Search results for: algorithm techniques

Authors: Yessenia Parrado, Ana Barbosa, Daniela Mahe, Sebastian Toro, Jhon Garcia

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Public innovation has gained strength in recent years in response to the need to find new strategies or mechanisms to interact between government entities and citizens. In this way, the Colombian government has been promoting policies aimed at strengthening innovation as a fundamental aspect in the work of public entities. However, in order to potentiate the capacities of public servants and therefore of the institutions and organizations to which they belong, it is necessary to be able to understand the context under which they operate in their daily work. This article aims to compile the work developed by the laboratory of innovation, creativity, and new technologies LAB101 of the National University of Colombia for the National Department of Planning. A case study was developed in the central region of Colombia made up of five departments, through the construction of instruments based on quantitative techniques in response to the item combined with qualitative analysis through semi-structured interviews to understand the perception of possible barriers to innovation and the obstacles that have prevented the acceleration of transformation within public organizations. From the information collected, different analyzes are carried out that allows a more robust explanation to be given to the results obtained, and a set of categories are established to group different characteristics associated with possible difficulties that officials perceive to innovate and that are later conceived as barriers. Finally, a proposal for an indicator was built to measure the degree of innovation within public entities in order to be able to carry a metric in future opportunities. The main findings of this study show three key components to be strengthened in public entities and organizations: governance, knowledge management, and the promotion of collaborative workspaces.

Keywords: barriers, enablers, management, public innovation

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Authors: Usman Jilani, Ibad Khurram, Irshad Hussain

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Environmentally sustainable waste management is a challenging task as it involves multiple and diverse economic, environmental, technical and regulatory issues. Municipal Solid Waste Management (MSWM) is more challenging in developing countries like Pakistan due to lack of awareness, technology and human resources, insufficient funding, inefficient collection and transport mechanism resulting in the lack of a comprehensive waste management system. This work presents an overview of current MSWM practices in Peshawar, the provincial capital of Khyber Pakhtunkhwa, Pakistan and proposes a better and sustainable integrated solid waste management system with incineration (Waste to Energy) option. The diverted waste would otherwise generate revenue; minimize land fill requirement and negative impact on the environment. The proposed optimized solution utilizing scientific techniques (like mathematical modeling, optimization algorithms and GIS) as decision support tools enhances the technical & institutional efficiency leading towards a more sustainable waste management system through incorporating: - Improved collection mechanisms through optimized transportation / routing and, - Resource recovery through incineration and selection of most feasible sites for transfer stations, landfills and incineration plant. These proposed methods shift the linear waste management system towards a cyclic system and can also be used as a decision support tool by the WSSP (Water and Sanitation Services Peshawar), agency responsible for the MSWM in Peshawar.

Keywords: municipal solid waste management, incineration, mathematical modeling, optimization, GIS, Peshawar

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Authors: Noraziah Nordin, Najihah Mohd Hashim, Nazia Abdul Majid, Mashitoh Abdul Rahman, Hamed Karimian, Hapipah Mohd Ali

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Enicosanthellum pulchrum belongs to family Annonaceae is also known as family of 'mempisang' in Malaysia. Liriodenine was isolated by prep-HPLC method. This method was first technique used for the isolation of this compound. The structure of the liriodenine was elucidated by 1D and 2D spectroscopy techniques. Liriodenine was tested on ovarian cancer cells line (CAOV-3) for MTT, AO/PI and cytotoxicity 3 assays. The MTT assay was performed to determine the cytotoxicity effect of lirodenine on CAOV-3 cells. The morphological changes on CAOV-3 cells were observed by AO/PI assay for the early and late stage of apoptosis, as well as necrosis. Meanwhile, the measurement of cell loss, nuclear morphology, DNA content, cell membrane permeability, mitochondrial membrane potential changes and cytochrome c release from mitochondria were detected through cytotoxicity 3 assay. The IC50 results showed liriodenine inhibits the growth of CAOV-3 cells after 24 h of treatment at 10.25 ± 1.06 µg/mL. After 48 and 72 h of treatments, the IC50 values were decreased to 7.65 ± 0:07 and 6.35 ± 1.62 µg/mL, respectively. The morphology changes can be seen on CAOV-3 with a production of cell membrane blebbing, cromatin condensation and apoptotic bodies with increasing time of treatment from 24 to 72 h. Evaluation of cytotoxicity 3 on CAOV-3 cells after treated with liriodenine, resulting loss of mitochondrial membrane potential and release of cytochrome c from mitochondria. The results demonstrated the capability of liriodenine as a promising anticancer agent, particularly on human ovarian cancer.

Keywords: Enicosanthellum pulchrum, ovarian cancer, apoptosis, cytotoxicity

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Authors: Banu Hatice Gürcüm, Pınar Arslan, Mahmut Yalçın

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From the oldest production methods with yarns used to weave, knit, braid and knot to the newest production methods with fibres used to stitch, bond or structures of innovative technologies, laminates, nanoparticles, composites or 3D printing systems, textile industry advanced through materials, processes and context mostly within the last five decades. The creative momentum of fabric like 3D printed structures have come to the point of transforming as for the newest form of textile applications. Moreover, pioneering studies on the applications of 3D Printing Technology and Additive Manufacturing have been focusing on fashion and apparel sector from the last two decades beginning with fashion designers. After the advent of chain-mail like structures and flexible micro or meso structures created by SLS rapid manufacturing a more textile-like behavior is achieved. Thus, the primary aim of this paper is to discuss the most important properties of traditional fabrics that are to be expected of future fabrics. For this reason, this study deals primarily with the physical properties like softness, hand, flexibility, drapability and wearability of 3D Printed structures necessary to identify the possible ways in which it can be used instead of contemporary textile structures, namely knitted and woven fabrics. The aim of this study is to compare the physical properties of 3D printed fabrics regarding different rapid manufacturing methods (FDM and SLS). The implemented method was Material Driven Design (MDD), which comprise the use of innovative materials according to the production techniques such as 3D printing system. As a result, advanced textile processes and materials enable to the creation of new types of fabric structures and rapid solutions in the field of textiles and 3D fabrics on the other hand, are to be used in this regard.

