Search results for: NMR techniques

Authors: Neha Parekh, Divya Ladha, Poonam Wadhwani, Nisha Shah

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Nano scaled materials have attracted tremendous interest as corrosion inhibitor due to their high surface area on the metal surfaces. It is well known that the zinc oxide nanoparticles have higher reactivity towards aqueous acidic solution. This work presents a new method to incorporate zinc oxide nanoparticles with white sesame seeds extract (nano-green inhibitor) for corrosion protection of zinc in acidic medium. The morphology of the zinc oxide nanoparticles was investigated by TEM and DLS. The corrosion inhibition efficiency of the green inhibitor and nano-green inhibitor was determined by Gravimetric and electrochemical impedance spectroscopy (EIS) methods. Gravimetric measurements suggested that nano-green inhibitor is more effective than green inhibitor. Furthermore, with the increasing temperature, inhibition efficiency increases for both the inhibitors. In addition, it was established the Temkin adsorption isotherm fits well with the experimental data for both the inhibitors. The effect of temperature and Temkin adsorption isotherm revealed Chemisorption mechanism occurring in the system. The activation energy (Ea) and other thermodynamic parameters for inhibition process were calculated. The data of EIS showed that the charge transfer controls the corrosion process. The surface morphology of zinc metal (specimen) in absence and presence of green inhibitor and nano-green inhibitor were performed using Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM) techniques. The outcomes indicated a formation of a protective layer over zinc metal (specimen).

Keywords: corrosion, green inhibitor, nanoparticles, zinc

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Authors: Davoud Mokhtari

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One of the factors behind the increasing development of geotourism is the identification and introduction of new facets of amazing geosphere phenomena. The Misho-Dagh Mountains in northwestern Iran are one of the rich geodiversity areas. The presence of some rare and interesting phenomena in this mountain has increased the potential of this region for geotourism development. Active pressure ridges, arcuate valleys, sag Ponds, granite complexes, glacial rock springs, and displaced habitats due to tectonic activity are among the most significant phenomena in the study area. The research is based on the literature review of geotourism and personal research experiences on geomorphosites of the northwest of Iran. Monitoring the changes of geomorphosites and evaluation of corresponding changes in the geomorphosite̕s location and their capabilities using satellite images and fieldwork is done. In this study, six geomorphosite were introduced, each with special characteristics and with one of the geotourism topics. Selection of this location of northwestern Iran is due to the focus of author of this paper is on this part of the country, and there is no doubt that such places, even with higher values of geotourism, there are in various parts of Iran and the world that could be interested in this field of emerging science. From in situ observations taken in the field and estimating a level of impact, employing assessment techniques, and then finally extrapolating the resultant factors across all case studies, we have been able to generate a geotourism map for future planning purposes. Accordingly, it should be noted that we are not just part of the landscape of the geomorphosites. The geomorphosites are also part of our landscape. It is hoped that the findings of this paper can open a new world of geotourism that, if is not associated with geomorphological processes, will be very short.

Keywords: geotourism, sources of geotourism, geotouristic areas, mishow_dagh, northwest of Iran

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Authors: Nomthandazo Precious Sibiya, Thembisile Patience Mahlangu, Sudesh Rathilal

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Heavy metal removal is critical in the wastewater treatment process due to its numerous harmful effects on human and aquatic life. There are several chemical and physical techniques for removing heavy metals from wastewater, including ion exchange, reverse osmosis, adsorption, electrodialysis, and ultrafiltration. However, adsorption technology has captivated researchers for years due to its low cost, high efficiency, and compatible with the environment. In this study, the adsorption effectiveness of three modified agro-waste materials was explored for the removal of lead from synthetic wastewater: banana peels (BP), orange peels (OP), and sugarcane bagasse (SB). The magnetite (Fe₃O₄) is incorporated with BP, OP, and SB at a ratio of 1:1 to create magnetic biosorbents. Characterization of biosorbents was carried out using and scanning electron microscopy (SEM) combined with energy-dispersive X-ray (EDX) to investigate surface morphology and elemental compositions, respectively. A series of batch experiments were carried out to investigate the effects of adsorbent mass, agitation time, and initial pH concentration on adsorption behaviour, as well as adsorption isotherms and kinetics. The removal efficiency of lead by the modified agro-waste materials proved to be superior to that of non-modified agro-waste materials. The proof of concept was achieved, and agro-waste materials can be paired with adsorption technology to effectively remove lead from aqueous media. The use of agricultural waste as biosorbents will aid in waste reduction and management.

Keywords: adsorption, isotherms, kinetics, agro waste, nanoparticles, batch

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Authors: Oxana Vasilyeva

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This paper draws on research in progress focusing on independent art in the Russian Federation. I am using the concept of independent art to mean art free from state control and established restrictive narratives. The Russian state pursues its interests by supporting or forbidding certain forms of art, and art that promotes values in opposition to the official political course is often forbidden. Arguments presented below draw from fieldwork carried out in Russian cities of Moscow and Saint Petersburg in June – August 2019, which included in-depth interviews with artists. This research explores socially engaged artistic works and their effect on socio-political state of affairs. It argues that artistic works entering public places have a potential to challenge autocratic system and inspire civil society to be critically engaged and to be capable to resist state propaganda. I am focusing on those artists who have a critical stance towards the current Russian political regime and analyzing their works in terms of transgression. By using the framework of transgression I aim to demonstrate how artists step across existing norms with their art influencing political and social order. To show the connection between the factors mentioned above, I will turn to two examples of transgressive aesthetics; one is individual and another is collective. The first example is Konstantin Benkovich, an artist who makes his works out of steel rebar, which is considered to be a symbol of the lack of freedom, as it is usually encountered in prison settings. The second example is a collective art practice called Monstration. It combines techniques of a demonstration and a carnival atmosphere. In 2019 Monstration was held in 30 Russian cities, despite the dissatisfaction of the authorities.

