Search results for: processing parameters

Authors: Daniel Nelson, Valeria La Saponara

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Material extrusion is an additive manufacturing modality that continues to show great promise in the ability to create low-cost, highly intricate, and exceedingly useful structural elements. As more capable and versatile filament materials are devised, and the resolution of manufacturing systems continues to increase, the need to understand and predict manufacturing-induced warping will gain ever greater importance. The following study presents an in situ remote sensing and data analysis construct that allows for the in situ mapping and quantification of surface displacements induced by residual stresses on a specified test structure. This proof-of-concept experimental process shows that it is possible to provide designers and manufacturers with insight into the manufacturing parameters that lead to the manifestation of these deformations and a greater understanding of the behavior of these warping events over the course of the manufacturing process.

Keywords: additive manufacturing, deformation, digital image correlation, fused filament fabrication, residual stress, warping

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Authors: Bhaveek Maini, Sanjay Dhanka, Surita Maini

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Electroencephalography (EEG) is used to classify several epileptic seizures worldwide. It is a very crucial task for the neurologist to identify the epileptic seizure with manual EEG analysis, as it takes lots of effort and time. Human error is always at high risk in EEG, as acquiring signals needs manual intervention. Disease diagnosis using machine learning (ML) has continuously been explored since its inception. Moreover, where a large number of datasets have to be analyzed, ML is acting as a boon for doctors. In this research paper, authors proposed two different ML models, i.e., logistic regression (LR) and Naïve Bayes (NB), to predict epileptic seizures based on general parameters. These two techniques are applied to the epileptic seizures recognition dataset, available on the UCI ML repository. The algorithms are implemented on an 80:20 train test ratio (80% for training and 20% for testing), and the performance of the model was validated by 10-fold cross-validation. The proposed study has claimed accuracy of 81.87% and 95.49% for LR and NB, respectively.

Keywords: epileptic seizure recognition, logistic regression, Naïve Bayes, machine learning

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Authors: Elyas Akbari, Jafar Hasani, Newsha Dehestani, Mohammad Khaleghi, Alireza Moradi

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The aim of the present study was to assess the effect of emotional experience induction in the mirror neurons systems (MNS) activity with regard to the spectrum of depressive symptoms. For this purpose, at first stage, 449 students of Kharazmi University of Tehran were selected randomly and completed the second version of the Beck Depression Inventory (BDI-II). Then, 36 students with standard Z-score equal or above +1.5 and equal or equal or below -1.5 were selected to construct two groups of high and low spectrum of depressive symptoms. In the next stage, the basic activity of MNS was recorded (mu wave) before presenting the positive and negative emotional video clips by Electroencephalography (EEG) technique. The findings related to emotion induction (neutral, negative and positive emotion) demonstrated that the activity of recorded mirror neuron areas had a significant difference between the depressive and non-depressive groups. These findings suggest that probably processing of negative emotions in depressive individuals is due to the idea that the mirror neurons in motor cortex matched up the activity of cognitive regions with the person’s schema. Considering the results of the present study, it could be said that the MNS provides a substrate where emotional disorders can be studied and evaluated.

Keywords: emotional experiences, mirror neurons, depressive symptoms, negative and positive emotion

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Authors: Samia Hachemi, Abdelhafid Ounis, W. Heriheri

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This paper presents an experimental investigation of high temperatures applied to normal and high performance concrete made with natural coarse aggregates. The experimental results of physical and mechanical properties were compared with those obtained with recycled brick aggregates produced by replacing 30% of natural coarse aggregates by recycled brick aggregates. The following parameters: compressive strength, concrete mass loss, apparent density and water porosity were examined in this experiment. The results show that concrete could be produced by using recycled brick aggregates and reveals that at high temperatures recycled aggregate concrete preformed similar or even better than natural aggregate concrete.

