Search results for: input processing

Authors: Abdelrahman Taha, Niloofar Malekghaini, Hamed Ebrahimian, Ramin Motamed

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This paper compares the substructure and direct methods for soil-structure interaction (SSI) analysis in the time domain. In the substructure SSI method, the soil domain is replaced by a set of springs and dashpots, also referred to as the impedance function, derived through the study of the behavior of a massless rigid foundation. The impedance function is inherently frequency dependent, i.e., it varies as a function of the frequency content of the structural response. To use the frequency-dependent impedance function for time-domain SSI analysis, the impedance function is approximated at the fundamental frequency of the structure-soil system. To explore the potential limitations of the substructure modeling process, a two-dimensional reinforced concrete frame structure is modeled using substructure and direct methods in this study. The results show discrepancies between the simulated responses of the substructure and the direct approaches. To isolate the effects of higher modal responses, the same study is repeated using a harmonic input motion, in which a similar discrepancy is still observed between the substructure and direct approaches. It is concluded that the main source of discrepancy between the substructure and direct SSI approaches is likely attributed to the way the impedance functions are calculated, i.e., assuming a massless rigid foundation without considering the presence of the superstructure. Hence, a refined impedance function, considering the presence of the superstructure, shall be developed. This refined impedance function is expected to significantly improve the simulation accuracy of the substructure approach for structural systems whose behavior is dominated by the fundamental mode response.

Keywords: direct approach, impedance function, soil-structure interaction, substructure approach

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Authors: W. Riahi, M. L. Mansour

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Using tools of data processing such as geographic information system (GIS) for the contribution of the space management becomes more and more frequent. It allows collecting and analyzing diverse natural information relative to the same territory. Space technologies play crucial role in agricultural phenomenon analysis. For this, satellite images treatment were used to classify vegetation density and particularly agricultural areas in Setif province by making recourse to the Normalized Difference Vegetation Index (NDVI). This step was completed by mapping agricultural activities of the province by using ArcGIS.10 software in order to display an overall view and to realize spatial analysis of various themes combined between them which are chosen according to their strategic importance in different thematic maps. The synthesis map elaborately showed that geographic information system can contribute significantly to agricultural management by describing potentialities and development opportunities of production systems and agricultural sectors.

Keywords: GIS, satellite image, agriculture, NDVI, thematic map

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Authors: Hao-Hsi Tseng, Hsin-Yun Lee

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The Most Advantageous Tender (MAT) has been criticized for its susceptibility to dictatorial situations and for its processing of same score, same rank issues. This study applies the four criteria from Arrow's Impossibility Theorem to construct a mechanism for revealing illegitimate scores in scoring methods. While commonly be used to improve on problems resulting from extreme scores, ranking methods hide significant defects, adversely affecting selection fairness. To address these shortcomings, this study relies mainly on the overall evaluated score method, using standardized scores plus normal cumulative distribution function conversion to calculate the evaluation of vender preference. This allows for free score evaluations, which reduces the influence of dictatorial behavior and avoiding same score, same rank issues. Large-scale simulations confirm that this method outperforms currently used methods using the Impossibility Theorem.

Keywords: Arrow’s impossibility theorem, cumulative normal distribution function, most advantageous tender, scoring method

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Authors: Anil Giri, Kyle Lovercamp, Sankalp Sharma

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Farm level incomes fluctuate significantly due to extreme weather events such as drought. In the light of recent extreme weather events it is important to understand the implications of extreme weather events, flood and drought, on farm level incomes. This study examines the variation in farm level incomes for the United States in drought and no- drought years. Factoring heterogeneity in different enterprises (crop, livestock) and geography this paper analyzes the impact of drought in farm level incomes at state and national level. Livestock industry seems to be affected more by the lag in production of input feed for production, crops, as preliminary results show. Furthermore, preliminary results also show that while crop producers are not affected much due to drought, as price and quantity effect worked on opposite direction with same magnitude, that was not the case for livestock and horticulture enterprises. Results also showed that even when price effect was not as high the crop insurance component helped absorb much of shock for crop producers. Finally, the effect was heterogeneous for different states more on the coastal states compared Midwest region. This study should generate a lot of interest from policy makers across the world as some countries are actively seeking to increase subsidies in their agriculture sector. This study shows how subsidies absorb the shocks for one enterprise more than others. Finally, this paper should also be able to give an insight to economists to design/recommend policies such that it is optimal given the production level of different enterprises in different countries.

