Search results for: strain monitoring

Authors: Mohamed Sarrab, Hadj Bourdoucen

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Mobile applications are verified to check the correctness or evaluated to check the performance with respect to specific security properties such as availability, integrity, and confidentiality. Where they are made available to the end users of the mobile application is achievable only to a limited degree using software engineering static verification techniques. The more sensitive the information, such as credit card data, personal medical information or personal emails being processed by mobile application, the more important it is to ensure the confidentiality of this information. Monitoring non-trusted mobile application during execution in an environment where sensitive information is present is difficult and unnerving. The paper addresses the issue of monitoring and controlling the flow of confidential information during non-trusted mobile application execution. The approach concentrates on providing a dynamic and usable information security solution by interacting with the mobile users during the run-time of mobile application in response to information flow events.

Keywords: mobile application, run-time verification, usable security, direct information flow

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Authors: Richard Abel

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In the United States, increased incarceration rates have caused many adolescents to feel the strain of parental absence. This absence is then manifest through adolescent feelings of parental rejection. Additionally, upon reentry maternal incarceration may be related to adolescents experienced perceived excessive disciple. It is possible parents engage in this manner of discipline attempting to prevent the child from taking the same path to incarceration as the parent. According to General Strain Theory, adolescents encountering strain are likely to experience negative emotions. The emotion that is most likely to lead to delinquency is anger through reduced inhibitions and motivation to act. Additionally, males are more likely to engage in delinquent behavior, regardless of experiencing strain. This is not the case for every male who experiences maternal incarceration, parental rejection, excessive discipline, or anger. There are protective factors that enable agency within individuals. One such protective factor is mastery, or the perception that one is in control of his or her own future. The model proposed in this research suggests maternal incarceration is associated with increased parental rejection and excessive discipline in males. Males experiencing parental rejection and excessive discipline are likely to experience increased anger, which is then associated with increases in delinquent behavior. This model explores whether agency, in the form of mastery, mediates the relationship between strains and negative emotions, or between negative emotions and delinquent behavior. The Kaplan Longitudinal and Multigenerational Study (KLAMS) dataset is uniquely situated to analyze this model providing longitudinal data collected from both parents and their offspring. Maternal incarceration is constructed using parental responses such that the mother was incarcerated after the child’s birth, and any incarceration that happened prior to birth is excluded. The remaining variables of the study are all constructed from varying waves of the adolescent survey. Parental rejection, along with control variables for age, race, parental socioeconomic status, neighborhood effects, delinquent peers, and prior delinquent behavior are all constructed using Wave I data. To increase causal inference, the negative emotion of anger and the mediating variable of mastery are measured during Wave II. Lastly, delinquent behavior is measured at Wave III. Results of the analysis show expected relationships such that adolescent males encountering maternal incarceration show increased perception of parental rejection and excessive discipline. Additionally, there is a positive relationship between parental rejection and excessive discipline at Wave I and feelings of anger at Wave II for males. For males experiencing either of these strains in Wave I, feelings of anger in Wave II are found to be associated with increased delinquent behavior in Wave III. Mastery was found to mediate the relationship between both parental rejection and excessive discipline and anger, but no such mediation occurs in the relationship between anger and delinquency, regardless of the strain being experienced. These findings suggest adolescent males who feel they are in control of their own lives are less likely to experience negative emotions produced by the occurrence of strain, thereby decreasing male engagement in delinquent behavior later in life.

Keywords: delinquency, mastery, maternal incarceration, strain

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Authors: Lars Laußat, Manfred Helmus, Kamil Szczesny, Markus König

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As one result of the project “Reactive Construction Project Scheduling using Real Time Construction Logistic Data and Simulation”, a procedure for using data about uncertain resource availability assumptions in reactive scheduling processes has been developed. Prediction data about resource availability is generated in a formalized way using real-time monitoring data e.g. from auto-ID systems on the construction site and in the supply chains. The paper focuses on the formalization of the procedure for monitoring construction logistic processes, for the detection of disturbance and for generating of new and uncertain scheduling assumptions for the reactive resource constrained simulation procedure that is and will be further described in other papers.

Keywords: auto-ID, construction logistic, fuzzy, monitoring, RFID, scheduling

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Authors: Tzong-Ying Hao, Mohammad T. Rahmani

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The Torre Central building is a 9-story shear wall structure located in Santiago, Chile, and has been instrumented since 2009. Events of different intensity (ambient vibrations, weak and strong earthquake motions) have been recorded, and thus the building can serve as a full-scale benchmark to evaluate the structural health monitoring method developed. The first part of this article presents an analysis of inter-story drifts, and of changes in the first system frequencies (estimated from the relative displacement response of the 8th-floor with respect to the basement from recorded data) as baseline indicators of the occurrence of damage. During 2010 Chile earthquake the system frequencies were detected decreasing approximately 24% in the EW and 27% in NS motions. Near the end of shaking, an increase of about 17% in the EW motion was detected. The structural health monitoring (SHM) method based on changes in wave traveling time (wave method) within a layered shear beam model of structure is presented in the second part of this article. If structural damage occurs the velocity of wave propagated through the structure changes. The wave method measures the velocities of shear wave propagation from the impulse responses generated by recorded data at various locations inside the building. Our analysis and results show that the detected changes in wave velocities are consistent with the observed damages. On this basis, the wave method is proven for actual implementation in structural health monitoring systems.

