Search results for: heatmap visualization techniques

Authors: Abdelkrim Belhaoua, Jean-Pierre Radoux, Mariana Kuras, Vincent Récamier, Martial Piotto, Karim Elbayed, François Proust, Izzie Namer

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This paper proposes an augmented reality system dedicated to neurosurgery in order to assist the surgeon during an operation. This work is part of the ExtempoRMN project (Funded by Bpifrance) which aims at analyzing during a surgical operation the metabolic content of tumoral brain biopsy specimens by HRMAS NMR. Patients affected with a brain tumor (gliomas) frequently need to undergo an operation in order to remove the tumoral mass. During the operation, the neurosurgeon removes biopsy specimens using image-guided surgery. The biopsy specimens removed are then sent for HRMAS NMR analysis in order to obtain a better diagnosis and prognosis. Image-guided refers to the use of MRI images and a computer to precisely locate and target a lesion (abnormal tissue) within the brain. This is performed using preoperative MRI images and the BrainLab neuro-navigation system. With the patient MRI images loaded on the Brainlab Cranial neuro-navigation system in the operating theater, surgeons can better identify their approach before making an incision. The Brainlab neuro-navigation tool tracks in real time the position of the instruments and displays their position on the patient MRI data. The results of the biopsy analysis by 1H HRMAS NMR are then sent back to the operating theater and superimposed on the 3D localization system directly on the MRI images. The method we have developed to communicate between the HRMAS NMR analysis software and Brainlab makes use of a combination of C++, VTK and the Insight Toolkit using OpenIGTLink protocol.

Keywords: neuro-navigation, augmented reality, biopsy, BrainLab, HR-MAS NMR

Procedia PDF Downloads 365

Authors: Elif Doğru, Bülent Kızılduman, Huriye İcil

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Throughout history, Cyprus has been involved in various commercial and cultural relationships with different civilizations, owing to its strategic location. Particularly during the Late Bronze Age, Cyprus emerged as a significant region engaged in interactions with the Mycenaeans and other Mediterranean civilizations. Presently, findings from archaeological excavations provide valuable insights into Cyprus' cultural history and its connections with other civilizations. Painted Mycenaean ceramics discovered during the excavations at Kaleburnu-Kral Tepesi (Galinaporni-Vasili), dated to the Late Bronze Age in Cyprus, are considered significant archaeological findings that carry traces of the art and culture of that era, reflecting the island's commercial and cultural connections. Considering these findings, there is a need for archaeometric studies to aid in the understanding of the commercial and cultural ties at Kaleburnu-Kral Tepesi. In line with this need, analytical studies have been initiated concerning the provenance and production techniques of the Mycenaean ceramics discovered in the excavations at Kaleburnu-Kral Tepesi, dated to the Late Bronze Age. In the context of origin analysis studies, it is advocated that understanding the techniques and materials used for the figures and designs applied on Mycenaean ceramics would significantly contribute to a better comprehension of historical contexts. Hence, the adopted approach involves not only the analysis of the ceramic raw material but also the characterization of the pigments on the ceramics as a whole. In light of this, in addition to the studies aimed at determining the provenance and production techniques of the Mycenaean ceramic bodies, the characterization of the pigments used in the decorations of the relevant ceramics has been included in the research scope. Accordingly, this study aims to characterize the pigments used in the decorations of Mycenaean ceramics discovered at Kaleburnu-Kral Tepesi, dated to the Late Bronze Age. The X-Ray diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), and Scanning Electron Microscopy with Energy Dispersive X-ray Spectroscopy (SEM-EDX) methods have been employed to determine the surface morphology and chemical properties of the Mycenaean pigments. The characterization has been conducted through the combination of multiple analytical methods. The characterization of the pigments of Mycenaean ceramics aims to enhance the scientific perspective adopted for understanding the contributions of Mycenaean ceramics found in Cyprus to the island's culture, by providing scientific data on the types and origins of pigments used during the Late Bronze Age.

Keywords: mycenaean, ceramic, provenance, pigment

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Authors: Megh Patel, Arjun Chauhan, Jay Thakkar

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Hydrofracturing is the most prominent but at the same time expensive, highly skilled and time consuming well stimulation technique. Due to high cost and skilled labor involved, it is generally carried out as the consummate solution among other well stimulation techniques. Considering today’s global petroleum market, no gaffe or complications could be entertained during fracturing, as it would further hamper the current dwindling economy. The literature would be dealing with the challenges encountered during fracturing low temperature waxy reservoirs and the prominent solutions to overcome such teething troubles. During fracturing treatment for, shallow and high freezing point waxy oil reservoirs, the first line problems are to overcome uncompleted breakdown, uncompleted cleanup of fracturing fluids and cold damages to the formations by injecting cold fluid (fluid at ambient conditions). Injecting fracturing fluids at ambient conditions have the tendency to decrease the near wellbore reservoir temperature below the freezing point of oil reservoir and hence leading to wax deposition around the wellbore thereby hampering the fluid production as well as fracture propagation. To overcome such problems, solutions such as hot fracturing fluid injection, encapsulated heat generating hydraulic fracturing fluid system, and injection of wax inhibitor techniques would be discussed. The paper would also be throwing light on changes in rheological properties occurred during heating fracturing fluids and solutions to deal with it taking economic considerations into account.