Keywords: high temperature, compressive strength, mass loss, recycled brick aggregate

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Authors: Mohamed Fredj, Abdallah Hafsaoui, Radouane Nakache

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The study of the stability of the mining works in rock masses fractured is the major concern of the operating engineer. For geotechnical works in mines and quarries, it there is not today's general methodology for analysis and the quantification of the risks relating to the dangers inherent in these concrete types (falling boulders, landslides, etc.). The reasons for this are uncertainty, which weighs on available data or lack of knowledge of the values of the parameters required for this analysis type. Stability calculations must be based on reliable knowledge of the distribution of discontinuities that dissect the Rocky massif and the resistance to shear of the intact rock and discontinuities. This study is aimed to study the stability of slope of mine (Kef Sennoun - Tebessa, Algeria). The problem is analyzed using a numerical model based on the finite elements (software Plaxis 3D).

Keywords: stability, discontinuities, finite elements, rock mass, open-pit mine

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Authors: Maja Benkovic, Dubravka Novotni, Bojana Voucko, Duska Curic, Damir Jezek, Nikolina Cukelj

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Cryo-grinding is an ultra-fine grinding method used in the pharmaceutical industry, production of herbs and spices and in the production and handling of cereals, due to its ability to produce powders with small particle sizes which maintain their favorable bioactive profile. The aim of this study was to determine the particle size distributions of the proso millet (Panicum miliaceum) bran fraction grinded at cryogenic temperature (using liquid nitrogen (LN₂) cooling, T = - 196 °C), in comparison to non-cooled grinding. Proso millet bran is primarily used as an animal feed, but has a potential in food applications, either as a substrate for extraction of bioactive compounds or raw material in the bakery industry. For both applications finer particle sizes of the bran could be beneficial. Thus, millet bran was ground for 2, 4, 8 and 12 minutes using the ball mill (CryoMill, Retsch GmbH, Haan, Germany) at three grinding modes: (I) without cooling, (II) at cryo-temperature, and (III) at cryo-temperature with included 1 minute of intermediate cryo-cooling step after every 2 minutes of grinding, which is usually applied when samples require longer grinding times. The sample was placed in a 50 mL stainless steel jar containing one grinding ball (Ø 25 mm). The oscillation frequency in all three modes was 30 Hz. Particle size distributions of the bran were determined by a laser diffraction particle sizing method (Mastersizer 2000) using the Scirocco 2000 dry dispersion unit (Malvern Instruments, Malvern, UK). Three main effects of the grinding set-up were visible from the results. Firstly, grinding time at all three modes had a significant effect on all particle size parameters: d(0.1), d(0.5), d(0.9), D[3,2], D[4,3], span and specific surface area. Longer grinding times resulted in lower values of the above-listed parameters, e.g. the averaged d(0.5) of the sample (229.57±1.46 µm) dropped to 51.29±1.28 µm after 2 minutes grinding without LN₂, and additionally to 43.00±1.33 µm after 4 minutes of grinding without LN₂. The only exception was the sample ground for 12 minutes without cooling, where an increase in particle diameters occurred (d(0.5)=62.85±2.20 µm), probably due to particles adhering to one another and forming larger particle clusters. Secondly, samples with LN₂ cooling exhibited lower diameters in comparison to non-cooled. For example, after 8 minutes of non-cooled grinding d(0.5)=46.97±1.05 µm was achieved, while the LN₂ cooling enabled collection of particles with average sizes of d(0.5)=18.57±0.18 µm. Thirdly, the application of intermediate cryo-cooling step resulted in similar particle diameters (d(0.5)=15.83±0.36 µm, 12 min of grinding) as cryo-milling without this step (d(0.5)=16.33±2.09 µm, 12 min of grinding). This indicates that intermediate cooling is not necessary for the current application, which consequently reduces the consumption of LN₂. These results point out the potential beneficial effects of millet bran grinding at cryo-temperatures. Further research will show if the lower particle size achieved in comparison to non-cooled grinding could result in increased bioavailability of bioactive compounds, as well as protein digestibility and solubility of dietary fibers of the proso millet bran fraction.

