Search results for: plant detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6754

Search results for: plant detection

2824 Fault Diagnosis and Fault-Tolerant Control of Bilinear-Systems: Application to Heating, Ventilation, and Air Conditioning Systems in Multi-Zone Buildings

Authors: Abderrhamane Jarou, Dominique Sauter, Christophe Aubrun

Abstract:

Over the past decade, the growing demand for energy efficiency in buildings has attracted the attention of the control community. Failures in HVAC (heating, ventilation and air conditioning) systems in buildings can have a significant impact on the desired and expected energy performance of buildings and on the user's comfort as well. FTC is a recent technology area that studies the adaptation of control algorithms to faulty operating conditions of a system. The application of Fault-Tolerant Control (FTC) in HVAC systems has gained attention in the last two decades. The objective is to maintain the variations in system performance due to faults within an acceptable range with respect to the desired nominal behavior. This paper considers the so-called active approach, which is based on fault and identification scheme combined with a control reconfiguration algorithm that consists in determining a new set of control parameters so that the reconfigured performance is "as close as possible, "in some sense, to the nominal performance. Thermal models of buildings and their HVAC systems are described by non-linear (usually bi-linear) equations. Most of the works carried out so far in FDI (fault diagnosis and isolation) or FTC consider a linearized model of the studied system. However, this model is only valid in a reduced range of variation. This study presents a new fault diagnosis (FD) algorithm based on a bilinear observer for the detection and accurate estimation of the magnitude of the HVAC system failure. The main contribution of the proposed FD algorithm is that instead of using specific linearized models, the algorithm inherits the structure of the actual bilinear model of the building thermal dynamics. As an immediate consequence, the algorithm is applicable to a wide range of unpredictable operating conditions, i.e., weather dynamics, outdoor air temperature, zone occupancy profile. A bilinear fault detection observer is proposed for a bilinear system with unknown inputs. The residual vector in the observer design is decoupled from the unknown inputs and, under certain conditions, is made sensitive to all faults. Sufficient conditions are given for the existence of the observer and results are given for the explicit computation of observer design matrices. Dedicated observer schemes (DOS) are considered for sensor FDI while unknown input bilinear observers are considered for actuator or system components FDI. The proposed strategy for FTC works as follows: At a first level, FDI algorithms are implemented, making it also possible to estimate the magnitude of the fault. Once the fault is detected, the fault estimation is then used to feed the second level and reconfigure the control low so that that expected performances are recovered. This paper is organized as follows. A general structure for fault-tolerant control of buildings is first presented and the building model under consideration is introduced. Then, the observer-based design for Fault Diagnosis of bilinear systems is studied. The FTC approach is developed in Section IV. Finally, a simulation example is given in Section V to illustrate the proposed method.

Keywords: bilinear systems, fault diagnosis, fault-tolerant control, multi-zones building

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2823 Dynamical Models for Enviromental Effect Depuration for Structural Health Monitoring of Bridges

Authors: Francesco Morgan Bono, Simone Cinquemani

Abstract:

This research aims to enhance bridge monitoring by employing innovative techniques that incorporate exogenous factors into the modeling of sensor signals, thereby improving long-term predictability beyond traditional static methods. Using real datasets from two different bridges equipped with Linear Variable Displacement Transducer (LVDT) sensors, the study investigates the fundamental principles governing sensor behavior for more precise long-term forecasts. Additionally, the research evaluates performance on noisy and synthetically damaged data, proposing a residual-based alarm system to detect anomalies in the bridge. In summary, this novel approach combines advanced modeling, exogenous factors, and anomaly detection to extend prediction horizons and improve preemptive damage recognition, significantly advancing structural health monitoring practices.

Keywords: structural health monitoring, dynamic models, sindy, railway bridges

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2822 Small Target Recognition Based on Trajectory Information

Authors: Saad Alkentar, Abdulkareem Assalem

Abstract:

Recognizing small targets has always posed a significant challenge in image analysis. Over long distances, the image signal-to-noise ratio tends to be low, limiting the amount of useful information available to detection systems. Consequently, visual target recognition becomes an intricate task to tackle. In this study, we introduce a Track Before Detect (TBD) approach that leverages target trajectory information (coordinates) to effectively distinguish between noise and potential targets. By reframing the problem as a multivariate time series classification, we have achieved remarkable results. Specifically, our TBD method achieves an impressive 97% accuracy in separating target signals from noise within a mere half-second time span (consisting of 10 data points). Furthermore, when classifying the identified targets into our predefined categories—airplane, drone, and bird—we achieve an outstanding classification accuracy of 96% over a more extended period of 1.5 seconds (comprising 30 data points).

