Search results for: processing schemes

Authors: Ayhan Kucukmanisa, Orhan Akbulut, Oguzhan Urhan

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Nowadays, advanced driver assistance systems (ADAS) have become popular, since they enable safe driving. Lane detection is a vital step for ADAS. The performance of the lane detection process is critical to obtain a high accuracy lane departure warning system (LDWS). Challenging factors such as road cracks, erosion of lane markings, weather conditions might affect the performance of a lane detection system. In this paper, 1-D weighted filter based on row filtering to detect lane marking is proposed. 2-D input image is filtered by 1-D weighted filter considering four-pixel values located symmetrically around the center of candidate pixel. Performance evaluation is carried out by two metrics which are true positive rate (TPR) and false positive rate (FPR). Experimental results demonstrate that the proposed approach provides better lane marking detection accuracy compared to the previous methods while providing real-time processing performance.

Keywords: lane marking filter, lane detection, ADAS, LDWS

Procedia PDF Downloads 193

Authors: Ava Salmanpour, Hanieh Saeedi, Payam Rouhi, Elahe Hamzeil, Shima Alimohammadi, Siamak Hossein Khalaj, Mohammad Asadian

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Software-defined network (SDN) is a network architecture designed to control network using software application in a central manner. This ability enables remote control of the whole network regardless of the network technology. In fact, in this architecture network intelligence is separated from physical infrastructure, it means that required network components can be implemented virtually using software applications. Today, power networks are characterized by a high range of complexity with a large number of intelligent devices, processing both huge amounts of data and important information. Therefore, reliable and secure communication networks are required. SDNs are the best choice to meet this issue. In this paper, SDN networks capabilities and characteristics will be reviewed and different basic controllers will be compared. The importance of using SDNs to escalate efficiency and reliability in utility power networks is going to be discussed and the comparison between the SDN-based power networks and traditional networks will be explained.

Keywords: software-defined network, SDNs, utility network, open flow, communication, gas and electricity, controller

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Authors: Maryam Fallahpoor, Biswajeet Pradhan

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Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

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Authors: Amirhossein Safi

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Internet of things (IOT) is a kind of advanced information technology which has drawn societies’ attention. Sensors and stimulators are usually recognized as smart devices of our environment. Simultaneously, IOT security brings up new issues. Internet connection and possibility of interaction with smart devices cause those devices to involve more in human life. Therefore, safety is a fundamental requirement in designing IOT. IOT has three remarkable features: overall perception, reliable transmission, and intelligent processing. Because of IOT span, security of conveying data is an essential factor for system security. Hybrid encryption technique is a new model that can be used in IOT. This type of encryption generates strong security and low computation. In this paper, we have proposed a hybrid encryption algorithm which has been conducted in order to reduce safety risks and enhancing encryption's speed and less computational complexity. The purpose of this hybrid algorithm is information integrity, confidentiality, non-repudiation in data exchange for IOT. Eventually, the suggested encryption algorithm has been simulated by MATLAB software, and its speed and safety efficiency were evaluated in comparison with conventional encryption algorithm.

Keywords: internet of things, security, hybrid algorithm, privacy

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Authors: K. Bensafia, A. Mansour, G. Le Maillot, B. Clement, O. Reynet, P. Ariès, S. Haddab

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This paper presents a system designed for wireless acquisition, the recording of electrocardiogram (ECG) signals and the monitoring of the heart’s health during surgery. This wireless recording system allows us to visualize and monitor the state of the heart’s health during a surgery, even if the patient is moved from the operating theater to post anesthesia care unit. The acquired signal is transmitted via a Bluetooth unit to a PC where the data are displayed, stored and processed. To test the reliability of our system, a comparison between ECG signals processed by a conventional ECG monitoring system (Datex-Ohmeda) and by our wireless system is made. The comparison is based on the shape of the ECG signal, the duration of the QRS complex, the P and T waves, as well as the position of the ST segments with respect to the isoelectric line. The proposed system is presented and discussed. The results have confirmed that the use of Bluetooth during surgery does not affect the devices used and vice versa. Pre- and post-processing steps are briefly discussed. Experimental results are also provided.

