack type and target. Analysis shows that the number of attacks per year will keep on increasing, and Al-Harmayan in Saudi Arabia, Al-Qai’da in Gulf Region and Tehreek-e-Taliban in Pakistan will remain responsible for many future terrorist attacks. Top main targets of each group will be private citizen & property, police, government and military sector under constant circumstances.

Keywords: data mining, counter terrorism, machine learning, SVM

Procedia PDF Downloads 410

Authors: Isabel N. Sierra-Garcia, Maria J. Ferreira, Sandro Figuereido, Newton Gomes, Helena Silva, Angela Cunha

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Plant-associated microbial communities are considered crucial in the adaptation of halophytes to coastal environments. The plant microbiota can be horizontally acquired from the environment or vertically transmitted from generation to generation via seeds. Recruiting of the microbial communities by the plant is affected by geographical location, soil source, host genotype, and cultivation practice. There is limited knowledge reported on the microbial communities in halophytes the influence of biotic and abiotic factors. In this work, the microbiota associated with the halophyte Salicornia ramosissima was investigated to determine whether the structure of bacterial communities is influenced by host genotype or soil source. For this purpose, two contrasting sites where S. ramosissima is established in the estuarine system of the Ria de Aveiro were investigated. One site corresponds to a natural salt marsh where S. ramosissima plants are present (wild plants), and the other site is a former salt pan that nowadays are subjected to intensive crop production of S. ramosissima (crop plants). Bacterial communities from the rhizosphere, seeds and root endosphere of S. ramossisima from both sites were investigated by sequencing bacterial 16S rRNA gene using the Illumina MiSeq platform. The analysis of the sequences showed that the three plant-associated compartments, rhizosphere, root endosphere, and seed endosphere, harbor distinct microbiomes. However, bacterial richness and diversity were higher in seeds of wild plants, followed by rhizosphere in both sites, while seeds in the crop site had the lowest diversity. Beta diversity measures indicated that bacterial communities in root endosphere and seeds were more similar in both wild and crop plants in contrast to rhizospheres that differed by local, indicating that the recruitment of the similar bacterial communities by the plant genotype is active in regard to the site. Moreover, bacterial communities from the root endosphere and rhizosphere were phylogenetically more similar in both sites, but the phylogenetic composition of seeds in wild and crop sites was distinct. These results indicate that cultivation practices affect the seed microbiome. However, minimal vertical transmission of bacteria from seeds to adult plants is expected. Seeds from the crop site showed higher abundances of Kushneria and Zunongwangia genera. Bacterial members of the classes Alphaprotebacteria and Bacteroidia were the most ubiquitous across sites and compartments and might encompass members of the core microbiome. These findings indicate that bacterial communities associated with S. ramosissima are more influenced by host genotype rather than local abiotic factors or cultivation practices. This study provides a better understanding of the composition of the plant microbiota in S. ramosissima , which is essential to predict the interactions between plant and associated microbial communities and their effects on plant health. This knowledge is useful to the manipulations of these microbial communities to enhance the health and productivity of this commercially important plant.

