Search results for: supply chain delivery models

Authors: A.Beril Tugrul, Selahattin Cimen

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Dependency of humanity on the energy is ever-increasing today and the energy policies are reaching undeniable and un-ignorable dimensions steering the political events as well. Therefore, energy has the highest priority for Turkey like any other country. In this study, the energy supply security for Turkey evaluated according to the strategic criteria of energy policy. Under these circumstances, different alternatives are described and assessed with in terms of the energy expansion of Turkey. With this study, different opportunities in the energy expansion of Turkey is clarified and emphasized.

Keywords: energy policy, energy strategy, future projection, Turkey

Procedia PDF Downloads 383

Authors: Sebastião Milton Pinheiro da Silva, Michele Barbosa da Rocha, Ana Lúcia Fernandes Campos, Miquéias Rildo de Souza Silva

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Water is an essential natural resource for life on Earth. Rivers, lakes, lagoons and dams are the main sources of water storage for human consumption. The costs of extracting and using these water sources are lower than those of exploiting groundwater on transition zones to semi-arid terrains. However, the volume of surface water has decreased over time, with the depletion of first-order drainage and the disappearance of springs, phenomena which are easily observed in the field. Climate change worsens water scarcity, compromising supply and hydric security for rural populations. To minimize the expected impacts, producing and storing water through watershed management planning requires detailed cartographic information on the relief and topography, and updated data on the stage and intensity of catchment basin environmental degradation problems. The cartography available of the Brazilian northeastern territory dates to the 70s, with topographic maps, printed, at a scale of 1:100,000 which does not meet the requirements to execute this project. Exceptionally, there are topographic maps at scales of 1:50,000 and 1:25,000 of some coastal regions in northeastern Brazil. Still, due to scale limitations and outdatedness, they are products of little utility for mapping low-order watersheds drainage and springs. Remote sensing data and geographic information systems can contribute to guiding the process of mapping and environmental recovery by integrating detailed relief and topographic data besides social and other environmental information in the Guajiru River Basin, located on the east coast of Rio Grande do Norte, on the Northeast region of Brazil. This study aimed to recognize and map catchment basin, springs and low-order drainage features along estimating morphometric parameters. Alos PALSAR and Copernicus DEM digital elevation models were evaluated and provided regional drainage features and the watersheds limits extracted with Terraview/Terrahidro 5.0 software. CBERS 4A satellite images with 2 m spatial resolution, processed with ESA SNAP Toolbox, allowed generating land use land cover map of Guajiru River. A Mappir Survey 3 multiespectral camera onboard of a DJI Phantom 4, a Mavic 2 Pro PPK Drone and an X91 GNSS receiver to collect the precised position of selected points were employed to detail mapping. Satellite images enabled a first knowledge approach of watershed areas on a more regional scale, yet very current, and drone images were essential in mapping details of catchment basins. The drone multispectral image mosaics, the digital elevation model, the contour lines and geomorphometric parameters were generated using OpenDroneMap/ODM and QGis softwares. The drone images generated facilitated the location, understanding and mapping of watersheds, recharge areas and first-order ephemeral watercourses on an adequate scale and will be used in the following project’s phases: watershed management planning, recovery and environmental protection of Rio's springs Guajiru. Environmental degradation is being analyzed from the perspective of the availability and quality of surface water supply.

Keywords: imaging, relief, UAV, water

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Authors: Maryam Khalilzadeh Poshtegal, Seyed Ahmad Mirbagheri, Mojtaba Noury

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In this paper, by application of the input yearly data of rainfall, temperature and flow to the Urmia Lake, the simulation of water level fluctuation were applied by means of three models. According to the climate change investigation the fluctuation of lakes water level are of high interest. This study investigate data-driven models, support vector machines (SVM), SVM method which is a new regression procedure in water resources are applied to the yearly level data of Lake Urmia that is the biggest and the hyper saline lake in Iran. The evaluated lake levels are found to be in good correlation with the observed values. The results of SVM simulation show better accuracy and implementation. The mean square errors, mean absolute relative errors and determination coefficient statistics are used as comparison criteria.

Keywords: simulation, water level fluctuation, urmia lake, support vector machine

Procedia PDF Downloads 359

Authors: Carmela Nardelli, Laura Iaffaldano, Valentina Capobianco, Antonietta Tafuto, Maddalena Ferrigno, Angela Capone, Giuseppe Maria Maruotti, Maddalena Raia, Rosa Di Noto, Luigi Del Vecchio, Pasquale Martinelli, Lucio Pastore, Lucia Sacchetti

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Maternal obesity and nutrient excess in utero increase the risk of future metabolic diseases in the adult life. The mechanisms underlying this process are probably based on genetic, epigenetic alterations and changes in foetal nutrient supply. In mammals, the placenta is the main interface between foetus and mother, it regulates intrauterine development, modulates adaptive responses to sub optimal in uterus conditions and it is also an important source of human amniotic mesenchymal stem cells (hA-MSCs). We previously highlighted a specific microRNA (miRNA) profiling in amnion from obese (Ob) pregnant women, here we compared the miRNA expression profile of hA-MSCs isolated from (Ob) and control (Co) women, aimed to search for any alterations in metabolic pathways that could predispose the new-born to the obese phenotype. Methods: We isolated, at delivery, hA-MSCs from amnion of 16 Ob- and 7 Co-women with pre-pregnancy body mass index (mean/SEM) 40.3/1.8 and 22.4/1.0 kg/m2, respectively. hA-MSCs were phenotyped by flow cytometry. Globally, 384 miRNAs were evaluated by the TaqMan Array Human MicroRNA Panel v 1.0 (Applied Biosystems). By the TargetScan program we selected the target genes of the miRNAs differently expressed in Ob- vs Co-hA-MSCs; further, by KEGG database, we selected the statistical significant biological pathways. Results: The immunophenotype characterization confirmed the mesenchymal origin of the isolated hA-MSCs. A large percentage of the tested miRNAs, about 61.4% (232/378), was expressed in hA-MSCs, whereas 38.6% (146/378) was not. Most of the expressed miRNAs (89.2%, 207/232) did not differ between Ob- and Co-hA-MSCs and were not further investigated. Conversely, 4.8% of miRNAs (11/232) was higher and 6.0% (14/232) was lower in Ob- vs Co-hA-MSCs. Interestingly, 7/232 miRNAs were obesity-specific, being expressed only in hA-MSCs isolated from obese women. Bioinformatics showed that these miRNAs significantly regulated (P<0.001) genes belonging to several metabolic pathways, i.e. MAPK signalling, actin cytoskeleton, focal adhesion, axon guidance, insulin signaling, etc. Conclusions: Our preliminary data highlight an altered miRNA profile in Ob- vs Co-hA-MSCs and suggest that an epigenetic miRNA-based mechanism of gene regulation could affect pathways involved in placental growth and function, thereby potentially increasing the newborn’s risk of metabolic diseases in the adult life.

