Search results for: real time stress detection

Authors: Sundru Manjulata Devi, Prakash M. Halami

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The immemorial use of fermented foods from vegetables, dairy and other biological sources are of great demand in India because of their health benefits. However, the diversity of Lactobacillus plantarum group (LPG) of vegetable origin has not been revealed yet, particularly with reference to their probiotic functionalities. In the present study, the different species of probiotic Lactobacillus plantarum group (LPG) i.e., L. plantarum subsp. plantarum MTCC 5422 (from fermented cereals), L. plantarum subsp. argentoratensis FG16 (from fermented bamboo shoot) and L. paraplantarum MTCC 9483 (from fermented gundruk) (as characterized by multiplex recA PCR assay) were considered to investigate their relative expression of MUB domains of mub gene (mucin binding protein) by Real time PCR. Initially, the allelic variation in the mub gene was assessed and found to encode three different variants (Type I, II and III). All the three types had 8, 9 and 10 MUB domains respectively (as analysed by Pfam database) and were found to be responsible for adhesion of bacteria to the host intestinal epithelial cells. These domains either get inserted or deleted during speciation or evolutionary events and lead to divergence. The reverse transcriptase qPCR analysis with mubLPF1+R1 primer pair supported variation in amplicon sizes with 300, 500 and 700 bp among different LPG strains. The relative expression of these MUB domains significantly unregulated in the presence of 1% mucin in overnight grown cultures. Simultaneously, the mub gene expressed efficiently by 7 fold in the culture L. paraplantarum MTCC 9483 with 10 MUB domains. An increase in the expression levels for L. plantarum subsp. plantarum MTCC 5422 and L. plantarum subsp. argentoratensis FG16 (MCC 2974) with 9 and 8 repetitive domains was around 4 and 2 fold, respectively. The detection and expression of an integrase (int) gene in the upstream region of mub gene reveals the excision and integration of these repetitive domains. Concurrently, an in vitro adhesion assay to mucin and exclusion of pathogens (such as Listeria monocytogenes and Micrococcus leuteus) was investigated and observed that the L. paraplantarum MTCC 9483 with more adhesion domains has more ability to adhere to mucin and inhibited the growth of pathogens. The production and expression of plantaricin-like bacteriocin (plnNC8 type) in MTCC 9483 suggests the pathogen inhibition. Hence, the expression of MUB domains can act as potential biomarkers in the screening of a novel probiotic LPG strain with adherence property. The present study provides a platform for an easy, rapid, less time consuming, low-cost methodology for the detection of potential probiotic bacteria. It was known that the traditional practices followed in the preparation of fermented bamboo shoots/gundruk/cereals of Indian foods contain different kinds of neutraceuticals for functional food and novel compounds with health promoting factors. In future, a detailed study of these food products can add more nutritive value, consumption and suitable for commercialization.

Keywords: adhesion gene, fermented foods, MUB domains, probiotics

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Authors: Eyosiyas Aga

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The development of information communication technology has transformed the paper-based mapping and land registration processes to a computerized and networked system. The computerization and networking of real property information system play a vital role in good governance and sustainable development of emerging countries through cost effective, easy and accessible service delivery for the customer. The efficient, transparent and sustainable real property system is becoming the basic infrastructure for the urban development thus improve the data management system and service delivery in the organizations. In Ethiopia, the real property administration is paper based as a result, it confronted problems of data management, illegal transactions, corruptions, and poor service delivery. In order to solve this problem and to facilitate real property market, the implementation of web-based real property updating system is crucial. A web-based real property updating is one of the automation (computerizations) methods to facilitate data sharing, reduce time and cost of the service delivery in real property administration system. In additions, it is useful for the integration of data onto different information systems and organizations. This system is designed by combining open source software which supported by open Geo-spatial consortium. The web-based system is mainly designed by using open source software with the help of open Geo-spatial Consortium. The Open Geo-spatial Consortium standards such as the Web Feature Service and Web Map Services are the most widely used standards to support and improves web-based real property updating. These features allow the integration of data from different sources, and it can be used to maintain consistency of data throughout transactions. The PostgreSQL and Geoserver are used to manage and connect a real property data to the flex viewer and user interface. The system is designed for both internal updating system (municipality); which is mainly updating of spatial and textual information, and the external system (customer) which focus on providing and interacting with the customer. This research assessed the potential of open source web applications and adopted this technology for real property updating system in Ethiopia through simple, cost effective and secured way. The system is designed by combining and customizing open source software to enhance the efficiency of the system in cost effective way. The existing workflow for real property updating is analyzed to identify the bottlenecks, and the new workflow is designed for the system. The requirement is identified through questionnaire and literature review, and the system is prototype for the study area. The research mainly aimed to integrate human resource with technology in designing of the system to reduce data inconsistency and security problems. In additions, the research reflects on the current situation of real property administration and contributions of effective data management system for efficient, transparent and sustainable urban development in Ethiopia.