Keywords: farm level income, United States, crop, livestock

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Authors: H. Lee, J. Park

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In this present study, for the first time, we retrieved the Formaldehyde (HCHO) Vertical Column Density (HCHOVCD) using Pandora instruments in Seoul, a megacity in northeast Asia, for the period between 2012 and 2014 and investigated the temporal characteristics of HCHOVCD. HCHO Slant Column Density (HCHOSCD) was obtained using the Differential Optical Absorption Spectroscopy (DOAS) method. HCHOSCD was converted to HCHOVCD using geometric Air Mass Factor (AMFG) as Pandora is the direct-sun measurement. The HCHOVCDs is low at 12:00 Local Time (LT) and is high in the morning (10:00 LT) and late afternoon (16:00 LT) except for winter. The maximum (minimum) values of Pandora HCHOVCD are 2.68×1016 (1.63×10¹⁶), 3.19×10¹⁶ (2.23×10¹⁶), 2.00×10¹⁶ (1.26×10¹⁶), and 1.63×10¹⁶ (0.82×10¹⁶) molecules cm⁻² in spring, summer, autumn, and winter, respectively. In terms of seasonal variations, HCHOVCD was high in summer and low in winter which implies that photo-oxidation plays an important role in HCHO production in Seoul. In comparison with the Ozone Monitoring Instrument (OMI) measurements, the HCHOVCDs from the OMI are lower than those from Pandora. The correlation coefficient (R) between monthly HCHOVCDs values from Pandora and OMI is 0.61, with slop of 0.35. Furthermore, to understand HCHO mixing ratio within Planetary Boundary Layer (PBL) in Seoul, we converted Pandora HCHOVCDs to HCHO mixing ratio in the PBL using several meteorological input data from the Atmospheric InfraRed Sounder (AIRS). Seasonal HCHO mixing ratio in PBL converted from Pandora (OMI) HCHOVCDs are estimated to be 6.57 (5.17), 7.08 (6.68), 7.60 (4.70), and 5.00 (4.76) ppbv in spring, summer, autumn, and winter, respectively.

Keywords: formaldehyde, OMI, Pandora, remote sensing

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Authors: Inas Kamel, Noor Z. Habib

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Utilizing construction and demolition wastes in hotmix asphalt (HMA) pavement construction can reduce the adverse environmental effect of its inadequate disposal and reduce the pressure of extracting and processing mineral aggregates (MA). This study aims to examine the viability of replacing MA by recycled construction and demolition waste aggregates (RCDWA) in the wearing course of asphaltic concrete (AC) pavements without compromising its loadbearing capacity. The Marshall Method was used to evaluate the performance of AC wearing course specimens by replacing MA by 10%, 20% and 30% RCDWA. Grade 60/70 bitumen was used in the range 3.0-5.5%, with 05% increments, to generate the optimum bitumen content (OBC). From the volumetric analysis and test property curves, the mixture containing 20% RCDWA was chosen as the preferred mix at 5.1% OBC. It possessed a 10% increase in Marshall Stability compared to the reference specimen, containing 100% MA, and a 6% increase in Marshall flow.

Keywords: aggregate, asphaltic concrete, Marshall method, optimum bitumen content, recycled construction and demolition waste

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Authors: Muhamad Sani Buang, Shahrul Azam Abdullah, Juri Saedon

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There is not much effective guideline on development of design parameters selection on springback for advanced high strength steel sheet metal in U-channel process during cold forming process. This paper presents the development of predictive model for springback in U-channel process on advanced high strength steel sheet employing Response Surface Methodology (RSM). The experimental was performed on dual phase steel sheet, DP590 in U-channel forming process while design of experiment (DoE) approach was used to investigates the effects of four factors namely blank holder force (BHF), clearance (C) and punch travel (Tp) and rolling direction (R) were used as input parameters using two level values by applying Full Factorial design (24). From a statistical analysis of variant (ANOVA), result showed that blank holder force (BHF), clearance (C) and punch travel (Tp) displayed significant effect on springback of flange angle (β2) and wall opening angle (β1), while rolling direction (R) factor is insignificant. The significant parameters are optimized in order to reduce the springback behavior using Central Composite Design (CCD) in RSM and the optimum parameters were determined. A regression model for springback was developed. The effect of individual parameters and their response was also evaluated. The results obtained from optimum model are in agreement with the experimental values

Keywords: advance high strength steel, u-channel process, springback, design of experiment, optimization, response surface methodology (rsm)

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Authors: Venkatesan Sundaramoorthy

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The field of ceramics has undergone a remarkable transformation with the advent of additive manufacturing technologies. This comprehensive review explores the mechanical properties of additively manufactured ceramic components, focusing on key materials such as Alumina, Zirconia, and Silicon Carbide. The study delves into various authors' review technology into the various additive manufacturing techniques, including Stereolithography, Powder Bed Fusion, and Binder Jetting, highlighting their advantages and challenges. It provides a detailed analysis of the mechanical properties of these ceramics, offering insights into their hardness, strength, fracture toughness, and thermal conductivity. Factors affecting mechanical properties, such as microstructure and post-processing, are thoroughly examined. Recent advancements and future directions in 3D-printed ceramics are discussed, showcasing the potential for further optimization and innovation. This review underscores the profound implications of additive manufacturing for ceramics in industries such as aerospace, healthcare, and electronics, ushering in a new era of engineering and design possibilities for ceramic components.

