Search results for: real estate pricing

Authors: Fekadu Melak, Tsegaye Girma Asere

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Trace element ions, such as Cr(VI) and F−, are of particular interest due to their environmental impact. Both ions exhibit an anionic nature in water that can show similar removal tendencies except for their significant differences in ionic radius. Accordingly, partial freezing was performed to examine freeze separation efficiencies of Cr(VI) and F– from aqueous solutions. Real groundwater and simulated wastewater were included to test effeciency of F– and Cr(VI), respectively. Parameters such as initial ion concentration, salt addition, and freeze duration were explored. Under optimal operating conditions, freeze separation efficiencies of 90 ± 0.12 to 97 ± 0.54% and 58 ± 0.23% to 60 ± 0.34% from 5 mg/L of Cr(VI) and F–, respectively, were demonstrated. The F– ion intercalation into the ice, initiating the decrement of freeze separation efficiency was observed in the salt addition processes. The influences of structuring-destructuring (kosmotropicity-chaotropicity) and the size-exclusion nature of ice crystals were used to explain the plausible mechanism in freeze separation efficiency trace elemental ions.

Keywords: Cr(VI), F-, partial freezing, size exclusion

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Authors: Saeid Jalilzadeh

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PID controllers are widely used to control the industrial plants because of their robustness and simple structures. Tuning of the controller's parameters to get a desired response is difficult and time consuming. With the development of computer technology and artificial intelligence in automatic control field, all kinds of parameters tuning methods of PID controller have emerged in endlessly, which bring much energy for the study of PID controller, but many advanced tuning methods behave not so perfect as to be expected. Honey Bee algorithm (HBA) and genetic algorithm (GA) are extensively used for real parameter optimization in diverse fields of study. This paper describes an application of HBA and GA to the problem of designing a PID controller whose parameters comprise proportionality constant, integral constant and derivative constant. Presence of three parameters to optimize makes the task of designing a PID controller more challenging than conventional P, PI, and PD controllers design. The suitability of the proposed approach has been demonstrated through computer simulation using MATLAB/SIMULINK.

Keywords: controller, GA, optimization, PID, PSO

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Authors: Ramzi Farra, Detre Teschner, Marc Willinger, Robert Schlögl

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Introduction: The conventional approach of characterizing solid catalysts under static conditions, i.e., before and after reaction, does not provide sufficient knowledge on the physicochemical processes occurring under dynamic conditions at the molecular level. Hence, the necessity of improving new in situ characterizing techniques with the potential of being used under real catalytic reaction conditions is highly desirable. In situ Prompt Gamma Activation Analysis (PGAA) is a rapidly developing chemical analytical technique that enables us experimentally to assess the coverage of surface species under catalytic turnover and correlate these with the reactivity. The catalytic HCl oxidation (Deacon reaction) over bulk ceria will serve as our example. Furthermore, the in situ Transmission Electron Microscopy is a powerful technique that can contribute to the study of atmosphere and temperature induced morphological or compositional changes of a catalyst at atomic resolution. The application of such techniques (PGAA and TEM) will pave the way to a greater and deeper understanding of the dynamic nature of active catalysts. Experimental/Methodology: In situ Prompt Gamma Activation Analysis (PGAA) experiments were carried out to determine the Cl uptake and the degree of surface chlorination under reaction conditions by varying p(O2), p(HCl), p(Cl2), and the reaction temperature. The abundance and dynamic evolution of OH groups on working catalyst under various steady-state conditions were studied by means of in situ FTIR with a specially designed homemade transmission cell. For real in situ TEM we use a commercial in situ holder with a home built gas feeding system and gas analytics. Conclusions: Two complimentary in situ techniques, namely in situ PGAA and in situ FTIR were utilities to investigate the surface coverage of the two most abundant species (Cl and OH). The OH density and Cl uptake were followed under multiple steady-state conditions as a function of p(O2), p(HCl), p(Cl2), and temperature. These experiments have shown that, the OH density positively correlates with the reactivity whereas Cl negatively. The p(HCl) experiments give rise to increased activity accompanied by Cl-coverage increase (opposite trend to p(O2) and T). Cl2 strongly inhibits the reaction, but no measurable increase of the Cl uptake was found. After considering all previous observations we conclude that only a minority of the available adsorption sites contribute to the reactivity. In addition, the mechanism of the catalysed reaction was proposed. The chlorine-oxygen competition for the available active sites renders re-oxidation as the rate-determining step of the catalysed reaction. Further investigations using in situ TEM are planned and will be conducted in the near future. Such experiments allow us to monitor active catalysts at the atomic scale under the most realistic conditions of temperature and pressure. The talk will shed a light on the potential and limitations of in situ PGAA and in situ TEM in the study of catalyst dynamics.

