An Assessment of Urban Expansion Impacts on Land Transformation of Rajpur-Sonarpur Municipality

Urban expansion, population pressure, and increasing industrialization are influenced the world's natural environment, increased climate change, and global warming. Land use and land cover (LULC) changes are occurring due to anthropogenic activities and the results are land transformation, thermal variation, heat stress, and massive vegetation loss, which is increased oxygen deficiency and air pollution. Remote sensing-based Landsat TM and OLI/TIRS data were used to identify the land transformation and the effect of urbanization in Rajpur-Sonarpur Municipality in the years 2000 and 2020. The Built-up land was increased due to anthropogenic activities and around 12.16% area has been increased. Similarly, the agricultural land has been increased by 2.10 km2 area and vegetation area has been decreased around 6.52 km2 in the study area. The vegetation degradation areas were located in the South, South-west, and central parts of this study area. Correspondingly, North, North-west and central parts have a noticeable amount of built-up area developed. During twenty years, 6.97°C temperature was increased due to urban expansion, population pressure, transportation accessibility, and other urban amenities. The overall accuracies of classification maps were 96.25% and 91.64 % and the kappa coefficients were 0.95 and 0.89 respectively.

Estimation at Completion in Civil Engineering Projects: Review of Regression and Soft Computing Models

Construction projects are usually associated with several challenges owing to the varying process during the project lifetime. Hence, the final cost of any civil engineering project is influenced by many factors. There are numerous ways of determining the final cost of a project, however, the most essential approach is the Estimate at Completion (EAC) technique. This technique is mostly favored because it considers the probability of risks and project performance. Furthermore, EAC helps project managers in the definition and determination of the critical problems expected during the project period and the likely solutions toward these problems. In this review research, the basic empirical, regression and advanced soft computing methodologies adopted for the EAC computation, were surveyed and reported in detail. The review established on the base to recognize the modern advancement of the soft computing in computing the EAC with accurate, reliable and robust manner. The review was highlighted the main literature limitation, current status and possible future direction.

Impact of Increasing Pumping Discharge on Groundwater Level in the Nile Delta Aquifer, Egypt

The main goal of this research is to develop a 3D groundwater (GW) model using MODFLOW software to assess the potential effect of increasing pumping discharges on GW level in the Nile Delta Aquifer (NDA). In this study, the current state of the irrigation canals and GW recharge are considered in the GW model. The simulated GW level was compared with the observed GW level for model validation. Three vertical cross sections in western central and eastern areas of the ND are selected to check the impacts of GW pumping on variations of GW level. Ten scenarios of increasing the abstraction rates in all areas of the ND are tested. The results confirmed that increasing the pumping discharges has a substantial effect on decreasing the GW level in central and southern areas of the NDA. In addition, the tenth scenario is considered the last case where the drawdown of GW level reached 1.32, 1.59, and 2.41m in the southern boundaries. The findings of the study should be considered when studying the management of GW resources and the impacts of climate change on the ND.

Dew Point Time Series Forecasting at the North Dakota

Hydrological time series forecasting is one of the hot topics in the domain of statistical hydrology. Providing accurate forecasting can contribute to diverse applications for catchment sustainability and management. Dew point temperature (Tdew) is one of the complex hydrological processes that highly essential to be quantified accurately for several catchment activities such as crops, agriculture, and others. In this study, three types of models’ recursive strategy, direct strategy, and DirRec which is the combination of recursive and direct strategies were adopted to obtain h-steps ahead predictions of Tdew. Ten years monthly scale dataset of Tdew at two meteorological stations (Beach and Cavalier) located at the North Dakota, USA, were used for the modeling development. The performance of the considered models was compared with two benchmark models: autoregressive moving average (ARIMA) and exponential smoothing (ETS). Modeling results indicated that, compared with the benchmark models, the proposed methods gave good results for the multi-ahead forecasting. For instance, for Cavalier station, the root mean squared prediction errors obtained from the proposed and benchmark methods when the forecast horizon is 12 are as follows: recursive strategy (RMSPE = 3.731) direct strategy (RMSPE = 3.385), DirRec (RMSPE = 3.141), ARIMA (RMSPE = 12.957), and ETS (RMSPE = 27.479).

Implementing Recommender Systems using Machine Learning and Knowledge Discovery Tools

The current research offers a novel use of machine learning strategies to create a recommendation system. At recent era, recommender systems (RSs) have been used widely in e-commerce, entertainment purposes, and search engines. In more general, RSs are set of algorithms designed to recommend relevant items to users (movies to watch, books to read, products to buy, songs to listen, and others). This article discovers the different characteristics and features of many approaches used for recommendation systems in order to filter and prioritize the relevant information and work as a compass for searching. Recommender engines are crucial in some companies as they can create a big amount of income when they are effective or be a way to stand out remarkably from other rivals. As a proof of the importance of recommender engine, it can be stated that Netflix arrange a challenge (the “Netflix prize”) where the mission was to create a recommender engine that achieves better than its own algorithm with a prize of 1 million dollars to win.