Keywords: art, culture, resistance, Russia

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Authors: Rana Alaa El-Deen Ahmed, M. Elemam Shehab, Shereen Morsy, Nermeen Mekawie

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With the growing popularity and acceptance of e-commerce platforms, users face an ever increasing burden in actually choosing the right product from the large number of online offers. Thus, techniques for personalization and shopping guides are needed by users. For a pleasant and successful shopping experience, users need to know easily which products to buy with high confidence. Since selling a wide variety of products has become easier due to the popularity of online stores, online retailers are able to sell more products than a physical store. The disadvantage is that the customers might not find products they need. In this research the customer will be able to find the products he is searching for, because recommender systems are used in some ecommerce web sites. Recommender system learns from the information about customers and products and provides appropriate personalized recommendations to customers to find the needed product. In this paper eleven classification algorithms are comparatively tested to find the best classifier fit for consumer online shopping attitudes and behavior in the experimented dataset. The WEKA knowledge analysis tool, which is an open source data mining workbench software used in comparing conventional classifiers to get the best classifier was used in this research. In this research by using the data mining tool (WEKA) with the experimented classifiers the results show that decision table and filtered classifier gives the highest accuracy and the lowest accuracy classification via clustering and simple cart.

Keywords: classification, data mining, machine learning, online shopping, WEKA

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Authors: Rachida Houssa, Hassan Rhinane, Fadoumo Ali Malouw, Amina Oulmaalem

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Since the early 70s, the Moroccan Atlantic sea was subjected to the pressure of the bottom trawling, one of the most destructive techniques seabed that cause havoc on fishing catch, nonselective, and responsible for more than half of all releases of fish around the world. The present paper aims to map and assess the impact of the activity of the bottom trawling of the Moroccan Atlantic coast. For this purpose, a dataset of thirty years, between 1962 and 1999, from foreign fishing vessels using bottom trawling, has been used and integrated in a GIS. To estimate the extent and the importance of the geographical distribution of the trawling effort, the Moroccan Atlantic area was divided into a grid of cells of 25 km2 (5x5 km). This grid was joined to the effort trawling data, creating a new entity with a table containing spatial overlay grid with the polygon of swept surfaces. This mapping model allowed to quantify the used fishing effort versus time and to generate the trace indicative of trawling efforts on the seabed. Indeed, for a given year, a grid cell may have a swept area equal to 0 (never been touched by the trawl) or 25 km2 (the trawled area is similar to the cell size) or may be 100 km2 indicating that for this year, the scanned surface is four times the cell area. The results show that the total cumulative sum of trawled area is approximately 28,738,326 km2, scattered throughout the Atlantic coast. 95% of the overall trawling effort is located in the southern zone, between 29°N and 20°30'N. Nearly 5% of the trawling effort is located in the northern coastal region, north of 33°N. The center area between 33°N and 29°N is the least swept by Russian commercial vessels because in this region the majority of the area is rocky, and non trawlable.

Keywords: GIS, Moroccan Atlantic Ocean, seabed, trawling

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Authors: Virender Singh, Mathew Rees, Simon Hampton, Sivaram Annadurai

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Plant identification is a challenging task that aims to identify the family, genus, and species according to plant morphological features. Automated deep learning-based computer vision algorithms are widely used for identifying plants and can help users narrow down the possibilities. However, numerous morphological similarities between and within species render correct classification difficult. In this paper, we tested custom convolution neural network (CNN) and vision transformer (ViT) based models using the PyTorch framework to classify plants. We used a large dataset of 88,000 provided by the Royal Horticultural Society (RHS) and a smaller dataset of 16,000 images from the PlantClef 2015 dataset for classifying plants at genus and species levels, respectively. Our results show that for classifying plants at the genus level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420 and other state-of-the-art CNN-based models suggested in previous studies on a similar dataset. ViT model achieved top accuracy of 83.3% for classifying plants at the genus level. For classifying plants at the species level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420, with a top accuracy of 92.5%. We show that the correct set of augmentation techniques plays an important role in classification success. In conclusion, these results could help end users, professionals and the general public alike in identifying plants quicker and with improved accuracy.

Keywords: plant identification, CNN, image processing, vision transformer, classification

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Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifying the RBCs as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-alaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively.

Keywords: K-nearest neighbors algorithm, radial basis function neural network, red blood cells, support vector machine

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Authors: Ramachandra C. G., Amarnath. M., Prashanth Pai M., Nagesh S. N.

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The machine's performance level drops down over a period of time due to the wear and tear of its components. The early detection of an emergent fault becomes very vital in order to obtain uninterrupted production in a plant. Maintenance is an activity that helps to keep the machine's performance at an anticipated level, thereby ensuring the availability of the machine to perform its intended function. At present, a number of modern maintenance techniques are available, such as preventive maintenance, predictive maintenance, condition-based maintenance, total productive maintenance, etc. Condition-based maintenance or condition monitoring is one such modern maintenance technique in which the machine's condition or health is checked by the measurement of certain parameters such as sound level, temperature, velocity, displacement, vibration, etc. It can recognize most of the factors restraining the usefulness and efficacy of the total manufacturing unit. This research work is conducted on a Batch Mill in a tire production unit located in the Southern Karnataka region. The health of the mill is assessed using amplitude of vibration as a parameter of measurement. Most commonly, the vibration level is assessed using various points on the machine bearing. The normal or standard level is fixed using reference materials such as manuals or catalogs supplied by the manufacturers and also by referring vibration standards. The Rio-Vibro meter is placed in different locations on the batch-off mill to record the vibration data. The data collected are analyzed to identify the malfunctioning components in the batch off the mill, and corrective measures are suggested.