Keywords: Chile earthquake, damage detection, earthquake response, impulse response, layered shear beam, structural health monitoring, Torre Central building, wave method, wave travel time

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Authors: Hyun-Woo Cho

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Detection of incipient abnormal events in production processes is important to improve safety and reliability of manufacturing operations and reduce losses caused by failures. The construction of calibration models for predicting faulty conditions is quite essential in making decisions on when to perform preventive maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of process measurement data. The calibration model is used to predict faulty conditions from historical reference data. This approach utilizes variable selection techniques, and the predictive performance of several prediction methods are evaluated using real data. The results shows that the calibration model based on supervised probabilistic model yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: calibration model, monitoring, quality improvement, feature selection

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Authors: Bothinah Altaf, Gary Montague, Elaine B. Martin

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This study involves the modeling and monitoring of an ammonia synthesis fixed-bed reactor using partial least squares (PLS) and its variants. The process exhibits complex dynamic behavior due to the presence of heat recycling and feed quench. One limitation of static PLS model in this situation is that it does not take account of the process dynamics and hence dynamic PLS was used. Although it showed, superior performance to static PLS in terms of prediction, the monitoring scheme was inappropriate hence adaptive PLS was considered. A limitation of adaptive PLS is that non-conforming observations also contribute to the model, therefore, a new adaptive approach was developed, robust adaptive dynamic PLS. This approach updates a dynamic PLS model and is robust to non-representative data. The developed methodology showed a clear improvement over existing approaches in terms of the modeling of the reactor and the detection of faults.

Keywords: ammonia synthesis fixed-bed reactor, dynamic partial least squares modeling, recursive partial least squares, robust modeling

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Authors: J. Aliyu, A. O. Raji, A. A. Ibrahim

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The study was carried out to assess the fertility, early and late embryonic mortalities as well as hatchability by strain, season and hen’s weight in Nigerian indigenous chickens reared on deep litter. Four strains (normal feathered, naked neck, frizzle and dwarf) of hens maintained at a mating ratio of 1 cock to 4 hens, fed breeders mash and water ad libitum were used in a three year experiment. The data generated were subjected to analysis of variance using the SAS package and the means, where significant, were separated using the least significant difference (LSD). There were significant effects (P < 0.05) of strain on all the traits studied. Fertility was generally high (84.29 %) in all the strains. Early embryonic mortality was significantly lowest (P < 0.01) in naked neck which had the highest late embryonic mortality (P < 0.001). Hatchability was significantly highest (P < 0.01) in normal feathered (80.23 %) and slightly depressed in frizzle (74.95 %) and dwarf (72.27 %) while naked neck had the lowest (60.80 %). Season of the year had significant effects on early embryonic mortality. Dry hot season significantly (P < 0.05) depressed fertility while early embryonic mortality was depressed in the wet season (15.33 %). Early and late embryonic mortalities significantly increased (P < 0.05) with increasing weight of hen. Dwarf, frizzle and normal feathered hens could be used to improve hatchability as well as reduce early and late embryonic mortalities in Nigerian indigenous chickens.

Keywords: chicken, fertility, hatchability, indigenous, strain

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Authors: Won Mog Choi, Seong Kyeong Hong, Seok Young Jeong

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The stress on the buried pipeline under pavement is significantly affected by vehicle loads and elastic modulus of the soil surrounding the pipeline. The correct elastic modulus of soil has to be applied to the finite element model to investigate the effect of the vehicle loads on the buried pipeline using finite element analysis. The purpose of this study is to establish the approach to calculating the correct elastic modulus of soil using the optimization process. The optimal elastic modulus of soil, which minimizes the difference between the strain measured from vehicle driving test at the velocity of 35km/h and the strain calculated from finite element analyses, was calculated through the optimization process using multi-response surface methodology. Three elastic moduli of soil (road layer, original soil, dense sand) surrounding the pipeline were defined as the variables for the optimization. Further analyses with the optimal elastic modulus at the velocities of 4.27km/h, 15.47km/h, 24.18km/h were performed and compared to the test results to verify the applicability of multi-response surface methodology. The results indicated that the strain of the buried pipeline was mostly affected by the elastic modulus of original soil, followed by the dense sand and the load layer, as well as the results of further analyses with optimal elastic modulus of soil show good agreement with the test.

