Search results for: selective adsorption sensor

Authors: Ons Slimene, Aroua Taamallah, Maha Khemaja

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In recent years, human activity recognition (HAR) has been a key area of research due to its diverse applications. It has garnered increasing attention in the field of computer vision. HAR plays an important role in people’s daily lives as it has the ability to learn advanced knowledge about human activities from data. In HAR, activities are usually represented by exploiting different types of sensors, such as embedded sensors or visual sensors. However, these sensors have limitations, such as local obstacles, image-related obstacles, sensor unreliability, and consumer concerns. Recently, several deep learning-based approaches have been proposed for HAR and these approaches are classified into two categories based on the type of data used: vision-based approaches and sensor-based approaches. This research paper highlights the importance of multimodal data fusion from skeleton data obtained from videos and data generated by embedded sensors using deep neural networks for achieving HAR. We propose a deep multimodal fusion network based on a twostream architecture. These two streams use the Convolutional Neural Network combined with the Bidirectional LSTM (CNN BILSTM) to process skeleton data and data generated by embedded sensors and the fusion at the feature level is considered. The proposed model was evaluated on a public OPPORTUNITY++ dataset and produced a accuracy of 96.77%.

Keywords: human activity recognition, action recognition, sensors, vision, human-centric sensing, deep learning, context-awareness

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Authors: John E. Foley, Martin Miele, Raul Fonda, Jon Jacobson

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This paper presents development and implementation of new and innovative data collection and analysis methodologies based on deployment of total field magnetometer arrays. Our research has focused on the development of a vertically-integrated suite of platforms all utilizing common data acquisition, data processing and analysis tools. These survey platforms include low-altitude helicopters and ground-based vehicles, including robots, for terrestrial mapping applications. For marine settings the sensor arrays are deployed from either a hydrodynamic bottom-following wing towed from a surface vessel or from a towed floating platform for shallow-water settings. Additionally, sensor arrays are deployed from tethered remotely operated vehicles (ROVs) for underwater settings where high maneuverability is required. While the primary application of these systems is the detection and mapping of unexploded ordnance (UXO), these system are also used for various infrastructure mapping and geologic investigations. For each application, success is driven by the integration of magnetometer arrays, accurate geo-positioning, system noise mitigation, and stable deployment of the system in appropriate proximity of expected targets or features. Each of the systems collects geo-registered data compatible with a web-enabled data management system providing immediate access of data and meta-data for remote processing, analysis and delivery of results. This approach allows highly sophisticated magnetic processing methods, including classification based on dipole modeling and remanent magnetization, to be efficiently applied to many projects. This paper also briefly describes the initial development of magnetometer-based detection systems deployed from low-altitude helicopter platforms and the subsequent successful transition of this technology to the marine environment. Additionally, we present examples from a range of terrestrial and marine settings as well as ongoing research efforts related to sensor miniaturization for unmanned aerial vehicle (UAV) magnetic field mapping applications.

Keywords: dipole modeling, magnetometer mapping systems, sub-surface infrastructure mapping, unexploded ordnance detection

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Authors: Hafawa Messaoudi, Taoufik Aguili

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Due to the rapid growth in the use of wireless communication systems, there has been a recent increase in public concern regarding the exposure of humans to Radio Frequency (RF) electromagnetic radiation. This is particularly evident in the case of mobile telephone handsets. Previously, the insertion of a ferrite sheet between the antenna and the human head, the use of conductive materials (such as aluminum), the use of metamaterials (SRR), frequency selective surface (FSS), and electromagnetic band gap (EBG) structures to design high performance devices were proposed as methods of reducing the SAR value. This paper aims to provide an investigation of the effectiveness of various available Specific Absorption Rate (SAR) reduction solutions.

Keywords: EBG, HIS, metamaterials, SAR reduction

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Authors: A. Rinaldi, A. Proietti, C. Aquarelli, F. Marra, A. Tamburrano, M. Ciminello, M. S. Sarto

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A new type of high sensitive piezoresistive sensors based on graphene was developed within the SARISTU project for application on Structural Health Monitoring (SHM). The new sensor consists of a graphene-based film, obtained through the spray deposition of a colloidal suspension of Multi-Layer Graphene (MLGs) nano platelets over a substrate. MLGs are produced by liquid exfoliation of thermally expanded Graphite Intercalation Compound. An array of 8 sensors is produced by spray deposition over an aeronautical CFRC plate of dimensions 550 mm (length) × 550 mm (width) × 3 mm (thickness). Electromechanical tests were performed in order to assess the sensitivity of the new piezoresistive sensors, which are characterized by an isotropic response. In the quasi-static characterizations, the CFRC plate was clamped on one side and loaded on the opposite one. The local strain map of the plate was then obtained from displacement measurements and numerical analysis. The dynamic tests were performed lying the plate over an anti-vibration table and actuating a piezoelectric element located in the middle of the sensing array. The obtained experimental results demonstrated that the sensors possess a good repeatability and a high constant gauge factor (~200) in the applied strain range 0.001%-0.02%. Moreover, they can follow dynamics up to 400 kHz and for this reason they are good candidates for Lamb-wave analysis.

Keywords: graphene, strain sensor, spray deposition, lamb-wave analysis

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Authors: N. Ouslimani, T. Abadlia, M. Fadel

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This work focused on the elimination of acid textile dye (red bermacide acid dye BN-CL-200), widely used for dyeing wool and polyamide fibers, by adsorption on a natural material, wood sawdust, in the static mode by keeping under continuous stirring, a specific mass of the adsorbent, with a dye solution of known concentration. The influence of various parameters is studied like the influence of particle size, mass, pH and time. The best results were obtained with 0.4 mm grain size, mass of 3g, Temperature of 20 °C, pH 2 and Time contact of 120 min.

