Search results for: water cycle algorithm

Authors: Robyn Augustine, Irena Petrinic, Claus Helix-Nielsen, Marshall S. Sheldon

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This study examined the performance of two commercial forward osmosis (FO) membranes; an aquaporin (AQP) based biomimetic membrane, and cellulose triacetate (CTA) membrane in a fertiliser is drawn forward osmosis (FDFO) system for the reclamation of water from synthetic winery wastewater (SWW) operated over 24 hr. Straight, 1 M KCl and 1 M NH₄NO₃ fertiliser solutions were evaluated as draw solutions in the FDFO system. The performance of the AQP-based biomimetic and CTA FO membranes were evaluated in terms of permeate water flux (Jw), reverse solute flux (Js) and percentage water recovery (Re). The average water flux and reverse solute flux when using 1 M KCl as a draw solution against controlled feed solution, deionised (DI) water, was 11.65 L/m²h and 3.98 g/m²h (AQP) and 6.24 L/m²h and 2.89 g/m²h (CTA), respectively. Using 1 M NH₄NO₃ as a draw solution yielded average water fluxes and reverse solute fluxes of 10.73 L/m²h and 1.31 g/m²h (AQP) and 5.84 L/m²h and 1.39 g/m²h (CTA), respectively. When using SWW as the feed solution and 1 M KCl and 1 M NH₄NO₃ as draw solutions, respectively, the average water fluxes observed were 8.15 and 9.66 L/m²h (AQP) and 5.02 and 5.65 L/m²h (CTA). Membrane water flux decline was the result of a combined decrease in the effective driving force of the FDFO system, reverse solute flux and organic fouling. Permeate water flux recoveries of between 84-98%, and 83-89% were observed for the AQP-based biomimetic and CTA membrane, respectively after physical cleaning by flushing was employed. The highest water recovery rate of 49% was observed for the 1 M KCl fertiliser draw solution with AQP-based biomimetic membrane and proved superior in the reclamation of water from SWW.

Keywords: aquaporin biomimetic membrane, cellulose triacetate membrane, forward osmosis, reverse solute flux, synthetic winery wastewater and water flux

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Authors: Derjew Ayele Ejigu, Houde Song, Xiaojing Liu

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This work presents the particle swarm optimization trained neural network (PSO-NN) supervisory proportional integral derivative (PID) control method to monitor the pressurized water reactor (PWR) core power for safe operation. The proposed control approach is implemented on the transfer function of the PWR core, which is computed from the state-space model. The PWR core state-space model is designed from the neutronics, thermal-hydraulics, and reactivity models using perturbation around the equilibrium value. The proposed control approach computes the control rod speed to maneuver the core power to track the reference in a closed-loop scheme. The particle swarm optimization (PSO) algorithm is used to train the neural network (NN) and to tune the PID simultaneously. The controller performance is examined using integral absolute error, integral time absolute error, integral square error, and integral time square error functions, and the stability of the system is analyzed by using the Bode diagram. The simulation results indicated that the controller shows satisfactory performance to control and track the load power effectively and smoothly as compared to the PSO-PID control technique. This study will give benefit to design a supervisory controller for nuclear engineering research fields for control application.

Keywords: machine learning, neural network, pressurized water reactor, supervisory controller

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Authors: Niharika Verma, Sandeep Santosh

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DOA technique is a localization technique used in the communication field. Various algorithms have been developed for direction of arrival estimation like MUSIC, ROOT MUSIC, etc. These algorithms depend on various parameters like antenna array elements, number of snapshots and various others. Basically the MUSIC spectrum is evaluated and peaks obtained are considered as the angle of arrivals. The angles evaluated using this process depends on the scanning interval chosen. The accuracy of the results obtained depends on the coarseness of the interval chosen. In this paper, golden section search is applied to the MUSIC algorithm and therefore, more accurate results are achieved. Initially the coarse DOA estimations is done using the MUSIC algorithm in the range -90 to 90 degree at the interval of 10 degree. After the peaks obtained then fine DOA estimation is done using golden section search. Also, the partitioning method is applied to estimate the number of signals incident on the antenna array. Dependency of the algorithm on the number of snapshots is also being explained. Hence, the accurate results are being determined using this algorithm.

Keywords: Direction of Arrival (DOA), golden section search, MUSIC, number of snapshots

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Authors: Ingrid Argote, John Archila, Marcelo Becker

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In agriculture, intelligent systems applications have generated great advances in automating some of the processes in the production chain. In order to improve the efficiency of those systems is proposed a vision system to estimate the amount of fruits in sweet orange trees. This work presents a system proposal using capture of thermal images and fuzzy logic. A bibliographical review has been done to analyze the state-of-the-art of the different systems used in fruit recognition, and also the different applications of thermography in agricultural systems. The algorithm developed for this project uses the metrics of the fuzzines parameter to the contrast improvement and segmentation of the image, for the counting algorith m was used the Hough transform. In order to validate the proposed algorithm was created a bank of images of sweet orange Citrus (L.) Osbeck acquired in the Maringá Farm. The tests with the algorithm Indicated that the variation of the tree branch temperature and the fruit is not very high, Which makes the process of image segmentation using this differentiates, This Increases the amount of false positives in the fruit counting algorithm. Recognition of fruits isolated with the proposed algorithm present an overall accuracy of 90.5 % and grouped fruits. The accuracy was 81.3 %. The experiments show the need for a more suitable hardware to have a better recognition of small temperature changes in the image.