Keywords: hA-MSCs, obesity, miRNA, biosystem

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Authors: Melissa Angus Baboun

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Utilizing a Critical Discourse Analysis (CDA) methodology and a theoretical framework based on disability studies, how Jamaican and Trinidadian newspapers discussed issues relating to the Deaf community were examined. The term deaf was inputted into the search engine tool of the online website for the Jamaica Observer and the Trinidad & Tobago Guardian. All 27 articles that contained the term deaf in its content and were written between August 1, 2017 and November 15, 2017 were chosen for the study. The data analysis was divided into three steps: (1) listing and analysis instances of metaphorical deafness (e.g. fall on deaf ears), (2) categorization of the content of the articles into the models of disability discourse (the medical, socio-cultural, and superscrip models of disability narratives), and (3) the analysis of any additional data found. A total of 42% of the articles pulled for this study did not deal with the Deaf community in any capacity, but rather instances of the use of idiomatic expressions that use deafness as a metaphor for a non-physical, undesirable trait. The most common idiomatic expression found was fall on deaf ears. Regarding the models of disability discourse, eight articles were found to follow the socio-cultural model, two were found to follow the medical model, and two were found to follow the superscrip model. The additional data found in these articles include two instances of the term deaf and mute, an overwhelming use of lower case d for the term deaf, and the misuse of the term translator (to mean interpreter).

Keywords: deafness, disability, news coverage, Caribbean newspapers

Procedia PDF Downloads 230

Authors: Yi-Chiang Huang, Hsu-Feng Lee, Yu-Chao Tseng, Wen-Yao Huang

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Proton exchange membranes as a key component in fuel cells have been widely studying over the past few decades. As proton exchange, membranes should have some main characteristics, such as good mechanical properties, low oxidative stability and high proton conductivity. In this work, trifluoromethyl groups had been introduced on polymer backbone and phenyl side chain which can provide densely located sulfonic acid group substitution and also promotes solubility, thermal and oxidative stability. Herein, a series of novel sulfonated aromatic hydrocarbon polyelectrolytes was synthesized by polycondensation of 4,4''''-difluoro-3,3''''- bis(trifluoromethyl)-2'',3''-bis(3-(trifluoromethyl)phenyl)-1,1':4',1'':4'',1''':4''',1''''-quinquephenyl with 2'',3''',5'',6''-tetraphenyl-[1,1':4',1'': 4'',1''':4''',1''''-quinquephenyl]-4,4''''-diol and post-sulfonated was through chlorosulfonic acid to given sulfonated polymers (SFC3-X) possessing ion exchange capacities ranging from 1.93, 1.91 and 2.53 mmol/g. ¹H NMR and FT-IR spectroscopy were applied to confirm the structure and composition of sulfonated polymers. The membranes exhibited considerably dimension stability (10-27.8% in length change; 24-56.5% in thickness change) and excellent oxidative stability (weight remain higher than 97%). The mechanical properties of membranes demonstrated good tensile strength on account of the high rigidity multi-phenylated backbone. Young's modulus were ranged 0.65-0.77GPa which is much larger than that of Nafion 211 (0.10GPa). Proton conductivities of membranes ranged from 130 to 240 mS/cm at 80 °C under fully humidified which were comparable or higher than that of Nafion 211 (150 mS/cm). The morphology of membranes was investigated by transmission electron microscopy which demonstrated a clear hydrophilic/hydrophobic phase separation with spherical ionic clusters in the size range of 5-20 nm. The SFC3-1.97 single fuel cell performance demonstrates the maximum power density at 1.08W/cm², and Nafion 211 was 1.24W/cm² as a reference in this work. The result indicated that SFC3-X are good candidates for proton exchange membranes in fuel cell applications. Fuel cell of other membranes is under testing.

Keywords: fuel cells, polyelectrolyte, proton exchange membrane, sulfonated polymers

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Authors: Satpreet Singh

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This paper introduces the new LACGC model to sustain the academic and non-academic business to future educational and organizational generations. The consumption of knowledge and the creation of new knowledge is a strength and focal interest of all academics and Non-academic organizations. Implementing newly created knowledge sustains the businesses to the next generation with growth without detriment. Existing models like the Scholar-practitioner model and Organization knowledge creation models focus specifically on academic or non-academic, not both. LACGC model can be used for both Academic and Non-academic at the domestic or international level. Researchers and scholars play a substantial role in finding literature and practice gaps in academic and non-academic disciplines. LACGC model has unrestricted the number of recurrences because the Consumption, Creation, and implementation of new ideas, disciplines, systems, and knowledge is a never-ending process and must continue from one generation to the next.