Keywords: acid dye, environment, wood sawdust, wastewater

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Authors: Jing Zhang, Yvonne Reinwald, Nick Poulson, Alicia El Haj, Chung See, Mike Somekh, Melissa Mather

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Biomedical imaging of native tissue using light offers the potential to obtain excellent structural and functional information in a non-invasive manner with good temporal resolution. Image contrast can be derived from intrinsic absorption, fluorescence, or scatter, or through the use of extrinsic contrast. A major challenge in applying optical microscopy to in vivo tissue imaging is the effects of light attenuation which limits light penetration depth and achievable imaging resolution. Recently Selective Plane Illumination Microscopy (SPIM) has been used to map the 3D distribution of fluorophores dispersed in biological structures. In this approach, a focused sheet of light is used to illuminate the sample from the side to excite fluorophores within the sample of interest. Images are formed based on detection of fluorescence emission orthogonal to the illumination axis. By scanning the sample along the detection axis and acquiring a stack of images, 3D volumes can be obtained. The combination of rapid image acquisition speeds with the low photon dose to samples optical sectioning provides SPIM is an attractive approach for imaging biological samples in 3D. To date all implementations of SPIM rely on the use of fluorescence reporters be that endogenous or exogenous. This approach has the disadvantage that in the case of exogenous probes the specimens are altered from their native stage rendering them unsuitable for in vivo studies and in general fluorescence emission is weak and transient. Here we present for the first time to our knowledge a label-free implementation of SPIM that has downstream applications in the clinical setting. The experimental set up used in this work incorporates both label-free and fluorescent illumination arms in addition to a high specification camera that can be partitioned for simultaneous imaging of both fluorescent emission and scattered light from intrinsic sources of optical contrast in the sample being studied. This work first involved calibration of the imaging system and validation of the label-free method with well characterised fluorescent microbeads embedded in agarose gel. 3D constructs of mammalian cells cultured in agarose gel with varying cell concentrations were then imaged. A time course study to track cell proliferation in the 3D construct was also carried out and finally a native tissue sample was imaged. For each sample multiple images were obtained by scanning the sample along the axis of detection and 3D maps reconstructed. The results obtained validated label-free SPIM as a viable approach for imaging cells in a 3D gel construct and native tissue. This technique has the potential use in a near-patient environment that can provide results quickly and be implemented in an easy to use manner to provide more information with improved spatial resolution and depth penetration than current approaches.

Keywords: bioimaging, optics, selective plane illumination microscopy, tissue imaging

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Authors: Kirandeep Kaur, Rohit Mehra, Pargin Bangotra

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Radon and thoron are pervasive radioactive gases and so are their progenies. The progenies of radon and thoron are present in the indoor atmosphere as attached/unattached fractions. In the present work, seasonal variation of concentration of attached and total (attached + unattached) nanosized decay products of indoor radon and thoron has been studied in the dwellings of Bathinda District of Punjab using Deposition based progeny sensors over long integrated times, which are independent of air turbulence. The preliminary results of these measurements are reported particularly regarding DTPS (Direct Thoron Progeny Sensor) and DRPS (Direct Radon Progeny Sensor) for the first time in Bathinda. It has been observed that there is a strong linear relationship in total EERC (Equilibrium Equivalent Radon Concentration) and EETC (Equilibrium Equivalent Thoron Concentration) in rainy season (R2 = 0.83). Further a strong linear relation between total indoor radon concentration and attached fraction has also been observed for the same rainy season (R2= 0.91). The concentration of attached progeny of radon (EERCatt) is 76.3 % of the total Equilibrium Equivalent Radon Concentration (EERC).

Keywords: radon, thoron, progeny, DTPS/DRPS, EERC, EETC, seasonal variation

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Authors: Abayomi O. Adetuyi, Jamiu M. Jabar, Samuel O. Afolabi

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Vegetable fibres are classes of fibres of low density, biodegradable and non-abrasive that are largely abundant fibre materials with specific properties and mostly found/ obtained in plants on earth surface. They are classified into three categories, depending on the part of the plant from which they are gotten from namely: fruit, Blast and Leaf fibre. Ever since four/five millennium B.C, attention has been focussing on the commonest and highly utilized cotton fibre obtained from the fruit of cotton plants (Gossypium spp), for the production of cotton fabric used in every home today. The present study, therefore, focused on the ability of three underutilized vegetable (fruit) fibres namely: coir fiber (Eleas coniferus), palm kernel fiber and empty fruit bunch fiber (Elias guinensis) through chemical modifications for better composite value addition performance to polyurethane form and dye adsorption. These fibres were sourced from their parents’ plants, identified and cleansed with 2% hot detergent solution 1:100, rinsed in distilled water and oven-dried to constant weight, before been chemically modified through alkali bleaching, mercerization and acetylation. The alkali bleaching involves treating 0.5g of each fiber material with 100 mL of 2% H2O2 in 25 % NaOH solution with refluxing for 2 h. While that of mercerization and acetylation involves the use of 5% sodium hydroxide NaOH solution for 2 h and 10% acetic acid- acetic anhydride 1:1 (v/v) (CH3COOH) / (CH3CO)2O solution with conc. H2SO4 as catalyst for 1 h, respectively on the fibres. All were subsequently washed thoroughly with distilled water and oven dried at 105 0C for 1 h. These modified fibres were incorporated as composite into polyurethane form and used in dye adsorption study of indigo. The first two treatments led to fiber weight reduction, while the acidified acetic anhydride treatment gave the fibers weight increment. All the treated fibers were found to be of less hydrophilic nature, better mechanical properties, higher thermal stabilities as well as better adsorption surfaces/capacities than the untreated ones. These were confirmed by gravimetric analysis, Instron Universal Testing Machine, Thermogravimetric Analyser and the Scanning Electron Microscope (SEM) respectively. The fiber morphology of the modified fibers showed smoother surfaces than unmodified fibres.The empty fruit bunch fibre and the coconut coir fibre are better than the palm kernel fibres as reinforcers for composites or as adsorbents for waste-water treatment. Acetylation and alkaline bleaching treatment improve the potentials of the fibres more than mercerization treatment. Conclusively, vegetable fibres, especially empty fruit bunch fibre and the coconut coir fibre, which are cheap, abundant and underutilized, can replace the very costly powdered activated carbon in wastewater treatment and as reinforcer in foam.