Keywords: Agricultural systems, Citrus, Fuzzy logic, Thermal images.

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Authors: Sanjay Kumar Parjapati, Ajai Jain

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This paper presents optimization of makespan for ‘n’ jobs and ‘m’ machines flexible job shop scheduling problem with sequence dependent setup time using genetic algorithm (GA) approach. A restart scheme has also been applied to prevent the premature convergence. Two case studies are taken into consideration. Results are obtained by considering crossover probability (pc = 0.85) and mutation probability (pm = 0.15). Five simulation runs for each case study are taken and minimum value among them is taken as optimal makespan. Results indicate that optimal makespan can be achieved with more than one sequence of jobs in a production order.

Keywords: flexible job shop, genetic algorithm, makespan, sequence dependent setup times

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Authors: Gabrielle O'Donoghue

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Background: Pre-operative radiographs facilitate assessment and treatment planning in minor oral surgery. Quality assurance for dental radiography advocates the As Low As Reasonably Achievable (ALARA) principle in collecting accurate diagnostic information. Aims: To audit the quality of digital intraoral periapicals (IOPAs) taken prior to dental extractions in a metropolitan general dental practice setting. Standards: The National Radiological Protection Board (NRPB) guidance outlines three grades of radiograph quality: excellent (Grade 1 > 70% of total exposures), diagnostically acceptable (Grade 2 <20%), and unacceptable (Grade 3 <10%). Methodology: A study of pre-operative radiographs taken prior to dental extractions across 12 private general dental practices in a large metropolitan area by 44 practitioners. A total of 725 extractions were assessed, allowing 258 IOPAs to be reviewed in one audit cycle. Results: First cycle: Of 258 IOPAs: 223(86.4%) scored Grade 1, 27(10.5%) Grade 2, and 8(3.1%) Grade 3. The standard was met. 35 dental extractions were performed without an available pre-operative radiograph. Action Plan & Recommendations: Results were distributed to all staff and a continuous professional development evening organized to outline recommendations to improve image quality. A second audit cycle is proposed at a six-month interval to review the recommendations and appraise results. Conclusion: The overall standard of radiographs met the published guidelines. A significant improvement in the number of procedures undertaken without pre-operative imaging is expected at a six-month interval period. An investigation into undiagnostic imaging and associated adverse patient outcomes is being considered. Maintenance of the standards achieved is predicted in the second audit cycle to ensure consistent high quality imaging.

Keywords: audit, oral radiology, oral surgery, periapical radiographs, quality assurance

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Authors: T. Boonraksa, B. Marungsri

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This paper presents the experimental results on role of ionic solutions affect water treeing propagation in cross-linked polyethylene insulation for high voltage cable. To study the water treeing expansion due to the ionic solutions, discs of 4mm thickness and 4cm diameter were taken from 115 kV XLPE insulation cable and were used as test specimen in this study. Ionic solutions composed of CuSO4, FeSO4, Na2SO4 and K2SO4 were used. Each specimen was immersed in 0.1 mole ionic solutions and was tested for 120 hrs. under a voltage stress at 7 kV AC rms, 1000 Hz. The results show that Na2SO4 and CuSO4solutions play an important role in the expansion of water treeing and cause degradation of the cross-linked polyethylene (XLPE) in the presence of the applied electric field.

Keywords: ionic solutions, water treeing, water treeing expansion, cross-linked polyethylene (XLPE)

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Authors: Vani Singhal, Jitendra Parmar, Satyendra Singh Chouhan

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Unseen class discovery has now become an important part of a machine-learning algorithm to judge new classes. Unseen classes are the classes on which the machine learning model is not trained on. With the advancement in technology and AI replacing humans, the amount of data has increased to the next level. So while implementing a model on real-world examples, we come across unseen new classes. Our aim is to find the number of unseen classes by using a hierarchical-based active learning algorithm. The algorithm is based on hierarchical clustering as well as active sampling. The number of clusters that we will get in the end will give the number of unseen classes. The total clusters will also contain some clusters that have unseen classes. Instead of first discovering unseen classes and then finding their number, we directly calculated the number by applying the algorithm. The dataset used is for intent classification. The target data is the intent of the corresponding query. We conclude that when the machine learning model will encounter real-world data, it will automatically find the number of unseen classes. In the future, our next work would be to label these unseen classes correctly.