Keywords: CeO2, deacon process, in situ PGAA, in situ TEM, in situ FTIR

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Authors: Qing K. Zhu

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Very Large Scale Integration (VLSI) design becomes very complex due to the continuous integration of millions of gates in one chip based on Moore’s law. Designers have encountered numerous report files during design iterations using timing and noise analysis tools. This paper presented our work using data mining techniques combined with HTML tables to extract and represent critical timing/noise data. When we apply this data-mining tool in real applications, the running speed is important. The software employs table look-up techniques in the programming for the reasonable running speed based on performance testing results. We added several advanced features for the application in one industry chip design.

Keywords: VLSI design, data mining, big data, HTML forms, web, VLSI, EDA, timing, noise

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Authors: Shinji Kawakura, Ryosuke Shibasaki

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We have been grouping and developing various kinds of practical, promising sensing applied systems concerning agricultural advancement and technical tradition (guidance). These include advanced devices to secure real-time data related to worker motion, and we analyze by methods of various advanced statistics and human dynamics (e.g. primary component analysis, Ward system based cluster analysis, and mapping). What is more, we have been considering worker daily health and safety issues. Targeted fields are mainly common farms, meadows, and gardens. After then, we observed and discussed time-line style, changing data. And, we made some suggestions. The entire plan makes it possible to improve both the aforementioned applied systems and farms.

Keywords: advanced statistical analysis, wearable sensing system, tradition of skill, supporting for workers, detecting crisis

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Authors: Bader Alruwaili, Surajit Ray

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Finite mixtures are a flexible and powerful tool that can be used for univariate and multivariate distributions, and a wide range of research analysis has been conducted based on the multivariate normal mixture and multivariate of a t-mixture. Determining the number of modes is an important activity that, in turn, allows one to determine the number of homogeneous groups in a population. Our work currently being carried out relates to the study of the modality of the skew normal distribution in the univariate and multivariate cases. For the skew normal distribution, the aims are associated with studying the modality of the skew normal distribution and providing the ridgeline, the ridgeline elevation function, the $\Pi$ function, and the curvature function, and this will be conducive to an exploration of the number and location of mode when mixing the two components of skew normal distribution. The subsequent objective is to apply these results to the application of real world data sets, such as flow cytometry data.

Keywords: mode, modality, multivariate skew normal, finite mixture, number of mode

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Authors: Arshia Aflaki, Hadis Karimipour, Anik Islam

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Generative Adversarial Attacks (GAAs) threaten critical sectors, ranging from fingerprint recognition to industrial control systems. Existing Deep Learning (DL) algorithms are not robust enough against this kind of cyber-attack. As one of the most critical industries in the world, the power grid is not an exception. In this study, a Deep Reinforcement Learning-based (DRL) framework assisting the DL model to improve the robustness of the model against generative adversarial attacks is proposed. Real-world smart grid stability data, as an IIoT dataset, test our method and improves the classification accuracy of a deep learning model from around 57 percent to 96 percent.

Keywords: generative adversarial attack, deep reinforcement learning, deep learning, IIoT, generative adversarial networks, power system

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Authors: Hafila Banu

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Minimalism is a postmodern style movement which emerged in the 50s of the twentieth century, but it was rapidly growing in the years of 60s and 70s. Minimalism is defined as the concept of minimizing distractions from what is truly valuable or essential. On the same grounds, works of minimalism offer a direct view at and raises questions about the true nature of the subject or object inviting the viewer to consider it for it for the real shape, a thought, a movement reminding us to focus on what is really important. The Architecture of Minimalism is characterized by an economy with materials , focusing on building quality with considerations for ‘essences’ as light, form, detail of material, texture, space and scale, place and human conditions . The research of this paper is mainly into the basis of designing a minimalistic mosque in India while analysing the parameters for the design from the matching characteristics of Islamic architecture in specific to a mosque and the minimalism. Therefore, the paper is about the mosque architecture and minimalism and of their underlying principles, matching characteristics and design goals.