Keywords: electrocardiography, monitoring, surgery, wireless system

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Authors: Barbara Heinisch, Mikael Snaprud

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A common, well understood language is crucial in critical situations like landing a plane. For e-Government solutions, a clear and common language is needed to allow users to successfully complete transactions online. Misunderstandings here may not risk a safe landing but can cause delays, resubmissions and drive costs. This holds also true for higher education, where misunderstandings can also arise due to inconsistent use of terminology. Thus, language barriers are a societal challenge that needs to be tackled. The major means to bridge language barriers is translation. However, achieving high-quality translation and making texts understandable and accessible require certain framework conditions. Therefore, the EU and individual projects take (strategic) actions. These actions include the identification, collection, processing, re-use and development of language resources. These language resources may be used for the development of machine translation systems and the provision of (public) services including higher education. This paper outlines some of the existing resources and indicate directions for further development to increase the quality and usage of these resources.

Keywords: language resources, machine translation, terminology, translation

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Authors: Hanna Lu, Sandra S. M. Chan, Linda C. W. Lam

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Objectives: Intra-individual variability (IIV) has been considered as a biomarker of healthy ageing. However, the composite role of IIV in attention, as an impending indicator for neurocognitive disorders warrants further exploration. This study aims to investigate the IIV, as well as their relationships with attention network functions in adults with neurocognitive disorders (NCD). Methods: 36adults with NCD due to Alzheimer’s disease(NCD-AD), 31adults with NCD due to vascular disease (NCD-vascular), and 137 healthy controls were recruited. Intraindividual standard deviations (iSD) and intraindividual coefficient of variation of reaction time (ICV-RT) were used to evaluate the IIV. Results: NCD groups showed greater IIV (iSD: F= 11.803, p < 0.001; ICV-RT:F= 9.07, p < 0.001). In ROC analyses, the indices of IIV could differentiateNCD-AD (iSD: AUC value = 0.687, p= 0.001; ICV-RT: AUC value = 0.677, p= 0.001) and NCD-vascular (iSD: AUC value = 0.631, p= 0.023;ICV-RT: AUC value = 0.615, p= 0.045) from healthy controls. Moreover, the processing speed could distinguish NCD-AD from NCD-vascular (AUC value = 0.647, p= 0.040). Discussion: Intra-individual variability in attention provides a stable measure of cognitive performance, and seems to help distinguish the senior adults with different cognitive status.

Keywords: intra-individual variability, attention network, neurocognitive disorders, ageing

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Authors: Mohammed Abed, Rita Nemes, Salem Nehme

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The present study experimentally investigated the impact of incorporating unprocessed waste fly ash (UWFA) on the residual mechanical properties of self-compacting concrete (SCC) after exposure to elevated temperature. Three mixtures of SCC have been produced by replacing the cement mass by 0%, 15% and 30% of UWFA. Generally, the fire resistance of SCC has been enhanced by replacing the cement up to 15% of UWFA, especially in case of residual modulus of elasticity which considers more sensitive than other mechanical properties at elevated temperature. However, a strong linear relationship has been observed between the residual flexural strength and modulus of elasticity, where both of them affected significantly by the cracks appearance and propagation as a result of elevated temperature. Sustainable products could be produced by incorporating unprocessed waste powder materials in the production of concrete, where the waste materials, CO₂ emissions, and the energy needed for processing are reduced.

Keywords: self-compacting high-performance concrete, unprocessed waste fly ash, fire resistance, residual modulus of elasticity

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Authors: R. R. Ali, W. A. W. A. Rahman, R. M. Kasmani, H. Hasbullah, N. Ibrahim, A. N. Sadikin, U. A. Asli

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In this study, tapioca starch which acts as natural polymer was added in the blend in order to produce biodegradable product. Low density polyethylene (LDPE) and tapioca starch blends were prepared by extrusion and the test sample by injection moulding process. Ethylene vinyl acetate (EVA) acts as compatibilizer while glycerol as processing aid was added in the blend. The blends were characterized by using melt flow index (MFI), fourier transform infrared (FTIR) and the effects of water absorption to the sample. As the starch content increased, MFI of the blend was decreased. Tensile testing were conducted shows the tensile strength and elongation at break decreased while the modulus increased as the starch increased. For the biodegradation, soil burial test was conducted and the loss in weight was studied as the starch content increased. Morphology studies were conducted in order to show the distribution between LDPE and starch.