Keywords: active sampling, hierarchical clustering, open world learning, unseen class discovery

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Authors: Nana Bolashvili, Vakhtang Geladze, Tamazi Karalashvili, Nino Machavariani, George Geladze, Davit Kartvelishvili, Ana Karalashvili

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Fresh water is the major natural resource of Georgia. The average perennial sum of the rivers' runoff in Georgia is 52,77 km³, out of which 9,30 km³ inflows from abroad. The major volume of transit river runoff is ascribed to the Chorokhi river. Average perennial runoff in Western Georgia is 41,52 km³, in Eastern Georgia 11,25 km³. The indices of Eastern and Western Georgia were calculated with 50% and 90% river runoff respectively, while the same index calculation for other countries is based on a 50% river runoff. Out of total volume of resources, 133,2 m³/sec (4,21 km³) has been geologically prospected by the State Commission on Reserves and Acknowledged as reserves available for exploitation, 48% (2,02 km³) of which is in Western Georgia and 2,19 km³ in Eastern Georgia. Considering acknowledged water reserves of all categories per capita water resources accounts to 2,2 m³/day, whereas high industrial category -0. 88 m³ /day fresh drinking water. According to accepted norms, the possibility of using underground water reserves is 2,5 times higher than the long-term requirements of the country. The volume of abundant fresh-water reserves in Georgia is about 150 m³/sec (4,74 km³). Water in Georgia is consumed mostly in agriculture for irrigation purposes. It makes 66,4% around Georgia, in Eastern Georgia 72,4% and 38% in Western Georgia. According to the long-term forecast provision of population and the territory with water resources in Eastern Georgia will be quite normal. A bit different is the situation in the lower reaches of the Khrami and Iori rivers which could be easily overcome by corresponding financing. The present day irrigation system in Georgia does not meet the modern technical requirements. The overall efficiency of their majority varies between 0,4-0,6. Similar is the situation in the fresh water and public service water consumption. Organization of the mentioned systems, installation of water meters, introduction of new methods of irrigation without water loss will substantially increase efficiency of water use. Besides new irrigation norms developed from agro-climatic, geographical and hydrological angle will significantly reduce water waste. Taking all this into account we assume that for irrigation agricultural lands in Georgia is necessary 6,0 km³ water, 5,5 km³ of which goes to Eastern Georgia on irrigation arable areas. To increase water supply in Eastern Georgian territory and its population is possible by means of new water reservoirs as the runoff of every river considerably exceeds the consumption volume. In conclusion, we should say that fresh water resources by which Georgia is that rich could be significant source for barter exchange and investment attraction. Certain volume of fresh water can be exported from Western Georgia quite trouble free, without bringing any damage to population and hydroecosystems. The precise volume of exported water per region/time and method/place of water consumption should be defined after the estimation of different hydroecosystems and detailed analyses of water balance of the corresponding territories.

Keywords: GIS, management, rivers, water resources

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Authors: Haozhe Xiang

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With the rise of the Internet of Things era, intelligent products are gradually integrating into people's lives. Pedestrian trajectory prediction has become a key issue, which is crucial for the motion path planning of intelligent agents such as autonomous vehicles, robots, and drones. In the current technological context, deep learning technology is becoming increasingly sophisticated and gradually replacing traditional models. The pedestrian trajectory prediction algorithm combining neural networks and attention mechanisms has significantly improved prediction accuracy. Based on in-depth research on deep learning and pedestrian trajectory prediction algorithms, this article focuses on physical environment modeling and learning of historical trajectory time dependence. At the same time, social interaction between pedestrians and scene interaction between pedestrians and the environment were handled. An improved pedestrian trajectory prediction algorithm is proposed by analyzing the existing model architecture. With the help of these improvements, acceptable predicted trajectories were successfully obtained. Experiments on public datasets have demonstrated the algorithm's effectiveness and achieved acceptable results.

Keywords: deep learning, graph convolutional network, attention mechanism, LSTM

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Authors: Young-Taeg Kim, Gwang Ho Seo, Hyungju Oh, Ho Kyung Ha, Kuk Jin Kim

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Kim et al., hypothesized an increase in volume transport in the Korea Strait based on the concurrent increase in water temperature and mean sea level observed by the Korea Hydrographic and Oceanographic Agency (KHOA) in the vicinity of the Korea Strait from 2000 to 2009. Since then, to our best knowledge, no definitive studies have been reported on the increase in volume transport through the Korea Strait, but the observed water temperature (2000-2021) and sea level (1989-2021) in the Korea Strait and East Sea have been found to be increasing. In particular, the rapid increase rate in the mean sea level rise (2.55~3.53 mm/y) in these areas cannot be explained by only steric effect due to the increased water temperature. It is more reasonable interpretation that the sea level rise is due to an increase in the volume transport of warm and salty currents. If the increase in the volume transport is explained by the geostrophic equation without considering the sea level rise in the Korea Strait, the current velocity should increase. However, up to now, there are no reports of an increase in current velocity from direct observations using ADCP (e.g., observations of Camellia) or from various numerical models. Therefore, the increase in volume transport cannot be explained by the geostrophic equation. Another possible explanation for the increase in the volume transport is the effect of wind. Although Korea is dominated by monsoon, it is affected by winds according to El Niño and La Niña, which have a cycle of about 3 to 4 years. During El Niño (La Niña), northerly winds (southerly winds) prevail in Korea. Consequently, it is inferred that the transported volume in the Korea Strait slowly increases interannually. However, in this study, it was difficult to find a clear correlation between annually-averaged mean sea level and El Niño (or La Niña) during 1989-2021. This is probably due to the interactions of the PDO (Pacific Decadal Oscillation) and AO (Arctic Oscillation) along with the ENSO (El niño-Southern Oscillation). However, it is clear that the interannual variability of winds is affecting the volume transport in the Korean Strait. On the other hand, the effect of global sea level rise on the volume transport in the Korea Strait is small compared to the interannual variability of the volume transport, but it seems to play a constant role.

