Search results for: conventionally manufacturing techniques

Authors: V. Sulakatko, F. U. Vogdt, I. Lill

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Construction technology and on-site construction activities have a direct influence on the life cycle costs of energy efficiently renovated apartment buildings. The systematic inadequacies of the External Thermal Insulation Composite System (ETICS) which occur during the construction phase increase the risk for all stakeholders, reduce mechanical durability and increase the life cycle costs of the building. The economic effect of these shortcomings can be minimised if the risk of the most significant on-site activities is recognised. The objective of the presented ETICS economic assessment concept is to evaluate the economic influence of on-site shortcomings and reveal their significance to the foreseeable future repair costs. The model assembles repair techniques, discusses their direct cost calculation methods, argues over the proper usage of net present value over the life cycle of the building, and proposes a simulation tool to evaluate the risk of on-site activities. As the technique is dependent on the selected real interest rate, a sensitivity analysis is anticipated to determine the validity of the recommendations. After the verification of the model on the sample buildings by the industry, it is expected to increase economic rationality of resource allocation and reduce high-risk systematic shortcomings during the construction process of ETICS.

Keywords: activity-based cost estimating, cost estimation, ETICS, life cycle costing

Procedia PDF Downloads 279

Authors: Marcia Silva, Jayme Kolarik, Brennon Garthwait, William Lee, Hai-Feng Zhang

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Adsorption of lead by a natural porous material was studied to establish a baseline for the removal of heavy metals from drinking and waste water. Samples were examined under different conditions such as solution pH, solution concentration, solution temperature, and exposure time. New materials with potentially enhanced adsorption properties were developed by functionalizing the surface of the natural porous material to fabricate graphene based coated and sulfide based treated porous material. The functionalized materials were characterized with Fourier Transform Infrared Spectroscopy (FTIR), Raman, Thermogravimetric Analysis (TGA) and Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy (EDS) techniques. Solution pH effect on removal efficiency has been investigated in acidic (pH = 4), neutral (pH = 6) and basic (pH = 10) pH levels. All adsorbent materials showed highest adsorption capacities at neutral pH levels. Batch experiment was employed to assess the efficacy for the removal of lead with the sorption kinetics and the adsorption isotherms being determined for the natural and treated porous materials. The addition of graphene-based and sulfide-based materials increased the lead removal capacity of the natural clean porous material. Theoretical calculations confirmed pseudo-second order model as kinetic mechanism for lead adsorption for all adsorbents.

Keywords: heavy metals, ion exchange, adsorption, water remediation

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Authors: Mahdieh Jajroudi

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Developing a pharmacokinetic model for the neuroendocrine tumors therapy agent 177Lu-DOTATATE in nude mice bearing AR42J rat pancreatic tumor to investigate and evaluate the behavior of the complex was the main purpose of this study. The utilization of compartmental analysis permits the mathematical differencing of tissues and organs to become acquainted with the concentration of activity in each fraction of interest. Biodistribution studies are onerous and troublesome to perform in humans, but such data can be obtained facilely in rodents. A physiologically based pharmacokinetic model for scaling up activity concentration in particular organs versus time was developed. The mathematical model exerts physiological parameters including organ volumes, blood flow rates, and vascular permabilities; the compartments (organs) are connected anatomically. This allows the use of scale-up techniques to forecast new complex distribution in humans' each organ. The concentration of the radiopharmaceutical in various organs was measured at different times. The temporal behavior of biodistribution of 177Lu labeled somatostatin analogues was modeled and drawn as function of time. Conclusion: The variation of pharmaceutical concentration in all organs is characterized with summation of six to nine exponential terms and it approximates our experimental data with precision better than 1%.

Keywords: biodistribution modeling, compartmental analysis, 177Lu labeled somatostatin analogues, neuroendocrine tumors

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Authors: Nattabhorn Leamcharaskul

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This study aims to examine determining factors of the dynamics of poverty in Thailand by using panel data of 3,567 households in 2007-2017. Four techniques of estimation are employed to analyze the situation of poverty across households and time periods: the multinomial logit model, the sequential logit model, the quantile regression model, and the difference in difference model. Households are categorized based on their experiences into 5 groups, namely chronically poor, falling into poverty, re-entering into poverty, exiting from poverty and never poor households. Estimation results emphasize the effects of demographic and socioeconomic factors as well as unexpected events on the economic status of a household. It is found that remittances have positive impact on household’s economic status in that they are likely to lower the probability of falling into poverty or trapping in poverty while they tend to increase the probability of exiting from poverty. In addition, not only receiving a secondary source of household income can raise the probability of being a never poor household, but it also significantly increases household income per capita of the chronically poor and falling into poverty households. Public work programs are recommended as an important tool to relieve household financial burden and uncertainty and thus consequently increase a chance for households to escape from poverty.