Keywords: hydrofracturing, waxy reservoirs, low temperature, viscosity, crosslinkers

Procedia PDF Downloads 259

Authors: M. Koray Cetin, Mehmet Mert

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The purpose of the study is to examine impacts on tourism revenues of the exchange rate and country overall security level. There are numerous studies that examine the bidirectional relation between macroeconomic factors and tourism revenues and tourism demand. Most of the studies support the existence of impact of tourism revenues on growth rate but not vice versa. Few studies examine the impact of factors like real exchange rate or purchasing power parity on the tourism revenues. In this context, firstly impact of real exchange rate on tourism revenues examination is aimed. Because exchange rate is one of the main determinants of international tourism services price in guests currency unit. Another determinant of tourism demand for a country is country’s overall security level. This issue can be handled in the context of the relationship between tourism revenues and overall security including turmoil, terrorism, border problem, political violence. In this study, factors are handled for several countries which have tourism revenues on a certain level. With this structure, it is a panel data, and it is evaluated with panel data analysis techniques. Panel data have at least two dimensions, and one of them is time dimensions. The panel data analysis techniques are applied to data gathered from Worldbank data web page. In this study, it is expected to find impacts of real exchange rate and security factors on tourism revenues for the countries that have noteworthy tourism revenues.

Keywords: exchange rate, panel data analysis, security, tourism revenues

Procedia PDF Downloads 351

Authors: K. C. Rajan, H. B. Rijal, Kazui Yoshida, Masanori Shukuya

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The electricity consumption in the Japanese household sector has increased with higher rate than that of other sectors. This may be because of aging and information oriented society that requires more electrical appliances to make the life better and easier, under this circumstances, energy saving is one of the essential necessity in Japanese society. To understand the way of energy use and demand response of the residential occupants, it is important to understand the structure of energy used. Home Energy Management System (HEMS) may be used for understanding the pattern and the structure of energy used. HEMS is a visualization system of the energy usage by connecting the electrical equipment in the home and thereby automatically control the energy use in each device, so that the energy saving is achieved. Therefore, the HEMS can provide with the easiest way to understand the structure of energy use. The HEMS has entered the mainstream of the Japanese market. The objective of this study is to understand the pattern of energy saving and cost saving in different regions including Japan during HEMS use. To observe thermal comfort level of HEMS managed residential buildings in Japan, the field survey was made and altogether, 1534 votes from 37 occupants related to thermal comfort, occupants’ behaviors and clothing insulation were collected and analyzed. According to the result obtained, approximately 17.9% energy saving and 8.9% cost saving is possible if HEMS is applied effectively. We found the thermal sensation and overall comfort level of the occupants is high in the studied buildings. The occupants residing in those HEMS buildings are satisfied with the thermal environment and they have accepted it. Our study concluded that the significant reduction in Japanese residential energy use can be achieved by the proper utilization of the HEMS. Better thermal comfort is also possible with the use of HEMS if energy use is managed in a rationally effective manner.

Keywords: energy reduction, thermal comfort, HEMS utility, thermal environment

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Authors: Devon Brown, Liu Chunmei

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This paper will present an analysis as part of the researchers dissertation topic focusing on the intersection of affective and analytical directed acyclic graphs (DAGs) in the context of Decision Support Systems (DSS). The researcher’s work involves analyzing decision theory models like Affective and Bayesian Decision theory models and how they could be implemented under an Affective Computing Framework using Information Fusion and Human-Centered Design. Additionally, the researcher is beginning research on an Affective-Analytic Decision Framework (AADF) model for their dissertation research and are looking to merge logic and analytic models with empathetic insights into affective DAGs. Data-collection efforts begin Fall 2024 and in preparation for the efforts this paper looks to analyze previous research in this area and introduce the AADF framework and propose conceptual models for consideration. For this paper, the research emphasis is placed on analyzing Bayesian networks and Markov models which offer probabilistic techniques during uncertainty in decision-making. Ideally, including affect into analytic models will ensure algorithms can increase user trust with algorithms by including emotional states and the user’s experience with the goal of developing emotionally intelligent A.I. systems that can start to navigate the complex fabric of human emotion during decision-making.

Keywords: decision support systems, explainable AI, HCAI techniques, affective-analytical decision framework

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Authors: Arindam Chowdhury, Andres Tremante, Mohammadtaghi Moravej, Bodhisatta Hajra, Ioannis Zisis, Peter Irwin

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Extreme wind events, such as hurricanes, have caused significant damage to buildings, resulting in losses worth millions of dollars. The roof of a building is most vulnerable to wind-induced damage due to the high suctions experienced by the roof in extreme wind conditions. Wind turbines fitted to buildings can help generate energy, but to our knowledge, their application to wind load mitigation is not well known. This paper presents results from an experimental study to assess the effect of small wind turbines (developed and patented by the first and second authors) on the wind loads on a low rise building roof. The tests were carried out for an open terrain at the Wall of Wind (WOW) experimental facility at Florida International University (FIU), Miami, Florida, USA, for three cases – bare roof, roof fitted with wind turbines placed closer to the roof edges, and roof with wind turbines placed away from the roof edges. Results clearly indicate that the presence of the wind turbines reduced the mean and peak pressure coefficients (less suction) on the roof when compared to the bare deck case. Furthermore, the peak pressure coefficients were found to be lower (less suction) when the wind turbines were placed closer to the roof, than away from the roof. Flow visualization studies using smoke and gravel clearly showed that the presence of the turbines disrupted the formation of vortices formed by cornering winds, thereby reducing roof suctions and preventing lift off of roof coverings. This study shows that the wind turbines besides generating wind energy, can be used for mitigating wind induced damage to the building roof. Future research must be directed towards understanding the effect of these wind turbines on other roof geometries (e.g. hip/gable) in different terrain conditions.