Keywords: mean sea level, volume transport, El nino, La nina

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Authors: Rahaba Marima, Clement Penny

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The Health-related quality of life (HRQoL) for HIV positive patients has improved since the introduction of the highly active antiretroviral treatment (HAART). However, in the present HAART era, HIV co-morbidities such as lung cancer, a non-AIDS (NAIDS) defining cancer have been documented to be on the rise. Under normal physiological conditions, cells grow, repair and proliferate through the cell-cycle as cellular homeostasis is important in the maintenance and proper regulation of tissues and organs. Contrarily, the deregulation of the cell-cycle is a hallmark of cancer, including lung cancer. The association between lung cancer and the use of HAART components such as Efavirenz (EFV) is poorly understood. This study aimed at elucidating the effects of EFV on the cell-cycle genes’ expression in lung cancer. For this purpose, the human cell-cycle gene array composed of 84 genes was evaluated on both normal lung fibroblasts (MRC-5) cells and adenocarcinoma (A549) lung cells, in response to 13µM EFV or 0.01% vehicle. The ±2 up or down fold change was used as a basis of target selection, with p < 0.05. Additionally, RT-qPCR was done to validate the gene array results. Next, In-silico bio-informatics tools, Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), Reactome, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Ingenuity Pathway Analysis (IPA) were used for gene/gene interaction studies as well as to map the molecular and biological pathways influenced by the identified targets. Interestingly, the DNA damage response (DDR) pathway genes such as p53, Ataxia telangiectasia mutated and Rad3 related (ATR), Growth arrest and DNA damage inducible alpha (GADD45A), HUS1 checkpoint homolog (HUS1) and Role of radiation (RAD) genes were shown to be upregulated following EFV treatment, as revealed by STRING analysis. Additionally, functional enrichment analysis by the KEGG pathway revealed that most of the differentially expressed gene targets function at the cell-cycle checkpoint such as p21, Aurora kinase B (AURKB) and Mitotic Arrest Deficient-Like 2 (MAD2L2). Core analysis by IPA revealed that p53 downstream targets such as survivin, Bcl2, and cyclin/cyclin dependent kinases (CDKs) complexes are down-regulated, following exposure to EFV. Furthermore, Reactome analysis showed a significant increase in cellular response to stress genes, DNA repair genes, and apoptosis genes, as observed in both normal and cancerous cells. These findings implicate the genotoxic effects of EFV on lung cells, provoking the DDR pathway. Notably, the constitutive expression of this pathway (DDR) often leads to uncontrolled cell proliferation and eventually tumourigenesis, which could be the attribute of HAART components’ (such as EFV) effect on human cancers. Targeting the cell-cycle and its regulation holds a promising therapeutic intervention to the potential HAART associated carcinogenesis, particularly lung cancer.

Keywords: cell-cycle, DNA damage response, Efavirenz, lung cancer

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Authors: M. Derraz, M. Farhaoui

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Problem statement: In the water treatment processes, the coagulation and flocculation processes produce sludge according to the level of the water turbidity. The aluminum sulfate is the most common coagulant used in water treatment plants of Morocco as well as many countries. It is difficult to manage Sludge produced by the treatment plant. However, it can be used in the process to improve the quality of the treated water and reduce the aluminum sulfate dose. Approach: In this study, the effectiveness of sludge was evaluated at different turbidity levels (low, medium, and high turbidity) and coagulant dosage to find optimal operational conditions. The influence of settling time was also studied. A set of jar test experiments was conducted to find the sludge and aluminum sulfate dosages in order to improve the produced water quality for different turbidity levels. Results: Results demonstrated that using sludge produced by the treatment plant can improve the quality of the produced water and reduce the aluminum sulfate using. The aluminum sulfate dosage can be reduced from 40 to 50% according to the turbidity level (10, 20, and 40 NTU). Conclusions/Recommendations: Results show that sludge can be used in order to reduce the aluminum sulfate dosage and improve the quality of treated water. The highest turbidity removal efficiency is observed within 6 mg/l of aluminum sulfate and 35 mg/l of sludge in low turbidity, 20 mg/l of aluminum sulfate and 50 mg/l of sludge in medium turbidity and 20 mg/l of aluminum sulfate and 60 mg/l of sludge in high turbidity. The turbidity removal efficiency is 97.56%, 98.96%, and 99.47% respectively for low, medium and high turbidity levels.