Keywords: halophytes, plant microbiome, Salicornia ramosissima, agriculture

Procedia PDF Downloads 172

Authors: Tuji Jemal Ahmed

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Fresh produce is an essential component of a healthy diet. However, it can also be a potential source of pathogenic microorganisms that can cause foodborne illnesses. Traditional disinfection methods, such as washing with water and chlorine, have limitations and may not effectively remove or inactivate all microorganisms. This has led to the development of alternative/new methods of fresh produce disinfection, including physical and chemical methods. In this paper, we explore the physical and chemical new methods of fresh produce disinfection, their advantages and disadvantages, and their suitability for different types of produce. Physical methods of disinfection, such as ultraviolet (UV) radiation and high-pressure processing (HPP), are crucial in ensuring the microbiological safety of fresh produce. UV radiation uses short-wavelength UV-C light to damage the DNA and RNA of microorganisms, and HPP applies high levels of pressure to fresh produce to reduce the microbial load. These physical methods are highly effective in killing a wide range of microorganisms, including bacteria, viruses, and fungi. However, they may not penetrate deep enough into the product to kill all microorganisms and can alter the sensory characteristics of the product. Chemical methods of disinfection, such as acidic electrolyzed water (AEW), ozone, and peroxyacetic acid (PAA), are also important in ensuring the microbiological safety of fresh produce. AEW uses a low concentration of hypochlorous acid and a high concentration of hydrogen ions to inactivate microorganisms, ozone uses ozone gas to damage the cell membranes and DNA of microorganisms, and PAA uses a combination of hydrogen peroxide and acetic acid to inactivate microorganisms. These chemical methods are highly effective in killing a wide range of microorganisms, but they may cause discoloration or changes in the texture and flavor of some products and may require specialized equipment and trained personnel to produce and apply. In conclusion, the selection of the most suitable method of fresh produce disinfection should take into consideration the type of product, the level of microbial contamination, the effectiveness of the method in reducing the microbial load, and any potential negative impacts on the sensory characteristics, nutritional composition, and safety of the produce.

Keywords: fresh produce, pathogenic microorganisms, foodborne illnesses, disinfection methods

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Authors: Yu Zhang, Pedro Desouza

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Since big data has become substantially more accessible and manageable due to the development of powerful tools for dealing with unstructured data, people are eager to mine information from social media resources that could not be handled in the past. Sentiment analysis, as a novel branch of text mining, has in the last decade become increasingly important in marketing analysis, customer risk prediction and other fields. Scientists and researchers have undertaken significant work in creating and improving their sentiment models. In this paper, we present a concept of selecting appropriate classifiers based on the features and qualities of data sources by comparing the performances of five classifiers with three popular social media data sources: Twitter, Amazon Customer Reviews, and Movie Reviews. We introduced a couple of innovative models that outperform traditional sentiment classifiers for these data sources, and provide insights on how to further improve the predictive power of sentiment analysis. The modelling and testing work was done in R and Greenplum in-database analytic tools.

Keywords: sentiment analysis, social media, Twitter, Amazon, data mining, machine learning, text mining

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Authors: Sezin Ekşioğlu

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Multilabel classification has a huge importance for several applications, it is also a challenging research topic. It is a kind of supervised learning that contains binary targets. The distance between multilabel and binary classification is having more than one class in multilabel classification problems. Features can belong to one class or many classes. There exists a wide range of applications for multi label prediction such as image labeling, text categorization, gene functionality. Even though features are classified in many classes, they may not always be properly classified. There are many ensemble methods for the classification. However, most of the researchers have been concerned about better multilabel methods. Especially little ones focus on both efficiency of classifiers and pairwise relationships at the same time in order to implement better multilabel classification. In this paper, we worked on modified ensemble methods by getting benefit from k-Nearest Neighbors and neural network structure to address issues within a beneficial way and to get better impacts from the multilabel classification. Publicly available datasets (yeast, emotion, scene and birds) are performed to demonstrate the developed algorithm efficiency and the technique is measured by accuracy, F1 score and hamming loss metrics. Our algorithm boosts benchmarks for each datasets with different metrics.

Keywords: multilabel, classification, neural network, KNN

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Authors: Sabir Tehrankhan Hasanov, Mir Movsum Anar Dadashev

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The article provides a brief overview of irrigation systems and canals applied to slopes, landslide-prone, seismic areas, and swelling and collapsing soils. The contemporary construction of the canal used for irrigation, energy, and water supply purposes is described. In order to ensure the durability, longevity, and reliability of the channel, a damping mat made of cast material is created under its cover, and the top is covered with a waterproof screen. Dowels are placed on the bottom and sides of the channel, and the bottom dowel is riveted to the solid bedrock and connected with piles placed at certain distances. Drainage was placed next to the bottom dowel, an operation road was created on one side of the channel, and a berm road was created on the other side. A bathtub was built on the side of the road, and a forest-bush strip was built on its bank.