Keywords: mechanical properties, additive manufacturing, ceramic materials, PBF

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Authors: Nurbanu Guzey, S. Jagannathan

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Locating radio controlled (RC) devices using their unintended emissions has a great interest considering security concerns. Weak nature of these emissions requires near field localization approach since it is hard to detect these signals in far field region of array. Instead of only angle estimation, near field localization also requires range estimation of the source which makes this method more complicated than far field models. Challenges of locating such devices in a near field region and real time environment are analyzed in this paper. An ESPRIT like near field localization scheme is utilized for both angle and range estimation. 1-D search with symmetric subarrays is provided. Two 7 element uniform linear antenna arrays (ULA) are employed for locating RC source. Experiment results of location estimation for one unintended emitting walkie-talkie for different positions are given.

Keywords: localization, angle of arrival (AoA), range estimation, array signal processing, ESPRIT, Uniform Linear Array (ULA)

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Authors: Eduwin Eko Franjaya, Yesi Hendriani Supartoyo

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Integrated farming with LEISA concept as one of the systems or sustainable farming techniques in agriculture has provided opportunities to increase farmers' income. This system also has a positive impact on the environment. However, the development of integrated farming is still on a small scale/site scale. Development on a larger scale is necessary considering to the number of potential resources in the village that can be integrated each other. The aim of this research is to develop an integrated farming landscape on small scale that has been done in previous study, into the village scale. The method used in this study follows the rules of scientific planning in landscape architecture. The initial phase begins with an inventory of the existing condition of the village, by conducting a survey. The second stage is analysis of potential and constraints in the village based on the results of a survey that has been done before. The next stage is concept-making that consists of basic concept, design concept, and development concept. The basic concept is integrated farming based on LEISA. The design concept is based on commodities that are developed in the village. The development concept consists of space concept, circulation concept, the concept of vegetation and commodities, and the concept of the production system. The last stage is planning process which produces Site Plan based on LEISA on village scale. Site Plan is also the end product of this research. The results of this research are expected to increase the income and welfare of the farmers in the village, and can be develop into a tourism area of integrated farming.

Keywords: integrated farming, LEISA, site plan, sustainable agriculture

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Authors: Aleksandr Medvedev, Zakhar Slukovsii

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Waterbodies, which are located either within urban areas or nearby towns, permanently undergo anthropogenic load. The extent of the load can be determined via investigations of chemical composition of both water and sediments. Lakes, as a rule, are considered as a landscape depressions, hence they are capable of natural material accumulating, which has been delivered from the catchment area through rivers as well as temporary flows. As a result, lacustrine sediments (especially closed-basin lakes sediments) are considered as perfect archives, which are served for reconstructing past sedimentation process, assessment of the modern contamination level, and prognostication of possible ways of changing in the future. The purposes of the survey are to define a heavy metals content in lake sediments cores, which were retrieved from four urban lakes located in the southern part of Karelia Republic, and to ascertain the main sources of heavy metals input to these waterbodies. It is really crucial to be aware of heavy metals content in environment, because chemical composition of a landscape may have a significant effect on living organisms and people’s health. Sediment columns were sampled in a field with 2-cm intervals by a gravitational corer called «Limnos». The sediment samples were analyzed by inductively coupled plasma spectrometry (ICP MS) for 8 chemical elements (Pb, Cd, Zn, Cr, Ni, Cu, Mn, V). The highest concentrations of trace elements were established in the upper and middle layers of the cores. It has also been ascertained that the extent of contamination mostly depends on a remoteness of a lake from various pollution sources and features of the sources.

Keywords: bottom sediments, environmental pollution, heavy metals, lakes

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Authors: Brenden M. Shutt, Lubjana Beshaj, Paul L. Goethals, Ambrose Kam

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Communication security is of particular interest to military data networks. A relatively novel approach to network security is blockchain, a cryptographically secured distribution ledger with a decentralized consensus mechanism for data transaction processing. Recent advances in blockchain technology have proposed new techniques for both data validation and trust management, as well as different frameworks for managing dataflow. The purpose of this work is to test the feasibility of different blockchain architectures as applied to military command and control networks. Various architectures are tested through discrete-event simulation and the feasibility is determined based upon a blockchain design’s ability to maintain long-term stable performance at industry standards of throughput, network latency, and security. This work proposes a consortium blockchain architecture with a computationally inexpensive consensus mechanism, one that leverages a Proof-of-Identity (PoI) concept and a reputation management mechanism.

