Search results for: calibration data requirements

Authors: Burmansyah Muhammad, Supriyoto Supriyoto

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Crop yield, quality and food safety are three important components that all estate and food crops must put into consideration to lifting the economic value. These measurements should be evaluated because marketplace demand is simultaneously changing and farmers must adapt quickly to remain competitive. The increase in economic value could be done by producing high quality product that aligns with harvest collector preferences. The purpose of this study is to examine the causal effects of value added farming in agriculture economic aspects towards crop yield, quality and food security. This research is using descriptive survey research by employing data from small-scale cocoa farmers listed to off-taker company, located on Sulawesi area of Indonesia. The questionnaire was obtained from 650 cocoa farmers, selected randomly. Major findings of the study indicate that 78% of respondents agree that agriculture inputs have positive effect on crop yield, quality and food safety. The study recommended that cocoa stakeholders should ensure access to agriculture inputs in first priority and then followed by ensuring access to cocoa supply chain trader and micro-financing. Value Added Farming refers to lifting the economic value of a commodity through particular intervention. Regarding access to agriculture inputs, one of significant intervention is fertilization and plant nutrition management, both organic and inorganic fertilizer. Small-scale cocoa farmers can get access to fertilizer intervention through establishment of demo farm. Ordinary demo farm needs large area, selective requirements, lots of field resources and centralization impact. On the contrary, satellite demo farm is developing to wide-spread the impact of agriculture economic aspects and also the involvement in number of farmers. In Sulawesi Project, we develop leveling strata of small-scale demo farm with group of farmers and local cooperative. With this methodology, all of listed small-scale farmers can get access to agriculture input, micro-financing and how to deliver quality output. PT Pupuk Kaltim is member firm of holding company PT Pupuk Indonesia, private company belongs to the government of Indonesia. The company listed as Indonesia's largest producer of urea fertilizers, besides ammonia, Compound Fertilizer (NPK) and biological fertilizers. To achieve strategic objectives, the company has distinguished award such as SNI Platinum, SGS Award IFA Protect and Sustain Stewardship and Gold Rank of Environment Friendly Company. This achievement has become the strategic foundation for our company to energize value added farming in sustaining food security program. Moreover, to ensure cocoa sustainability farming the company has developed partnership with international companies and Non-Government Organization (NGO).

Keywords: fertilizer and plant nutrition management, good agriculture practices, agriculture economic aspects, value-added farming

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Authors: Rusnardi Rahmat Putra, Junji Kiyono, Aiko Furukawa

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Several powerful earthquakes have struck Padang during recent years, one of the largest of which was an M 7.6 event that occurred on September 30, 2009 and caused more than 1000 casualties. Following the event, we conducted a 12-site microtremor array investigation to gain a representative determination of the soil condition of subsurface structures in Padang. From the dispersion curve of array observations, the central business district of Padang corresponds to relatively soft soil condition with Vs30 less than 400 m/s. because only one accelerometer existed, we simulated the 2009 Padang earthquake to obtain peak ground acceleration for all sites in Padang city. By considering the damage data of the 2009 Padang earthquake, we produced seismic risk vulnerability estimation of non-engineered houses for rock, medium and soft soil condition. We estimated the loss ratio based on the ground response, seismic hazard of Padang and the existing damaged to non-engineered structure houses due to Padang earthquake in 2009 data for several return periods of earthquake events.

Keywords: profile, Padang earthquake, microtremor array, seismic vulnerability

Procedia PDF Downloads 388

Authors: Ammar Alali, Mahmoud Abughaban, William Contreras Otalvora

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Optimizing the drilling process for cost and efficiency requires the optimization of the rate of penetration (ROP). ROP is the measurement of the speed at which the wellbore is created, in units of feet per hour. It is the primary indicator of measuring drilling efficiency. Maximization of the ROP can indicate fast and cost-efficient drilling operations; however, high ROPs may induce unintended events, which may lead to nonproductive time (NPT) and higher net costs. The proposed ROP optimization solution is a hybrid, data-driven system that aims to improve the drilling process, maximize the ROP, and minimize NPT. The system consists of two phases: (1) utilizing existing geological and drilling data to train the model prior, and (2) real-time adjustments of the controllable dynamic drilling parameters [weight on bit (WOB), rotary speed (RPM), and pump flow rate (GPM)] that direct influence on the ROP. During the first phase of the system, geological and historical drilling data are aggregated. After, the top-rated wells, as a function of high instance ROP, are distinguished. Those wells are filtered based on NPT incidents, and a cross-plot is generated for the controllable dynamic drilling parameters per ROP value. Subsequently, the parameter values (WOB, GPM, RPM) are calculated as a conditioned mean based on physical distance, following Inverse Distance Weighting (IDW) interpolation methodology. The first phase is concluded by producing a model of drilling best practices from the offset wells, prioritizing the optimum ROP value. This phase is performed before the commencing of drilling. Starting with the model produced in phase one, the second phase runs an automated drill-off test, delivering live adjustments in real-time. Those adjustments are made by directing the driller to deviate two of the controllable parameters (WOB and RPM) by a small percentage (0-5%), following the Constrained Random Search (CRS) methodology. These minor incremental variations will reveal new drilling conditions, not explored before through offset wells. The data is then consolidated into a heat-map, as a function of ROP. A more optimum ROP performance is identified through the heat-map and amended in the model. The validation process involved the selection of a planned well in an onshore oil field with hundreds of offset wells. The first phase model was built by utilizing the data points from the top-performing historical wells (20 wells). The model allows drillers to enhance decision-making by leveraging existing data and blending it with live data in real-time. An empirical relationship between controllable dynamic parameters and ROP was derived using Artificial Neural Networks (ANN). The adjustments resulted in improved ROP efficiency by over 20%, translating to at least 10% saving in drilling costs. The novelty of the proposed system lays is its ability to integrate historical data, calibrate based geological formations, and run real-time global optimization through CRS. Those factors position the system to work for any newly drilled well in a developing field event.

