Search results for: water pipe networks

Authors: Purva Joshi, Rohit Thanki, Omar Hanif

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Unmanned aerial vehicles (UAVs) are becoming increasingly important in various industrial applications and sectors. Nowadays, a multi UAV network is used for specific types of communication (e.g., military) and monitoring purposes. Therefore, it is critical to reducing propagation delay during communication between UAVs, which is essential in a multi UAV network. This paper presents how the propagation delay between the base station (BS) and the UAVs is reduced using a searching algorithm. Furthermore, the iterative-based K-nearest neighbor (k-NN) algorithm and Travelling Salesmen Problem (TSP) algorthm were utilized to optimize the distance between BS and individual UAV to overcome the problem of propagation delay in multi UAV networks. The simulation results show that this proposed method reduced complexity, improved reliability, and reduced propagation delay in multi UAV networks.

Keywords: multi UAV network, optimal distance, propagation delay, K - nearest neighbor, traveling salesmen problem

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Authors: Won-Seok Kim, Hyung-Ik Shin

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Self-rated health (SRH) is a subjective assessment of individual health and has been identified as a strong predictor for mortality and morbidity. However few studies have been directed to the factors associated with SRH in persons with disabilities (PWD). We used data of 7th Korean national survey for 5307 PWD in 2008. Multiple logistic regression analysis was performed to find out independent risk factors for poor SRH in PWD. As a result, indicators of physical condition (poor instrumental ADL), socioeconomic disadvantages (poor education, economically inactive, low self-rated social class, medicaid in health insurance, presence of unmet need for hospital use) and social participation and networks (no use of internet service) were selected as independent risk factors for poor SRH in final model. Findings in the present study would be helpful in making a program to promote the health and narrow the gap of health status between the PWD.

Keywords: disabilities, risk factors, self-rated health, socioeconomic disadvantages, social networks

Procedia PDF Downloads 382

Authors: Chaitanya Chawla, Divya Panwar, Gurneesh Singh Anand, M. P. S Bhatia

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This paper presents a deep-learning mechanism for classifying computer generated images and photographic images. The proposed method accounts for a convolutional layer capable of automatically learning correlation between neighbouring pixels. In the current form, Convolutional Neural Network (CNN) will learn features based on an image's content instead of the structural features of the image. The layer is particularly designed to subdue an image's content and robustly learn the sensor pattern noise features (usually inherited from image processing in a camera) as well as the statistical properties of images. The paper was assessed on latest natural and computer generated images, and it was concluded that it performs better than the current state of the art methods.

Keywords: image forensics, computer graphics, classification, deep learning, convolutional neural networks

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Authors: T. Prommi, P. Thamsenanupap

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The influence of physicochemical water quality parameters on the abundance and diversity of caddisfly larvae was studied in seven sampling stations in Mae Tao and Mae Ku watersheds, Mae Sot District, Tak Province, northern Thailand. The streams: MK2 and MK8 as reference site, and impacted streams (MT1-MT5) were sampled bi-monthly during July 2011 to May 2012. A total of 4,584 individual of caddisfly larvae belonging to 10 family and 17 genera were found. The larvae of family Hydropsychidae were the most abundance, followed by Philopotamidae, Odontoceridae, and Leptoceridae, respectively. The genus Cheumatopsyche, Hydropsyche, and Chimarra were the most abundance genera in this study. Results of CCA ordination showed the total dissolved solids, sulfate, water temperature, dissolved oxygen and pH were the most important physicochemical factors to affect distribution of caddisflies communities. Changes in the caddisfly fauna may indicate changes in physicochemical factors owing to agricultural pollution, urbanization, or other human activities. Results revealed that the order Trichoptera, identified to species or genus, can be potentially used to assess environmental water quality status in freshwater ecosystems.

Keywords: Caddisfly larvae, environmental variables, diversity, streams

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Authors: Natia Gavardashvili

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From April through June of 2017, the field-scientific studies to ensure the safety of the population of Tbilisi were accomplished in the water catch basin of the river Vere, in the water catch basin of the river Jakhana dry gully. 5 sensitive sites were identified, and areas, 20x20 m each, were marked around them, with their locations fixed with GPS coordinates. The gained areas were plotted on a digital map, and the state of the surface was explored by considering the evaluation of erosive processes. Aiming at evaluating the soils and grounds of the sensitive areas, the ground samples were taken, and average diameter was identified, with its value changing to D0 = 4,67-15,48 mm, and integral curves of the grain size were drafted. By using the obtained data, the transporting capability of mudflow can be identified at the next stage to use to calculate mudflow peak discharges of different provisions in developing the new designs of mudflow-protection structures with the goal of ensuring the safety of Tbilisi population. The studies were accomplished under the financing of Young Scientists’ Grant of Shota Rustaveli National Science Foundation 'The study of erosive-mudflow processes in the water catch basin in the river Vere to ensure the safety of the population of Tbilisi and their consideration in developing new environmental protection plans' (YS15_2.1.5_8)

Keywords: water catch basin, mudflow-protection structures, erosive-mudflow processes, safety

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Authors: Ulas Vural, M. Ergun Okay, E. Mesut Yildiz

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Telecommunication service providers demand accurate and precise prediction of customer churn probabilities to increase the effectiveness of their customer relation services. The large amount of customer data owned by the service providers is suitable for analysis by machine learning methods. In this study, expenditure data of customers are analyzed by using an artificial neural network (ANN). The ANN model is applied to the data of customers with different billing duration. The proposed model successfully predicts the churn probabilities at 83% accuracy for only three months expenditure data and the prediction accuracy increases up to 89% when the nine month data is used. The experiments also show that the accuracy of ANN model increases on an extended feature set with information of the changes on the bill amounts.