Keywords: coagulation process, coagulant dose, sludge reuse, turbidity removal

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Authors: Daniel Murrant, Andrew Quinn, Lee Chapman

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A growing population has led to increasing global water and energy demand. This demand, combined with the effects of climate change and an increasing need to maintain and protect the natural environment, represents a potentially severe threat to many national infrastructure systems. This has resulted in a considerable quantity of published material on the interdependencies that exist between the supply of water and the thermal generation of electricity, often known as the water-energy nexus. Focusing specifically on the UK, there is a growing concern that the future availability of water may at times constrain thermal electricity generation, and therefore hinder the UK in meeting its increasing demand for a secure, and affordable supply of low carbon electricity. To provide further information on the threat the water-energy nexus may pose to the UK’s energy system, this paper models the regional water demand of UK thermal electricity generation in 2030 and 2050. It uses the strategically important Energy Systems Modelling Environment model developed by the Energy Technologies Institute. Unlike previous research, this paper was able to use abstraction and consumption factors specific to UK power stations. It finds that by 2050 the South East, Yorkshire and Humber, the West Midlands and North West regions are those with the greatest freshwater demand and therefore most likely to suffer from a lack of resource. However, it finds that by 2050 it is the East, South West and East Midlands regions with the greatest total water (fresh, estuarine and seawater) demand and the most likely to be constrained by environmental standards.

Keywords: climate change, power station cooling, UK water-energy nexus, water abstraction, water resources

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Authors: Jaimin Patel

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Cloud computing is one of the most sharp and important movement in various computing technologies. It provides flexibility to users, cost effectiveness, location independence, easy maintenance, enables multitenancy, drastic performance improvements, and increased productivity. On the other hand, there are also major issues like security. Being a common server, security for a cloud is a major issue; it is important to provide security to protect user’s private data, and it is especially important in e-commerce and social networks. In this paper, encryption algorithms such as Advanced Encryption Standard algorithms, their vulnerabilities, risk of attacks, optimal time and complexity management and comparison with other algorithms based on software implementation is proposed. Encryption techniques to improve the performance of AES algorithms and to reduce risk management are given. Secure Hash Algorithms, their vulnerabilities, software implementations, risk of attacks and comparison with other hashing algorithms as well as the advantages and disadvantages between hashing techniques and encryption are given.

Keywords: Cloud computing, encryption algorithm, secure hashing algorithm, brute force attack, birthday attack, plaintext attack, man in middle attack

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Authors: Chengalappa Seenappa, Narayanappa Devkumar, Narayanappa Nagaraja

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Mulberry leaf is the major economic component in sericulture and quality of leaf produced per unit area has a direct effect on quality of cocoon. Among all the agronomical inputs, irrigation water has highest impact on mulberry leaf quantity and quality. The water productivity in sericulture in the country is inadequate and inefficient though India has the largest irrigated area. There is a need of proper irrigation methods and conservation practices to ensure efficiency and economy in water use. Hence, this field experiment was conducted at College of Sericulture, Chintamani, Chickaballapur district, Karnataka, India during 2013 and 2014 to know the quantity, quality and water productivity of mulberry influenced by different methods, levels of irrigation and mulching in Eastern Dry Zone (EDZ) of Karnataka, India. The results revealed that the mulberry leaf quantity, quality and water productivity were significantly influenced by different methods, levels of irrigation and mulching. Subsurface drip irrigation at 0.8 CPE (Cumulative Pan Evaporation) recorded higher leaf yield, chlorophyll, relative water, protein content and water productivity (42857 kg ha-1 yr-1, 8.54, 65.80%, 22.27% and 364.41 kg hacm-1, respectively) than surface drip at 1.0 CPE (38809 kg ha-1 yr-1, 7.34, 62.76%, 17.75% and 264 10 kg hacm-1, respectively) and micro spray jet at 1.0 CPE (39931 kg ha-1 yr-1, 7.96, 63.50%, 19.00%, 35617 kg ha-1 yr-1 and 271.83 kg hacm-1, respectively). Mulching treatment recorded maximum leaf yield, chlorophyll, relative water, protein content and water productivity (38035 kg ha-1 yr-1, 7.12, 62.11%, 16.14% and 330 kg hacm-1, respectively) compared to without mulching. These results clearly indicated that subsurface drip irrigation at lower level of irrigation (0.8 CPE) and mulching increased the quantity, quality and water productivity of mulberry leaf than surface drip and micro spray jet irrigation at higher level of irrigation (1.0 CPE) by saving 20 per cent of water. Therefore, in the coming days subsurface drip irrigation in mulberry cultivation may be more appropriate to realise higher yield, quality and water productivity in EDZ of Karnataka, India.

Keywords: subsurface drip irrigation, mulching, water productivity, mulberry

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Authors: Ahmed Z. Gabr, Ahmed A. Helal, Hussein E. Said

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With the incessant increase of power systems capacity and voltage grade, the safety of grounding grid becomes more and more prominent. In this paper, the designing substation grounding grid is presented by means of genetic algorithm (GA). This approach purposes to control the grounding cost of the power system with the aid of controlling grounding rod number and conductor lengths under the same safety limitations. The proposed technique is used for the design of the substation grounding grid in Khalda Petroleum Company “El-Qasr” power plant and the design was simulated by using CYMGRD software for results verification. The result of the design is highly complying with IEEE 80-2000 standard requirements.