Keywords: Islamic architecture, minimalism, minimalistic mosque, mosque in India

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Authors: Anastasios Charisis, Evangelos Kaisar, Steven Spana, Lili Du

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Logistics play a vital role in the prosperity of today’s cities, but current urban logistics practices are proving problematic, causing negative effects such as traffic congestion and environmental impacts. This paper proposes an alternative urban logistics system, leasing hubs inside cities for designated time intervals, and using handcarts for last-mile deliveries. A mathematical model for selecting the locations of hubs and allocating customers, while also scheduling the optimal times during the day for leasing hubs is developed. The proposed model is compared to current delivery methods requiring door-to-door truck deliveries. It is shown that truck traveled distances decrease by more than 60%. In addition, analysis shows that in certain conditions the approach can be economically competitive and successfully applied to address real problems.

Keywords: hub location, last-mile, logistics, optimization

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Authors: Muhammmad Riandhy Anindika Yudhy, Harry Patria, Ramadhani Santoso

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Loss of containment is the primary hazard that process safety management is concerned within the oil and gas industry. Escalation to more serious consequences all begins with the loss of containment, starting with oil and gas release from leakage or spillage from primary containment resulting in pool fire, jet fire and even explosion when reacted with various ignition sources in the operations. Therefore, the heart of process safety management is avoiding loss of containment and mitigating its impact through the implementation of safeguards. The most effective safeguard for the case is an early detection system to alert Operations to take action prior to a potential case of loss of containment. The detection system value increases when applied to a long surface pipeline that is naturally difficult to monitor at all times and is exposed to multiple causes of loss of containment, from natural corrosion to illegal tapping. Based on prior researches and studies, detecting loss of containment accurately in the surface pipeline is difficult. The trade-off between cost-effectiveness and high accuracy has been the main issue when selecting the traditional detection method. The current best-performing method, Real-Time Transient Model (RTTM), requires analysis of closely positioned pressure, flow and temperature (PVT) points in the pipeline to be accurate. Having multiple adjacent PVT sensors along the pipeline is expensive, hence generally not a viable alternative from an economic standpoint.A conceptual approach to combine mathematical modeling using computational fluid dynamics and a supervised machine learning model has shown promising results to predict leakage in the pipeline. Mathematical modeling is used to generate simulation data where this data is used to train the leak detection and localization models. Mathematical models and simulation software have also been shown to provide comparable results with experimental data with very high levels of accuracy. While the supervised machine learning model requires a large training dataset for the development of accurate models, mathematical modeling has been shown to be able to generate the required datasets to justify the application of data analytics for the development of model-based leak detection systems for petroleum pipelines. This paper presents a review of key leak detection strategies for oil and gas pipelines, with a specific focus on crude oil applications, and presents the opportunities for the use of data analytics tools and mathematical modeling for the development of robust real-time leak detection and localization system for surface pipelines. A case study is also presented.

Keywords: pipeline, leakage, detection, AI

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Authors: N. Meddeb, A. M. Makhlouf, M. A. Ben Ayed

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Due to the real-time requirement of message in Vehicular Ad hoc NETworks (VANET), it is necessary to authenticate vehicles to achieve security, efficiency, and conditional privacy-preserving. Privacy is of utmost relevance in VANETs. For this reason, we have proposed a new protocol called ‘Multilevel Authentication Protocol’ (MAP) that considers different vehicle categories. The proposed protocol is based on our Multilevel Authentication protocol for Vehicular networks (MAVnet). But the MAP leads to human safety, where the priority is given to the ambulance vehicles. For evaluation, we used the Java language to develop a demo application and deployed it on the Network Security Simulation (Nessi2). Compared with existing authentication protocols, MAP markedly enhance the communication overhead and decreases the delay of exchanging messages while preserving conditional privacy.

Keywords: Vehicular Ad hoc NETworks (VANET), vehicle categories, safety, databases, privacy, authentication, throughput, delay

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Authors: Shafqat Ullah Khan, Ammar Nasir

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Using planar antenna array (PAA) in radars, Broadcasting, satellite antennas, and sonar for the detection of targets, Helps provide instant beam pattern control. High flexibility and Adaptability are achieved by multiple beam steering by using a Planar array and are particularly needed in real-life Sanrio’s where the need arises for several high-directivity beams. Faulty sensors in planar arrays generate asymmetry, which leads to service degradation, radiation pattern distortion, and increased levels of sidelobe. The POA, a nature-inspired optimization algorithm, accurately determines faulty sensors within an array, enhancing the reliability and performance of planar array antennas through extensive simulations and experiments. The analysis was done for different types of faults in 7 x 7 and 8 x 8 planar arrays in MATLAB.