Keywords: small targets, drones, trajectory information, TBD, multivariate time series

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2821 Assessment of Hargreaves Equation for Estimating Monthly Reference Evapotranspiration in the South of Iran

Authors: Ali Dehgan Moroozeh, B. Farhadi Bansouleh

Abstract:

Evapotranspiration is one of the most important components of the hydrological cycle. Evapotranspiration (ETo) is an important variable in water and energy balances on the earth’s surface, and knowledge of the distribution of ET is a key factor in hydrology, climatology, agronomy and ecology studies. Many researchers have a valid relationship, which is a function of climate factors, to estimate the potential evapotranspiration presented to the plant water stress or water loss, prevent. The FAO-Penman method (PM) had been recommended as a standard method. This method requires many data and these data are not available in every area of world. So, other methods should be evaluated for these conditions. When sufficient or reliable data to solve the PM equation are not available then Hargreaves equation can be used. The Hargreaves equation (HG) requires only daily mean, maximum and minimum air temperature extraterrestrial radiation .In this study, Hargreaves method (HG) were evaluated in 12 stations in the North West region of Iran. Results of HG and M.HG methods were compared with results of PM method. Statistical analysis of this comparison showed that calibration process has had significant effect on efficiency of Hargreaves method.

Keywords: evapotranspiration, hargreaves, equation, FAO-Penman method

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2820 Advanced Real-Time Fluorescence Imaging System for Rat's Femoral Vein Thrombosis Monitoring

Authors: Sang Hun Park, Chul Gyu Song

Abstract:

Artery and vein occlusion changes observed in patients and experimental animals are unexplainable symptoms. As the fat accumulated in cardiovascular ruptures, it causes vascular blocking. Likewise, early detection of cardiovascular disease can be useful for treatment. In this study, we used the mouse femoral occlusion model to observe the arterial and venous occlusion changes without darkroom. We observed the femoral arterial flow pattern changes by proposed fluorescent imaging system using an animal model of thrombosis. We adjusted the near-infrared light source current in order to control the intensity of the fluorescent substance light. We got the clear fluorescent images and femoral artery flow pattern were measured by a 5-minute interval. The result showed that the fluorescent substance flowing in the femoral arteries were accumulated in thrombus as time passed, and the fluorescence of other vessels gradually decreased.

Keywords: thrombus, fluorescence, femoral, arteries

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2819 Antimicrobial Potential of Calendula officinalis Extracts on Flavobacterium columnare of Clarias gariepinus Fingerlings

Authors: Nelson Rotimi Osungbemiro, Sanni Rafiu Olugbenga, Abayomi Olufemi Olajuyigbe

Abstract:

Ninety Fingerlings of Clarias gariepinus were exposed to the pathogenic Flavobacterium columnare a Gram Negative bacteria responsible for high mortality in fish pond raised young fish (fries and fingerlings) of Clarias sp. in Southwestern Nigeria. After feeding with 40% crude protein pelletized fish feed for 5 days, the fishes were divided into two groups, one group was treated with extracts from Calendula officinalis flowers, while the second group was not treated (control). The results indicated that, at day 5, colony formation had been manifesting and at day 7, skin lesion occurred and at the 8th day, first mortality of fish occurred, and this continued steadily on the 9th-12th day when all the fishes were dead. Whereas, in the group that was treated with Calendula sp., no single mortality was recorded. This research shows that plant extract from Calendula flowers is an effective antimicrobial agent against the virulent pathogenic Flavobacterium columnare disease.

Keywords: antimicrobial, Flavobacterium columnare, Clarias gariepinus, fish

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2818 Experimental Set-Up for Investigation of Fault Diagnosis of a Centrifugal Pump

Authors: Maamar Ali Saud Al Tobi, Geraint Bevan, K. P. Ramachandran, Peter Wallace, David Harrison

Abstract:

Centrifugal pumps are complex machines which can experience different types of fault. Condition monitoring can be used in centrifugal pump fault detection through vibration analysis for mechanical and hydraulic forces. Vibration analysis methods have the potential to be combined with artificial intelligence systems where an automatic diagnostic method can be approached. An automatic fault diagnosis approach could be a good option to minimize human error and to provide a precise machine fault classification. This work aims to introduce an approach to centrifugal pump fault diagnosis based on artificial intelligence and genetic algorithm systems. An overview of the future works, research methodology and proposed experimental setup is presented and discussed. The expected results and outcomes based on the experimental work are illustrated.

Keywords: centrifugal pump setup, vibration analysis, artificial intelligence, genetic algorithm

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2817 Research of Acoustic Propagation within Marine Riser in Deepwater Drilling

Authors: Xiaohui Wang, Zhichuan Guan, Roman Shor, Chuanbin Xu

Abstract:

Early monitoring and real-time quantitative description of gas intrusion under the premise of ensuring the integrity of the drilling fluid circulation system will greatly improve the accuracy and effectiveness of deepwater gas-kick monitoring. Therefore, in order to study the propagation characteristics of ultrasonic waves in the gas-liquid two-phase flow within the marine riser, in this paper, a numerical simulation method of ultrasonic propagation in the annulus of the riser was established, and the credibility of the numerical analysis was verified by the experimental results of the established gas intrusion monitoring simulation experimental device. The numerical simulation can solve the sound field in the gas-liquid two-phase flow according to different physical models, and it is easier to realize the single factor control. The influence of each parameter on the received signal can be quantitatively investigated, and the law with practical guiding significance can be obtained.