Keywords: academics, consumption, creation, generations, non-academics, research, sustainability

Procedia PDF Downloads 188

Authors: Wadha Alqahtani

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In recent times, polymers have seen a great surge in interest in the field of medicine, particularly chemotherapeutics. One recent innovation is the conversion of polymeric materials into “polymeric nanoparticles”. These nanoparticles can be designed and modified to encapsulate and transport drugs selectively to cancer cells, minimizing collateral damage to surrounding healthy tissues, and improve patient quality of life. In this study, we have synthesized pseudo-branched polyester polymers from bio-based small molecules, including sorbitol, glutaric acid and a propargylic acid derivative to further modify the polymer to make it “click-able" with an azide-modified target ligand. Melt polymerization technique was used for this polymerization reaction, using lipase enzyme catalyst NOVO 435. This reaction was conducted between 90- 95 °C for 72 hours. The polymer samples were collected in 24-hour increments for characterization and to monitor reaction progress. The resulting polymer was purified with the help of methanol dissolving and filtering with filter paper then characterized via NMR, GPC, FTIR, DSC, TGA and MALDI-TOF. Following characterization, these polymers were converted to a polymeric nanoparticle drug delivery system using solvent diffusion method, wherein DiI optical dye and chemotherapeutic drug Taxol can be encapsulated simultaneously. The efficacy of the nanoparticle’s apoptotic effects were analyzed in-vitro by incubation with prostate cancer (LNCaP) and healthy (CHO) cells. MTT assays and fluorescence microscopy were used to assess the cellular uptake and viability of the cells after 24 hours at 37 °C and 5% CO2 atmosphere. Results of the assays and fluorescence imaging confirmed that the nanoparticles were successful in both selectively targeting and inducing apoptosis in 80% of the LNCaP cells within 24 hours without affecting the viability of the CHO cells. These results show the potential of using biodegradable polymers as a vehicle for receptor-specific drug delivery and a potential alternative for traditional systemic chemotherapy. Detailed experimental results will be discussed in the e-poster.

Keywords: chemotherapeutic drug, click chemistry, nanoparticle, prostat cancer

Procedia PDF Downloads 111

Authors: Morteza Sharifhasan, Davoud Hosseini, Mohammad. R. Salimpour

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The geothermal energy is considered as a worldwide important renewable energy in recent years due to rising environmental pollution concerns. Low- and medium-grade geothermal heat (< 200 ºC) is commonly employed for space heating and in domestic hot water supply. However, there is also much interest in converting the abundant low- and medium-grade geothermal heat into electrical power. The Iranian Ministry of Power - through the Iran Renewable Energy Organization (SUNA) – is going to build the first Geothermal Power Plant (GPP) in Iran in the Sabalan area in the Northwest of Iran. This project is a 5.5 MWe single flash steam condensing power plant. The efficiency of GPPs is low due to the relatively low pressure and temperature of the saturated steam. In addition to GPPs, Gas Turbines (GTs) are also known by their relatively low efficiency. The Iran ministry of Power is trying to increase the efficiency of these GTs by adding bottoming steam cycles to the GT to form what is known as combined gas/steam cycle. One of the most effective methods for increasing the efficiency is combined heat and power (CHP). This paper investigates the feasibility of superheating the saturated steam that enters the steam turbine of the Sabalan GPP (SGPP-1) to improve the energy efficiency and power output of the GPP. This purpose is achieved by combining the GPP with two 3.5 MWe GTs. In this method, the hot gases leaving GTs are utilized through a superheater similar to that used in the heat recovery steam generator of combined gas/steam cycle. Moreover, brine separated in the separator, hot gases leaving GTs and superheater are used for the supply of domestic hot water (in this paper, the cycle combined of GTs and CHP systems is named the modified SGPP-1) . In this research, based on the Heat Balance presented in the basic design documents of the SGPP-1, mathematical/numerical model of the power plant are developed together with the mentioned GTs and CHP systems. Based on the required hot water, the amount of hot gasses needed to pass through CHP section directly can be adjusted. For example, during summer when hot water is less required, the hot gases leaving both GTs pass through the superheater and CHP systems respectively. On the contrary, in order to supply the required hot water during the winter, the hot gases of one of the GTs enter the CHP section directly, without passing through the super heater section. The results show that there is an increase in thermal efficiency up to 40% through using the modified SGPP-1. Since the gross efficiency of SGPP-1 is 9.6%, the achieved increase in thermal efficiency is significant. The power output of SGPP-1 is increased up to 40% in summer (from 5.5MW to 7.7 MW) while the GTs power output remains almost unchanged. Meanwhile, the combined-cycle power output increases from the power output of the two separate plants of 12.5 MW [5.5+ (2×3.5)] to the combined-cycle power output of 14.7 [7.7+(2×3.5)]. This output is more than 17% above the output of the two separate plants. The modified SGPP-1 is capable of producing 215 T/Hr hot water ( 90 ºC ) for domestic use in the winter months.

Keywords: combined cycle, chp, efficiency, gas turbine, geothermal power plant, gas turbine, power output

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Authors: Yee Hooi Min, Mohdnasir Abdul Hadi

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Tensioned membrane structure in the form of Enneper minimal surface can be considered as a sustainable development for the green environment and technology, it also can be used to support the effectiveness used of energy and the structure. Soap film in the form of Enneper minimal surface model has been studied. The combination of shape and internal forces for the purpose of stiffness and strength is an important feature of membrane surface. For this purpose, form-finding using soap film model has been carried out for Enneper minimal surface models with variables u=v=0.6 and u=v=1.0. Enneper soap film models with variables u=v=0.6 and u=v=1.0 provides an alternative choice for structural engineers to consider the tensioned membrane structure in the form of Enneper minimal surface applied in the building industry. It is expected to become an alternative building material to be considered by the designer.