Keywords: pipeline, optimization, elastic modulus of soil, response surface methodology

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Authors: Launcelot McGrath

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A comprehensive understanding of physiological data is a vital aid to the anaesthesiologist in monitoring and maintaining the well-being of a patient undergoing surgery. Bio signal analysis is one of the most important topics that researchers have tried to develop over the last century to understand numerous human diseases. Understanding which biological signals are most important during anaesthesia is critically important. It is important that the anaesthesiologist understand both the signals themselves and the limitations introduced by the processes of acquisition. In this article, we provide an overview of different types of biological signals as well as the mechanisms applied to acquire them.

Keywords: biological signals, signal acquisition, anaesthesiology, patient monitoring

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Authors: Bilal Arshad, Johan Barthelemy, Elliott Pilton, Pascal Perez

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Getting reliable, informative, and up-to-date information about the location, mobility, and behavioural patterns of animals will enhance our ability to research and preserve biodiversity. The fusion of infra-red sensors and camera traps offers an inexpensive way to collect wildlife data in the form of images. However, extracting useful data from these images, such as the identification and counting of animals remains a manual, time-consuming, and costly process. In this paper, we demonstrate that such information can be automatically retrieved by using state-of-the-art deep learning methods. Another major challenge that ecologists are facing is the recounting of one single animal multiple times due to that animal reappearing in other images taken by the same or other camera traps. Nonetheless, such information can be extremely useful for tracking wildlife and understanding its behaviour. To tackle the multiple count problem, we have designed a meshed network of camera traps, so they can share the captured images along with timestamps, cumulative counts, and dimensions of the animal. The proposed method takes leverage of edge computing to support real-time tracking and monitoring of wildlife. This method has been validated in the field and can be easily extended to other applications focusing on wildlife monitoring and management, where the traditional way of monitoring is expensive and time-consuming.

Keywords: computer vision, ecology, internet of things, invasive species management, wildlife management

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Authors: Abdull Halim Abdul, Muhaimin Sulam

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This paper is about a subsurface study of Taman Pudu Ulu, Cheras, Kuala Lumpur with emphasize of Geo mechanic properties based on stratum index factor in humanities environment. Subsurface drilling and seismic data were used to understand the subsurface condition of the study area such as the type and thickness of the strata. Borehole and soil samples were recovered Geo mechanic properties of the area by conducting number of experiments. Taman Pudu Ulu overlies the Kuala Lumpur Limestone formation that is known for its karstic features such as caves and cavities. Hence by knowing the Geo mechanic properties such as the normal strain and shear strain we can plan a safer and economics construction that is plan at the area in the future.

Keywords: stratum, index factor, geo mechanic properties, humanities environment

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Authors: Fatemeh Elmi, Zahra Etemadifar

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Improvement of soil mechanical properties is crucial before its use in construction, as the low mechanical strength and unstable structure of soil in many parts of the world can lead to the destruction of engineering infrastructure, resulting in financial and human losses. Although, conventional methods, such as chemical injection, are often utilized to enhance soil strength and stiffness, they are generally expensive, require heavy machinery, and cause significant environmental effects due to chemical usage, and also disrupt urban infrastructure. Moreover, they are not suitable for treating large volume of soil. Recently, an alternative method to improve various soil properties, including strength, hardness, and permeability, has received much attention: the application of biological methods. One of the most widely used is biocementation, which is based on the microbial precipitation of calcium carbonte crystalls using ureolytic bacteria However, there are still limitations to its large-scale use that need to be resolved before it can be commercialized. These issues have not received enough attention in prior research. One limitation of MICP (microbially induced calcium carbonate precipitation) is that microorganisms cannot operate effectively in harsh and variable environments, unlike the controlled conditions of a laboratory. Another limitation of applying this technique on a large scale is the high cost of producing a substantial amount of bacterial culture and reagents required for soil treatment. Therefore, the purpose of the present study was to investigate soil improvement using the biocementation activity of poly-extremophile, calcium carbonate crystal- producing bacterial strain, Bhargavaea cecembensis N1, in whey as an inexpensive medium. This strain was isolated and molecularly identified from sandy soils in our previous research, and its 16S rRNA gene sequences was deposited in the NCBI Gene Bank with an accession number MK420385. This strain exhibited a high level of urease activity (8.16 U/ml) and produced a large amount of calcium carbonate (4.1 mg/ ml). It was able to improve the soil by increasing the compressive strength up to 205 kPa and reducing permeability by 36%, with 20% of the improvement attributable of calcium carbonate production. This was achieved using this strain in a whey culture medium. This strain can be an eco-friendly and economical alternative to conventional methods in soil stabilization, and other MICP related applications.