Keywords: drilling optimization, geological formations, machine learning, rate of penetration

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Authors: Elnaz Lalezari, Ramin Ghasemi Shaya

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The birth way is influenced by a fracture within the quiet care handle, making a brokenness of this final one. The pregnant lady has got to interface with numerous experts, both amid the pregnancy, the childbirth, and the puerperium. Be that as it may, amid the final ten a long time, there has been an expanding of the pregnancy care worked by the midwife, who is considered to be the administrator with the correct competences, who can beware of each pregnancy and may profit herself of other professionals' commitments in arrange to make strides the results of maternal and neonatal health. To confirm whether there are proofs of viability that bolster the caseload birthing assistance care show, and in case it is conceivable to apply this show within the birth way in Italy. A amendment of writing has been done utilizing a few look motor (Google, Bing) and particular databases (MEDLINE, CINAHL, Embase, Domestic - ClinicalTrials.gov). There has, too, been a discussion of the Italian directions, the national rules, and the proposals of WHO. Results: The look string, legitimately adjusted to the three databases, has given the taking after comes about: MEDLINE 64 articles, CINAHL 94 articles, Embase 88 articles. From this choice, 14 articles have been extricated: 1 orderly survey, 3 controlled arbitrary trial, 7 observational ponders, 3 subjective studies. The caseload maternity care appears to be an successful and dependable organisational/caring strategy. It reacts to the criterions of quality and security, to the requirements of ladies not as it were amid the pregnancy but moreover amid the post-partum stage. For these reasons, it appears exceptionally valuable also for the birth way within the Italian reality.

Keywords: midwifery, care, caseload, maternity

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Authors: Kumar Sambhav Pandey, Anamika Singh

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The continuous researches in the field of computer architecture basically aims at accelerating the computational speed and to gain enhanced performance. In this era, the superscalar, sub-scalar concept has not gained enough attention for improving the computation performance. In this paper, we have presented a sub-scalar approach to utilize the parallelism present with in the data while processing. The main idea is to split the data into individual smaller entities and these entities are processed with a defined known set of instructions. This sub-scalar approach to the MIPS architecture can bring out significant improvement in the computational speedup. MIPS-I is the basic design taken in consideration for the development of sub-scalar MIPS64 for increasing the instruction level parallelism (ILP) and resource utilization.

Keywords: dataword, MIPS, processor, sub-scalar

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Authors: Ahmed I. Al-Amoud

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A laboratory and field study were conducted on subsurface drip irrigation systems. In the first laboratory study, eight subsurface drip irrigation lines available locally, were selected and a number of experiments were made to evaluate line hydraulic characteristics to insure it's suitability for drip irrigation design requirements and high performance to select the best for field experiments. The second study involves field trials on mature date palm trees to study the effect of subsurface drip irrigation system on the yield and water consumption of date palms, and to compare that with the traditional surface drip irrigation system. Experiments were conducted in Alwatania Agricultural Project, on 50 mature palm trees (17 years old) of Helwa type with 10 meters spacing between rows and between trees. A high efficiency subsurface line (Techline) was used based on the results of the first study. Irrigation scheduling was made through a soil moisture sensing device to ensure enough soil water levels in the soil. Experiment layouts were installed during 2001 season, measurements continued till end of 2008 season. Results have indicated that there is an increase in the yield and a considerable saving in water compared to the conventional drip irrigation method. In addition there were high increases in water use efficiency using the subsurface system. The subsurface system proves to be durable and highly efficient for irrigating date palm trees.

Keywords: drip irrigation, subsurface drip irrigation, date palm trees, date palm water use, date palm yield

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Authors: Genady Shlomper

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During the process of language teaching, each teacher faces some general and some specific problems. Some of these problems are mutual to all languages because they yield to the rules of cognition, conscience, perception, understanding and memory; to the physiological and psychological principles pertaining to the human race irrespective of origin and nationality. Still, every language is a distinctive system, possessing individual properties and an obvious identity, as a result of a development in specific natural, geographical, cultural and historical conditions. The individual properties emerge in the script, in the phonetics, morphology and syntax. All these problems can and should be a subject of a detailed research and scientific analysis, mainly from practical considerations and language teaching requirements. There are some formidable obstacles in the language acquisition process. Among the first to be mentioned is the existence of concepts and entire categories in foreign languages, which are absent in the language of the students. Such phenomena reflect specific ways of thinking and the world-outlook, which were shaped during the evolution. Hindi is the national language of India, which belongs to the group of Indo-Iranian languages from the Indo-European family of languages. The lecturer has gained experience in teaching Hindi language to native speakers of Uzbek, Russian and Hebrew languages. He will show the difficulties in the field of phonetics, morphology and syntax, which the students have to deal with during the acquisition of the language. In the proposed lecture the lecturer will share his experience in making the process of language teaching more efficient by using non-formal semantic approach.