Keywords: gas-kick detection, ultrasonic, void fraction, coda wave velocity

Procedia PDF Downloads 150
2816 Absorption Capability Examination of Heavy Metals by Spirogyra Alga in Ahvaz Water Treatment Plant

Authors: F. Fakheri Raof, F. Zobeidizadeh

Abstract:

The present study examined the potential capability of Spirogyra algae remove heavy metals Zn, Pb, Cu, and Cr from the water. For this purpose, the water treatment No. 3 of Ahvaz County in Khuzestan Province of Iran was selected as a case study. From 8 sampling stations, 4 stations were dedicated to the water samples and 4 stations to the algae samples. According to the obtained results, the concentration of the heavy metals Cr, Cu, Pb, and Zn in water samples were within the ranges of 1.98-19.53, 0.67-13.45, 1-23.18, and 2.12-83.04 µg/L. Besides, the concentration of heavy metal Cr, Pb, Cu, and Zn in spirogyra algae samples varied between the ranges 2.30-3.61, 2.06-3.43, 2.29-2.56, and 9.88-10.84 µg/L. The highest amount of metal absorption in spirogyra algae samples was related to the zinc. The obtained results also indicated that the last spirogyra algae sample which was at the inlet of Tank 4 absorbed the lowest concentration of metals. This would be due to the treatment process along the course of ponds resulted in completely pure water at the outlet without the existence of algae on the sides. The paper also provides some useful recommendations on this issue.

Keywords: absorption, Ahvaz, heavy metal, spirogyra algae, water treatment plants

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2815 Applications of AI, Machine Learning, and Deep Learning in Cyber Security

Authors: Hailyie Tekleselase

Abstract:

Deep learning is increasingly used as a building block of security systems. However, neural networks are hard to interpret and typically solid to the practitioner. This paper presents a detail survey of computing methods in cyber security, and analyzes the prospects of enhancing the cyber security capabilities by suggests that of accelerating the intelligence of the security systems. There are many AI-based applications used in industrial scenarios such as Internet of Things (IoT), smart grids, and edge computing. Machine learning technologies require a training process which introduces the protection problems in the training data and algorithms. We present machine learning techniques currently applied to the detection of intrusion, malware, and spam. Our conclusions are based on an extensive review of the literature as well as on experiments performed on real enterprise systems and network traffic. We conclude that problems can be solved successfully only when methods of artificial intelligence are being used besides human experts or operators.

Keywords: artificial intelligence, machine learning, deep learning, cyber security, big data

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2814 Digitalization in Aggregate Quarries

Authors: José Eugenio Ortiz, Pierre Plaza, Josefa Herrero, Iván Cabria, José Luis Blanco, Javier Gavilanes, José Ignacio Escavy, Ignacio López-Cilla, Virginia Yagüe, César Pérez, Silvia Rodríguez, Jorge Rico, Cecilia Serrano, Jesús Bernat

Abstract:

The development of Artificial Intelligence services in mining processes, specifically in aggregate quarries, is facilitating automation and improving numerous aspects of operations. Ultimately, AI is transforming the mining industry by improving efficiency, safety and sustainability. With the ability to analyze large amounts of data and make autonomous decisions, AI offers great opportunities to optimize mining operations and maximize the economic and social benefits of this vital industry. Within the framework of the European DIGIECOQUARRY project, various services were developed for the identification of material quality, production estimation, detection of anomalies and prediction of consumption and production automatically with good results.

Keywords: aggregates, artificial intelligence, automatization, mining operations

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2813 Specialized Phytochemical Properties of Stachys inflata Eco-Types in Different Ecological Circumstances of Southern Iran

Authors: Ghasem Khodahami, Vahid Rowshan, Mojtaba Pakparvar

Abstract:

Stachys forms one of the largest genera in the flowering plant family Lamiaceae. The number of species in the genus is estimated from about 300 to about 450 and comprises some 34 species in Iran. This genus is one of the richest sources of diterpenes which are particularly interesting because of their ecological role as antifeedants against different species of insects and for their role as the medicinal properties of the plants. The ecological distribution of Stachys inflata was studied and the resulted eco-types were sampled from four regions ranging 230-340 mm of rainfall and 1690-2125 m a.s.l of height In Fars Province Southern Iran. The essential oils of air-dried samples were obtained by hydrodistillation and analyzed by gas chromatography and gas chromatography/mass spectrometry. The number of secondary metabolites varied from 25 to 50 depending to ecological conditions. The main compounds in these areas were: Germacrene D, Bicyclogermacrene, spathulenol, δ-cadinene. Statistical analysis of photochemical resulted in recognizing 3 distinct groups that show internal variety in these herbs.