Keywords: biopolymers, degradable polymers, starch based polyethylene, injection moulding

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Authors: Armineh Nourbakhsh, Sameena Shah, Carolyn Rose

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Layout-aware language models have been used to create multimodal representations for documents that are in image form, achieving relatively high accuracy in document understanding tasks. However, the large number of parameters in the resulting models makes building and using them prohibitive without access to high-performing processing units with large memory capacity. We propose an alternative approach that can create efficient representations without the need for a neural visual backbone. This leads to an 80% reduction in the number of parameters compared to the smallest SOTA model, widely expanding applicability. In addition, our layout embeddings are pre-trained on spatial and visual cues alone and only fused with text embeddings in downstream tasks, which can facilitate applicability to low-resource of multi-lingual domains. Despite using 2.5% of training data, we show competitive performance on two form understanding tasks: semantic labeling and link prediction.

Keywords: layout understanding, form understanding, multimodal document understanding, bias-augmented attention

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Authors: Ganesh V., Asit Kumar Khanra

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An in-situ powder metallurgy technique was employed to create Ni-Al3Ni/Al3Ni2 core-shell-shaped aluminum-based intermetallic reinforced composites. The impact of Ni addition on the phase composition, microstructure, and mechanical characteristics of the Al-4Cu-xNi (x = 0, 2, 4, 6, 8, 10 wt.%) in relation to various sintering temperatures was investigated. Microstructure evolution was extensively examined using X-ray diffraction (XRD), scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX), and transmission electron microscopy (TEM) techniques. Initially, under sintering conditions, the formation of "Single Core-Shell" structures was observed, consisting of Ni as the core with Al3Ni2 intermetallic, whereas samples sintered at 620°C exhibited both "Single Core-Shell" and "Double Core-Shell" structures containing Al3Ni2 and Al3Ni intermetallics formed between the Al matrix and Ni reinforcements. The composite achieved a high compressive yield strength of 198.13 MPa and ultimate strength of 410.68 MPa, with 24% total elongation for the sample containing 10 wt.% Ni. Additionally, there was a substantial increase in hardness, reaching 124.21 HV, which is 2.4 times higher than that of the base aluminum. Nanoindentation studies showed hardness values of 1.54, 4.65, 21.01, 13.16, 5.52, 6.27, and 8.39GPa corresponding to α-Al matrix, Ni, Al3Ni2, Ni and Al3Ni2 interface, Al3Ni, and their respective interfaces. Even at 200°C, it retained 54% of its room temperature strength (90.51 MPa). To investigate the deformation behavior of the composite material, experiments were conducted at deformation temperatures ranging from 300°C to 500°C, with strain rates varying from 0.0001s-1 to 0.1s-1. A sine-hyperbolic constitutive equation was developed to characterize the flow stress of the composite, which exhibited a significantly higher hot deformation activation energy of 231.44 kJ/mol compared to the self-diffusion of pure aluminum. The formation of Al2Cu intermetallics at grain boundaries and Al3Ni2/Al3Ni within the matrix hindered dislocation movement, leading to an increase in activation energy, which might have an adverse effect on high-temperature applications. Two models, the Strain-compensated Arrhenius model and the Artificial Neural Network (ANN) model, were developed to predict the composite's flow behavior. The ANN model outperformed the Strain-compensated Arrhenius model with a lower average absolute relative error of 2.266%, a smaller root means square error of 1.2488 MPa, and a higher correlation coefficient of 0.9997. Processing maps revealed that the optimal hot working conditions for the composite were in the temperature range of 420-500°C and strain rates between 0.0001s-1 and 0.001s-1. The changes in the composite microstructure were successfully correlated with the theory of processing maps, considering temperature and strain rate conditions. The uneven distribution in the shape and size of Core-shell/Al3Ni intermetallic compounds influenced the flow stress curves, leading to Dynamic Recrystallization (DRX), followed by partial Dynamic Recovery (DRV), and ultimately strain hardening. This composite material shows promise for applications in the automobile and aerospace industries.

Keywords: core-shell structure, hot deformation, intermetallic compounds, powder metallurgy

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Authors: A. Biran, P. Sobhe Bidari, K. Raahemifar

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Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.