Keywords: slope, channel, landslide, collapse, swell, soil, structure

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Authors: Annisa Dewanti Putri, Wang Juan, Y. Qing Shan

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The structural assessment is one of a crucial part for ancient timber structure, in which this phase will be the reference for the maintenance and preservation phase. The mechanical properties of a structure are one of an important component of the structural assessment of building. Feiyun as one of the particular preserved building in China will become one of the Pioneer of Timber Structure Building Assessment. The 3-storey building which is located in Shanxi Province consists of complex ancient timber structure. Due to condition and preservation purpose, assessments (visual inspections, Non-Destructive Test and a Semi Non-Destructive test) were conducted. The stress wave measurement, moisture content analyzer, and the micro-drilling resistance meter data will overview the prediction of Mechanical Properties. As a result, the mechanical properties can be used for the next phase as reference for structural damage solutions.

Keywords: ancient structure, mechanical properties, non destructive test, stress wave, structural assessment, timber structure

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Authors: F. Massri, M. Shkarneh, B. Almassri

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Water scarcity and increasing water demand especially for residential use are major challenges facing Palestine. The need to accurately forecast water consumption is useful for the planning and management of this natural resource. The main objective of this paper is to (i) study the major factors influencing the water consumption in Palestine, (ii) understand the general pattern of Household water consumption, (iii) assess the possible changes in household water consumption and suggest appropriate remedies and (iv) develop prediction model based on the Artificial Neural Network to the water consumption in Palestinian cities. The paper is organized in four parts. The first part includes literature review of household water consumption studies. The second part concerns data collection methodology, conceptual frame work for the household water consumption surveys, survey descriptions and data processing methods. The third part presents descriptive statistics, multiple regression and analysis of the water consumption in the two Palestinian cities. The final part develops the use of Artificial Neural Network for modeling the water consumption in Palestinian cities.

Keywords: water management, demand forecasting, consumption, ANN, Ramallah

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Authors: Mohamed Elkashouty, Mohamed Yehia, Ahmed Tawfuk

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The study area is located in the southern part of Giza Governorate at both side of the Nile Valley. A combination of major and trace elements have been used to classify surface- and ground-waters in El Kurimat village, Egypt. The main purpose of the project is to investigate the surface-and ground-waters quality and hydrochemical evaluation. The situation is further complicated by contamination with lithogenic and anthropogenic (agricultural and sewage wastewaters) sources and low groundwater management strategies. The Quaternary aquifer consists of sands and gravels of Pleistocene age intercalated with clay lenses and overlain by silty clay aquitard (Holocene). The semi-pervious silty clay aquitard of the Holocene Nile sediments cover the Quaternary aquifer in most areas. The groundwater flows generally from southwest to northeast. To achieve this target, thirty five and seventy three samples were collected from surface– and ground-waters within summer and winter seasons 2009-2010). Total dissolved solids (TDS), cations, anions, NO2, NO3, PO4 , Al, Ba, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Zn, As, F, Sb, Se, Sn, Sr and V) were determined in water samples. Grain size analysis was achieved to eight soil samples and measured the organic matter percent in different fractions. The TDS concentration is high in Arab El Ein canal by lithogenic and anthropogenic sources. The average concentrations of TDS in the River Nile are 245 (summer) and 254 ppm (winter). NO3 content ranges from 1.7 to 12 mg/l (summer), while in winter it ranges from 0.4 to 2.4. Most of the toxic metal concentrations are below the drinking and irrigation guidelines except Mn, V, Cr, Al, and Fe, which are higher than the guidelines in some canals and drains. The TDS concentration in groundwater increases toward northeastern and northwestern part of the study area (i.e. toward limestone plateau). It is due to hydrogeological interconnection between Quaternary and Eocene aquifer (saline water), wastewater dump and recharge from wadi El Atfihi wastewater. There is a good match between the hydrogeology and the hydrogeochemistry. Total dissolved solid in groundwater increases toward southwestern part, may be due to hydrogeological interconnection between Quaternary and Eocene aquifer and leakage from agricultural waste water of El Mohut drain. Fe, Mn, Cr, Al, PO4 and NO3 concentrations are high due to anthropogenic sources, therefore they are unsuitable for drinking. The average concentration of Cr, Cu, Fe, Mn &Zn are higher in winter than those in summer due to winter drought. The organic matter content in soil are increases in the northeastern and southwestern part, with different fractions, sue to agricultural wastewaters. Reused of contaminated surface- and ground-waters samples by mixing with fresh water (By AquaChem) was estimated to increase the income per capita.