Keywords: biocementation, Bhargavaea cecembensis, soil improvement, whey culture medium

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Authors: Khoa Tan Nguyen, Tuan Anh Le, Kihak Lee

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This paper presents the flexural response of Reinforced Geopolymer Concrete (RGPC) beams. A commercial finite element (FE) software ABAQUS has been used to perform a structural behavior of RGPC beams. Using parameters such: stress, strain, Young’s modulus, and Poisson’s ratio obtained from experimental results, a beam model has been simulated in ABAQUS. The results from experimental tests and ABAQUS simulation were compared. Due to friction forces at the supports and loading rollers; slip occurring, the actual deflection of RGPC beam from experimental test results were slightly different from the results of ABAQUS. And there is good agreement between the crack patterns of fly ash-based geopolymer concrete generated by FE analysis using ABAQUS, and those in experimental data.

Keywords: geopolymer concrete beam, finite element mehod, stress strain relation, modulus elasticity

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Authors: Hyun-Woo Cho

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It is quite important to utilize right time and intelligent production monitoring and diagnosis of industrial processes in terms of quality and safety issues. When compared with monitoring task, fault diagnosis represents the task of finding process variables responsible causing a specific fault in the process. It can be helpful to process operators who should investigate and eliminate root causes more effectively and efficiently. This work focused on the active use of combining a nonlinear statistical technique with a preprocessing method in order to implement practical real-time fault identification schemes for data-rich cases. To compare its performance to existing identification schemes, a case study on a benchmark process was performed in several scenarios. The results showed that the proposed fault identification scheme produced more reliable diagnosis results than linear methods. In addition, the use of the filtering step improved the identification results for the complicated processes with massive data sets.

Keywords: diagnosis, filtering, nonlinear statistical techniques, process monitoring

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Authors: Andrey V. Timofeev

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The practical efficient approach is suggested to estimate the high-speed objects instant bounds in C-OTDR monitoring systems. In case of super-dynamic objects (trains, cars) is difficult to obtain the adequate estimate of the instantaneous object localization because of estimation lag. In other words, reliable estimation coordinates of monitored object requires taking some time for data observation collection by means of C-OTDR system, and only if the required sample volume will be collected the final decision could be issued. But it is contrary to requirements of many real applications. For example, in rail traffic management systems we need to get data off the dynamic objects localization in real time. The way to solve this problem is to use the set of statistical independent parameters of C-OTDR signals for obtaining the most reliable solution in real time. The parameters of this type we can call as 'signaling parameters' (SP). There are several the SP’s which carry information about dynamic objects instant localization for each of C-OTDR channels. The problem is that some of these parameters are very sensitive to dynamics of seismoacoustic emission sources but are non-stable. On the other hand, in case the SP is very stable it becomes insensitive as a rule. This report contains describing the method for SP’s co-processing which is designed to get the most effective dynamic objects localization estimates in the C-OTDR monitoring system framework.

Keywords: C-OTDR-system, co-processing of signaling parameters, high-speed objects localization, multichannel monitoring systems

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Authors: Vathsala Kaluarachchi, Oshani Wimalarathna, Charith Vandebona, Gayani Chandrarathna, Lakmal Rupasinghe, Windhya Rankothge

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It is the fundamental function of a monitoring system to allow users to collect and process data. A worldwide threat, the corona outbreak has wreaked havoc in Sri Lanka, and the situation has gotten out of hand. Since the epidemic, the Sri Lankan government has been unable to establish a systematic system for monitoring corona patients and providing emergency care in the event of an outbreak. Most patients have been held at home because of the high number of patients reported in the nation, but they do not yet have access to a functioning medical system. It has resulted in an increase in the number of patients who have been left untreated because of a lack of medical care. The absence of competent medical monitoring is the biggest cause of mortality for many people nowadays, according to our survey. As a result, a smartphone app for analyzing the patient's state and determining whether they should be hospitalized will be developed. Using the data supplied, we are aiming to send an alarm letter or SMS to the hospital once the system recognizes them. Since we know what those patients need and when they need it, we will put up a desktop program at the hospital to monitor their progress. Deep learning, image processing and application development, natural language processing, and blockchain management are some of the components of the research solution. The purpose of this research paper is to introduce a mechanism to connect hospitals and patients even when they are physically apart. Further data security and user-friendliness are enhanced through blockchain and NLP.

Keywords: blockchain, deep learning, NLP, monitoring system

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Authors: Frank Hespeler, Giuseppe Loiacono

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We propose measures for systemic risk generated through intra-sectorial interdependencies in the hedge fund sector. These measures are based on variations in the average cross-effects of funds showing significant interdependency between their individual returns and the moments of the sector’s return distribution. The proposed measures display a high ability to identify periods of financial distress, are robust to modifications in the underlying econometric model and are consistent with intuitive interpretation of the results.