Keywords: 3D printing technology, FDM, SLS, textile structure

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Authors: Gal Belsitzman, Rose Stamp, Atay Citron, Wendy Sandler

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Sign languages are considered endangered. The vitality of sign languages is compromised by its unique sociolinguistic situation, in which hearing parents that give birth to deaf children usually decide to cochlear implant their child. Therefore, these children don’t acquire their natural language – Sign Language. Despite this, many sign languages, such as Israeli Sign Language (ISL) are thriving. The continued survival of similar languages under threat has been associated with the remarkable resilience of the language community. In particular, deaf literary traditions are central in reminding the community of the importance of the language. One example of a deaf literary tradition which has received increased popularity in recent years is deaf theatre. The Ebisu Sign Language Theatre Laboratory, developed as part of the multidisciplinary Grammar of the Body Research Project, is the first deaf theatre company in Israel. Ebisu Theatre combines physical theatre and sign language research, to allow for a natural laboratory to analyze the creative use of the body. In this presentation, we focus on the recent theatre production called ‘Their language’ which tells of the struggle faced by the deaf community to use their own natural language in the education system. A thorough analysis unravels how linguistic properties are integrated with the use of poetic devices and physical theatre techniques in this performance, enabling wider access by both deaf and hearing audiences, without interpretation. Interviews with the audience illustrate the significance of this art form which serves a dual purpose, both as empowering for the deaf community and educational for the hearing and deaf audiences, by raising awareness of community-related issues.

Keywords: deaf theatre, empowerment, language revitalization, sign language

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Authors: Khalid Bashir, Hammad Zahid

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Most of the investors consider that economic and financial information is the most important at the time of making investment decisions. But it is not true, as in the past two decades, the Behavioral aspects and the behavioral biases have gained an important place in the decision-making process of an investor. This study is basically conducted on this fact. The purpose of this study is to examine the impact of behavioral factors on the decision-making of the individual real estate investor in Pakistan. Some important behavioral factors like overconfidence, anchoring, gambler’s fallacy, home bias, loss aversion, regret aversion, mental accounting, herding and representativeness are used in this study to find their impact on the psychology of individual investors. The targeted population is the real estate investor of Pakistan, and a sample of 650 investors is selected on the basis of convenience sampling technique. The data is collected through the questionnaire with a response rate of 46.15 %. Descriptive statistical techniques and SEM are used to analyze the data by using statistical software. The results revealed the fact that some behavioral factors have a significant impact on the decision-making of investors. Among all the behavioral biases, overconfidence, anchoring, gambler’s fallacy, loss aversion and representativeness have a significant positive impact on the decision-making of the individual investor, while the rest of biases like home bias, regret aversion, mental accounting, herding have less impact on the decision-making process of an individual.

Keywords: behavioral finance, anchoring, gambler’s fallacy, loss aversion

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Authors: V. G. Cappellesso, D. M. G. da Silva, J. A. Arndt, N. dos Santos Petry, A. B. Masuero, D. C. C. Dal Molin

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Concrete elements are subject to cracking, which can be an access point for deleterious agents that can trigger pathological manifestations reducing the service life of these structures. Finding ways to minimize or eliminate the effects of this aggressive agents’ penetration, such as the sealing of these cracks, is a manner of contributing to the durability of these structures. The cementitious self-healing phenomenon can be classified in two different processes. The autogenous self-healing that can be defined as a natural process in which the sealing of this cracks occurs without the stimulation of external agents, meaning, without different materials being added to the mixture, while on the other hand, the autonomous seal-healing phenomenon depends on the insertion of a specific engineered material added to the cement matrix in order to promote its recovery. This work aims to evaluate the autogenous self-healing of concretes produced with different water/cement ratios and exposed to wet/dry cycles, considering two ages of crack openings, 3 days and 28 days. The self-healing phenomenon was evaluated using two techniques: crack healing measurement using ultrasonic waves and image analysis performed with an optical microscope. It is possible to observe that by both methods, it possible to observe the self-healing phenomenon of the cracks. For young ages of crack openings and lower water/cement ratios, the self-healing capacity is higher when compared to advanced ages of crack openings and higher water/cement ratios. Regardless of the crack opening age, these concretes were found to stabilize the self-healing processes after 80 days or 90 days.

Keywords: sealf-healing, autogenous, water/cement ratio, curing cycles, test methods

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Authors: Didem Kepir Savoly, Selen Demirtas Zorbaz

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This research focuses on the unique developmental stage of university students, known as emerging adulthood, which can be filled with stressors relating to academics, career aspirations, and relationships. The impact of these factors on the wellbeing and mental health of students is not well understood and requires further investigation. The aim of this study is to investigate the influence of career optimism and relationship status on the wellbeing/life satisfaction of university students. The specific hypotheses being tested are: 1) University students with higher career optimism will exhibit a higher level of life satisfaction, and 2) University students in relationships will report a higher level of life satisfaction. This research adopts a quantitative approach, utilizing scales and questionnaires to collect data from university students in Turkey. The data was collected from university students in Turkey through the administration of the Career Optimism Scale, The Satisfaction with Life Scale, and the Perceived Romantic Relationship Quality Scale. The data is then analyzed using scale implementation, correlational analysis, and group comparison. One-way ANOVA, regression, and t-test analysis techniques are employed. The research findings provide insights into the relationship between career optimism and university students’ life satisfaction, as well as the influence of relationship status on their life satisfaction. The results suggest that life satisfaction was predicted by career optimism but not by relationship status. Moreover, significant relationships between life satisfaction and relationship quality were found among the university students who were in a relationship. These results can be utilized by practitioners, particularly those in counseling centers and career services at universities, to develop tailored psychoeducational and intervention programs aimed at promoting the mental health of university students.