Keywords: cadaster, real property, sustainable, transparency, web feature service, web map service

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Authors: Maryam Monazzah, Ronak Samadpour, Mehdi Nasr-esfahani, Fatemeh Qalavand, Marziye Motamedi

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Bipolaris sorokiniana, and Heterodera filipjevi, are important wheat diseases that lead to yield losses worldwide. Identifying novel resistant sources helps us combat these devastating diseases. In this study, we studied the role of Cre3 gene and antioxidant enzymes in the immune responses of wheat genotypes to H. filipjevi and B. sorokiniana. Therefore, real-time PCR analysis using Cre3 gene marker, a resistant gene to cereal cyst nematodes, was conducted on leaves and roots, along with changes ‎in the activity of antioxidant enzymes, peroxidase, and catalase. Enzyme activity assay was performed on roots attacked by nematode and in leaves infected with Bipolaris. Wheat accessions including “Bam” (resistant), “Parsi” (moderately-resistant), “Azar2”, “Ohadi”, “Homa” (highly-susceptible) were previously screened against both stresses under greenhouse and field conditions. Results showed that Cre3 expression against cyst nematodes was significantly higher in resistant cultivars compared to susceptible cultivars. Cre3 was used in marker-assisted selection programs to identify genotypes carrying resistant genes to cyst nematodes. Interestingly, Cre3 was also up-regulated in both tissues of resistant cultivars to B. sorokiniana. Therefore, Cre3 in wheat similarly modulates immunity against B. sorokiniana and might be one of the central components of the induced immune system in wheat. The activity of antioxidant enzymes also indicated the highest increase in resistant genotypes upon both stresses that subsequently neutralize oxidative stress in tissues and decrease damage. Further studies on these resistance components may help us gain insight into the molecular basis of resistance and shed new light on the interaction and overlap between different forms of stress.

Keywords: Bipolaris sorokiniana, Heterodera filipjevi, resistant gene expression, wheat

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Authors: A. Şahinoğlu, R. Gürbüz, A. Güllü, M. Karhan

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This study in production machines, it is aimed that machine will automatically perceive cutting data and alter cutting parameters. The two most important parameters have to be checked in machine control unit are progress feed rate and speeds. These parameters are aimed to be controlled by sounds of machine. Optimum sound’s features introduced to computer. During process, real time data is received and converted by Matlab software. Data is converted into numerical values. According to them progress and speeds decreases/increases at a certain rate and thus optimum sound is acquired. Cutting process is made in respect of optimum cutting parameters. During chip remove progress, features of cutting tools, kind of cut material, cutting parameters and used machine; affects on various parameters. Instead of required parameters need to be measured such as temperature, vibration, and tool wear that emerged during cutting process; detailed analysis of the sound emerged during cutting process will provide detection of various data that included in the cutting process by the much more easy and economic way. The relation between cutting parameters and sound is being identified.

Keywords: cutting process, sound processing, intelligent late, sound analysis

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Authors: Hyun-Woo Cho

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The real-time fault monitoring and diagnosis of large scale production processes is helpful and necessary in order to operate industrial process safely and efficiently producing good final product quality. Unusual and abnormal events of the process may have a serious impact on the process such as malfunctions or breakdowns. This work try to utilize process measurement data obtained in an on-line basis for the safe and some fault-free operation of industrial processes. To this end, this work evaluated the proposed intelligent process data monitoring framework based on a simulation process. The monitoring scheme extracts the fault pattern in the reduced space for the reliable data representation. Moreover, this work shows the results of using linear and nonlinear techniques for the monitoring purpose. It has shown that the nonlinear technique produced more reliable monitoring results and outperforms linear methods. The adoption of the qualitative monitoring model helps to reduce the sensitivity of the fault pattern to noise.

Keywords: process data, data mining, process operation, real-time monitoring

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Authors: Ja'afar Umar, Salisu Naziru

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Submergence stress in plants refers to the physiological and biochemical challenges that occur when plants are partially or fully submerged in water. This type of stress primarily affects plants in flood-prone areas or regions with heavy rainfall, where oxygen availability and other essential resources are limited. Salicylic acid (SA) is an important plant hormone involved in various physiological processes and responses to environmental stress, particularly in plant defense mechanisms against pathogens. Its role as a signaling molecule in plants is crucial for activating defense pathways, regulating growth, and managing responses to biotic (living) and abiotic (non-living) stresses. The study involved using salicylic acid (SA) at concentrations of 1g/L, 2g/L, and 3g/L, dissolved in water, to treat rice plants during submergence stress. The experiment had four treatments: 0g/L (control), 1g/L, 2g/L, and 3g/L of SA, each with four replications. Rice seedlings were submerged in water for 11 days and then desubmerged for 7 days. During the experiment, all plants except the control received a foliar spray of SA solutions, while control plants were sprayed with distilled water. The results indicate a significant difference (P<0.05) between the control and salicylic acid (SA)-treated rice plants. SalicyJalic acid, particularly at concentrations of 1g/L, 2g/L, and 3g/L, generally improved the recovery of all four rice cultivars from submergence stress, as reflected by increased numbers of nodes, longer internodes, taller plants, and longer root lengths compared to untreated controls. Salicylic acid, particularly at concentrations of 1g/L, 2g/L, and 3g/L, generally improved the recovery of all four rice cultivars from submergence stress, as reflected by increased numbers of nodes, longer internodes, taller plants, and longer root lengths compared to untreated controls.