Keywords: chemical modification, industrial application, value addition, vegetable fibre

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Authors: Jin Lin, Shouxiang Lu, Kim Meow Liew

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In a fire accident, fire smoke often poses a serious threat to human safety especially in the enclosed space such as submarine and space-crafts environment. Efficient removal of the hazardous gas products particularly a large amount of CO and CO₂ gases from these confined space is critical for the security of the staff and necessary for the post-fire environment recovery. In this work, Cu-Mn-Ce composite oxide catalysts coupled with CO₂ sorbents were prepared using wet impregnation method, solid-state impregnation method and wet/solid-state impregnation method. The as-prepared samples were tested dynamically and isothermally for CO oxidation and CO₂ sorption and further characterized by the X-ray diffraction (XRD), nitrogen adsorption and desorption, and field emission scanning electron microscopy (FE-SEM). The results showed that all the samples were able to catalyze CO into CO₂ and capture CO₂ in situ by chemisorption. Among all the samples, the sample synthesized by the wet/solid-state impregnation method showed the highest catalytic activity toward CO oxidation and the fine ability of CO₂ sorption. The sample prepared by the solid-state impregnation method showed the second CO oxidation performance, while the coupled sample using the wet impregnation method exhibited much poor CO oxidation activity. The various CO oxidation and CO₂ sorption properties of the samples might arise from the different dispersed states of the CO₂ sorbent in the CO catalyst, owing to the different preparation methods. XRD results confirmed the high-dispersed sorbent phase in the samples prepared by the wet and solid impregnation method, while that of the sample prepared by wet/solid-state impregnation method showed the larger bulk phase as indicated by the high-intensity diffraction peaks. Nitrogen adsorption and desorption results further revealed that the latter sample had a higher surface area and pore volume, which were beneficial for the CO oxidation over the catalyst. Hence, the Cu-Mn-Ce oxide catalyst coupled with CO₂ sorbent using wet/solid-state impregnation method could be a good choice for fire smoke removal in the enclosed space.

Keywords: CO oxidation, CO₂ sorption, preparation methods, smoke removal

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Authors: Larry Powell, Seth Polsley, Drew Casey, Tracy Hammond

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Human activity recognition (HAR) systems have shown positive performance when recognizing repetitive activities like walking, running, and sleeping. Water-based activities are a reasonably new area for activity recognition. However, water-based activity recognition has largely focused on supporting the elite and competitive swimming population, which already has amazing coordination and proper form. Beginner swimmers are not perfect, and activity recognition needs to support the individual motions to help beginners. Activity recognition algorithms are traditionally built around short segments of timed sensor data. Using a time window input can cause performance issues in the machine learning model. The window’s size can be too small or large, requiring careful tuning and precise data segmentation. In this work, we present a method that uses a time window as the initial segmentation, then separates the data based on the change in the sensor value. Our system uses a multi-phase segmentation method that pulls all peaks and valleys for each axis of an accelerometer placed on the swimmer’s lower back. This results in high recognition performance using leave-one-subject-out validation on our study with 20 beginner swimmers, with our model optimized from our final dataset resulting in an F-Score of 0.95.

Keywords: time window, peak/valley segmentation, feature extraction, beginner swimming, activity recognition

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Authors: Prasanna Belur, P. R. Ashwini, Sampath Charanyaa, I. Regupathi

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Indian oil sardine (Sardinella longiceps) are one of the richest and cheapest sources of n-3 polyunsaturated fatty acids (n-3 PUFA) such as Eicosapentaenoic acid (EPA) and Docosahexaenoic acid (DHA). The health benefits conferred by n-3 PUFA upon consumption, in the prevention and treatment of coronary, neuromuscular, immunological disorders and allergic conditions are well documented. Natural refined Indian Sardine oil generally contain about 25% (w/w) n-3 PUFA along with various unsaturated and saturated fatty acids in the form of mono, di, and triglycerides. Having high concentration of n-3 PUFA content in the glyceride form is most desirable for human consumption to avail maximum health benefits. Thus, enhancing the n-3 PUFA content while retaining it in the glyceride form with green technology is the need of the hour. In this study, refined Indian Sardine oil was subjected to selective hydrolysis by Candida antartica lipase to enhance n-3 PUFA content. The degree of hydrolysis and enhancement of n-3 PUFA content was estimated by determining acid value, Iodine value, EPA and DHA content (by Gas Chromatographic methods after derivitization) before and after hydrolysis. Various reaction parameters such as pH, temperature, enzyme load, lipid to aqueous phase volume ratio and incubation time were optimized by conducting trials with one parameter at a time approach. Incubating enzyme solution with refined sardine oil with a volume ratio of 1:1, at pH 7.0, for 60 minutes at 50 °C, with an enzyme load of 60 mg/ml was found to be optimum. After enzymatic treatment, the oil was subjected to refining to remove free fatty acids and moisture content using previously optimized refining technology. Enzymatic treatment at the optimal conditions resulted in 12.11 % enhancement in Degree of hydrolysis. Iodine number had increased by 9.7 % and n-3 PUFA content was enhanced by 112 % (w/w). Selective enhancement of n-3 PUFA glycerides, eliminating saturated and unsaturated fatty acids from the oil using enzyme is an interesting preposition as this technique is environment-friendly, cost effective and provide natural source of n-3 PUFA rich oil.

Keywords: Candida antartica, lipase, n-3 polyunsaturated fatty acids, sardine oil

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Authors: Anusha Jain, Santosh Vishwanathan, Praveen K. Gupta, Shwetha S., Kavitha S. N.