Keywords: wall of wind, wind loads, wind turbine, building

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Authors: Satish Kumar Peddapelli

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This paper presents advances in pulse width modulation techniques which refers to a method of carrying information on train of pulses and the information be encoded in the width of pulses. Pulse Width Modulation is used to control the inverter output voltage. This is done by exercising the control within the inverter itself by adjusting the ON and OFF periods of inverter. By fixing the DC input voltage we get AC output voltage. In variable speed AC motors the AC output voltage from a constant DC voltage is obtained by using inverter. Recent developments in power electronics and semiconductor technology have lead improvements in power electronic systems. Hence, different circuit configurations namely multilevel inverters have become popular and considerable interest by researcher are given on them. A fast Space-Vector Pulse Width Modulation (SVPWM) method for five-level inverter is also discussed. In this method, the space vector diagram of the five-level inverter is decomposed into six space vector diagrams of three-level inverters. In turn, each of these six space vector diagrams of three-level inverter is decomposed into six space vector diagrams of two-level inverters. After decomposition, all the remaining necessary procedures for the three-level SVPWM are done like conventional two-level inverter. The proposed method reduces the algorithm complexity and the execution time. It can be applied to the multilevel inverters above the five-level also. The experimental setup for three-level diode-clamped inverter is developed using TMS320LF2407 DSP controller and the experimental results are analysed.

Keywords: five-level inverter, space vector pulse wide modulation, diode clamped inverter, electrical engineering

Procedia PDF Downloads 388

Authors: Kirstin Burger, Paul Watts, Nicole Vorster

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Green chemistry focuses on synthesis which has a low negative impact on the environment. This research focuses on synthesizing novel compounds from an all-natural Eucalyptus citriodora oil. Eight novel plasticizer compounds are synthesized and optimized using flow chemistry technology. A precursor to one novel compound can be synthesized from the lauric acid present in coconut oil. Key parameters, such as catalyst screening and loading, reaction time, temperature, residence time using flow chemistry techniques is investigated. The compounds are characterised using GC-MS, FT-IR, 1H and 13C-NMR techniques, X-ray crystallography. The efficiency of the compounds is compared to two commercial plasticizers, i.e. Dibutyl phthalate and Eastman 168. Several PVC-plasticized film formulations are produced using the bio-based novel compounds. Tensile strength, stress at fracture and percentage elongation are tested. The property of having increasing plasticizer percentage in the film formulations is investigated, ranging from 3, 6, 9 and 12%. The diastereoisomers of each compound are separated and formulated into PVC films, and differences in tensile strength are measured. Leaching tests, flexibility, and change in glass transition temperatures for PVC-plasticized films is recorded. Research objective includes using these novel compounds as a green bio-plasticizer alternative in plastic products for infants. The inhibitory effect of the compounds on six pathogens effecting infants are studied, namely; Escherichia coli, Staphylococcus aureus, Shigella sonnei, Pseudomonas putida, Salmonella choleraesuis and Klebsiella oxytoca.

Keywords: bio-based compounds, plasticizer, tensile strength, microbiological inhibition , synthesis

Procedia PDF Downloads 188

Authors: Tomas Trainys, Algimantas Venckauskas

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Application of biometric features to the cryptography for human identification and authentication is widely studied and promising area of the development of high-reliability cryptosystems. Biometric cryptosystems typically are designed for patterns recognition, which allows biometric data acquisition from an individual, extracts feature sets, compares the feature set against the set stored in the vault and gives a result of the comparison. Preprocessing and fusion of biometric data are the most important phases in generating a feature vector for key generation or authentication. Fusion of biometric features is critical for achieving a higher level of security and prevents from possible spoofing attacks. The paper focuses on the tasks of initial processing and fusion of multiple representations of finger vein modality patterns. These tasks are solved by applying conventional image preprocessing methods and machine learning techniques, Convolutional Neural Network (SVM) method for image segmentation and feature extraction. An article presents a method for generating sets of biometric features from a finger vein network using several instances of the same modality. Extracted features sets were fused at the feature level. The proposed method was tested and compared with the performance and accuracy results of other authors.

Keywords: bio-cryptography, biometrics, cryptographic key generation, data fusion, information security, SVM, pattern recognition, finger vein method.

Procedia PDF Downloads 152

Authors: Saad M. Darwish, Mohamed A. El-Iskandarani, Guitar M. Shawkat

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Nowadays, the amount of available multimedia data is continuously on the rise. The need to find a required image for an ordinary user is a challenging task. Content based image retrieval (CBIR) computes relevance based on the visual similarity of low-level image features such as color, textures, etc. However, there is a gap between low-level visual features and semantic meanings required by applications. The typical method of bridging the semantic gap is through the automatic image annotation (AIA) that extracts semantic features using machine learning techniques. In this paper, a multi-label image annotation system guided by Firefly and Bayesian method is proposed. Firstly, images are segmented using the maximum variance intra cluster and Firefly algorithm, which is a swarm-based approach with high convergence speed, less computation rate and search for the optimal multiple threshold. Feature extraction techniques based on color features and region properties are applied to obtain the representative features. After that, the images are annotated using translation model based on the Net Bayes system, which is efficient for multi-label learning with high precision and less complexity. Experiments are performed using Corel Database. The results show that the proposed system is better than traditional ones for automatic image annotation and retrieval.