Keywords: career optimism, relationship status, university students, wellbeing

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Authors: Esther M. Folarin, Evans Osabuohien, Ademola Onabote

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Agriculture constitutes an important part of development and poverty mitigation in lower-middle-income countries, like Nigeria. The level of agricultural productivity in the Nigerian economy in line with the level of demand necessary to meet the desired expectation of the Nigerian populace is threatening to meeting the standard of the United Nations (UN) Sustainable Development Goals (SDGs); This includes the SDG-2 (achieve food security through agricultural productivity). The overall objective of the study is to reveal the performance of the interaction variable in the model among other factors that help in the achievement of greater Nigerian agricultural productivity. The study makes use of Wave 4 (2018/2019) of the Living Standard Measurement Studies, Integrated Survey on Agriculture (LSMS-ISA). Qualitative analysis of the information was also used to provide complimentary answers to the quantitative analysis done in the study. The study employed human capital theory and Grossman’s theory of health Demand in explaining the relationships that exist between the variables within the model of the study. The study engages the Instrumental Variable Regression technique in achieving the broad objectives among other techniques for the other specific objectives. The estimation results show that there exists a positive relationship between female healthcare and the level of female agricultural productivity in Nigeria. In conclusion, the study emphasises the need for more provision and empowerment for greater female access to healthcare and educational attainment levels that aids higher female agricultural productivity and consequently an improvement in the total agricultural productivity of the Nigerian economy.

Keywords: agricultural productivity, education, female, healthcare, investment

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Authors: Z. Jamalzadeh, A. Niaei, H. Erfannia, S. G. Hosseini, A. S. Razmgir

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Due to developing the industries, the emission of pollutants such as NOx, SOx, and CO2 are rapidly increased. Generally, NOx is attributed to the mono nitrogen oxides of NO and NO2 that is one of the most important atmospheric contaminants. Hence, controlling the emission of nitrogen oxides is urgent environmentally. Selective Catalytic Reduction of NOx is one of the most common techniques for NOx removal in which Zeolites have wide application due to their high performance. In zeolitic processes, the catalytic reaction occurs mostly in the pores. Therefore, investigation the adsorption phenomena of the molecules in order to gain an insight and understand the catalytic cycle is of important. Hence, in current study, molecular simulations is applied for studying the adsorption phenomena in nanocatalysts applied for SCR of NOx process. The effect of cation addition to the support in the catalysts’ behavior through adsorption step was explored by Mont Carlo (MC). Simulation time of 1 Ns accompanying 1 fs time step, COMPASS27 Force Field and the cut off radios of 12.5 Ȧ was applied for performed runs. It was observed that the adsorption capacity increases in the presence of cations. The sorption isotherms demonstrated the behavior of type I isotherm categories and sorption capacity diminished with increase in temperature whereas an increase was observed at high pressures. Besides, NO sorption showed higher sorption capacity than NH3 in H–ZSM5. In this respect, the Energy distributions signified that the molecules could adsorb in just one sorption site at the catalyst and the sorption energy of NO was stronger than the NH3 in H-ZSM5. Furthermore, the isosteric heat of sorption data showed nearly same values for the molecules; however, it indicated stronger interactions of NO molecules with H-ZSM5 Zeolite compared to the isosteric heat of NH3 which was low in value.

Keywords: Monte Carlo simulation, adsorption, NOx, ZSM5

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Authors: Piyush V. Surjagade, Jiamei Deng, Paul Doney, S. R. Shimjith, A. John Arul

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In sophisticated and complex systems such as nuclear power plants, maintaining the system's stability in the presence of uncertainties and disturbances and obtaining a fast dynamic response are the most challenging problems. Thus, to ensure the satisfactory and safe operation of nuclear power plants, this work proposes a new fast, robust optimal switching control strategy for pressurized water reactor-type nuclear power plants. The proposed control strategy guarantees a substantial degree of robustness, fast dynamic response over the entire operational envelope, and optimal performance during the nominal operation of the plant. To improve the robustness, obtain a fast dynamic response, and make the system optimal, a bank of controllers is designed. Various controllers, like a baseline proportional-integral-derivative controller, an optimal linear quadratic Gaussian controller, and a robust adaptive L1 controller, are designed to perform distinct tasks in a specific situation. At any instant of time, the most suitable controller from the bank of controllers is selected using the switching logic unit that designates the controller by monitoring the health of the nuclear power plant or transients. The proposed switching control strategy optimizes the overall performance and increases operational safety and efficiency. Simulation studies have been performed considering various uncertainties and disturbances that demonstrate the applicability and effectiveness of the proposed switching control strategy over some conventional control techniques.

Keywords: switching control, robust control, optimal control, nuclear power control

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Authors: Vishal Mahale, Jayashree Bijwe, Sujeet K. Sinha

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Nowadays extensive research is going on in the field of friction materials (FMs) for development of eco-friendly brake-materials by removing copper as it is a proven threat to the aquatic organisms. Researchers are keen to find the solution for copper-free FMs by using different metals or without metals. Steel wool is used as a reinforcement in non-asbestos organic (NAO) FMs mainly for increasing thermal conductivity, and it affects wear adversely, most of the times and also adds friction fluctuations. Copper and brass used to be the preferred choices because of superior performance in almost every aspect except cost. Since these are being phased out because of a proven threat to the aquatic life. Keeping this in view, a series of realistic multi-ingredient FMs containing stainless steel (SS) swarfs as a theme ingredient in increasing amount (0, 5, 10 and 15 wt. %- S₅, S₁₀, and S₁₅) were developed in the form of brake-pads. One more composite containing copper instead of SS swarfs (C₁₀) was developed. These composites were characterized for physical, mechanical, chemical and tribological performance. Composites were tribo-evaluated on a chase machine with various test loops as per SAE J661 standards. Various performance parameters such as normal µ, hot µ, performance µ, fade µ, recovery µ, % fade, % recovery, wear resistance, etc. were used to evaluate the role of amount of SS swarfs in FMs. It was concluded that SS swarfs proved successful in Cu replacement almost in all respects except wear resistance. With increase in amount of SS swarfs, most of the properties improved. Worn surface analysis and wear mechanism were studied using SEM and EDAX techniques.