Keywords: blockchain, consensus mechanism, discrete-event simulation, fog computing

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Authors: Kishor K. Podh

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Agriculture in India treated as the backbone of its economy. It has been accommodated to more than 60 percent of its population as their economic base, directly or indirectly for their livelihood. Besides its significant role, the sharp declines in public investment and development in agriculture have witnessed. After independence Hirakud Command Area (HCA) popularly known as the Rice Bowl of State, due to its fabulous production and provides food to a larger part of the state. After the great green revolution and then liberalization agrarian families become overburden with the loan. They started working as wage laborer in other’s field and non-farm sectors to overcome from the uninvited indebtedness. Although production increases at present, still the youths of this area migrating outsides for job Tamil Nadu, Andhra Pradesh, Maharashtra, Gujarat, etc. Because agriculture no longer remains a profitable occupation; increasing input costs, the uncertainty of crops, improper pricing, poor marketing, etc. compels the youths to choose the alternative occupations. They work in industries (under contractors), construction workers and other menial jobs due to lack of skills and degrees. Kharmunda a village within HCA selected as per the convenience and 100 youth migrants were interviewed purposively selected who were present during data collection. The study analyses the types of migration; its similarity/differentiations, its determining factors, in tow geographical areas of Western Odisha, i.e., single crop and double crops in relation to agricultural situations.

Keywords: agrarian distress, double crops, Hirakud Command Area, indebtedness, out migration, Western Odisha

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Authors: Aaron J. Small, Craig A. Fletcher

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This study investigates the effect of closed circuit television (CCTV) image patch layout on performance of a simulated train-platform departure task. The within-subjects experimental design measures target detection rate and response latency during a CCTV visual search task conducted as part of the procedure for safe train dispatch. Three interface designs were developed by manipulating CCTV image patch layout. Eye movements, perceived workload and system usability were measured across experimental conditions. Task performance was compared to identify significant differences between conditions. The results of this study have not been determined.

Keywords: rail human factors, workload, closed circuit television, platform departure, attention, information processing, interface design

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Authors: Fatima Gouiferda

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Uncertainty and competitiveness are changing firm’s environment to become more complicated. The competition is moving to supply chain’s level, and firms need to collaborate and innovate to survive. In the current economy, common efforts between organizations and developing new capacities mutually are the key resources in gaining collaborative advantage and enhancing supply chain performance. The purpose of this paper is to explore different practices of collaboration activities that exist in the pharmaceutical industry of Morocco. Also, to inquire how these practices affect supply chain performance. The exploration is based on interpretativism research paradigm. Data were collected through semi-structured interviews from supply chain practitioners. Qualitative data was analyzed via Iramuteq software to explore different themes of the study.The findings include descriptive analysis as a result of data processing using Iramuteq. It also encompasses the content analysis of the themes extracted from interviews.

Keywords: inter-firm relationships, collaboration, supply chain innovation, morocco

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Authors: M. Duran Toksari, Berrin Ucarkus

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In this paper, we propose two algorithms to optimally solve makespan and total completion time scheduling problems with learning effect and job dependent delivery times in a single machine environment. The delivery time is the extra time to eliminate adverse effect between the main processing and delivery to the customer. In this paper, we introduce the job dependent delivery times for some single machine scheduling problems with position dependent learning effect, which are makespan are total completion. The results with respect to two algorithms proposed for solving of the each problem are compared with LINGO solutions for 50-jobs, 100-jobs and 150-jobs problems. The proposed algorithms can find the same results in shorter time.

Keywords: delivery Times, learning effect, makespan, scheduling, total completion time

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Authors: Adel Ahmadi Hosseini, Fatemeh Tavanaei, Alessandro Navarra, Ferri Hassani

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Mining engineering, as a part of geoscience, must address modern concerns. Traditional mining methods incorporate drill and blast technologies, which are followed by different issues, including excessive noise, vibration, air pollution, and safety hazards. Over the past two decades, mining engineers have sought alternative solutions to move from drill and blast to continuous methods to prevent such issues and improve sustainability in mining. Among the suggested methods, microwave treatment has shown promising results by creating micro/macro cracks in the rock structure prior to the operations. This research utilizes an energy-based analysis methodology to evaluate the efficiency of the microwave treatment in improving mining operations. The data analysis shows that increasing the input microwave energy dosage intensifies the rock damage. However, this approach can decrease the energy efficiency of the method by more than 50% in some cases. In this study, rock samples were treated with three power levels (3 kW, 7 kW, and 12 kW) and two energy dosages (20 kWh/t and 50 kWh/t), resulting in six conditions. To evaluate the impact of microwave treatment on the geomechanical behavior of the rocks, Unconfined Compressive Strength (UCS) tests were conducted on the microwave-treated samples, yielding stress-strain curves. Using the stress-strain curves, the effect of the different powers and energy dosages of microwaves are discussed. This research shows the potential of using microwave treatment to lead the industry to more sustainable mining.