Keywords: diabetic retinopathy, fundus, CHT, exudates, hemorrhages

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Authors: McClain Thiel

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Object detection and localization has historically required two or more sensors due to the loss of information from 3D to 2D space, however, most surveillance systems currently in use in the real world only have one sensor per location. Generally, this consists of a single low-resolution camera positioned above the area under observation (mall, jewelry store, traffic camera). This is not sufficient for robust 3D tracking for applications such as security or more recent relevance, contract tracing. This paper proposes a lightweight system for 3D person tracking that requires no additional hardware, based on compressed object detection convolutional-nets, facial landmark detection, and projective geometry. This approach involves classifying the target into a demographic category and then making assumptions about the relative locations of facial landmarks from the demographic information, and from there using simple projective geometry and known constants to find the target's location in 3D space. Preliminary testing, although severely lacking, suggests reasonable success in 3D tracking under ideal conditions.

Keywords: monocular distancing, computer vision, facial analysis, 3D localization

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Authors: Felicisimo Azagra Tejuco Jr.

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Mentoring architecture thesis students is a very critical and exhausting task for both the adviser and advisee. It poses the challenges of resource and time management for the candidate while the best professional guidance from the mentor. The University of Santo Tomas (Manila, Philippines) is Asia's oldest university. Among its notable program is its Architecture curriculum. Presently, the five-year Architecture program requires ten semesters of academic coursework. The last three semesters are relevant to each Architecture graduating student's thesis proposal and defense. The thesis proposal is developed and submitted for approval in the subject Research Methods for Architecture (RMA). Data gathering and initial schemes are conducted in Architectural Design (AD), 9, and are finalized and defended in AD 10. In recent years, their graduating students have maintained an average of 300 candidates before the pandemic. They are encouraged to explore any topic of interest or relevance. Since 2019-2020, one thesis class has used a community planning approach in mentoring the class. Compared to other sections, the first meeting of RMA has been allocated for a visioning exercise and assessment of the class's strengths-weaknesses and opportunities-threats (SWOT). Here, the work activities of the group have been finetuned to address some identified concerns while still being aligned with the academic calendar. Occasional peer critics complement class lectures. The course will end with the approval of the student's proposal. The final year or last two semesters of the graduating class will be focused on the approved proposal. Compared to the other class, the 18 weeks of the first semester consist of regular consultations, complemented by lectures from the adviser or guest speakers. Through remote peer consultations, the mentor maximized each meeting in groups of three to five, encouraging constructive criticism among the class. At the end of the first semester, mock presentations to the external jury are conducted to check the design outputs for improvement. The final semester is spent more on the finalization of the plans. Feedback from the previous semester is expected to be integrated into the final outputs. Before the final deliberations, at least two technical rehearsals were conducted per group. Regardless of the outcome, an assessment of each student's performance is held as a class. Personal realizations and observations are encouraged. Through Online surveys, Interviews, and Focused Group Discussions with the former students, the effectiveness of the mentoring strategies was reviewed and evaluated. Initial feedback highlighted the relevance of setting a positive tone for the course, constructive criticisms from peers & experts, and consciousness of deadlines as essential elements for a practical semester.

Keywords: cooperation, competition, student empowerment, class vision

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Authors: Jeoffrey Oostrom, Robbert James Schlingmann, Hani Alers

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This document depicts the research into the indicators of dementia progression, the automation of quality of life assignments, and the visualization of it. To do this, the Smart Teddy project was initiated to make a smart companion that both monitors the senior citizen as well as processing the captured data into an insightful dashboard. With around 50 million diagnoses worldwide, dementia proves again and again to be a bothersome strain on the lives of many individuals, their relatives, and society as a whole. In 2015 it was estimated that dementia care cost 818 billion U.S Dollars globally. The Smart Teddy project aims to take away a portion of the burden from caregivers by automating the collection of certain data, like movement, geolocation, and sound-levels. This paper proves that the Smart Teddy has the potential to become a useful tool for caregivers but won’t pose as a solution. The Smart Teddy still faces some problems in terms of emotional privacy, but its non-intrusive nature, as well as diversity in usability, can make up for it.