Keywords: hedge funds, systemic risk, vector autoregressive model, risk monitoring

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Authors: Nishu Atrey, Priyanka Singh, G. P. Talwar, Jagdish Gupta, Alka Kriplani, Rohini Sehgal, Indrani Ganguli, Soni Sinha

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Background: Vaginosis is a widely prevalent syndrome in India and elsewhere. Recurrence is frequent in women treated with antibiotics, whose vagina pH remains above 5.0 indicative of the loss of resident lactobacilli. The objective of the present trial was to determine whether a Polyherbal microbicide BASANT can regress Vaginosis. Another objective was to determine whether the three selected strains of Probiotics endowed with making high amounts of lactic acid can colonise and restore the pH of the vagina to the acidic healthy range. Materials and Procedure: BASANT, was employed in powder form in veg (cellulose) capsules. TRF#36 strain of Lactobacillus fermentum, TRF#8 strain of L.gasseri, and TRF#30 strain of L.salivarius (combination termed as Pro-vag-Health) were employed at 3x109 bacilli lyophilized, packaged in capsules. The trials were conducted in women suffering from vaginosis with vaginal pH above 5.0. Women were given intravaginally either BASANT, Pro-vag-Health or a combination of the two intravaginally for seven days and thereafter once weekly as a maintenance dose. Results: BASANT cleared vaginosis in 14/20 women and Pro-vag-Health in 13/20 women. Interestingly, the combination of BASANT plus Pro-vag-Health was effective in 19/20 women, in contrast to Placebo capsules effective only in 1/20 women. Interpretation and Conclusion: The combination of BASANT and Pro-veg-Health Probiotics taken together intravaginally for seven days relieves 19 out of 20 women from vaginosis to restore acidic pH and healthy vagina. Extension of trial with this combination in larger number is indicated.

Keywords: microbicide, probiotics, vaginal pH, vaginosis

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Authors: Mohamad Mohsen Yavarizadeh

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Polystyrene (PS) and related homopolymers are brittle materials that typically fail in tensile tests at very low strains. These polymers can be toughened by the addition of rubbery particles which initiate a large number of crazes that produce substantial plastic strain at relatively low stresses. Considerable energy is dissipated in the formation of these crazes, producing a relatively tough material that shows an impact toughness of more than 5 times of pure PS. While cross linking of rubbery phase is necessary in aforementioned mechanism of toughening, another mechanism of toughening was also introduced in which low molecular weight liquid rubbers can also toughen PS when dispersed in the form of small pools in the glassy matrix without any cross linking. However, this new mechanism which is based on local plasticization, fails to act properly at high strain rate deformations, i.e. impact tests. In this work, the idea of combination of these two mechanisms was tried. To do so, Polybutadiene rubbers (PB) with bimodal distribution of molecular weight were prepared in which, comparable fractions of very high and very low molecular weight rubbers were mixed. Incorporation of these materials in PS matrix in a reactive process resulted in more significant increases in toughness of PS. In other words, although low molecular weight PB is ineffective in high strain rate impact test by itself, it showed a significant synergistic effect when combined with high molecular weight PB. Surprisingly, incorporation of just 10% of low molecular weight PB doubled the impact toughness of regular high impact PS (HIPS). It was observed that most of rubbery particles could initiate crazes. The effectiveness of low molecular weight PB in impact test was attributed to low strain rate deformation of each individual craze as a result of producing a large number of crazes in this material. In other words, high molecular weight PB chains make it possible to have an appropriate dispersion of rubbery phase in order to create a large number of crazes in the PS matrix and consequently decrease the velocity of each craze. Low molecular weight PB, in turn, would have enough time to locally plasticize craze fibrils and enhance the energy dissipation.

Keywords: molecular weight distribution, polystyrene, toughness, homopolymer

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Authors: Chen-Fang Tsai, Shin-Li Lu

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Distribution-free control chart is an oncoming area from the statistical process control charts in recent years. Some researchers have developed various nonparametric control charts and investigated the detection capability of these charts. The major advantage of nonparametric control charts is that the underlying process is not specifically considered the assumption of normality or any parametric distribution. In this paper, two nonparametric exponentially weighted moving average (EWMA) control charts based on nonparametric tests, namely NE-S and NE-M control charts, are proposed for monitoring process variability. Generally, weighted moving average (GWMA) control charts are extended by utilizing design and adjustment parameters for monitoring the changes in the process variability, namely NG-S and NG-M control charts. Statistical performance is also investigated on NG-S and NG-M control charts with run rules. Moreover, sensitivity analysis is performed to show the effects of design parameters under the nonparametric NG-S and NG-M control charts.