Keywords: microwave treatment, microwave energy dosage, sustainable mining, rock fragmentation

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Authors: N. Bouhamou, F. Mostefa, A. Mebrouki, N. Belas

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Every year, millions of cube meters are dredged from dams and restraints as an entertaining and prevention procedure all over the world. These dredged sediments are considered as natural waste leading to an environmental, ecological and even an economical problem in their processing and deposing. Nevertheless, in the context of the sustainable development policy, a way of management is opened aiming to the valorization of sediments as a building material and particularly as a new binder that can be industrially exploited and that improve the physical, chemical and mechanical characteristics of the concrete. This study is a part of the research works realized in the civil engineering department at the university of Mostaganem (Algeria), on the impact of the dredged mud of Fergoug dam on the behaviour of self-consolidating concrete in fresh and hardened state, such as the mechanical performance of SCC and its impact on the differed deformations (shrinkage). The work aims to valorize this mud in SCC and to show eventual interactions between constituents. The results obtained presents a good perspectives in order to perform SCC based in calcined mud.

Keywords: sediment, calcination, reuse, self-consolidating concrete, fresh state, hard state, shrinkage

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Authors: Assma Azeroual, Karim Afdel, Mohamed El Hajji, Hassan Douzi

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Key frame extraction methods select the most representative frames of a video, which can be used in different areas of video processing such as video retrieval, video summary, and video indexing. In this paper we present a novel approach for extracting key frames from video sequences. The frame is characterized uniquely by his contours which are represented by the dominant blocks. These dominant blocks are located on the contours and its near textures. When the video frames have a noticeable changement, its dominant blocks changed, then we can extracte a key frame. The dominant blocks of every frame is computed, and then feature vectors are extracted from the dominant blocks image of each frame and arranged in a feature matrix. Singular Value Decomposition is used to calculate sliding windows ranks of those matrices. Finally the computed ranks are traced and then we are able to extract key frames of a video. Experimental results show that the proposed approach is robust against a large range of digital effects used during shot transition.

Keywords: FSDWT, key frame extraction, shot detection, singular value decomposition

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Authors: Milda A. Cruz-Huaranga, Natalí Carbo-Bustinza, Javier Linkolk López-Gonzales, K. Depaz, Gina M. Tito T., Soledad Torres-Calderón

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The objective of this study was to improve water quality in the “La Mansión” pond in order to irrigate green spaces on the Peruvian Union University campus (Lima, Peru) using the aquatic species Eichhornia Crassipes. Furthermore, tree trimming and cleaning activities were performed that reduced water pollution caused by organic deposits and feathers from wild birds. The impaired waterbody is located on the campus of the Peruvian Union University, 580 meters above sea level, with a volume of 6,405.336 m3, an area of 3,050.16 m2, 256.81 m perimeter, and 0.12 m3/s input flow. Seven 1.8 m2 floating systems were implemented, with 12 common water hyacinth plants in each system. Before implementing this system, a water quality analysis was performed to analyse the physical-chemical, microbiological, and organoleptic parameters. The pre-analysis revealed the pond’s critical condition, with electrical conductivity: 556 mg/l; phosphate: < 0.5; pH: 7.06; total solids: 412 mg/l; arsenic: <0.01; lead: 0.115; BOD5: 14; COD: 16.94; dissolved oxygen: 13; total coliforms: 24000 MCL/100 ml; and thermo-tolerant coliforms: 11000 MCL/100 ml. After implementing the system, the following results were obtained: EC: 495 mg/l; DO:9.2 mg/l; TS: 235 mg/l; BOD5: 7.7; COD: 8.47; Pb: 0.001 mg/l; TC: 460 MCL/100 ml; FC: 240 MCL/100 ml. Thus, we confirmed that the system is 78.79% efficient regarding the Peruvian ECA (Environmental Quality Standards) established for water according to DS #015-2015-MINAM. Therefore, the water is suitable for plant irrigation. Finally, we concluded that treating wastewater with the species Eichhornia Crassipes is efficient since an improvement was achieved in the impaired waterbody.