Keywords: Chase type friction tester, copper-free, non-asbestos organic (NAO) friction materials, stainless steel swarfs

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Authors: Supannika Klangphukhiew, Roongnapa Srichana, Rina Patramanon

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Cortisol has been used as a well-known commercial stress biomarker. A homeostasis response to psychological stress is indicated by an increased level of cortisol produced in hypothalamus-pituitary-adrenal (HPA) axis. Chronic psychological stress contributing to the high level of cortisol relates to several health problems. In this study, the cortisol biosensor was fabricated that mimicked the natural receptors. The artificial antibodies were prepared using molecular imprinted polymer technique that can imitate the performance of natural anti-cortisol antibody with high stability. Cortisol-molecular imprinted polymer (cortisol-MIP) was obtained using the multi-step swelling and polymerization protocol with cortisol as a target molecule combining methacrylic acid:acrylamide (2:1) with bisacryloyl-1,2-dihydroxy-1,2-ethylenediamine and ethylenedioxy-N-methylamphetamine as cross-linkers. Cortisol-MIP was integrated to the sensor. It was coated on the disposable screen-printed carbon electrode (SPCE) for portable electrochemical analysis. The physical properties of Cortisol-MIP were characterized by means of electron microscope techniques. The binding characteristics were evaluated via covalent patterns changing in FTIR spectra which were related to voltammetry response. The performance of cortisol-MIP modified SPCE was investigated in terms of detection range, high selectivity with a detection limit of 1.28 ng/ml. The disposable cortisol biosensor represented an application of MIP technique to recognize steroids according to their structures with feasibility and cost-effectiveness that can be developed to use in point-of-care.

Keywords: stress biomarker, cortisol, molecular imprinted polymer, screen-printed carbon electrode

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Authors: Premjit K. Sanjram, Gagan Jakhotiya, Apoorv Goyal, Shanu Shukla

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In psychological research, laboratory experiments often face the trade-off issue between experimental control and mundane realism. With the advent of Immersive Virtual Environment Technology (IVET), this issue seems to be at bay. However there is a growing challenge within the IVET itself to design and develop system or software that captures the psychological phenomenon of everyday lives. One such phenomena that is of growing interest is ‘media-multitasking’ To aid laboratory researches in media-multitasking this paper introduces Query Task Modulator (QTM), a computerized experimentation system to study media-multitasking behavior in a controlled laboratory environment. The system provides a computerized platform in conducting an experiment for experimenters to study media-multitasking in which participants will be involved in a query task. The system has Instant Messaging, E-mail, and Voice Call features. The answers to queries are provided on the left hand side information panel where participants have to search for it and feed the information in the respective communication media blocks as fast as possible. On the whole the system will collect multitasking behavioral data. To analyze performance there is a separate output table that records the reaction times and responses of the participants individually. Information panel and all the media blocks will appear on a single window in order to ensure multi-modality feature in media-multitasking and equal emphasis on all the tasks (thus avoiding prioritization to a particular task). The paper discusses the development of QTM in the light of current techniques of studying media-multitasking.

Keywords: experimentation system, human performance, media-multitasking, query-task

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Authors: Anna Zoli

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In recent years, we have been witnessing a surge of locally-sustained communities committed to promoting new ethical economies while fostering the full participation of socially excluded groups and individuals into the labor market. This article explores the practices of a particular community development model, Transition Towns, as implemented in Monteveglio, Italy. Data were gathered throughout two years long ethnography, using multiple qualitative techniques, namely participant observation, document analysis, and semi-structured interviews. Data were analyzed triangulating from multiple sources of evidence and using hybrid thematic analysis. Major findings show that Transition Town movement works on two main axes, vertical and horizontal. Vertical transition involves interactions with an overreaching political, economic, and social structure which is not transitioning, and therefore poses structural resistances to the transformative social change fostered by the TT. Conversely, horizontal transition involves intragroup dynamics within the communal relational and geographical spaces and therefore poses process resistances between 'self and others' to the interpersonal communication between TT members. The study concludes that a psychosocial approach to community development is essential in order to conflate macro-social dynamics and psychological processes that may obstacle grassroots social movements to thrive. Skills from psychosocial disciplines are a unique set that could facilitate communication and relational processes for community development, and ultimately enabling social change.