Keywords: Distribution-free control chart, EWMA control charts, GWMA control charts

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Authors: Khairul Zahreen Mohd Arof, Rahimah Muhamad

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Oil palm fiber (OPF) is a fibrous material produced from the waste of palm oil industry which is suitable to be used in construction industry. The applications of OPF in concrete can reduce the material costs and enhance concrete behavior. Dog-bone test provides significant results for investigating the behavior of fiber reinforced concrete under tensile loading. It is able to provide stress-strain profile, modulus of elasticity, stress at cracking point and total crack width. In this research, dog-bone tests have been conducted to analyze total crack width, stress-strain profile, and modulus of elasticity of OPFC. Specimens are in a dog-bone shape with a long notch in the middle as compared to the end, to ensure cracks occur only within the notch. Tests were instrumented using a universal testing machine Shimadzu 300kN, a linear variable differential transformer and two strain gauges. A total of nine specimens with different fibers at fiber volume fractions of 0.75%, 1.00%, and 1.25% have been tested to analyze the behavior under tensile loading. Also, three specimens of plain concrete fiber have been tested as control specimens. The tensile test of all specimens have been carried out for concrete age exceed 28 days. It shows that OPFC able to reduce total crack width. In addition, OPFC has higher cracking stress than plain concrete. The study shows plain concrete can be improved with the addition of OPF.

Keywords: cracks, crack width, dog-bone test, oil palm fiber concrete

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Authors: Afef Dridi, Salah Mezlini

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Since experimental devices cannot calculate stress and deformation of complex structures. The Finite Element Method FEM has been widely used in several fields of research. One of these fields is orthodontics. The advantage of using such a method is the use of an accurate and non invasive method that allows us to have a sufficient data about the physiological reactions can happening in soft tissues. Most of researches done in this field were interested in the study of stresses and deformations induced by orthodontic apparatus in soft tissues (alveolar tissues). Only few studies were interested in the distribution of stress and strain in the orthodontic brackets. These studies, although they tried to be as close as possible to real conditions, their models did not reproduce the clinical cases. For this reason, the model generated by our research is the closest one to reality. In this study, a numerical model was developed to explore the stress and strain distribution under the application of real conditions. A comparison between different material properties was also done.

Keywords: visco-hyperelasticity, FEM, orthodontic treatment, inverse method

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Authors: Henrique C. C. Andrade, Ana Beatriz C. G. Silva, Fernando Luiz B. Ribeiro, Samir Maghous, Jose Claudio F. Telles, Eduardo M. R. Fairbairn

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The present paper aims at developing a parallel computational model for numerical simulation of poromechanics analyses of heterogeneous reservoirs. In the context of macroscopic poroelastoplasticity, the hydromechanical coupling between the skeleton deformation and the fluid pressure is addressed by means of two constitutive equations. The first state equation relates the stress to skeleton strain and pore pressure, while the second state equation relates the Lagrangian porosity change to skeleton volume strain and pore pressure. A specific algorithm for local plastic integration using a tangent operator is devised. A modified Cam-clay type yield surface with associated plastic flow rule is adopted to account for both contractive and dilative behavior.

Keywords: finite element method, poromechanics, poroplasticity, reservoir analysis

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Authors: Mohsen Sanayei, Jerzy Szpunar

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The present study investigates the effects of deformation strain and annealing temperature on the formation of twin boundaries, deformation and recrystallization texture evolution and grain boundary networks and connectivity. The resulting microstructures were characterized using Electron Backscatter Diffraction (EBSD) and X-Ray Diffraction (XRD) both immediately following small amount of deformation and after short time annealing at high temperature to correlate the micro and macro texture evolution of these alloys. Furthermore, this study showed that the process of grain boundary engineering, consisting cycles of deformation and annealing, is found to substantially reduce the mass and size of random boundaries and increase the proportion of low Coincidence Site Lattice (CSL) grain boundaries.

Keywords: coincidence site lattice, grain boundary engineering, electron backscatter diffraction, texture, x-ray diffraction

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Authors: Bryce Benson, Sooin Lee, Ashwin Belle

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Unrecognized or delayed identification of patient deterioration is a key cause of in-hospitals adverse events. Clinicians rely on vital signs monitoring to recognize patient deterioration. However, due to ever increasing nursing workloads and the manual effort required, vital signs tend to be measured and recorded intermittently, and inconsistently causing large gaps during patient monitoring. Additionally, during deterioration, the body’s autonomic nervous system activates compensatory mechanisms causing the vital signs to be lagging indicators of underlying hemodynamic decline. This study analyzes the predictive efficacy of the Analytic for Hemodynamic Instability (AHI) system, an automated tool that was designed to help clinicians in early identification of deteriorating patients. The lead time analysis in this retrospective observational study assesses how far in advance AHI predicted deterioration prior to the start of an episode of hemodynamic instability (HI) becoming evident through vital signs? Results indicate that of the 362 episodes of HI in this study, 308 episodes (85%) were correctly predicted by the AHI system with a median lead time of 57 minutes and an average of 4 hours (240.5 minutes). Of the 54 episodes not predicted, AHI detected 45 of them while the episode of HI was ongoing. Of the 9 undetected, 5 were not detected by AHI due to either missing or noisy input ECG data during the episode of HI. In total, AHI was able to either predict or detect 98.9% of all episodes of HI in this study. These results suggest that AHI could provide an additional ‘pair of eyes’ on patients, continuously filling the monitoring gaps and consequently giving the patient care team the ability to be far more proactive in patient monitoring and adverse event management.