Keywords: difference in difference, dynamic, multinomial logit model, panel data, poverty, quantile regression, remittance, sequential logit model, Thailand, transfer

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Authors: Subrata Sarkar

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The aerospace industry is experiencing a profound product development transformation driven by the powerful integration of digitalization and 3D printing technologies. This paper delves into the significant impact of this convergence on aerospace innovation, specifically focusing on developing jet pumps for fuel systems. This case study is a compelling example of the immense potential of these technologies. In response to the industry's increasing demand for lighter, more efficient, and customized components, the combined capabilities of digitalization and 3D printing are reshaping how we envision, design, and manufacture critical aircraft parts, offering a distinct paradigm in aerospace engineering. Consider the development of a jet pump for a fuel system, a task that presents unique and complex challenges. Despite its seemingly simple design, the jet pump's development is hindered by many demanding operating conditions. The qualification process for these pumps involves many analyses and tests, leading to substantial delays and increased costs in fuel system development. However, by harnessing the power of automated simulations and integrating legacy design, manufacturing, and test data through digitalization, we can optimize the jet pump's design and performance, thereby revolutionizing product development. Furthermore, 3D printing's ability to create intricate structures using various materials, from lightweight polymers to high-strength alloys, holds the promise of highly efficient and durable jet pumps. The combined impact of digitalization and 3D printing extends beyond design, as it also reduces material waste and advances sustainability goals, aligning with the industry's increasing commitment to environmental responsibility. In conclusion, the convergence of digitalization and 3D printing is not just a technological advancement but a gateway to a new era in aerospace product development, particularly in the design of jet pumps. This revolution promises to redefine how we create aerospace components, making them safer, more efficient, and environmentally responsible. As we stand at the forefront of this technological revolution, aerospace companies must embrace these technologies as a choice and a strategic imperative for those striving to lead in innovation and sustainability in the 21st century.

Keywords: jet pump, digitalization, 3D printing, aircraft fuel system.

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Authors: James Sinclair, Katy Soapi, Brad Carte

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The marine environment has continuously demonstrated to be a rich source of secondary metabolites and bioactive compounds that can address the many pharmaceutical problems facing mankind. The emergence of multidrug resistant pathogens has caused scientists to explore contemporary ways of combating these super bugs. A red-pigmented bacterial strain isolated from a marine alga collected in Fiji was identified to be Pseudoalteromonas rubra from 16s rRNA sequencing. This bacterial strain was cultured using a yeast-peptone media and incubated for five days. The ethyl acetate extract of this bacterium was subjected to chromatographic separation techniques such as vacuum liquid chromatography, flash chromatography, size exclusion chromatography and high-pressure liquid chromatography to yield the pure compound and a number of semi-pure fractions. The crude extract and subsequent purified fractions were analyzed by ultraviolet/visible spectroscopy and mass spectroscopy and was found to contain the compounds ivermectin, stenothricin, cyclo-L-pro-L-val, prodigiosin, mycophenolic acid, phenazine-1-carboxylic acid, eplerenone, staurosporine and pseudoalteromone A. The structure of the pure compound, pseudoalteromone A, was elucidated using NMR 1H, 13C, 1H-1H COSY, HSQC and HMBC spectroscopic data.

Keywords: Pseudoalteromonas rubra, Pseudoalteromone A, secondary metabolites, structure elucidation

Procedia PDF Downloads 195

Authors: Abdullah Faqihi, John Hedley

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Biosensors play a significant role in the healthcare sectors, scientific and technological progress. Developing electrodes that are easy to manufacture and deliver better electrochemical performance is advantageous for diagnostics and biosensing. They can be implemented extensively in various analytical tasks such as drug discovery, food safety, medical diagnostics, process controls, security and defence, in addition to environmental monitoring. Development of biosensors aims to create high-performance electrochemical electrodes for diagnostics and biosensing. A biosensor is a device that inspects the biological and chemical reactions generated by the biological sample. A biosensor carries out biological detection via a linked transducer and transmits the biological response into an electrical signal; stability, selectivity, and sensitivity are the dynamic and static characteristics that affect and dictate the quality and performance of biosensors. In this research, a developed experimental study for laser scribing technique for graphene oxide inside a vacuum chamber for processing of graphene oxide is presented. The processing of graphene oxide (GO) was achieved using the laser scribing technique. The effect of the laser scribing on the reduction of GO was investigated under two conditions: atmosphere and vacuum. GO solvent was coated onto a LightScribe DVD. The laser scribing technique was applied to reduce GO layers to generate rGO. The micro-details for the morphological structures of rGO and GO were visualised using scanning electron microscopy (SEM) and Raman spectroscopy so that they could be examined. The first electrode was a traditional graphene-based electrode model, made under normal atmospheric conditions, whereas the second model was a developed graphene electrode fabricated under a vacuum state using a vacuum chamber. The purpose was to control the vacuum conditions, such as the air pressure and the temperature during the fabrication process. The parameters to be assessed include the layer thickness and the continuous environment. Results presented show high accuracy and repeatability achieving low cost productivity.