Keywords: submergence, stress, rice, salicylic

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Authors: Hesam Khajehsaeid, Naeimeh Alagheband

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Magnetorheological fluids (MRF) are a category of smart materials. They exhibit a reversible change from a Newtonian-like fluid to a semi-solid state upon application of an external magnetic field. In contrast to ordinary fluids, MRFs can tolerate shear stresses up to a threshold value called yield stress which strongly depends on the strength of the magnetic field, magnetic particles volume fraction and temperature. Even beyond the yield, a magnetic field can increase MR fluid viscosity up to several orders. As yield stress is an important parameter in the design of MR devices, in this work, the effects of magnetic field intensity and magnetic particle concentration on the yield stress of MRFs are investigated. Four MRF samples with different particle concentrations are developed and tested through flow-ramp analysis to obtain the flow curves at a range of magnetic field intensity as well as shear rate. The viscosity of the fluids is determined by means of the flow curves. The results are then used to determine the yield stresses by means of the steady stress sweep method. The yield stresses are then determined by means of a modified form of the dipole model as well as empirical models. The exponential distribution function is used to describe the orientation of particle chains in the dipole model under the action of the external magnetic field. Moreover, the modified dipole model results in a reasonable distribution of chains compared to previous similar models.

Keywords: magnetorheological fluids, yield stress, particles concentration, dipole model

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Authors: Ke Guek Nee, Wong Siew Fan, Nigel V. Marsh

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Excessive use of the Internet has become a cause for concern in many countries, including Malaysia. Such behaviour is reported to be more prevalent amongst young adults who are reported to be spending large amount of time on the Internet. The present study has three objectives. First one is designing a manual-based Cognitive Behavioural Therapy (CBT) programme to reduce problematic Internet use among young adults in Malaysia. Second one is examining the effectiveness of a manual-based CBT programme at the pilot study stage. Thirdly, the programme focuses on reducing the level of stress and anxiety in problematic Internet users. We adopted CBT with single subject experimental design method. A total of six participants completed the entire program. They were asked to report their daily Internet use and software was installed on their devices to record actual use. The data collection involved three time frame measurements: T1 (baseline), T2 (immediately during the last session of the intervention sessions), and T3 (follow-up). Three scales were used to measure the effectiveness of the program: Depression, Anxiety, Stress Scales (DASS), Social Interaction Anxiety Scale (SIAS), and Problematic Internet Use Questionnaire (PIUQ). The results revealed that the intervention programme has significantly improved two dimensions of problematic Internet use which were obsession and control disorder. The participants’ mental health also showed a deduction in means scores for depression, anxiety and stress with depression showing the greatest improvement after the intervention programme. The participants’ social anxiety showed a slight deduction in means scores. We concluded that the intervention programme designed was effective. However, its limitations need to be addressed in future research.

Keywords: excessive internet use, cognitive behavioral thearapy (CBT), psychological well-being, young adults

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Authors: Sang Hun Park, Moung Young Lee, Su Min Yu, Hyun Sang Jo, Ji Hyeon Kim, Chul Gyu Song

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A near-infrared light source used as a light source in the fluorescence imaging system is suitable for use in real-time during the operation since it has no interference in surgical vision. However, fluorescence images do not have depth information. In this paper, we configured the device with the research on molecular imaging systems for monitoring thrombus imaging using fluorescence and photoacoustic. Fluorescence imaging was performed using a phantom experiment in order to search the exact location, and the Photoacoustic image was in order to detect the depth. Fluorescence image obtained when evaluated through current phantom experiments when the concentration of the contrast agent is 25μg / ml, it was confirmed that it looked sharper. The phantom experiment is has shown the possibility with the fluorescence image and photoacoustic image using an indocyanine green contrast agent. For early diagnosis of cardiovascular diseases, more active research with the fusion of different molecular imaging devices is required.

Keywords: fluorescence, photoacoustic, indocyanine green, carotid artery

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Authors: Muhammad Hassan Khalil, Xu Jiadong

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Early detection through screening is the best tool short of a perfect treatment against the malignant tumor inside the breast of a woman. By detecting cancer in its early stages, it can be recognized and treated before it has the opportunity to spread and change into potentially dangerous. Microwave tomography is a new imaging method based on contrast in dielectric properties of materials. The mathematical theory of microwave tomography involves solving an inverse problem for Maxwell’s equations. In this paper, we present designed antenna for breast cancer detection, which will use in microwave tomography configuration.

Keywords: microwave imaging, inverse scattering, breast cancer, malignant tumor detection

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Authors: Antonio Monteiro, Jorge Azevedo, Severiano Silva, Alfredo Teixeira

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The objective of this study was to compare the carcass and in vivo real-time ultrasound measurements (RTU) and their capacity to predict the composition of Serrana goats up to 40% of maturity. Twenty one females (11.1 ± 3.97 kg) and Twenty one males (15.6 ± 5.38 kg) were utilized to made in vivo measurements with a 5 MHz probe (ALOKA 500V scanner) at the 9th-10th, 10th-11th thoracic vertebrae (uT910 and uT1011, respectively), at the 1st- 2nd, 3rd-4th, and 4th-5th lumbar vertebrae (uL12, ul34 and uL45, respectively) and also at the 3rd-4th sternebrae (EEST). It was recorded the images of RTU measurements of Longissimus thoracis et lumborum muscle (LTL) depth (EM), width (LM), perimeter (PM), area (AM) and subcutaneous fat thickness (SFD) above the LTL, as well as the depth of tissues of the sternum (EEST) between the 3rd-4th sternebrae. All RTU images were analyzed using the ImageJ software. After slaughter, the carcasses were stored at 4 ºC for 24 h. After this period the carcasses were divided and the left half was entirely dissected into muscle, dissected fat (subcutaneous fat plus intermuscular fat) and bone. Prior to the dissection measurements equivalent to those obtained in vivo with RTU were recorded. Using the Statistica 5, correlation and regression analyses were performed. The prediction of carcass composition was achieved by stepwise regression procedure, with live weight and RTU measurements with and without transformation of variables to the same dimension. The RTU and carcass measurements, except for SFD measurements, showed high correlation (r > 0.60, P < 0.001). The RTU measurements and the live weight, showed ability to predict carcass composition on muscle (R2 = 0.99, P < 0.001), subcutaneous fat (R2 = 0.41, P < 0.001), intermuscular fat (R2 = 0.84, P < 0.001), dissected fat (R2 = 0.71, P < 0.001) and bone (R2 = 0.94, P < 0.001). The transformation of variables allowed a slight increase of precision, but with the increase in the number of variables, with the exception of subcutaneous fat prediction. In vivo measurements by RTU can be applied to predict kid goat carcass composition, from 5 measurements of RTU and the live weight.