Keywords: eco-type, phytochemistry, secondary metabolites, Stachys inflata

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2812 Characterization of Aluminium Alloy 6063 Hybrid Metal Matrix Composite by Using Stir Casting Method

Authors: Balwinder Singh

Abstract:

The present research is a paper on the characterization of aluminum alloy-6063 hybrid metal matrix composites using three different reinforcement materials (SiC, red mud, and fly ash) through stir casting method. The red mud was used in solid form, and particle size range varies between 103-150 µm. During this investigation, fly ash is received from Guru Nanak Dev Thermal Plant (GNDTP), Bathinda. The study has been done by using Taguchi’s L9 orthogonal array by taking fraction wt.% (SiC 5%, 7.5%, and 10% and Red Mud and Fly Ash 2%, 4%, and 6%) as input parameters with their respective levels. The study of the mechanical properties (tensile strength, impact strength, and microhardness) has been done by using Analysis of Variance (ANOVA) with the help of MINITAB 17 software. It is revealed that silicon carbide is the most significant parameter followed by red mud and fly ash affecting the mechanical properties, respectively. The fractured surface morphology of the composites using Field Emission Scanning Electron Microscope (FESEM) shows that there is a good mixing of reinforcement particles in the matrix. Energy-dispersive X-ray spectroscopy (EDS) was performed to know the presence of the phases of the reinforced material.

Keywords: reinforcement, silicon carbide, fly ash, red mud

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2811 Revolution Biopolibag System Based on Water Hyacinth's Fiber as a Solution for Environmental Friendly Seeding and Seedling

Authors: Supriady R. P. Siregar, Rizki Barkah Aulia, Dhiya Fadilla Dewi

Abstract:

Polybag is a plastic that is used to seed plants. The common type that used for polybag is a synthetic that made from petroleum such as polyethylene. Beside the character of the raw material that are non-renewable and limited, synthetic polybag ability to disintegrate in the environment is very low. According to that situation, we need a solution to overcome these problems by creating an environmentally friendly polybag. In this research, using the water hyacinth plant fibers (Eichornia crassipes) as a major component in manufacturing the environmentally friendly polybag, the water hyacinth (Eichornia crassipes) contains approximately 60% cellulose. The research method used is an experiment by testing the mechanical characters and biodegradability bio-polybag water hyacinth fibers (Eichornia crassipes) on three medium that is dissolved in water, river water and buried in soil. The research shows bio-polybag of hyacinth fibers can rapidly degraded. This study is expected to be the beginning of the creation bio-polybag of water hyacinth fiber (Eichornia crassipes) and can be applied in agriculture.

Keywords: revolution, biopolybag, renewable, environment

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2810 Assessment of Cellular Metabolites and Impedance for Early Diagnosis of Oral Cancer among Habitual Smokers

Authors: Ripon Sarkar, Kabita Chaterjee, Ananya Barui

Abstract:

Smoking is one of the leading causes of oral cancer. Cigarette smoke affects various cellular parameters and alters molecular metabolism of cells. Epithelial cells losses their cytoskeleton structure, membrane integrity, cellular polarity that subsequently initiates the process of epithelial cells to mesenchymal transition due to long exposure of cigarette smoking. It changes the normal cellular metabolic activity which induces oxidative stress and enhances the reactive oxygen spices (ROS) formation. Excessive ROS and associated oxidative stress are considered to be a driving force in alteration in cellular phenotypes, polarity distribution and mitochondrial metabolism. Noninvasive assessment of such parameters plays essential role in development of routine screening system for early diagnosis of oral cancer. Electrical cell-substrate impedance sensing (ECIS) is one of such method applied for detection of cellular membrane impedance which can be correlated to cell membrane integrity. Present study intends to explore the alteration in cellular impedance along with the expression of cellular polarity molecules and cytoskeleton distributions in oral epithelial cells of habitual smokers and to correlate the outcome to that of clinically diagnosed oral leukoplakia and oral squamous cell carcinoma patients. Total 80 subjects were categorized into four study groups: nonsmoker (NS), cigarette smoker (CS), oral leukoplakia (OLPK) and oral squamous cell carcinoma (OSCC). Cytoskeleton distribution was analyzed by staining of actin filament and generation of ROS was measured using assay kit using standard protocol. Cell impedance was measured through ECIS method at different frequencies. Expression of E-cadherin and protease-activated receptor (PAR) proteins were observed through immune-fluorescence method. Distribution of actin filament is well organized in NS group however; distribution pattern was grossly varied in CS, OLPK and OSCC. Generation of ROS was low in NS which subsequently increased towards OSCC. Expressions of E-cadherin and change in cellular electrical impedance in different study groups indicated the hallmark of cancer progression from NS to OSCC. Expressions of E-cadherin, PAR protein, and cell impedance were decreased from NS to CS and farther OSCC. Generally, the oral epithelial cells exhibit apico-basal polarity however with cancer progression these cells lose their characteristic polarity distribution. In this study expression of polarity molecule and ECIS observation indicates such altered pattern of polarity among smoker group. Overall the present study monitored the alterations in intracellular ROS generation and cell metabolic function, membrane integrity in oral epithelial cells in cigarette smokers. Present study thus has clinical significance, and it may help in developing a noninvasive technique for early diagnosis of oral cancer amongst susceptible individuals.