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Agriculture has a major impact on the Indian economy, with the highest employment ratio than any sector of the country. Currently, most of the traditional agricultural practices and farming methods are manual, which results in farmers not realizing their maximum productivity often due to increasing in labour cost, inefficient use of water sources leading to wastage of water, inadequate soil moisture content, subsequently leading to food insecurity of the country. This research paper aims to solve this problem by developing a full-fledged web application-based platform that has the capacity to associate itself with a Microcontroller-based Automated Irrigation System which schedules the irrigation of crops based on real-time soil moisture content employing soil moisture sensors centric to the crop’s requirements using WSN (Wireless Sensor Networks) and M2M (Machine To Machine Communication) concepts, thus optimizing the use of the available limited water resource, thereby maximizing the crop yield. This robust automated irrigation system provides end-to-end automation of Irrigation of crops at any circumstances such as droughts, irregular rainfall patterns, extreme weather conditions, etc. This platform will also be capable of achieving a nationwide united farming community and ensuring the welfare of farmers. This platform is designed to equip farmers with prerequisite knowledge on tech and the latest farming practices in general. In order to achieve this, the MailChimp mailing service is used through which interested farmers/individuals' email id will be recorded and curated articles on innovations in the world of agriculture will be provided to the farmers via e-mail. In this proposed system, service is enabled on the platform where nearby crop vendors will be able to enter their pickup locations, accepted prices and other relevant information. This will enable farmers to choose their vendors wisely. Along with this, we have created a blogging service that will enable farmers and agricultural enthusiasts to share experiences, helpful knowledge, hardships, etc., with the entire farming community. These are some of the many features that the platform has to offer.

Keywords: WSN (wireless sensor networks), M2M (M/C to M/C communication), automation, irrigation system, sustainability, SAAS (software as a service), soil moisture sensor

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Authors: Sivananth Murugesan, I. Regupathi, B. Vishwas Prabhu, Ankit Devatwal, Vishnu Sivan Pillai

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Pectinase is an important enzyme which has a wide range of applications including textile processing and bioscouring of cotton fibers, coffee and tea fermentation, purification of plant viruses, oil extraction etc. Selective separation and purification of pectinase from fermentation broth and recover the enzyme form process stream for reuse are cost consuming process in most of the enzyme based industries. It is difficult to identify a suitable medium to enhance enzyme activity and retain its enzyme characteristics during such processes. The cost effective, selective separation of enzymes through the modified Liquid-liquid extraction is of current research interest worldwide. Reverse micellar extraction, globally acclaimed Liquid-liquid extraction technique is well known for its separation and purification of solutes from the feed which offers higher solute specificity and partitioning, ease of operation and recycling of extractants used. Surfactant concentrations above critical micelle concentration to an apolar solvent form micelles and addition of micellar phase to water in turn forms reverse micelles or water-in-oil emulsions. Since, electrostatic interaction plays a major role in the separation/purification of solutes using reverse micelles. These interaction parameters can be altered with the change in pH, addition of cosolvent, surfactant and electrolyte and non-electrolyte. Even though many chemical based commercial surfactant had been utilized for this purpose, the biosurfactants are more suitable for the purification of enzymes which are used in food application. The present work focused on the partitioning of pectinase from the synthetic aqueous solution within the reverse micelle phase formed by a biosurfactant, Soybean Lecithin dissolved in chloroform. The critical micelle concentration of soybean lecithin/chloroform solution was identified through refractive index and density measurements. Effect of surfactant concentrations above and below the critical micelle concentration was considered to study its effect on enzyme activity, enzyme partitioning within the reverse micelle phase. The effect of pH and electrolyte salts on the partitioning behavior was studied by varying the system pH and concentration of different salts during forward and back extraction steps. It was observed that lower concentrations of soybean lecithin enhanced the enzyme activity within the water core of the reverse micelle with maximizing extraction efficiency. The maximum yield of pectinase of 85% with a partitioning coefficient of 5.7 was achieved at 4.8 pH during forward extraction and 88% yield with a partitioning coefficient of 7.1 was observed during backward extraction at a pH value of 5.0. However, addition of salt decreased the enzyme activity and especially at higher salt concentrations enzyme activity declined drastically during both forward and back extraction steps. The results proved that reverse micelles formed by Soybean Lecithin and chloroform may be used for the extraction of pectinase from aqueous solution. Further, the reverse micelles can be considered as nanoreactors to enhance enzyme activity and maximum utilization of substrate at optimized conditions, which are paving a way to process intensification and scale-down.

Keywords: pectinase, reverse micelles, soybean lecithin, selective partitioning

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Authors: Marlon Gallo, Eduardo Miguel, Laura Oca, Eneko Gonzalez, Unai Iraola

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The heat generation of an energy storage system is an essential topic when designing a battery pack and its cooling system. Heat generation estimation is used together with thermal models to predict battery temperature in operation and adapt the design of the battery pack and the cooling system to these thermal needs guaranteeing its safety and correct operation. In the present work, a comparison between the use of a heat flux sensor (HFS) for indirect measurement of heat losses in a cell and the widely used and simplified version of Bernardi’s equation for estimation is presented. First, a Li-ion cell is thermally characterized with an HFS to measure the thermal parameters that are used in a first-order lumped thermal model. These parameters are the equivalent thermal capacity and the thermal equivalent resistance of a single Li-ion cell. Static (when no current is flowing through the cell) and dynamic (making current flow through the cell) tests are conducted in which HFS is used to measure heat between the cell and the ambient, so thermal capacity and resistances respectively can be calculated. An experimental platform records current, voltage, ambient temperature, surface temperature, and HFS output voltage. Second, an equivalent circuit model is built in a Matlab-Simulink environment. This allows the comparison between the generated heat predicted by Bernardi’s equation and the HFS measurements. Data post-processing is required to extrapolate the heat generation from the HFS measurements, as the sensor records the heat released to the ambient and not the one generated within the cell. Finally, the cell temperature evolution is estimated with the lumped thermal model (using both HFS and Bernardi’s equation total heat generation) and compared towards experimental temperature data (measured with a T-type thermocouple). At the end of this work, a critical review of the results obtained and the possible mismatch reasons are reported. The results show that indirectly measuring the heat generation with HFS gives a more precise estimation than Bernardi’s simplified equation. On the one hand, when using Bernardi’s simplified equation, estimated heat generation differs from cell temperature measurements during charges at high current rates. Additionally, for low capacity cells where a small change in capacity has a great influence on the terminal voltage, the estimated heat generation shows high dependency on the State of Charge (SoC) estimation, and therefore open circuit voltage calculation (as it is SoC dependent). On the other hand, with indirect measuring the heat generation with HFS, the resulting error is a maximum of 0.28ºC in the temperature prediction, in contrast with 1.38ºC with Bernardi’s simplified equation. This illustrates the limitations of Bernardi’s simplified equation for applications where precise heat monitoring is required. For higher current rates, Bernardi’s equation estimates more heat generation and consequently, a higher predicted temperature. Bernardi´s equation accounts for no losses after cutting the charging or discharging current. However, HFS measurement shows that after cutting the current the cell continues generating heat for some time, increasing the error of Bernardi´s equation.