Keywords: feature extraction, feature selection, image annotation, classification

Procedia PDF Downloads 586

Authors: Theresia El Khoury, Georges Badr, Amir Hajjam El Hassani, Stéphane N’Guyen Van Ky

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The widespread adoption of machine learning and artificial intelligence across different domains can be attributed to the digitization of data over several decades, resulting in vast amounts of data, types, and structures. Thus, data processing and preparation turn out to be a crucial stage. However, applying these techniques to S1000D standard-based data poses a challenge due to its complexity and the need to preserve logical information. This paper describes SALERNO, an S1000d AppLicability dEpended pRocessiNg mOdel. This python-based model analyzes and converts the XML S1000D-based files into an easier data format that can be used in machine learning techniques while preserving the different logic and relationships in files. The model parses the files in the given folder, filters them, and extracts the required information to be saved in appropriate data frames and Excel sheets. Its main idea is to group the extracted information by applicability. In addition, it extracts the full text by replacing internal and external references while maintaining the relationships between files, as well as the necessary requirements. The resulting files can then be saved in databases and used in different models. Documents in both English and French languages were tested, and special characters were decoded. Updates on the technical manuals were taken into consideration as well. The model was tested on different versions of the S1000D, and the results demonstrated its ability to effectively handle the applicability, requirements, references, and relationships across all files and on different levels.

Keywords: aeronautics, big data, data processing, machine learning, S1000D

Procedia PDF Downloads 159

Authors: Ibrahim Rassoul, E-K. Si Ahmed

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The growth, deformation, and detachment of fluid droplets adherent to solid substrates is a problem of fundamental interest with numerous practical applications. Specific interest in this proposal is the problem of a droplet on a fibrous, hydrophobic substrate subjected to body or external forces (gravity, convection). The past decade has seen tremendous advances in proton exchange membrane fuel cell (PEMFC) technology. However, there remain many challenges to bring commercially viable stationary PEMFC products to the market. PEMFCs are increasingly emerging as a viable alternative clean power source for automobile and stationary applications. Before PEMFCs can be employed to power automobiles and homes, several key technical challenges must be properly addressed. One technical challenge is elucidating the mechanisms underlying water transport in and removal from PEMFCs. On the one hand, sufficient water is needed in the polymer electrolyte membrane or PEM to maintain sufficiently high proton conductivity. On the other hand, too much liquid water present in the cathode can cause 'flooding' (that is, pore space is filled with excessive liquid water) and hinder the transport of the oxygen reactant from the gas flow channel (GFC) to the three-phase reaction sites. The aim of this work is to investigate the stability of a liquid water droplet emerging form a GDL pore, to gain fundamental insight into the instability process leading to detachment. The approach will combine analytical and numerical modeling with experimental visualization and measurements.

Keywords: polymer electrolyte fuel cell, water droplet, gas diffusion layer, contact angle, surface tension

Procedia PDF Downloads 253

Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

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Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction

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Authors: Mateusz Paszko, Ksenia Siadkowska

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Due to the low-altitude and relatively low-speed flight, helicopters are easy targets for actual combat assets e.g. infrared-guided missiles. Current techniques aim to increase the combat effectiveness of the military helicopters. Protection of the helicopter in flight from early detection, tracking and finally destruction can be realized in many ways. One of them is cooling hot exhaust gasses, emitting from the engines to the atmosphere in special heat exchangers. Nowadays, this process is realized in ejective coolers, where strong heat and momentum exchange between hot exhaust gases and cold air ejected from atmosphere takes place. Flow effects of air, exhaust gases; mixture of those two and the heat transfer between cold air and hot exhaust gases are given by differential equations of: Mass transportation–flow continuity, ejection of cold air through expanding exhaust gasses, conservation of momentum, energy and physical relationship equations. Calculation of those processes in ejective cooler by means of classic mathematical analysis is extremely hard or even impossible. Because of this, it is necessary to apply the numeric approach with modern, numeric computer programs. The paper discussed the general usability of the Computational Fluid Dynamics (CFD) in a process of projecting the ejective exhaust gases cooler cooperating with helicopter turbine engine. In this work, the CFD calculations have been performed for ejective-based cooler cooperating with the PA W3 helicopter’s engines.

Keywords: aviation, CFD analysis, ejective-cooler, helicopter techniques

Procedia PDF Downloads 333

Authors: A. M. John-Otumu, M. M. Rahman, M. C. Onuoha, E. P. Ojonugwa

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A Convolutional Neural Network (CNN) model for predicting Lassa fever was built using Python 3.8.0 programming language, alongside Keras 2.2.4 and TensorFlow 2.6.1 libraries as the development environment in order to reduce the current high risk of Lassa fever in West Africa, particularly in Nigeria. The study was prompted by some major flaws in existing conventional laboratory equipment for diagnosing Lassa fever (RT-PCR), as well as flaws in AI-based techniques that have been used for probing and prognosis of Lassa fever based on literature. There were 15,679 blood smear microscopic image datasets collected in total. The proposed model was trained on 70% of the dataset and tested on 30% of the microscopic images in avoid overfitting. A 3x3x3 convolution filter was also used in the proposed system to extract features from microscopic images. The proposed CNN-based model had a recall value of 96%, a precision value of 93%, an F1 score of 95%, and an accuracy of 94% in predicting and accurately classifying the images into clean or infected samples. Based on empirical evidence from the results of the literature consulted, the proposed model outperformed other existing AI-based techniques evaluated. If properly deployed, the model will assist physicians, medical laboratory scientists, and patients in making accurate diagnoses for Lassa fever cases, allowing the mortality rate due to the Lassa fever virus to be reduced through sound decision-making.