Keywords: surface water, groundwater, major ions, toxic metals

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Authors: Kalpana Adhikari, Mandip Subedi, Keshab Sharma, Indra P. Acharya

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The Gorkha Nepal earthquake of moment magnitude (Mw) 7.8 struck the central region of Nepal on April 25, 2015 with the epicenter about 77 km northwest of Kathmandu Valley . Peak ground acceleration observed during the earthquake was 0.18g. This motion induced several geotechnical effects such as landslides, foundation failures liquefaction, lateral spreading and settlement, and local amplification. An aftershock of moment magnitude (Mw) 7.3 hit northeast of Kathmandu on May 12 after 17 days of main shock caused additional damages. Kathmandu is the largest city in Nepal, have a population over four million. As the Kathmandu Valley deposits are composed mainly of sand, silt and clay layers with a shallow ground water table, liquefaction is highly anticipated. Extensive liquefaction was also observed in Kathmandu Valley during the 1934 Nepal-Bihar earthquake. Field investigations were carried out in Kathmandu Valley immediately after Mw 7.8, April 25 main shock and Mw 7.3, May 12 aftershock. Geotechnical investigation of both liquefied and non-liquefied sites were conducted after the earthquake. This paper presents observations of liquefaction and liquefaction induced damage, and the liquefaction potential assessment based on Standard Penetration Tests (SPT) for liquefied and non-liquefied sites. SPT based semi-empirical approach has been used for evaluating liquefaction potential of the soil and Liquefaction Potential Index (LPI) has been used to determine liquefaction probability. Recorded ground motions from the event are presented. Geological aspect of Kathmandu Valley and local site effect on the occurrence of liquefaction is described briefly. Observed liquefaction case studies are described briefly. Typically, these are sand boils formed by freshly ejected sand forced out of over-pressurized sub-strata. At most site, sand was ejected to agricultural fields forming deposits that varied from millimetres to a few centimeters thick. Liquefaction-induced damage to structures in these areas was not significant except buildings on some places tilted slightly. Boiled soils at liquefied sites were collected and the particle size distributions of ejected soils were analyzed. SPT blow counts and the soil profiles at ten liquefied and non-liquefied sites were obtained. The factors of safety against liquefaction with depth and liquefaction potential index of the ten sites were estimated and compared with observed liquefaction after 2015 Gorkha earthquake. The liquefaction potential indices obtained from the analysis were found to be consistent with the field observation. The field observations along with results from liquefaction assessment were compared with the existing liquefaction hazard map. It was found that the existing hazard maps are unrepresentative and underestimate the liquefaction susceptibility in Kathmandu Valley. The lessons learned from the liquefaction during this earthquake are also summarized in this paper. Some recommendations are also made to the seismic liquefaction mitigation in the Kathmandu Valley.

