Search results for: semiconductor production monitoring

Authors: Kaarthik K., Harshini S., Karthika M., Kripanandhini T.

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Water is an essential part of living organisms. Major water pollution is caused due to contamination of industrial wastewater in the river. The most important step in bringing wastewater contaminants down to levels that are safe for nature is wastewater treatment. The contamination of river water harms both humans who consume it and the aquatic life that lives there. We introduce a new cloud-based industrial IoT paradigm in this work for real-time control and monitoring of wastewater. The proposed system prevents prohibited entry of industrial wastewater into the plant by monitoring temperature, hydrogen power (pH), CO₂ and turbidity factors from the wastewater input that the wastewater treatment facility will process. Real-time sensor values are collected and uploaded to the cloud by the system using an IoT Wi-Fi Module. By doing so, we can prevent the contamination of industrial wastewater entering the river earlier, and the necessary actions will be taken by the users. The proposed system's results are 90% efficient, preventing water pollution due to industry and protecting human lives.

Keywords: sensors, pH, CO₂, temperature, turbidity

Procedia PDF Downloads 97

Authors: Mohammed Al Awadh

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In order for businesses to take advantage of the opportunities for expanded production and trade that have arisen as a result of globalization and increased levels of competition, productivity growth is required. The number of available sources is decreasing with each passing day, which results in an ever-increasing demand. In response to this, there will be an increased demand placed on firms to improve the efficiency with which they utilise their resources. As a scientific method, work and time research techniques have been employed in all manufacturing and service industries to raise the efficiency of use of the factors of production. These approaches focus on work and time. The goal of this research is to improve the productivity of a manufacturing industry's production system by looking at ways to measure work. The work cycles were broken down into more manageable and quantifiable components. On the observation sheet, these aspects were noted down. The operation has been properly analysed in order to identify value-added and non-value-added components, and observations have been recorded for each of the different trails.

Keywords: time study, work measurement, work study, efficiency

Procedia PDF Downloads 62

Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

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Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

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Authors: Eman M. Elmazek

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Green roofs and walls are a rising technology in the global sustainable architectural industry. The idea takes great steps towards the future of sustainable design due to its many benefits. However, there are many barriers and constraints. Economical, structural, and knowledge barriers prevent the spread of the usage of green roofs and living walls. Understanding the benefits and expanding them will spread the idea. Benefits provided by these green spots interrupt and maintain the current urban cover. Food production is one of the benefits of green roofs. It can save money and energy spent in food transportation. The goal of this paper is to put a better understanding of implementing green systems. The paper aims to identify gains versus challenges facing the technology. It surveys with case studies buildings with green roofs and walls used for food production.

Keywords: green roof, green walls, urban farming, roof herb garden

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Authors: Slim Amami

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A model is developed to prevent the risks related to climate conditions in the agricultural sector. It will determine the yearly optimum premium to be paid by a farmer in order to reach his required turnover. The model is mainly based on both climatic stability and 'soft' responses of usually grown species to average climate variations at the same place and inside a safety ball which can be determined from past meteorological data. This allows the use of linear regression expression for dependence of production result in terms of driving meteorological parameters, main ones of which are daily average sunlight, rainfall and temperature. By a simple best parameter fit from the expert table drawn with professionals, optimal representation of yearly production is deduced from records of previous years, and yearly payback is evaluated from minimum yearly produced turnover. Optimal premium is then deduced, and gives the producer a useful bound for negotiating an offer by insurance companies to effectively protect their harvest. The application to wheat production in the French Oise department illustrates the reliability of the present model with as low as 6% difference between predicted and real data. The model can be adapted to almost every agricultural field by changing state parameters and calibrating their associated coefficients.

Keywords: agriculture, database, meteorological factors, production model, optimal price

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Authors: Hang Tran, Victor Brial, Luca Sorelli, Claudiane Ouellet-Plamondon, David Conciatori, Laurent Birry

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Spend pot lining (SPL) is a by-product generated from primary aluminum production. SPL consists of two parts, the first cut is rich in carbonaceous materials, and the second cut is rich in aluminum and silicon oxides. After treating by the hydrometallurgical Low Caustic Leaching and Liming process, the refractory part of SPL becomes an inert material, called LCLL ash in this project. LCLL ash was calcined at different temperatures (800 and 1000°C) and Calcined LCLL ash ground as fines of cement and replacement a part of cement in concrete production. The effect of LCLL ash on the chemical properties, mechanical properties and fresh behavior of concrete was evaluated by isothermal calorimetry, compressive test, and slump test. These results were compared to the reference mixture.