Keywords: ball mill, cryo-milling, particle size distribution, proso millet (Panicum miliaceum) bran

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Authors: Khenfer-Koummich Fatima, Mesbahi Larbi, Hendel Fatiha

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This paper presents a recognition system for isolated words like robot commands. It’s carried out by Time Delay Neural Networks; TDNN. To teleoperate a robot for specific tasks as turn, close, etc… In industrial environment and taking into account the noise coming from the machine. The choice of TDNN is based on its generalization in terms of accuracy, in more it acts as a filter that allows the passage of certain desirable frequency characteristics of speech; the goal is to determine the parameters of this filter for making an adaptable system to the variability of speech signal and to noise especially, for this the back propagation technique was used in learning phase. The approach was applied on commands pronounced in two languages separately: The French and Arabic. The results for two test bases of 300 spoken words for each one are 87%, 97.6% in neutral environment and 77.67%, 92.67% when the white Gaussian noisy was added with a SNR of 35 dB.

Keywords: TDNN, neural networks, noise, speech recognition

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Authors: Sam Khozama, Ali M. Mayya

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Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data needs a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM) and ensemble learning with hyper parameters optimization are used, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.

Keywords: machine learning, deep learning, cancer prediction, breast cancer, LSTM, fusion

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Authors: S. Bangphan, P. Bangphan, C. Ketsombun, T. Sammana

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Optimization of response surface methodology (RSM) was employed to study the effects of three factor (rubber of clearance, spindle of speed, and rice of moisture) in brown rice peeling machine of the optimal good rice yield (99.67, average of three repeats). The optimized composition derived from RSM regression was analyzed using Regression analysis and Analysis of Variance (ANOVA). At a significant level α=0.05, the values of Regression coefficient, R2 adjust were 96.55% and standard deviation were 1.05056. The independent variables are initial rubber of clearance, spindle of speed and rice of moisture parameters namely. The investigating responses are final rubber clearance, spindle of speed and moisture of rice.

Keywords: brown rice, response surface methodology (RSM), peeling machine, optimization, paddy husker

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Authors: Andrew Anis Fakhrey Mosaad

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This Musculoskeletal (MSK) conditions are a major contributing factor in disability. This becomes more challenging as the world population is witnessing an increase in the geriatric population. Various treatment strategies are being researched to provide the most effective and non-invasive approach. To date, low-level laser therapy (LLLT) is one of the emerging modalities to treat different musculoskeletal conditions in physical therapy practice. Physical therapy practice uses different modalities to control pain and inflammation. LLLT has been under research for the last two decades and has shown varying results. This literature review focuses on the effectiveness of LLLT in different musculoskeletal conditions. Using search engines of PubMed and Google Scholar, a number of articles have been reviewed based on the inclusion and exclusion criteria. LLLT shows promising results in treating different musculoskeletal conditions. However, clinicians need to ensure to follow the recommended dosage parameters for specific musculoskeletal conditions.

Keywords: musculoskeletal conditions, low level laser therapy, ultrasound, wavelength, pain and inflammation

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Authors: I. Savitskaya, A. Kistaubayeva, A. Zhubanova, I. Blavachinskaiya, D. Ibrayeva, M. Abdulzhanova, A. Otarbay, A.Isabekova

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This study was conducted for the investigation of number of cellulolytic bacteria and their ability in decomposition. Seven samples surface soil were collected on cellulose Zailiskii Alatau slopes. Cellulolitic activity of new strains of Bacillus, isolated from soil is determined. Isolated cellulose degrading bacteria were screened for determination of the highest cellulose activity by quantitative assay using Congo red, gravimetric assay and colorimetric DNS method trough of the determination of the parameters of sugar reduction. Strains are assigned to: B.subtilis, B.licheniformis, B. cereus and, В. megaterium. Bacillus strains consisting of several different types of cellulases have broad substrate specificity of cellulase complexes formed by them. Cellulolitic bacteria were recorded to have highest cellulase activity and selected for optimization of cellulase enzyme production.