Keywords: applied linguistics, foreign language teaching, language teaching methodology, semantics

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Authors: Dipti Govil, Nidhi Khosla

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Couple-level reports of contraception are important as wives and husbands may give different reports about contraceptive use. Using matched couple-data (N=62910), from India's NFHS–IV (2015-16), this paper examines concordance in spousal reports of current contraceptive use and its differentials. Reporting of contraceptive use was higher among wives (59%) than husbands (25%). Concordance was low; 16.5% of couples reported the use of the same method, while 21% reported the use of any method. There existed a huge denial from husbands on the use of female sterilization. Reconstruction of contraceptive use among men increased concordance by 10%. Multivariate analysis shows that concordance was low in urban and Southern India, among younger women and women with lower wealth-index. Men's control over household decision-making and negative attitudes towards contraception were associated with a lower concordance. Findings highlight the importance of using couple-level data to estimate contraceptive prevalence, the role of education programs to inculcate positive attitudes towards contraception, fostering gender equality, and involving men into family planning efforts. The results also raise the issue of data quality as the questions were asked differently from men and women, which might have contributed to wide discordance.

Keywords: concordance, contraceptive use, couple, female sterilisation, India

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Authors: T. Yu, L. Audibert, J. F. Chaix, D. Komatitsch, V. Garnier, J. M. Henault

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Linear Ultrasonic Techniques play a major role in Non-Destructive Evaluation (NDE) for civil engineering structures in concrete since they can meet operational requirements. Interpretation of ultrasonic measurements could be improved by a better understanding of ultrasonic wave propagation in a multiple scattering medium. This work aims to develop a 2D numerical model of ultrasonic wave propagation in a heterogeneous medium, like concrete, integrating the multiple scattering phenomena in SPECFEM software. The coherent field of multiple scattering is obtained by averaging numerical wave fields, and it is used to determine the effective phase velocity and attenuation corresponding to an equivalent homogeneous medium. First, this model is applied to one scattering element (a cylinder) in a homogenous medium in a linear-elastic system, and its validation is completed thanks to the comparison with analytical solution. Then, some cases of multiple scattering by a set of randomly located cylinders or polygons are simulated to perform parametric studies on the influence of frequency and scatterer size, concentration, and shape. Also, the effective properties are compared with the predictions of Waterman-Truell model to verify its validity. Finally, the mortar viscoelastic behavior is introduced in the simulation in order to considerer the dispersion and the attenuation due to porosity included in the cement paste. In the future, different steps will be developed: The comparisons with experimental results, the interpretation of NDE measurements, and the optimization of NDE parameters before an auscultation.

Keywords: attenuation, multiple-scattering medium, numerical modeling, phase velocity, ultrasonic measurements

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Authors: Mohammad A. Al-Madi, Nagham A. Al-Madi, Fanan A. Al-Madi

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The current concept of the technology of cloud computing libraries has been increasing where users can store their data in a virtual space and can be retrieved from anywhere whilst using the network. By using cloud computing technology, industries and individuals save money, time, and space. Moreover, data and information about libraries can be placed in the cloud. This paper discusses the meaning of cloud computing along with its types. Further, the focus has been given to the application of cloud computing in modern libraries. Additionally, the advantages of cloud computing and the areas in which cloud computing be applied with current usage are discussed. Finally, the present situation of the Jordanian libraries is considered and discussed in further detail.

Keywords: cloud computing, community cloud, hybrid cloud, private cloud, public cloud

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Authors: Farhad Imanshoar

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The regime or equilibrium geometry of alluvial rivers remains a topic of fundamental scientific and engineering interest. There are several approaches to analyze the problem, namely: empirical formulas, semi-theoretical methods and rational (extreme) procedures. However, none of them is widely accepted at present, due to lack of knowledge of some physical processes associated with channel formation and the simplification hypotheses imposed in order to reduce the high quantity of involved variables. The study presented in this paper shows a new approach to estimate stable width and depth of sand-bed rivers by using developed stream power equation (DSPE). At first, a new procedure based on theoretical analysis and by considering DSPE and ultimate sediment concentration were developed. Then, experimental data for regime condition in sand-bed rivers (flow depth, flow width, sediment feed rate for several cases) were gathered. Finally, the results of this research (regime equations) are compared with the field data and other regime equations. A good agreement was observed between the field data and the values resulted from developed regime equation.

Keywords: regime equations, developed stream power equation, sand-bed rivers, semi-theoretical methods

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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: Sukhwinder K. Bhullar, M. B. G. Jun

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The developments in biomedical industry have demanded the development of biocompatible, high performance materials to meet higher engineering specifications. The general requirements of such materials are to provide a combination of high stiffness and strength with significant weight savings, resistance to corrosion, chemical resistance, low maintenance, and reduced costs. Auxetic materials which come under the category of smart materials offer huge potential through measured enhancements in mechanical properties. Unique deformation mechanism, providing cushioning on indentation, automatically adjustable with its strength and thickness in response to forces and having memory returns to its neutral state on dissipation of stresses make them good candidate in biomedical industry. As simple extension and compression of tissues is of fundamental importance in biomechanics, therefore, to study the elastic behaviour of auxetic soft tissues implant is targeted in this paper. Therefore development and characterization of auxetic soft tissue implant is studied in this paper. This represents a real life configuration where soft tissue such as meniscus in knee replacement, ligaments and tendons often are taken as transversely isotropic. Further, as composition of alternating polydisperse blocks of soft and stiff segments combined with excellent biocompatibility make polyurethanes one of the most promising synthetic biomaterials. Hence selecting auxetic polyurathylene foam functional characterization is performed and compared with conventional polyurathylene foam.