Keywords: laser scribing, lightscribe DVD, graphene oxide, scanning electron microscopy

Procedia PDF Downloads 100

Authors: Barbara Polo Martin

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During the 18th century, the border between Spain and France underwent various changes, primarily due to territorial agreements, wars, and treaties between the two nations and other European powers. For studying these changes, the Cassini maps remain valuable historical documents, offering a glimpse into the landscape and geography of 18th-century France and its neighboring regions, including the border between Spain and France. However, it's essential to recognize that these maps may not reflect modern political boundaries or territorial changes that have occurred since their creation. The project was initiated by King Louis XV in 1744 and continued by his successor, Louis XVI. The primary objective was to produce accurate maps of France, which would serve various purposes, including military, administrative, and scientific. The Cassini maps were groundbreaking for their time, as they were among the earliest attempts to create topographic maps on a national scale. They covered the entirety of France and were based on meticulous surveying and cartographic techniques. The maps featured precise geographic details, including elevation contours, rivers, roads, forests, and settlements. This study aims to analyze this rich and unknown cartography of France, study the rich place names it offers, as well as the accuracy of delimitations created over time between both empires in a historical way but also through a Geographical Information System. This study will offer a deeper knowledge about the cartography that supposes the beginning of topography in Europe.

Keywords: cartography, engineering, borders, Spain, France, Cassini

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Authors: Dewi Juliah Ratnaningsih, Imas Sukaesih Sitanggang

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Classification is one of data mining techniques that aims to discover a model from training data that distinguishes records into the appropriate category or class. Data mining classification methods can be applied in education, for example, to determine the classification of non-active students in Indonesia Open University. This paper presents a comparison of three methods of classification: Naïve Bayes, Bagging, and C.45. The criteria used to evaluate the performance of three methods of classification are stratified cross-validation, confusion matrix, the value of the area under the ROC Curve (AUC), Recall, Precision, and F-measure. The data used for this paper are from the non-active Indonesia Open University students in registration period of 2004.1 to 2012.2. Target analysis requires that non-active students were divided into 3 groups: C1, C2, and C3. Data analyzed are as many as 4173 students. Results of the study show: (1) Bagging method gave a high degree of classification accuracy than Naïve Bayes and C.45, (2) the Bagging classification accuracy rate is 82.99 %, while the Naïve Bayes and C.45 are 80.04 % and 82.74 % respectively, (3) the result of Bagging classification tree method has a large number of nodes, so it is quite difficult in decision making, (4) classification of non-active Indonesia Open University student characteristics uses algorithms C.45, (5) based on the algorithm C.45, there are 5 interesting rules which can describe the characteristics of non-active Indonesia Open University students.

Keywords: comparative analysis, data mining, clasiffication, Bagging, Naïve Bayes, C.45, non-active students, Indonesia Open University

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Authors: Iqra Yaseen

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One of the well-known areas of computer science and engineering, image processing in the context of computer vision has been essential to automation. In remote sensing, medical science, and many other fields, it has made it easier to uncover previously undiscovered facts. Grading of diverse items is now possible because of neural network algorithms, categorization, and digital image processing. Its use in the classification of agricultural products, particularly in the grading of seeds or grains and their cultivars, is widely recognized. A grading and sorting system enables the preservation of time, consistency, and uniformity. Global population growth has led to an increase in demand for food staples, biofuel, and other agricultural products. To meet this demand, available resources must be used and managed more effectively. Image processing is rapidly growing in the field of agriculture. Many applications have been developed using this approach for crop identification and classification, land and disease detection and for measuring other parameters of crop. Vegetation localization is the base of performing these task. Vegetation helps to identify the area where the crop is present. The productivity of the agriculture industry can be increased via image processing that is based upon Unmanned Aerial Vehicle photography and satellite. In this paper we use the machine learning techniques like Convolutional Neural Network, deep learning, image processing, classification, You Only Live Once to UAV imaging dataset to divide the crop into distinct groups and choose the best way to use it.

Keywords: image processing, UAV, YOLO, CNN, deep learning, classification

Procedia PDF Downloads 90

Authors: S. Belakry, D. Fasquelle, A. Rolle, E. Capoen, R. N. Vannier, J. C. Carru

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Solid oxide fuel cells (SOFCs) are promising devices for energy conversion due to their high electrical efficiency and eco-friendly behavior. Their performance is not only influenced by the microstructural and electrical properties of the electrodes and electrolyte but also depends on the interactions at the interfaces. Nowadays, commercial SOFCs are electrically efficient at high operating temperatures, typically between 800 and 1000 °C, which restricts their real-life applications. The present work deals with the objectives to reduce the operating temperature and to develop cost-effective intermediate-temperature solid oxide fuel cells (IT-SOFCs). This work focuses on the development of metal-supported solid oxide fuel cells (MS-IT-SOFCs) that would provide cheaper SOFC cells with increased lifetime and reduced operating temperature. In the framework, the local company TIBTECH brings its skills for the manufacturing of porous metal supports. This part of the work focuses on the physical, chemical, and electrical characterizations of porous metallic supports (stainless steel 316 L and FeCrAl alloy) under different exposure conditions of temperature and atmosphere by studying oxidation, mechanical resistance, and electrical conductivity of the materials. Within the target operating temperature (i.e., 500 to 700 ° C), the stainless steel 316 L and FeCrAl alloy slightly oxidize in the air and H2, but don’t deform; whereas under Ar atmosphere, they oxidize more than with previously mentioned atmospheres. Above 700 °C under air and Ar, the two metallic supports undergo high oxidation. From 500 to 700 °C, the resistivity of FeCrAl increases by 55%. But nevertheless, the FeCrAl resistivity increases more slowly than the stainless steel 316L resistivity. This study allows us to verify the compatibility of electrodes and electrolyte materials with metallic support at the operating requirements of the IT-SOFC cell. The characterizations made in this context will also allow us to choose the most suitable fabrication process for all functional layers in order to limit the oxidation of the metallic supports.