Keywords: Enneper, minimal surface, soap film, tensioned membrane structure

Procedia PDF Downloads 547

Authors: Mauro Callejas-Cuervo, Andrea Catherine Alarcon-Aldana, Lorena Paola Castillo-Guerra

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The software industry requires highly-trained professionals, capable of developing the roles integrated in the cycle of software development. That is why a large part of the task is the responsibility of higher education institutions; often through a curriculum established to orientate the academic development of the students. It is so that nowadays there are different models that support proposals for the improvement of the curricula for the area of Software Engineering, such as ACM, IEEE, ABET, Swebok, of which the last stands out, given that it manages and organises the knowledge of Software Engineering and offers a vision of theoretical and practical aspects. Moreover, it has been applied by different universities in the pursuit of achieving coverage in delivering the different topics and increasing the professional quality of future graduates. This research presents the structure of teaching and learning guides from the objectives of training and methodological strategies immersed in the levels of learning of Bloom’s taxonomy with which it is intended to improve the delivery of the topics in the area of Requirements Engineering. Said guides were implemented and validated in a course of Requirements Engineering of the Systems and Computer Engineering programme in the Universidad Pedagógica y Tecnológica de Colombia (Pedagogical and Technological University of Colombia) using a four stage methodology: definition of the evaluation model, implementation of the guides, guide evaluation, and analysis of the results. After the collection and analysis of the data, the results show that in six out of the seven topics proposed in the Swebok guide, the percentage of students who obtained total marks within the 'High grade' level, that is between 4.0 and 4.6 (on a scale of 0.0 to 5.0), was higher than the percentage of students who obtained marks within the 'Acceptable' range of 3.0 to 3.9. In 86% of the topics and the strategies proposed, the teaching and learning guides facilitated the comprehension, analysis, and articulation of the concepts and processes of the students. In addition, they mainly indicate that the guides strengthened the argumentative and interpretative competencies, while the remaining 14% denotes the need to reinforce the strategies regarding the propositive competence, given that it presented the lowest average.

Keywords: pedagogic guide, pedagogic strategies, requirements engineering, Swebok, teaching-learning process

Procedia PDF Downloads 282

Authors: Hung-Chieh Chen, Kuo-Hui Wang, Tsu-Lin Yeh

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Proteomics represent the performance of genomic complement proteins and the protein level on functional genomics. This study adopted proteomic strategies for comparing serum proteins among three groups: elite sprinter (sprint runner group, SR), long-distance runners (long-distance runner group, LDR), and the untrained control group (control group, CON). Purposes: This study aims to identify elite sprinters and long-distance runners’ serum protein and to provide a comparison of their serum proteome’ composition. Methods: Serum protein fractionations that separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and analyzed by a quantitative nano-LC-MS/MS-based proteomic profiling. The one-way analysis of variance (ANOVA) and Scheffe post hoc comparison (α= 0.05) was used to determine whether there is any significant difference in each protein level among the three groups. Results: (1) After analyzing the 307 identified proteins, there were 26 unique proteins in the SR group, and 18 unique proteins in the LDR group. (2) For the LDR group, 7 coagulation function-associated proteins’ expression levels were investigated: vitronectin, serum paraoxonase/arylesterase 1, fibulin-1, complement C3, vitamin K-dependent protein, inter-alpha-trypsin inhibitor heavy chain H3 and von Willebrand factor, and the findings show the seven coagulation function-associated proteins were significantly lower than the group of SR. (3) Comparing to the group of SR, this study found that the LDR group’s expression levels of the 2 antioxidant proteins (afamin and glutathione peroxidase 3) were also significantly lower. (4) The LDR group’s expression levels of seven immune function-related proteins (Ig gamma-3 chain C region, Ig lambda-like polypeptide 5, clusterin, complement C1s subcomponent, complement factor B, complement C4-A, complement C1q subcomponent subunit A) were also significantly lower than the group of SR. Conclusion: This study identified the potential serum protein markers for elite sprinters and long-distance runners. The changes in the regulation of coagulation, antioxidant, or immune function-specific proteins may also provide further clinical applications for these two different track athletes.

Keywords: biomarkers, coagulation, immune response, oxidative stress

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Authors: Lokvendra S. Budania, Yogesh K Gaude, Vamsidhar Chamala

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Introduction: Congenitally corrected transposition of great arteries (CCTGA) is a complex congenital heart disease where there are both atrioventricular and ventriculoarterial discordances, usually accompanied by other cardiovascular malformations. Case Report: A 24-year-old primigravida known case of CCTGA at 37 weeks of gestation was referred to our hospital for safe delivery. Her electrocardiogram showed HR-40/pm, echocardiography showed Ejection Fraction of 65% and CCTGA. Temporary pacemaker was inserted by cardiologist in catheterization laboratory, before giving trial of labour in view of complete heart block. She was planned for normal delivery, but emergency Caesarean section was planned due to non-reassuring foetal Cardiotocography Pre-op vitals showed PR-50 bpm with temporary pacemaker, Blood pressure-110/70 mmHg, SpO2-99% on room air. Nil per oral was inadequate. Patency of two peripheral IV cannula checked and left radial arterial line secured. Epidural Anaesthesia was planned, and catheter was placed at L2-L3. Test dose was given, Anaesthesia was provided with 5ml + 5ml of 2% Lignocaine with 25 mcg Fentanyl and further 2.5Ml of 0.5% Bupivacaine was given to achieve a sensory level of T6. Cesarean section was performed and baby was delivered. Cautery was avoided during this procedure. IV Oxytocin (15U) was added to 500 mL of ringer’s lactate. Hypotension was treated with phenylephrine boluses. Patient was shifted to post-operative care unit and later to high dependency unit for monitoring. Post op vitals remained stable. Temporary pacemaker was removed after 24 hours of surgery. Her post-operative period was uneventful and discharged from hospital. Conclusion: Rare congenital cardiac disorders require detail knowledge of pathophysiology and associated comorbidities with the disease. Meticulously planned and carefully titrated neuraxial techniques will be beneficial for such cases.