Keywords: availability, displacement, vibration, rio-vibro, condition monitoring

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Authors: Özgür Öztürk, Cumhur Sipahi, Hande Yeşil

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Implant retained restorations commonly consist of a metal-framework veneered with ceramic or composite facings. The increasing and expanding use of indirect resin composites in dentistry is a result of innovations in materials and processing techniques. Of special interest to the implant restorative field is the possibility that composites present significantly lower peak vertical and transverse forces transmitted at the peri-implant level compared to metal-ceramic supra structures in implant-supported restorations. A 43-year-old male patient referred to the department of prosthodontics for an implant retained fixed prosthesis. The clinical and radiographic examination of the patient demonstrated the presence of an implant in the right mandibular first molar tooth region. A considerable amount of marginal bone loss around the implant was detected in radiographic examinations combined with a remarkable peri-implant soft tissue deficiency. To minimize the chewing loads transmitted to the implant-bone interface it was decided to fabricate an indirect composite resin veneered single metal crown over a screw-retained abutment. At the end of the treatment, the functional and aesthetic deficiencies were fully compensated. After a 6 months clinical and radiographic follow-up period the not any additional pathologic invasion was detected in the implant-bone interface and implant retained restoration did not reveal any vehement complication.

Keywords: dental implant, fixed partial dentures, indirect composite resin, peri-implant defects

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Authors: Dibyendu Roy, V. Ramu Reddy, Parijat Deshpande, Ranjan Dasgupta

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Imaging of underwater objects is primarily conducted by acoustic imagery due to the severe attenuation of electro-magnetic waves in water. Acoustic imagery underwater has varied range of significant applications such as side-scan sonar, mine hunting sonar. It also finds utility in other domains such as imaging of body tissues via ultrasonography and non-destructive testing of objects. In this paper, we explore the feasibility of using active acoustic imagery in air and simulate phased array beamforming techniques available in literature for various array designs to achieve a suitable acoustic sensor array design for a portable mobile robot which can be applied to detect the presence/absence of anomalous objects in a room. The multi-path reflection effects especially in enclosed rooms and environmental noise factors are currently not simulated and will be dealt with during the experimental phase. The related hardware is designed with the same feasibility criterion that the developed system needs to be deployed on a portable mobile robot. There is a trade of between image resolution and range with the array size, number of elements and the imaging frequency and has to be iteratively simulated to achieve the desired acoustic sensor array design. The designed acoustic imaging array system is to be mounted on a portable mobile robot and targeted for use in surveillance missions for intruder alerts and imaging objects during dark and smoky scenarios where conventional optic based systems do not function well.

Keywords: acoustic sensor array, acoustic imagery, anomaly detection, phased array beamforming

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Authors: Doriane Micaela Andeme Bikoro, Samuel Fosso Wamba, Jean Robert Kala Kamdjoug

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Currently one of the leading fields in the market of technological innovation is digital health. In developed countries, this booming innovation is experiencing an exponential speed. We understand that in developed countries, e-health could also revolutionize the practice of medicine and therefore fill the many failures observed in medical care. Everything leads to believe that future technology is oriented towards the medical sector. The aim of this work is to explore at the same time the technological resources and the potential of health care based on new technologies; it is a case study in a rural area of Southern Cameroon. Among other things, we will make a census of the shortcomings and problems encountered, and we will propose various appropriate solutions. The work methodology used here is essentially qualitative. We used two qualitative data collection techniques, direct observation, and interviews. In fact, we spent two weeks in the field observing and conducting some semi-directive interviews with some of those responsible for these health structures. This study was conducted in three health facilities in the south of the country; including two health centers and a rural hospital. Many technological failures have been identified in the day-to-day management of these health facilities and especially in the administration of health care to patients. We note major problems such as the digital divide, the lack of qualified personnel, the state of isolation of this area. This is why various proposals are made to improve the health sector in Cameroon both technologically and medically.

Keywords: Cameroon, capacities, census, digital health, qualitative method, rural area

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Authors: Maninderjeet K. Grewal, Sakshi Bhatnor, Renu Chadha

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The composition of pharmaceutical entities and the molecular interactions can be altered to optimize drug properties such as solubility and bioavailability by the crystal engineering technique. The present work has emphasized on the preparation, characterization, and biopharmaceutical evaluation of co-crystal of BCS Class II anti-osteoarthritis drug, Oxaprozin (OXA) with aspartic acid (ASPA) as co-former. The co-crystals were prepared through the mechanochemical solvent drop grinding method. Characterization of the prepared co-crystal (OXA-ASPA) was done by using analytical tools such as differential scanning calorimetry (DSC), Fourier transform infrared spectroscopy (FT-IR), powder X-ray diffraction (PXRD). DSC thermogram of OXA-ASPA cocrystal showed a single sharp melting endotherm at 235 ºC, which was between the melting peaks of the drug and the counter molecules suggesting the formation of a new phase which is a co-crystal that was further confirmed by using other analytical techniques. FT-IR analysis of OXA-ASPA cocrystal showed a shift in a hydroxyl, carbonyl, and amine peaks as compared to pure drugs indicating all these functional groups are participating in cocrystal formation. The appearance of new peaks in the PXRD pattern of cocrystals in comparison to individual components showed that a new crystalline entity has been formed. The Crystal structure of cocrystal was determined using material studio software (Biovia) from PXRD. The equilibrium solubility study of OXA-ASPA showed improvement in solubility as compared to pure drug. Therefore, it was envisioned to prepare the co-crystal of oxaprozin with a suitable conformer to modulate its physiochemical properties and consequently, the biopharmaceutical parameters.