Keywords: cellulose-degrading bacteria, cellulase complex, foothills soil, screening

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Authors: M. Brandt, A. Peniak, J. Makarovič, P. Rafajdus

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This paper deals with a novel approach of power transformers diagnostics. This approach identifies the exact location and the range of a fault in the transformer and helps to reduce operation costs related to handling of the faulty transformer, its disassembly and repair. The advantage of the approach is a possibility to simulate healthy transformer and also all faults, which can occur in transformer during its operation without its disassembling, which is very expensive in practice. The approach is based on creating frequency dependent impedance of the transformer by sweep frequency response analysis measurements and by 3D FE parametrical modeling of the fault in the transformer. The parameters of the 3D FE model are the position and the range of the axial short circuit. Then, by comparing the frequency dependent impedances of the parametrical models with the measured ones, the location and the range of the fault is identified. The approach was tested on a real transformer and showed high coincidence between the real fault and the simulated one.

Keywords: transformer, parametrical model of transformer, fault, sweep frequency response analysis, finite element method

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Authors: Zoubida Lounis, Naouel Boumesla, Abd El Kader Bengueddach

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The main objective of this study is to synthesize a composite materials by direct synthesis at atmospheric pression having the MFI structure and MCM-41 by using double structuring. In the first part of this work we are interested in the study of the synthesis parameters, in addition to temperature, the crystallization time and pH. The second part of this work is to vary the ratio of the concentrations of both structuring C9 [C9H19(CH3)3NBr] and C16 [C16H33(CH3)3NBr] and determining the area of formation of the two materials (microporous and mesoporous at same time), for this reason we performed a battery of experiments ranging from 0 to 100% for both structural. To enhance the economic purposes of this study, the experiments were carried out by using very cheap and simple process, the pyrex tubes were used instead of the reactors, and the synthesis were done at atmospheric pressure and moderate temperature. The final products (composite materials) were obtained at high and pure quality.

Keywords: composite materials, syntheisis, catalysts, mesoporous materials, microporous materials

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Authors: Anu Malhotra

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An Ad-hoc network is one that is an autonomous, self configuring network made up of mobile nodes connected via wireless links. Ad-hoc networks often consist of nodes, mobile hosts (MH) or mobile stations (MS, also serving as routers) connected by wireless links. Different routing protocols are used for data transmission in between the nodes in an adhoc network. In this paper two protocols (OLSR and AODV) are analyzed on the basis of two parameters i.e. time delay and throughput with different data rates. On the basis of these analysis, we observed that with same data rate, AODV protocol is having more time delay than the OLSR protocol whereas throughput for the OLSR protocol is less compared to the AODV protocol.

Keywords: routing adhoc, mobile hosts, mobile stations, OLSR protocol, AODV protocol

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Authors: Sarah Werner, Michael J. Pritchard

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From pilots to engineers, the skills development within the aerospace industry is exceptionally broad. Employers often struggle with finding the right mixture of qualified skills to fill their organizational demands. This effort to find qualified talent is further complicated by the industrial delineation between two key areas: aviation and aerospace. In a broad sense, the aerospace industry overlaps with the aviation industry. In turn, the aviation industry is a smaller sector segment within the context of the broader definition of the aerospace industry. Furthermore, it could be conceptually argued that -in practice- there is little distinction between these two sectors (i.e., aviation and aerospace). However, through our unstructured text analysis of over 6,000 job listings captured, our team found a clear delineation between aviation-related jobs and aerospace-related jobs. Using techniques in natural language processing, our research identifies an integrated workforce skill pattern that clearly breaks between these two sectors. While the aviation sector has largely maintained its need for pilots, mechanics, and associated support personnel, the staffing needs of the aerospace industry are being progressively driven by integrative engineering needs. Increasingly, this is leading many aerospace-based organizations towards the acquisition of 'system level' staffing requirements. This research helps to better align higher educational institutions with the current industrial staffing complexities within the broader aerospace sector.