Keywords: spend pot lining, concrete, cement, compressive strength, calorimetry

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Authors: Eduardo Kanagushiku Pereira, Frank Gregory Cavalcante da Silva, Barbara Soares Gonçalves, Ana Lúcia Bergamasco Galastri, Ronei Luciano Mamoni

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The inflammatory response initiates after the recognition of pathogens by receptors expressed by innate immune cells. Among these receptors, the NLRP3 was associated with the recognition of pathogenic fungi in experimental models. NLRP3 operates forming a multiproteic complex called inflammasome, which actives caspase-1, responsible for the production of the inflammatory cytokines IL-1beta and IL-18. In this study, we aimed to investigate the involvement of NLRP3 in the inflammatory response elicited in macrophages against Paracoccidioides brasiliensis (Pb), the etiologic agent of PCM. Macrophages were differentiated from THP-1 cells by treatment with phorbol-myristate-acetate. Following differentiation, macrophages were stimulated by Pb yeast cells for 24 hours, after previous treatment with specific NLRP3 (3,4-methylenedioxy-beta-nitrostyrene) and/or caspase-1 (VX-765) inhibitors, or specific inhibitors of pathways involved in NLRP3 activation such as: Reactive Oxigen Species (ROS) production (N-Acetyl-L-cysteine), K+ efflux (Glibenclamide) or phagossome acidification (Bafilomycin). Quantification of IL-1beta and IL-18 in supernatants was performed by ELISA. Our results showed that the production of IL-1beta and IL-18 by THP-1-derived-macrophages stimulated with Pb yeast cells was dependent on NLRP3 and caspase-1 activation, once the presence of their specific inhibitors diminished the production of these cytokines. Furthermore, we found that the major pathways involved in NLRP3 activation, after Pb recognition, were dependent on ROS production and K+ efflux. In conclusion, our results showed that NLRP3 participates in the recognition of Pb yeast cells by macrophages, leading to the activation of the NLRP3-inflammasome and production of IL-1beta and IL-18. Together, these cytokines can induce an inflammatory response against P. brasiliensis, essential for the establishment of the initial inflammatory response and for the development of the subsequent acquired immune response.

Keywords: inflammation, IL-1beta, IL-18, NLRP3, Paracoccidioidomycosis

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Authors: Majid AghaAlikhani, Mostafa Hojati, Saeid Satari-Yuzbashkandi

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This paper studies energy use patterns and relationship between energy input and yield for soybean (Glycine max (L.) Merrill) in Mazandaran province of Iran. In this study, data were collected by administering a questionnaire in face-to-face interviews. Results revealed that the highest share of energy consumption belongs to chemical fertilizers (29.29%) followed by diesel (23.42%) and electricity (22.80%). Our investigations showed that a total energy input of 23404.1 MJ.ha-1 was consumed for soybean production. The energy productivity, specific energy, and net energy values were estimated as 0.12 kg MJ-1, 8.03 MJ kg-1, and 49412.71 MJ.ha-1, respectively. The ratio of energy outputs to energy inputs was 3.11. Obtained results indicated that direct, indirect, renewable and non-renewable energies were (56.83%), (43.17%), (15.78%) and (84.22%), respectively. Three econometric models were also developed to estimate the impact of energy inputs on yield. The results of econometric models revealed that impact of chemical, fertilizer, and water on yield were significant at 1% probability level. Also, direct and non-renewable energies were found to be rather high. Cost analysis revealed that total cost of soybean production per ha was around 518.43$. Accordingly, the benefit-cost ratio was estimated as 2.58. The energy use efficiency in soybean production was found as 3.11. This reveals that the inputs used in soybean production are used efficiently. However, due to higher rate of nitrogen fertilizer consumption, sustainable agriculture should be extended and extension staff could be proposed substitution of chemical fertilizer by biological fertilizer or green manure.

Keywords: Cobbe Douglas function, economical analysis, energy efficiency, energy use patterns, soybean

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Authors: Chairul Fajar, Muhammad Nur Hidayat, Muksalmina