Keywords: auxetic materials, deformation mechanism, enhanced mechanical properties, soft tissues

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Authors: Ahmed El Naggar, Homyan Saleh

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Dams are crucial for flood control, water supply, and the creation of hydroelectric power. Every dam has a water conveyance system, such as a spillway, providing the safe discharge of catastrophic floods when necessary. Spillway design has historically been investigated in laboratory research owing to the absence of suitable full-scale flow monitoring equipment and safety problems. Prototype measurements of aerated flows are urgently needed to quantify projected scale effects and provide missing validation data for design guidelines and numerical simulations. In this work, an image-based investigation of free-surface flows on a tiered spillway was undertaken at the laboratory (fixed camera installation) and prototype size (drone video) (drone footage) (drone footage). The drone videos were generated using data from citizen science. Analyses permitted the measurement of the free-surface aeration inception point, air-water surface velocities, fluctuations, and residual energy at the chute's downstream end from a remote site. The prototype observations offered full-scale proof of concept, while laboratory results were efficiently confirmed against invasive phase-detection probe data. This paper stresses the efficacy of image-based analyses at prototype spillways. It highlights how citizen science data may enable academics better understand real-world air-water flow dynamics and offers a framework for a small collection of long-missing prototype data.

Keywords: remote sensing, aerated flows, large dams, proof of concept, dam spillways, air-water flows, prototype operation, remote sensing, inception point, optical flow, turbulence, residual energy

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Authors: P. S. Jagadeesh Kumar, S. Meenakshi Sundaram

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With the increase of prevailing non-traditional rivalry, mobile banking experiences an ever changing commercial backdrop. Substantial customer demands have established to be more intricate as customers request more expediency and superintend over their banking services. To enterprise advance and modernization in mobile banking applications, it is gradually obligatory to deeply leapfrog the scuffle using business model transformation. The dramaturgical vicissitudes taking place in mobile banking entail advanced traditions to exploit security. By reforming and transforming older back office into integrated mobile banking applications, banks can engender a supple and nimble banking environment that can rapidly respond to new business requirements over cloud computing. Cloud computing is transfiguring ecosystems in numerous industries, and mobile banking is no exemption providing services innovation, greater flexibility to respond to improved security and enhanced business intelligence with less cost. Cloud technology offer secure deployment possibilities that can provision banks in developing new customer experiences, empower operative relationship and advance speed to efficient banking transaction. Cloud adoption is escalating quickly since it can be made secured for commercial mobile banking transaction through backend as a service in scrutinizing the security strategies of the cloud service provider along with the antiquity of transaction details and their security related practices.

Keywords: cloud adoption, backend as a service, business intelligence, secured mobile banking

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Authors: Abdolamir Gatezadeh, Jamal Daghaleh

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The lifestyle of individuals is important and determinant for the status of psychological and social health. Recently, especially in developed countries, the relationship between lifestyle and mental illnesses, including depression, has attracted the attention of many people. In order to test the causal model of depression based on lifestyle with mediation of social health in the study, basic and applied methods were used in terms of objective and descriptive-field as well as the data collection. Methods: This study is a basic research type and is in the framework of correlational plans. In this study, the population includes all adults in Ahwaz city. A randomized, multistage sampling of 384 subjects was selected as the subjects. Accordingly, the data was collected and analyzed using structural equation modeling. Results: In data analysis, path analysis indicated the confirmation of the assumed model fit of research. This means that subscales lifestyle has a direct effect on depression and subscales lifestyle through the mediation of social health which in turn has an indirect effect on depression. Discussion and conclusion: According to the results of the research, the depression can be used to explain the components of the lifestyle and social health.

Keywords: depression, subscales lifestyle, social health, causal model

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Authors: Kevin Potoczny, Katsuichiro Goda

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The St. Lawrence lowlands extend from Ottawa to Quebec City and are known for large deposits of sensitive Leda clay. Leda clay deposits are responsible for many large landslides, such as the 1993 Lemieux and 2010 St. Jude (4 fatalities) landslides. Due to the large extent and sensitivity of Leda clay, regional hazard analysis for landslides is an important tool in risk management. A 2018 regional study by Farzam et al. on the susceptibility of Leda clay slopes to landslide hazard uses 1 arc second topographical data. A qualitative method known as Hazus is used to estimate susceptibility by checking for various criteria in a location and determine a susceptibility rating on a scale of 0 (no susceptibility) to 10 (very high susceptibility). These criteria are slope angle, geological group, soil wetness, and distance from waterbodies. Given the flat nature of St. Lawrence lowlands, the current assessment fails to capture local slopes, such as the St. Jude site. Additionally, the data did not allow one to analyze failure planes accurately. This study majorly improves the analysis performed by Farzam et al. in two aspects. First, regional assessment with high resolution data allows for identification of local locations that may have been previously identified as low susceptibility. This then provides the opportunity to conduct a more refined analysis on the failure plane of the slope. Slopes derived from 1 arc second data are relatively gentle (0-10 degrees) across the region; however, the 1- and 2-meter resolution 2022 HRDEM provided by NRCAN shows that short, steep slopes are present. At a regional level, 1 arc second data can underestimate the susceptibility of short, steep slopes, which can be dangerous as Leda clay landslides behave retrogressively and travel upwards into flatter terrain. At the location of the St. Jude landslide, slope differences are significant. 1 arc second data shows a maximum slope of 12.80 degrees and a mean slope of 4.72 degrees, while the HRDEM data shows a maximum slope of 56.67 degrees and a mean slope of 10.72 degrees. This equates to a difference of three susceptibility levels when the soil is dry and one susceptibility level when wet. The use of GIS software is used to create a regional susceptibility map across the St. Lawrence lowlands at 1- and 2-meter resolutions. Failure planes are necessary to differentiate between small and large landslides, which have so far been ignored in regional analysis. Leda clay failures can only retrogress as far as their failure planes, so the regional analysis must be able to transition smoothly into a more robust local analysis. It is expected that slopes within the region, once previously assessed at low susceptibility scores, contain local areas of high susceptibility. The goal is to create opportunities for local failure plane analysis to be undertaken, which has not been possible before. Due to the low resolution of previous regional analyses, any slope near a waterbody could be considered hazardous. However, high-resolution regional analysis would allow for more precise determination of hazard sites.