Keywords: Planar antenna array, , Pelican optimisation Algorithm, , Faculty sensor, Antenna arrays

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Authors: Christine K. Fulmer

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Social work education is competency based in nature. There is an expectation that graduates of social work programs throughout the world are to be prepared to practice at a level of competence, which is beneficial to both the well-being of individuals and community. Experiential learning is one way to prepare students for competent practice. The use of Problem-Based Learning (PBL) is a form experiential education that has been successful in a number of disciplines to bridge the gap between the theoretical concepts in the classroom to the real world. PBL aligns with the constructivist theoretical approach to learning, which emphasizes the integration of new knowledge with the beliefs students already hold. In addition, the basic tenants of PBL correspond well with the practice behaviors associated with social work practice including multi-disciplinary collaboration and critical thinking. This paper makes an argument for utilizing PBL in social work education.

Keywords: social work education, problem-based learning, pedagogy, experiential learning, constructivist theoretical approach

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Authors: Rana Rimawi, Ayman Baklizi

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Skewed distributions are important models that are frequently used in applications. Generalized distributions form a class of skewed distributions and gain widespread use in applications because of their flexibility in data analysis. More specifically, the Generalized Logistic Distribution with its different types has received considerable attention recently. In this study, based on progressively type-II censored data, we will consider point estimation in type II Generalized Logistic Distribution (Type II GLD). We will develop several estimators for its unknown parameters, including maximum likelihood estimators (MLE), Bayes estimators and linear estimators (BLUE). The estimators will be compared using simulation based on the criteria of bias and Mean square error (MSE). An illustrative example of a real data set will be given.

Keywords: point estimation, type II generalized logistic distribution, progressive censoring, maximum likelihood estimation

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Authors: Jan Doutreloigne

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The main goal of this paper is to develop a switching amplifier with optimized power efficiency for analog signals with a very high crest factor such as audio or DSL signals. Theoretical calculations show that a switching amplifier architecture based on multi-level pulse width modulation outperforms all other types of linear or switching amplifiers in that respect. Simulations on a 2 W multi-level switching audio amplifier, designed in a 50 V 0.35 mm IC technology, confirm its superior performance in terms of power efficiency. A real silicon implementation of this audio amplifier design is currently underway to provide experimental validation.

Keywords: audio amplifier, multi-level switching amplifier, power efficiency, pulse width modulation, PWM, self-oscillating amplifier

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Authors: M. Vimal Raj, S. Sakthivel Murugan

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Underwater images degrade their quality due to atmospheric conditions. One of the major problems in an underwater image is motion blur caused by the imaging device or the movement of the object. In order to rectify that in post-imaging, parameters of the blurred image are to be estimated. So, the point spread function is estimated by the properties, using the spectrum of the image. To improve the estimation accuracy of the parameters, Optimized Polynomial Lagrange Interpolation (OPLI) method is implemented after the angle and length measurement of motion-blurred images. Initially, the data were collected from real-time environments in Chennai and processed. The proposed OPLI method shows better accuracy than the existing classical Cepstral, Hough, and Radon transform estimation methods for underwater images.

Keywords: image restoration, motion blur, parameter estimation, radon transform, underwater

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Authors: Kunal Shah, Swati Patel

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Many real world problems involve data which can be considered as multi-label data streams. Efficient methods exist for multi-label classification in non streaming scenarios. However, learning in evolving streaming scenarios is more challenging, as the learners must be able to adapt to change using limited time and memory. Classification is used to predict class of unseen instance as accurate as possible. Multi label classification is a variant of single label classification where set of labels associated with single instance. Multi label classification is used by modern applications, such as text classification, functional genomics, image classification, music categorization etc. This paper introduces the task of multi-label classification, methods for multi-label classification and evolution measure for multi-label classification. Also, comparative analysis of multi label classification methods on the basis of theoretical study, and then on the basis of simulation was done on various data sets.