Keywords: genetic algorithm, optimum grounding grid design, power system analysis, power system protection, single layer model, substation

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Authors: Abdullah A. AlShaher

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In this paper, we demonstrate how regression curves can be used to recognize 2D non-rigid handwritten shapes. Each shape is represented by a set of non-overlapping uniformly distributed landmarks. The underlying models utilize 2^nd order of polynomials to model shapes within a training set. To estimate the regression models, we need to extract the required coefficients which describe the variations for a set of shape class. Hence, a least square method is used to estimate such modes. We then proceed by training these coefficients using the apparatus Expectation Maximization algorithm. Recognition is carried out by finding the least error landmarks displacement with respect to the model curves. Handwritten isolated Arabic characters are used to evaluate our approach.

Keywords: character recognition, regression curves, handwritten Arabic letters, expectation maximization algorithm

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Authors: Jiameng Wang, Yunfei Yin, Xiyu Deng

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Parallel optimization is one of the important research topics of data mining at this stage. Taking Classification and Regression Tree (CART) parallelization as an example, this paper proposes a parallel data mining algorithm based on SSP-OGini-PCCP. Aiming at the problem of choosing the best CART segmentation point, this paper designs an S-SP model without data association; and in order to calculate the Gini index efficiently, a parallel OGini calculation method is designed. In addition, in order to improve the efficiency of the pruning algorithm, a synchronous PCCP pruning strategy is proposed in this paper. In this paper, the optimal segmentation calculation, Gini index calculation, and pruning algorithm are studied in depth. These are important components of parallel data mining. By constructing a distributed cluster simulation system based on SPARK, data mining methods based on SSP-OGini-PCCP are tested. Experimental results show that this method can increase the search efficiency of the best segmentation point by an average of 89%, increase the search efficiency of the Gini segmentation index by 3853%, and increase the pruning efficiency by 146% on average; and as the size of the data set increases, the performance of the algorithm remains stable, which meets the requirements of contemporary massive data processing.

Keywords: classification, Gini index, parallel data mining, pruning ahead

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Authors: Sofia Ayouche, Rachid Ellaia, Rajae Aboulaich

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Today, insurers may use the yield curve as an indicator evaluation of the profit or the performance of their portfolios; therefore, they modeled it by one class of model that has the ability to fit and forecast the future term structure of interest rates. This class of model is the Nelson-Siegel-Svensson model. Unfortunately, many authors have reported a lot of difficulties when they want to calibrate the model because the optimization problem is not convex and has multiple local optima. In this context, we implement a hybrid Particle Swarm optimization and Nelder Mead algorithm in order to minimize by least squares method, the difference between the zero-coupon curve and the NSS curve.

Keywords: optimization, zero-coupon curve, Nelson-Siegel-Svensson, particle swarm optimization, Nelder-Mead algorithm

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Authors: Libena Cernohorska, Jan Cernohorsky

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This article aims to evaluate the impact of loans provided within the Czech banking sector on the growth of the Czech economy. The article is based on research of current scientific findings in respect to bank loans and economic development. The paper is based on data taken from the Czech Statistical Office on the development of the gross domestic product and data from the Czech National Bank on the development of loans from the period 2004-2015. Links between selected variables are tested using Granger causality tests. The results calculated confirm the hypothesis of the impact of the loans on economic growth, with a six-month delay. The results thus correspond to the standard economic findings and results of most previous studies.

Keywords: bank, business cycle, economic growth, loans

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Authors: B. Lee, B. H. Choi

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The loss of safety for reservoirs brought about by climate change and facility aging leads to reservoir failures, which results in the loss of lives and property damage in downstream areas. Therefore, it is necessary to provide a reservoir failure alert system for downstream residents to detect the early signs of failure (with sensors) in real-time and perform safety management to prevent and minimize possible damage. 10 case studies were carried out to verify the water level management criteria of four levels (attention, caution, alert, serious). Peak changes in water level data were analysed. The results showed that ‘Caution’ and ‘Alert’ were closed to 33% and 66% of difference in level between flood water level and full water level. Therefore, it is adequate to use initial water level management criteria of reservoir failure alert system for the first year. Acknowledgment: This research was supported by a grant (2017-MPSS31-002) from 'Supporting Technology Development Program for Disaster Management' funded by the Ministry of the Interior and Safety(MOIS)

Keywords: alert system, management criteria, reservoir failure, sensor

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Authors: Yili Chen, Xiaokun Liang, Zhicheng Zhang, Yaoqin Xie

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In an effort to restore visual perception in retinal diseases, an electronic retinal prosthesis with thousands of electrodes has been developed. The image processing strategies of retinal prosthesis system converts the original images from the camera to the stimulus pattern which can be interpreted by the brain. Practically, the original images are with more high resolution (256x256) than that of the stimulus pattern (such as 25x25), which causes a technical image processing challenge to do large-capacity image information reduction. In this paper, we focus on developing an efficient image processing stimulus pattern extraction algorithm by using a single cue saliency map for extracting salient objects in the image with an optimal trimming threshold. Experimental results showed that the proposed stimulus pattern extraction algorithm performs quite well for different scenes in terms of the stimulus pattern. In the algorithm performance experiment, our proposed SCSPE algorithm have almost five times of the score compared with Boyle’s algorithm. Through experiment s we suggested that when there are salient objects in the scene (such as the blind meet people or talking with people), the trimming threshold should be set around 0.4max, in other situations, the trimming threshold values can be set between 0.2max-0.4max to give the satisfied stimulus pattern.