Keywords: aerospace industry, job demand, text mining, workforce development

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Authors: Loretta Ichim, Dan Popescu, Grigore Stamatescu

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The paper reports the collaboration between a top university from Romania and three companies for the implementation of a research project in a multidisciplinary domain, focusing on the impact and benefits both for the education and industry. The joint activities were developed under the Space Technology and Advanced Research Program (STAR), funded by the Romanian Space Agency (ROSA) for a university-industry partnership. The context was defined by linking the European Space Agency optional programs, with the development and promotion national research, with the educational and industrial capabilities in the aeronautics, security and related areas by increasing the collaboration between academic and industrial entities as well as by realizing high-level scientific production. The project name is Multisensory Robotic System for Aerial Monitoring of Critical Infrastructure Systems (MUROS), which was carried 2013-2016. The project included the University POLITEHNICA of Bucharest (coordinator) and three companies, which manufacture and market unmanned aerial systems. The project had as main objective the development of an integrated system for combined ground wireless sensor networks and UAV monitoring in various application scenarios for critical infrastructure surveillance. This included specific activities related to fundamental and applied research, technology transfer, prototype implementation and result dissemination. The core area of the contributions laid in distributed data processing and communication mechanisms, advanced image processing and embedded system development. Special focus is given by the paper to analyzing the impact the project implementation in the educational process, directly or indirectly, through the faculty members (professors and students) involved in the research team. Three main directions are discussed: a) enabling students to carry out internships at the partner companies, b) handling advanced topics and industry requirements at the master's level, c) experiments and concept validation for doctoral thesis. The impact of the research work (as the educational component) developed by the faculty members on the increasing performances of the companies’ products is highlighted. The collaboration between university and companies was well balanced both for contributions and results. The paper also presents the outcomes of the project which reveals the efficient collaboration between high education and industry: master thesis, doctoral thesis, conference papers, journal papers, technical documentation for technology transfer, prototype, and patent. The experience can provide useful practices of blending research and education within an academia-industry cooperation framework while the lessons learned represent a starting point in debating the new role of advanced research and development performing companies in association with higher education. This partnership, promoted at UE level, has a broad impact beyond the constrained scope of a single project and can develop into long-lasting collaboration while benefiting all stakeholders: students, universities and the surrounding knowledge-based economic and industrial ecosystem. Due to the exchange of experiences between the university (UPB) and the manufacturing company (AFT Design), a new project, SIMUL, under the Bridge Grant Program (Romanian executive agency UEFISCDI) was started (2016 – 2017). This project will continue the educational research for innovation on master and doctoral studies in MUROS thematic (collaborative multi-UAV application for flood detection).

Keywords: education process, multisensory robotic system, research and innovation project, technology transfer, university-industry partnership

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Authors: Farideh Gheitasi, Zahra Mirzaei Pour

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Considering mutual interactions of industry and residence in an environmental point of view is essential in effective urban management and all the policies must be made based on the results of these interactions. So, District No 21 of Tehran Municipality (Iran) which is almost industrial combined with some residential area was selected to study the consequences of industrial and residential area neighborhood. In this paper the results of two observations conducted in two timescales in 2010 and 2015, according to completed questionnaires by residents of an industrial region in the study area, were analyzed. The questionnaires contain 19 different environmental parameters considering positive and negative effects of industry on human life. The results of this study show that 96% of the target group in 2010 believed if the companies regard the law, mutual coexistence of industry and residency is possible. While this number decreased to 21% in 2015, which indicates that the problem got worse and people became more unsatisfied with the situation.

Keywords: environment, industry, residence, pollution

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Authors: Saurav Kumar Suman, P. Karthigayani

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In this paper the height of the tree is estimated and forest types is classified from the multi temporal RISAT-1 Horizontal-Horizontal (HH) and Horizontal-Vertical (HV) Polarised Satellite Aperture Radar (SAR) data. The novelty of the proposed project is combined use of the Back-scattering Coefficients (Sigma Naught) and the Coherence. It uses Water Cloud Model (WCM). The approaches use two main steps. (a) Extraction of the different forest parameter data from the Product.xml, BAND-META file and from Grid-xxx.txt file come with the HH & HV polarized data from the ISRO (Indian Space Research Centre). These file contains the required parameter during height estimation. (b) Calculation of the Vegetation and Ground Backscattering, Coherence and other Forest Parameters. (c) Classification of Forest Types using the ENVI 5.0 Tool and ROI (Region of Interest) calculation.

