Search results for: Saba Shams Bidhendi
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 37

Search results for: Saba Shams Bidhendi

7 Hydraulic Conductivity Prediction of Cement Stabilized Pavement Base Incorporating Recycled Plastics and Recycled Aggregates

Authors: Md. Shams Razi Shopnil, Tanvir Imtiaz, Sabrina Mahjabin, Md. Sahadat Hossain

Abstract:

Saturated hydraulic conductivity is one of the most significant attributes of pavement base course. Determination of hydraulic conductivity is a routine procedure for regular aggregate base courses. However, in many cases, a cement-stabilized base course is used with compromised drainage ability. Traditional hydraulic conductivity testing procedure is a readily available option which leads to two consequential drawbacks, i.e., the time required for the specimen to be saturated and extruding the sample after completion of the laboratory test. To overcome these complications, this study aims at formulating an empirical approach to predicting hydraulic conductivity based on Unconfined Compressive Strength test results. To do so, this study comprises two separate experiments (Constant Head Permeability test and Unconfined Compressive Strength test) conducted concurrently on a specimen having the same physical credentials. Data obtained from the two experiments were then used to devise a correlation between hydraulic conductivity and unconfined compressive strength. This correlation in the form of a polynomial equation helps to predict the hydraulic conductivity of cement-treated pavement base course, bypassing the cumbrous process of traditional permeability and less commonly used horizontal permeability tests. The correlation was further corroborated by a different set of data, and it has been found that the derived polynomial equation is deemed to be a viable tool to predict hydraulic conductivity.

Keywords: Hydraulic conductivity, unconfined compressive strength, recycled plastics, recycled concrete aggregates.

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6 Q-Map: Clinical Concept Mining from Clinical Documents

Authors: Sheikh Shams Azam, Manoj Raju, Venkatesh Pagidimarri, Vamsi Kasivajjala

Abstract:

Over the past decade, there has been a steep rise in the data-driven analysis in major areas of medicine, such as clinical decision support system, survival analysis, patient similarity analysis, image analytics etc. Most of the data in the field are well-structured and available in numerical or categorical formats which can be used for experiments directly. But on the opposite end of the spectrum, there exists a wide expanse of data that is intractable for direct analysis owing to its unstructured nature which can be found in the form of discharge summaries, clinical notes, procedural notes which are in human written narrative format and neither have any relational model nor any standard grammatical structure. An important step in the utilization of these texts for such studies is to transform and process the data to retrieve structured information from the haystack of irrelevant data using information retrieval and data mining techniques. To address this problem, the authors present Q-Map in this paper, which is a simple yet robust system that can sift through massive datasets with unregulated formats to retrieve structured information aggressively and efficiently. It is backed by an effective mining technique which is based on a string matching algorithm that is indexed on curated knowledge sources, that is both fast and configurable. The authors also briefly examine its comparative performance with MetaMap, one of the most reputed tools for medical concepts retrieval and present the advantages the former displays over the latter.

Keywords: Information retrieval (IR), unified medical language system (UMLS), Syntax Based Analysis, natural language processing (NLP), medical informatics.

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5 Forecasting Stock Price Manipulation in Capital Market

Authors: F. Rahnamay Roodposhti, M. Falah Shams, H. Kordlouie

Abstract:

The aim of the article is extending and developing econometrics and network structure based methods which are able to distinguish price manipulation in Tehran stock exchange. The principal goal of the present study is to offer model for approximating price manipulation in Tehran stock exchange. In order to do so by applying separation method a sample consisting of 397 companies accepted at Tehran stock exchange were selected and information related to their price and volume of trades during years 2001 until 2009 were collected and then through performing runs test, skewness test and duration correlative test the selected companies were divided into 2 sets of manipulated and non manipulated companies. In the next stage by investigating cumulative return process and volume of trades in manipulated companies, the date of starting price manipulation was specified and in this way the logit model, artificial neural network, multiple discriminant analysis and by using information related to size of company, clarity of information, ratio of P/E and liquidity of stock one year prior price manipulation; a model for forecasting price manipulation of stocks of companies present in Tehran stock exchange were designed. At the end the power of forecasting models were studied by using data of test set. Whereas the power of forecasting logit model for test set was 92.1%, for artificial neural network was 94.1% and multi audit analysis model was 90.2%; therefore all of the 3 aforesaid models has high power to forecast price manipulation and there is no considerable difference among forecasting power of these 3 models.

Keywords: Price Manipulation, Liquidity, Size of Company, Floating Stock, Information Clarity

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4 Effect of Reynolds Number on Flow past a Square Cylinder in Presence of Upstream and Downstream Flat Plate at Small Gap Spacing

Authors: Shams-ul-Islam, Raheela Manzoor, Zhou Chao Ying

Abstract:

A two-dimensional numerical study for flow past a square cylinder in presence of flat plate both at upstream and downstream position is carried out using the single-relaxation-time lattice Boltzmann method for gap spacing 0.5 and 1. We select Reynolds numbers from 80 to 200. The wake structure mechanism within gap spacing and near wake region, vortex structures around and behind the main square cylinder in presence of flat plate are studied and compared with flow pattern around a single square cylinder. The results are obtained in form of vorticity contour, streamlines, power spectra analysis, time trace analysis of drag and lift coefficients. Four different types of flow patterns were observed in both configurations, named as (i) Quasi steady flow (QSF), (ii) steady flow (SF), (iii) shear layer reattachment (SLR), (iv) single bluff body (SBB). It is observed that upstream flat plate plays a vital role in significant drag reduction. On the other hand, rate of suppression of vortex shedding is high for downstream flat plate case at low Reynolds numbers. The reduction in mean drag force and root mean square value of drag force for upstream flat plate case are89.1% and 86.3% at (Re, g) = (80, 0.5d) and (120, 1d) and reduction for downstream flat plate case for mean drag force and root mean square value of drag force are 11.10% and 97.6% obtained at (180, 1d) and (180, 0.5d).