Keywords: retinal prosthesis, image processing, region of interest, saliency map, trimming threshold selection

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Authors: Nima Samie, Batoul Sadat Haerian, Sekaran Muniandy, M. S. Kanthimathi

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Colon and breast cancers are categorized as the most prevalent types of cancer worldwide. Recently, the broad clinical application of metal complex compounds has led to the discovery of potential therapeutic drugs. The aim of this study was to evaluate the cytotoxic action of a selected nickel complex compound (NCC) against human colon and breast cancer cells. In this context, we determined the potency of the compound in the induction of apoptosis, cell cycle arrest, and cytoskeleton rearrangement. HT-29, WiDr, CCD-18Co, MCF-7 and Hs 190.T cell lines were used to determine the IC50 of the compound using the MTT assay. Analysis of apoptosis was carried out using immunofluorescence, acridine orange/ propidium iodide double staining, Annexin-V-FITC assay, evaluation of the translocation of NF-kB, oxygen radical antioxidant capacity, quenching of reactive oxygen species content , measurement of LDH release, caspase-3/-7, -8 and -9 assays and western blotting. The cell cycle arrest was examined using flowcytometry and gene expression was assessed using qPCR array. Results showed that our nickel complex compound displayed a potent suppressive effect on HT-29, WiDr, MCF-7 and Hs 190.T after 24 h of treatment with IC50 value of 2.02±0.54, 2.13±0.65, 3.76±015 and 3.14±0.45 µM respectively. This cytotoxic effect on normal cells was insignificant. Dipping in the mitochondrial membrane potential and increased release of cytochrome c from the mitochondria indicated induction of the intrinsic apoptosis pathway by the nickel complex compound. Activation of this pathway was further evidenced by significant activation of caspase 9 and 3/7.The nickel complex compound (NCC) was also shown activate the extrinsic pathways of apoptosis by activation of caspase-8 which is linked to the suppression of NF-kB translocation to the nucleus. Cell cycle arrest in the G1 phase and up-regulation of glutathione reductase, based on excessive ROS production were also observed. The results of this study suggest that the nickel complex compound is a potent anti-cancer agent inducing both intrinsic and extrinsic pathways as well as cell cycle arrest in colon and breast cancer cells.

Keywords: nickel complex, apoptosis, cytoskeletal rearrangement, colon cancer, breast cancer

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Authors: Martin Mundo-Molina

Abstract:

In Mexico, there are many small rural communities with serious water supply deficiencies. In Chiapas, Mexico, there are 19,972 poor rural communities, 15,712 of which have fewer than 100 inhabitants. The lack of a constant water supply is most severe in the highlands of Chiapas where the population is made up mainly of indigenous groups. The communities are on mountainous terrain with a widely dispersed population. These characteristics combine to make the provision of public utilities, such as water, electricity and sewerage, difficult with conventional means. The introduction of alternative, low-cost technologies represents means of supplying water such as through fog and rain catchment with zero greenhouse emissions. In this paper is presented the rainwater harvesting system (RWS) constructed in Yalentay, Chiapas Mexico. The RWS is able to store 1.2 M liters of water to provide drinking water to small rural indigenous communities of 500 people in the drought stage. Inside the system of rainwater harvesting there isn't photosynthesis in order to conserve water for long periods. The natural filters of the system of rainwater harvesting guarantee the drinking water for using to the community. The combination of potability and low cost makes rain collection a viable alternative for rural areas, weather permitting. The Mexican Institute of Water Technology and Chiapas University constructed a rainwater harvesting system in Yalentay Chiapas, it consists of four parts: 1. Roof of aluminum, for collecting rainwater, 2. Underground-cistern, divided in two tanks, 3. Filters, to improve the water quality and 4. The system of rainwater harvesting dignified the lives of people in Yalentay, saves energy, prevents the emission of greenhouse gases into the atmosphere, conserves natural resources such as water and air.

Keywords: appropriate technologies, climate change, greenhouse gases, rainwater harvesting

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Authors: R. Berrached, H. Ait Mahamed, A. Iddou

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Water pollution is nowadays a serious problem, due to the increasing scarcity of water and thus to the impact induced by such pollution on the human health. Various techniques are made use of to deal with water pollution. Among the most used ones, some can be enumerated: the bacterian bed, the activated mud, the Lagunage as biological processes and coagulation-floculation as a physic-chemical process. These processes are very expensive and an treatment efficiency which decreases along with the increase of the initial pollutants’ concentration. This is the reason why research has been reoriented towards the use of a process by adsorption as an alternative solution instead of the other traditional processes. In our study, we have tempted to exploit the characteristics of two metallic hydroxides Al and Fe to purify contaminated water by two industrial dyes SBL blue and SRL-150 orange. Results have shown the efficiency of the two materials on the blue SBL dye.