Keywords: carcass, goats, real time, ultrasound

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Authors: Miroslav Popelka, Jakub Nozicka

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The whole work is based on possibility to use Lego Mindstorms robotics systems to reduce costs. Lego Mindstorms consists of a wide variety of hardware components necessary to simulate, programme and test of robotics systems in practice. To programme algorithm, which simulates space using the ultrasonic sensor, was used development environment supplied with kit. Software Matlab was used to render values afterwards they were measured by ultrasonic sensor. The algorithm created for this paper uses theoretical knowledge from area of signal processing. Data being processed by algorithm are collected by ultrasonic sensor that scans 2D space in front of it. Ultrasonic sensor is placed on moving arm of robot which provides horizontal moving of sensor. Vertical movement of sensor is provided by wheel drive. The robot follows map in order to get correct positioning of measured data. Based on discovered facts it is possible to consider Lego Mindstorm for low-cost and capable kit for real-time modelling.

Keywords: LEGO Mindstorms, ultrasonic sensor, real-time modeling, 2D object, low-cost robotics systems, sensors, Matlab, EV3 Home Edition Software

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Authors: Zulkifli Zainal Abidin, Ahmad Shahril Mohd Ghani

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Agent-based systems technology has been addressed as a new paradigm for conceptualizing, designing, and implementing software systems. Agents are sophisticated systems that act autonomously across open and distributed environments in solving problems. Nevertheless, it is impractical to rely on a single agent to do all computing processes in solving complex problems. An increasing number of applications lately require multiple agents to work together. A multi-agent system (MAS) is a loosely coupled network of agents that interact to solve problems that are beyond the individual capacities or knowledge of each problem solver. However, the network of MAS still requires a main system to govern or oversees the operation of the agents in order to achieve a unified goal. We had developed a fleet management system (FMS) in order to manage the fleet of agents, plan route for the agents, perform real-time data processing and analysis, and issue sets of general and specific instructions to the agents. This FMS should be able to perform real-time data processing, communicate with the autonomous surface vehicle (ASV) agents and generate bathymetric map according to the data received from each ASV unit. The first algorithm is developed to communicate with the ASV via radio communication using standard National Marine Electronics Association (NMEA) protocol sentences. Next, the second algorithm will take care of the path planning, formation and pattern generation is tested using various sample data. Lastly, the bathymetry map generation algorithm will make use of data collected by the agents to create bathymetry map in real-time. The outcome of this research is expected can be applied on various other multi-agent systems.

Keywords: autonomous surface vehicle, fleet management system, multi agent system, bathymetry

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Authors: Caio Marcelo Nunes, Anderson da Silva Soares, Gustavo Teodoro Laureano, Clarimar Jose Coelho

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This paper presents a methodology to pixel recognition in aerial images using fuzzy $c$-means algorithm. This algorithm is a alternative to recognize areas considering uncertainties and inaccuracies. Traditional clustering technics are used in recognizing of multispectral images of earth's surface. This technics recognize well-defined borders that can be easily discretized. However, in the real world there are many areas with uncertainties and inaccuracies which can be mapped by clustering algorithms that use fuzzy sets. The methodology presents in this work is applied to multispectral images obtained from Landsat-5/TM satellite. The pixels are joined using the $c$-means algorithm. After, a classification process identify the types of surface according the patterns obtained from spectral response of image surface. The classes considered are, exposed soil, moist soil, vegetation, turbid water and clean water. The results obtained shows that the fuzzy clustering identify the real type of the earth's surface.

Keywords: aerial images, fuzzy clustering, image processing, pattern recognition

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Authors: Rishi Agarwal

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Digital twins are emerging as a strong technology used to imitate and monitor physical objects digitally in real time across sectors. It is not only dealing with the digital space, but it is also actuating responses in the physical space in response to the digital space processing like storage, modeling, learning, simulation, and prediction. This paper explores the application of digital twins for enhancing physical security in retail stores. The retail sector still relies on outdated physical security practices like manual monitoring and metal detectors, which are insufficient for modern needs. There is a lack of real-time data and system integration, leading to ineffective emergency response and preventative measures. As retail automation increases, new digital frameworks must control safety without human intervention. To address this, the paper proposes implementing an intelligent digital twin framework. This collects diverse data streams from in-store sensors, surveillance, external sources, and customer devices and then Advanced analytics and simulations enable real-time monitoring, incident prediction, automated emergency procedures, and stakeholder coordination. Overall, the digital twin improves physical security through automation, adaptability, and comprehensive data sharing. The paper also analyzes the pros and cons of implementation of this technology through an Emerging Technology Analysis Canvas that analyzes different aspects of this technology through both narrow and wide lenses to help decision makers in their decision of implementing this technology. On a broader scale, this showcases the value of digital twins in transforming legacy systems across sectors and how data sharing can create a safer world for both retail store customers and owners.