Keywords: factor of safety, geotechnical investigation, liquefaction, Nepal earthquake

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Authors: Abdull Halim Abdul, Muhaimin Sulam

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This paper is about a subsurface study of Taman Pudu Ulu, Cheras, Kuala Lumpur with emphasize of Geo mechanic properties based on stratum index factor in humanities environment. Subsurface drilling and seismic data were used to understand the subsurface condition of the study area such as the type and thickness of the strata. Borehole and soil samples were recovered Geo mechanic properties of the area by conducting number of experiments. Taman Pudu Ulu overlies the Kuala Lumpur Limestone formation that is known for its karstic features such as caves and cavities. Hence by knowing the Geo mechanic properties such as the normal strain and shear strain we can plan a safer and economics construction that is plan at the area in the future.

Keywords: stratum, index factor, geo mechanic properties, humanities environment

Procedia PDF Downloads 497

Authors: Snezhana G. Gocheva-Ilieva, Maya P. Stoimenova

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Ambient air pollution with fine particulate matter (PM10) is a systematic permanent problem in many countries around the world. The accumulation of a large number of measurements of both the PM10 concentrations and the accompanying atmospheric factors allow for their statistical modeling to detect dependencies and forecast future pollution. This study applies the classification and regression trees (CART) method for building and analyzing PM10 models. In the empirical study, average daily air data for the city of Pleven, Bulgaria for a period of 5 years are used. Predictors in the models are seven meteorological variables, time variables, as well as lagged PM10 variables and some lagged meteorological variables, delayed by 1 or 2 days with respect to the initial time series, respectively. The degree of influence of the predictors in the models is determined. The selected best CART models are used to forecast future PM10 concentrations for two days ahead after the last date in the modeling procedure and show very accurate results.

Keywords: cross-validation, decision tree, lagged variables, short-term forecasting

Procedia PDF Downloads 198

Authors: R. Testoni, R. Levizzari, M. De Salve

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Radioactive waste management is fundamental to safeguard population and environment by radiological risks. Environmental assessment of a site, where nuclear activities are located, allows understanding the hydro geological system and the radionuclides transport in groundwater and subsoil. Use of dedicated software is the basis of transport phenomena investigation and for dynamic scenarios prediction; this permits to understand the evolution of accidental contamination events, but at the same time the potentiality of the software itself can be verified. The aim of this paper is to perform a numerical analysis by means of HYDRUS 1D code, so as to evaluate radionuclides transport in a nuclear site in Piedmont region (Italy). In particular, the behaviour in vadose zone was investigated. An iterative assessment process was performed for risk assessment of radioactive contamination. The analysis therein developed considers the following aspects: i) hydro geological site characterization; ii) individuation of the main intrinsic and external site factors influencing water flow and radionuclides transport phenomena; iii) software potential for radionuclides leakage simulation purposes.

Keywords: HYDRUS 1D, radionuclides transport phenomena, site characterization, radiation protection

Procedia PDF Downloads 399

Authors: Ranveet Saggu, Saad Bin Ahmed

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Cardiovascular Disease (CVD) is the leading cause of death worldwide. One of its main manifestations, myocardial infarction (commonly known as a heart attack), occurs about 750,000 times a year, caused by insufficient blood flow to a portion of the heart muscle. A quick and accurate diagnosis of a heart attack or heart failure is crucial in the treatment of the patient. The aim of this research project is to improve the prediction of cardiovascular diseases by automating risk assessment using binary classifiers. The methodology includes Exploratory Data Analysis (EDA), which helps to obtain information about the dataset with the help of visualizations and metrics. Additionally, Feature Engineering techniques is employed to address missing values, outliers, feature extraction, and normalizing the dataset. Subsequently, various classification machine learning algorithms are trained, and their accuracy along with other metrics are evaluated to identify the most efficient model in terms of processing time and predictive performance.