Keywords: hazus, high-resolution DEM, leda clay, regional analysis, susceptibility

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Authors: Binder Hans

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Cancer is no longer seen as solely a genetic disease where genetic defects such as mutations and copy number variations affect gene regulation and eventually lead to aberrant cell functioning which can be monitored by transcriptome analysis. It has become obvious that epigenetic alterations represent a further important layer of (de-)regulation of gene activity. For example, aberrant DNA methylation is a hallmark of many cancer types, and methylation patterns were successfully used to subtype cancer heterogeneity. Hence, unraveling the interplay between different omics levels such as genome, transcriptome and epigenome is inevitable for a mechanistic understanding of molecular deregulation causing complex diseases such as cancer. This objective requires powerful downstream integrative bioinformatics methods as an essential prerequisite to discover the whole genome mutational, transcriptome and epigenome landscapes of cancer specimen and to discover cancer genesis, progression and heterogeneity. Basic challenges and tasks arise ‘beyond sequencing’ because of the big size of the data, their complexity, the need to search for hidden structures in the data, for knowledge mining to discover biological function and also systems biology conceptual models to deduce developmental interrelations between different cancer states. These tasks are tightly related to cancer biology as an (epi-)genetic disease giving rise to aberrant genomic regulation under micro-environmental control and clonal evolution which leads to heterogeneous cellular states. Machine learning algorithms such as self organizing maps (SOM) represent one interesting option to tackle these bioinformatics tasks. The SOMmethod enables recognizing complex patterns in large-scale data generated by highthroughput omics technologies. It portrays molecular phenotypes by generating individualized, easy to interpret images of the data landscape in combination with comprehensive analysis options. Our image-based, reductionist machine learning methods provide one interesting perspective how to deal with massive data in the discovery of complex diseases, gliomas, melanomas and colon cancer on molecular level. As an important new challenge, we address the combined portrayal of different omics data such as genome-wide genomic, transcriptomic and methylomic ones. The integrative-omics portrayal approach is based on the joint training of the data and it provides separate personalized data portraits for each patient and data type which can be analyzed by visual inspection as one option. The new method enables an integrative genome-wide view on the omics data types and the underlying regulatory modes. It is applied to high and low-grade gliomas and to melanomas where it disentangles transversal and longitudinal molecular heterogeneity in terms of distinct molecular subtypes and progression paths with prognostic impact.

Keywords: integrative bioinformatics, machine learning, molecular mechanisms of cancer, gliomas and melanomas

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Authors: Wei Chen, Jinlong Pan

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3D concrete printing technology is a novel and highly efficient construction method that holds significant promise for advancing low-carbon initiatives within the construction industry. In contrast to traditional construction practices, 3D printing offers a manual and formwork-free approach, resulting in a transformative shift in labor requirements and fabrication techniques. This transition yields substantial reductions in carbon emissions during the construction phase, as well as decreased on-site waste generation. Furthermore, when compared to conventionally printed concrete, 3D concrete exhibits mechanical anisotropy due to its layer-by-layer construction methodology. Therefore, it becomes imperative to investigate the influence of the printing process on the mechanical properties of 3D printed strips and to optimize the mechanical characteristics of these coagulated strips. In this study, we conducted three-dimensional reconstructions of printed blocks using both circular and directional print heads, incorporating various overlap distances between strips, and employed CT scanning for comprehensive analysis. Our research focused on assessing mechanical properties and micro-pore characteristics under different loading orientations. Our findings reveal that increasing the overlap degree between strips leads to enhanced mechanical properties of the strips. However, it's noteworthy that once full overlap is achieved, further increases in the degree of coincidence do not lead to a decrease in porosity between strips. Additionally, due to its superior printing cross-sectional area, the square printing head exhibited the most favorable impact on mechanical properties.

Keywords: 3D printing concrete, mechanical anisotropy, micro-pore structure, printing technology

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Authors: Khadidja Rahmani, Nahla Bouaziz

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The climate change and the economic crisis, which are currently running, are the origin of the emergence of many issues and problems, which are related to the domain of energy and environment in à direct or indirect manner. Since the urban space is the core element and the key to solve the current problem, particular attention is given to it in this study. For this reason, we rented to the later a very particular attention; this is for the opportunities that it provides and that can be invested to attenuate a little this situation, which is disastrous and worried, especially in the face of the requirements of sustainable development. Indeed, the purpose of this work is to develop a method, which will allow us to guide designers towards projects with a certain degree of thermo-aeraulic comfort while requiring a minimum energy consumption. In this context, the architects, the urban planners and the engineers (energeticians) have to collaborate jointly to establish a method based on indicators for the improvement of the urban environmental quality (aeraulic-thermo comfort), correlated with a reduction in the energy demand of the entities that make up this environment, in areas with a sub-humid climate. In order to test the feasibility and to validate the method developed in this work, we carried out a series of simulations using computer-based simulation. This research allows us to evaluate the impact of the use of the indicators in the design of the urban sets, on the economic and ecological plan. Using this method, we prove that an urban design, which carefully considered energetically, can contribute significantly to the preservation of the environment and the reduction of the consumption of energy.