Keywords: lithium-ion battery, heat flux sensor, heat generation, thermal characterization

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Authors: Gopalasingam Daisan

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Landmines and ammunitions have been creating a significant threat to the people and animals, after the war, the landmines remain in the land and it plays a vital role in civilian’s security. Especially the Children are at the highest risk because they are curious. After all, an unexploded bomb can look like a tempting toy to an inquisitive child. The initial step of designing the UAS (Unmanned Aircraft Systems) for landmine detection is to choose an appropriate and effective sensor to locate the landmines and other unexploded ammunitions. The sensor weight and other components related to the sensor supporting device’s weight are taken as a payload weight. The mission requirement is to find the landmines in a particular area by making a proper path that will cover all the vicinity in the desired area. The weight estimation of the UAV (Unmanned Aerial Vehicle) can be estimated by various techniques discovered previously with good accuracy at the first phase of the design. The next crucial part of the design is to calculate the power requirement and the wing loading calculations. The matching plot techniques are used to determine the thrust-to-weight ratio, and this technique makes this process not only easiest but also precisely. The wing loading can be calculated easily from the stall equation. After these calculations, the wing area is determined from the wing loading equation and the required power is calculated from the thrust to weight ratio calculations. According to the power requirement, an appropriate engine can be selected from the available engine from the market. And the wing geometric parameter is chosen based on the conceptual sketch. The important steps in the wing design to choose proper aerofoil and which will ensure to create sufficient lift coefficient to satisfy the requirements. The next component is the tail; the tail area and other related parameters can be estimated or calculated to counteract the effect of the wing pitching moment. As the vertical tail design depends on many parameters, the initial sizing only can be done in this phase. The fuselage is another major component, which is selected based on the slenderness ratio, and also the shape is determined on the sensor size to fit it under the fuselage. The landing gear is one of the important components which is selected based on the controllability and stability requirements. The minimum and maximum wheel track and wheelbase can be determined based on the crosswind and overturn angle requirements. The minor components of the landing gear design and estimation are not the focus of this project. Another important task is to calculate the weight of the major components and it is going to be estimated using empirical relations and also the mass is added to each such component. The CG and moment of inertia are also determined to each component separately. The sensitivity of the weight calculation is taken into consideration to avoid extra material requirements and also reduce the cost of the design. Finally, the aircraft performance is calculated, especially the V-n (velocity and load factor) diagram for different flight conditions such as not disturbed and with gust velocity.

Keywords: landmine, UAS, matching plot, optimization

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Authors: Hang Zhou, Limin Zhu

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This paper investigates the fabrication of microstructures on Si surfaces by using electrochemical anodic oxidation with agarose stamps. The fabricating process is based on a selective anodic oxidation reaction that occurs in the contact area between a stamp and a Si substrate. The stamp which is soaked in electrolyte previously acts as a current flow channel. After forming the oxide patterns as an etching mask, a KOH aqueous is used for the wet etching of Si. A complicated microstructure array of 1 cm2 was fabricated by the method with high accuracy.

Keywords: microstructures, anodic oxidation, silicon, agarose stamps

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Authors: Nikolai A. Khlebnikov, Vladimir N. Krasilnikov, Evgenii V. Polyakov, Anastasia A. Maltceva

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Carbon materials with advanced surfaces are widely used both in modern industry and in environmental protection. The physical-chemical nature of these materials is determined by the morphology of primary atomic and molecular carbon structures, which are the basis for synthesizing the following materials: zero-dimensional (fullerenes), one-dimensional (fiber, tubes), two-dimensional (graphene) carbon nanostructures, three-dimensional (multi-layer graphene, graphite, foams) with unique physical-chemical and functional properties. Experience shows that the microscopic morphological level is the basis for the creation of the next mesoscopic morphological level. The dependence of the morphology on the chemical way and process prehistory (crystallization, colloids formation, liquid crystal state and other) is the peculiarity of the last called level. These factors determine the consumer properties of carbon materials, such as specific surface area, porosity, chemical resistance in corrosive environments, catalytic and adsorption activities. Based on the developed ideology of thin precursor synthesis, the authors discuss one of the approaches of the porosity control of carbon-containing materials with a given aggregates morphology. The low-temperature thermolysis of precursors in a gas environment of a given composition is the basis of the above-mentioned idea. The processes of carbothermic precursor synthesis of two different compounds: tungsten carbide WC:nC and zinc oxide ZnO:nC containing an impurity phase in the form of free carbon were selected as subjects of the research. In the first case, the transition metal (tungsten) forming carbides was the object of the synthesis. In the second case, there was selected zinc that does not form carbides. The synthesis of both kinds of transition metals compounds was conducted by the method of precursor carbothermic synthesis from the organic solution. ZnO:nC composites were obtained by thermolysis of succinate Zn(OO(CH2)2OO), formate glycolate Zn(HCOO)(OCH2CH2O)1/2, glycerolate Zn(OCH2CHOCH2OH), and tartrate Zn(OOCCH(OH)CH(OH)COO). WC:nC composite was synthesized from ammonium paratungstate and glycerol. In all cases, carbon structures that are specific for diamond- like carbon forms appeared on the surface of WC and ZnO particles after the heat treatment. Tungsten carbide and zinc oxide were removed from the composites by selective chemical dissolution preserving the amorphous carbon phase. This work presents the results of investigating WC:nC and ZnO:nC composites and carbon nanopowders with tubular, tape, plate and onion morphologies of aggregates that are separated by chemical dissolution of WC and ZnO from the composites by the following methods: SEM, TEM, XPA, Raman spectroscopy, and BET. The connection between the carbon morphology under the conditions of synthesis and chemical nature of the precursor and the possibility of regulation of the morphology with the specific surface area up to 1700-2000 m2/g of carbon-structured materials are discussed.