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The issue of Over Dimension Over Loading (ODOL) in Indonesia remains a significant challenge, causing traffic accidents, disrupting traffic flow, accelerating road damage, and potentially leading to bridge collapses. Klaten Regency, located on the slopes of Mount Merapi along the Woro River in Kemalang District, has potential Class C excavation materials such as sand and stone. Data from the Klaten Regency Transportation Department indicates that ODOL violations account for 72%, while non-violating vehicles make up only 28%. ODOL involves modifying factory-standard vehicles beyond the limits specified in the Type Test Registration Certificate (SRUT) to save costs and travel time. This study aims to develop a prototype ‘Sabrang’ monitoring system based on Arduino Mega to control and monitor ODOL freight transportation in the mining of Class C excavation materials in Klaten Regency. The prototype is designed to automatically measure the dimensions and weight of objects using a microcontroller. The data analysis techniques used in this study include the Normality Test and Paired T-Test, comparing sensor measurement results on scaled objects. The study results indicate differences in measurement validation under room temperature and ambient temperature conditions. Measurements at room temperature showed that the majority of H0 was accepted, meaning there was no significant difference in measurements when the prototype tool was used. Conversely, measurements at ambient temperature showed that the majority of H0 was rejected, indicating a significant difference in measurements when the prototype tool was used. In conclusion, the ‘Sabrang’ monitoring system prototype is effective for controlling ODOL, although measurement results are influenced by temperature conditions. This study is expected to assist in the monitoring and control of ODOL, thereby enhancing traffic safety and road infrastructure.

Keywords: over dimension over loading, prototype, microcontroller, Arduino, normality test, paired t-test

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Authors: Haythem Barrak, Gaetan Laroche, Adel M’nif, Ahmed Hichem Hamzaoui

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The use of semiconductor oxides, as chemical or biological, requires their functionalization with appropriate dependent molecules of the substance to be detected. generally, the support materials used are TiO2 and SiO2. In the present work, we used zinc oxide (ZnO) known for its interesting physical properties. The synthesis of nano scale ZnO was performed by co-precipitation at low temperature (60 ° C).To our knowledge, the obtaining of this material at this temperature was carried out for the first time. This shows the low cost of this operation. On the other hand, the surface functionalization of ZnO was performed with (3-aminopropyl) triethoxysilane (APTES) by using a specific method using ethanol for the first time. In addition, the duration of this stage is very low compared to literature. The samples obtained were analyzed by XRD, TEM, DLS, FTIR, and TGA shows that XPS that the operation of grafting of APTES on our support was carried out with success.

Keywords: functionalization, nanoparticle, ZnO, APTES, caractérisation

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Authors: Achim Kampker, Christoph Deutskens, Heiner Hans Heimes, Mathias Ordung, Felix Optehostert

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In the past years electric mobility became part of a public discussion. The trend to fully electrified vehicles instead of vehicles fueled with fossil energy has notably gained momentum. Today nearly every big car manufacturer produces and sells fully electrified vehicles, but electrified vehicles are still not as competitive as conventional powered vehicles. As the traction battery states the largest cost driver, lowering its price is a crucial objective. In addition to improvements in product and production processes a non-negligible, but widely underestimated cost driver of production can be found in logistics, since the production technology is not continuous yet and neither are the logistics systems. This paper presents an approach to evaluate cost factors on different designs of load carrier systems. Due to numerous interdependencies, the combination of costs factors for a particular scenario is not transparent. This is effecting actions for cost reduction negatively, but still cost reduction is one of the major goals for simultaneous engineering processes. Therefore a concurrent and phase appropriate cost valuation method is necessary to serve cost transparency. In this paper the four phases of this cost valuation method are defined and explained, which based upon a new approach integrating the logistics development process in to the integrated product and process development.

Keywords: research and development, technology and innovation, lithium-ion-battery production, load carrier development process, cost valuation method

Procedia PDF Downloads 578

Authors: Cecilia Elisabeth Fåhraeus

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In 2016, this author conducted a study on agricultural livelihoods in urban and peri-urban low-income settings in Lusaka, Zambia. The overarching aim was to determine the impact of physical space on agricultural activities, with a particular emphasis on geographical distinctions between urban and peri-urban environments. Agricultural activities among the areas’ residents were mapped through questionnaires, interviews and observations, and included variables such as type of activity and product; degree of marketization; inputs; location of production, storage and vending; labour distribution; production constraints, and associated mobility patterns, among others. The study confirmed that spatial idiosyncrasies of urban and peri-urban environments both enabled and constrained agricultural activity, but not always as anticipated. There were also cross-cutting issues on which physical space appeared to have a limited impact.

Keywords: agricultural production systems, geography, low-income settlements, Lusaka, peri-urban, urban

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Authors: Sonia Vanessa Campos Moreira

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The aim of this research is the production and mechanical properties of Alkali-Activated Inorganic Binders (AAIB) made from The Basic Oxygen Furnace Slag (BOF Slag) and Thin Film Transistor Liquid Crystal Display (TFT-LCD), glass powder (waste and industrial by-products). Many factors have an influence on the production of AAIB like the glass powder finesses, the alkaline equivalent content (AE %), water binder ratios (w/b ratios) and the differences curing process. The findings show different behavior in the AAIB related to the factors mentioned, the best results are given with a glass powder fineness of 4,500 cm²/g, w/b=0.30, a curing temperature of 70 ℃, curing duration of 4 days and an aging duration of 14 days results in the highest compressive strength of 18.51 MPa.