Keywords: cardiovascular disease, machine learning, deci- sion trees, logistic regression, k-nearest neighbor, xgboost, random forest, gradient boosting

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Authors: Anurag Bhambhani, Jan Peter Van Der Hoek, Zoran Kapelan

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The food system depends on the availability of Phosphorus (P) and Nitrogen (N). Growing population, depleting Phosphorus reserves and energy-intensive industrial nitrogen fixation are threats to their future availability. Recovering P and N from domestic sewage water offers a solution. Recovered P and N can be applied to agricultural land, replacing virgin P and N. Thus, recovery from sewage water offers a solution befitting a circular economy. To ensure minimum waste and maximum resource efficiency a circularity assessment method is crucial to optimize nutrient flows and minimize losses. Material Circularity Indicator (MCI) is a useful method to quantify the circularity of materials. It was developed for materials that remain within the market and recently extended to include biotic materials that may be composted or used for energy recovery after end-of-use. However, MCI has not been used in the context of nutrient recovery. Besides, MCI is time-static, i.e., it cannot account for dynamic systems such as the terrestrial nutrient cycles. Nutrient application to agricultural land is a highly dynamic process wherein flows and stocks change with time. The rate of recycling of nutrients in nature can depend on numerous factors such as prevailing soil conditions, local hydrology, the presence of animals, etc. Therefore, a dynamic model of nutrient flows with indicators is needed for the circularity assessment. A simple substance flow model of P and N will be developed with the help of flow equations and transfer coefficients that incorporate the nutrient recovery step along with the agricultural application, the volatilization and leaching processes, plant uptake and subsequent animal and human uptake. The model is then used for calculating the proportions of linear and restorative flows (coming from reused/recycled sources). The model will simulate the adsorption process based on the quantity of adsorbent and nutrient concentration in the water. Thereafter, the application of the adsorbed nutrients to agricultural land will be simulated based on adsorbate release kinetics, local soil conditions, hydrology, vegetation, etc. Based on the model, the restorative nutrient flow (returning to the sewage plant following human consumption) will be calculated. The developed methodology will be applied to a case study of resource recovery from wastewater. In the aforementioned case study located in Italy, biochar or zeolite is to be used for recovery of P and N from domestic sewage through adsorption and thereafter, used as a slow-release fertilizer in agriculture. Using this model, information regarding the efficiency of nutrient recovery and application can be generated. This can help to optimize the recovery process and application of the nutrients. Consequently, this will help to optimize nutrient recovery and application and reduce the dependence of the food system on the virgin extraction of P and N.

Keywords: circular economy, dynamic substance flow, nutrient cycles, resource recovery from water

Procedia PDF Downloads 200

Authors: Sanjay M. Tailor, Urmila H. Patel

Abstract:

Phthalyl Sulfacetamide belongs to well-known member of antimicrobial sulfonamide family. It is a potent antitumor drug. Structural characteristics of 4-amino-N-(2quinoxalinyl) benzene-sulfonamides (Phthalyl Sulfacetamide), C14H12N4O2S has been studied by method of X-ray crystallography. The compound crystallizes in monoclinic space group P21/n with unit cell parameters a= 7.9841 Ǻ, b= 12.8208 Ǻ, c= 16.6607 Ǻ, α= 90˚, β= 93.23˚, γ= 90˚and Z=4. The X-ray based three-dimensional structure analysis has been carried out by direct methods and refined to an R-value of 0.0419. The crystal structure is stabilized by intermolecular N-H…N, N-H…O and π-π interactions. The Hirshfeld surfaces and consequently the fingerprint analysis have been performed to study the nature of interactions and their quantitative contributions towards the crystal packing. An analysis of Hirshfeld surfaces and fingerprint plots facilitates a comparison of intermolecular interactions, which are the key elements in building different supramolecular architectures. Docking is used for virtual screening for the prediction of the strongest binders based on various scoring functions. Docking studies are carried out on Phthalyl Sulfacetamide for better activity, which is important for the development of a new class of inhibitors.

Keywords: phthalyl sulfacetamide, crystal structure, hirshfeld surface analysis, docking

Procedia PDF Downloads 351