Keywords: Eichhornia crassipes, plantlets, cleaning, impaired waterbody, pond

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Authors: Payam Haghparast, Mikhail V. Sorin, Hakim Nesreddine

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The complex oblique shock phenomenon can be simply assumed as a normal shock at the constant area section to simulate a sharp pressure increase and velocity decrease in 1-D thermodynamic models. The assumed normal shock location is one of the greatest sources of error in ejector thermodynamic models. Most researchers consider an arbitrary location without justifying it. Our study compares the effect of normal shock place on ejector dimensions in 1-D models. To this aim, two different ejector experimental test benches, a constant area-mixing ejector (CAM) and a constant pressure-mixing (CPM) are considered, with different known geometries, operating conditions and working fluids (R245fa, R141b). In the first step, in order to evaluate the real value of the efficiencies in the different ejector parts and critical back pressure, a CFD model was built and validated by experimental data for two types of ejectors. These reference data are then used as input to the 1D model to calculate the lengths and the diameters of the ejectors. Afterwards, the design output geometry calculated by the 1D model is compared directly with the corresponding experimental geometry. It was found that there is a good agreement between the ejector dimensions obtained by the 1D model, for both CAM and CPM, with experimental ejector data. Furthermore, it is shown that normal shock place affects only the constant area length as it is proven that the inlet normal shock assumption results in more accurate length. Taking into account previous 1D models, the results suggest the use of the assumed normal shock location at the inlet of the constant area duct to design the supersonic ejectors.

Keywords: 1D model, constant area-mixing, constant pressure-mixing, normal shock location, ejector dimensions

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Authors: Jozef Mindas, Jaroslav Skvarenina, Jana Skvareninova

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Study of the effects of climate change on Norway Spruce (Picea abies) forests has mainly focused on the diversity of tree species diversity of tree species as a result of the ability of species to tolerate temperature and moisture changes as well as some effects of disturbance regime changes. The tree species’ diversity changes in spruce forests due to climate change have been analyzed via gap model. Forest gap model is a dynamic model for calculation basic characteristics of individual forest trees. Input ecological data for model calculations have been taken from the permanent research plots located in primeval forests in mountainous regions in Slovakia. The results of regional scenarios of the climatic change for the territory of Slovakia have been used, from which the values are according to the CGCM3.1 (global) model, KNMI and MPI (regional) models. Model results for conditions of the climate change scenarios suggest a shift of the upper forest limit to the region of the present subalpine zone, in supramontane zone. N. spruce representation will decrease at the expense of beech and precious broadleaved species (Acer sp., Sorbus sp., Fraxinus sp.). The most significant tree species diversity changes have been identified for the upper tree line and current belt of dwarf pine (Pinus mugo) occurrence. The results have been also discussed in relation to most important disturbances (wind storms, snow and ice storms) and phenological changes which consequences are little known. Special discussion is focused on biomass production changes in relation to carbon storage diversity in different carbon pools.

Keywords: biodiversity, climate change, Norway spruce forests, gap model

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Authors: Parthiban Srinivasan

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With recent advances in computational power and access to enough data in biosciences, artificial intelligence methods are increasingly being used in drug discovery research. These methods are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Our goal is to develop a model that accurately predicts biological activity and toxicity parameters for novel compounds. We have compiled a robust library of over 150,000 chemical compounds with different pharmacological properties from literature and public domain databases. The compounds are stored in simplified molecular-input line-entry system (SMILES), a commonly used text encoding for organic molecules. We utilize an automated process to generate an array of numerical descriptors (features) for each molecule. Redundant and irrelevant descriptors are eliminated iteratively. Our prediction engine is based on a portfolio of machine learning algorithms. We found Random Forest algorithm to be a better choice for this analysis. We captured non-linear relationship in the data and formed a prediction model with reasonable accuracy by averaging across a large number of randomized decision trees. Our next step is to apply deep neural network (DNN) algorithm to predict the biological activity and toxicity properties. We expect the DNN algorithm to give better results and improve the accuracy of the prediction. This presentation will review all these prominent machine learning and deep learning methods, our implementation protocols and discuss these techniques for their usefulness in biomedical and health informatics.

Keywords: deep learning, drug discovery, health informatics, machine learning, toxicity prediction

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Authors: Marina Shakleina, Konstantin Shaklein, Stanislav Yakiro