Keywords: alkaline activators, BOF slag, glass powder fineness, TFT-LCD, w/b ratios

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Authors: F. M. Pisano, M. Ciminello

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Aerospace, mechanical, and civil engineering infrastructures can take advantages from damage detection and identification strategies in terms of maintenance cost reduction and operational life improvements, as well for safety scopes. The challenge is to detect so called “barely visible impact damage” (BVID), due to low/medium energy impacts, that can progressively compromise the structure integrity. The occurrence of any local change in material properties, that can degrade the structure performance, is to be monitored using so called Structural Health Monitoring (SHM) systems, in charge of comparing the structure states before and after damage occurs. SHM seeks for any "anomalous" response collected by means of sensor networks and then analyzed using appropriate algorithms. Independently of the specific analysis approach adopted for structural damage detection and localization, textual reports, tables and graphs describing possible outlier coordinates and damage severity are usually provided as artifacts to be elaborated for information extraction about the current health conditions of the structure under investigation. Visual Analytics can support the processing of monitored measurements offering data navigation and exploration tools leveraging the native human capabilities of understanding images faster than texts and tables. Herein, a SHM system enrichment by integration of a Visual Analytics component is investigated. Analytical dashboards have been created by combining worksheets, so that a useful Visual Analytics tool is provided to structural analysts for exploring the structure health conditions examined by a Principal Component Analysis based algorithm.

Keywords: interactive dashboards, optical fibers, structural health monitoring, visual analytics

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Authors: Meha Alouini, Wissem Mnif, Yasmine Souissi

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This work will be conducted within the framework of the environmental sustainable development. It involves waste recovering into biodiesel fuel. Low cost feedstocks such as waste of frying oil and animal fats have been utilized to replace refined vegetable oil for biodiesel production. Biodiesel which refers to fatty acid methyl esters (FAME) was carried out by both chemical and enzymatic reaction of transesterification. In order to compare the two studied reactions the obtained biodiesel was characterized by determining its esters content and its fuel properties according to the European standard EN 14214. It was noted that the chemical method gave the product with the best physical property. But the biological one was found more effective for obtaining important ester content. Thus it would be interesting to optimize the enzymatic pathway of production of biodiesel to obtain a better property of biodiesel.

Keywords: biodiesel, fatty acid methyl esters, transesterification, waste frying oil, waste beef fat

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Authors: Fidiana Suwitho

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Research and community service is one of important lecturer assignment in Indonesia. This article was made to meet those needs by assisting home industry entrepreneurs of various chips in Banyuwangi. Community service in this scheme are intended to increase the revenue of craftsmen of chips by improving value added of chips through food engineering technology. Ibu Anisa has produced various kinds of chips that are breadfruit chips, banana chips, yam chips, and cassava chips. In business development, Ibu Anisa facing various problems both in terms of production and management aspects. The process of production and management and marketing are still conventional so that increased demand cannot be offset by production capacity. A researcher team of STIESIA has assist partners in the processing stage, from manually to the technologically. This activity has a positive impact to However, this process has not been reached on sustainable marketing aspect, which is where the partners are still difficult to reach a wider market because of limited access.

Keywords: food engineering technology, value added of chips, community service

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Authors: Andrii Natochii

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The UA9 collaboration in the last two years has installed two different types of detectors to investigate the channeling effect in the bent silicon crystals with high-energy particles beam on the CERN accelerator facilities: Cherenkov detector CpFM and silicon pixel detector Timepix. In the current work, we describe the main performances of the Timepix detector operation at the SPS and H8 extracted beamline at CERN. We are presenting some detector calibration results and tuning. Our research topics also cover a cluster analysis algorithm for the particle hits reconstruction. We describe the optimal acquisition setup for the Timepix device and the edges of its functionality for the high energy and flux beam monitoring. The measurements of the crystal parameters are very important for the future bent crystal applications and needs a track reconstruction apparatus. Thus, it was decided to construct a short range (1.2 m long) particle telescope based on the Timepix sensors and test it at H8 SPS extraction beamline. The obtained results will be shown as well.