Keywords: binary relevance, concept drift, data stream mining, MLSC, multiple window with buffer

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Authors: Mudasir Ahmad Syed, Raashid Ahmd Wani, Mashooq Ahmad Dar, Uneeb Urwat, Riaz Ahmad Shah, Nazir Ahmad Ganai

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Salmonella enterica serovar Typhimurium (Salmonella Typhimurium) is a primary avian pathogen responsible for severe intestinal pathology in younger chickens and economic losses. However, the Salmonella Typhimurium is also able to cause infection in humans, described by typhoid fever and acute gastro-intestinal disease. A study was conducted at days to investigate pathological, histopathological, haemato-biochemical, immunological and expression kinetics of NRAMP (natural resistance associated macrophage protein) gene family (NRAMP1 and NRAMP2) in broiler chickens following experimental infection of Salmonella Typhimurium at 0,1,3,5,7,9,11,13 and 15 days respectively. Infection was developed in birds through oral route at 2×108 CFU/ml. Clinical symptoms appeared 4 days post infection (dpi) and after one-week birds showed progressive weakness, anorexia, diarrhea and lowering of head. On postmortem examination, liver showed congestion, hemorrhage and necrotic foci on surface, while as spleen, lungs and intestines revealed congestion and hemorrhages. Histopathological alterations were principally observed in liver in second week post infection. Changes in liver comprised of congestion, areas of necrosis, reticular endothelial hyperplasia in association with mononuclear cell and heterophilic infiltration. Hematological studies confirm a significant decrease (P<0.05) in RBC count, Hb concentration and PCV. White blood cell count showed significant increase throughout the experimental study. An increase in heterophils was found up to 7dpi and a decreased pattern was observed afterwards. Initial lymphopenia followed by lymphocytosis was found in infected chicks. Biochemical studies showed a significant increase in glucose, AST and ALT concentration and a significant decrease (P<0.05) in total protein and albumin level in the infected group. Immunological studies showed higher titers of IgG in infected group as compared to control group. The real time gene expression of NRAMPI and NRAMP2 genes increased significantly (P<0.05) in infected group as compared to controls. The peak expression of NRAMP1 gene was seen in liver, spleen and caecum of infected birds at 3dpi, 5dpi and 7dpi respectively, while as peak expression of NRAMP2 gene in liver, spleen and caecum of infected chicken was seen at 9dpi, 5dpi and 9dpi respectively. This study has role in diagnostics and prognostics in the poultry industry for the detection of salmonella infections at early stages of poultry development.

Keywords: biochemistry, histopathology, NRAMP, poultry, real time expression, Salmonella Typhimurium

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Authors: Margarida Plana

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End-users behavior has become one of the main aspects to be solved on energy efficiency projects. Especially on the residential sector, the end-users have a direct impact that affects the achievement of energy saving’s targets. This paper is focused on presenting and quantify the impact of end-users behavior on basis of the analysis of real projects’ data. The analysis study which is the role of buiding’s occupants and how their behavior can change the success of energy efficiency projects how to limit their impact. The results obtained show two main conclusions. The first one is easiest to solve: we need to control and limit the end-users interaction with the equipment operation to be able to reach the targets fixed. The second one: as the plugged equipment are increasing exponentially on the residential sector, big efforts of disseminations are needed in order to explain to citizens the impact of their day by day actions through dissemination campaigns.

Keywords: end-users impacts, energy efficiency, energy savings, impact limitations

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Authors: Kai Chen, Shuguang Cui, Feng Yin

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Gaussian process (GP) with spectral mixture (SM) kernel demonstrates flexible non-parametric Bayesian learning ability in modeling unknown function. In this work a novel time-varying and non-stationary convolution spectral mixture (TN-CSM) kernel with a significant enhancing of interpretability by using process convolution is introduced. A way decomposing the SM component into an auto-convolution of base SM component and parameterizing it to be input dependent is outlined. Smoothly, performing a convolution between two base SM component yields a novel structure of non-stationary SM component with much better generalized expression and interpretation. The TN-CSM perfectly allows compatibility with the stationary SM kernel in terms of kernel form and spectral base ignored and confused by previous non-stationary kernels. On synthetic and real-world datatsets, experiments show the time-varying characteristics of hyper-parameters in TN-CSM and compare the learning performance of TN-CSM with popular and representative non-stationary GP.

Keywords: Gaussian process, spectral mixture, non-stationary, convolution

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Authors: M. Valentini, D. Melisi, M. A. Nitti, R A. Picca, M. C. Sportelli, E. Bonerba, G. Casamassima, N. Cioffi, L. Sabbatini, G. Tantillo, A. Valentini

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In recent years antimicrobial coatings are receiving increasing attention due to their high demand in medical applications as well as in healthcare and hygiene. Research and technology are constantly involved to develop advanced finishing which can provide bacteriostatic growth without compromising the other typical properties of a textile as durability and non-toxicity, just to cite a few. Here we report on the antimicrobial coatings obtained, at room temperature and without the use of solvents, by means of the ion beam co-sputtering technique of an Ag target and a polytetrafluoroethylene one. In particular, such method allows to conjugate the well-known antimicrobial action of silver with the anti-stain and water-repellent properties of the fluoropolymer. Moreover, different Ag nanoparticle loadings (φ) were prepared by tuning the material deposition conditions achieving a fine control on film thickness and their antimicrobial/anti-stain properties.