Keywords: congenitally corrected transposition of great arteries, complete heart block, emergency LSCS, epidural anaesthesia

Procedia PDF Downloads 129

Authors: Karima Abdel Aty Hassan Mohamed, Manal Mohamed Ismail, Mona Hassan Gamal Eldein, Ahmed Hassan Hussein, Abdel Aziz Mohamed Elsingerg

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Background: Patellofemoral pain (PFP) is a common musculoskeletal pain condition, especially in females. Decreased hip muscle strength has been implicated as a contributing factor, yet the relationships between pain, hip muscle strength and function are not known. Objective: The purpose of this study is to investigate the effects of strengthening hip abductors and lateral rotators on pain intensity, function and hip abductor and hip lateral rotator eccentric and concentric torques in patients with PFPS. Methods: Thirty patients had participated in this study; they were assigned into two experimental groups. With age ranged for eighty to thirty five years. Group A consisted of 15 patients (11females and 4 males) with mean age 20.8 (±2.73) years, received closed kinetic chain exercises program, stretching exercises for tight lower extremity soft tissues, and hip strengthening exercises .Group B consisted of 15 patients (12 females and 3 males) with mean age 21.2(±3.27) years, received closed kinetic chain exercises program and stretching exercises for tight lower extremity soft tissues. Treatment was given 2-3times/week, for 6 weeks. Patients were evaluated pre and post treatment for their pain severity, function of knee joint, hip abductors and external rotators concentric/eccentric peak torque. Result: the results revealed that there were significant differences in pain and function between both groups, while there was improvement for all values for both group. Conclusion: Six weeks rehabilitation program focusing on knee strengthening exercises either supplemented by hip strengthening exercises or not effective in improving function, reducing pain and improving hip muscles torque in patients with PFPS. However, adding hip abduction and lateral rotation strengthening exercises seem to reduce pain and improve function more efficiently.

Keywords: patellofemoral pain syndrome, hip muscles, rehabilitation, isokinetic

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Authors: Shanshan Zhu, Mohammad Nasim

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Financial fraud continues to be a major threat to financial institutions across the world, causing colossal money losses and undermining public trust. Fraud prevention techniques, based on hard rules, have become ineffective due to evolving patterns of fraud in recent times. Against such a background, the present study probes into distinct methodologies that exploit emergent AI-driven techniques to further strengthen fraud detection. We would like to compare the performance of generative adversarial networks and graph neural networks with other popular techniques, like gradient boosting, random forests, and neural networks. To this end, we would recommend integrating all these state-of-the-art models into one robust, flexible, and smart system for real-time anomaly and fraud detection. To overcome the challenge, we designed synthetic data and then conducted pattern recognition and unsupervised and supervised learning analyses on the transaction data to identify which activities were fishy. With the use of actual financial statistics, we compare the performance of our model in accuracy, speed, and adaptability versus conventional models. The results of this study illustrate a strong signal and need to integrate state-of-the-art, AI-driven fraud detection solutions into frameworks that are highly relevant to the financial domain. It alerts one to the great urgency that banks and related financial institutions must rapidly implement these most advanced technologies to continue to have a high level of security.

Keywords: AI-driven fraud detection, financial security, machine learning, anomaly detection, real-time fraud detection

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Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

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Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

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Authors: Amin Salighehdar, Ziwen Ye, Mingzhe Liu, Ionut Florescu, Alan F. Blumberg

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Storm surge is an abnormal water level caused by a storm. Accurate prediction of a storm surge is a challenging problem. Researchers developed various ensemble modeling techniques to combine several individual forecasts to produce an overall presumably better forecast. There exist some simple ensemble modeling techniques in literature. For instance, Model Output Statistics (MOS), and running mean-bias removal are widely used techniques in storm surge prediction domain. However, these methods have some drawbacks. For instance, MOS is based on multiple linear regression and it needs a long period of training data. To overcome the shortcomings of these simple methods, researchers propose some advanced methods. For instance, ENSURF (Ensemble SURge Forecast) is a multi-model application for sea level forecast. This application creates a better forecast of sea level using a combination of several instances of the Bayesian Model Averaging (BMA). An ensemble dressing method is based on identifying best member forecast and using it for prediction. Our contribution in this paper can be summarized as follows. First, we investigate whether the ensemble models perform better than any single forecast. Therefore, we need to identify the single best forecast. We present a methodology based on a simple Bayesian selection method to select the best single forecast. Second, we present several new and simple ways to construct ensemble models. We use correlation and standard deviation as weights in combining different forecast models. Third, we use these ensembles and compare with several existing models in literature to forecast storm surge level. We then investigate whether developing a complex ensemble model is indeed needed. To achieve this goal, we use a simple average (one of the simplest and widely used ensemble model) as benchmark. Predicting the peak level of Surge during a storm as well as the precise time at which this peak level takes place is crucial, thus we develop a statistical platform to compare the performance of various ensemble methods. This statistical analysis is based on root mean square error of the ensemble forecast during the testing period and on the magnitude and timing of the forecasted peak surge compared to the actual time and peak. In this work, we analyze four hurricanes: hurricanes Irene and Lee in 2011, hurricane Sandy in 2012, and hurricane Joaquin in 2015. Since hurricane Irene developed at the end of August 2011 and hurricane Lee started just after Irene at the beginning of September 2011, in this study we consider them as a single contiguous hurricane event. The data set used for this study is generated by the New York Harbor Observing and Prediction System (NYHOPS). We find that even the simplest possible way of creating an ensemble produces results superior to any single forecast. We also show that the ensemble models we propose generally have better performance compared to the simple average ensemble technique.

Keywords: Bayesian learning, ensemble model, statistical analysis, storm surge prediction

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Authors: Linda Chularojmontri, Seewaboon Sireeratawong, Suvara Wattanapitayakul

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Terminalia arjuna Roxb. (family Combretaceae) is commonly known as ‘Sa maw thet’ in Thai. The fruit is used in traditional medicine as natural mild laxatives, carminative and expectorant. Aim of the study: This research aims to study the anti-inflammatory, analgesic and antipyretic activities of Terminalia arjuna extract by using animal models in comparison to the reference drugs. Materials and Methods: The anti-inflammatory study was conducted by two experimental animal models namely ethyl phenylpropionate (EPP)-induced ear edema and carrageenan-induced paw edema. The study of analgesic activity used two methods of pain induction including acetic acid and heat-induced pain. In addition, the antipyretic activity study was performed by induced hyperthermia with yeast. Results: The results showed that the oral administration of Terminalia arjuna extract possessed acute anti-inflammatory effect in carrageenan-induced paw edema. Terminalia arjuna extract showed the analgesic activity in acetic acid-induced writhing response and heat-induced pain. This indicates its peripheral effect by inhibiting the biosynthesis and/or release of some pain mediators and some mechanism through Central nervous system. Moreover, Terminalia arjuna extract at the dose of 1000 and 1500 mg/kg body weight showed the antipyretic activity, which might be because of the inhibition of prostaglandins. Conclusion: The findings of this study indicated that the Terminalia arjuna extract possesses the anti-inflammatory, analgesic and antipyretic activities in animals.