Keywords: beam monitoring, channeling, particle tracking, Timepix detector

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Authors: Pranav Gulati, Isha Sharma

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Hypertension and hypotension are known to have repercussions on the health of an individual, with hypertension contributing to an increased probability of risk to cardiovascular diseases and hypotension resulting in syncope. This prompts the development of a non-invasive, non-intrusive, continuous and cuff-less blood pressure monitoring system to detect blood pressure variations and to identify individuals with acute and chronic heart ailments, but due to the unavailability of such devices for practical daily use, it becomes difficult to screen and subsequently regulate blood pressure. The complexities which hamper the steady monitoring of blood pressure comprises of the variations in physical characteristics from individual to individual and the postural differences at the site of monitoring. We propose to develop a continuous, comprehensive cardio-analysis tool, based on reflective photoplethysmography (PPG). The proposed device, in the form of an eyewear captures the PPG signal and estimates the systolic and diastolic blood pressure using a sensor positioned near the temporal artery. This system relies on regression models which are based on extraction of key points from a pair of PPG wavelets. The proposed system provides an edge over the existing wearables considering that it allows for uniform contact and pressure with the temporal site, in addition to minimal disturbance by movement. Additionally, the feature extraction algorithms enhance the integrity and quality of the extracted features by reducing unreliable data sets. We tested the system with 12 subjects of which 6 served as the training dataset. For this, we measured the blood pressure using a cuff based BP monitor (Omron HEM-8712) and at the same time recorded the PPG signal from our cardio-analysis tool. The complete test was conducted by using the cuff based blood pressure monitor on the left arm while the PPG signal was acquired from the temporal site on the left side of the head. This acquisition served as the training input for the regression model on the selected features. The other 6 subjects were used to validate the model by conducting the same test on them. Results show that the developed prototype can robustly acquire the PPG signal and can therefore be used to reliably predict blood pressure levels.

Keywords: blood pressure, photoplethysmograph, eyewear, physiological monitoring

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Authors: Mpaphi Major

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Soil erosion is becoming an important aspect of land degradation. Therefore it is of great consideration to note any factor that may escalate the rate of soil erosion in our arable land. There exist 3 main driving forces in soil erosion which are rainfall, wind and land use of which in this project only rainfall and land use will be looked at. With the increase in world population at an alarming rate, the demand for food production is expected to increase which will in turn lead to more land being converted from forests to agricultural use of which very few of it are now fertile. In our country Botswana, the rate of crop production is decreasing due to the wearing away of the fertile top soil and poor arable land management. As a result, some studies on the rate of soil loss and farm management practices should be conducted so that best soil and water conservation practices should be employed and hence reduce the risk of soil loss and increase the rate of crop production and yield. The Soil loss estimation model for Southern Africa (SLEMSA) will be used to estimate the rate of soil loss in some selected arable farms within the Palapye watershed and some field observations will be made to determine the management practices used and their impact on the arable land. Upon observations it have been found that many arable fields have been exposed to soil erosion, of which the affected parts are no longer suitable for any crop production unless the land areas are modified. Improper land practices such as ploughing along the slope and land cultivation practices were observed. As a result farmers need to be educated on best conservation practices that can be used to manage their arable land hence reduced risk of soil erosion and improved crop production.

Keywords: soil and water conservation, soil erosion, SLEMSA, land degradation

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Authors: Aminah Muchdar

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Efforts to increase soybean production have been pursued for years in Indonesia through the process of intensification and extensification. Increased production through intensification of increasing grain yield per hectare, among others includes the improvement of cultivation system such as the use of cultivars that have superior resistance to drought. Increased soybean production has been through the expansion of planting areas utilizing available idle dry land. However, one of the constraints faced in dryland agriculture was the limited water supply due to low intensity of rainfall that leads to low crop production. In order to ensure that soybeans are cultivated on dry land remains capable of high production, it is necessary to physiologically engineer the soybean with open stomata. The study was conducted in the greenhouse of Balai Penelitian Tanaman Serealia (BALITSEREAL) Maros, Sulawesi, Indonesia with a completely randomized block design h factorial pattern. The first factor was the water stress stadia while the second was the amount of sorbitol osmolit concentration application. Results indicated that there was an interaction between the plant height growth and number of leaves between the water clamping time and concentration of the osmolit sorbitol. The vegetative stage especially during flowering and pod formation was inhibited when the water was clamped, but by spraying osmolit sorbitol, soybean growth in terms of its height and number of leaves was enhanced. This study implies that the application of osmolit sorbitol may enhance the drought resistance of soybean growth. Future research suggested that more work should be done on the application of osmolit sorbital to other agriculture crops to increase their drought resistance in the drylands.