Keywords: dementia care, medical data visualization, quality of life, smart companion

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Authors: Jerome T. Tolentino, Ma. Victoria Rejuso, Jara Kaye Villanueva, Loureal Camille Inocencio, Ma. Rosario Concepcion O. Ang

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Wind energy is rapidly emerging as the primary source of electricity in the Philippines, although developing an accurate wind resource model is difficult. In this study, Weather Research and Forecasting (WRF) Model, an open source mesoscale Numerical Weather Prediction (NWP) model, was used to produce a 1-year atmospheric simulation with 4 km resolution on the Ilocos Region of the Philippines. The WRF output (netCDF) extracts the annual mean wind speed data using a Python-based Graphical User Interface. Lastly, wind resource assessment was produced using a GIS software. Results of the study showed that it is more flexible to use Python scripts than using other post-processing tools in dealing with netCDF files. Using WRF Model, Python, and Geographic Information Systems, a reliable wind resource map is produced.

Keywords: wind resource assessment, weather research and forecasting (WRF) model, python, GIS software

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Authors: Prasenjit Singha, Sunil Yadav, Soumya Ranjan Mohantry, Ajay Kumar Shukla

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Temperature distribution in the hematite ore mixed with 7.5% coal was predicted by solving a 1-D heat conduction equation using an implicit finite difference approach. In this work, it was considered a square slab of 20 cm x 20 cm, which assumed the coal to be uniformly mixed with hematite ore. It was solved the equations with the use of MATLAB 2018a software. Heat transfer effects in this 1D dimensional slab convective and the radiative boundary conditions are also considered. Temperature distribution obtained inside hematite slab by considering microwave heating time, thermal conductivity, heat capacity, carbon percentage, sample dimensions, and many other factors such as penetration depth, permittivity, and permeability of coal and hematite ore mixtures. The resulting temperature profile can be used as a guiding tool for optimizing the microwave-assisted carbothermal reduction process of hematite slab was extended to other dimensions as well, viz., 1 cm x 1 cm, 5 cm x 5 cm, 10 cm x 10 cm, 20 cm x 20 cm. The model predictions are in good agreement with experimental results.

Keywords: hematite ore, coal, microwave processing, heat transfer, implicit method, temperature distribution

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Authors: Gerald Steyn

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Despite the huge number of identical, tiny, boxy, freestanding houses built by the South African government after the advent of democracy in 1994, squatter camps continue to mushroom, and there is no evidence that the backlog is being reduced. Not only is the wasteful low-density detached-unit approach of the past being perpetuated, but the social, spatial, and economic marginalization is worse than before 1994. The situation is precarious since squatters are vulnerable to fires and flooding. At the same time, the occupants of the housing schemes are trapped far from employment opportunities or any public amenities. Despite these insecurities, the architectural, urban design, and city planning professions are puzzlingly quiet. Design projects address these issues only at the universities, albeit inevitably with somewhat Utopian notions. Geoffrey Payne, the renowned urban housing and urban development consultant and researcher focusing on issues in the Global South, once proclaimed that “we do not have a housing problem – we have a settlement problem.” This dictum was used as the guiding philosophy to conceptualize urban design and architectural principles that foreground the needs of low-income households and allow them to be fully integrated into the larger conurbation. Information was derived from intensive research over two decades, involving frequent visits to informal settlements, historic Black townships, and rural villages. Observations, measured site surveys, and interviews resulted in several scholarly articles from which a set of desirable urban and architectural criteria could be extracted. To formulate culturally appropriate design principles, existing vernacular and informal patterns were analyzed, reconciled with contemporary designs that align with the requirements for the envisaged settlement attributes, and reimagined as residential design principles. Five interrelated design principles are proposed, ranging in scale from (1) Integrating informal settlements into the city, (2) linear neighborhoods, (3) market streets as wards, (4) linear neighborhoods, and (5) typologies and densities for clustered and aggregated patios and courtyards. Each design principle is described, first in terms of its context and associated issues of concern, followed by a discussion of the patterns available to inform a possible solution, and finally, an explanation and graphic illustration of the proposed design. The approach is predominantly bottom-up since each of the five principles is unfolded from existing informal and vernacular practices studied in situ. They are, however, articulated and represented in terms of contemporary design language. Contrary to an idealized vision of housing for South Africa’s low-income urban households, this study proposes actual principles for critical assessment by peers in the tradition of architectural research in design.