Keywords: customer relationship management, churn prediction, telecom industry, deep learning, artificial neural networks

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Authors: Zita I. Šereš, Ljubica P. Dokić, Dragana M. Šoronja Simović, Cecilia Hodur, Zsuzsanna Laszlo, Ivana Nikolić, Nikola Maravić

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In this work the concentration of steep-water from corn starch industry is monitored using ultrafiltration membrane. The aim was to examine the conditions of ultrafiltration of steep-water by applying the membrane of 2.5nm. The parameters that vary during the course of ultrafiltration, were the transmembrane pressure, flow rate, while the permeate flux and the dry matter content of permeate and retentive were the dependent parameter constantly monitored during the process. Experiments of ultrafiltration are conducted on the samples of steep-water, which were obtained from the starch wet milling plant Jabuka, Pancevo. The procedure of ultrafiltration on a single-channel 250mm length, with inner diameter of 6.8mm and outer diameter of 10mm membrane were carried on. The membrane is made of a-Al2O3 with TiO2 layer obtained from GEA (Germany). The experiments are carried out at a flow rate ranging from 100 to 200lh-1 and transmembrane pressure of 1-3 bars. During the experiments of steep-water ultrafiltration, the change of permeate flux, dry matter content of permeate and retentive, as well as the absorbance changes of the permeate and retentive were monitored. The experimental results showed that the maximum flux reaches about 40lm-2h-1. For responses obtained after experiments, a polynomial model of the second degree is established to evaluate and quantify the influence of the variables. The quadratic equitation fits with the experimental values, where the coefficient of determination for flux is 0.96. The dry matter content of the retentive is increased for about 6%, while the dry matter content of permeate was reduced for about 35-40%, respectively. During steep-water ultrafiltration in permeate stays 40% less dry matter compared to the feed.

Keywords: ultrafiltration, steep-water, starch industry, ceramic membrane

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Authors: Neda Seyyedi, Reza Berangi

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Voice over IP (VOIP) network, also known as Internet telephony, is growing increasingly having occupied a large part of the communications market. With the growth of each technology, the related security issues become of particular importance. Taking advantage of this technology in different environments with numerous features put at our disposal, there arises an increasing need to address the security threats. Being IP-based and playing a signaling role in VOIP networks, Session Initiation Protocol (SIP) lets the invaders use weaknesses of the protocol to disable VOIP service. One of the most important threats is denial of service attack, a branch of which in this article we have discussed as flooding attacks. These attacks make server resources wasted and deprive it from delivering service to authorized users. Distributed denial of service attacks and attacks with a low rate can mislead many attack detection mechanisms. In this paper, we introduce a mechanism which not only detects distributed denial of service attacks and low rate attacks, but can also identify the attackers accurately. We detect and prevent flooding attacks in SIP protocol using Shannon (FDP-S), Renyi (FDP-R) and Tsallis (FDP-T) entropy. We conducted an experiment to compare the percentage of detection and rate of false alarm messages using any of the Shannon, Renyi and Tsallis entropy as a measure of disorder. Implementation results show that, according to the parametric nature of the Renyi and Tsallis entropy, by changing the parameters, different detection percentages and false alarm rates will be gained with the possibility to adjust the sensitivity of the detection mechanism.

Keywords: VOIP networks, flooding attacks, entropy, computer networks

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Authors: Guenther Schuh, Sebastian Woelk

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Companies face increasing challenges in research due to higher costs and risks. The intensifying technology complexity and interdisciplinarity require unique know-how. Therefore, companies need to decide whether research shall be conducted internally or externally with partners. On the other hand, research institutes meet increasing efforts to achieve good financing and to maintain high research reputation. Therefore, relevant research topics need to be identified and specialization of competency is necessary. However, additional competences for solving interdisciplinary research projects are also often required. Secured financing can be achieved by bonding industry partners as well as public fundings. The realization of faster and better research drives companies and research institutes to cooperate in organized research networks, which are managed by an administrative organization. For an effective and efficient cooperation, necessary processes, roles, tools and a set of rules need to be determined. The goal of this paper is to show the state-of-art research and to propose a governance framework for organized research networks.

Keywords: interorganizational cooperation, design of network governance, research network

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Authors: Oluwaseun K. Oyebode, Josiah A. Adeyemo

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Hydrological modelling plays a crucial role in the planning and management of water resources, most especially in water stressed regions where the need to effectively manage the available water resources is of critical importance. However, due to the complex, nonlinear and dynamic behaviour of hydro-climatic interactions, achieving reliable modelling of water resource systems and accurate projection of hydrological parameters are extremely challenging. Although a significant number of modelling techniques (process-based and data-driven) have been developed and adopted in that regard, the field of hydrological modelling is still considered as one that has sluggishly progressed over the past decades. This is majorly as a result of the identification of some degree of uncertainty in the methodologies and results of techniques adopted. In recent times, evolutionary computation (EC) techniques have been developed and introduced in response to the search for efficient and reliable means of providing accurate solutions to hydrological related problems. This paper presents a comprehensive review of the underlying principles, methodological needs and applications of a promising evolutionary computation modelling technique – genetic programming (GP). It examines the specific characteristics of the technique which makes it suitable to solving hydrological modelling problems. It discusses the opportunities inherent in the application of GP in water related-studies such as rainfall estimation, rainfall-runoff modelling, streamflow forecasting, sediment transport modelling, water quality modelling and groundwater modelling among others. Furthermore, the means by which such opportunities could be harnessed in the near future are discussed. In all, a case for total embracement of GP and its variants in hydrological modelling studies is made so as to put in place strategies that would translate into achieving meaningful progress as it relates to modelling of water resource systems, and also positively influence decision-making by relevant stakeholders.