Keywords: community development, grassroots social movements, psychosocial approaches, Transition Towns

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Authors: Suminar Pratapa, Agus Riyanto, Silmi Machmudah, Sri Yani Purwaningsih

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The objective of this study was to investigate the optical properties of polyvinyl alcohol (PVA) and its prospective applications by adding crystalline silica which is usually used as a reinforcing agent. To do this, we synthesized and evaluated PVA-based composites reinforced with silica crystals, namely cristobalite, derived from rice husk. The experimental procedure involved the production of SiO2 particles using rice husk precursors, which were subsequently subjected to calcination at a rate of 10 °C/min for a duration of 3 hours. This process primarily resulted in the formation of SiO2 crystals in the cristobalite phase, according to X-ray diffraction (XRD). Following this, the crystals were incorporated into polyvinyl alcohol (PVA) via a casting technique, resulting in the formation of composite sheets. The SiO2 contents in the composites were 0, 2.5, 5.0, and 10.%. XRD and Fourier-transform infrared spectroscopy (FTIR) techniques provided confirmation of the composites' successful synthesis, i.e., it did not yield any indications of chemical bonding between polyvinyl alcohol (PVA) and silicon dioxide (SiO2), indicating that the interaction was limited to interfacial reactions. The incorporation of SiO2 crystals resulted in a notable enhancement in UV-vis light absorption and a decrease in the optical band gap. Addition of 2.5, 5.0, and 10.% SiO2, for example, decreases the direct optical band gap of the composites form 5.37, 5.19, and 5.02 eV respectively, while the indirect band gaps of the samples were 4.44, 4.84, and 4.48 eV, correspondingly. These findings emphasize the efficacy of rice husk-derived SiO2 crystals as both reinforcement agents and modifiers of optical properties in the polymer composites, showcasing their significant potential to modify the composite's structural and optical characteristics.

Keywords: rice husk, cristaline SiO₂, PVA-based composites, structural characteristics, optical properties.

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Authors: Dewi Retno Sari Saputro, Purnami Widyaningsih, Hendrika Handayani

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Extreme data on an observation can occur due to unusual circumstances in the observation. The data can provide important information that can’t be provided by other data so that its existence needs to be further investigated. The method for obtaining extreme data is one of them using maxima block method. The distribution of extreme data sets taken with the maxima block method is called the distribution of extreme values. Distribution of extreme values is Gumbel distribution with two parameters. The parameter estimation of Gumbel distribution with maximum likelihood method (ML) is difficult to determine its exact value so that it is necessary to solve the approach. The purpose of this study was to determine the parameter estimation of Gumbel distribution with quasi-Newton BFGS method. The quasi-Newton BFGS method is a numerical method used for nonlinear function optimization without constraint so that the method can be used for parameter estimation from Gumbel distribution whose distribution function is in the form of exponential doubel function. The quasi-New BFGS method is a development of the Newton method. The Newton method uses the second derivative to calculate the parameter value changes on each iteration. Newton's method is then modified with the addition of a step length to provide a guarantee of convergence when the second derivative requires complex calculations. In the quasi-Newton BFGS method, Newton's method is modified by updating both derivatives on each iteration. The parameter estimation of the Gumbel distribution by a numerical approach using the quasi-Newton BFGS method is done by calculating the parameter values that make the distribution function maximum. In this method, we need gradient vector and hessian matrix. This research is a theory research and application by studying several journals and textbooks. The results of this study obtained the quasi-Newton BFGS algorithm and estimation of Gumbel distribution parameters. The estimation method is then applied to daily rainfall data in Purworejo District to estimate the distribution parameters. This indicates that the high rainfall that occurred in Purworejo District decreased its intensity and the range of rainfall that occurred decreased.

Keywords: parameter estimation, Gumbel distribution, maximum likelihood, broyden fletcher goldfarb shanno (BFGS)quasi newton

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Authors: Mouhamadou Diop, Mohamed I. Hassan

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Molten metallic flow in metallurgical plant is highly turbulent and presents a complex coupling with heat transfer, phase transfer, chemical reaction, momentum transport, etc. Molten silicon flow has significant effect in directional solidification of multicrystalline silicon by affecting the temperature field and the emerging crystallization interface as well as the transport of species and impurities during casting process. Owing to the complexity and limits of reliable measuring techniques, computational models of fluid flow are useful tools to study and quantify these problems. The overall objective of this study is to investigate the potential of a traveling magnetic field for an efficient operating control of the molten metal flow. A multidimensional numerical model will be developed for the calculations of Lorentz force, molten metal flow, and the related phenomenon. The numerical model is implemented in a laboratory-scale silicon crystallization furnace. This study presents the potential of traveling magnetic field approach for an efficient operating control of the molten flow. A numerical model will be used to study the effects of magnetic force applied on the molten flow, and their interdependencies. In this paper, coupled and decoupled, steady and unsteady models of molten flow and crystallization interface will be compared. This study will allow us to retrieve the optimal traveling magnetic field parameter range for crystallization furnaces and the optimal numerical simulations strategy for industrial application.

Keywords: multidimensional, numerical simulation, solidification, multicrystalline, traveling magnetic field

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Authors: R. Santos Alimi

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Using time-series techniques, this study empirically tested the validity of existing theory which stipulates there is a nonlinear relationship between government size and economic growth; such that government spending is growth-enhancing at low levels but growth-retarding at high levels, with the optimal size occurring somewhere in between. This study employed three estimation equations. First, for the size of government, two measures are considered as follows: (i) share of total expenditures to gross domestic product, (ii) share of recurrent expenditures to gross domestic product. Second, the study adopted real GDP (without government expenditure component), as a variant measure of economic growth other than the real total GDP, in estimating the optimal level of government expenditure. The study is based on annual Nigeria country-level data for the period 1970 to 2012. Estimation results show that the inverted U-shaped curve exists for the two measures of government size and the estimated optimum shares are 19.81% and 10.98%, respectively. Finally, with the adoption of real GDP (without government expenditure component), the optimum government size was found to be 12.58% of GDP. Our analysis shows that the actual share of government spending on average (2000 - 2012) is about 13.4%.This study adds to the literature confirming that the optimal government size exists not only for developed economies but also for developing economy like Nigeria. Thus, a public intervention threshold level that fosters economic growth is a reality; beyond this point economic growth should be left in the hands of the private sector. This finding has a significant implication for the appraisal of government spending and budgetary policy design.