Keywords: artificial intelligence, ANN, blood smear, CNN, deep learning, Lassa fever

Procedia PDF Downloads 120

Authors: Danielle Schneider, Ying Xie

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Middle school science, technology, engineering, and math (STEM) teachers experience an exceptional challenge in the expectation to incorporate curricula that builds strong spatial reasoning skills on rudimentary geometry concepts. Because spatial ability is so closely tied to STEM students’ success, researchers are tasked to determine effective instructional practices that create an authentic learning environment within the immersive virtual reality learning environment (IVRLE). This study looked to investigate the effect of the IVRLE on middle school STEM students’ spatial reasoning skills as a methodology to benefit the STEM middle school students’ spatial reasoning skills. This experimental study was comprised of thirty 7th-grade STEM students divided into a treatment group that was engaged in an immersive VR platform where they engaged in building an object in the virtual realm by applying spatial processing and visualizing its dimensions and a control group that built the identical object using a desktop computer-based, computer-aided design (CAD) program. Before and after the students participated in the respective “3D modeling” environment, their spatial reasoning abilities were assessed using the Middle Grades Mathematics Project Spatial Visualization Test (MGMP-SVT). Additionally, both groups created a physical 3D model as a secondary measure to measure the effectiveness of the IVRLE. The results of a one-way ANOVA in this study identified a negative effect on those in the IVRLE. These findings suggest that with middle school students, virtual reality (VR) proved an inadequate tool to benefit spatial relation skills as compared to desktop-based CAD.

Keywords: virtual reality, spatial reasoning, CAD, middle school STEM

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Authors: Fatai Olakunle Ogundele

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Road construction is increasingly common in today's world as human development expands and people increasingly rely on cars for transportation on a daily basis. The construction of a large network of roads has dramatically altered the landscape and impacted well-being in a number of deleterious ways. In addition, the road can also shift population demographics and be a source of pollution into the environment. Road construction activities normally result in changes in alteration of the soil's physical properties through soil compaction on the road itself and on adjacent areas and chemical and biological properties, among other effects. Understanding roadside soil properties that are influenced by road construction activities can serve as a basis for formulating conservation-based management strategies. Therefore, this study examined the effects of road construction on soil properties and soil organic carbon along Lagos Badagry Expressway, Lagos, Nigeria. The study adopted purposive sampling techniques and 40 soil samples were collected at a depth of 0 – 30cm from each of the identified road intersections and infrastructures using a soil auger. The soil samples collected were taken to the laboratory for soil properties and carbon stock analysis using standard methods. Both descriptive and inferential statistical techniques were applied to analyze the data obtained. The results revealed that soil compaction inhibits ecological succession on roadsides in that increased compaction suppresses plant growth as well as causes changes in soil quality.

Keywords: highway, soil properties, organic carbon, road construction, land degradation

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Authors: Hatim Laalej, Salvador Sumohano-Verdeja, Thomas McLeay

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Monitoring of tool wear in milling operations is essential for achieving the desired dimensional accuracy and surface finish of a machined workpiece. Although there are numerous statistical models and artificial intelligence techniques available for monitoring the wear of cutting tools, these techniques cannot pin point which cutting edge of the tool, or which insert in the case of indexable tooling, is worn or broken. Currently, the task of monitoring the wear on the tool cutting edges is carried out by the operator who performs a manual inspection, causing undesirable stoppages of machine tools and consequently resulting in costs incurred from lost productivity. The present study is concerned with the development of a flute tracking system to segment signals related to each physical flute of a cutter with three flutes used in an end milling operation. The purpose of the system is to monitor the cutting condition for individual flutes separately in order to determine their progressive wear rates and to predict imminent tool failure. The results of this study clearly show that signals associated with each flute can be effectively segmented using the proposed flute tracking system. Furthermore, the results illustrate that by segmenting the sensor signal by flutes it is possible to investigate the wear in each physical cutting edge of the cutting tool. These findings are significant in that they facilitate the online condition monitoring of a cutting tool for each specific flute without the need for operators/engineers to perform manual inspections of the tool.

Keywords: machining, milling operation, tool condition monitoring, tool wear prediction

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Authors: M. Gil, R. Montalvo

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Business Intelligence (BI) has become a major source of competitive advantages for firms around the world. BI has been defined as the process of data visualization and reporting for understanding what happened and what is happening. Moreover, BI has been studied for its predictive capabilities in the context of trade and financial transactions. The current literature has identified that BI permits managers to identify market trends, understand customer relations, and predict demand for their products and services. This last capability of BI has been of special concern to academics. Specifically, due to its power to build predictive models adaptable to specific time horizons and geographical regions. However, the current literature of BI focuses on predicting specific markets and industries because the impact of such predictive models was relevant to specific industries or organizations. Currently, the existing literature has not developed a predictive model of BI that takes into consideration the whole economy of a geographical area. This paper seeks to create a predictive model of BI that would show the bigger picture of a geographical area. This paper uses a data set from the Secretary of Economic Development of the state of Jalisco, Mexico. Such data set includes data from all the commercial transactions that occurred in the state in the last years. By analyzing such data set, it will be possible to generate a BI model that predicts supply and demand from specific industries around the state of Jalisco. This research has at least three contributions. Firstly, a methodological contribution to the BI literature by generating the predictive supply and demand model. Secondly, a theoretical contribution to BI current understanding. The model presented in this paper incorporates the whole picture of the economic field instead of focusing on a specific industry. Lastly, a practical contribution might be relevant to local governments that seek to improve their economic performance by implementing BI in their policy planning.