Keywords: digital twin, retail store safety, digital twin in retail, digital twin for physical safety

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Authors: Malla Vijayeta, Y. Vijaya Kumar, N. Ramakrishna Raju, K. Satyanarayana

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Global AEC (architecture, engineering, and construction) industry has been coined as one of the most resistive domains in embracing technology. Although this digital era has been inundated with software tools like CAD, STADD, CANDY, Microsoft Project, Primavera etc. the key stakeholders have been working in siloes and processes remain fragmented. Unlike the yesteryears’ simpler project delivery methods, the current projects are of fast-track, complex, risky, multidisciplinary, stakeholder’s influential, statutorily regulative etc. pose extensive bottlenecks in preventing timely completion of projects. At this juncture, a paradigm shift surfaced in construction industry, and Building Information Modeling, aka BIM, has been a panacea to bolster the multidisciplinary teams’ cooperative and collaborative work leading to productive, sustainable and leaner project outcome. Building information modeling has been integrative, stakeholder engaging and centralized approach in providing a common platform of communication. A common misconception that BIM can be used for building/high rise projects in Indian Construction Industry, while this paper discusses of the implementation of BIM processes/methodologies in water and waste water industry. It elucidates about BIM 4D planning and constructability reviews of a Sewage Treatment Plant in India. Conventional construction planning and logistics management involves a blend of experience coupled with imagination. Even though the excerpts or judgments or lessons learnt gained from veterans might be predictive and helpful, but the uncertainty factor persists. This paper shall delve about the case study of real time implementation of BIM 4D planning protocols for one of the Sewage Treatment Plant of Dravyavati River Rejuvenation Project in India and develops a Time Liner to identify logistics planning and clash detection. With this BIM processes, we shall find that there will be significant reduction of duplication of tasks and reworks. Also another benefit achieved will be better visualization and workarounds during conception stage and enables for early involvement of the stakeholders in the Project Life cycle of Sewage Treatment Plant construction. Moreover, we have also taken an opinion poll of the benefits accrued utilizing BIM processes versus traditional paper based communication like 2D and 3D CAD tools. Thus this paper concludes with BIM framework for Sewage Treatment Plant construction which will achieve optimal construction co-ordination advantages like 4D construction sequencing, interference checking, clash detection checking and resolutions by primary engagement of all key stakeholders thereby identifying potential risks and subsequent creation of risk response strategies. However, certain hiccups like hesitancy in adoption of BIM technology by naïve users and availability of proficient BIM trainers in India poses a phenomenal impediment. Hence the nurture of BIM processes from conception, construction and till commissioning, operation and maintenance along with deconstruction of a project’s life cycle is highly essential for Indian Construction Industry in this digital era.

Keywords: integrated BIM workflow, 4D planning with BIM, building information modeling, clash detection and visualization, constructability reviews, project life cycle

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Authors: Aniela Pop, Ianina Birsan, Corina Orha, Rodica Pode, Florica Manea

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Carbon nanofiber-epoxy composite electrode has been investigated through voltammetric and amperometric techniques in order to detect parabens from aqueous solutions. The occurrence into environment as emerging pollutants of these preservative compounds has been extensively studied in the last decades, and consequently, a rapid and reliable method for their quantitative quantification is required. In this study, methylparaben (MP) and propylparaben (PP) were chosen as representatives for paraben class. The individual electrochemical detection of each paraben has been successfully performed. Their electrochemical oxidation occurred at the same potential value. Their simultaneous quantification should be assessed electrochemically only as general index of paraben class as a cumulative signal corresponding to both MP and PP from solution. The influence of pH on the electrochemical signal was studied. pH ranged between 1.3 and 9.0 allowed shifting the detection potential value to smaller value, which is very desired for the electroanalysis. Also, the signal is better-defined and higher sensitivity is achieved. Differential-pulsed voltammetry and square-wave voltammetry were exploited under the optimum pH conditions to improve the electroanalytical performance for the paraben detection. Also, the operation conditions were selected, i.e., the step potential, modulation amplitude and the frequency. Chronomaprometry application as the easiest electrochemical detection method led to worse sensitivity, probably due to a possible fouling effect of the electrode surface. The best electroanalytical performance was achieved by pulsed voltammetric technique but the selection of the electrochemical technique is related to the concrete practical application. A good reproducibility of the voltammetric-based method using carbon nanofiber-epoxy composite electrode was determined and no interference effect was found for the cation and anion species that are common in the water matrix. Besides these characteristics, the long life-time of the electrode give to carbon nanofiber-epoxy composite electrode a great potential for practical applications.