Keywords: carbon morphology, composite materials, precursor synthesis, tungsten carbide, zinc oxide

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Authors: Massimiliano Nastri

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The study examines the façade systems according to the constitutive and typological characters, as well as the functional and applicative requirements such as the expressive, constructive, and interactive criteria towards the environmental, perceptive, and energy conditions. The envelope systems are understood as instruments of mediation, interchange, and dynamic interaction between environmental conditions. The façades are observed for the sustainable concept of eco-efficient envelopes, selective and multi-purpose filters, adaptable and adjustable according to the environmental performance.

Keywords: typologies of façades, environmental and energy sustainability, interaction and perceptive mediation, technical skins

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Authors: Meriem Abid, Erika Oliveria-Jardim, Andres Fullana, Joaquin Silvestre-Albero

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The rapid industrial development associated with the increase of volatile organic compounds (VOCs) has seriously impacted the environment. Among VOCs, hydrogen sulfide (H₂S) is known as a highly toxic, malodorous, flammable, and corrosive gas, which is emitted from diverse chemical processes, including industrial waste-gas streams, natural gas processing, and biogas purification. The high toxicity, corrosively, and very characteristic odor threshold of H2S call for urgent development of efficient desulfurization processes from the viewpoint of environmental protection and resource regeneration. In order to reduce H₂S emissions, effective technologies for have been performed. The general method of H₂S removal included amine aqueous solution, adsorption process, biological methods, and fixed-bed solid catalytic oxidation processes. Ecologically and economically, low-temperature direct oxidation of H₂S to elemental sulfur using catalytic oxidation is the preferred approach for removing H₂S-containing gas streams. A large number of catalysts made from carbon, metal oxides, clay, and others, have been studied extensively for this application. In this sense, activated carbon (AC) is an attractive catalyst for H₂S removal because it features a high specific surface area, diverse functional groups, low cost, durability, and high efficiency. It is interesting to stand out that AC is modified using metal oxides to promote the efficiency of H₂S removal and to enhance the catalytic performance. Based on these premises, the main goal of the present study is the evaluation of the H₂S adsorption performance in carbon-encapsulated iron nanoparticles obtained from an olive mill, thermally treated at 600, 800 and 1000 ºC temperatures under anaerobic conditions. These results anticipate that carbon-encapsulated iron nanoparticles exhibit a promising performance for the H₂S removal up to 360 mg/g.

Keywords: H₂S removal, catalytic oxidation, carbon encapsulated iron, olive mill wastewater

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Authors: Houssam Hijazi, Laurent Cantrel, Jean-François Paul

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Periodic DFT calculations were performed to study the chemistry of CsI particles and the possible release of volatile iodine from CsI surfaces for nuclear safety interest. The results show that water adsorbs at low temperature associatively on the (011) surface of CsI, while water desorbs at higher temperatures. On the other hand, removing iodine species from the surface requires oxidizing the surface one time for each removed iodide atom. The activation energy of removing I₂ from the surface in the presence of two OH is 1,2 eV.

Keywords: aerosols, CSI, reactivity, DFT, water adsorption

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Authors: Asim Laeeq Khan, Mazhar Amjad Gilani, Tayub Raza

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The use of fossil fuels for energy generation leads to the emission of greenhouse gases particularly CO2 into the atmosphere. To date, several techniques have been proposed for the efficient removal of CO2 from flue gas mixtures. Membrane technology is a promising choice due to its several inherent advantages such as low capital cost, high energy efficiency, and low ecological footprint. One of the goals in the development of membranes is to achieve high permeability and selectivity. Mixed matrix membranes comprising of inorganic fillers embedded in polymer matrix are a class of membranes that have showed improved separation properties. One of the biggest challenges in the commercialization if mixed matrix membranes are the removal of non-selective voids existing at the polymer-filler interface. In this work, mixed matrix membranes were prepared using polysulfone as polymer matrix and ordered mesoporous MCM-41 as filler materials. A new approach to removing the interfacial voids was developed by introducing room temperature ionic (RTIL) at the polymer-filler interface. The results showed that the imidazolium based RTIL not only provided wettability characteristics but also helped in further improving the separation properties. The removal of interfacial voids and good contact between polymer and filler was verified by SEM measurement. The synthesized membranes were tested in a custom built gas permeation set-up for the measurement of gas permeability and ideal gas selectivity. The results showed that the mixed matrix membranes showed significantly higher CO2 permeability in comparison to the pristine membrane. In order to have further insight into the role of fillers, diffusion and solubility measurements were carried out. The results showed that the presence of highly porous fillers resulted in increasing the diffusion coefficient while the solubility showed a slight drop. The RTIL filled membranes showed higher CO2/CH4 and CO2/N2 selectivity than unfilled membranes while the permeability dropped slightly. The increase in selectivity was due to the highly selective RTIL used in this work. The study revealed that RTIL filled mixed matrix membranes are an interesting candidate for gas separation membranes.

Keywords: ionic liquids, CO2 separation, membranes, mixed matrix membranes

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Authors: Raz Flieshman, Adam Michael Altenbuchner, Jörg Krüger

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This paper presents an approach to optimizing the Fused Deposition Modeling (FDM) 3D printing process through a preprocess calibration routine of printing parameters. The core of this method involves the use of a low-cost thermal sensor capable of measuring tempera-tures within the range of -20 to 500 degrees Celsius for detailed process observation. The calibration process is conducted by printing a predetermined path while varying the process parameters through machine instructions (g-code). This enables the extraction of critical thermal, dimensional, and surface properties along the printed path. The calibration routine utilizes computer vision models to extract features and metrics from the thermal images, in-cluding temperature distribution, layer adhesion quality, surface roughness, and dimension-al accuracy and consistency. These extracted properties are then analyzed to optimize the process parameters to achieve the desired qualities of the printed material. A significant benefit of this calibration method is its potential to create printing parameter profiles for new polymer and composite materials, thereby enhancing the versatility and application range of FDM 3D printing. The proposed method demonstrates significant potential in enhancing the precision and reliability of FDM 3D printing, making it a valuable contribution to the field of additive manufacturing.