Keywords: computational modelling, evolutionary algorithms, genetic programming, hydrological modelling

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Authors: Lungile Maliba, O. I. Nkwonta, E Onyari

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Water resources development and management are regarded as crucial for poverty reduction in many developing countries and sustainable economic growth such as South Africa. The contribution of large hydraulic infrastructure and management of it, particularly reservoirs, to development remains controversial. This controversy stems from the fact that from a historical point of view construction of reservoirs has brought fewer benefits than envisaged and has resulted in significant environmental and social costs. A further complexity in reservoir management is the variety of stakeholders involved, all with different objectives, including domestic and industrial water use, flood control, irrigation and hydropower generation. The objective was to evaluate technical adaptation options for kleinfontein Dam’s current operating rule curves. To achieve this objective, the current operating rules curves being used in the sub-basin were analysed. An objective methodology was implemented in other to get the operating rules with regards to the target storage curves. These were derived using the Water Resources Yield/Planning Model (WRY/PM), with the aim of maximising of releases to demand zones. The result showed that the system is over allocated and in addition the demands exceed the long-term yield that is available for the system. It was concluded that the current operating rules in the system do not produce the optimum operation such as target storage curves to avoid supply failures in the system.

Keywords: infrastructure, Kleinfontein dam, operating rule curve, water resources yield and planning model

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Authors: Eka Sari

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Potential degradation of cellulose and hemicellulose during the fungal pretreatment of lignocellulose has led to fermentable sugar yield will be low. This potential is even greater if the pretreatment of lignocellulosic that have low lignin such as water hyacinth. In order to prepare lignocellulose that have low lignin content, especially water hyacinth efforts are needed to prevent the degradation of cellulose and cellulose. One attempt to prevent the degradation of cellulose and hemicellulose is to replace the substrate needed by the addition of a simple carbon compounds such as glucose. Glucose sources used in this study is molasses. The purpose of this research to get the right of concentration of molasses to reduce the degradation of cellulose and hemicellulose during the pretreatment process and obtain fermentable sugar yields on high. The results showed that the addition of molasses with a concentration of 2% is able to reduce the degradation of cellulose from 25.53% to 10% and hemicellulose degradation of 20.12% to 10.89%. Fermentable sugar yields produced only reached 43.91%. To improve the yield of glucose is then performed additional combonation of molasses of 2% molasses and co-factor Mn2+ 0.5%. Fermentable sugar yield increased to 67.66% and the degradation of cellulose and hemicellulose decreased to 2.44% and 2.71%, respectively.

Keywords: water hyacinth, cellulose, hemicelulose, degradation, pretreatment, fungus

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Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a distributed hybrid algorithm is proposed for solving the job shop scheduling problem. The suggested method executes different artificial neural networks, heuristics and meta-heuristics simultaneously on more than one machine. The neural networks are used to control the constraints of the problem while the meta-heuristics search the global space and the heuristics are used to prevent the premature convergence. To attain an efficient distributed intelligent method for solving big and distributed job shop scheduling problems, Apache Spark and Hadoop frameworks are used. In the algorithm implementation and design steps, new approaches are applied. Comparison between the proposed algorithm and other efficient algorithms from the literature shows its efficiency, which is able to solve large size problems in short time.

Keywords: distributed algorithms, Apache Spark, Hadoop, job shop scheduling, neural network

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Authors: Ahmadu Maidorawa, Kamalrulnizam Abu Bakar

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This paper proposed an Enhanced Connectivity Aware Routing (ECAR) protocol for Vehicular Ad hoc Network (VANET). The protocol uses a control broadcast to reduce the number of overhead packets needed in a route discovery process. It is also equipped with an alternative backup route that is used whenever a primary path to destination failed, which highly reduces the frequent launching and re-launching of the route discovery process that waste useful bandwidth and unnecessarily prolonging the average packet delay. NS2 simulation results show that the performance of ECAR protocol outperformed the original connectivity aware routing (CAR) protocol by reducing the average packet delay by 28%, control overheads by 27% and increased the packet delivery ratio by 22%.