Keywords: DROUGHT, engineered physiology, osmolit sorbitol, soybean

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Authors: Ali Asheibi

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The rapid increase in the size of databases required to store power quality monitoring data has demanded new techniques for analysing and understanding the data. One suggested technique to assist in analysis is data mining. Preparing raw data to be ready for data mining exploration take up most of the effort and time spent in the whole data mining process. Clustering is an important technique in data mining and machine learning in which underlying and meaningful groups of data are discovered. Large amounts of harmonic data have been collected from an actual harmonic monitoring system in a distribution system in Australia for three years. This amount of acquired data makes it difficult to identify operational events that significantly impact the harmonics generated on the system. In this paper, harmonic data preparation processes to better understanding of the data have been presented. Underlying classes in this data has then been identified using clustering technique based on the Minimum Message Length (MML) method. The underlying operational information contained within the clusters can be rapidly visualised by the engineers. The C5.0 algorithm was used for classification and interpretation of the generated clusters.

Keywords: data mining, harmonic data, clustering, classification

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Authors: B. M. Patil

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Calcium Zirconate (CaZrO3) has high protonic conductivities at elevated temperature in water or hydrogen atmosphere. Undoped calcium zirconate acts as a p-type semiconductor in air. In this paper, we reported synthesis of CaZrO3 nanoparticles via modified molecular precursor method. The precursor calcium zirconium oxalate (CZO) was synthesized by exchange reaction between freshly generated aqueous solution of sodium zirconyl oxalate and calcium acetate at room temperature. The controlled pyrolysis of CZO in air at 700°C for one hour resulted in the formation nanocrystalline CaZrO3 powder. CaZrO3 obtained by the present method was characterized by Simultaneous thermogravimetry and differential thermogravimetry (TG-DTA), X-ray diffraction (XRD), infra-red spectroscopy and transmission electron microscopy (TEM). The pellets of synthesized CaZrO3 fabricated, sintered at 1000°C for 5 hr and tested as sensors for NO2 and NH3 gases.

Keywords: CaZrO3, CZO, NO2, NH3

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Authors: Namhun Lee, Seong Jin Kim

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The construction industry represents one of the largest industries in the United States, yet it continues to face several occupational health and safety challenges. Many workers on construction sites are suffering from extended exposure to stressful situations such as poor and hazardous work environments and task complexity. Stress can be commonly defined as a feeling of emotional or physical tension, which can easily impact construction safety and result in a higher rate of job-related injuries in the construction industry. Physiological signals transmitted from wearable biosensors can be used to detect excessive stress. Therefore, workers’ stress should be detected and mitigated to prevent any type of serious incident or accident proactively. By doing this, construction productivity, as well as job satisfaction, would also be improved in the construction industry. To establish a foundation in this field of research, a conceptual framework for using wearable technology for construction safety has been developed for continuous and automatic monitoring of worker’s stress. The conceptual framework will serve as a foothold in future studies on the application of wearable technology for construction safety.

Keywords: construction safety, occupational stress, stress monitoring, wearable biosensors

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Authors: Esmael Makarian, Ayub Elyasi, Fatemeh Saberi, Olusegun Stanley Tomomewo

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Rock mechanical investigation is one of the most crucial activities in underground operations, especially in surveys related to hydrocarbon exploration and production, geothermal reservoirs, energy storage, mining, and geotechnics. There is a wide range of traditional methods for driving, collecting, and analyzing rock mechanics data. However, these approaches may not be suitable or work perfectly in some situations, such as fractured zones. Cutting-edge technologies have been provided to solve and optimize the mentioned issues. Internet of Things (IoT), Edge, and Cloud Computing technologies (ECt & CCt, respectively) are among the most widely used and new artificial intelligence methods employed for geomechanical studies. IoT devices act as sensors and cameras for real-time monitoring and mechanical-geological data collection of rocks, such as temperature, movement, pressure, or stress levels. Structural integrity, especially for cap rocks within hydrocarbon systems, and rock mass behavior assessment, to further activities such as enhanced oil recovery (EOR) and underground gas storage (UGS), or to improve safety risk management (SRM) and potential hazards identification (P.H.I), are other benefits from IoT technologies. EC techniques can process, aggregate, and analyze data immediately collected by IoT on a real-time scale, providing detailed insights into the behavior of rocks in various situations (e.g., stress, temperature, and pressure), establishing patterns quickly, and detecting trends. Therefore, this state-of-the-art and useful technology can adopt autonomous systems in rock mechanical surveys, such as drilling and production (in hydrocarbon wells) or excavation (in mining and geotechnics industries). Besides, ECt allows all rock-related operations to be controlled remotely and enables operators to apply changes or make adjustments. It must be mentioned that this feature is very important in environmental goals. More often than not, rock mechanical studies consist of different data, such as laboratory tests, field operations, and indirect information like seismic or well-logging data. CCt provides a useful platform for storing and managing a great deal of volume and different information, which can be very useful in fractured zones. Additionally, CCt supplies powerful tools for predicting, modeling, and simulating rock mechanical information, especially in fractured zones within vast areas. Also, it is a suitable source for sharing extensive information on rock mechanics, such as the direction and size of fractures in a large oil field or mine. The comprehensive review findings demonstrate that digital transformation through integrated IoT, Edge, and Cloud solutions is revolutionizing traditional rock mechanical investigation. These advanced technologies have empowered real-time monitoring, predictive analysis, and data-driven decision-making, culminating in noteworthy enhancements in safety, efficiency, and sustainability. Therefore, by employing IoT, CCt, and ECt, underground operations have experienced a significant boost, allowing for timely and informed actions using real-time data insights. The successful implementation of IoT, CCt, and ECt has led to optimized and safer operations, optimized processes, and environmentally conscious approaches in underground geological endeavors.