Keywords: stainless steel 316L, FeCrAl alloy, solid oxide fuel cells, porous metallic support

Procedia PDF Downloads 79

Authors: Zeliha Ustun, Mustafa Ersoz

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In the study, a traditional herbal supplement black cumin seed (Nigella sativa) oil properties has been studied to protect the main quality parameters by a new supplement application. Black cumin seed and its oil is used as a dietary supplement and preferred traditional remedy in Africa, Asia and Middle East for centuries. Now it has been consuming by millions of people in America and Europe as natural supplements and/or phytotherapeutic agents to support immune system, asthma, allergic rinnitis etc. by the scientists’ advices. With the study, it is aimed to prove that soft gelatin capsules are a new and more practical way of usage for Nigella sativa oil that has a longer stability. With the study soft gelatin capsules formulation has been developed to protect cold pressed black cumin seed oil physicochemical properties for a longer period. The product design has been developed in laboratory and implemented in pilot scale soft gelatin capsule manufacturing. Physicochemical properties (peroxide value, free fatty acids, fatty acid composition, refractive index, iodine value, saponification value, unsaponifiable matters) of Nigella sativa oil soft gelatin capsules and Nigella sativa oil in liquid form in amber glass bottles have been compared and followed for 8 months. The main parameters for capsules and liquid form found that for free fatty acids 2.29±0.03, 3.92±0.11 % oleic acid, peroxide 23.11±1.18, 27.85±2.50 meqO2/kg, refractive index at 20 0C 1.4738±0.00, 1.4737±0.00, soap 0 ppm, moisture and volatility 0.32±0.01, 0.36±0.01 %, iodine value 123.00±0.00, 122.00±0.00 wijs, saponification value 196.25±0.46, 194.13±0.35 mg KOH/g and unsaponifiable matter 7.72±0.13, 6.88±0.36 g/kg respectively. The main fatty acids are found that linoleic acid 56.17%, oleic acid 24.64%, palmitic acid 11,94 %. As a result, it is found that cold pressed Nigella sativa oil soft gelatin capsules physicochemical properties are more stable than the Nigella sativa oil stored in glass bottles.

Keywords: black cumin seed (Nigella sativa) oil, cold press, nutritional supplements, soft gelatin capsule

Procedia PDF Downloads 360

Authors: Jiang Zhenbo, Ishikura Ryohei, Yasufuku Noriyuki

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Improvement of soft clay deposits by the combination of surface stabilization and floating type cement-treated columns is one of the most popular techniques worldwide. On the basis of one dimensional consolidation model, a time-dependent skin friction model for the column-soil interaction is proposed. The nonlinear relationship between column shaft shear stresses and effective vertical pressure of the surrounding soil can be described in this model. The influence of column-soil surface roughness can be represented using a roughness coefficient R, which plays an important role in the design of column length. Based on the homogenization method, a part of floating type improved ground will be treated as an unimproved portion, which with a length of αH1 is defined as a time-dependent equivalent skin friction length. The compression settlement of this unimproved portion can be predicted only using the soft clay parameters. Apart from calculating the settlement of this composited ground, the load transfer mechanism is discussed utilizing model tests. The proposed model is validated by comparing with calculations and laboratory results of model and ring shear tests, which indicate the suitability and accuracy of the solutions in this paper.

Keywords: floating type improved foundation, time-dependent skin friction, roughness, consolidation

Procedia PDF Downloads 455

Authors: Ava Zarif Sanayei, Sedigheh Sina

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Interventional radiology (IR) uses imaging guidance, including X-rays and CT scans, to deliver therapy precisely. Most IR procedures are performed under local anesthesia and start with a small needle being inserted through the skin, which may be called pinhole surgery or image-guided surgery. There is increasing concern about radiation exposure during interventional radiology procedures due to procedure complexity. The basic aim of optimizing radiation protection as outlined in ICRP 139, is to strike a balance between image quality and radiation dose while maximizing benefits, ensuring that diagnostic interpretation is satisfactory. This study aims to estimate the equivalent doses to the main trunk of the body for the Interventional radiologist and Superintendent using LiF: Mg, Ti (TLD-100) chips at the IR department of a hospital in Shiraz, Iran. In the initial stage, the dosimeters were calibrated with the use of various phantoms. Afterward, a group of dosimeters was prepared, following which they were used for three months. To measure the personal equivalent dose to the body, three TLD chips were put in a tissue-equivalent batch and used under a protective lead apron. After the completion of the duration, TLDs were read out by a TLD reader. The results revealed that these individuals received equivalent doses of 387.39 and 145.11 µSv, respectively. The findings of this investigation revealed that the total radiation exposure to the staff was less than the annual limit of occupational exposure. However, it's imperative to implement appropriate radiation protection measures. Although the dose received by the interventional radiologist is a bit noticeable, it may be due to the reason for using conventional equipment with over-couch x-ray tubes for interventional procedures. It is therefore important to use dedicated equipment and protective means such as glasses and screens whenever compatible with the intervention when they are available or have them fitted to equipment if they are not present. Based on the results, the placement of staff in an appropriate location led to increasing the dose to the radiologist. Manufacturing and installation of moveable lead curtains with a thickness of 0.25 millimeters can effectively minimize the radiation dose to the body. Providing adequate training on radiation safety principles, particularly for technologists, can be an optimal approach to further decreasing exposure.