Keywords: alternative path, primary path, protocol, routing, VANET, vehicular ad hoc networks

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Authors: Jennifer Cuellar, Angie L. Parada, Kevin N. S. Chacon, Sol M. Mejia

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The purification of bio-ethanol through distillation methods is an unresolved issue at the biofuel industry because of the ethanol-water azeotrope formation, which increases the steps of the purification process and subsequently increases the production costs. Therefore, understanding the mixture nature at the molecular level could provide new insights for improving the current methods and/or designing new and more efficient purification methods. For that reason, the present study focuses on the evaluation and analysis of (ethanol)₉-water heterodecamers, as the systems with the minimum molecular proportion that represents the azeotropic concentration (96 %m/m in ethanol). The computational modelling was carried out with B3LYP-D3/6-311++G(d,p) in Gaussian 09. Initial explorations of the potential energy surface were done through two methods: annealing simulated runs and molecular dynamics trajectories besides intuitive structures obtained from smaller (ethanol)n-water heteroclusters, n = 7, 8 and 9. The energetic order of the seven stable heterodecamers determines the most stable heterodecamer (Hdec-1) as a structure forming a bicyclic geometry with the O-H---O hydrogen bonds (HBs) where the water is a double proton donor molecule. Hdec-1 combines 1 water molecule and the same quantity of every ethanol conformer; this is, 3 trans, 3 gauche 1 and 3 gauche 2; its abundance is 89%, its decamerization energy is -80.4 kcal/mol, i.e. 13 kcal/mol most stable than the less stable heterodecamer. Besides, a way to understand why methanol does not form an azeotropic mixture with water, analogous systems ((ethanol)10, (methanol)10, and (methanol)9-water)) were optimized. Topologic analysis of the electron density reveals that Hec-1 forms 33 weak interactions in total: 11 O-H---O, 8 C-H---O, 2 C-H---C hydrogen bonds and 12 H---H interactions. The strength and abundance of the most unconventional interactions (H---H, C-H---O and C-H---O) seem to explain the preference of the ethanol for forming heteroclusters instead of clusters. Besides, O-H---O HBs present a significant covalent character according to topologic parameters as the Laplacian of electron density and the relationship between potential and kinetic energy densities evaluated at the bond critical points; obtaining negatives values and values between 1 and 2, for those two topological parameters, respectively.

Keywords: ADMP, DFT, ethanol-water azeotrope, Grimme dispersion correction, simulated annealing, weak interactions

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Authors: Trevor Malambo Simbayi, Diane Hildebrandt, Tonderayi Matambo

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The rapid growth of population in recent decades has resulted in an increased need for energy to meet human activities. As energy demands increase, the need for other sources of energy other than fossil fuels, increases in turn. Furthermore, environmental concerns such as global warming due to the use of fossil fuels, depleting fossil fuel reserves and the rising cost of oil have contributed to an increased interest in renewables sources of energy. Biogas is a renewable source of energy produced through the process of anaerobic digestion (AD) and it offers a two-fold solution; it provides an environmentally friendly source of energy and its production helps to reduce the amount of organic waste taken to landfills. This research seeks to address the waste management problem caused by an aquatic weed called water hyacinth (Eichhornia crassipes) at the Hartbeespoort (Harties) Dam in the North West Province of South Africa, through biogas production of the weed. Water hyacinth is a category 1 invasive species and it is deemed to be the most problematic aquatic weed. This weed is said to double its size in the space of five days. Eutrophication in the Hartbeespoort Dam has manifested itself through the excessive algae bloom and water hyacinth infestation. A large amount of biomass from water hyacinth and algae are generated per annum from the two hundred hectare surface area of the dam exposed to the sun. This biomass creates a waste management problem. Water hyacinth when in full bloom can cover nearly half of the surface of Hartbeespoort Dam. The presence of water hyacinth in the dam has caused economic and environmental problems. Economic activities such as fishing, boating, and recreation, are hampered by the water hyacinth’s prolific growth. This research proposes the use of water hyacinth as a feedstock or substrate for biogas production in order to find an economic and environmentally friendly means of waste management for the communities living around the Hartbeespoort Dam. In order to achieve this objective, water hyacinth will be collected from the dam and it will be mechanically pretreated before anaerobic digestion. Pretreatment is required for lignocellulosic materials like water hyacinth because such materials are called recalcitrant solid materials. Cow manure will be employed as a source of microorganisms needed for biogas production to occur. Once the water hyacinth and the cow dung are mixed, they will be placed in laboratory anaerobic reactors. Biogas production will be monitored daily through the downward displacement of water. Characterization of the substrates (cow manure and water hyacinth) to determine the nitrogen, sulfur, carbon and hydrogen, total solids (TS) and volatile solids (VS). Liquid samples from the anaerobic digesters will be collected and analyzed for volatile fatty acids (VFAs) composition by means of a liquid gas chromatography machine.

Keywords: anaerobic digestion, biogas, waste management, water hyacinth

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Authors: Natsuki Kishizawa, Keiko Nakano, Hussam Organji, Amer Shaiban, Mohammad Albeirutty