Keywords: carbon nanofiber-epoxy composite electrode, electroanalysis, methylparaben, propylparaben

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Authors: Rabaa Tlili Yaakoubi, Hind Nakouri, Olivier Blanpain

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The current tools for real time management of sewer systems are based on two software tools: the software of weather forecast and the software of hydraulic simulation. The use of the first ones is an important cause of imprecision and uncertainty, the use of the second requires temporal important steps of decision because of their need in times of calculation. This way of proceeding fact that the obtained results are generally different from those waited. The major idea of the CARDIO project is to change the basic paradigm by approaching the problem by the "automatic" face rather than by that "hydrology". The objective is to make possible the realization of a large number of simulations at very short times (a few seconds) allowing to take place weather forecasts by using directly the real time meditative pluviometric data. The aim is to reach a system where the decision-making is realized from reliable data and where the correction of the error is permanent. A first model of control laws was realized and tested with different return-period rainfalls. The gains obtained in rejecting volume vary from 40 to 100%. The development of a new algorithm was then used to optimize calculation time and thus to overcome the subsequent combinatorial problem in our first approach. Finally, this new algorithm was tested with 16- year-rainfall series. The obtained gains are 60% of total volume rejected to the natural environment and of 80 % in the number of discharges.

Keywords: RTC, paradigm, optimization, automation

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Authors: K. Rumchev, S. Gilbey

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Airborne particulate matter is a known hazard to human health, with a considerable body of evidence linking agricultural dust exposures to adverse human health effects in exposed populations. It is also known that agricultural workers are exposed to high levels of soil dust and other types of airborne particulate matter within the farming environment. The aim of this study was to examine exposure to agricultural dust among farm workers during the seeding season. Twenty-one wheat-belt farms consented to participate in the study with 30 workers being monitored for dust exposure whilst seeding or undertaking seeding associated tasks. Each farm was visited once and farmers’ were asked to wear a personal air sampler for a 4-hour sampling period. Simultaneous, real-time, tractor cabin air quality monitoring was also undertaken. Data for this study was collected using real-time aerosol dust monitors to determine in-tractor cabin PM exposure to five size fractions (total, PM10, respirable, PM2.5 and PM1), and personal sampling was undertaken to establish individual exposure to inhalable and respirable dust concentrations. The study established a significant difference between personal exposures and simultaneous real-time in-cabin exposures for both inhalable and respirable fractions. No significant difference was shown between in-cabin and personal inhalable dust concentrations during seeding and spraying tasks, although both in-cabin and personal concentrations were two times greater for seeding than spraying. Future research should focus on educating and providing farm owners and workers with more information on adopting safe work practices to minimise harmful exposures to agricultural dust.

Keywords: agriculture, air quality, Australia, particulate matter

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Authors: Josef Novák, Alena Kohoutková, Vladimír Křístek, Jan Vodička

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Numerical analysis software belong to the main tools for simulating the real behavior of various concrete structures and elements. In comparison with experimental tests, they offer an affordable way to study the mechanical behavior of structures under various conditions. The contribution deals with a precast element of an innovative airfield pavement system which is being developed within an ongoing scientific project. The proposed system consists a two-layer surface course of precast concrete panels positioned on a two-layer base of fiber-reinforced concrete with recycled aggregate. As the panels are supposed to be installed directly on the hardened base course, imperfections at the interface between the base course and surface course are expected. Considering such circumstances, three various behavior patterns could be established and considered when designing the precast element. Enormous costs of full-scale experiments force to simulate the behavior of the element in a numerical analysis software using finite element method. The simulation was conducted on a nonlinear model in order to obtain such results which could fully compensate results from the experiments. First, several loading schemes were considered with the aim to observe the critical one which was used for the simulation later on. The main objective of the simulation was to optimize reinforcement of the element subject to quasi-static loading from airplanes. When running the simulation several parameters were considered. Namely, it concerns geometrical imperfections, manufacturing imperfections, stress state in reinforcement, stress state in concrete and crack width. The numerical simulation revealed that the precast element should be heavily reinforced to fulfill all the demands assumed. The main cause of using high amount of reinforcement is the size of the imperfections which could occur at real structure. Improving manufacturing quality, the installation of the precast panels on a fresh base course or using a bedding layer underneath the surface course belong to the main steps how to reduce the size of imperfections and consequently lower the consumption of reinforcement.

Keywords: nonlinear analysis, numerical simulation, precast concrete, pavement

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Authors: Khalak Bin Khair, Saqib Jahir, Mohammed Ibrahim, Fahad Bin, Debajyoti Karmaker

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Object detection is a computer technology that deals with searching through digital images and videos for occurrences of semantic elements of a particular class. It is associated with image processing and computer vision. On top of object detection, we detect camouflage objects within an image using Deep Learning techniques. Deep learning may be a subset of machine learning that's essentially a three-layer neural network Over 6500 images that possess camouflage properties are gathered from various internet sources and divided into 4 categories to compare the result. Those images are labeled and then trained and tested using vgg16 architecture on the jupyter notebook using the TensorFlow platform. The architecture is further customized using Transfer Learning. Methods for transferring information from one or more of these source tasks to increase learning in a related target task are created through transfer learning. The purpose of this transfer of learning methodologies is to aid in the evolution of machine learning to the point where it is as efficient as human learning.