Keywords: comfort, energy consumption, energy mastery, morpho-energetic indicators, simulation, sub-humid climate, urban sets

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Authors: Omar Alzeley, Sergey Utev

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Minimizing a constrained multivariate function is the fundamental of Machine learning, and these algorithms are at the core of data mining and data visualization techniques. The decision function that maps input points to output points is based on the result of optimization. This optimization is the central of learning theory. One approach to complex systems where the dynamics of the system is inferred by a statistical analysis of the fluctuations in time of some associated observable is time series analysis. The purpose of this paper is a mathematical transition from the autoregressive model of classical time series to the matrix formalization of quantum theory. Firstly, we have proposed a quantum time series model (QTS). Although Hamiltonian technique becomes an established tool to detect a deterministic chaos, other approaches emerge. The quantum probabilistic technique is used to motivate the construction of our QTS model. The QTS model resembles the quantum dynamic model which was applied to financial data. Secondly, various statistical methods, including machine learning algorithms such as the Kalman filter algorithm, are applied to estimate and analyses the unknown parameters of the model. Finally, simulation techniques such as Markov chain Monte Carlo have been used to support our investigations. The proposed model has been examined by using real and simulated data. We establish the relation between quantum statistical machine and quantum time series via random matrix theory. It is interesting to note that the primary focus of the application of QTS in the field of quantum chaos was to find a model that explain chaotic behaviour. Maybe this model will reveal another insight into quantum chaos.

Keywords: machine learning, simulation techniques, quantum probability, tensor product, time series

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Authors: Ali A. Abdollahi

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During the last several decades, scientists have consistently applied Multiple Criteria Decision-Making methods in making decisions about multi-faceted, complicated subjects. While making such decisions and in order to achieve more accurate evaluations, they have regularly used a variety of criteria instead of applying just one Optimum Evaluation Criterion. The method presented here utilizes both ‘quantity’ and ‘quality’ to assess the function of the Multiple-Criteria method. Applying Data envelopment analysis (DEA), weighted aggregated sum product assessment (WASPAS), Weighted Sum Approach (WSA), Analytic Network Process (ANP), and Charnes, Cooper, Rhodes (CCR) methods, we have analyzed thirteen parks in Kerman city. It further indicates that the functions of WASPAS and WSA are compatible with each other, but also that their deviation from DEA is extensive. Finally, the results for the CCR technique do not match the results of the DEA technique. Our study indicates that the ANP method, with the average rate of 1/51, ranks closest to the DEA method, which has an average rate of 1/49.

Keywords: multiple criteria decision making, Data envelopment analysis (DEA), Charnes Cooper Rhodes (CCR), Weighted Sum Approach (WSA)

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Authors: Mayada Attia Ibrahim

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Evaluating and developing the electroplating production process is a key challenge in this type of process. The process is influenced by several factors such as process parameters, process costs, and production environments. Analyzing and optimizing all these factors together requires extensive analytical techniques that are not available in real-case industrial entities. This paper presents a practice-based framework for the evaluation and optimization of some of the crucial factors that affect the costs and production times associated with this type of process, energy costs, material costs, and product flow times. The proposed approach uses Design of Experiments, Discrete-Event Simulation, and Theory of Constraints were respectively used to identify the most significant factors affecting the production process and simulate a real production line to recognize the effect of these factors and assign possible bottlenecks. Several scenarios are generated as corrective strategies for improving the production line. Following that, data envelopment analysis CCR input-oriented DEA model is used to evaluate and optimize the suggested scenarios.

Keywords: electroplating process, simulation, design of experiment, performance optimization, theory of constraints, data envelopment analysis

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Authors: Zhuanfang Fred Zhang, Tim C. Johnson, Yilin Fang, Chris E. Strickland

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A variety of geophysical techniques are available to image the opaque subsurface with little or no contact with the soil. It is common to conduct time-lapse surveys of different types for a given site for improved results of subsurface imaging. Regardless of the chosen survey methods, it is often a challenge to process the massive amount of survey data. The currently available software applications are generally based on the one-dimensional assumption for a desktop personal computer. Hence, they are usually incapable of imaging the three-dimensional (3D) processes/variables in the subsurface of reasonable spatial scales; the maximum amount of data that can be inverted simultaneously is often very small due to the capability limitation of personal computers. Presently, high-performance or integrating software that enables real-time integration of multi-process geophysical methods is needed. E4D-MP enables the integration and inversion of time-lapsed large-scale data surveys from geophysical methods. Using the supercomputing capability and parallel computation algorithm, E4D-MP is capable of processing data across vast spatiotemporal scales and in near real time. The main code and the modules of E4D-MP for inverting individual or combined data sets of time-lapse 3D electrical resistivity, spectral induced polarization, and gravity surveys have been developed and demonstrated for sub-surface imaging. E4D-MP provides capability of imaging the processes (e.g., liquid or gas flow, solute transport, cavity development) and subsurface properties (e.g., rock/soil density, conductivity) critical for successful control of environmental engineering related efforts such as environmental remediation, carbon sequestration, geothermal exploration, and mine land reclamation, among others.