Keywords: clinical deterioration prediction, decision support system, early warning system, hemodynamic status, physiologic monitoring

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Authors: Deepika Biswas

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Acinetobacter baumannii, a hospital-acquired pathogen, causes nosocomial infections including pneumonia, urinary tract infection, and secondary meningitis. Carbapenem is most effective antibiotics against it. Its increased resistance to carbapenems has been a rising global concern. Antibiotics such as carbapenem are unable to use on hospital setups to eradicate A. baumannii, hence different concentrations of disinfectants including phenol; sodium hypochlorite and ethanol are increasingly being used. The objective of the present study is to find an effective concentration of above disinfectants against carbapenem-resistant strain RS307 of A. baumannii. Growth kinetics of RS307 has been determined using UV-Vis spectrophotometer in the presence and absence of disinfectants in triplicate and its standard deviation has also been calculated which make the results more reliable. Differential growth curves were plotted, which showed the effective concentration among all the concentrations of phenol, sodium hypochlorite and ethanol. On disc diffusion assay, antimicrobial effect was observed by comparing all the concentrations of disinfectants to check its synergy with imipenem, most effective carbapenem. All the results collectively revealed that 0.5% phenol, 0.5% sodium hypochlorite, and 70% ethanol could preferably be used as disinfectant for hospital setup against the carbapenem-resistant strain of A. baumannii. SDS PAGE analysis showed differential expression in the protein profile of A. baumannii after treatment. The present study highlighted that few disinfectants even in low concentration had shown better antimicrobial activity hence may be recommended for regular use in the hospitals, which will be cost effective and less harmful.

Keywords: Acenatobacter bomunii, phenol, sodium hypoclirite, ethanol, carbapenem resistance, disinfectant

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Authors: Pouya Taraghi, Yong Li, Nader Yoosef-Ghodsi, Muntaseer Kainat, Samer Adeeb

Abstract:

Buried pipelines play a crucial role in the transportation of energy products such as oil, gas, and various chemical fluids, ensuring their efficient and safe distribution. However, these pipelines are often susceptible to ground movements caused by geohazards like landslides, fault movements, lateral spreading, and more. Such ground movements can lead to strain-induced failures in pipes, resulting in leaks or explosions, leading to fires, financial losses, environmental contamination, and even loss of human life. Therefore, it is essential to study how buried pipelines respond when traversing geohazard-prone areas to assess the potential impact of ground movement on pipeline design. As such, this study introduces an approach called the Physics-Informed Neural Network (PINN) to predict the strain demand in inelastic pipes subjected to permanent ground displacement (PGD). This method uses a deep learning framework that does not require training data and makes it feasible to consider more realistic assumptions regarding existing nonlinearities. It leverages the underlying physics described by differential equations to approximate the solution. The study analyzes various scenarios involving different geohazard types, PGD values, and crossing angles, comparing the predictions with results obtained from finite element methods. The findings demonstrate a good agreement between the results of the proposed method and the finite element method, highlighting its potential as a simulation-free, data-free, and meshless alternative. This study paves the way for further advancements, such as the simulation-free reliability assessment of pipes subjected to PGD, as part of ongoing research that leverages the proposed method.

Keywords: strain demand, inelastic pipe, permanent ground displacement, machine learning, physics-informed neural network

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Authors: F. Sahnoune, M. Belhamel, M. Zelmat

Abstract:

Solar thermal systems available today provide reliability, efficiency and significant environmental benefits. In housing, they can satisfy the hot water demand and reduce energy bills by 60 % or more. Additionally, collective systems or large scale solar thermal systems are increasingly used in different conditions for hot water applications and space heating in hotels and multi-family homes, hospitals, nursing homes and sport halls as well as in commercial and industrial building. However, in situ real performance data for collective solar water heating systems has not been extensively outlined. This paper focuses on the study of real energy performances of a collective solar water heating system using the remote monitoring technique in Algerian climatic conditions. This is to ensure proper operation of the system at any time, determine the system performance and to check to what extent solar performance guarantee can be achieved. The measurements are performed on an active indirect heating system of 12 m2 flat plate collector’s surface installed in Algiers and equipped with a various sensors. The sensors transmit measurements to a local station which controls the pumps, valves, electrical auxiliaries, etc. The simulation of the installation was developed using the software SOLO 2000. The system provides a yearly solar yield of 6277.5 KWh for an estimated annual need of 7896 kWh; the yearly average solar cover rate amounted to 79.5%. The productivity is in the order of 523.13 kWh / m²/year. Simulation results are compared to measured results and to guaranteed solar performances. The remote monitoring shows that 90% of the expected solar results can be easy guaranteed on a long period. Furthermore, the installed remote monitoring unit was able to detect some dysfunctions. It follows that remote monitoring is an important tool in energy management of some building equipment.