Keywords: interventional radiology, personal monitoring, radiation protection, thermoluminescence dosimetry

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Authors: Jeremy Schultz

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The purpose of this study was to understand the perceptions of vineyard managers in the Krasnodar Region of Southern Russia located between the city of Kransnodar and the Black Sea. In recent years, wine tourism throughout the region has seen tremendous growth due in part to the concurrent growth in the number of tourists vacationing at the Black Sea. This trend has contributed to the development of large-scale wine operations developing in numerous rural locations along the tourists’ travel path. Niche areas of tourism, such as wine tourism, have proven to provide economic viability for rural communities all around the world. Understanding their shared group characteristics while honoring their unique qualities as individuals aids in responsible wine tourism development that provides a sense of well-being for the communities and stakeholders involved. Semi-structured interviews and lived experience methodologies were used in locations that were associated with wine food tourism operations. By understanding management perspectives, it lends insight into sustainable destination management and wine tourism product development, furthering our progress toward ethical, responsible, and financially feasible operations. This research also represents a collaborative effort between Russia and the United States that supports an agenda of sustainable destination development and management. As a global community, we need to continue to investigate stakeholder perceptions and strategic management techniques that best support the pillars upon which responsible tourism was founded.

Keywords: wine tourism, tourism development, Russia, rural tourism

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Authors: G. S. Thyagaraju, U. P. Kulkarni

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Context-aware computing refers to a general class of computing systems that can sense their physical environment, and adapt their behaviour accordingly. Context aware computing makes systems aware of situations of interest, enhances services to users, automates systems and personalizes applications. Context-aware services have been introduced into mobile devices, such as PDA and mobile phones. In this paper we are presenting a novel approaches used to realize the context aware mobile. The context aware mobile phone (CAMP) proposed in this paper senses the users situation automatically and provides user context required services. The proposed system is developed by using artificial intelligence techniques like Bayesian Network, fuzzy logic and rough sets theory based decision table. Bayesian Network to classify the incoming call (high priority call, low priority call and unknown calls), fuzzy linguistic variables and membership degrees to define the context situations, the decision table based rules for service recommendation. To exemplify and demonstrate the effectiveness of the proposed methods, the context aware mobile phone is tested for college campus scenario including different locations like library, class room, meeting room, administrative building and college canteen.

Keywords: context aware mobile, fuzzy logic, decision table, Bayesian probability

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Authors: Sara Jelodarian

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Organic agriculture is a kind of living and dynamic agriculture that was introduced in the early 20^th century. The fundamental basis for organic agriculture is in harmony with nature. This version of farming emphasizes removing growth hormones, chemical fertilizers, toxins, radiation, genetic manipulation and instead, integration of modern scientific techniques (such as biologic and microbial control) that leads to the production of healthy food and the preservation of the environment and use of agricultural products such as forage and manure. Supports from governments for the markets producing organic products and taking advantage of the experiences from other successful societies in this field can help progress the positive and effective aspects of this technology, especially in developing countries. This research proves that till 2030, 25% of the global agricultural lands would be covered by organic farming. Consequently Iran, due to its rich genetic resources and various climates, can be a pioneer in promoting organic products. In addition, for sustainable farming, blend of organic and other innovative systems is needed. Important limitations exist to accept these systems, also a diversity of policy instruments will be required to comfort their development and implementation. The paper was conducted to results of compilation of reports, issues, books, articles related to the subject with library studies and research. Likewise we combined experimental and survey to get data.

Keywords: develop, production markets, progress, strategic role, technology

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Authors: Maryam Kiani

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This study focuses on the development of composite nanomaterials based on SiO₂ and carbon black for oxygen reduction reaction (ORR) electrocatalysts in batteries and fuel cells. The aim was to explore the potential of these composite materials as efficient catalysts for ORR, which is a critical process in energy conversion devices. The SiO₂/carbon black composite nanomaterials were synthesized using a facile and scalable method. The morphology, structure, and electrochemical properties of the materials were characterized using various techniques including scanning electron microscopy (SEM), X-ray diffraction (XRD), and electrochemical measurements. The results demonstrated that the incorporation of SiO₂ into the carbon black matrix enhanced the ORR performance of the composite material. The composite nanomaterials exhibited improved electrocatalytic activity, enhanced stability, and increased durability compared to pure carbon black. The presence of SiO₂ facilitated the formation of active sites, improved electron transfer, and increased the surface area available for ORR. This study contributes to the advancement of battery and fuel cell technology by offering a promising approach for the development of high-performance ORR electrocatalysts. The SiO₂/carbon black composite nanomaterials show great potential for improving the efficiency and durability of energy conversion devices, leading to more sustainable and efficient energy solutions.