Keywords: analgesic activity, anti-inflammatory activity, antipyretic activity, Terminalia arjuna extract

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Authors: Jinil Patel, Sarthak Patel, Sarthak Thakkar, Deepti Saraswat

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Recently, the COVID-19 outbreak has spread across the world, leading the World Health Organization to classify it as a global pandemic. To save the patient’s life, the COVID-19 symptoms have to be identified. But using an AI (Artificial Intelligence) model to identify COVID-19 symptoms within the allotted time was challenging. The RT-PCR test was found to be inadequate in determining the COVID status of a patient. To determine if the patient has COVID-19 or not, a Computed Tomography Scan (CT scan) of patient is a better alternative. It will be challenging to compile and store all the data from various hospitals on the server, though. Federated learning, therefore, aids in resolving this problem. Certain deep learning models help to classify Covid-19. This paper will have detailed work of certain deep learning models like VGG19, ResNet50, MobileNEtv2, and Deep Learning Aggregation (DLA) along with maintaining privacy with encryption.

Keywords: federated learning, COVID-19, CT-scan, homomorphic encryption, ResNet50, VGG-19, MobileNetv2, DLA

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Authors: Parveen Kumar

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The cope the rapid change of technology and to control the ephemeral rate of information generation, librarians along with their professional colleagues need to equip themselves as per the requirement of the electronic information society. E-learning is purely based on computer and communication technologies. The terminologies like computer based learning. It is the delivery of content via all electronic media through internet, internet, Extranets television broadcast, CD-Rom documents, etc. E-learning poses lot of issues in the transformation of literature or knowledge from the conventional medium to ICT based format and web based services.

Keywords: e-learning, digital libraries, online learning, electronic information society

Procedia PDF Downloads 505

Authors: Abid Boudiar

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We propose a simple model to obtain an exact expression of Tc/(Tc,max) for the temperature-doping phase diagram of superconducting cuprates. We showed that our model predicted most phase diagram scenario. We found the exact special doping points p(opt), p(qcp) and an accurate E(g,max). Some other properties such as the stripes length 100.1°A and the energy gap in cuprates chain
6meV can also be calculated exactly. Another interesting consequence of this simple picture is the new magic numbers and the ability to express everything using a (Tc,p) diagram via the golden ratio.

Keywords: superconducting cuprates, phase, pseudogap, hole doping, strips, golden ratio, soliton

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Authors: Heeba A. Gurku

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Introduction: Cone Beam CT(CBCT) images play an integral part in proper patient positioning in cancer patients undergoing radiation therapy treatment. But these images are low in quality. The purpose of this study is to generate high-quality synthetic CT images from CBCT using generative models. Material and Methods: This study utilized two datasets from The Cancer Imaging Archive (TCIA) 1) Lung cancer dataset of 20 patients (with full view CBCT images) and 2) Pancreatic cancer dataset of 40 patients (only 27 patients having limited view images were included in the study). Cycle Generative Adversarial Networks (GAN) and its variant Attention Guided Generative Adversarial Networks (AGGAN) models were used to generate the synthetic CTs. Models were evaluated by visual evaluation and on four metrics, Structural Similarity Index Measure (SSIM), Peak Signal Noise Ratio (PSNR) Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), to compare the synthetic CT and original CT images. Results: For pancreatic dataset with limited view CBCT images, our study showed that in Cycle GAN model, MAE, RMSE, PSNR improved from 12.57to 8.49, 20.94 to 15.29 and 21.85 to 24.63, respectively but structural similarity only marginally increased from 0.78 to 0.79. Similar, results were achieved with AGGAN with no improvement over Cycle GAN. However, for lung dataset with full view CBCT images Cycle GAN was able to reduce MAE significantly from 89.44 to 15.11 and AGGAN was able to reduce it to 19.77. Similarly, RMSE was also decreased from 92.68 to 23.50 in Cycle GAN and to 29.02 in AGGAN. SSIM and PSNR also improved significantly from 0.17 to 0.59 and from 8.81 to 21.06 in Cycle GAN respectively while in AGGAN SSIM increased to 0.52 and PSNR increased to 19.31. In both datasets, GAN models were able to reduce artifacts, reduce noise, have better resolution, and better contrast enhancement. Conclusion and Recommendation: Both Cycle GAN and AGGAN were significantly able to reduce MAE, RMSE and PSNR in both datasets. However, full view lung dataset showed more improvement in SSIM and image quality than limited view pancreatic dataset.