Keywords: antimicrobial, ion beam sputtering, nanocoatings, anti-stain

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Authors: Enwin Anthony Dornubari, Visigah Kpobari Peter

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This research has developed a framework for the provision of sustainable and affordable housing to accommodate the low-income population of Greater Port Harcourt City. The objectives of this study among others, were to: examine UN-Habitat guidelines for acceptable and sustainable social housing provision, describe past efforts of the Rivers State Government and the Federal Government of Nigeria to provide housing for the poor in the Greater Port Harcourt City area; obtain a profile of prospective beneficiaries of the social housing proposed by this research as well as perceptions of their present living conditions, and living in the proposed self-sustaining social housing development, based on the initial simulation of the proposal; describe the nature of the framework, guideline and management of the proposed social housing development and explain the modalities for its implementation. The study utilized the mixed methods research approach, aimed at triangulating findings from the quantitative and qualitative paradigms. Opinions of professional of the built environment; Director, Development Control, Greater Port Harcourt City Development Authority; Directors of Ministry of Urban Development and Physical Planning; Housing and Property Development Authority and managers of selected Primary Mortgage Institutions were sought and analyzed. There were four target populations for the study, namely: members of occupational sub-groups for FGDs (Focused Group Discussions); development professionals for KIIs (Key Informant Interviews), household heads in selected communities of GPHC; and relevant public officials for IDI (Individual Depth Interview). Focus Group Discussions (FGDs) were held with members of occupational sub-groups in each of the eight selected communities (Fisherfolk). The table shows that there were forty (40) members across all occupational sub-groups in each selected community, yielding a total of 320 in the eight (8) communities of Mgbundukwu (Mile 2 Diobu), Rumuodomaya, Abara (Etche), Igwuruta-Ali(Ikwerre), Wakama(Ogu-Bolo), Okujagu (Okrika), Akpajo (Eleme), and Okoloma (Oyigbo). For key informant interviews, two (2) members were judgmentally selected from each of the following development professions: urban and regional planners; architects; estate surveyors; land surveyors; quantity surveyors; and engineers. Concerning Population 3-Household Heads in Selected Communities of GPHC, a stratified multi-stage sampling procedure was adopted: Stage 1-Obtaining a 10% (a priori decision) sample of the component communities of GPHC in each stratum. The number in each stratum was rounded to one whole number to ensure representation of each stratum. Stage 2-Obtaining the number of households to be studied after applying the Taro Yamane formula, which aided in determining the appropriate number of cases to be studied at the precision level of 5%. Findings revealed, amongst others, that poor implementation of the UN-Habitat global shelter strategy, lack of stakeholder engagement, inappropriate locations, undue bureaucracy, lack of housing fairness and equity and high cost of land and building materials were the reasons for the failure of past efforts towards social housing provision in the Greater Port Harcourt City area. The study recommended a public-private partnership approach for the implementation and management of the framework. It also recommended a robust and sustained relationship between the management of the framework and the UN-Habitat office and other relevant government agencies responsible for housing development and all investment partners to create trust and efficiency.

Keywords: development, framework, low-income, sustainable, social housing

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Authors: Sujan Kumari Chaudhary