Keywords: gravity survey, high-performance computing, sub-surface monitoring, electrical resistivity tomography

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Authors: Darren A. Whitaker, Dan Palmer, Jens Wesholowski, James Flaherty, John Mack, Ahmad B. Albadarin, Gavin Walker

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Traditional mechanosynthesis has been performed by either ball milling or manual grinding. However, neither of these techniques allow the easy application of process control. The temperature may change unpredictably due to friction in the process. Hence the amount of energy transferred to the reactants is intrinsically non-uniform. Recently, it has been shown that the use of Twin-Screw extrusion (TSE) can overcome these limitations. Additionally, TSE enables a platform for continuous synthesis or manufacturing as it is an open-ended process, with feedstocks at one end and product at the other. Several materials including metal-organic frameworks (MOFs), co-crystals and small organic molecules have been produced mechanochemically using TSE. The described advantages of TSE are offset by drawbacks such as increased process complexity (a large number of process parameters) and variation in feedstock flow impacting on product quality. To handle the above-mentioned drawbacks, this study utilizes UV-Vis spectrophotometry (InSpectroX, ColVisTec) as an online tool to gain real-time information about the quality of the product. Additionally, this is combined with real-time process information in an Advanced Process Control system (PharmaMV, Perceptive Engineering) allowing full supervision and control of the TSE process. Further, by characterizing the dynamic behavior of the TSE, a model predictive controller (MPC) can be employed to ensure the process remains under control when perturbed by external disturbances. Two reactions were studied; a Knoevenagel condensation reaction of barbituric acid and vanillin and, the direct amidation of hydroquinone by ammonium acetate to form N-Acetyl-para-aminophenol (APAP) commonly known as paracetamol. Both reactions could be carried out continuously using TSE, nuclear magnetic resonance (NMR) spectroscopy was used to confirm the percentage conversion of starting materials to product. This information was used to construct partial least squares (PLS) calibration models within the PharmaMV development system, which relates the percent conversion to product to the acquired UV-Vis spectrum. Once this was complete, the model was deployed within the PharmaMV Real-Time System to carry out automated optimization experiments to maximize the percentage conversion based on a set of process parameters in a design of experiments (DoE) style methodology. With the optimum set of process parameters established, a series of PRBS process response tests (i.e. Pseudo-Random Binary Sequences) around the optimum were conducted. The resultant dataset was used to build a statistical model and associated MPC. The controller maximizes product quality whilst ensuring the process remains at the optimum even as disturbances such as raw material variability are introduced into the system. To summarize, a combination of online spectral monitoring and advanced process control was used to develop a robust system for optimization and control of two TSE based mechanosynthetic processes.

Keywords: continuous synthesis, pharmaceutical, spectroscopy, advanced process control

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Authors: Nesrine Gaaliche

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This study provides a finite element dynamic model for analyzing rolling bearing system vibration response. The vibration responses of polypropylene bearings with and without defects are studied using FE analysis and compared to experimental data. The viscoelastic behavior of thermoplastic is investigated in this work to evaluate the influence of material flexibility and damping viscosity. The vibrations are detected using 3D dynamic analysis. Peak vibrations are more noticeable in an inner ring defect than in an outer ring defect, according to test data. The performance of thermoplastic bearings is compared to that of metal parts using vibration signals. Both the test and numerical results show that Polypropylene bearings exhibit less vibration than steel counterparts. Unlike bearings made from metal, polypropylene bearings absorb vibrations and handle shaft misalignments. Following validation of the overall vibration spectrum data, Von Mises stresses inside the rings are assessed under high loads. Stress is significantly high under the balls, according to the simulation findings. For the test cases, the computational findings correspond closely to the experimental results.

Keywords: viscoelastic, FE analysis, polypropylene, bearings

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Authors: Eliane Abdo, Olivier Colot

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SMEs are always considered as a national priority due to their contribution to job creation, innovation and growth. Once the start-up phase is crossed with encouraging results, the company enters the phase of growth. In order to improve its competitiveness, maintain and increase its market share, the company is in the necessity even the obligation to develop its tangible and intangible investments. SMEs are generally closed companies with special and critical financial situation, limited resources and difficulty to access the capital markets; their shareholders are always living in a conflict between their independence and their need to increase capital that leads to the entry of new shareholder. The capital structure was always considered the core of research in corporate finance; moreover, the financial crisis and its repercussions on the credit’s availability, especially for SMEs make SME financing a hot topic. On the other hand, financial theories do not provide answers to capital structure’s questions; they offer tools and mode of financing that are more accessible to larger companies. Yet, SME’s capital structure can’t be independent of their governance structure. The classic financial theory supposes independence between the investment decision and the financing decision. Thus, investment determines the volume of funding, but not the split between internal or external funds. In this context, we find interesting to study the hypothesis that SMEs respond positively to the financial theories applied to large firms and to check if they are constrained by conventional solutions used by large companies. In this context, this research focuses on the analysis of the resource’s structure of SME in parallel with their investments’ structure, in order to highlight a link between their assets and liabilities structure. We founded our conceptual model based on two main theoretical frameworks: the Pecking order theory, and the Trade Off theory taking into consideration the SME’s characteristics. Our data were generated from DIANE database. Five hypotheses were tested via a panel regression to understand the type of dependence between the financing methods of 3,244 French SMEs and the development of their investment over a period of 10 years (2007-2016). The results show dependence between equity and internal financing in case of intangible investments development. Moreover, this type of business is constraint to financial debts since the guarantees provided are not sufficient to meet the banks' requirements. However, for tangible investments development, SMEs count sequentially on internal financing, bank borrowing, and new shares issuance or hybrid financing. This is compliant to the Pecking Order Theory. We, therefore, conclude that unlisted SMEs incur more financial debts to finance their tangible investments more than their intangible. However, they always prefer internal financing as a first choice. This seems to be confirmed by the assumption that the profitability of the company is negatively related to the increase of the financial debt. Thus, the Pecking Order Theory predictions seem to be the most plausible. Consequently, SMEs primarily rely on self-financing and then go, into debt as a priority to finance their financial deficit.