Keywords: CT images, CBCT images, cycle GAN, AGGAN

Procedia PDF Downloads 78

Authors: Auwal Abubakar, Shazril Imran Shaukat, Noor Khairiah A. Karim, Mohammed Zakir Kassim, Gokula Kumar Appalanaido, Hafiz Mohd Zin

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Background: Voluntary deep inspiration breath-hold radiotherapy (vDIBH-RT) is an effective cardiac dose reduction technique during left breast radiotherapy. This study aimed to assess the accuracy of the implementation of the vDIBH technique among left breast cancer patients without the use of a special device such as a surface-guided imaging system. Methods: The vDIBH-RT technique was implemented among thirteen (13) left breast cancer patients at the Advanced Medical and Dental Institute (AMDI), Universiti Sains Malaysia. Breath-hold monitoring was performed based on breath-hold skin marks and laser light congruence observed on zoomed CCTV images from the control console during each delivery. The initial setup was verified using cone beam computed tomography (CBCT) during breath-hold. Each field was delivered using multiple beam segments to allow a delivery time of 20 seconds, which can be tolerated by patients in breath-hold. The data were analysed using an in-house developed MATLAB algorithm. PTV margin was computed based on van Herk's margin recipe. Results: The setup error analysed from CBCT shows that the population systematic error in lateral (x), longitudinal (y), and vertical (z) axes was 2.28 mm, 3.35 mm, and 3.10 mm, respectively. Based on the CBCT image guidance, the Planning target volume (PTV) margin that would be required for vDIBH-RT using CCTV/Laser monitoring technique is 7.77 mm, 10.85 mm, and 10.93 mm in x, y, and z axes, respectively. Conclusion: It is feasible to safely implement vDIBH-RT among left breast cancer patients without special equipment. The breath-hold monitoring technique is cost-effective, radiation-free, easy to implement, and allows real-time breath-hold monitoring.

Keywords: vDIBH, cone beam computed tomography, radiotherapy, left breast cancer

Procedia PDF Downloads 48

Authors: Dila Ram Bhandari

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Throughout the 20th century, new governments were created where identities such as ethnic, religious, linguistic, caste, communal, tribal, and others played a part in the development of constitutions and the legal system of victim and criminal justice. Acute issues with extremism, poverty, environmental degradation, cybercrimes, human rights violations, crime against, and victimization of both individuals and groups have recently plagued South Asian nations. Everyday massive number of crimes are steadfast, these frequent crimes have made the lives of common citizens restless. Crimes are one of the major threats to society and also for civilization. Crime is a bone of contention that can create a societal disturbance. The old-style crime solving practices are unable to live up to the requirement of existing crime situations. Crime analysis is one of the most important activities of the majority of intelligent and law enforcement organizations all over the world. The South Asia region lacks such a regional coordination mechanism, unlike central Asia of Asia Pacific regions, to facilitate criminal intelligence sharing and operational coordination related to organized crime, including illicit drug trafficking and money laundering. There have been numerous conversations in recent years about using data mining technology to combat crime and terrorism. The Data Detective program from Sentient as a software company, uses data mining techniques to support the police (Sentient, 2017). The goals of this internship are to test out several predictive model solutions and choose the most effective and promising one. First, extensive literature reviews on data mining, crime analysis, and crime data mining were conducted. Sentient offered a 7-year archive of crime statistics that were daily aggregated to produce a univariate dataset. Moreover, a daily incidence type aggregation was performed to produce a multivariate dataset. Each solution's forecast period lasted seven days. Statistical models and neural network models were the two main groups into which the experiments were split. For the crime data, neural networks fared better than statistical models. This study gives a general review of the applied statistics and neural network models. A detailed image of each model's performance on the available data and generalizability is provided by a comparative analysis of all the models on a comparable dataset. Obviously, the studies demonstrated that, in comparison to other models, Gated Recurrent Units (GRU) produced greater prediction. The crime records of 2005-2019 which was collected from Nepal Police headquarter and analysed by R programming. In conclusion, gated recurrent unit implementation could give benefit to police in predicting crime. Hence, time series analysis using GRU could be a prospective additional feature in Data Detective.

Keywords: time series analysis, forecasting, ARIMA, machine learning

Procedia PDF Downloads 161

Authors: Nayak Amar, Turner Naomi, Gobina Edward

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The Scottish Higher Education Institutes must report their scope 1 & 2 emissions, whereas reporting scope 3 is optional. Scope 3 is indirect emissions which embodies a significant component of total carbon footprint and therefore it is important to record, measure and report it accurately. Robert Gordon University (RGU) reported only business travel, grid transmission and distribution, water supply and transport, and recycling scope 3 emissions. This study estimates the RGUs total scope 3 emissions by comparing it with a similar HEI in scale. The scope 3 emission reporting of sixteen Scottish HEI was studied. Glasgow Caledonian University was identified as the nearest neighbour by comparing its students' full time equivalent, staff full time equivalent, research-teaching split, budget, and foundation year. Apart from the peer, data was also collected from the Higher Education Statistics Agency database. RGU reported emissions from business travel, grid transmission and distribution, water supply, and transport and recycling. This study estimated RGUs scope 3 emissions from procurement, student-staff commute, and international student trip. The result showed that RGU covered only 11% of the scope 3 emissions. The major contributor to scope 3 emissions were procurement (48%), student commute (21%), international student trip (16%), and staff commute (4%). The estimated scope 3 emission was more than 14 times the reported emissions. This study has shown the relative importance of each scope 3 emissions source, which gives a guideline for the HEIs, on where to focus their attention to capture maximum scope 3 emissions. Moreover, it has demonstrated that it is possible to estimate the scope 3 emissions with limited data.

Keywords: HEI, university, emission calculations, scope 3 emissions, emissions reporting

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Authors: Mohsen Farhadloo, Majid Farhadloo

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Aspect-level opinion mining that aims at discovering aspects (aspect identification) and their corresponding ratings (sentiment identification) from customer reviews have increasingly attracted attention of researchers and practitioners as it provides valuable insights about products/services from customer's points of view. Instead of addressing aspect identification and sentiment identification in two separate steps, it is possible to simultaneously identify both aspects and sentiments. In recent years many graphical models based on Latent Dirichlet Allocation (LDA) have been proposed to solve both aspect and sentiment identifications in a single step. Although LDA models have been effective tools for the statistical analysis of document collections, they also have shortcomings in addressing some unique characteristics of opinion mining. Our goal in this paper is to address one of the limitations of topic models to date; that is, they fail to directly model the associations among topics. Indeed in many text corpora, it is natural to expect that subsets of the latent topics have higher probabilities. We propose a probabilistic graphical model called focus-LDA, to better capture the associations among topics when applied to aspect-level opinion mining. Our experiments on real-life data sets demonstrate the improved effectiveness of the focus-LDA model in terms of the accuracy of the predictive distributions over held out documents. Furthermore, we demonstrate qualitatively that the focus-LDA topic model provides a natural way of visualizing and exploring unstructured collection of textual data.