Keywords: FDM 3D printing, preprocess calibration, thermal sensor, process optimization, additive manufacturing, computer vision, material profiles

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Authors: Hui Zhang, Sherif Beskhyroun

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In this study, a highly flexible LoRa-Based wireless sensing system was used to assess the strain state performance of building structures. The system was developed to address the local damage limitation of structural health monitoring (SHM) systems. The system is part of an intelligent SHM system designed to monitor, collect and transmit strain changes in key structural components. The main purpose of the wireless sensor system is to reduce the development and installation costs, and reduce the power consumption of the system, so as to achieve long-time monitoring. The highly stretchable flexible strain gauge is mounted on the surface of the structure and is waterproof, heat resistant, and low temperature resistant, greatly reducing the installation and maintenance costs of the sensor. The system was also developed with the aim of using LoRa wireless communication technology to achieve both low power consumption and long-distance transmission, therefore solving the problem of large-scale deployment of sensors to cover more areas in large structures. In the long-term monitoring of the building structure, the system shows very high performance, very low actual power consumption, and wireless transmission stability. The results show that the developed system has a high resolution, sensitivity, and high possibility of long-term monitoring.

Keywords: LoRa, SHM system, strain measurement, civil structures, flexible sensing system

Procedia PDF Downloads 81

Authors: Ru-Yin Yang, Chi Wu, Cheng-Yu Tsai, Yin-Tzu Lin, Wen-Te Liu

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Background: Sleep breathing disorder (SDB) is a condition demonstrated by recurrent episodes of the airway obstruction leading to intermittent hypoxia and quality fragmentation during sleep time. However, the procedures for SDB severity examination remain complicated and costly. Objective: The objective of this study is to establish a simplified examination method for SDB by the respiratory impendence pattern sensor combining the signal processing and machine learning model. Methodologies: We records heart rate variability by the electrocardiogram and respiratory pattern by impendence. After the polysomnography (PSG) been done with the diagnosis of SDB by the apnea and hypopnea index (AHI), we calculate the episodes with the absence of flow and arousal index (AI) from device record. Subjects were divided into training and testing groups. Neuron network was used to establish a prediction model to classify the severity of the SDB by the AI, episodes, and body profiles. The performance was evaluated by classification in the testing group compared with PSG. Results: In this study, we enrolled 66 subjects (Male/Female: 37/29; Age:49.9±13.2) with the diagnosis of SDB in a sleep center in Taipei city, Taiwan, from 2015 to 2016. The accuracy from the confusion matrix on the test group by NN is 71.94 %. Conclusion: Based on the models, we established a prediction model for SDB by means of the wearable sensor. With more cases incoming and training, this system may be used to rapidly and automatically screen the risk of SDB in the future.

Keywords: sleep breathing disorder, apnea and hypopnea index, body parameters, neuron network

Procedia PDF Downloads 124

Authors: Olakanmi Oladayo Olufemi, Bamifewe Olusegun James, Badmus Yaya Opeyemi, Adegoke Kayode

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The wireless sensor network (WSN) has made a significant contribution to the emergence of various intelligent services or cloud-based applications. Most of the time, these data are stored on a cloud platform for efficient management and sharing among different services or users. However, the sensitivity of the data makes them prone to various confidentiality and performance-related attacks during and after harvesting. Various security schemes have been developed to ensure the integrity and confidentiality of the WSNs' data. However, their specificity towards particular attacks and the resource constraint and heterogeneity of WSNs make most of these schemes imperfect. In this paper, we propose a secure variance-aware routing and authentication scheme with two-tier verification to collect, share, and manage WSN data. The scheme is capable of classifying WSN into different subnets, detecting any attempt of wormhole and black hole attack during harvesting, and enforcing access control on the harvested data stored in the cloud. The results of the analysis showed that the proposed scheme has more security functionalities than other related schemes, solves most of the WSNs and cloud security issues, prevents wormhole and black hole attacks, identifies the attackers during data harvesting, and enforces access control on the harvested data stored in the cloud at low computational, storage, and communication overheads.

Keywords: data block, heterogeneous IoT network, data harvesting, wormhole attack, blackhole attack access control

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Authors: M. Shaheen Sarkar, M. Lutfor Rahman, Mashitah Mohd Yusoff

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We prepared a highly active Khaya cellulose supported poly(hydroxamic acid) copper nanoparticles by the surface modification of Khaya cellulose through graft co-polymerization and subsequently amidoximation. The Cu-nanoparticle (0.05 mol% to 50 mol ppm) was selectively promoted Aza-Michael reaction of aliphatic amines to give the corresponding alkylated products at room temperature in methanol. The supported nanoparticle was easy to recover and reused seven times without significance loss of its activity.

Keywords: Aza-Michael, copper, cellulose, nanoparticles, poly(hydroxamic acid)

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Authors: B. Padmaja, V. V. Rama Prasad, K. V. N. Sunitha, E. Krishna Rao Patro

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Stress is a psychological condition that reduces the quality of sleep and affects every facet of life. Constant exposure to stress is detrimental not only for mind but also body. Nevertheless, to cope with stress, one should first identify it. This paper provides an effective method for the cognitive stress level detection by using data provided from a physical activity tracker device Fitbit. This device gathers people’s daily activities of food, weight, sleep, heart rate, and physical activities. In this paper, four major stressors like physical activities, sleep patterns, working hours and change in heart rate are used to assess the stress levels of individuals. The main motive of this system is to use machine learning approach in stress detection with the help of Smartphone sensor technology. Individually, the effect of each stressor is evaluated using logistic regression and then combined model is built and assessed using variants of ordinal logistic regression models like logit, probit and complementary log-log. Then the quality of each model is evaluated using Akaike Information Criterion (AIC) and probit is assessed as the more suitable model for our dataset. This system is experimented and evaluated in a real time environment by taking data from adults working in IT and other sectors in India. The novelty of this work lies in the fact that stress detection system should be less invasive as possible for the users.