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One of the most important tasks in operating desalination plants using a reverse osmosis (RO) method is preventing RO membrane fouling caused by foulants found in seawater. Optimal design of the pre-treatment process of RO process for plants enables the reduction of foulants. Therefore, a quantitative evaluation of the fouling risk in pre-treated water, which is fed to RO, is required for optimal design. Some measurement methods for water quality such as silt density index (SDI) and total organic carbon (TOC) have been conservatively applied for evaluations. However, these methods have not been effective in some situations for evaluating the fouling risk of RO feed water. Furthermore, stable management of plants will be possible by alerts and appropriate control of the pre-treatment process by using the method if it can be applied to the inline monitoring system for the fouling risk of RO feed water. The purpose of this study is to develop a method to evaluate the fouling risk of RO feed water. We applied a quartz crystal microbalance (QCM) to measure the amount of foulants found in seawater using a sensor whose surface is coated with polyamide thin film, which is the main material of a RO membrane. The increase of the weight of the sensor after a certain length of time in which the sample water passes indicates the fouling risk of the sample directly. We classified the values as “FP: Fouling Potential”. The characteristics of the method are to measure the very small amount of substances in seawater in a short time: < 2h, and from a small volume of the sample water: < 50mL. Using some RO cell filtration units, a higher correlation between the pressure increase given by RO fouling and the FP from the method than SDI and TOC was confirmed in the laboratory-scale test. Then, to establish the correlation in the actual bench-scale RO membrane module, and to confirm the feasibility of the monitoring system as a control tool for the pre-treatment process, we have started a long-term test at an experimental desalination site by the Red Sea in Jeddah, Kingdom of Saudi Arabia. Implementing inline equipment for the method made it possible to measure FP intermittently (4 times per day) and automatically. Moreover, for two 3-month long operations, the RO operation pressure among feed water samples of different qualities was compared. The pressure increase through a RO membrane module was observed at a high FP RO unit in which feed water was treated by a cartridge filter only. On the other hand, the pressure increase was not observed at a low FP RO unit in which feed water was treated by an ultra-filter during the operation. Therefore, the correlation in an actual scale RO membrane was established in two runs of two types of feed water. The result suggested that the FP method enables the evaluation of the fouling risk of RO feed water.

Keywords: fouling, monitoring, QCM, water quality

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Authors: AmirHossein Mohajerzadeh, Mohammad Alishahi, Saeed Aslishahi, Mohsen Zabihi

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In this paper, we consider sensor nodes with the capability of measuring the bearings (relative angle to the target). We use geometric methods to select a set of observer nodes which are responsible for collecting data from the target. Considering the characteristics of target tracking applications, it is clear that significant numbers of sensor nodes are usually inactive. Therefore, in order to minimize the total network energy consumption, a set of sensor nodes, called sentinel, is periodically selected for monitoring, controlling the environment and transmitting data through the network. The other nodes are inactive. Furthermore, the proposed algorithm provides a joint scheduling and routing algorithm to transmit data between network nodes and the fusion center (FC) in which not only provides an efficient way to estimate the target position but also provides an efficient target tracking. Performance evaluation confirms the superiority of the proposed algorithm.

Keywords: coverage, routing, scheduling, target tracking, wireless sensor networks

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Authors: Humanyun Zahir, Irtsam Ghazi

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This report outlines the basic installation and operation of magnetic inductive flow velocity sensors on large underground cooling water pipelines. Research on the effects of cathodic protection as well as into other factors that might influence the overall performance of the meter are presented in this paper. The experiments were carried out on an immersion type magnetic meter specially used for flow measurement of cooling water pipeline. An attempt has been made in this paper to outline guidelines that can ensure accurate measurement related to immersion type magnetic meters on underground pipelines.

Keywords: magnetic induction, flow meter, Faraday's law, immersion, cathodic protection, anode, cathode, flange, grounding, plant information management system, electrodes

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Authors: Inga Badasyan

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Every year we do monitoring of water pollution of catchment basin of Debed River. Next, the Ministry of Nature Protection does modeling programme. Finely, we are managing the impact of water pollution in Debed river. Ecosystem technologies efficiency performance were estimated based on the physical, chemical, and macrobiological analyses of water on regular base between 2012 to 2015. Algae community composition was determined to assess the ecological status of Debed river, while vegetation was determined to assess biodiversity. Last time, experts werespeaking about global warming, which is having bad impact on the surface water, freshwater, etc. As, we know that global warming is caused by the current high levels of carbon dioxide in the water. Geochemical modelling is increasingly playing an important role in various areas of hydro sciences and earth sciences. Geochemical modelling of highly concentrated aqueous solutions represents an important topic in the study of many environments such as evaporation ponds, groundwater and soils in arid and semi-arid zones, costal aquifers, etc. The sampling time is important for benthic macroinvertebrates, for that reason we have chosen in the spring (abundant flow of the river, the beginning of the vegetation season) and autumn (the flow of river is scarce). The macroinvertebrates are good indicator for a chromic pollution and aquatic ecosystems. Results of our earlier investigations in the Debed river reservoirs clearly show that management problem of ecosystem reservoirs is topical. Research results can be applied to studies of monitoring water quality in the rivers and allow for rate changes and to predict possible future changes in the nature of the lake.

Keywords: ecohydrological monitoring, flood risk management, global warming, aquatic macroinvertebrates

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Authors: Rosendo Mendoza, María Carmen Hidalgo, María José Campos-Suñol, Julián Martínez, Javier Rey

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The impact of mining environmental liabilities and mine drainage on surface water quality has been investigated in the hydrographic basin of the La Carolina mining district (southern Spain). This abandoned mining district is characterized by the existence of important mineralizations of sulfoantimonides of Pb - Ag, and sulfides of Cu - Fe. All surface waters reach the main river of this mining area, the Grande River, which ends its course in the Rumblar reservoir. This waterbody is intended to supply 89,000 inhabitants, as well as irrigation and livestock. Therefore, the analysis and control of the metal(loid) concentration that exists in these surface waters is an important issue because of the potential pollution derived from metallic mining. A hydrogeochemical campaign consisting of 20 water sampling points was carried out in the hydrographic network of the Grande River, as well as two sampling points in the Rumbler reservoir and at the main tailings impoundment draining to the river. Although acid mine drainage (pH below 4) is discharged into the Grande river from some mine adits, the pH values in the river water are always neutral or slightly alkaline. This is mainly the result of a dilution process of the small volumes of mine waters by net alkaline waters of the river. However, during the dry season, the surface waters present high mineralization due to a constant discharge from the abandoned flooded mines and a decrease in the contribution of surface runoff. The concentrations of dissolved Cd and Pb in the water reach values of 2 and 81 µg/l, respectively, exceeding the limit established by the Environmental Quality Standard for surface water. In addition, the concentrations of dissolved As, Cu, and Pb in the waters of the Rumblar reservoir reached values of 10, 20, and 11 µg/l, respectively. These values are higher than the maximum allowable concentration for human consumption, a circumstance that is especially alarming.