Keywords: cigarette smoking, early oral cancer detection, electric cell-substrate impedance sensing, noninvasive screening

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2809 A Comparative Analysis of Hyper-Parameters Using Neural Networks for E-Mail Spam Detection

Authors: Syed Mahbubuz Zaman, A. B. M. Abrar Haque, Mehedi Hassan Nayeem, Misbah Uddin Sagor

Abstract:

Everyday e-mails are being used by millions of people as an effective form of communication over the Internet. Although e-mails allow high-speed communication, there is a constant threat known as spam. Spam e-mail is often called junk e-mails which are unsolicited and sent in bulk. These unsolicited emails cause security concerns among internet users because they are being exposed to inappropriate content. There is no guaranteed way to stop spammers who use static filters as they are bypassed very easily. In this paper, a smart system is proposed that will be using neural networks to approach spam in a different way, and meanwhile, this will also detect the most relevant features that will help to design the spam filter. Also, a comparison of different parameters for different neural network models has been shown to determine which model works best within suitable parameters.

Keywords: long short-term memory, bidirectional long short-term memory, gated recurrent unit, natural language processing, natural language processing

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2808 A Radiofrequency Spectrophotometer Device to Detect Liquids in Gastroesophageal Ways

Authors: R. Gadea, J. M. Monzó, F. J. Puertas, M. Castro, A. Tebar, P. J. Fito, R. J. Colom

Abstract:

There exists a wide array of ailments impacting the structural soundness of the esophageal walls, predominantly linked to digestive issues. Presently, the techniques employed for identifying esophageal tract complications are excessively invasive and discomforting, subjecting patients to prolonged discomfort in order to achieve an accurate diagnosis. This study proposes the creation of a sensor with profound measuring capabilities designed to detect fluids coursing through the esophageal tract. The multi-sensor detection system relies on radiofrequency photospectrometry. During experimentation, individuals representing diverse demographics in terms of gender and age were utilized, positioning the sensors amidst the trachea and diaphragm and assessing measurements in vacuum conditions, water, orange juice, and saline solutions. The findings garnered enabled the identification of various liquid mediums within the esophagus, segregating them based on their ionic composition.

Keywords: radiofrequency spectrophotometry, medical device, gastroesophageal disease, photonics

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2807 Real-Time Compressive Strength Monitoring for NPP Concrete Construction Using an Embedded Piezoelectric Self-Sensing Technique

Authors: Junkyeong Kim, Seunghee Park, Ju-Won Kim, Myung-Sug Cho

Abstract:

Recently, demands for the construction of Nuclear Power Plants (NPP) using high strength concrete (HSC) has been increased. However, HSC might be susceptible to brittle fracture if the curing process is inadequate. To prevent unexpected collapse during and after the construction of HSC structures, it is essential to confirm the strength development of HSC during the curing process. However, several traditional strength-measuring methods are not effective and practical. In this study, a novel method to estimate the strength development of HSC based on electromechanical impedance (EMI) measurements using an embedded piezoelectric sensor is proposed. The EMI of NPP concrete specimen was tracked to monitor the strength development. In addition, cross-correlation coefficient was applied in sequence to examine the trend of the impedance variations more quantitatively. The results confirmed that the proposed technique can be applied successfully monitoring of the strength development during the curing process of HSC structures.

Keywords: concrete curing, embedded piezoelectric sensor, high strength concrete, nuclear power plant, self-sensing impedance

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2806 An Industrial Scada System Remote Control Using Mobile Phones

Authors: Ahmidah Elgali

Abstract:

SCADA is the abbreviation for "Administrative Control And Data Acquisition." SCADA frameworks are generally utilized in industry for administrative control and information securing of modern cycles. Regular SCADA frameworks use PC, journal, slim client, and PDA as a client. In this paper, a Java-empowered cell phone has been utilized as a client in an example SCADA application to show and regulate the place of an example model crane. The paper presents a genuine execution of the online controlling of the model crane through a cell phone. The remote correspondence between the cell phone and the SCADA server is performed through a base station by means of general parcel radio assistance GPRS and remote application convention WAP. This application can be used in industrial sites in areas that are likely to be exposed to a security emergency (like terrorist attacks) which causes the sudden exit of the operators; however, no time to perform the shutdown procedures for the plant. Hence this application allows shutting down units and equipment remotely by mobile and so avoids damage and losses.