Keywords: aspect-level opinion mining, document modeling, Latent Dirichlet Allocation, LDA, sentiment analysis

Procedia PDF Downloads 91

Authors: Bongs Lainjo

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Educational institutions and authorities that are mandated to run education systems in various countries need to implement a curriculum that considers the possibility and existence of elementary school dropouts. This research focuses on elementary school dropout rates and the ability to replicate various predictive models carried out globally on selected Elementary Schools. The study was carried out by comparing the classical case studies in Africa, North America, South America, Asia and Europe. Some of the reasons put forward for children dropping out include the notion of being successful in life without necessarily going through the education process. Such mentality is coupled with a tough curriculum that does not take care of all students. The system has completely led to poor school attendance - truancy which continuously leads to dropouts. In this study, the focus is on developing a model that can systematically be implemented by school administrations to prevent possible dropout scenarios. At the elementary level, especially the lower grades, a child's perception of education can be easily changed so that they focus on the better future that their parents desire. To deal effectively with the elementary school dropout problem, strategies that are put in place need to be studied and predictive models are installed in every educational system with a view to helping prevent an imminent school dropout just before it happens. In a competency-based curriculum that most advanced nations are trying to implement, the education systems have wholesome ideas of learning that reduce the rate of dropout.

Keywords: elementary school, predictive models, machine learning, risk factors, data mining, classifiers, dropout rates, education system, competency-based curriculum

Procedia PDF Downloads 168

Authors: Rizwana Tabassum

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Introductive Statement: Delay in budget releases is often cited as one of the biggest bottlenecks to smooth and efficient service delivery. While budget release from the ministry of finance to the line ministries has been expedited by simplifying the procedure, budget distribution within the line ministries remains one of the major causes of slow budget utilization. While the budget preparation is a bottom-up process where all DDOs submit their proposals to their controlling officers (such as Upazila Civil Surgeon sends it to Director General Health), who consolidate the budget proposals in iBAS++ budget preparation module, the approved budget is not disaggregated by all DDOs. Instead, it is left to the discretion of the controlling officers to distribute the approved budget to their sub-ordinate offices over the course of the year. Though there are some need-based criteria/formulae to distribute the approved budget among DDOs in some sectors, there is little evidence that these criteria are actually used. This means that majority of the DDOs don’t know their yearly allocations upfront to enable yearly planning of activities and expenditures. This delays the implementation of critical activities and the payment to the suppliers of goods and services and sometimes leads to undocumented arrears to suppliers for essential goods/services. In addition, social sector budgets are fragmented because of the vertical programs and externally financed interventions that pose several management challenges at the level of the budget holders and frontline service providers. Slow procurement processes further delay the provision of necessary goods and services. For example, it takes an average of 15–18 months for drugs to reach the Upazila Health Complex and below, while it should not take more than 9 months in procuring and distributing these. Aim of the Study: This paper aims to investigate the budget distribution practices of an emerging economy, Bangladesh. The paper identifies challenges of timely distribution and ways to deal with problems as well. Methodology: The study draws conclusions on the basis of document analysis which is a branch of the qualitative research method. Major Findings: Upon approval of the National Budget, the Ministry of Finance is required to distribute the budget to budget holders at the department level; however, budget is distributed to drawing and disbursing officers much later. Conclusions: Timely and predictable budget releases assist completion of development schemes on time and on budget, with sufficient recurrent resources for effective operation. ADP implementation is usually very low at the beginning of the fiscal year and expedited dramatically during the last few months, leading to inefficient use of resources. The timely budget release will resolve this issue and deliver economic benefits faster, better, and more reliably. This will also give the project directors/DDOs the freedom to think and plan the budget execution in a predictable manner, thereby ensuring value for money by reducing time overrun and expediting the completion of capital investments, and improving infrastructure utilization through timely payment of recurrent costs.

Keywords: budget distribution, challenges, digitization, emerging economy, service delivery

Procedia PDF Downloads 77

Authors: Wesam Rohouma

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The aim of this paper is to investigate the use of repetitive controller to regulate the output voltage of three phase four leg matric converter for an Aircraft Ground Power Supply Unit. The proposed controller improve the steady state error and provide good regulation during different loading. Simulation results of 7.5 KW converter are presented to verify the operation of the proposed controller.

Keywords: matrix converter, Power electronics, controller, regulation

Procedia PDF Downloads 1501

Authors: Wynne De Jong, Robert Miller, Ross Riggs

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Beyond the number of nurses providing care for patients, having nurses with the right skills, experience and education is essential to ensure the best possible outcomes for patients. Research studies continue to link nurse staffing and skill mix with nurse-sensitive patient outcomes; numerous studies clearly show that superior patient outcomes are associated with higher levels of regulated staff. Due to the limited number of tools and processes available to assist nurse leaders with staffing models of care, nurse leaders are constantly faced with the ongoing challenge to ensure their staffing models of care best suit their patient population. In 2009, several hospitals in Ontario, Canada participated in a research study to develop and evaluate an RN/RPN utilization toolkit. The purpose of this study was to develop and evaluate a toolkit for Registered Nurses/Registered Practical Nurses Staff mix decision-making based on the College of Nurses of Ontario, Canada practice standards for the utilization of RNs and RPNs. This paper will highlight how an organization has further developed the Patient Care Needs Assessment (PCNA) questionnaire, a major component of the toolkit. Moreover, it will demonstrate how it has utilized the information from PCNA to clearly identify patient and family care needs, thus providing evidence-based results to assist leaders with matching the best staffing skill mix to their patients.

Keywords: nurse staffing models of care, skill mix, nursing health human resources, patient safety

Procedia PDF Downloads 310