Keywords: environmental quality, hydrogeochemistry, metal mining, surface water

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Authors: Srestha Chaturabul, Wanchalerm Srirachat, Thanaporn Wannachod, Prakorn Ramakul, Ura Pancharoen, Soorathep Kheawhom

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The separation of mercury(II) from petroleum-produced water from the Gulf of Thailand was carried out using a hollow fiber supported liquid membrane system (HFSLM). Optimum parameters for feed pretreatment were 0.2 M HCl, 4% (v/v) Aliquat 336 for extractant and 0.1 M thiourea for stripping solution. The best percentage obtained for extraction was 99.73% and for recovery 90.11%, respectively. The overall separation efficiency noted was 94.92% taking account of both extraction and recovery prospects. The model for this separation developed along a combined flux principle i.e. convection–diffusion–kinetic. The results showed excellent agreement with theoretical data at an average standard deviation of 1.5% and 1.8%, respectively.

Keywords: separation, mercury(ii), petroleum produced water, hollow fiber, liquid membrane

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Authors: Rajkumar Ghosh

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Water scarcity is a significant challenge in urban areas, even in smart cities (Lucknow, Bangalore, Jaipur, etc.) where efficient resource management is prioritized. The depletion of groundwater resources in Gomti Nagar, Lucknow, Uttar Pradesh, India is particularly severe, posing a significant challenge for sustainable development in the region. This study focuses on addressing the water shortage by investigating the effectiveness of rooftop rainwater harvesting systems (RTRWHs) as a sustainable approach to bridge the gap between groundwater recharge and extraction. The aim of this study is to assess the effectiveness of RTRWHs in reducing aquifer depletion and addressing the water scarcity issue in the Gomti Nagar region. The research methodology involves the utilization of RTRWHs as the primary method for collecting rainwater. RTRWHs will be implemented in residential and commercial buildings to maximize the collection of rainwater. Data for this study were collected through various sources such as government reports, surveys, and existing groundwater abstraction patterns. Statistical analysis and modelling techniques were employed to assess the current water situation, groundwater depletion rate, and the potential impact of implementing RTRWHs. The study reveals that the installation of RTRWHs in the Gomti Nagar region has a positive impact on addressing the water scarcity issue. Currently, RTRWHs cover only a small percentage of the total rainfall collected in the region. However, when RTRWHs are installed in all buildings, their influence on increasing water availability and reducing aquifer depletion will be significantly greater. The study also highlights the significant water imbalance in the region, emphasizing the urgent need for sustainable water management practices. This research contributes to the theoretical understanding of sustainable water management systems in smart cities. By highlighting the effectiveness of RTRWHs in reducing aquifer depletion, it emphasizes the importance of implementing such systems in urban areas. Data for this study were collected through various sources such as government reports, surveys, and existing groundwater abstraction patterns. The collected data were then analysed using statistical analysis and modelling techniques to assess the current water situation, groundwater depletion rate, and the potential impact of implementing RTRWHs. The findings of this study demonstrate that the implementation of RTRWHs can effectively mitigate the water scarcity crisis in Gomti Nagar. By reducing aquifer depletion and bridging the gap between groundwater recharge and extraction, RTRWHs offer a sustainable solution to the region's water scarcity challenges. Widespread adoption of RTRWHs in all buildings and integration into urban planning and development processes are crucial for efficient water management in smart cities like Gomti Nagar. These findings can serve as a basis for policymakers, urban planners, and developers to prioritize and incentivize the installation of RTRWHs as a potential solution to the water shortage crisis.

Keywords: water scarcity, urban areas, smart cities, resource management, groundwater depletion, rooftop rainwater harvesting systems, sustainable development, sustainable water management, mitigating water scarcity

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Authors: Zied Guidara, Alexander Morgenstern, Aref Younes Maalej

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In this paper, a desiccant solar unit for air conditioning and desalination is presented first. Secondly, a dynamic modelling study of the desiccant wheel is developed. After that, a simulation study and an experimental investigation of the behaviour of desiccant wheel are developed. The experimental investigation is done in the chamber of commerce in Freiburg-Germany. Indeed, the variations of calculated and measured temperatures and specific humidity of dehumidified and rejected air are presented where a good agreement is found when comparing the model predictions with experimental data under the considered range of operating conditions. Finally, the study of the compartments of desalination and water condensation shows that the unit can produce an acceptable quantity of water at the same time of the air conditioning operation.