Keywords: control, industrial, mobile, network, remote, SCADA

Procedia PDF Downloads 69
2805 Improved Pitch Detection Using Fourier Approximation Method

Authors: Balachandra Kumaraswamy, P. G. Poonacha

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Automatic Music Information Retrieval has been one of the challenging topics of research for a few decades now with several interesting approaches reported in the literature. In this paper we have developed a pitch extraction method based on a finite Fourier series approximation to the given window of samples. We then estimate pitch as the fundamental period of the finite Fourier series approximation to the given window of samples. This method uses analysis of the strength of harmonics present in the signal to reduce octave as well as harmonic errors. The performance of our method is compared with three best known methods for pitch extraction, namely, Yin, Windowed Special Normalization of the Auto-Correlation Function and Harmonic Product Spectrum methods of pitch extraction. Our study with artificially created signals as well as music files show that Fourier Approximation method gives much better estimate of pitch with less octave and harmonic errors.

Keywords: pitch, fourier series, yin, normalization of the auto- correlation function, harmonic product, mean square error

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2804 Energy Analysis of an Ejector Based Solar Assisted Trigeneration System for Dairy Application

Authors: V. Ravindra, P. A. Saikiran, M. Ramgopal

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This paper presents an energy analysis of a solar assisted trigeneration system using an Ejector for dairy applications. The working fluid in the trigeneration loop is Supercritical CO₂. The trigeneration system is a combination of Brayton cycle and ejector based vapor compression refrigeration cycle. The heating and cooling outputs are used for simultaneous pasteurization and chilling of the milk. The electrical power is used to drive the auxiliary equipment in the dairy plant. A numerical simulation is done with Engineering Equation Solver (EES), and a parametric analysis is performed by varying the operating variables over a meaningful range. The results show that the overall performance index decreases with increase in ambient temperature. For an ejector based system, the compressor work and cooling output are significant output quantities. An increase in total mass flow rate of the refrigerant (primary + secondary) results in an increase in the compressor work and cooling output.

Keywords: trigeneration, solar thermal, supercritical CO₂, ejector

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2803 Multi-Sensor Target Tracking Using Ensemble Learning

Authors: Bhekisipho Twala, Mantepu Masetshaba, Ramapulana Nkoana

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Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfill requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates.

Keywords: single classifier, ensemble learning, multi-target tracking, multiple classifiers

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2802 Automatic Diagnosis of Electrical Equipment Using Infrared Thermography

Authors: Y. Laib Dit Leksir, S. Bouhouche

Abstract:

Analysis and processing of data bases resulting from infrared thermal measurements made on the electrical installation requires the development of new tools in order to obtain correct and additional information to the visual inspections. Consequently, the methods based on the capture of infrared digital images show a great potential and are employed increasingly in various fields. Although, there is an enormous need for the development of effective techniques to analyse these data base in order to extract relevant information relating to the state of the equipments. Our goal consists in introducing recent techniques of modeling based on new methods, image and signal processing to develop mathematical models in this field. The aim of this work is to capture the anomalies existing in electrical equipments during an inspection of some machines using A40 Flir camera. After, we use binarisation techniques in order to select the region of interest and we make comparison between these methods of thermal images obtained to choose the best one.

Keywords: infrared thermography, defect detection, troubleshooting, electrical equipment

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2801 Phytoremediation Potential of Hibiscus Cannabinus L. Grown on Different Soil Cadmium Concentration

Authors: Sarra Arbaoui, Taoufik Bettaieb

Abstract:

Contaminated soils and problems related to them have increasingly become a matter of concern. The most common the contaminants generated by industrial urban emissions and agricultural practices are trace metals). Remediation of trace metals which pollute soils can be carried out using physico-chemical processes. Nevertheless, these techniques damage the soil’s biological activity and require expensive equipment. Phytoremediation is a relatively low-cost technology based on the use of selected plants to remove, degrades or contains pollutants. The potential of kenaf for phytoremediation on Cd-contaminated soil was investigated. kenaf plants have been grown in pots containing different concentrations of cadmium. The observations made were for biomass production and cadmium content in different organs determinate by atomic emission spectrometry. Cadmium transfer from a contaminated soil to plants and into plant tissues are discussed in terms of the Bioconcentration Factor (BCF) and the Transfer Factor (TF). Results showed that Cd was found in kenaf plants at different levels. Tolerance and accumulation potential and biomass productivity indicated that kenaf could be used in phytoremediation.