Keywords: business intelligence, predictive model, supply and demand, Mexico

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Authors: Shatha Ghareeb, Rawaa Al-Jumeily, Thar Baker

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In Abu Dhabi, there are many different education curriculums where sector of private schools and quality assurance is supervising many private schools in Abu Dhabi for many nationalities. As there are many different education curriculums in Abu Dhabi to meet expats’ needs, there are different requirements for registration and success. In addition, there are different age groups for starting education in each curriculum. In fact, each curriculum has a different number of years, assessment techniques, reassessment rules, and exam boards. Currently, students that transfer curriculums are not being placed in the right year group due to different start and end dates of each academic year and their date of birth for each year group is different for each curriculum and as a result, we find students that are either younger or older for that year group which therefore creates gaps in their learning and performance. In addition, there is not a way of storing student data throughout their academic journey so that schools can track the student learning process. In this paper, we propose to develop a computational framework applicable in multicultural countries such as UAE in which multi-education systems are implemented. The ultimate goal is to use cloud and fog computing technology integrated with Artificial Intelligence techniques of Machine Learning to aid in a smooth transition when assigning students to their year groups, and provide leveling and differentiation information of students who relocate from a particular education curriculum to another, whilst also having the ability to store and access student data from anywhere throughout their academic journey.

Keywords: admissions, algorithms, cloud computing, differentiation, fog computing, levelling, machine learning

Procedia PDF Downloads 143

Authors: Alia Alghosoun, Nabil El Moçayd, Mohammed Seaid

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Modeling dam-break flows over non-flat beds requires an accurate representation of the topography which is the main source of uncertainty in the model. Therefore, developing robust and accurate techniques for reconstructing topography in this class of problems would reduce the uncertainty in the flow system. In many hydraulic applications, experimental techniques have been widely used to measure the bed topography. In practice, experimental work in hydraulics may be very demanding in both time and cost. Meanwhile, computational hydraulics have served as an alternative for laboratory and field experiments. Unlike the forward problem, the inverse problem is used to identify the bed parameters from the given experimental data. In this case, the shallow water equations used for modeling the hydraulics need to be rearranged in a way that the model parameters can be evaluated from measured data. However, this approach is not always possible and it suffers from stability restrictions. In the present work, we propose an adaptive optimal control technique to numerically identify the underlying bed topography from a given set of free-surface observation data. In this approach, a minimization function is defined to iteratively determine the model parameters. The proposed technique can be interpreted as a fractional-stage scheme. In the first stage, the forward problem is solved to determine the measurable parameters from known data. In the second stage, the adaptive control Ensemble Kalman Filter is implemented to combine the optimality of observation data in order to obtain the accurate estimation of the topography. The main features of this method are on one hand, the ability to solve for different complex geometries with no need for any rearrangements in the original model to rewrite it in an explicit form. On the other hand, its achievement of strong stability for simulations of flows in different regimes containing shocks or discontinuities over any geometry. Numerical results are presented for a dam-break flow problem over non-flat bed using different solvers for the shallow water equations. The robustness of the proposed method is investigated using different numbers of loops, sensitivity parameters, initial samples and location of observations. The obtained results demonstrate high reliability and accuracy of the proposed techniques.

Keywords: erodible beds, finite element method, finite volume method, nonlinear elasticity, shallow water equations, stresses in soil

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Authors: Hendradi Hardhienata, Tony Sumaryada, Sri Setyaningsih

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Current progress in the field of nonlinear optics has enabled precise surface characterization in semiconductor materials. Nonlinear optical techniques are favorable due to their nondestructive measurement and ability to work in nonvacuum and ambient conditions. The advance of the bond hyperpolarizability models opens a wide range of nanoscale surface investigation including the possibility to detect molecular orientation at the surface of silicon and zincblende semiconductors, investigation of electric field induced second harmonic fields at the semiconductor interface, detection of surface impurities, and very recently, study surface defects such as twin boundary in wurtzite semiconductors. In this work, we show using nonlinear optical techniques, e.g. nonlinear bond models how arbitrary polarization of the incoming electric field in Rotational Anisotropy Spectroscopy experiments can provide more information regarding the origin of the nonlinear sources in zincblende and wurtzite semiconductor structure. In addition, using hyperpolarizability consideration, we describe how the nonlinear susceptibility tensor describing SHG can be well modelled using only few parameter because of the symmetry of the bonds. We also show how the third harmonic intensity feature shows considerable changes when the incoming field polarization angle is changed from s-polarized to p-polarized. We also propose a method how to investigate surface reconstruction and defects in wurtzite and zincblende structure at the nanoscale level.