Keywords: ORR, fuel cells, batteries, electrocatalyst

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Authors: M. Ahmadi, M. Kafil, H. Ebrahimi

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Nowadays, induction motors have a significant role in industries. Condition monitoring (CM) of this equipment has gained a remarkable importance during recent years due to huge production losses, substantial imposed costs and increases in vulnerability, risk, and uncertainty levels. Motor current signature analysis (MCSA) is one of the most important techniques in CM. This method can be used for rotor broken bars detection. Signal processing methods such as Fast Fourier transformation (FFT), Wavelet transformation and Empirical Mode Decomposition (EMD) are used for analyzing MCSA output data. In this study, these signal processing methods are used for broken bar problem detection of Mobarakeh steel company induction motors. Based on wavelet transformation method, an index for fault detection, CF, is introduced which is the variation of maximum to the mean of wavelet transformation coefficients. We find that, in the broken bar condition, the amount of CF factor is greater than the healthy condition. Based on EMD method, the energy of intrinsic mode functions (IMF) is calculated and finds that when motor bars become broken the energy of IMFs increases.

Keywords: broken bar, condition monitoring, diagnostics, empirical mode decomposition, fourier transform, wavelet transform

Procedia PDF Downloads 139

Authors: Mariya Salihu Ingawa, Sani Suleiman Isah

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The assessment of Integrated Information System (IIS) in organisation is an important initiative to enable the Information System (IS) managers, as well as top management to understand the success status of their investment in IS integration efforts. However, without a proper assessment, an organisation will not know its IIS status, which may affect their judgment on what action should be taken onwards. Current research on IIS assessment is lacking and those related literature on IIS assessment focus more on assessing the technical aspect of IIS. It is argued that assessing technical aspect alone is inadequate since organisational and strategic aspects in IIS should also be considered. Current methods, techniques and tools used by vendors for IIS assessment also are lack of comprehensive measures to fully assess the Integrated Information System in term of technical, organisational and strategic domains. The purpose of this study is to establish critical success factors for measuring success of an Integrated Information System. These factors are used as the basis for constructing an approach to comprehensively assess IIS in an organisation. A comprehensive list of success factors for IIS assessment, established from literature, was initially presented. An expert surveys using both manual and online methods were conducted to verify the factors. Based on the factors, an instrument for IIS assessment was constructed. The results from a case study indicate that through comprehensive assessment approach, not only the level of success been known, but also reveals the contributing factors. This research contributes to the field of Information Systems specifically in the area of Integrated Information System assessment.

Keywords: integrated information system, expert surveys, organisation, assessment

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Authors: Anyeres N. Atehortua Jimenez, J. David Lambraño, Juan Carlos Muñoz

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Navier-Stokes equations (NSE), which describe the dynamics of a fluid, have an important application on modeling waves used for data inversion techniques as full waveform inversion (FWI). In this work a linearized version of NSE and its variables, neglecting deviatoric terms of stress tensor, is presented. In order to get a theoretical modeling of pressure p(x,t) and wave velocity profile c(x,t), a wave equation of visco-acoustic medium (VAE) is written. A change of variables p(x,t)=q(x,t)h(ρ), is made on the equation for the VAE leading to a well known Klein-Gordon equation (KGE) describing waves propagating in variable density medium (ρ) with dispersive term α^2(x). KGE is reduced to a Poisson equation and solved by proposing a specific function for α^2(x) accounting for the energy dissipation and dispersion. Finally, an integral form solution is derived for p(x,t), c(x,t) and kinematics variables like particle velocity v(x,t), displacement u(x,t) and bulk modulus function k_b(x,t). Further, it is compared this visco-acoustic formulation with another form broadly used in the geophysics; it is argued that this formalism is more general and, given its integral form, it may offer several advantages from the modern parallel computing point of view. Applications to minimize the errors in modeling for FWI applied to oils resources in geophysics are discussed.

Keywords: Navier-Stokes equations, modeling, visco-acoustic, inversion FWI

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Authors: M. Sunitha, B. Nithyavani, Mathew Yohannan, S. Thiruvieni Balajji, M. A. Rathi, C. Arul Raj, P. Ragavendran, V. K. Gopalkrishnan

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Establishment of an early and reliable biomarker for ovarian carcinogenesis whose expression can be monitored through noninvasive techniques will enable early diagnosis of cancer. Carbonic anhydrases (CA) isozymes IX and XII have been suggested to play a role in oncogenic processes. In von Hippel-Lindau (VHL)-defective tumors, the cell surface transmembrane carbonic anhydrase (CA) CA XI and CA XII genes are overexpressed because of the absence of pVHL. These enzymes are involved in causing a hypoxia condition, thereby providing an environment for metastasis. Aberrant expression of the facilitative glucose transporter GLUT I is found in a wide spectrum of epithelial malignancies. Studying the mRNA expression of CA IX, CA XII and Glut I isozymes in ovarian cancer cell lines (OAW-42 and PA-1) revealed the expression of these hypoxia genes. Immunohistochemical staining of carbonic anhydrases was also performed in 40 ovarian cancer tissues. CA IX and CA XII were expressed at 540 bp and 520 bp in OAW42, PA1 in ovarian cancer cell lines. GLUT-1 was expressed at 325bp in OAW 42, PA1 genes in ovarian cancer cell lines. Immunohistochemistry revealed high to moderate levels of expression of these enzymes. The immuostaining was seen predominantly on the cell surface membrane. The study concluded that these genes CA IX, CA XII and Glut I are expressed under hypoxic condition in tumor cells. From the present results expression of CA IX, XII and Glut I may represent potential targets in ovarian cancer therapy.