Keywords: cocrystals, coformer, oxaprozin, solubility

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Authors: Priya Tomar, Pallavi Mittal

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Bioremediation has been recognized as an environment friendly and less expensive method which involves the natural processes resulting in the efficient conversion of hazardous compounds into innocuous products. The pulp and paper mill effluent is one of the high polluting effluents amongst the effluents obtained from polluting industries. The colouring body present in the wastewater from pulp and paper mill is organic in nature and is comprised of wood extractives, tannin, resins, synthetic dyes, lignin, and its degradation products formed by the action of chlorine on lignin which imparts an offensive colour to the water. These mills use different chemical process for paper manufacturing due to which lignified chemicals are released into the environment. Therefore, the chemical oxygen demand (COD) of the emanating stream is quite high. For solving the above problem we present this paper with some new techniques that were developed for the efficiency of paper mill effluents. In the present study we utilized the consortia of fungal and bacterial strain and the treatment named as C1, C2, and C3 for the decolourization of paper mill effluent. During the study, role of carbon source i.e. glucose was studied for decolourization. From the results it was observed that a maximum colour reduction of 66.9%, COD reduction of 51.8%, TSS reduction of 0.34%, TDS reduction of 0.29% and pH changes of 4.2 is achieved by consortia of Aspergillus niger with Pseudomonas aeruginosa. Data indicated that consortia of Aspergillus niger with Pseudomonas aeruginosa is giving better result with glucose.

Keywords: bioremediation, decolourization, black liquor, mycoremediation

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Authors: M. Ottenbrite, G. Yilmaz, J. Devenish, M. Kang, H. Dan, M. Lin, C. Lau, C. Carrillo, K. Bessonov, J. Nash, E. Topp, J. Guan

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Consumption of food contaminated by antibiotic-resistant (AR) bacteria may lead to the transmission of AR genes in the gut microbiota and cause AR bacterial infection, a significant public health concern. However, information is limited on if and how background microbes from the food matrix (food microbes) may influence resistance transmission. Thus, we assessed the colonization of a β-lactam resistant Salmonella Heidelberg strain (donor) and a β-lactam susceptible S. Typhimurium strain (recipient) and the transfer of the resistance genes in the mouse gut in the presence or absence of food microbes that were derived from washing freshly-harvested carrots. Mice were pre-treated with streptomycin and then inoculated with both donor and recipient bacteria or recipient only. Fecal shedding of the donor, recipient, and transconjugant bacteria was enumerated using selective culture techniques. Transfer of AR genes was confirmed by whole genome sequencing. Gut microbial composition was determined by 16s rRNA amplicon sequencing. Significantly lower numbers of donors and recipients were shed from mice that were inoculated with food microbes compared to those without food microbe inoculation. S. Typhimurium transconjugants were only recovered from mice without inoculation of food microbes. A significantly higher survival rate was in mice with vs. without inoculation of food microbes. The results suggest that the food microbes may compete with both the donor and recipient Salmonella, limit their growth and reduce transmission of the β-lactam resistance gene in the mouse gut.

Keywords: antibiotic resistance, gene transfer, gut microbiota, Salmonella infection

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Authors: Sahabeh Safarpour, Khiruddin Abdullah, Hwee San Lim, Mohsen Dadras

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Air pollution is a growing problem arising from domestic heating, high density of vehicle traffic, electricity production, and expanding commercial and industrial activities, all increasing in parallel with urban population. Monitoring and forecasting of air quality parameters are important due to health impact. One widely available metric of aerosol abundance is the aerosol optical depth (AOD). The AOD is the integrated light extinction coefficient over a vertical atmospheric column of unit cross section, which represents the extent to which the aerosols in that vertical profile prevent the transmission of light by absorption or scattering. Seasonal aerosol optical depth (AOD) values at 550 nm derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA’s Terra satellites, for the 10 years period of 2000-2010 were used to test 7 different spatial interpolation methods in the present study. The accuracy of estimations was assessed through visual analysis as well as independent validation based on basic statistics, such as root mean square error (RMSE) and correlation coefficient. Based on the RMSE and R values of predictions made using measured values from 2000 to 2010, Radial Basis Functions (RBFs) yielded the best results for spring, summer, and winter and ordinary kriging yielded the best results for fall.