Keywords: surface characterization, bond model, rotational anisotropy spectroscopy, effective hyperpolarizability

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Authors: Khairul Bariah Sulaiman, Tajul Aris Yang

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Malaysian dried cocoa beans have been reported to have low quality flavour and are often sold at discounted prices. Various efforts have been made to improve the Malaysian beans quality. Among these efforts is introduction of the shallow box fermentation technique and pulp preconditioned through pods storage. However, after nearly four decades of the effort was done, Malaysian cocoa farmers still received lower prices for their beans. So, this study was carried out in order to assess the flavour quality of dried cocoa beans produced by shallow box fermentation techniques, combination of shallow box fermentation with pods storage and compared to dried cocoa beans obtained from Ghana. A total of eight samples of dried cocoa was used in this study, which one of the samples was Ghanaian beans (coded with no.8), while the rest were Malaysian cocoa beans with different post-harvest processing (coded with no. 1, 2, 3, 4, 5, 6 and 7). Cocoa liquor was prepared from all samples in the prescribed techniques and sensory evaluation was carried out using Quantitative Descriptive Analysis (QDA) Method with 0-10 scale by Malaysian Cocoa Board trained panelist. Sensory evaluation showed that cocoa attributes for all cocoa liquors ranging from 3.5 to 5.3, whereas bitterness was ranging from 3.4 to 4.6 and astringent attribute ranging from 3.9 to 5.5, respectively. Meanwhile, all cocoa liquors were having acid or sourness attribute ranging from 1.6 to 3.6, respectively. In general cocoa liquor prepared from sample coded no 4 has almost similar flavour profile and no significantly different at p < 0.05 with Ghana, in term of most flavour attributes as compared to the other six samples.

Keywords: cocoa beans, flavour, fermentation, shallow box, pods storage

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Authors: Masoomeh Alsadat Mirshafaei

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The present study aims to explore the effect of an 8-week aerobic training regimen combined with cinnamon extract on serum irisin and leptin levels in insulin-resistant rats. Additionally, this research leverages various machine learning (ML) and deep learning (DL) algorithms to model the complex interdependencies between exercise, nutrition, and metabolic markers, offering a groundbreaking approach to obesity and diabetes research. Forty-eight Wistar rats were selected and randomly divided into four groups: control, training, cinnamon, and training cinnamon. The training protocol was conducted over 8 weeks, with sessions 5 days a week at 75-80% VO2 max. The cinnamon and training-cinnamon groups were injected with 200 ml/kg/day of cinnamon extract. Data analysis included serum data, dietary intake, exercise intensity, and metabolic response variables, with blood samples collected 72 hours after the final training session. The dataset was analyzed using one-way ANOVA (P<0.05) and fed into various ML and DL models, including Support Vector Machines (SVM), Random Forest (RF), and Convolutional Neural Networks (CNN). Traditional statistical methods indicated that aerobic training, with and without cinnamon extract, significantly increased serum irisin and decreased leptin levels. Among the algorithms, the CNN model provided superior performance in identifying specific interactions between cinnamon extract concentration and exercise intensity, optimizing the increase in irisin and the decrease in leptin. The CNN model achieved an accuracy of 92%, outperforming the SVM (85%) and RF (88%) models in predicting the optimal conditions for metabolic marker improvements. The study demonstrated that advanced ML and DL techniques could uncover nuanced relationships and potential cellular responses to exercise and dietary supplements, which is not evident through traditional methods. These findings advocate for the integration of advanced analytical techniques in nutritional science and exercise physiology, paving the way for personalized health interventions in managing obesity and diabetes.

Keywords: aerobic training, cinnamon extract, insulin resistance, irisin, leptin, convolutional neural networks, exercise physiology, support vector machines, random forest

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Authors: S. M. Shahinul Islam, Israt Ara, Narendra Tuteja, Sreeramanan Subramaniam

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Through anther and microspore culture methods, complete homozygous plants can be produced within a year as compared to the long inbreeding method. Isolated microspore culture is one of the most important techniques for rapid development of haploid plants. The efficiency of this method is influenced by several factors such as cultural conditions, growth regulators, plant media, pretreatments, physical and growth conditions of the donor plants, pollen isolation procedure, etc. The main purpose of this study was to improve the isolated microspore culture protocol in order to increase the efficiency of embryoids, its regeneration and reducing albinisms. Under this study we have tested mainly three different microspore isolation procedures by glass rod, homozeniger and by blending and found the efficiency on gametic embryogenesis. There are three types of media viz. washing, pre-culture and induction was used. The induction medium as AMC (modified MS) supplemented by 2, 4-D (2.5 mg/l), kinetin (0.5 mg/l) and higher amount of D-Manitol (90 g/l) instead of sucrose and two types of amino acids (L-glutamine and L-serine) were used. Out of three main microspore isolation procedure by homogenizer isolation (P4) showed best performance on ELS induction (177%) and green plantlets (104%) compared with other techniques. For all cases albinisims occurred but microspore isolation from excised anthers by glass rod and homogenizer showed lesser numbers of albino plants that was also one of the important findings in this study.

Keywords: androgenesis, pretreatment, microspore culture, regeneration, albino plants, Oryza sativa

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Authors: Leticia Cervantes, Edith Garcia, Oscar Castillo

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At today, there are several control problems where the main objective is to obtain the best control in the study to decrease the error in the application. Many techniques can use to control these problems such as Neural Networks, PID control, Fuzzy Logic, Optimization techniques and many more. In this case, fuzzy logic with fuzzy system and an optimization technique are used to control the case of study. In this case, Ant Lion Optimization is used to optimize a fuzzy system to control the velocity of a simple treadmill. The main objective is to achieve the control of the velocity in the control problem using the ALO optimization. First, a simple fuzzy system was used to control the velocity of the treadmill it has two inputs (error and error change) and one output (desired speed), then results were obtained but to decrease the error the ALO optimization was developed to optimize the fuzzy system of the treadmill. Having the optimization, the simulation was performed, and results can prove that using the ALO optimization the control of the velocity was better than a conventional fuzzy system. This paper describes some basic concepts to help to understand the idea in this work, the methodology of the investigation (control problem, fuzzy system design, optimization), the results are presented and the optimization is used for the fuzzy system. A comparison between the simple fuzzy system and the optimized fuzzy systems are presented where it can be proving the optimization improved the control with good results the major findings of the study is that ALO optimization is a good alternative to improve the control because it helped to decrease the error in control applications even using any control technique to optimized, As a final statement is important to mentioned that the selected methodology was good because the control of the treadmill was improve using the optimization technique.