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Indo-Nepal border Biratnaga/Jogbani is a hub where economic exchange and cultural ties are forged daily. Furthermore, the porous and open border not only allows for the free movement of people and goods, but it also makes women more vulnerable, as they are frequently harassed by local authorities who are supposed to protect them. On the other hand, drug users roam around this region where many women experience that the place is not safe for women and girls. Moreover, women's safety is compromised by the open-border policy, which makes it difficult to control trafficking routes. Whereas the city was supposed to be a gateway for economic and cultural exchange, due to a lack of sensitivity in urban planning regarding gender, Biratnagar, and Jogbani have emerged as spaces of insecurity, limiting the free movement of women to various opportunities. The research explores a comprehensive analysis, identifies the gap in existing conditions, and proposes women-centered improvement focusing on Gender-based disparities, public space safety, and crime prevalence. It also addresses the issues that women confront in public spaces and recommends design approaches that prioritize safety and inclusivity. Research based on pragmatic paradigm emphasizes useful outcomes and the use of research in the real world to solve issues in an efficient way. The research topic "Designing Gender-Inclusive Urban Space: A Vision for Women's Safety CrossCountry Movement at Indo-Nepal Border Case of Biratnagar/Jogbani" seeks to generate actionable strategies and designs for gender-inclusive urban spaces in a specific socio-spatial context. Pragmatic focuses on solving real-world problems making it appropriate for gender safety issues. The pragmatic paradigm is the most appropriate for this subject because it strikes a balance between the necessity of comprehending women's experiences and the need to provide concrete policy and urban design solutions. Using the pragmatic paradigm, this study used a mixed-methods approach to investigate perceptions of safety for women and girls in a cross-border zone. Both surveys and interviews will be used because sexual harassment is a delicate topic. A thorough understanding of harassment experiences is provided by this mixed-methods approach, which enables the collection of quantitative data through structured questionnaires and qualitative insights through open-ended interviews. The findings aim to provide actionable strategies for policymakers and stakeholders to transform Indo-Nepal cross border into a model of gender-inclusive planning that empowers women and fosters equitable mobility across the border areas.

Keywords: gender-inclusive urban spaces, women's safety, public space design, pragmatic paradigm

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Authors: Boudemagh Naime

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Automatic radar detection requires some methods of adapting to variations in the background clutter in order to control their false alarm rate. The problem becomes more complicated in non-Gaussian environment. In fact, the conventional approach in real time applications requires a complex statistical modeling and much computational operations. To overcome these constraints, we propose another approach based on artificial neural network (ANN-CMLD-CFAR) using a Back Propagation (BP) training algorithm. The considered environment follows a log-normal distribution in the presence of multiple Rayleigh-targets. To evaluate the performances of the considered detector, several situations, such as scale parameter and the number of interferes targets, have been investigated. The simulation results show that the ANN-CMLD-CFAR processor outperforms the conventional statistical one.

Keywords: radat detection, ANN-CMLD-CFAR, log-normal clutter, statistical modelling

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Authors: M. Taha, Hala H. Zayed, T. Nazmy, M. Khalifa

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Recently, traffic monitoring has attracted the attention of computer vision researchers. Many algorithms have been developed to detect and track moving vehicles. In fact, vehicle tracking in daytime and in nighttime cannot be approached with the same techniques, due to the extreme different illumination conditions. Consequently, traffic-monitoring systems are in need of having a component to differentiate between daytime and nighttime scenes. In this paper, a HSV-based day/night detector is proposed for traffic monitoring scenes. The detector employs the hue-histogram and the value-histogram on the top half of the image frame. Experimental results show that the extraction of the brightness features along with the color features within the top region of the image is effective for classifying traffic scenes. In addition, the detector achieves high precision and recall rates along with it is feasible for real time applications.

Keywords: day/night detector, daytime/nighttime classification, image classification, vehicle tracking, traffic monitoring

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Authors: Farha Sattar, Laurence Tamatea, Muhammad Nawaz

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Drones, the Unmanned Aerial Vehicles are playing an important role in real-world problem-solving. With the new advancements in technology, drones are becoming available, affordable and user- friendly. Use of drones in education is opening new trends in teaching and learning practices in an innovative and engaging way. Drones vary in types and sizes and possess various characteristics and capabilities which enhance their potential to be used in education from basic to advanced and challenging learning activities which are suitable for primary, middle and high school level. This research aims to provide an insight to explore different types of drones and their compatibility to be used in teaching different subjects at various levels. Research focuses on integrating the drone technology along with Australian curriculum content knowledge to reinforce the understanding of the fundamental concepts and helps to develop the critical thinking and reasoning in the learning process.

Keywords: critical thinking, drone technology, drone types, innovative learning

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Authors: Pimploi Tirastittam, Suppara Charoenpoom

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Nowadays the asynchronous learning has granted the permission to the anywhere and anything learning via the technology and E-media which give the learner more convenient. This research is about the design of the blended and online learning for the asynchronous learning of the process management subject in order to create the prototype of this subject asynchronous learning which will create the easiness and increase capability in the learning. The pattern of learning is the integration between the in-class learning and online learning via the internet. This research is mainly focused on the online learning and the online learning can be divided into 5 parts which are virtual classroom, online content, collaboration, assessment and reference material. After the system design was finished, it was evaluated and tested by 5 experts in blended learning design and 10 students which the user’s satisfaction level is good. The result is as good as the assumption so the system can be used in the process management subject for a real usage.