On The Evaluation of Water Quality Index: Case Study of Euphrates River, Iraq

This study is used the water quality index (WQI), which is generated by combining several water quality parameters. This index gives a helpful representation of overall water quality for the public and all intended applications, and it demonstrates that pollution is beneficial in water quality management and decision-making. The Euphrates River was assessed in order to determine the quality of drinking water. The Euphrates River was assessed for drinking water quality using the WQI, which includes ten physicochemical water quality criteria. This was achieved by submitting comprehensive physicochemical analysis of water samples collected from 5 stations in the city of Hit-Iraq during 2020-2021. The ten physicochemical parameters included: pH value, Nitrate (NO3), Sulphate (SO4­), Turbidity, temperature, Calcium (Ca), Magnesium (Mg), sodium (Na), electric conductivity (EC) and Total Dissolved Solids (TDS). This was accomplished by submitting a full physicochemical analysis of water samples obtained from 5 sites in Hit, Iraq, between 2020 and 2021. The results of the present study show, the total average WQI was 110,156. The high WQI achieved is caused by the high TDS and magnesium concentration due to the different human activities along the river reach. The Euphrates River quality is classified as 'very poor quality' with a minimum WQI of 97.85 in June and 121.75 in November.

Feasibility of Utilizing Waste Polyethylene Terephthalate as Replacement in Asphalt binder Mixture

The feasibility of utilizing waste material for road construction is encouraging as it can decrease waste material harmful to the environment. Hence, a more sustainable method and a meticulous study of the available admixtures utilized to substitute standard asphalt binders with waste material must be conducted. However, there are several concerns and doubts about the real situation arising from the chemical and physical traits, as well as the mechanical performance issuing from the integration of waste material within the asphalt pavement to alleviate roads surface's permanent deformation. This investigation was carried out to study physical improvements made on ACW-14 bitumen by adding waste Polyethylene Terephthalate (PET) to serve as a partial replacement for bitumen content compared to normal, conventional 80/100 bitumen physical and rheological behavior. PET percentage added to the bitumen content was 10%, 8%, 6%, 4% and 2% of optimum bitumen content weight. The outcomes concluded that the best performance of bitumen on its density, VTM, VFB, flow, stability, and stiffness was achieved when 5.8% of Optimum Modified-Bitumen Content using PET. All the results obtained have been compared according to JKR Standards results, and the conclusion has fulfilled these requirements.

Identification of Affecting Factors on the Travel Time Reliability for Bus Transportation

Public bus transit travel time is affected by many factors, including traffic signals and traffic condition. Transit agencies have implemented transit signal priority (TSP) strategies to reduce transit travel time and improve service reliability. However, due to the lack of empirical data, these factors' collective impact and bus travel time strategies have not been studied at the stop-to-stop segment level. This research focuses on the factors affecting travel time reliability, emphasising the variability between operators and the policy implications of such differences. One-way analysis of variance (ANOVA) statistical methods have been used to assess the quality implications of public bus transportation time reliability. This research seeks to investigate the factors affecting the travel time (TT) reliability of bus transport. Studies were conducted along three bus routes serving different areas. Factors strongly related to TT reliability include route length, number of signalised intersections, day of the week, bus stops, departure delays, bus lane, passenger boarding and alighting, weather condition, and fare structure. Based on the proposed model factors affecting TT reliability, it was found that TT is strongly affected by the number of bus stoppings and also the length of the route. The reliability of all three routes during the weekday is low because of delays in departure. The number of signalised intersections along the route affects reliability. Meanwhile, more passengers boarding and paying cash increased the travel time reliability of buses.

A Comparison of Soft Computing Methods for the Prediction of Wave Height Parameters

In the previous studies on the prediction of wave height parameters, only the significant wave height has been considered as the unknown parameter to be predicted. However, the other wave height parameters, which may be required for the design of coastal structures depending on their importance level, have been neglected. Therefore, in this study, novel soft computing methods were used to predict all wave height parameters required for the design of coastal structures. To this end, wave data were derived from a buoy located in Southwest Black Sea Coast. Then, Multi-layer Perceptron Neural Network (MLPNN) and Adaptive-Neuro Fuzzy Inference System (ANFIS) models were developed to predict wave height parameters. Various input combinations were selected to create seven different sub-models. These sub-models were applied using developed MLPNN and ANFIS models. Accuracy of sub-models were evaluated for each wave height parameters in terms of performance evaluation criteria. The results showed that the wave height parameters predicted by the MLPNN and ANFIS methods are similar and both methods yield results acceptable for design purposes. However, for maximum wave height, Hmax, ANFIS sub-model yields slightly better results.

Lead sorption from aqueous solutions by kaolinite: laboratory experiments

The lead has adverse effects in contamination the aquatic environment, for this reason, a laboratory simulation was conducted using kaolinite collected from the Ga’ara Formation at western Iraq to be considered as a natural sorbent material that can be addressed Pb2+ from the aqueous environments. The Energy-Dispersive X-ray Spectroscopy and atomic absorption spectroscopy clarifying very fine grains and pure phase with a very little quantity of quartz and has a number of active sites for adsorption. The sorption of kaolinite for the Pb2+ has been carefully tested by several designed laboratory experiments. Five lead solutions of different concentrations (25, 50, 75, 100 and 125 ppm) were tested under different values of pH (1.3-9). The best sorption has been recorded at pH 9, with an equilibrium reaction time 40 m and the solid-liquid ration 1.25 gm:50 ml. The sorption reaction is endothermic with two main mechanisms were identified, the rapid ion exchange which gets at the beginning of the reaction during the first 10 m, and ion exchange, which gets slow later due to form ionic complexes