Keywords: metallic hydroxydes, industrial dyes, purificatıon,

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Authors: Shyh Ming Chern

Abstract:

Cubic equations of state (EoS), popular due to their simple mathematical form, ease of use, semi-theoretical nature and, reasonable accuracy are normally fitted to vapor-liquid equilibrium P-v-T data. As a result, They often show poor accuracy in the region near and above the critical point. In this study, the performance of the renowned Peng-Robinson (PR) and Patel-Teja (PT) EoS’s around the critical area has been examined against the P-v-T data of water. Both of them display large deviations at critical point. For instance, PR-EoS exhibits discrepancies as high as 47% for the specific volume, 28% for the enthalpy departure and 43% for the entropy departure at critical point. It is shown that incorporating P-v-T data of the supercritical region into the retuning of a cubic EoS can improve its performance above the critical point dramatically. Adopting a retuned acentric factor of 0.5491 instead of its genuine value of 0.344 for water in PR-EoS and a new F of 0.8854 instead of its original value of 0.6898 for water in PT-EoS reduces the discrepancies to about one third or less.

Keywords: equation of state, EoS, supercritical water, SCW

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Authors: S. Neelima, P. S. Subramanyam

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A distribution system is an interface between the bulk power system and the consumers. Among these systems, radial distributions system is popular because of low cost and simple design. In distribution systems, the voltages at buses reduces when moved away from the substation, also the losses are high. The reason for a decrease in voltage and high losses is the insufficient amount of reactive power, which can be provided by the shunt capacitors. But the placement of the capacitor with an appropriate size is always a challenge. Thus, the optimal capacitor placement problem is to determine the location and size of capacitors to be placed in distribution networks in an efficient way to reduce the power losses and improve the voltage profile of the system. For this purpose, in this paper, two stage methodologies are used. In the first stage, the load flow of pre-compensated distribution system is carried out using ‘dimension reducing distribution load flow algorithm (DRDLFA)’. On the basis of this load flow the potential locations of compensation are computed. In the second stage, Genetic Algorithm (GA) technique is used to determine the optimal location and size of the capacitors such that the cost of the energy loss and capacitor cost to be a minimum. The above method is tested on IEEE 9 and 34 bus system and compared with other methods in the literature.

Keywords: dimension reducing distribution load flow algorithm, DRDLFA, genetic algorithm, electrical distribution network, optimal capacitors placement, voltage profile improvement, loss reduction

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Authors: Bliss Singhal

Abstract:

Machine learning (ML) is a branch of Artificial Intelligence (AI) where computers analyze data and find patterns in the data. The study focuses on the detection of metastatic cancer using ML. Metastatic cancer is the stage where cancer has spread to other parts of the body and is the cause of approximately 90% of cancer-related deaths. Normally, pathologists spend hours each day to manually classifying whether tumors are benign or malignant. This tedious task contributes to mislabeling metastasis being over 60% of the time and emphasizes the importance of being aware of human error and other inefficiencies. ML is a good candidate to improve the correct identification of metastatic cancer, saving thousands of lives and can also improve the speed and efficiency of the process, thereby taking fewer resources and time. So far, the deep learning methodology of AI has been used in research to detect cancer. This study is a novel approach to determining the potential of using preprocessing algorithms combined with classification algorithms in detecting metastatic cancer. The study used two preprocessing algorithms: principal component analysis (PCA) and the genetic algorithm, to reduce the dimensionality of the dataset and then used three classification algorithms: logistic regression, decision tree classifier, and k-nearest neighbors to detect metastatic cancer in the pathology scans. The highest accuracy of 71.14% was produced by the ML pipeline comprising of PCA, the genetic algorithm, and the k-nearest neighbor algorithm, suggesting that preprocessing and classification algorithms have great potential for detecting metastatic cancer.

Keywords: breast cancer, principal component analysis, genetic algorithm, k-nearest neighbors, decision tree classifier, logistic regression

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Authors: John Lorenzo Bautista, Yoon-Joong Kim

Abstract:

In this paper, a set of Filipino Phonetically Balanced Word list consisting of 250 words (PBW250) were constructed for a phoneme-level ASR system for the Filipino language. The Entropy Maximization is used to obtain phonological balance in the list. Entropy of phonemes in a word is maximized, providing an optimal balance in each word’s phonological distribution using the Add-Delete Method (PBW algorithm) and is compared to the modified PBW algorithm implemented in a dynamic algorithm approach to obtain optimization. The gained entropy score of 4.2791 and 4.2902 for the PBW and modified algorithm respectively. The PBW250 was recorded by 40 respondents, each with 2 sets data. Recordings from 30 respondents were trained to produce an acoustic model that were tested using recordings from 10 respondents using the HMM Toolkit (HTK). The results of test gave the maximum accuracy rate of 97.77% for a speaker dependent test and 89.36% for a speaker independent test.

Keywords: entropy maximization, Filipino language, Hidden Markov Model, phonetically balanced words, speech recognition

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