Keywords: deep learning, transfer learning, TensorFlow, camouflage, object detection, architecture, accuracy, model, VGG16

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Authors: Jarek Krajewski, Andre Wittenborn, Martin Sauerland

Abstract:

This abstract describes a promising approach for estimating post-traumatic stress disorder (PTSD) based on prosodic speech characteristics. It illustrates the validity of this method by briefly discussing results from an Arabic refugee sample (N= 47, 32 m, 15 f). A well-established standardized self-report scale “Reaction of Adolescents to Traumatic Stress” (RATS) was used to determine the ground truth level of PTSD. The speech material was prompted by telling about autobiographical related sadness inducing experiences (sampling rate 16 kHz, 8 bit resolution). In order to investigate PTSD-induced speech changes, a self-developed set of 136 prosodic speech features was extracted from the .wav files. This set was adapted to capture traumatization related speech phenomena. An artificial neural network (ANN) machine learning model was applied to determine the PTSD level and reached a correlation of r = .37. These results indicate that our classifiers can achieve similar results to those seen in speech-based stress research.

Keywords: speech prosody, PTSD, machine learning, feature extraction

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Authors: Andres F. Ramirez, Carlos F. Valencia

Abstract:

The increasing interest in renewable energies strategies application and the path for diminishing the use of carbon related energy sources have encouraged the development of novel strategies for integration of solar energy into the electricity network. A correct inclusion of the fluctuating energy output of a photovoltaic (PV) energy system into an electric grid requires improvements in the forecasting and simulation methodologies for solar energy potential, and the understanding not only of the mean value of the series but the associated underlying stochastic process. We present a methodology for synthetic generation of solar irradiance (shortwave flux) and air temperature bivariate time series based on copula functions to represent the cross-dependence and temporal structure of the data. We explore the advantages of using this nonlinear time series method over traditional approaches that use a transformation of the data to normal distributions as an intermediate step. The use of copulas gives flexibility to represent the serial variability of the real data on the simulation and allows having more control on the desired properties of the data. We use discrete zero mass density distributions to assess the nature of solar irradiance, alongside vector generalized linear models for the bivariate time series time dependent distributions. We found that the copula autoregressive methodology used, including the zero mass characteristics of the solar irradiance time series, generates a significant improvement over state of the art strategies. These results will help to better understand the fluctuating nature of solar energy forecasting, the underlying stochastic process, and quantify the potential of a photovoltaic (PV) energy generating system integration into a country electricity network. Experimental analysis and real data application substantiate the usage and convenience of the proposed methodology to forecast solar irradiance time series and solar energy across northern hemisphere, southern hemisphere, and equatorial zones.

Keywords: copula autoregressive, solar irradiance forecasting, solar energy forecasting, time series generation

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Authors: Mubarak Saadu Nabunkari, Abdullahi Abdu Ibrahim, Muhammad Ilyas

Abstract:

This study looks at how Internet of Things (IoT) devices are used in healthcare to monitor and treat patients better. However, using these devices in healthcare comes with security problems. The research explores using Security Information and Event Management (SIEM) systems with healthcare IoT devices to solve these security challenges. Reviewing existing literature shows the current state of IoT security and emphasizes the need for better protection. The main worry is that healthcare IoT devices can be easily hacked, putting patient data and device functionality at risk. To address this, the research suggests a detailed security framework designed for these devices. This framework, based on literature and best practices, includes important security measures like authentication, data encryption, access controls, and anomaly detection. Adding SIEM systems to this framework helps detect threats in real time and respond quickly to incidents, making healthcare IoT devices more secure. The study highlights the importance of this integration and offers guidance for implementing healthcare IoT securely, efficiently, and effectively.

Keywords: cyber security, threat intelligence, forensics, heath care

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Authors: Jose A. Diaz-Olivares, Nafise Mahdavian, Farhad Abtahi, Kaj Lindecrantz, Abdelakram Hafid, Fernando Seoane

Abstract:

Despite new recommendations and guidelines for the evaluation of occupational risk assessments and their prevention, work-related musculoskeletal disorders are still one of the biggest causes of work activity disruption, productivity loss, sick leave and chronic work disability. It affects millions of workers throughout Europe, with a large-scale economic and social burden. These specific efforts have failed to produce significant results yet, probably due to the limited availability and high costs of occupational risk assessment at work, especially when the methods are complex, consume excessive resources or depend on self-evaluations and observations of poor accuracy. To overcome these limitations, a pervasive system of risk assessment tools in real time has been developed, which has the characteristics of a systematic approach, with good precision, usability and resource efficiency, essential to facilitate the prevention of musculoskeletal disorders in the long term. The system allows the combination of different wearable sensors, placed on different limbs, to be used for data collection and evaluation by a software solution, according to the needs and requirements in each individual working environment. This is done in a non-disruptive manner for both the occupational health expert and the workers. The creation of this solution allows us to attend different research activities that require, as an essential starting point, the recording of data with ergonomic value of very diverse origin, especially in real work environments. The software platform is here presented with a complimentary smart clothing system for data acquisition, comprised of a T-shirt containing inertial measurement units (IMU), a vest sensorized with textile electronics, a wireless electrocardiogram (ECG) and thoracic electrical bio-impedance (TEB) recorder and a glove sensorized with variable resistors, dependent on the angular position of the wrist. The collected data is processed in real-time through a mobile application software solution, implemented in commercially available Android-based smartphones and tablet platforms. Based on the collection of this information and its analysis, real-time risk assessment and feedback about postural improvement is possible, adapted to different contexts. The result is a tool which provides added value to ergonomists and occupational health agents, as in situ analysis of postural behavior can assist in a quantitative manner in the evaluation of work techniques and the occupational environment.