Keywords: air conditioning, desalination, condensation, design, desiccant wheel

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Authors: Xiyang Li, Qi Yu, Lun Zhang

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In the face of natural disasters and other emergency situations, determining the optimal location of rescue centers is crucial for improving rescue efficiency and minimizing impact on affected populations. This paper proposes a method that integrates genetic algorithms (GA) and backpropagation neural networks (BPNN) to address the site selection optimization problem for emergency rescue centers. We utilize BPNN to accurately estimate the cost of delivering supplies from rescue centers to each temporary camp. Moreover, a genetic algorithm with a special partially matched crossover (PMX) strategy is employed to ensure that the number of temporary camps assigned to each rescue center adheres to predetermined limits. Using the population distribution data during the 2022 epidemic in Jiading District, Shanghai, as an experimental case, this paper verifies the effectiveness of the proposed method. The experimental results demonstrate that the BPNN-GA method proposed in this study outperforms existing algorithms in terms of computational efficiency and optimization performance. Especially considering the requirements for computational resources and response time in emergency situations, the proposed method shows its ability to achieve rapid convergence and optimal performance in the early and mid-stages. Future research could explore incorporating more real-world conditions and variables into the model to further improve its accuracy and applicability.

Keywords: emergency rescue centers, genetic algorithms, back-propagation neural networks, site selection optimization

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Authors: Komal Saini, S. K. Sahoo, B. S. Bajwa

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The Laser Fluorimetery Technique has been used for the microanalysis of uranium content in water samples collected from different sources like the hand pumps, tube wells in the drinking water samples of SW & NE Punjab, India. The geographic location of the study region in NE Punjab is between latitude 31.21º- 32.05º N and longitude 75.60º-76.14º E and for SW Punjab is between latitude 29.66º-30.48º N and longitude 74.69º-75.54º E. The purpose of this study was mainly to investigate the uranium concentration levels of ground water being used for drinking purposes and to determine its health effects, if any, to the local population of these regions. In the present study 131 samples of drinking water collected from different villages of SW and 95 samples from NE, Punjab state, India have been analyzed for chemical and radiological toxicity. In the present investigation, uranium content in water samples of SW Punjab ranges from 0.13 to 908 μgL−1 with an average of 82.1 μgL−1 whereas in samples collected from NE- Punjab, it ranges from 0 to 28.2 μgL−1 with an average of 4.84 μgL−1. Thus, revealing that in the SW- Punjab 54 % of drinking water samples have uranium concentration higher than international recommended limit of 30 µgl-1 (WHO, 2011) while 35 % of samples exceeds the threshold of 60 µgl-1 recommended by our national regulatory authority of Atomic Energy Regulatory Board (AERB), Department of Atomic Energy, India, 2004. On the other hand in the NE-Punjab region, none of the observed water sample has uranium content above the national/international recommendations. The observed radiological risk in terms of excess cancer risk ranges from 3.64x10-7 to 2.54x10-3 for SW-Punjab, whereas for NE region it ranges from 0 to 7.89x10-5. The chemical toxic effect in terms of Life-time average Daily Dose (LDD) and Hazard Quotient (HQ) have also been calculated. The LDD for SW-Punjab varies from 0.0098 to 68.46 with an average of 6.18 µg/ kg/day whereas for NE region it varies from 0 to 2.13 with average 0.365 µg/ kg/day, thus indicating presence of chemical toxicity in SW Punjab as 35% of the observed samples in the SW Punjab are above the recommendation limit of 4.53 µg/ kg/day given by AERB for 60 µgl-1 of uranium. Maximum & Minimum values for hazard quotient for SW Punjab is 0.002 & 15.11 with average 1.36 which is considerably high as compared to safe limit i.e. 1. But for NE Punjab HQ varies from 0 to 0.47. The possible sources of high uranium observed in the SW- Punjab will also be discussed.

Keywords: uranium, groundwater, radiological and chemical toxicity, Punjab, India

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Authors: Tingyu Zhang

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This paper utilizes the Super-SBM model to assess water resources green efficiency (WRGE) among provinces in China and investigate its spatial and temporal features, based on the characteristic framework of “economy-environment-society.” The social network analysis is employed to examine the network pattern and spatial interaction of WRGE. Further, the quadratic assignment procedure method is utilized for examining the influencing factors of the spatial association of WRGE regarding “relationship.” The study reveals that: (1) the spatial distribution of WRGE demonstrates a distribution pattern of Eastern>Western>Central; (2) a remarkable spatial association exists among provinces; however, no strict hierarchical structure is observed. The internal structure of the WRGE network is characterized by the feature of "Eastern strong and Western weak". The block model analysis discovers that the members of the “net spillover” and “two-way spillover” blocks are mostly in the eastern and central provinces; “broker” block, which plays an intermediary role, is mostly in the central provinces; and members of the “net beneficiary” block are mostly in the western region. (3) Differences in economic development, degree of urbanization, water use environment, and water management have significant impacts on the spatial connection of WRGE. This study is dedicated to the realization of regional linkages and synergistic enhancement of WRGE, which provides a meaningful basis for building a harmonious society of human and water coexistence.