Keywords: aerosol optical depth, MODIS, spatial interpolation techniques, Radial Basis Functions

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Authors: M. Benzerara, B. Redjel, B. Kebaili

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The cracking of the concrete is a more crucial problem with the development of the complex structures related to technological progress. The projections in the knowledge of the breaking process make it possible today for better prevention of the risk of the fracture. The breaking strength brutal of a quasi-fragile material like the concrete called Toughness is measured by a breaking value of the factor of the intensity of the constraints K1C for which the crack is propagated, it is an intrinsic property of the material. Many studies reported in the literature treating of the concrete were carried out on specimens which are in fact inadequate compared to the intrinsic characteristic to identify. We started from this established fact, in order to compare the evolution of the parameter of toughness K1C measured by calling upon ordinary concrete specimens of three prismatic geometries different (10*10*40) Cm3, (12*12*60) Cm3 & (5*20*120) Cm3 containing from the side notches various depths simulating of the cracks was set up.The notches are carried out using triangular pyramidal plates into manufactured out of sheet coated placed at the center of the specimens at the time of the casting, then withdrawn to leave the trace of a crack. The tests are carried out in 3 points bending test in mode 1 of fracture, by using the techniques of mechanical fracture. The evolution of the parameter of toughness K1C measured with the three geometries specimens gives almost the same results. They are acceptable and return in the beach of the results determined by various researchers (toughness of the ordinary concrete turns to the turn of the 1 MPa √m). These results inform us about the presence of an economy on the level of the geometry specimen (5*20*120) Cm3, therefore, to use plates specimens later if one wants to master the toughness of this material complexes, astonishing but always essential that is the concrete.

Keywords: concrete, fissure, specimen, toughness

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Authors: Reza Nematirad, Anil Pahwa, Balasubramaniam Natarajan

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Time series data consist of successive data points collected over a period of time. Accurate prediction of future values is essential for informed decision-making in several real-world applications, including electricity load demand forecasting, lifetime estimation of industrial machinery, traffic planning, weather prediction, and the stock market. Due to their critical relevance and wide application, there has been considerable interest in time series forecasting in recent years. However, the proliferation of sensors and IoT devices, real-time monitoring systems, and high-frequency trading data introduce significant intricate temporal variations, rapid changes, noise, and non-linearities, making time series forecasting more challenging. Classical methods such as Autoregressive integrated moving average (ARIMA) and Exponential Smoothing aim to extract pre-defined temporal variations, such as trends and seasonality. While these methods are effective for capturing well-defined seasonal patterns and trends, they often struggle with more complex, non-linear patterns present in real-world time series data. In recent years, deep learning has made significant contributions to time series forecasting. Recurrent Neural Networks (RNNs) and their variants, such as Long short-term memory (LSTMs) and Gated Recurrent Units (GRUs), have been widely adopted for modeling sequential data. However, they often suffer from the locality, making it difficult to capture local trends and rapid fluctuations. Convolutional Neural Networks (CNNs), particularly Temporal Convolutional Networks (TCNs), leverage convolutional layers to capture temporal dependencies by applying convolutional filters along the temporal dimension. Despite their advantages, TCNs struggle with capturing relationships between distant time points due to the locality of one-dimensional convolution kernels. Transformers have revolutionized time series forecasting with their powerful attention mechanisms, effectively capturing long-term dependencies and relationships between distant time points. However, the attention mechanism may struggle to discern dependencies directly from scattered time points due to intricate temporal patterns. Lastly, Multi-Layer Perceptrons (MLPs) have also been employed, with models like N-BEATS and LightTS demonstrating success. Despite this, MLPs often face high volatility and computational complexity challenges in long-horizon forecasting. To address intricate temporal variations in time series data, this study introduces Times2D, a novel framework that parallelly integrates 2D spectrogram and derivative heatmap techniques. The spectrogram focuses on the frequency domain, capturing periodicity, while the derivative patterns emphasize the time domain, highlighting sharp fluctuations and turning points. This 2D transformation enables the utilization of powerful computer vision techniques to capture various intricate temporal variations. To evaluate the performance of Times2D, extensive experiments were conducted on standard time series datasets and compared with various state-of-the-art algorithms, including DLinear (2023), TimesNet (2023), Non-stationary Transformer (2022), PatchTST (2023), N-HiTS (2023), Crossformer (2023), MICN (2023), LightTS (2022), FEDformer (2022), FiLM (2022), SCINet (2022a), Autoformer (2021), and Informer (2021) under the same modeling conditions. The initial results demonstrated that Times2D achieves consistent state-of-the-art performance in both short-term and long-term forecasting tasks. Furthermore, the generality of the Times2D framework allows it to be applied to various tasks such as time series imputation, clustering, classification, and anomaly detection, offering potential benefits in any domain that involves sequential data analysis.

Keywords: derivative patterns, spectrogram, time series forecasting, times2D, 2D representation

Procedia PDF Downloads 25

Authors: Sadeq Al Yaari, Fayza Alhammadi, Ayman Al Yaari, Montaha Al Yaari, Aayah Al Yaari, Adham Al Yaari, Sajedah Al Yaari, Saleh Al Yami

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Background: There has been a debate in the literature over the years as to whether or not MossTalk Words program fits Arab Broca’s aphasics (BAs) due to that language differences and also the fact that the technique has not yet been used for aphasics with semantic dementia (SD aphasics). Aims: To oversimplify the above mentioned debate slightly for purposes of exposition, the purpose of the present study is to investigate the “usability” of this program as well as pictures and community as therapeutic techniques for both Arab BAs and SD aphasics. Method: The subjects of this study are two Saudi aphasics (53 and 57 years old, respectively). The former suffers from Broca’s aphasia due to a stroke, while the latter suffers from semantic dementia. Both aphasics can speak English and have used the Moss Talk Words program in addition to intensive picture-naming therapeutic sessions for two years. They were tested by one of the researchers four times (a time per six months). The families of the two subjects, in addition to their relatives and friends, played a major part in all therapeutic sessions. Conclusion: Results show that in averages across the entire therapeutic sessions, MossTalk Words program was clearly found more effective in modeling BAs’ pronunciation than that of SD aphasic. Furthermore, picture-naming intensive exercises in addition to the positive role of the community members played a major role in the progress of the two subjects’ performance.