Keywords: ovarian cancer, carbonic anhydrase IX, XII, Glut I, tumor markers

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Authors: Kittipong Tripetch, Nobuhiko Nakano

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This paper proposes one stage and two stage CMOS Complementary Regulated Cascode Distributed Amplifier (CRCDA) design based on Inductive and Transformer coupling techniques. Usually, Distributed amplifier is based on inductor coupling between gate and gate of MOSFET and between drain and drain of MOSFET. But this paper propose some new idea, by coupling with differential primary windings of transformer between gate and gate of MOSFET first stage and second stage of regulated cascade amplifier and by coupling with differential secondary windings transformer of MOSFET between drain and drain of MOSFET first stage and second stage of regulated cascade amplifier. This paper also proposes polynomial modeling of Silicon Transformer passive equivalent circuit from Nanyang Technological University which is used to extract frequency response of transformer. Cadence simulation results are used to verify validity of transformer polynomial modeling which can be used to design distributed amplifier without Cadence. 4 parameters of scattering matrix of 2 port of the propose circuit is derived as a function of 4 parameters of impedance matrix.

Keywords: CMOS regulated cascode distributed amplifier, silicon transformer modeling with polynomial, low power consumption, distribute amplification technique

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Authors: Ahmed Azizeldein Abubaker Abdelhafez

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This review explores the application of biochar as a strategy for enhancing soil fertility in arid regions, with a focus on Arab countries. Biochar, derived from the carbonization of biomass under low-oxygen conditions, has shown promise in improving the physical and chemical properties of soil, such as increasing water retention and nutrient availability. Despite the challenging conditions of arid and semi-arid regions, characterized by poor soil fertility and severe land degradation, biochar application has emerged as a viable method to enhance agricultural productivity and mitigate environmental issues. This paper examines various aspects of biochar, including production methods, such as pyrolysis and gasification, and the effects of biochar on soil fertility. It discusses different application techniques and presents case studies from Arab countries like Egypt, the United Arab Emirates, Saudi Arabia, Qatar, Oman, and Kuwait, highlighting the successes and challenges faced in implementing biochar technology. The review also addresses the limitations of biochar use in arid regions and suggests future research directions to optimize its effectiveness. Overall, this study underscores the potential of biochar to contribute significantly to sustainable agriculture and ecological restoration in arid environments, advocating for integrated strategies that combine biochar application with other innovative agricultural practices.

Keywords: biochar, soil fertility, arid region, Arab countries, challenges and limitations

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Authors: Syed Atif Hassan, Luv Mehta, Syed Asif Hassan

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Hit song science is a field of investigation wherein machine learning techniques are applied to music tracks in order to extract such features from audio signals which can capture information that could explain the popularity of respective tracks. Record companies invest huge amounts of money into recruiting fresh talents and churning out new music each year. Gaining insight into the basis of why a song becomes popular will result in tremendous benefits for the music industry. This paper aims to extract basic musical and more advanced, acoustic features from songs while also taking into account external factors that play a role in making a particular song popular. We use a dataset derived from popular Spotify playlists divided by genre. We use ten genres (blues, classical, country, disco, hip-hop, jazz, metal, pop, reggae, rock), chosen on the basis of clear to ambiguous delineation in the typical sound of their genres. We feed these features into three different classifiers, namely, SVM with RBF kernel, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model at the end. Predicting song popularity is particularly important for the music industry as it would allow record companies to produce better content for the masses resulting in a more competitive market.

Keywords: classifier, machine learning, music tracks, popularity, prediction

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Authors: Ken Hampshire, Thomas Mazzuchi, Shahram Sarkani

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As a subset of metaheuristics, nature-inspired optimization algorithms such as particle swarm optimization (PSO) have shown promise both in solving intractable problems and in their extensibility to novel problem formulations due to their general approach requiring few assumptions. Unfortunately, single instantiations of algorithms require detailed tuning of parameters and cannot be proven to be best suited to a particular illustrative problem on account of the “no free lunch” (NFL) theorem. Using these algorithms in real-world problems requires exquisite knowledge of the many techniques and is not conducive to reconciling the various approaches to given classes of problems. This research aims to present a unified view of PSO-based approaches from the perspective of relevant systems engineering problems, with the express purpose of then eliciting the best solution for any problem formulation in an ensemble learning bucket of models approach. The central hypothesis of the research is that extending the PSO algorithms found in the literature to real-world optimization problems requires a general ensemble-based method for all problem formulations but a specific implementation and solution for any instance. The main results are a problem-based literature survey and a general method to find more globally optimal solutions for any systems engineering optimization problem.