Keywords: rock mechanical studies, internet of things, edge computing, cloud computing, underground surveys, geological operations

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Authors: Zain Ul Hassan, Muhammad Zain Ul Abadin, Muhammad Zubair Khan

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Unmanned aerial vehicles (UAVs) have now become of predominant importance for various operations, and an immense amount of work is going on in this specific category. The structural stability and life of these UAVs is key factor that should be considered while deploying them to different intelligent operations as their failure leads to loss of sensitive real-time data and cost. This paper presents an applied research on the development of a structural health monitoring system for a UAV designed and fabricated by deploying modular approach. Firstly, a modular UAV has been designed which allows to dismantle and to reassemble the components of the UAV without effecting the whole assembly of UAV. This novel approach makes the vehicle very sustainable and decreases its maintenance cost to a significant value by making possible to replace only the part leading to failure. Then the SHM for the designed architecture of the UAV had been specified as a combination of wings integrated with strain gauges, on-board data logger, bridge circuitry and the ground station. For the research purpose sensors have only been attached to the wings being the most load bearing part and as per analysis was done on ANSYS. On the basis of analysis of the load time spectrum obtained by the data logger during flight, fatigue life of the respective component has been predicted using fracture mechanics techniques of Rain Flow Method and Miner’s Rule. Thus allowing us to monitor the health of a specified component time to time aiding to avoid any failure.

Keywords: fracture mechanics, rain flow method, structural health monitoring system, unmanned aerial vehicle

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Authors: P. Baltrenas, D. Paliulis, V. Kolodynskij, D. Urbanas

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Bioreactor; special device, which is used for biogas production from various organic material under anaerobic conditions. In this research, a batch bioreactor with a mechanical mixer was used for biogas production from sewage sludge and chicken manure bioloadings. The process of anaerobic digestion was mesophilic (35 °C). Produced biogas was stoted in a gasholder and the concentration of its components was measured with INCA 4000 biogas analyser. Also, a specific additive (pine wood biochar) was applied to prepare bioloadings. The application of wood biochar in bioloading increases the CH₄ concentration in the produced gas by 6-7%. The highest concentrations of CH₄ were found in biogas produced during the decomposition of sewage sludge bioloadings. The maximum CH₄ reached 77.4%. Studies have shown that the application of biochar in bioloadings also reduces average CO₂ and H₂S concentrations in biogas.

Keywords: biochar, biogas, bioreactor, sewage sludge

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Authors: Peter Burggräf, Matthias Dannapfel, Hanno Voet, Patrick-Benjamin Bök, Jérôme Uelpenich, Julian Hoppe

Abstract:

The increasing digitalization of value chains can help companies to handle rising complexity in their processes and thereby reduce the steadily increasing planning and control effort in order to raise performance limits. Due to technological advances, companies face the challenge of smart value chains for the purpose of improvements in productivity, handling the increasing time and cost pressure and the need of individualized production. Therefore, companies need to ensure quick and flexible decisions to create self-optimizing processes and, consequently, to make their production more efficient. Lean production, as the most commonly used paradigm for complexity reduction, reaches its limits when it comes to variant flexible production and constantly changing market and environmental conditions. To lift performance limits, which are inbuilt in current value chains, new methods and tools must be applied. Digitalization provides the potential to derive these new methods and tools. However, companies lack the experience to harmonize different digital technologies. There is no practicable framework, which instructs the transformation of current value chains into digital pervasive value chains. Current research shows that a connection between lean production and digitalization exists. This link is based on factors such as people, technology and organization. In this paper, the introduced method for the determination of digitally pervasive value chains takes the factors people, technology and organization into account and extends existing approaches by a new dimension. It is the first systematic approach for the digital transformation of lean production and consists of four steps: The first step of ‘target definition’ describes the target situation and defines the depth of the analysis with regards to the inspection area and the level of detail. The second step of ‘analysis of the value chain’ verifies the lean-ability of processes and lies in a special focus on the integration capacity of digital technologies in order to raise the limits of lean production. Furthermore, the ‘digital evaluation process’ ensures the usefulness of digital adaptions regarding their practicability and their integrability into the existing production system. Finally, the method defines actions to be performed based on the evaluation process and in accordance with the target situation. As a result, the validation and optimization of the proposed method in a German company from the electronics industry shows that the digital transformation of current value chains based on lean production achieves a raise of their inbuilt performance limits.