Keywords: moss talk words, program, technique, Broca’s aphasia, semantic dementia, subjects, picture, community

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Authors: Wi Sung Yoo, Seung Woo Lee, Youn Kyoung Hur, Sung Hwan Kim

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Large-scale construction projects are continuously increasing, and the need for tools to monitor and evaluate the project success is emphasized. At the construction industry level, there are limitations in deriving performance evaluation factors that reflect the diversity of construction sites and systems that can objectively evaluate and manage performance. Additionally, there are difficulties in integrating structured and unstructured data generated at construction sites and deriving improvements. In this study, we propose the Key Performance Indicators (KPIs) to enable performance evaluation that reflects the increased diversity of construction sites and the unstructured data generated, and present a model for measuring performance by the derived indicators. The comprehensive performance of a unit construction site is assessed based on 6 areas (Time, Cost, Quality, Safety, Environment, Productivity) and 26 indicators. We collect performance indicator information from 30 construction sites that meet legal standards and have been successfully performed. And We apply data augmentation and optimization techniques into establishing measurement standards for each indicator. In other words, the KPI for construction site performance evaluation presented in this study provides standards for evaluating performance in six areas using institutional requirement data and document data. This can be expanded to establish a performance evaluation system considering the scale and type of construction project. Also, they are expected to be used as a comprehensive indicator of the construction industry and used as basic data for tracking competitiveness at the national level and establishing policies.

Keywords: key performance indicator, performance measurement, structured and unstructured data, data augmentation

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Authors: Maria Angela Bedini, Fabio Bronzini

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Most of the Italian territory is at seismic risk. Many earthquakes have hit Italy, and devastating effects have been generated. The specific objective of the research is to distinguish the negative approaches that have generated unacceptable social situations of marginalization, abandonment, and economic regression, from positive methodological approaches. On the basis of the different situations examined, the study proposes strategies and guidelines to obtain the best possible results, in Italy or abroad, in the event of new earthquakes. At national and international level, many theoretical studies address the aspects of prevention, while the comparisons, carried out in this study, between the techniques and the operative procedures applied and the results obtained are rare. The adopted methodology compares the different pre-earthquake urban-planning approaches, for the emergency (temporary urban planning), and for the post-earthquake (socio-economic-territorial processes) in Italy. Attention is placed on the current consolidated planning and programming acquisitions, pre and post-earthquake. The main results of the study concern the prospects in Italy of protection from seismic risks in the next decades. An integrated settlement system for a new economic and social model, aimed at the rebirth of territories in crisis, is proposed. Finally, the conclusions describe the disciplinary positions, procedures and the fundamental points generally shared by the scientific community for each approach, in order to identify the strategic choices and the disciplinary and management paths that will be followed in the coming decades.

Keywords: post-earthquake, seismic emergency, seismic prevention, urban planning interventions in Italy

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Authors: I. V. Pinto, M. R. Sooriyarachchi

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It can be frequently observed that the data arising in our environment have a hierarchical or a nested structure attached with the data. Multilevel modelling is a modern approach to handle this kind of data. When multilevel modelling is combined with a binary response, the estimation methods get complex in nature and the usual techniques are derived from quasi-likelihood method. The estimation methods which are compared in this study are, marginal quasi-likelihood (order 1 & order 2) (MQL1, MQL2) and penalized quasi-likelihood (order 1 & order 2) (PQL1, PQL2). A statistical model is of no use if it does not reflect the given dataset. Therefore, checking the adequacy of the fitted model through a goodness-of-fit (GOF) test is an essential stage in any modelling procedure. However, prior to usage, it is also equally important to confirm that the GOF test performs well and is suitable for the given model. This study assesses the suitability of the GOF test developed for binary response multilevel models with respect to the method used in model estimation. An extensive set of simulations was conducted using MLwiN (v 2.19) with varying number of clusters, cluster sizes and intra cluster correlations. The test maintained the desirable Type-I error for models estimated using PQL2 and it failed for almost all the combinations of MQL. Power of the test was adequate for most of the combinations in all estimation methods except MQL1. Moreover, models were fitted using the four methods to a real-life dataset and performance of the test was compared for each model.

Keywords: goodness-of-fit test, marginal quasi-likelihood, multilevel modelling, penalized quasi-likelihood, power, quasi-likelihood, type-I error

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Authors: Xing Wang, Lin Feng, Xuan Zou, Hongchen liu

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Immediate Implantation after tooth extraction is considered to be the ideal way to retain the alveolar bone, but some scholars believe the aesthetic effect in the Early Implantation case are more reliable. In this study, 89 patients were added to this retrospective study up to 5 years. Assessment indicators was including the survival of the implant (peri-implant infection, implant loosening, shedding, crowns and occlusal), aesthetics (color and fullness gums, papilla height, probing depth, X-ray alveolar crest height, the patient's own aesthetic satisfaction, doctors aesthetics score), repair defects around the implant (peri-implant bone changes in height and thickness, whether the use of autologous bone graft, whether to use absorption/repair manual nonabsorbable material), treatment time, cost and the use of antibiotics.The results demonstrated that there is no significant difference in long-term success rate of immediate implantation, early implantation and delayed implantation (p> 0.05). But the results indicated immediate implantation group could get get better aesthetic results after two years (p< 0.05), but may increase the risk of complications and failures (p< 0.05). High-risk indicators include gingival recession, labial bone wall damage, thin gingival biotypes, planting position and occlusal restoration bad and so on. No matter which type of implanting methods was selected, the extraction methods and bone defect amplification techniques are observed as a significant factors on aesthetic effect (p< 0.05).