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The digitalization of modern human life over the last decade has facilitated the acquisition, storage, and processing of data, which are used to detect changes in consumer preferences and to improve the internal efficiency of the production process. This emerging trend has attracted academic interest in the use of big data in research. The study focuses on modeling the social comfort of the Russian population for the period 2010-2021 using big data. Big data provides enormous opportunities for understanding human interactions at the scale of society with plenty of space and time dynamics. One of the most popular big data sources is Google Trends. The methodology for assessing social comfort using big data involves several steps: 1. 574 words were selected based on the Harvard IV-4 Dictionary adjusted to fit the reality of everyday Russian life. The set of keywords was further cleansed by excluding queries consisting of verbs and words with several lexical meanings. 2. Search queries were processed to ensure comparability of results: the transformation of data to a 10-point scale, elimination of popularity peaks, detrending, and deseasoning. The proposed methodology for keyword search and Google Trends processing was implemented in the form of a script in the Python programming language. 3. Block and summary integral indicators of social comfort were constructed using the first modified principal component resulting in weighting coefficients values of block components. According to the study, social comfort is described by 12 blocks: ‘health’, ‘education’, ‘social support’, ‘financial situation’, ‘employment’, ‘housing’, ‘ethical norms’, ‘security’, ‘political stability’, ‘leisure’, ‘environment’, ‘infrastructure’. According to the model, the summary integral indicator increased by 54% and was 4.631 points; the average annual rate was 3.6%, which is higher than the rate of economic growth by 2.7 p.p. The value of the indicator describing social comfort in Russia is determined by 26% by ‘social support’, 24% by ‘education’, 12% by ‘infrastructure’, 10% by ‘leisure’, and the remaining 28% by others. Among 25% of the most popular searches, 85% are of negative nature and are mainly related to the blocks ‘security’, ‘political stability’, ‘health’, for example, ‘crime rate’, ‘vulnerability’. Among the 25% most unpopular queries, 99% of the queries were positive and mostly related to the blocks ‘ethical norms’, ‘education’, ‘employment’, for example, ‘social package’, ‘recycling’. In conclusion, the introduction of the latent category ‘social comfort’ into the scientific vocabulary deepens the theory of the quality of life of the population in terms of the study of the involvement of an individual in the society and expanding the subjective aspect of the measurements of various indicators. Integral assessment of social comfort demonstrates the overall picture of the development of the phenomenon over time and space and quantitatively evaluates ongoing socio-economic policy. The application of big data in the assessment of latent categories gives stable results, which opens up possibilities for their practical implementation.

Keywords: big data, Google trends, integral indicator, social comfort

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Authors: Tanmay Bisen, Aastha Shayla, Susham Biswas

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Oil spills from tankers can cause significant harm to the environment and local communities, as well as have economic consequences. Early predictions of oil spills can help to minimize these impacts. Our proposed system uses machine learning and neural networks to predict potential oil spills by monitoring data from ship Automatic Identification Systems (AIS). The model analyzes ship movements, speeds, and changes in direction to identify patterns that deviate from the norm and could indicate a potential spill. Our approach not only identifies anomalies but also predicts spills before they occur, providing early detection and mitigation measures. This can prevent or minimize damage to the reputation of the company responsible and the country where the spill takes place. The model's performance on the MV Wakashio oil spill provides insight into its ability to detect and respond to real-world oil spills, highlighting areas for improvement and further research.

Keywords: Anomaly Detection, Oil Spill Prediction, Machine Learning, Image Processing, Graph Neural Network (GNN)

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Authors: Ciro Cursio, Pio Luigi Cursio, Giulia Cursio, Isabella Chiardi, Luigi Cursio

Abstract:

Introduction: Full-face aesthetic treatments often present a difficult task: since different patients possess different anatomical and tissue characteristics, there is no guarantee that the same treatment will have the same effect on multiple patients; additionally, full-face rejuvenation and beautification treatments require not only a high degree of technical skill but also the ability to choose the right product for each area and a keen artistic eye. Method: We present an artificial intelligence-based algorithm that can generate realistic post-treatment 3D models based on the patient’s requests together with the doctor’s input. These 3-dimensional predictions can be used by the practitioner for two purposes: firstly, they help ensure that the patient and the doctor are completely aligned on the expectations of the treatment; secondly, the doctor can use them as a visual guide, obtaining a natural result that would normally stem from the practitioner's artistic skills. To this end, the algorithm is able to predict injection zones, the type and quantity of hyaluronic acid, the injection depth, and the technique to use. Results: Our innovation consists in providing an objective visual representation of the patient that is helpful in the patient-doctor dialogue. The patient, based on this information, can express her desire to undergo a specific treatment or make changes to the therapeutic plan. In short, the patient becomes an active agent in the choices made before the treatment. Conclusion: We believe that this algorithm will reveal itself as a useful tool in the pre-treatment decision-making process to prevent both the patient and the doctor from making a leap into the dark.