Keywords: physical activity tracker, sleep pattern, working hours, heart rate, smartphone sensor

Procedia PDF Downloads 241

Authors: Sardar Khana, Zar Ali Khana

Abstract:

Rapid industrial development and urbanization contribute a lot to wastewater discharge. The wastewater enters into natural aquatic ecosystems from industrial activities and considers as one of the main sources of water pollution. Discharge of effluents loaded with heavy metals into the surrounding environment has become a key issue regarding human health risk, environment, and food chain contamination. Nickel causes fatigue, cancer, headache, heart problems, skin diseases (Nickel Itch), and respiratory disorders. Nickel compounds such as Nickel Sulfide and Nickel oxides in industrial environment, if inhaled, have an association with an increased risk of lung cancer. Therefore the removal of Nickel from effluents before discharge is necessary. Removal of Nickel by low-cost biosorbents is an efficient method. This study was aimed to investigate the efficiency of activated carbon and Pinusroxburgiisaw dust for the removal of Nickel from industrial effluents using commercial Activated Carbon, and raw P.roxburgii saw dust. Batch and column adsorption experiments were conducted for the removal of Nickel. The study conducted indicates that removal of Nickel greatly dependent on pH, contact time, Nickel concentration, and adsorbent dose. Maximum removal occurred at pH 9, contact time of 600 min, and adsorbent dose of 1 g/100 mL. The highest removal was 99.62% and 92.39% (pH based), 99.76% and 99.9% (dose based), 99.80% and 100% (agitation time), 92% and 72.40% (Ni Conc. based) for P.roxburgii saw dust and activated Carbon, respectively. Similarly, the Ni removal in column adsorption was 99.77% and 99.99% (bed height based), 99.80% and 99.99% (Concentration based), 99.98%, and 99.81% (flow rate based) during column studies for Nickel using P.Roxburgiisaw dust and activated carbon, respectively. Results were compared with Freundlich isotherm model, which showed “r2” values of 0.9424 (Activated carbon) and 0.979 (P.RoxburgiiSaw Dust). While Langmuir isotherm model values were 0.9285 (Activated carbon) and 0.9999 (P.RoxburgiiSaw Dust), the experimental results were fitted to both the models. But the results were in close agreement with Langmuir isotherm model.

Keywords: nickel removal, batch, and column, activated carbon, saw dust, plant uptake

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Authors: Seyedeh Banafsheh Bagheri Marzouni, Sona Rostampour Yasouri

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Salmonella is one of the most important common pathogens between humans and animals worldwide. Globally, the prevalence of the disease in humans is due to the consumption of food contaminated with animal-derived Salmonella. These foods include eggs, red meat, chicken, and milk. Contamination of chicken and its products with Salmonella may occur at any stage of the chicken processing chain. Salmonella infection is usually not fatal. However, its occurrence is considered dangerous in some individuals, such as infants, children, the elderly, pregnant women, or individuals with weakened immune systems. If Salmonella infection enters the bloodstream, the possibility of contamination of tissues throughout the body will arise. Therefore, determining the potential risk of Salmonella at various stages is essential from the perspective of consumers and public health. The aim of this study is to isolate and identify Salmonella from chicken samples distributed in the Tehran market using the Gold standard culture method and PCR techniques based on specific genes, invA and ent. During the years 2022-2023, sampling was performed using swabs from the liver and intestinal contents of distributed chickens in the Tehran province, with a total of 120 samples taken under aseptic conditions. The samples were initially enriched in buffered peptone water (BPW) for pre-enrichment overnight. Then, the samples were incubated in selective enrichment media, including TT broth and RVS medium, at temperatures of 37°C and 42°C, respectively, for 18 to 24 hours. Organisms that grew in the liquid medium and produced turbidity were transferred to selective media (XLD and BGA) and incubated overnight at 37°C for isolation. Suspicious Salmonella colonies were selected for DNA extraction, and PCR technique was performed using specific primers that targeted the invA and ent genes in Salmonella. The results indicated that 94 samples were Salmonella using the PCR technique. Of these, 71 samples were positive based on the invA gene, and 23 samples were positive based on the ent gene. Although the culture technique is the Gold standard, PCR is a faster and more accurate method. Rapid detection through PCR can enable the identification of Salmonella contamination in food items and the implementation of necessary measures for disease control and prevention.

Keywords: culture, PCR, salmonella spp, salmonella enteritidis

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Authors: M. Zayoud, S. Oueida, S. Ionescu, P. AbiChar

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Background: Wireless sensor network is encompassed of diversified tools of information technology, which is widely applied in a range of domains, including military surveillance, weather forecasting, and earthquake forecasting. Strengthened grounds are always developed for wireless sensor networks, which usually emerges security issues during professional application. Thus, essential technological tools are necessary to be assessed for secure aggregation of data. Moreover, such practices have to be incorporated in the healthcare practices that shall be serving in the best of the mutual interest Objective: Aggregation of encrypted data has been assessed through homomorphic stream cipher to assure its effectiveness along with providing the optimum solutions to the field of healthcare. Methods: An experimental design has been incorporated, which utilized newly developed cipher along with CPU-constrained devices. Modular additions have also been employed to evaluate the nature of aggregated data. The processes of homomorphic stream cipher have been highlighted through different sensors and modular additions. Results: Homomorphic stream cipher has been recognized as simple and secure process, which has allowed efficient aggregation of encrypted data. In addition, the application has led its way to the improvisation of the healthcare practices. Statistical values can be easily computed through the aggregation on the basis of selected cipher. Sensed data in accordance with variance, mean, and standard deviation has also been computed through the selected tool. Conclusion: It can be concluded that homomorphic stream cipher can be an ideal tool for appropriate aggregation of data. Alongside, it shall also provide the best solutions to the healthcare sector.

Keywords: aggregation, cipher, homomorphic stream, encryption

Procedia PDF Downloads 241