Keywords: immediate implantation, long-term effects, aesthetics area, dental implants

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Authors: Vildan Cırık, Emine Efe

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Complementary health approaches are growing in popularity worldwide and play a substantial role in health care. It is very important for paediatric nurses to have knowledge of practices affecting the medical conditions of patients and to communicate with them through integrative nursing care. The purpose of this study was to determine paediatric nurses’ knowledge and experiences of complementary health approaches (CHA) and their personal and professional attitudes to the use of complementary health approaches. This multicentre study was conducted with 1450 paediatric nurses in 18 hospitals in Turkey. Paediatric nurses included in the study were working in the following clinics: Paediatric Service, Paediatric Intensive Care, Paediatric Haematology/Oncology. Data collection focused on the paediatric nurses’ knowledge and experiences of CHA. A high proportion of our sample of paediatric nurses reported that they had used some form of CHA themselves; the most popular choices of CHA were prayer, massage, and vitamins techniques. Paediatric nurses reported positive experiences (drawing/music/art/dance therapies, prayer, herbs, thermal springs, massage, and reflexology) and negative experiences (herbs, thermal springs, prayer, and massage). This study may contribute to increased awareness of the potentially important role of paediatric nurses in the delivery of CHA. Paediatric nurses play important roles in helping patients to use complementary health approaches safely and accurately. Trainings on CHA should be organised, data collection forms including CHA should be created, and evidence-based studies should be focused towards improving the clinical practice of paediatric nurses.

Keywords: complementary health approaches, paediatric nurses, knowledge, experience, attitude, Turkey

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Authors: Edwin Oviedo, Carlos Linares, Philippe Ayrault, Sylvette Brunet

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Nowadays, light conventional crude oils are going down. Therefore, the exploitation of heavy crude oils has been increasing. Hence, a major quantity of refractory sulfur compounds such as dibenzothiophene (DBT) should be removed. Many efforts have been carried out to modify hydrotreatment typical supports in order to increase hydrodesulfurization (HDS) reactions. The present work shows the synthesis of tertiaries MgFeAl(0.16), MgFeAl(0.32), CoFeAl, ZnFeAl hydrotalcites, as supports of CoMo based catalysts, where 0.16 and 0.32 are the Fe3+/Al3+ molar ratio. Solids were characterized by different techniques (XRD, CO2-TPD, H2-TPR, FT-IR, BET, Chemical Analysis and HRTEM) and tested in the DBT HDS reaction. The reactions conditions were: Temp=325°C, P=40 Bar, H2/feed=475. Results show that the catalysts CoMo/MgFeAl(0.16) and CoMo/MgFeAl(0.32), which were the most basics, reduced the sulfur content from 500ppm to less than 1 ppm, increasing the cyclohexylbenzene content, i.e. presented a higher selective toward the HYD pathway than reference catalyst CoMo/γ- Al2O3. This is suitable for improving the fuel quality due to the increase of the cetane number. These catalysts were also more active to the HDS reaction increasing the direct desulfurization (DDS) way and presented a good stability. It is advantageous when the gas oil centane number should be improved. Cobalt, iron or zinc species inside support could avoid the Co and Mo dispersion or form spinel species which could be less active to hydrodesulfuration reactions, while hydrotalcites containing Mg increases the HDS activity probably due to improved Co/Mo ratio.

Keywords: catalyst, cetane number, dibenzothiophene, diesel, hydrodesulfurization, hydrotreatment, MoS2

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Authors: Yiping Meng, Yiming Sun

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The traditional construction industry is unable to meet the requirements for novel fabrication and construction. Automated construction and digital design have emerged as industry development trends that compensate for this shortcoming under the backdrop of Industrial Revolution 4.0. Benefitting from more flexible working space and more various end-effector tools compared to CNC methods, robot fabrication and construction techniques have been used in irregular architectural design. However, there is a lack of a systematic and comprehensive design and optimisation workflow considering geometric form, material, and fabrication methods. This paper aims to propose a design optimisation workflow for improving the rationality of a free-form timber structure fabricated by the robotic arm. Firstly, the free-form surface is described by NURBS, while its structure is calculated using the finite element analysis method. Then, by considering the characteristics and limiting factors of robotic timber fabrication, strain energy and robustness are set as optimisation objectives to optimise structural morphology by gradient descent method. As a result, an optimised structure with axial force as the main force and uniform stress distribution is generated after the structure morphology optimisation process. With the decreased strain energy and the improved robustness, the generated structure's bearing capacity and mechanical properties have been enhanced. The results prove the feasibility and effectiveness of the proposed optimisation workflow for free-form timber structure morphology design.