Keywords: capital structure, investments, life cycle, pecking order theory, trade off theory

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Authors: Sarah Ryu

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Agricultural methods and ecological approaches employed by the pre-colonial Mayans may provide valuable insights into forest management and viable alternatives for resource sustainability in the face of major deforestation across Central and South America.Using a combination of observation data collected from the modern indigenous inhabitants near Mixco in Guatemala and historical data, this study was able to create a holistic picture of how the Maya maintained their ecosystems. Surveys and observations were conducted in the field, over a period of twelve weeks across two years. Geographic and archaeological data for this area was provided by Guatemalan organizations such as the Universidad de San Carlos de Guatemala. Observations of current indigenous populations around Mixco showed that they adhered to traditional Mayan methods of agriculture, such as terrace construction and arboriculture. Rather than planting one cash crop as was done by the Spanish, indigenous peoples practice agroforestry, cultivating forests that would provide trees for construction material, wild plant foods, habitat for game, and medicinal herbs. The emphasis on biodiversity prevented deforestation and created a sustainable balance between human consumption and forest regrowth. Historical data provided by MayaSim showed that the Mayans successfully maintained their ecosystems from about 800BCE to 700CE. When the Mayans practiced natural resource conservation and cultivated a harmonious relationship with the forest around them, they were able to thrive and prosper alongside nature. Having lasted over a thousand years, the Mayan empire provides a valuable lesson in sustainability and human attitudes towards the environment.

Keywords: biodiversity, forestry, mayan, sustainability

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Authors: Timur S. Zaripov, Artur K. Gilfanov, Sergei S. Sazhin, Steven M. Begg, Morgan R. Heikal

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The calculation of the concentration of inertial droplets in complex flows is encountered in the modelling of numerous engineering and environmental phenomena; for example, fuel droplets in internal combustion engines and airborne pollutant particles. The results of recent research, focused on the development of methods for calculating concentration and their implementation in the commercial CFD code, ANSYS Fluent, is presented here. The study is motivated by the investigation of the mixture preparation processes in internal combustion engines with direct injection of fuel sprays. Two methods are used in our analysis; the Fully Lagrangian method (also known as the Osiptsov method) and the Eulerian approach. The Osiptsov method predicts droplet concentrations along path lines by solving the equations for the components of the Jacobian of the Eulerian-Lagrangian transformation. This method significantly decreases the computational requirements as it does not require counting of large numbers of tracked droplets as in the case of the conventional Lagrangian approach. In the Eulerian approach the average droplet velocity is expressed as a function of the carrier phase velocity as an expansion over the droplet response time and transport equation can be solved in the Eulerian form. The advantage of the method is that droplet velocity can be found without solving additional partial differential equations for the droplet velocity field. The predictions from the two approaches were compared in the analysis of the problem of a dilute gas-droplet flow around an infinitely long, circular cylinder. The concentrations of inertial droplets, with Stokes numbers of 0.05, 0.1, 0.2, in steady-state and transient laminar flow conditions, were determined at various Reynolds numbers. In the steady-state case, flows with Reynolds numbers of 1, 10, and 100 were investigated. It has been shown that the results predicted using both methods are almost identical at small Reynolds and Stokes numbers. For larger values of these numbers (Stokes — 0.1, 0.2; Reynolds — 10, 100) the Eulerian approach predicted a wider spread in concentration in the perturbations caused by the cylinder that can be attributed to the averaged droplet velocity field. The transient droplet flow case was investigated for a Reynolds number of 200. Both methods predicted a high droplet concentration in the zones of high strain rate and low concentrations in zones of high vorticity. The maxima of droplet concentration predicted by the Osiptsov method was up to two orders of magnitude greater than that predicted by the Eulerian method; a significant variation for an approach widely used in engineering applications. Based on the results of these comparisons, the Osiptsov method has resulted in a more precise description of the local properties of the inertial droplet flow. The method has been applied to the analysis of the results of experimental observations of a liquid gasoline spray at representative fuel injection pressure conditions. The preliminary results show good qualitative agreement between the predictions of the model and experimental data.

Keywords: internal combustion engines, Eulerian approach, fully Lagrangian approach, gasoline fuel sprays, droplets and particle concentrations

Procedia PDF Downloads 246

Authors: Xiaoheng Tan, Xianfang Li, Tan Guo, Yuchuan Liu, Zhijun Yang, Hongye Li, Kai Fu, Yufang Wu, Heling Gong

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The image data collected in reality often have high dimensions, and it contains noise and redundant information. Therefore, it is necessary to extract the compact feature expression of the original perceived image. In this process, effective use of prior knowledge such as data structure distribution and sample label is the key to enhance image feature discrimination and robustness. Based on the above considerations, this paper proposes a local preserving discriminant feature learning model based on graph optimization. The model has the following characteristics: (1) Locality preserving constraint can effectively excavate and preserve the local structural relationship between data. (2) The flexibility of graph learning can be improved by constructing a new local geometric structure graph using label information and the nearest neighbor threshold. (3) The L₂,₁ norm is used to redefine LDA, and the diagonal matrix is introduced as the scale factor of LDA, and the samples are selected, which improves the robustness of feature learning. The validity and robustness of the proposed algorithm are verified by experiments in two public image datasets.

Keywords: feature extraction, graph optimization local preserving projection, linear discriminant analysis, L₂, ₁ norm

Procedia PDF Downloads 136