Keywords: kenaf, cadmium, phytoremediation, contaminated soil

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2800 Biosensors for Parathion Based on Au-Pd Nanoparticles Modified Electrodes

Authors: Tian-Fang Kang, Chao-Nan Ge, Rui Li

Abstract:

An electrochemical biosensor for the determination of organophosphorus pesticides was developed based on electrochemical co-deposition of Au and Pd nanoparticles on glassy carbon electrode (GCE). Energy disperse spectroscopy (EDS) analysis was used for characterization of the surface structure. Scanning electron micrograph (SEM) demonstrates that the films are uniform and the nanoclusters are homogeneously distributed on the GCE surface. Acetylcholinesterase (AChE) was immobilized on the Au and Pd nanoparticle modified electrode (Au-Pd/GCE) by cross-linking with glutaraldehyde. The electrochemical behavior of thiocholine at the biosensor (AChE/Au-Pd/GCE) was studied. The biosensors exhibited substantial electrocatalytic effect on the oxidation of thiocholine. The peak current of linear scan voltammetry (LSV) of thiocholine at the biosensor is proportional to the concentration of acetylthiocholine chloride (ATCl) over the range of 2.5 × 10-6 to 2.5 × 10-4 M in 0.1 M phosphate buffer solution (pH 7.0). The percent inhibition of acetylcholinesterase was proportional to the logarithm of parathion concentration in the range of 4.0 × 10-9 to 1.0 × 10-6 M. The detection limit of parathion was 2.6 × 10-9 M. The proposed method exhibited high sensitivity and good reproducibility.

Keywords: acetylcholinesterase, Au-Pd nanoparticles, electrochemical biosensors, parathion

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2799 Harnessing Nature's Fury: Hyptis Suaveolens Loaded Bioactive Liposome for Photothermal Therapy of Lung Cancer

Authors: Sajmina Khatun, Monika Pebam, Aravind Kumar Rengan

Abstract:

Photothermal therapy, a subset of nanomedicine, takes advantage of light-absorbing agents to generate localized heat, selectively eradicating cancer cells. This innovative approach minimizes damage to healthy tissues and offers a promising avenue for targeted cancer treatment. Unlike conventional therapies, photothermal therapy harnesses the power of light to combat malignancies precisely and effectively, showcasing its potential to revolutionize cancer treatment paradigms. The combined strengths of nanomedicine and photothermal therapy signify a transformative shift toward more effective, targeted, and tolerable cancer treatments in the medical landscape. Utilizing natural products becomes instrumental in formulating diverse bioactive medications owing to their various pharmacological properties attributed to the existence of phenolic structures, triterpenoids, and similar compounds. Hyptis suaveolens, commonly known as pignut, stands as an aromatic herb within the Lamiaceae family and represents a valuable therapeutic plant. Flourishing in swamps and alongside tropical and subtropical roadsides, these noxious weeds impede the development of adjacent plants. Hyptis suaveolens ranks among the most globally distributed alien invasive species. The present investigation revealed that a versatile, biodegradable liposome nanosystem (HIL NPs), incorporating bioactive molecules from Hyptis suaveolens, exhibits effective bioavailability to cancer cells, enabling tumor ablation upon near-infrared (NIR) laser exposure. The components within the nanosystem, specifically the bioactive molecules from Hyptis, function as anticancer agents, aiding in the photothermal ablation of highly metastatic lung cancer cells. Despite being a prolific weed impeding neighboring plant growth, Hyptis suaveolens showcases therapeutic benefits through its bioactive compounds. The obtained HIL NPs, characterized as a photothermally active liposome nanosystem, demonstrate a pronounced fluorescence absorption peak in the NIR range and achieve a high photothermal conversion efficiency under NIR laser irradiation. Transmission electron microscopy (TEM) and particle size analysis reveal that HIL NPs possess a spherical shape with a size of 141 ± 30 nm. Moreover, in vitro assessments of HIL NPs against lung cancer cell lines (A549) indicate effective anticancer activity through a combined cytotoxic effect and hyperthermia. Tumor ablation is facilitated by apoptosis induced by the overexpression of ɣ-H2AX, arresting cancer cell proliferation. Consequently, the multifunctional and biodegradable nanosystem (HIL NPs), incorporating bioactive compounds from Hyptis, provides valuable perspectives for developing an innovative therapeutic strategy originating from a challenging weed. This approach holds promise for potential applications in both bioimaging and the combined use of phyto-photothermal therapy for cancer treatment.

Keywords: bioactive liposome, hyptis suaveolens, photothermal therapy, lung cancer

Procedia PDF Downloads 87
2798 Multiple Plant-Based Cell Suspension as a Bio-Ink for 3D Bioprinting Applications in Food Technology

Authors: Yusuf Hesham Mohamed

Abstract:

Introduction: Three-dimensional printing technology includes multiple procedures that fabricate three-dimensional objects through consecutively layering two-dimensional cross-sections on top of each other. 3D bioprinting is a promising field of 3D printing, which fabricates tissues and organs by accurately controlling the proper arrangement of diverse biological components. 3D bioprinting uses software and prints biological materials and their supporting components layer-by-layer on a substrate or in a tissue culture plate to produce complex live tissues and organs. 3D food printing is an emerging field of 3D bioprinting in which the 3D printed products are food products that are cheap, require less effort to produce, and have more desirable traits. The Aim of the Study is the development of an affordable 3D bioprinter by altering a locally made CNC instrument with an open-source platform to suit the 3D bio-printer purposes. Later, we went through applying the prototype in several applications regarding food technology and drug testing, including the organ-On-Chip. Materials and Methods: An off-the-shelf 3D printer was modified by designing and fabricating the syringe unit, which was designed on the basis of the Milli-fluidics system. Sodium alginate and gelatin hydrogels were prepared, followed by leaf cell suspension preparation from narrow sections of Fragaria’s viable leaves. The desired 3D structure was modeled, and 3D printing preparations took place. Cell-free and cell-laden hydrogels were printed at room temperature under sterile conditions. Post printing curing process was performed. The printed structure was further studied. Results: Positive results have been achieved using the altered 3D bioprinter where a 3D hydrogel construct of two layers made of the combination of sodium alginate to gelatin (15%: 0.5%) has been printed. DLP 3D printer was used to design the syringe component with a transparent PLA-Pro resin for the creation of a microfluidics system having two channels altered to the double extruder. The hydrogel extruder’s design was based on peristaltic pumps, which utilized a stepper motor. The design and fabrication were made using DIY-3D printed parts. Hard plastic PLA was the material utilized for printing. SEM was used to carry out the porous 3D construct imaging. Multiple physical and chemical tests were performed in order to ensure that the cell line was suitable for hosting. Fragaria plant was developed by suspending Fragaria’s cells from its leaves using the 3D bioprinter. Conclusion: 3D bioprinting is considered to be an emerging scientific field that can facilitate and improve many scientific tests and studies. Thus, having a 3D bioprinter in labs is considered to be an essential requirement. 3D bioprinters are very expensive; however, the fabrication of a 3D printer into a 3D bioprinter can lower the cost of the bioprinter. The 3D bioprinter implemented made use of peristaltic pumps instead of syringe-based pumps in order to extend the ability to print multiple types of materials and cells.

Keywords: scaffold, eco on chip, 3D bioprinter, DLP printer

Procedia PDF Downloads 114
2797 Use of Predictive Food Microbiology to Determine the Shelf-Life of Foods

Authors: Fatih Tarlak

Abstract:

Predictive microbiology can be considered as an important field in food microbiology in which it uses predictive models to describe the microbial growth in different food products. Predictive models estimate the growth of microorganisms quickly, efficiently, and in a cost-effective way as compared to traditional methods of enumeration, which are long-lasting, expensive, and time-consuming. The mathematical models used in predictive microbiology are mainly categorised as primary and secondary models. The primary models are the mathematical equations that define the growth data as a function of time under a constant environmental condition. The secondary models describe the effects of environmental factors, such as temperature, pH, and water activity (aw) on the parameters of the primary models, including the maximum specific growth rate and lag phase duration, which are the most critical growth kinetic parameters. The combination of primary and secondary models provides valuable information to set limits for the quantitative detection of the microbial spoilage and assess product shelf-life.

Keywords: shelf-life, growth model, predictive microbiology, simulation

Procedia PDF Downloads 203
2796 Face Tracking and Recognition Using Deep Learning Approach

Authors: Degale Desta, Cheng Jian

Abstract:

The most important factor in identifying a person is their face. Even identical twins have their own distinct faces. As a result, identification and face recognition are needed to tell one person from another. A face recognition system is a verification tool used to establish a person's identity using biometrics. Nowadays, face recognition is a common technique used in a variety of applications, including home security systems, criminal identification, and phone unlock systems. This system is more secure because it only requires a facial image instead of other dependencies like a key or card. Face detection and face identification are the two phases that typically make up a human recognition system.The idea behind designing and creating a face recognition system using deep learning with Azure ML Python's OpenCV is explained in this paper. Face recognition is a task that can be accomplished using deep learning, and given the accuracy of this method, it appears to be a suitable approach. To show how accurate the suggested face recognition system is, experimental results are given in 98.46% accuracy using Fast-RCNN Performance of algorithms under different training conditions.

Keywords: deep learning, face recognition, identification, fast-RCNN

Procedia PDF Downloads 134
2795 Hardware Error Analysis and Severity Characterization in Linux-Based Server Systems

Authors: Nikolaos Georgoulopoulos, Alkis Hatzopoulos, Konstantinos Karamitsios, Konstantinos Kotrotsios, Alexandros I. Metsai

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In modern server systems, business critical applications run in different types of infrastructure, such as cloud systems, physical machines and virtualization. Often, due to high load and over time, various hardware faults occur in servers that translate to errors, resulting to malfunction or even server breakdown. CPU, RAM and hard drive (HDD) are the hardware parts that concern server administrators the most regarding errors. In this work, selected RAM, HDD and CPU errors, that have been observed or can be simulated in kernel ring buffer log files from two groups of Linux servers, are investigated. Moreover, a severity characterization is given for each error type. Better understanding of such errors can lead to more efficient analysis of kernel logs that are usually exploited for fault diagnosis and prediction. In addition, this work summarizes ways of simulating hardware errors in RAM and HDD, in order to test the error detection and correction mechanisms of a Linux server.

Keywords: hardware errors, Kernel logs, Linux servers, RAM, hard disk, CPU

Procedia PDF Downloads 151