Keywords: RISAT-1, classification, forest, SAR data

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Authors: H. Al-Jabli

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The research on the presence of heavy metals and bromate in drinking water is of immense scientific significance due to the potential risks these substances pose to public health. These contaminants are subject to regulatory limits outlined by the National Primary Drinking Water Regulations. Through a comprehensive analysis involving the compilation of existing data and the collection of new data via water sampling in residential areas of Kuwait, the aim is to create detailed maps illustrating the spatial distribution of these substances. Furthermore, the investigation will utilize GRAPHER software to explore correlations among different chemical parameters. By implementing rigorous scientific methodologies, the research will provide valuable insights for the Ministry of Electricity and Water and the Ministry of Health. These insights can inform evidence-based decision-making, facilitate the implementation of corrective measures, and support strategic planning for future infrastructure activities.

Keywords: heavy metals, bromate, ozonation, GIS

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Authors: Flavio Araujo, Livia Dias, Fabiolla Lima, Paulo Scalize, Antonio Albuquerque

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Water treatment residues (WTR) are solid waste produced during drinking water treatment and have recently been seen as a reusable material. The aim of this research was show how to use the residue generated in a Water Treatment Plant, located in Goiania, Brazil, following the considerations of the law of solid waste to obtain normative parameters and consider sustainable alternatives for reincorporation of the residues in the productive chain for manufacturing various materials construction. In order to reduce the environmental liabilities generated by sanitation companies and discontinue unsustainable forms of disposal. The analyzes performed: Granulometry, Scanning Electron Microscopy and X-Ray Diffraction demonstrated the potential application of residues to replace the soil and sand, because it has characteristics compatible with small aggregate and can be used as feedstock for the manufacture of materials as ceramic and soil-cement bricks, mortars, interlocking floors and concrete artifacts.

Keywords: residue, sustainable, water treatment plants, WTR, WTP

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Authors: Suresh Vidyasagar Chevuri, D. B. Karunakar Chevuri

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The main advantages of 'Metal Matrix Nano Composites (MMNCs)' include excellent mechanical performance, good wear resistance, low creep rate, etc. The method of fabrication of MMNCs is quite a challenge, which includes processing techniques like Spark Plasma Sintering (SPS), etc. The objective of the present work is to fabricate aluminum based MMNCs with the addition of small amounts of yttrium using Spark Plasma Sintering and to evaluate their mechanical and microstructure properties. Samples of 2024 AA with yttrium ranging from 0.1% to 0.5 wt% keeping 1 wt% TiB2 constant are fabricated by Spark Plasma Sintering (SPS). The mechanical property like hardness is determined using Vickers hardness testing machine. The metallurgical characterization of the samples is evaluated by Optical Microscopy (OM), Field Emission Scanning Electron Microscopy (FE-SEM) and X-Ray Diffraction (XRD). Unreinforced 2024 AA sample is also fabricated as a benchmark to compare its properties with that of the composite developed. It is found that the yttrium addition increases the above-mentioned properties to some extent and then decreases gradually when yttrium wt% increases beyond a point between 0.3 and 0.4 wt%. High density is achieved in the samples fabricated by spark plasma sintering when compared to any other fabrication route, and uniform distribution of yttrium is observed.

Keywords: spark plasma sintering, 2024 AA, yttrium addition, microstructure characterization, mechanical properties

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Authors: Aline F. Marcon, Eduardo F. da Silva, Marina Bouzon

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The impact of lean management on environmental sustainability is the research line that receives the most attention from academicians. Therefore, the social dimension of sustainable development has so far received less attention. This paper aims to evaluate the impact of intra-plant lean manufacturing practices on social sustainability indicators extracted from the Global Reporting Initiative (GRI) parameters. The method is two-phased, including MCDM approach to uncover the most relevant practices regarding social performance and Interpretive Structural Modeling (ISM) method to reveal the structural relationship among lean practices. Professionals from the academic and industrial fields answered the questionnaires. From the results of this paper, it is possible to verify that practices such as “Safety Improvement Programs”, “Total Quality Management” and “Cross-functional Workforce” are the ones which have the most positive influence on the set of GRI social indicators.