Keywords: hyaluronic acid, fillers, full face, artificial intelligence, 3D

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Authors: Mykhailo Moskalets, Pablo Burset, Benjamin Roussel, Christian Flindt

Abstract:

The single-particle injection from the Andreev level and how such injection is simulated using a voltage pulse are discussed. Recently, high-speed quantum-coherent electron sources injecting one- to few-particle excitations into the Fermi sea have been experimentally realized. The main obstacle to using these excitations as flying qubits for quantum-information processing purposes is decoherence due to the long-range Coulomb interaction. An obvious way to get around this difficulty is to employ electrically neutral excitations. Here it is discussed how such excitations can be generated on-demand using the same injection principles as in existing electron sources. Namely, with the help of a voltage pulse of a certain shape applied to the Fermi sea or using a driven quantum dot with superconducting correlations. The advantage of the latter approach is the possibility of varying the electron-hole content in the excitation and the possibility of creating a charge-neutral but spin-dipole excitation.

Keywords: Andreev level, on-demand, single-electron, spin-dipole

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Authors: Sachin Singh, Thomas Penzel, Dinesh Nandan

Abstract:

Accurate identification of Sleep Apnea Hypopnea Syndrom Diagnosis is difficult problem for human expert because of variability among persons and unwanted noise. This paper proposes the diagonosis of Sleep Apnea Hypopnea Syndrome (SAHS) using airflow, ECG, Pulse and SaO2 signals. The features of each type of these signals are extracted using statistical methods and ANN learning methods. These extracted features are used to approximate the patient's Apnea Hypopnea Index(AHI) using sample signals in model. Advance signal processing is also applied to snore sound signal to locate snore event and SaO2 signal is used to support whether determined snore event is true or noise. Finally, Apnea Hypopnea Index (AHI) event is calculated as per true snore event detected. Experiment results shows that the sensitivity can reach up to 96% and specificity to 96% as AHI greater than equal to 5.

Keywords: neural network, AHI, statistical methods, autoregressive models

Procedia PDF Downloads 115

Authors: Taekyong Lee, Joon-Young Kim, Jae-Min Cha

Abstract:

Piping and instrumentation diagram (P&ID) is an essential design drawing describing the interconnection of process equipment and the instrumentation installed to control the process. P&IDs are modified and managed throughout a whole life cycle of a process plant. For the ease of data transfer, P&IDs are generally handed over from a design company to an engineering company as portable document format (PDF) which is hard to be modified. Therefore, engineering companies have to deploy a great deal of time and human resources only for manually converting P&ID images into a computer aided design (CAD) file format. To reduce the inefficiency of the P&ID conversion, various symbols and texts in P&ID images should be automatically recognized. However, recognizing information in P&ID images is not an easy task. A P&ID image usually contains hundreds of symbol and text objects. Most objects are pretty small compared to the size of a whole image and are densely packed together. Traditional recognition methods based on geometrical features are not capable enough to recognize every elements of a P&ID image. To overcome these difficulties, state-of-the-art deep learning models, RetinaNet and connectionist text proposal network (CTPN) were used to build a system for recognizing symbols and texts in a P&ID image. Using the RetinaNet and the CTPN model carefully modified and tuned for P&ID image dataset, the developed system recognizes texts, equipment symbols, piping symbols and instrumentation symbols from an input P&ID image and save the recognition results as the pre-defined extensible markup language format. In the test using a commercial P&ID image, the P&ID information recognition system correctly recognized 97% of the symbols and 81.4% of the texts.

Keywords: object recognition system, P&ID, symbol recognition, text recognition

Procedia PDF Downloads 147

Authors: Rutebuka Evariste, Zhang Lixiao

Abstract:

Mobile phone sales and stocks showed an exponential growth in the past years globally and the number of mobile phones produced each year was surpassing one billion in 2007, this soaring growth of related e-waste deserves sufficient attentions paid to it regionally and globally as long as 40% of its total weight is made from metallic which 12 elements are identified to be highly hazardous and 12 are less harmful. Different research and methods have been used to estimate the obsolete mobile phones but none has developed a dynamic model and handle the discrepancy resulting from improper approach and error in the input data. The study aim was to develop a comprehensive dynamic system model for simulating the dynamism of e-waste production from mobile phone regardless the country or region and prevail over the previous errors. The logistic model method combined with STELLA program has been used to carry out this study. Then the simulation for Rwanda has been conducted and compared with others countries’ results as model testing and validation. Rwanda is about 1.5 million obsoletes mobile phone with 125 tons of waste in 2014 with e-waste production peak in 2017. It is expected to be 4.17 million obsoletes with 351.97 tons by 2020 along with environmental impact intensity of 21times to 2005. Thus, it is concluded through the model testing and validation that the present dynamic model is competent and able deal with mobile phone e-waste production the fact that it has responded to the previous studies questions from Czech Republic, Iran, and China.

Keywords: carrying capacity, dematerialization, logistic model, mobile phone, obsolescence, similarity, Stella, system dynamics

Procedia PDF Downloads 340