Keywords: robotic fabrication, free-form timber structure, Multi-objective optimisation, Structural morphology, rational design

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Authors: Lucia Perez, Maria Gaton y Santa Palella

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Starting from the etymology of the word culture, the Latin term ‘colere’, whose meaning is to cultivate, we understand that the society that cultivates its knowledge is laying the foundations for new possibilities. In this sense, art and fashion contain the same attributes: concept, aesthetic principles, and refined techniques. Both play a crucial role, communication, and this implies a sense of community, relationship with tradition, and innovation. This is the mirror in which to contemplate, but also the space that helps to grow. This is the framework where our object of study opens up: the anthropological management or the mission management model applied to fashion exhibitions in museums and cultural institutions. For this purpose, a bibliographic review has been carried out with its subsequent analysis, a case study of three successful exhibitions: ‘Christian Dior: designer of dreams’, ‘Balenciaga and the Spanish painting’, and ‘China: Through the Looking Glass’. The methodology has been completed with interviews focused on the curators. Amongst the results obtained, it is worth highlighting the fundamental role of transcendent leadership, which, in addition to being results-oriented, must align the motivations of the collaborators with the mission. The anthropological management model conceives management as a service, and it is oriented to the interests of the staff and the public, in short, of the person; this is what enables the objectives of effectiveness, efficiency, and social value to be achieved; dimensions, all necessary for the proper development of the mission of the exhibitions. Fashion, understood as art, is at the service of culture, and therefore of the human being, which defines a transcendent mission. We conclude that the profile of an anthropological management model applied to fashion exhibitions in museums is the ideal one to achieve the purpose of these institutions.

Keywords: art, culture, fashion, anthropological model, fashion exhibitions

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Authors: Simona Ziukaite, Remigijus Ivanauskas, Gintaras Denafas

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Market development of electrical and electronic equipment and a short life cycle is driven by the increasing waste streams. Gold Au, copper Cu, silver Ag and palladium Pd can be found on printed circuit board. These metals make up the largest value of printed circuit board. Therefore, the printed circuit boards scrap is valuable as potential raw material for precious metals recovery. A comparison of Cu, Au, Ag, Pd recovery from waste printed circuit techniques was selected metals leaching of chemical reagents. The study was conducted using the selected multistage technique for Au, Cu, Ag, Pd recovery of printed circuit board. In the first and second metals leaching stages, as the elution reagent, 2M H2SO4 and H2O2 (35%) was used. In the third stage, leaching of precious metals used solution of 20 g/l of thiourea and 6 g/l of Fe2 (SO4)3. Verify the efficiency of the method was carried out the metals leaching test with aqua regia. Based on the experimental study, the leaching efficiency, using the preferred methodology, 60 % of Au and 85,5 % of Cu dissolution was achieved. Metals leaching efficiency after waste mechanical crushing and thermal treatment have been increased by 1,7 times (40 %) for copper, 1,6 times (37 %) for gold and 1,8 times (44 %) for silver. It was noticed that, the Au amount in old (> 20 years) waste is 17 times more, Cu amount - 4 times more, and Ag - 2 times more than in the new (< 1 years) waste. Palladium in the new printed circuit board waste has not been found, however, it was established that from 1 t of old printed circuit board waste can be recovered 1,064 g of Pd (leaching with aqua regia). It was found that from 1 t of old printed circuit board waste can be recovered 1,064 g of Ag. Precious metals recovery in Lithuania was estimated in this study. Given the amounts of generated printed circuit board waste, the limits for recovery of precious metals were identified.

Keywords: leaching efficiency, limits for recovery, precious metals recovery, printed circuit board waste

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Authors: Sheikh Shams Azam, Manoj Raju, Venkatesh Pagidimarri, Vamsi Kasivajjala

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Over the past decade, there has been a steep rise in the data-driven analysis in major areas of medicine, such as clinical decision support system, survival analysis, patient similarity analysis, image analytics etc. Most of the data in the field are well-structured and available in numerical or categorical formats which can be used for experiments directly. But on the opposite end of the spectrum, there exists a wide expanse of data that is intractable for direct analysis owing to its unstructured nature which can be found in the form of discharge summaries, clinical notes, procedural notes which are in human written narrative format and neither have any relational model nor any standard grammatical structure. An important step in the utilization of these texts for such studies is to transform and process the data to retrieve structured information from the haystack of irrelevant data using information retrieval and data mining techniques. To address this problem, the authors present Q-Map in this paper, which is a simple yet robust system that can sift through massive datasets with unregulated formats to retrieve structured information aggressively and efficiently. It is backed by an effective mining technique which is based on a string matching algorithm that is indexed on curated knowledge sources, that is both fast and configurable. The authors also briefly examine its comparative performance with MetaMap, one of the most reputed tools for medical concepts retrieval and present the advantages the former displays over the latter.

Keywords: information retrieval, unified medical language system, syntax based analysis, natural language processing, medical informatics

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Authors: Benyelles Zakaria, Yousfi Djaafar, Karoui Moussa Sofiane

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Agriculture is fundamental and remains an important objective in the Algerian economy, based on traditional techniques and structures, it generally has a purpose of consumption. Collection of agricultural statistics in Algeria is done using traditional methods, which consists of investigating the use of land through survey and field survey. These statistics suffer from problems such as poor data quality, the long delay between collection of their last final availability and high cost compared to their limited use. The objective of this work is to develop a processing chain for a reliable inventory of agricultural land by trying to develop and implement a new method of extracting information. Indeed, this methodology allowed us to combine data from remote sensing and field data to collect statistics on areas of different land. The contribution of remote sensing in the improvement of agricultural statistics, in terms of area, has been studied in the wilaya of Sidi Bel Abbes. It is in this context that we applied a method for extracting information from satellite images. This method is called the non-negative matrix factorization, which does not consider the pixel as a single entity, but will look for components the pixel itself. The results obtained by the application of the MNF were compared with field data and the results obtained by the method of maximum likelihood. We have seen a rapprochement between the most important results of the FMN and those of field data. We believe that this method of extracting information from satellite data leads to interesting results of different types of land uses.

Keywords: blind source separation, hyper-spectral image, non-negative matrix factorization, remote sensing

Procedia PDF Downloads 405