Keywords: Detached flat plates, drag and lift coefficients, Reynolds numbers, square cylinder, Strouhal number.

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3 Land Suitability Prediction Modelling for Agricultural Crops Using Machine Learning Approach: A Case Study of Khuzestan Province, Iran

Authors: Saba Gachpaz, Hamid Reza Heidari

Abstract:

The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. This necessitates increased resource consumption and underscores the importance of addressing sustainable agriculture development along with other environmental considerations. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for 10 different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.

Keywords: Land suitability, machine learning, random forest, sustainable agriculture.

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2 Using 3-Glycidoxypropyltrimethoxysilane Functionalized SiO2 Nanoparticles to Improve Flexural Properties of Glass Fibers/Epoxy Grid-Stiffened Composite Panels

Authors: Reza Eslami-Farsani, Hamed Khosravi, Saba Fayazzadeh

Abstract:

Lightweight and efficient structures have the aim to enhance the efficiency of the components in various industries. Toward this end, composites are one of the most widely used materials because of durability, high strength and modulus, and low weight. One type of the advanced composites is grid-stiffened composite (GSC) structures, which have been extensively considered in aerospace, automotive, and aircraft industries. They are one of the top candidates for replacing some of the traditional components, which are used here. Although there are a good number of published surveys on the design aspects and fabrication of GSC structures, little systematic work has been reported on their material modification to improve their properties, to our knowledge. Matrix modification using nanoparticles is an effective method to enhance the flexural properties of the fibrous composites. In the present study, a silanecoupling agent (3-glycidoxypropyltrimethoxysilane/3-GPTS) was introduced onto the silica (SiO2) nanoparticle surface and its effects on the three-point flexural response of isogrid E-glass/epoxy composites were assessed. Based on the Fourier Transform Infrared Spectrometer (FTIR) spectra, it was inferred that the 3-GPTS coupling agent was successfully grafted onto the surface of SiO2 nanoparticles after modification. Flexural test revealed an improvement of 16%, 14%, and 36% in stiffness, maximum load and energy absorption of the isogrid specimen filled with 3 wt.% 3- GPTS/SiO2 compared to the neat one. It would be worth mentioning that in these structures, considerable energy absorption was observed after the primary failure related to the load peak. In addition, 3- GPTMS functionalization had a positive effect on the flexural behavior of the multiscale isogrid composites. In conclusion, this study suggests that the addition of modified silica nanoparticles is a promising method to improve the flexural properties of the gridstiffened fibrous composite structures.

Keywords: Isogrid-stiffened composite panels, silica nanoparticles, surface modification, flexural properties.

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1 Florida’s Groundwater and Surface Water System Reliability in Terms of Climate Change and Sea-Level Rise

Authors: Rahman Davtalab, Saba Ghotbi

Abstract:

Florida is one of the most vulnerable states to natural disasters among the 50 states of the USA. The state exposed by tropical storms, hurricanes, storm surge, landslide, etc. Besides the mentioned natural phenomena, global warming, sea-level rise, and other anthropogenic environmental changes make a very complicated and unpredictable system for decision-makers. In this study, we tried to highlight the effects of climate change and sea-level rise on surface water and groundwater systems for three different geographical locations in Florida; Main Canal of Jacksonville Beach in the northeast of Florida adjacent to the Atlantic Ocean, Grace Lake in central Florida, far away from surrounded coastal line, and Mc Dill in Florida and adjacent to Tampa Bay and Mexican Gulf. An integrated hydrologic and hydraulic model was developed and simulated for all three cases, including surface water, groundwater, or a combination of both. For the case study of Main Canal-Jacksonville Beach, the investigation showed that a 76 cm sea-level rise in time horizon 2060 could increase the flow velocity of the tide cycle for the main canal's outlet and headwater. This case also revealed how the sea level rise could change the tide duration, potentially affecting the coastal ecosystem. As expected, sea-level rise can raise the groundwater level. Therefore, for the Mc Dill case, the effect of groundwater rise on soil storage and the performance of stormwater retention ponds is investigated. The study showed that sea-level rise increased the pond’s seasonal high water up to 40 cm by time horizon 2060. The reliability of the retention pond is dropped from 99% for the current condition to 54% for the future. The results also proved that the retention pond could not retain and infiltrate the designed treatment volume within 72 hours, which is a significant indication of increasing pollutants in the future. Grace Lake case study investigates the effects of climate change on groundwater recharge. This study showed that using the dynamically downscaled data of the groundwater recharge can decline up to 24 % by the mid-21st century. 

Keywords: groundwater, surface water, Florida, retention pond, tide, sea-level rise

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