Keywords: digitalization, digital transformation, Industrie 4.0, lean production, value chain

Procedia PDF Downloads 300

Authors: V. V. Lakshmi, Y. V. S. Annapurna

Abstract:

Urinary tract infection (UTI) is one of the most common infectious diseases seen in the community. Susceptible individuals experience multiple episodes, and progress to acute pyelonephritis or uro-sepsis or develop asymptomatic bacteriuria (ABU). Ability to cause extraintestinal infections depends on several virulence factors required for survival at extraintestinal sites. Presence of virulence phenotypes enhances the pathogenicity of these otherwise commensal organisms and thus augments its ability to cause extraintestinal infections, the most frequent in urinary tract infections(UTI). The present study focuses on detection of the virulence characters exhibited by the uropathogenic organism and most common factors exhibited in the local pathogens. A total of 700 isolates of E.coli and Klebsiella spp were included in the study. These were isolated from patients from local hospitals reported to be suffering with UTI over a period of three years. Isolation and identification was done based on Gram character and IMVIC reactions. Antibiotic sensitivity profile was carried out by disc diffusion method and multi drug resistant strains with MAR index of 0.7 were further selected.. Virulence features examined included their ability to produce exopolysaccharides, protease- gelatinase production, hemolysin production, haemagglutination and hydrophobicity test. Exopolysaccharide production was most predominant virulence feature among the isolates when checked by congo red method. The biofilms production examined by microtitre plates using ELISA reader confirmed that this is the major factor contributing to virulencity of the pathogens followed by hemolysin production

Keywords: Escherichia coli, Klebsiella sp, Uropathogens, Virulence features.

Procedia PDF Downloads 412

Authors: Mustafa Ümi̇t Ünal, Nafi̇z Çeli̇ktaş, Aysun Şener, Sara Betül Dolgun, Duygu Keser

Abstract:

The aim of this study was to compare acid and base pretreatment of switchgrass for bioethanol production. Switchgrass was pretreated with sulfuric acid and sodium hydroxide at 0.5, 1.0 and 1.5% (v/v) at 120, 140, 180 °C for 10, 60 and 90. Optimization of enzymatic hydrolysis of the pretreated switchgrass samples were carried out using three different enzyme mixtures (22.5 mg cellulase and 75 mg cellobiase /g biomass; 45 mg cellulase and 150 mg cellobiase /g biomass; 90 mg cellulase and 300 mg cellobiase /g biomass). Samples were removed at 24-h interval for fermentable sugar analyses with HPLC. The results showed that use of 90 mg cellulase and 300 mg cellobiase/g biomass resulted in the highest fermentable sugar formation. Furthermore, the highest fermentable sugar yield was obtained by pretreatment at 120 °C for 10 min using 1.0 % sodium hydroxide.

Keywords: switchgrass, acid pretreatment, enzymatic hydrolysis, base pretreatment, ethanol production

Procedia PDF Downloads 512

Authors: Obiora E. Anisiji, Jeremiah L. Chukwuneke, Chinonso H. Achebe, Paul C. Okolie

Abstract:

This work developed a mathematical model of a biogas plant from a mechanistic point of view, for urban area clean energy requirement. It aimed at integrating thermodynamics; which deals with the direction in which a process occurs and Biochemical kinetics; which gives the understanding of the rates of biochemical reaction. The mathematical formulation of the proposed gas plant follows the fundamental principles of thermodynamics, and further analysis were accomplished to develop an algorithm for evaluating the plant performance preferably in terms of daily production capacity. In addition, the capacity of the plant is equally estimated for a given cycle of operation and presented in time histories. A nominal 1500m3 biogas plant was studied characteristically and its performance efficiency evaluated. It was observed that the rate of biogas production is essentially a function of enthalpy ratio, the reactor temperature, pH, substrate concentration, rate of degradation of the biomass, and the accumulation of matter in the system due to bacteria growth. The results of this study conform to a very large extent with reported empirical data of some existing plant and further model validations were conducted in line with classical records found in literature.

Keywords: anaerobic digestion, biogas plant, biogas production, bio-reactor, energy, fermentation, rate of production, temperature, therm

Procedia PDF Downloads 424