Keywords: water resources green efficiency, super-SBM model, social network analysis, quadratic assignment procedure

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Authors: Laura Bravo-García, Gotzone Barandika, Begoña Bazán, M. Karmele Urtiaga, Luis M. Lezama, María I. Arriortua

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Solid coordination networks (SCNs) are materials consisting of metal ions or clusters that are linked by polyfunctional organic ligands and can be designed to form tridimensional frameworks. Their structural features, as for example high surface areas, thermal stability, and in other cases large cavities, have opened a wide range of applications in fields like drug delivery, host-guest chemistry, biomedical imaging, chemical sensing, heterogeneous catalysis and others referred to greenhouse gases storage or even separation. In this sense, the use of polycarboxylate anions and dipyridyl ligands is an effective strategy to produce extended structures with the needed characteristics for these applications. In this context, a novel compound, [Cu4(m-BDC)4(bpa)2DMF]•DMF has been obtained by microwave synthesis, where m-BDC is 1,3-benzenedicarboxylate and bpa 1,2-bis(4-pyridyl)ethane. The crystal structure can be described as a three dimensional framework formed by two equal, interpenetrated networks. Each network consists of two different CuII dimers. Dimer 1 have two coppers with a square pyramidal coordination, and dimer 2 have one with a square pyramidal coordination and other with octahedral one, the last dimer is unique in literature. Therefore, the combination of both type of dimers is unprecedented. Thus, benzenedicarboxylate ligands form sinusoidal chains between the same type of dimers, and also connect both chains forming these layers in the (100) plane. These layers are connected along the [100] direction through the bpa ligand, giving rise to a 3D network with 10 Å2 voids in average. However, the fact that there are two interpenetrated networks results in a significant reduction of the available volume. Structural analysis was carried out by means of single crystal X-ray diffraction and IR spectroscopy. Thermal and magnetic properties have been measured by means of thermogravimetry (TG), X-ray thermodiffractometry (TDX), and electron paramagnetic resonance (EPR). Additionally, CO2 and CH4 high pressure adsorption measurements have been carried out for this compound.

Keywords: gas adsorption, interpenetrated networks, magnetic measurements, solid coordination network (SCN), thermal stability

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Authors: Yongjiang Zhang, Kallol Barai, Umesh R. Hodeghatta, Trang Tran, Vikas Dhiman

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Detecting water stress on crops early and accurately is crucial to minimize its impact. This study aims to measure water stress in wild blueberry crops non-destructively by analyzing proximal hyperspectral data. The data collection took place in the summer growing season of 2022. A drought experiment was conducted on wild blueberries in the randomized block design in the greenhouse, incorporating various genotypes and irrigation treatments. Hyperspectral data ( spectral range: 400-1000 nm) using a handheld spectroradiometer and leaf water potential data using a pressure chamber were collected from wild blueberry plants. Machine learning techniques, including multiple regression analysis and random forest models, were employed to predict leaf water potential (MPa). We explored the optimal wavelength bands for simple differences (RY1-R Y2), simple ratios (RY1/RY2), and normalized differences (|RY1-R Y2|/ (RY1-R Y2)). NDWI ((R857 - R1241)/(R857 + R1241)), SD (R2188 – R2245), and SR (R1752 / R1756) emerged as top predictors for predicting leaf water potential, significantly contributing to the highest model performance. The base learner models achieved an R-squared value of approximately 0.81, indicating their capacity to explain 81% of the variance. Research is underway to develop a neural vegetation index (NVI) that automates the process of index development by searching for specific wavelengths in the space ratio of linear functions of reflectance. The NVI framework could work across species and predict different physiological parameters.

Keywords: hyperspectral reflectance, water potential, spectral indices, machine learning, wild blueberries, optimal bands

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Authors: Roy B. Clariana, Ryan L. Solnosky

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Structural feedback is any form of feedback that aims to improve the quality of students’ domain-normative conceptual interrelationships. Research with structural feedback points to the potential mediating role of network graphs as feedback for tuning students’ conceptual understanding; for example, improved content knowledge and motivation were observed for undergraduate students who accessed the instructor’s networks of course content. This exploratory study uses a one-group pretest-posttest design to examine the effects of instructor-provided network feedback during lectures on students’ knowledge structure measured using a concept sorting task at the pretest and posttest. Undergraduate students in an architectural engineering course (n = 32) completed a lesson module and then an end-of-unit quiz on building with wood and wood framing. Three weeks later, as a review, students completed a sorting task that used 26 terms from that lesson, then a week later, the sorting task data were used to create a group-average network, this network along with the instructor’s expert network were added to that week’s lecture slides and were compared and discussed during class time. A week later, students completed the sorting task again. The pre and post-sorting data were rendered into pathfinder networks, and then these students’ networks were compared to five referent networks, specifically the textbook chapter network, the lecture slides network, a network of the end-of-unit quiz, the actual expert network that served as the feedback intervention, and the group-average network. Inspection of means shows that knowledge structure measures improved for all five measures from pre-to-post, becoming more like the lesson content and like the expert. Repeated measures analysis with follow-up paired samples t-tests showed pre-to-post significant increases for both the end-of-unit quiz and the expert network referents. The findings show that instructor presentation of structural feedback as networks improved or ‘tuned’ students’ knowledge structure of the lesson content. This approach only takes a few extra minutes of class time and is fairly simple to implement in ordinary classrooms, and so it has wide potential to support classroom instruction and student learning. Further research is needed to determine how critical it is to present both the group-average network along with the expert network for comparison in order to highlight group-level misconceptions, or is presenting only the expert network sufficient? If a group-level network is necessary, then a simple clicker-like classroom tool could be developed to collect sorting task data during lectures that could then immediately provide the group-average network for class discussion and reflection.

Keywords: classroom instruction, engineering education, knowledge structure, pathfinder networks, structural feedback

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