Keywords: public expenditure, economic growth, optimum level, fully modified OLS

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Authors: Neil Jordan M. Uy, Fe Pelilia V. Hernandez

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A counselor is always regarded as a professional who embodies the willingness to help others through the process of counseling. He is knowledgeable and skillful of the different theories, tools, and techniques that are useful in aiding the client to cope with their dilemmas. The negative experiences of the clients that are shared during the counseling session can affect the professional counselor. Compassion fatigue, a professional impairment, is characterized by the decline of one’s productivity and the feeling of anxiety and stress brought about as the counselor empathizes, listens, and cares for others. This descriptive type of research aimed to explore variables that are predictors of compassion fatigue utilizing three research instruments; Demographic Profile Sheet, Professional Quality of Life Scale, and Neo-Pi-R. The 52 respondents of this study were counselors from the different Dominican schools in the Philippines. Generally, the counselors have low level of compassion fatigue across personal characteristics (age, gender, years of service, highest educational attainment, and professional status) and personality traits (extraversion, agreeableness, conscientiousness, openness, and neuroticism). ANOVA validated the findings of this that among the personal characteristics and personality traits, extraversion with f-value of 3.944 and p-value of 0.026, and conscientiousness, with f-value of 4.125 and p-value of 0.022 were found to have significant difference in the level of compassion fatigue. A very significant difference was observed with neuroticism with f-value of 6.878 and p-value 0.002. Among the personal characteristics and personal characteristics, only neuroticism was found to predict compassion fatigue. The computed r2 value of 0.204 using multiple regression analysis suggests that 20.4 percent of compassion fatigue can be predicted by neuroticism. The predicting power of neuroticism can be computed from the regression model Y=0.156x+26.464; where x is the number of neuroticism.

Keywords: big five personality traits, compassion fatigue, counselors, professional quality of life scale

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Authors: Yahya Almurtadha, Mukhtar Ghaleb, Ahmed M. Shamsan Saleh

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The world witnessed a fierce attack from the Covid-19 virus, which affected public life socially, economically, healthily and psychologically. The world's governments tried to confront the pandemic by imposing a number of precautionary measures such as general closure, curfews and social distancing. Scientists have also made strenuous efforts to develop an effective vaccine to train the immune system to develop antibodies to combat the virus, thus reducing its symptoms and limiting its spread. Artificial intelligence, along with researchers and medical authorities, has accelerated the vaccine development process through big data processing and simulation. On the other hand, one of the most important negatives of the impact of Covid 19 was the state of anxiety and fear due to the blowout of rumors through social media, which prompted governments to try to reassure the public with the available means. This study aims to proposed using Sentiment Analysis (AKA Opinion Mining) and deep learning as efficient artificial intelligence techniques to work on retrieving the tweets of the public from Twitter and then analyze it automatically to extract their opinions, expression and feelings, negatively or positively, about the symptoms they may feel after vaccination. Sentiment analysis is characterized by its ability to access what the public post in social media within a record time and at a lower cost than traditional means such as questionnaires and interviews, not to mention the accuracy of the information as it comes from what the public expresses voluntarily.

Keywords: deep learning, opinion mining, natural language processing, sentiment analysis

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Authors: Jinhoa Lee

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The relationships between environmental quality, energy use and economic output have created growing attention over the past decades among researchers and policy makers. Focusing on the empirical aspects of the role of CO2 emissions and energy use in affecting the economic output, this paper is an effort to fulfil the gap in a comprehensive case study at a country level using modern econometric techniques. To achieve the goal, this country-specific study examines the short-run and long-run relationships among energy consumption, carbon dioxide (CO2) emissions and gross domestic product (GDP) for Oman using time series analysis from the year 1980-2010. To investigate the relationships between the variables, this paper employs the Augmented Dickey Fuller (ADF) test for stationary, Johansen maximum likelihood method for co-integration and a Vector Error Correction Model (VECM) for both short- and long-run causality among the research variables for the sample. All the variables in this study show very strong significant effects on GDP in the country for the long term. The long-run equilibrium in the VECM suggests positive long-run causalities from CO2 emissions to GDP. Conversely, negative impacts of energy consumption on GDP are found to be significant in Oman during the period. In the short run, there exist negative unidirectional causalities among GDP, CO2 emissions and energy consumption running from GDP to CO2 emissions and from energy consumption to CO2 emissions. Overall, the results support arguments that there are relationships among environmental quality, energy use and economic output in Oman over of period 1980-2010.

Keywords: CO2 emissions, energy consumption, GDP, Oman, time series analysis

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Authors: A. Rajesh Kanna, G. Suresh Kumar, Sathyanaryana N. Gummadi

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There are various sources of energies available worldwide and among them, crude oil plays a vital role. Oil recovery is achieved using conventional primary and secondary recovery methods. In-order to recover the remaining residual oil, technologies like Enhanced Oil Recovery (EOR) are utilized which is also known as tertiary recovery. Among EOR, Microbial enhanced oil recovery (MEOR) is a technique which enables the improvement of oil recovery by injection of bio-surfactant produced by microorganisms. Bio-surfactant can retrieve unrecoverable oil from the cap rock which is held by high capillary force. Bio-surfactant is a surface active agent which can reduce the interfacial tension and reduce viscosity of oil and thereby oil can be recovered to the surface as the mobility of the oil is increased. Research in this area has shown promising results besides the method is echo-friendly and cost effective compared with other EOR techniques. In our research, on laboratory scale we produced bio-surfactant using the strain Pseudomonas putida (MTCC 2467) and injected into designed simple sand packed column which resembles actual petroleum reservoir. The experiment was conducted in order to determine the efficiency of produced bio-surfactant in oil recovery. The column was made of plastic material with 10 cm in length. The diameter was 2.5 cm. The column was packed with fine sand material. Sand was saturated with brine initially followed by oil saturation. Water flooding followed by bio-surfactant injection was done to determine the amount of oil recovered. Further, the injection of bio-surfactant volume was varied and checked how effectively oil recovery can be achieved. A comparative study was also done by injecting Triton X 100 which is one of the chemical surfactant. Since, bio-surfactant reduced surface and interfacial tension oil can be easily recovered from the porous sand packed column.