Keywords: indicators, ISM, lean, social, sustainability

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Authors: S. S. Abdullahi, H. Musa, A. A. Salisu, A. Ismaila, A. H. Birniwa

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In this study the treated and untreated kenaf fiber reinforced unsaturated polyester conventional composites were prepared. Hand lay-up technique was used with dump-bell shaped mold. The kenaf bast fiber was retted enzymatically, washed, dried and combed with a nylon brush. A portion of the kenaf fiber was mercerized and treated with benzoylchloride prior to composite fabrication. Untreated kenaf fiber was also used to prepare the composites to serve as control. The cured composites were subjected to various mechanical testes, such as hardness test, impact test and tensile strength test. The results obtained indicated an increase in all the parameters tested with the fiber treatment. This is because the lignin, hemi-celluloses, pectin and other impurities were removed during alkaline treatment (i.e mercerization). This shows that, the durability of the natural cellulosic fibers to different composite applications can be achieved via fiber treatments.

Keywords: composite, kenaf fibre, reinforce, retted

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Authors: Ayesha Asif, Muhammad Zeeshan

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The sensitivity of hospital-microenvironments for all types of pollutants, due to the presence of patients with immune deficiencies, makes them complex indoor spaces. Keeping in view, this study investigated indoor air quality (IAQ) of two most sensitive places, i.e., operation theater (OT) and intensive care unit (ICU), of a publically managed hospital. Taking CO₂ concentration as air quality indicator and temperature (T) and relative humidity (RH) as thermal comfort parameters, continuous monitoring of the three variables was carried out. Measurements were recorded at an interval of 1 min for weekdays and weekends, including occupational and non-occupational hours. Outdoor T and RH measurements were also used in the analysis. Results show significant variation (p < 0.05) in CO₂, T and RH values over the day during weekdays while no significant variation (p > 0.05) have been observed during weekends of both the monitored sites. Maximum observed values of CO₂ in OT and ICU were found to be 2430 and 624 ppm, T as 24.7ºC and 28.9ºC and RH as 29.6% and 32.2% respectively.

Keywords: indoor air quality, CO₂ concentration, hospital building, comfort assessment

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Authors: Jiri Brozovsky

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Modulus of elasticity is one of the important parameters of construction materials, which considerably influence their deformation properties and which can also be determined by means of non-destructive test methods like ultrasonic pulse method. However, measurement results of ultrasonic pulse methods are influenced by various factors, one of which is the natural frequency of the transducers. The paper states knowledge about influence of natural frequency of the transducers (54; 82 and 150kHz) on ultrasonic pulse velocity and dynamic modulus of elasticity (Young's Dynamic modulus of elasticity). Differences between ultrasonic pulse velocity and dynamic modulus of elasticity were found with the same smallest dimension of test specimen in the direction of sounding and density their value decreases as the natural frequency of transducers grew.

Keywords: calcium silicate brick, ultrasonic pulse method, ultrasonic pulse velocity, dynamic modulus of elasticity

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Authors: Nagini Sabbineni, Rajini T. V. Kanth, B. V. Kiranmayee

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India’s economy primarily depends on agriculture yield growth and their allied agro industry products. The agriculture yield prediction is the toughest task for agricultural departments across the globe. The agriculture yield depends on various factors. Particularly countries like India, majority of agriculture growth depends on rain water, which is highly unpredictable. Agriculture growth depends on different parameters, namely Water, Nitrogen, Weather, Soil characteristics, Crop rotation, Soil moisture, Surface temperature and Rain water etc. In our paper, lot of Explorative Data Analysis is done and various predictive models were designed. Further various regression models like Linear, Multiple Linear, Non-linear models are tested for the effective prediction or the forecast of the agriculture yield for various crops in Andhra Pradesh and Telangana states.