Keywords: ant lion optimization, control problem, fuzzy control, fuzzy system

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Authors: Samaneh Nabavi, Hadi Shirzad, Somayeh Khanjani, Shirin Jalili

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Quantum dots (QDs) are semiconductor nanocrystals that exhibit intrinsic optical and electrical properties that are size dependent due to the quantum confinement effect. Quantum confinement is brought about by the fact that in bulk semiconductor material the electronic structure consists of continuous bands, and that as the size of the semiconductor material decreases its radius becomes less than the Bohr exciton radius (the distance between the electron and electron-hole) and discrete energy levels result. As a result QDs have a broad absorption range and a narrow emission which correlates to the band gap energy (E), and hence QD size. QDs can thus be tuned to give the desired wavelength of fluorescence emission.Due to their unique properties, QDs have attracted considerable attention in different scientific areas. Also, they have been considered for forensic applications in recent years. The ability of QDs to fluoresce up to 20 times brighter than available fluorescent dyes makes them an attractive nanomaterial for enhancing the visualization of latent fingermarks, or poorly developed fingermarks. Furthermore, the potential applications of QDs in the detection of nitroaromatic explosives, such as TNT, based on directive fluorescence quenching of QDs, electron transfer quenching process or fluorescence resonance energy transfer have been paid to attention. DNA analysis is associated tightly with forensic applications in molecular diagnostics. The amount of DNA acquired at a criminal site is inherently limited. This limited amount of human DNA has to be quantified accurately after the process of DNA extraction. Accordingly, highly sensitive detection of human genomic DNA is an essential issue for forensic study. QDs have also a variety of advantages as an emission probe in forensic DNA quantification.

Keywords: forensic science, quantum dots, DNA typing, explosive sensor, fingermark analysis

Procedia PDF Downloads 857

Authors: Kholood Baron

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Radiologic interventional studies use fluoroscopy imaging guidance to perform both diagnostic and therapeutic procedures. These could result in high radiation doses being delivered to the patients and also to the radiology team. This is due to the prolonged fluoroscopy time and the large number of images taken, even when dose-minimizing techniques and modern fluoroscopic tools are applied. Hence, these procedures are part of the everyday routine of interventional radiology doctors, assistant nurses, and radiographers. Thus, it is important to estimate the radiation exposure dose they received in order to give objective advice and reduce both patient and radiology team radiation exposure dose. The aim of this study was to find out the total radiation dose reaching the radiologist and the patient during an interventional procedure and to determine the impact of certain parameters on the patient dose. Method: The radiation dose was measured by TLD devices (thermoluminescent dosimeter; radiation dosimeter device). Physicians, patients, nurses, and radiographers wore TLDs during 12 interventional radiology procedures performed in two hospitals, Mubarak and Chest Hospital. This study highlights the need for interventional radiologists to be mindful of the radiation doses received by both patients and medical staff during interventional radiology procedures. The findings emphasize the impact of factors such as fluoroscopy duration and the number of images taken on the patient dose. By raising awareness and providing insights into optimizing techniques and protective measures, this research contributes to the overall goal of reducing radiation doses and ensuring the safety of patients and medical staff.

Keywords: dosimetry, radiation dose, interventional radiology procedures, patient radiation dose

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Authors: Armagan Gokcearslan

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The art of animation has developed very rapidly from the aspects of script, sound and music, motion, character design, techniques being used and technological tools being developed since the first years until today. Technical variety attracts a particular attention in the art of animation. Being perceived as a kind of illusion in the beginning; animations commonly used the Flash Sketch technique. Animations artists using the Flash Sketch technique created scenes by drawing them on a blackboard with chalk. The Flash Sketch technique was used by primary animation artists like Emile Cohl, Winsor McCay ande Blackton. And then tools like Magical Lantern, Thaumatrope, Phenakisticope, and Zeotrap were developed and started to be used intensely in the first years of the art of animation. Today, on the other hand, the art of animation is affected by developments in the computer technology. It is possible to create three-dimensional and two-dimensional animations with the help of various computer software. Cut-out technique is among the important techniques being used in the art of animation. Cut-out animation technique is based on the art of paper cutting. Examining cut-out animations; it is observed that they technically resemble the art of paper cutting. The art of paper cutting has a rooted history. It is possible to see the oldest samples of paper cutting in the People’s Republic of China in the period after the 2. century B.C. when the Chinese invented paper. The most popular artist using the cut-out animation technique is the German artist Lotte Reiniger. This study titled “Cut-out Animation as a Technic and Development Inside History Process” will embrace the art of paper cutting, the relationship between the art of paper cutting and cut-out animation, its development within the historical process, animation artists producing artworks in this field, important cut-out animations, and their technical properties.

Keywords: cut-out, paper art, animation, technic

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