Keywords: particle swarm optimization, nature-inspired optimization, metaheuristics, systems engineering, ensemble learning

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Authors: Lamiaa Shehata

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The current (COVID-19) pandemic is one of the international crises, and a lot of efforts have been directed toward the improvement of efficient vaccines, however vaccine hesitancy is one of the universal menaces that make the fulfillment of society immunity very hard. The World Health Organization acknowledges vaccine hesitancy as the society’s maximum risk to people's health protection, especially in little and moderate-revenue nations. Social media is strong in observing audience behaviors and evaluating the circulation, which would supply useful data for strategy makers. It has a significant function in spreading facts during the pandemic, it could assist to boost protective manners. The objective of this study is to determine the effects of social media exposure on vaccine hesitancy. Data were collected using a survey in a form of a structured questionnaire conducted during December 2021- January 2022 using convenient sampling techniques (680) in Egypt and the United Arab Emirates. The results revealed that there was a significant relationship between the high exposure to social media and the refusal of the Covid19 vaccine also, the percentage of the refusal of the vaccine is higher in Egypt, however, UAE forced people to take the vaccine. Furthermore, public attitudes toward COVID-19 vaccination vary from gender and region. In conclusion, policymakers must adjust their policies through the use of social media to immediate actions to vaccine-related news to support vaccination approval.

Keywords: COVID-19, hesitancy, social media, vaccine

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Authors: Ronal Muresano, Andrea Pagano

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Nowadays, the mathematical/statistical applications are developed with more complexity and accuracy. However, these precisions and complexities have brought as result that applications need more computational power in order to be executed faster. In this sense, the multicore environments are playing an important role to improve and to optimize the execution time of these applications. These environments allow us the inclusion of more parallelism inside the node. However, to take advantage of this parallelism is not an easy task, because we have to deal with some problems such as: cores communications, data locality, memory sizes (cache and RAM), synchronizations, data dependencies on the model, etc. These issues are becoming more important when we wish to improve the application’s performance and scalability. Hence, this paper describes an optimization method developed for Systemic Model of Banking Originated Losses (SYMBOL) tool developed by the European Commission, which is based on analyzing the application's weakness in order to exploit the advantages of the multicore. All these improvements are done in an automatic and transparent manner with the aim of improving the performance metrics of our tool. Finally, experimental evaluations show the effectiveness of our new optimized version, in which we have achieved a considerable improvement on the execution time. The time has been reduced around 96% for the best case tested, between the original serial version and the automatic parallel version.

Keywords: algorithm optimization, bank failures, OpenMP, parallel techniques, statistical tool

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Authors: Rana Sawaya, Jalal Halwani, Isam Bashour, Nada Nehme

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Mismanagement of municipal solid wastes in Lebanon might lead to serious environmental problems, especially that a big portion of mixed wastes including putrescible is transferred to Naameh landfill. One of the consequences of municipal solid waste deposition is the production of landfill leachate, which if unproperly treated will threaten the main crucial matrices such as soil, water, and air. The main aim of this one of a kind study is to assess the risk posed to groundwater as a result of leachate infiltration on off-site wells especially after stoppage of Naameh landfill's operation end of the year 2016 and initiation of the capping process which is still ongoing and will be finalized in December 2019. For this purpose, nine representative points around the landfill were selected to undergo physicochemical and microbial analysis on a seasonal basis (every three months). The study extended from the year 2014 until the end of the year 2016 (closure of Naameh landfill). The preliminary data obtained are statistically analyzed using the Statistical Package for Social Sciences (SPSS) and was found in conformity with international and Lebanese norms. Thus, the study will be extended an additional year, especially after the finalization of capping and the results obtained, will enable us to propose new techniques and tools (treatment systems) in water resources management depending on the direction of its usage (domestic, irrigation, drinking).

Keywords: contamination, groundwater, leachate, Lebanon, solid waste

Procedia PDF Downloads 117

Authors: Kanwal Javid, Shazia Pervaiz, Maria Mumtaz, Muhammad Ameer Nawaz Akram

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Forests and grasslands ecosystems play an important role in the global carbon cycle. Land management activities influence both ecosystems and enable them to absorb and sequester carbon dioxide (CO2). Similarly, in Pakistan, these terrestrial ecosystems are well known to mitigate carbon emissions and have a great source to supply a variety of services such as clean air and water, biodiversity, wood products, wildlife habitat, food, recreation and carbon sequestration. Carbon sequestration is the main agenda of developed and developing nations to reduce the impacts of global warming. But the amount of carbon storage within these ecosystems can be affected by many factors related to air quality such as land management, land-use change, deforestation, over grazing and natural calamities. Moreover, the long-term capacity of forests and grasslands to absorb and sequester CO2 depends on their health, productivity, resilience and ability to adapt to changing conditions. Thus, the main rationale of this study is to monitor the difference in carbon amount of forests and grasslands of Northern Pakistan using MODIS data sets and map results using Geographic Information System. Results of the study conclude that forests ecosystems are more effective in reducing the CO2 level and play a key role in improving the quality of air.

Keywords: carbon sequestration, grasslands, global warming, climate change.

Procedia PDF Downloads 173