Keywords: bio-surfactant, bacteria, interfacial tension, sand column

Procedia PDF Downloads 392

Authors: Alia Alghosoun, Ashraf Osman, Mohammed Seaid

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A coupled two-layer finite volume/finite element method was proposed for solving dam-break flow problem over deformable beds. The governing equations consist of the well-balanced two-layer shallow water equations for the water flow and a linear elastic model for the bed deformations. Deformations in the topography can be caused by a brutal localized force or simply by a class of sliding displacements on the bathymetry. This deformation in the bed is a source of perturbations, on the water surface generating water waves which propagate with different amplitudes and frequencies. Coupling conditions at the interface are also investigated in the current study and two mesh procedure is proposed for the transfer of information through the interface. In the present work a new procedure is implemented at the soil-water interface using the finite element and two-layer finite volume meshes with a conservative distribution of the forces at their intersections. The finite element method employs quadratic elements in an unstructured triangular mesh and the finite volume method uses the Rusanove to reconstruct the numerical fluxes. The numerical coupled method is highly efficient, accurate, well balanced, and it can handle complex geometries as well as rapidly varying flows. Numerical results are presented for several test examples of dam-break flows over deformable beds. Mesh convergence study is performed for both methods, the overall model provides new insight into the problems at minimal computational cost.

Keywords: dam-break flows, deformable beds, finite element method, finite volume method, hybrid techniques, linear elasticity, shallow water equations

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Authors: Xiaobin Liang, Wei Liang, Laibin Zhang, Xiaoyan Guo

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Pipelines pass through coal mined gobs inevitably in the mining area, the stability of which has great influence on the safety of pipelines. After extensive literature study and field research, it was found that there are a few risk assessment methods for coal mined gob pipelines, and there is a lack of data on the gob sites. Therefore, the fuzzy comprehensive evaluation method is widely used based on expert opinions. However, the subjective opinions or lack of experience of individual experts may lead to inaccurate evaluation results. Hence the accuracy of the results needs to be further improved. This paper presents a comprehensive approach to achieve this purpose by combining bow-tie model and cloud inference. The specific evaluation process is as follows: First, a bow-tie model composed of a fault tree and an event tree is established to graphically illustrate the probability and consequence indicators of pipeline failure. Second, the interval estimation method can be scored in the form of intervals to improve the accuracy of the results, and the censored mean algorithm is used to remove the maximum and minimum values of the score to improve the stability of the results. The golden section method is used to determine the weight of the indicators and reduce the subjectivity of index weights. Third, the failure probability and failure consequence scores of the pipeline are converted into three numerical features by using cloud inference. The cloud inference can better describe the ambiguity and volatility of the results which can better describe the volatility of the risk level. Finally, the cloud drop graphs of failure probability and failure consequences can be expressed, which intuitively and accurately illustrate the ambiguity and randomness of the results. A case study of a coal mine gob pipeline carrying natural gas has been investigated to validate the utility of the proposed method. The evaluation results of this case show that the probability of failure of the pipeline is very low, the consequences of failure are more serious, which is consistent with the reality.

Keywords: bow-tie model, natural gas pipeline, coal mine gob, cloud inference

Procedia PDF Downloads 238

Authors: Andrej Kocjan

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Introduction: Mobility has been shown to play an important role of health and quality of life among older adults. Falls, which are often related to decreased mobility, as well as to neuromuscular deficits, represent the most common injury among older adults. Fall risk has been shown to increase with reduced lower extremity flexibility. The aim of the paper is to assess the importance of flexibility training on joint range of motion and functional performance among elderly population. Methods: We performed literature research on PubMed and evaluated articles published until 2000. The articles found in the search strategy were also added. The population of interest included older adults (≥ 65 years of age). Results: Flexibility training programs still represent an important part of several rehabilitation programs. Static stretching and proprioceptive neuromuscular facilitation are the most frequently used techniques to improve the length of the muscle-tendon complex. Although the effectiveness of type of stretching seems to be related to age and gender, static stretching is a more appropriate technique to enhance shoulder, hip, and ankle range of motion in older adults. Stretching should be performed in multiple sets with holds of more than 60 seconds for a single muscle group. Conclusion: The literature suggests that flexibility training is an effective method to increase joint range of motion in older adults. In the light of increased functional outcome, activities such as strengthening, balance, and aerobic exercises should be incorporated into a training program for older people. Due to relatively little published literature, it is still not possible to prescribe detailed recommendations regarding flexibility training for older adults.

Keywords: elderly, exercise, flexibility, falls

Procedia PDF Downloads 170

Authors: Thomas Monahan, Nicolas Gorius, Thanh Nguyen

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Exoplanet atmospheric parameters retrieval is a complex, computationally intensive, inverse modeling problem in which an exoplanet’s atmospheric composition is extracted from an observed spectrum. Traditional Bayesian sampling methods require extensive time and computation, involving algorithms that compare large numbers of known atmospheric models to the input spectral data. Runtimes are directly proportional to the number of parameters under consideration. These increased power and runtime requirements are difficult to accommodate in space missions where model size, speed, and power consumption are of particular importance. The use of traditional Bayesian sampling methods, therefore, compromise model complexity or sampling accuracy. The Atmospheric Retrievals conditional Generative Adversarial Network (ARcGAN) is a deep convolutional generative adversarial network that improves on the previous model’s speed and accuracy. We demonstrate the efficacy of artificial intelligence to quickly and reliably predict atmospheric parameters and present it as a viable alternative to slow and computationally heavy Bayesian methods. In addition to its broad applicability across instruments and planetary types, ARcGAN has been designed to function on low power application-specific integrated circuits. The application of edge computing to atmospheric retrievals allows for real or near-real-time quantification of atmospheric constituents at the instrument level. Additionally, edge computing provides both high-performance and power-efficient computing for AI applications, both of which are critical for space missions. With the edge computing chip implementation, ArcGAN serves as a strong basis for the development of a similar machine-learning algorithm to reduce the downlinked data volume from the Compact Ultraviolet to Visible Imaging Spectrometer (CUVIS) onboard the DAVINCI mission to Venus.