Keywords: blended learning, asynchronous learning, design, process management

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Authors: T. A. Khan, A. B. Khan, M. Babar, T. A. Taj, Imran Ijaz Imran

Abstract:

Smart Meter is a key element in the evolving concept of Smart Grid, which plays an important role in interaction between the consumer and the supplier. In general, the smart meter is an intelligent digital energy meter that measures the consumption of electrical energy and provides other additional services as compared to the conventional energy meters. One of the important element that makes a meter smart and different is its communication module. Smart meters usually have two way and real-time communication between the consumer and the supplier through which its transfer data and information. In this paper, Ultra Wide Band (UWB) is recommended as communication platform because of its high data-rate and presents the physical layer, which could be easily incorporated in existing Smart Meters. The physical layer is simulated in MATLAB Simulink and the results are provided.

Keywords: Ultra Wide Band (UWB), Smart Meter, MATLAB, transfer data

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Authors: K. Ilicic, D. Smoljan

Abstract:

The purpose of the paper is to present and verify a methodology of decreasing water losses by introducing and managing District Metered Areas (DMA) and Pressure Management Areas (PMA) by analyzing the results of the application of the methodology to the water supply system of the city of Zagreb. Since it is a relatively large system that has been expanding rapidly, approach to addressing water losses was possible only by splitting the system to smaller flow and pressure zones. Besides, the geographical and technical limitations had imposed the necessity of high pressure in the system that needed to be reduced to the technically optimal level. Results of activities were monitored on a general and local level by establishing, monitoring, and controlling indicators that had been established by the International Water Association (IWA), among which the most recognizable were non-revenue water, water losses and real losses as presented in the paper.

Keywords: district metered area, pressure metered area, active leakage control, water losses

Procedia PDF Downloads 187

Authors: Michele Gattullo, Vito M. Manghisi, Alessandro Evangelista, Enricoandrea Laviola

Abstract:

In this work, we explored the use of Augmented Reality (AR) to support students in laboratory lectures in Distance Learning (DL), designing an application that proved to be ready for use next semester. AR could help students in the understanding of complex concepts as well as increase their motivation in the learning process. However, despite many prototypes in the literature, it is still less used in schools and universities. This is mainly due to the perceived limited advantages to the investment costs, especially regarding changes needed in the teaching modalities. However, with the spread of epidemiological emergency due to SARS-CoV-2, schools and universities were forced to a very rapid redefinition of consolidated processes towards forms of Distance Learning. Despite its many advantages, it suffers from the impossibility to carry out practical activities that are of crucial importance in STEM ("Science, Technology, Engineering e Math") didactics. In this context, AR perceived advantages increased a lot since teachers are more prepared for new teaching modalities, exploiting AR that allows students to carry on practical activities on their own instead of being physically present in laboratories. In this work, we designed an AR application for the support of engineering students in the understanding of assembly drawings of complex machines. Traditionally, this skill is acquired in the first years of the bachelor's degree in industrial engineering, through laboratory activities where the teacher shows the corresponding components (e.g., bearings, screws, shafts) in a real machine and their representation in the assembly drawing. This research aims to explore the effectiveness of AR to allow students to acquire this skill on their own without physically being in the laboratory. In a preliminary phase, we interviewed students to understand the main issues in the learning of this subject. This survey revealed that students had difficulty identifying machine components in an assembly drawing, matching between the 2D representation of a component and its real shape, and understanding the functionality of a component within the machine. We developed a mobile application using Unity3D, aiming to solve the mentioned issues. We designed the application in collaboration with the course professors. Natural feature tracking was used to associate the 2D printed assembly drawing with the corresponding 3D virtual model. The application can be displayed on students’ tablets or smartphones. Users could interact with selecting a component from a part list on the device. Then, 3D representations of components appear on the printed drawing, coupled with 3D virtual labels for their location and identification. Users could also interact with watching a 3D animation to learn how components are assembled. Students evaluated the application through a questionnaire based on the System Usability Scale (SUS). The survey was provided to 15 students selected among those we participated in the preliminary interview. The mean SUS score was 83 (SD 12.9) over a maximum of 100, allowing teachers to use the AR application in their courses. Another important finding is that almost all the students revealed that this application would provide significant power for comprehension on their own.

Keywords: augmented reality, distance learning, STEM didactics, technology in education

Procedia PDF Downloads 131