Keywords: agriculture yield growth, agriculture yield prediction, explorative data analysis, predictive models, regression models

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Authors: Tareq AlNuaim, Mubashir Alam, Abdulrazaq Aldowesh

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The usage of micro-Unmanned Ariel Vehicles (UAVs) has witnessed an enormous increase recently. Detection of such drones became a necessity nowadays to prevent any harmful activities. Typically, such targets have low velocity and low Radar Cross Section (RCS), making them indistinguishable from clutter and phase noise. Multiple-Input Multiple-Output (MIMO) Radars have many potentials; it increases the degrees of freedom on both transmit and receive ends. Such architecture allows for flexibility in operation, through utilizing the direct access to every element in the transmit/ receive array. MIMO systems allow for several array processing techniques, permitting the system to stare at targets for longer times, which improves the Doppler resolution. In this paper, a 2×2 MIMO radar prototype is developed using Software Defined Radio (SDR) technology, and its performance is evaluated against a slow-moving low radar cross section micro-UAV used by hobbyists. Radar cross section simulations were carried out using FEKO simulator, achieving an average of -14.42 dBsm at S-band. The developed prototype was experimentally evaluated achieving more than 300 meters of detection range for a DJI Mavic pro-drone

Keywords: digital beamforming, drone detection, micro-UAV, MIMO, phased array

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Authors: S. Nigri, R. Oumeddour, F. Djazi

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The inhibition of the corrosion of copper in 1 M HNO3 solution by oleic acid was investigated by weight loss measurement, potentiodynamic polarization and scanning electron microscope (SEM) studies. The experimental results have showed that this compound revealed a good corrosion inhibition and the inhibition efficiency is increased with the inhibitor concentration to reach 98%. The results obtained revealed that the adsorption of the inhibitor molecule onto metal surface is found to obey Langmuir adsorption isotherm. The temperature effect on the corrosion behavior of copper in 1 M HNO3 without and with inhibitor at different concentration was studied in the temperature range from 303 to 333 K and the kinetic parameters activation such as Ea, ∆Ha and ∆Sa were evaluated. Tafel plot analysis revealed that oleic acid acts as a mixed type inhibitor. SEM analysis substantiated the formation of protective layer over the copper surface.

Keywords: oleic acid, weight loss, electrochemical measurement, SEM analysis

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Authors: Laidi Maamar, Hanini Salah

Abstract:

The present work investigates the potential of artificial neural network (ANN) model to predict the horizontal global solar radiation (HGSR). The ANN is developed and optimized using three years meteorological database from 2011 to 2013 available at the meteorological station of Blida (Blida 1 university, Algeria, Latitude 36.5°, Longitude 2.81° and 163 m above mean sea level). Optimal configuration of the ANN model has been determined by minimizing the Root Means Square Error (RMSE) and maximizing the correlation coefficient (R2) between observed and predicted data with the ANN model. To select the best ANN architecture, we have conducted several tests by using different combinations of parameters. A two-layer ANN model with six hidden neurons has been found as an optimal topology with (RMSE=4.036 W/m²) and (R²=0.999). A graphical user interface (GUI), was designed based on the best network structure and training algorithm, to enhance the users’ friendliness application of the model.

Keywords: artificial neural network, global solar radiation, solar energy, prediction, Algeria

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Authors: V. J. Pillewan, D. N. Raut, K. N. Patil, D. K. Shinde

Abstract:

Forging, milling, turning, grinding and shaping etc. are the various industrial manufacturing processes which generate the metal waste. Grinding is extensively used in the finishing operation. The waste generated contains significant impurities apart from the metal particles. Due to these significant impurities, it becomes difficult to process and gets usually dumped in the landfills which create environmental problems. Therefore, it becomes essential to reuse metal waste to create value added products. Powder injection molding process is used for producing the porous metal matrix framework. This paper discusses the presented design of the porous framework to be used for the liquid filter application. Different parameters are optimized to obtain the better strength framework with variable porosity. Carbon nanotubes are used as reinforcing materials to enhance the strength of the metal matrix framework.

Keywords: grinding waste, powder injection molding (PIM), carbon nanotubes (CNTs), matrix composites (MMCs)

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