Keywords: deep learning, generative adversarial network, edge computing, atmospheric parameters retrieval

Procedia PDF Downloads 155

Authors: Zubair Khaliq, M. Bilal Qadir, Amir Shahzad, Zulfiqar Ali, Ahsan Nazir, Ali Afzal, Abdul Jabbar

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Carbon fibers are one of the most demanding materials on earth due to their potential application in energy, high strength materials, and conductive materials. The nanostructure of carbon fibers offers enhanced properties of conductivity due to the larger surface area. The next generation carbon nanofibers demand the porous structure as it offers more surface area. Multiple techniques are used to produce carbon fibers. However, electrospinning followed by carbonization of the polymeric materials is easy to carry process on a laboratory scale. Also, it offers multiple diversity of changing parameters to acquire the desired properties of carbon fibers. Polyacrylonitrile (PAN) is the most used material for the production of carbon fibers due to its promising processing parameters. Also, cellulose is one of the highest yield producers of carbon fibers. However, the electrospinning of cellulosic materials is difficult due to its rigid chain structure. The combination of PAN and cellulose can offer a suitable solution for the production of carbon fibers. Both materials are miscible in the mixed solvent of N, N, Dimethylacetamide and lithium chloride. This study focuses on the production of porous carbon fibers as a function of PAN/Cellulose blend ratio, solution properties, and electrospinning parameters. These single polymer and blend with different ratios were electrospun to give fine fibers. The higher amount of cellulose offered more difficulty in electrospinning of nanofibers. After carbonization, the carbon fibers were studied in terms of their blend ratio, surface area, and texture. Cellulose contents offered the porous structure of carbon fibers. Also, the presence of LiCl contributed to the porous structure of carbon fibers.

Keywords: cellulose, polyacrylonitrile, carbon nanofibers, electrospinning, blend

Procedia PDF Downloads 189

Authors: Po-Jung Huang, Chi-Ching Lee, Bertrand Chin-Ming Tan, Yuan-Ming Yeh, Julie Lichieh Chu, Tin-Wen Chen, Cheng-Yang Lee, Ruei-Chi Gan, Hsuan Liu, Petrus Tang

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Whole-exome sequencing focuses on the protein coding regions of disease/cancer associated genes based on a priori knowledge is the most cost-effective method to study the association between genetic alterations and disease. Recent advances in high throughput sequencing technologies and proteomic techniques has provided an opportunity to integrate genomics and proteomics, allowing readily detectable mutated peptides corresponding to mutated genes. Since sequence database search is the most widely used method for protein identification using Mass spectrometry (MS)-based proteomics technology, a mutant proteome database is required to better approximate the real protein pool to improve disease-associated mutated protein identification. Large-scale whole exome/genome sequencing studies were launched by National Cancer Institute (NCI), Broad Institute, and The Cancer Genome Atlas (TCGA), which provide not only a comprehensive report on the analysis of coding variants in diverse samples cell lines but a invaluable resource for extensive research community. No existing database is available for the collection of mutant protein sequences related to the identified variants in these studies. CMPD is designed to address this issue, serving as a bridge between genomic data and proteomic studies and focusing on protein sequence-altering variations originated from both germline and cancer-associated somatic variations.

Keywords: TCGA, cancer, mutant, proteome

Procedia PDF Downloads 576

Authors: Muhammad Farhan Ul Moazzam, Tamkeen Urooj Paracha, Ghani Rahman, Byung Gul Lee, Nasir Farid, Adnan Arshad

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The novel coronavirus pandemic disease (COVID-19) affected the whole globe, though there is a lack of clinical studies and its epidemiological features. But as per the observation, it has been seen that most of the COVID-19 infected patients show mild to moderate symptoms, and they get better without any medical assistance due to a better immune system to generate antibodies against the novel coronavirus. In this study, the active cases, serious cases, recovered cases, deaths and total confirmed cases had been analyzed using the geospatial inverse distance weightage technique (IDW) within the time span of 2nd March to 3rd June 2020. As of 3rd June, the total number of COVID-19 cases in Italy were 231,238, total deaths 33,310, serious cases 350, recovered cases 158,951, and active cases were 39,177, which has been reported by the Ministry of Health, Italy. March 2nd-June 3rd, 2020 a sum of 231,238 cases has been reported in Italy out of which 38.68% cases reported in the Lombardia region with a death rate of 18%, which is high from its national mortality rate followed by Emilia-Romagna (14.89% deaths), Piemonte (12.68% deaths), and Vento (10% deaths). As per the total cases in the region, the highest number of recoveries has been observed in Umbria (92.52%), followed by Basilicata (87%), Valle d'Aosta (86.85%), and Trento (84.54%). The COVID-19 evolution in Italy has been particularly found in the major urban area, i.e., Rome, Milan, Naples, Bologna, and Florence. Geospatial technology played a vital role in this pandemic by tracking infected patient, active cases, and recovered cases. Geospatial techniques are very important in terms of monitoring and planning to control the pandemic spread in the country.

Keywords: COVID-19, public health, geospatial analysis, IDW, Italy

Procedia PDF Downloads 134