Keywords: large-scale solar water heater, real energy performance, remote monitoring, solar performance guarantee, tool to promote solar water heater

Procedia PDF Downloads 232

Authors: Lucas Bublitz, Michael Herdrich

Abstract:

By achieving the first commercialization approval in San Francisco the Autonomous Driving (AD) industry proves the technology maturity of the SAE L4 AD systems and the corresponding software and hardware stack. This milestone reflects the upcoming phase in the industry, where the focus is now about scaling and supervising larger autonomous vehicle (AV) fleets in different operation areas. This requires an operation framework, which organizes and assigns responsibilities to the relevant AV technology and operation stakeholders from the AV system provider, the Remote Intervention Operator, the MaaS provider and regulatory & approval authority. This holistic operation framework consists of technological, processual, and organizational activities to ensure safe operation for fully automated vehicles. Regarding the supervision of large autonomous vehicle fleets, a major focus is on the continuous field monitoring. The field monitoring approach must reflect the safety and security criticality of incidents in the field during driving operation. This includes an automatic containment approach, with the overall goal to avoid safety critical incidents and reduce downtime by a malfunction of the AD software stack. An End-to-end (E2E) field monitoring approach detects critical faults in the field, uses a knowledge-based approach for evaluating the safety criticality and supports the automatic containment of these E/E faults. Applying such an approach will ensure the scalability of AV fleets, which is determined by the handling of incidents in the field and the continuous regulatory compliance of the technology after enhancing the Operational Design Domain (ODD) or the function scope by Functions on Demand (FoD) over the entire digital product lifecycle.

Keywords: field monitoring, incident management, multicompliance management for AI in AD, root cause analysis, database approach

Procedia PDF Downloads 64

Authors: Noor Ismael, Lisa Mische Lawson, Lauren Little, Murad Moqbel

Abstract:

Background/Significance: Caregivers of children with Autism Spectrum Disorders (ASD) develop coping mechanisms to overcome daily challenges to successfully parent their child. There is variability in coping strategies used among caregivers of children with ASD. Capturing homogeneity among such variable groups may help elucidate targeted intervention approaches for caregivers of children with ASD. Study Purpose: This study aimed to identify groups of caregivers of children with ASD based on coping mechanisms, and to examine whether there are differences among these groups in terms of strain level. Methods: This study utilized a secondary data analysis, and included survey responses of 273 caregivers of children with ASD. Measures consisted of the COPE Inventory and the Caregiver Strain Questionnaire. Data analyses consisted of cluster analysis to group caregiver coping strategies, and analysis of variance to compare the caregiver coping groups on strain level. Results: Cluster analysis results showed four distinct groups with different combinations of coping strategies: Social-Supported/Planning (group one), Spontaneous/Reactive (group two), Self-Supporting/Reappraisal (group three), and Religious/Expressive (group four). Caregivers in group one (Social-Supported/Planning) demonstrated significantly higher levels than the remaining three groups in the use of the following coping strategies: planning, use of instrumental social support, and use of emotional social support, relative to the other three groups. Caregivers in group two (Spontaneous/Reactive) used less restraint relative to the other three groups, and less suppression of competing activities relative to the other three groups as coping strategies. Also, group two showed significantly lower levels of religious coping as compared to the other three groups. In contrast to group one, caregivers in group three (Self-Supporting/Reappraisal) demonstrated significantly lower levels of the use of instrumental social support and the use of emotional social support relative to the other three groups. Additionally, caregivers in group three showed more acceptance, positive reinterpretation and growth coping strategies. Caregivers in group four (Religious/Expressive) demonstrated significantly higher levels of religious coping relative to the other three groups and utilized more venting of emotions strategies. Analysis of Variance results showed no significant differences between the four groups on the strain scores. Conclusions: There are four distinct groups with different combinations of coping strategies: Social-Supported/Planning, Spontaneous/Reactive, Self-Supporting/Reappraisal, and Religious/Expressive. Each caregiver group engaged in a combination of coping strategies to overcome the strain of caregiving.

Keywords: autism, caregivers, cluster analysis, coping strategies

Procedia PDF Downloads 277