Keywords: ergonomics, mobile technologies, risk assessment, smart textiles

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Authors: Jeong-Min Lee, Hyunwoo Song, Yonseok Kim, Junghan Yun, Jungin Byun, Jae-Mean Koo, Chang-Sung Seok

Abstract:

The Thermal Barrier Coating (TBC) prevents heat directly transferring from the high-temperature flame to the substrate. Top coat and bond coat compose the TBC and top coat consists of a ceramic and bond coat increases adhesion between the top coat and the substrate. The TBC technology drops the substrate surface temperature by about 150~200°C. In addition, the TBC system has a cooling system to lower the blade temperature by the air flow inside the blade. Then, as a result, the thermal gradient occurs inside the blade by cooling. Also, the internal stress occurs due to the difference in thermal expansion. In this paper, the finite element analyses (FEA) were performed and stress changes were derived according to the thermal gradient of the TBC system. The stress was increased due to the cooling, but difference of the stress between the top coat and bond coat was decreased. So, delamination in the interface between top coat and bond coat.

Keywords: gas turbine blade, Thermal Barrier Coating (TBC), thermal gradient, Finite Element Analysis (FEA)

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Authors: Gaokai Liu

Abstract:

The distribution of material grain sizes reflects the strength, fracture, corrosion and other properties, and the grain size can be acquired via the grain boundary. In recent years, the automatic grain boundary detection is widely required instead of complex experimental operations. In this paper, an effective solution is applied to acquire the grain boundary of material images. First, the initial superpixel segmentation result is obtained via a superpixel approach. Then, a region merging method is employed to merge adjacent regions based on certain similarity criterions, the experimental results show that the merging strategy improves the superpixel segmentation result on material datasets.

Keywords: grain boundary detection, image segmentation, material images, region merging

Procedia PDF Downloads 170

Authors: Meera Shanker

Abstract:

Excellent education and financial need have encouraged Indian women to go out and work in well-paid and high-status occupations. In the era of cutthroat competition, women are expected to work hard to produce the desired result; hence, workload and expectations haveincreased. At home, they are anticipated to take care of family members, children, and household work. Women are stretching themselves mechanically to remain in the job competition and try to give their best at home. Consequentially, they are under tremendous pressure, stressed, and having issues related to physical-mental wellness. Mental healthcare is often ignored and not accepted due to a lack of awareness and cultural barriers. These further compounds the problem, resulting in decreased productivity in economic terms and an increase in stress-related physical-mental ailments. The main objective of the study was to find out the impact of stress on the physical-mental wellbeing of working women in India, along with their awareness and acceptability related to mental health. Six hundred and one woman working at various levels took part in this study, responding to the items related to stress and physical-mental illness. Finally, 21 items were retained under four meaningful factors measuring stress dimensions along with 17 items with three factors measuring physical-mental wellbeing. Confirmatory Factor Analysis (CFA), path analysis, in Structural Equation Modeling (SEM), was used to get a relationship, validity of the instruments. The psychometric properties of items and Cronbach’s Alpha reliabilities calculated for the subscales were relatively acceptable. The subscale correlations, regression, and path analysis of stress dimensions with physical-mental illness were found to be positive, indicating the growing stress among working women in India, which is impacting their physical-mental health. Single item analysis revealed that 77 percent of women have never visited psychologists. However, 70 percent of working women were not ready to seek the help of a psychologist.

Keywords: working women, stress, physical-mental well-being, confirmatory factor analysis

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Authors: Tanvir Hasan, Minhaz Uddin, Anwar Sadat Anik

Abstract:

A pressurizer is a safety-related reactor component that maintains the reactor operating pressure to guarantee safety. Its structure is usually made of high thermal and pressure resistive material. The mechanical structure of these components should be maintained in all working settings, including transient to severe accidents conditions. The goal of this study is to examine the structural integrity and stress of the pressurizer in order to ensure its design integrity towards transient situations. For this, the finite element method (FEM) was used to analyze the mechanical stress on pressurizer components in this research. ANSYS MECHANICAL tool was used to analyze a 3D model of the pressurizer. The material for the body and safety relief nozzle is selected as low alloy steel i.e., SA-508 Gr.3 Cl.2. The model was put into ANSYS WORKBENCH and run under the boundary conditions of (internal Pressure, -17.2 MPa, inside radius, -1348mm, the thickness of the shell, -127mm, and the ratio of the outside radius to an inside radius, - 1.059). The theoretical calculation was done using the formulas and then the results were compared with the simulated results. When stimulated at design conditions, the findings revealed that the pressurizer stress analysis completely fulfilled the ASME standards.

Keywords: pressurizer, stress analysis, finite element method, nuclear reactor

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Authors: Alaka Padhye, S. P. Kane

Abstract:

The following study considers some variations made to the secretary problem (SP). In a multiple criteria secretary problem (MCSP), the selection of a unit is based on two independent characteristics. The units that appear before an observer are known say N, the best rank of a unit being N. A unit is selected, if it is better with respect to either first or second or both the characteristics. When the number of units is large and due to constraints like time and cost, the observer might want to stop earlier instead of inspecting all the available units. Let the process terminate at r2th unit where r1Keywords: joint distribution, marginal distribution, real ranks, secretary problem, selection criterion, two tailed secretary problem

Procedia PDF Downloads 271