Keywords: culturally appropriate design principles, informal settlements, South Africa’s housing backlog, squatter camps

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Authors: Sneha Noble, Rahul Krishnan, Uma G., D. K. Vijaykumar

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Breast-Cancer related Lymphedema is a major problem that affects many women. Lymphedema is the swelling that generally occurs in the arms or legs caused by the removal of or damage to lymph nodes as a part of cancer treatment. Treating it at the earliest possible stage is the best way to manage the condition and prevent it from leading to pain, recurrent infection, reduced mobility, and impaired function. So, this project aims to focus on the multi-modal approaches to identify the risks of Lymphedema in post-surgical oncology patients and prevent it at the earliest. The Kinect IR Sensor is utilized to capture the images of the body and after image processing techniques, the region of interest is obtained. Then, performing the voxelization method will provide volume measurements in pre-operative and post-operative periods in patients. The formation of a mathematical model will help in the comparison of values. Clinical pathological data of patients will be investigated to assess the factors responsible for the development of lymphedema and its risks.

Keywords: Kinect IR sensor, Lymphedema, voxelization, lymph nodes

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Authors: Hamid Fallah

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Asphalt is generally a mixture of stone materials with continuous granulation and a binder, which is usually bitumen. Asphalt is made in different shapes according to its use. The most familiar type of asphalt is hot asphalt or hot asphalt concrete. Stone materials usually make up more than 90% of the asphalt mixture. Therefore, stone materials have a significant impact on the quality of the resulting asphalt. According to the method of application and mixing, asphalt is divided into three categories: hot asphalt, protective asphalt, and cold asphalt. Cold mix asphalt is a mixture of stone materials and mixed bitumen or bitumen emulsion whose raw materials are mixed at ambient temperature. In some types of cold asphalt, the bitumen may be heated as necessary, but other materials are mixed with the bitumen without heating. Protective asphalts are used to make the roadbed impermeable, increase its abrasion and sliding resistance, and also temporarily improve the existing asphalt and concrete surfaces. This type of paving is very economical compared to hot asphalt due to the speed and ease of implementation and the limited need for asphalt machines and equipment. The present article, which is prepared in descriptive library form, introduces asphalt, its types, characteristics, and its application.

Keywords: asphalt, type of asphalt, asphalt concrete, sulfur concrete, bitumen in asphalt, sulfur, stone materials

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Authors: Oumaima Lahmar

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This paper aims to define a structured topography for finance researchers seeking to navigate the body of knowledge in their extrapolation of finance phenomena. To make sense of the body of knowledge in finance, a probabilistic topic modeling approach is applied on 6000 abstracts of academic articles published in three top journals in finance between 1976 and 2020. This approach combines both machine learning techniques and natural language processing to statistically identify the conjunctions between research articles and their shared topics described each by relevant keywords. The topic modeling analysis reveals 35 coherent topics that can well depict finance literature and provide a comprehensive structure for the ongoing research themes. Comparing the extracted topics to the Journal of Economic Literature (JEL) classification system, a significant similarity was highlighted between the characterizing keywords. On the other hand, we identify other topics that do not match the JEL classification despite being relevant in the finance literature.

Keywords: finance literature, textual analysis, topic modeling, perplexity

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Authors: Bernabeo R. Alberto

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With the tremendous improvements in the processing power of computers, the possibilities of artificial intelligence will increasingly be used in aviation and make autonomous flights, preventive maintenance, ATM (Air Traffic Management) optimization, pilots, cabin crew, ground staff, and airport staff training possible in a cost-saving, less time-consuming and less polluting way. Through the use of artificial intelligence, we foresee an interviewing scenario where the interviewee will interact with the artificial intelligence tool to contextualize the character and the necessary information in a way that aligns reasonably with the character and the scenario. We are creating simulated scenarios connected with either an aviation incident or accident to enhance also the training of future accident/incident investigators integrating artificial intelligence and augmented reality tools. The project's goal is to improve the learning and teaching scenario through academic and professional expertise in aviation and in the artificial intelligence field. Thus, we intend to contribute to the needed high innovation capacity, skills, and training development and management of artificial intelligence, supported by appropriate regulations and attention to ethical problems.

Keywords: artificial intelligence, aviation accident, aviation incident, risk, safety

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Authors: Manisha Ohlan, Manju Dahiya

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The present study was conducted in Karnal, Rohtak, and Jhajjar districts of Haryana state, covering 360 respondents. Results showed that 42.78 percent of the respondents had above average knowledge at the preparation stage followed by 48.33 percent of the respondents who had high knowledge at the production stage, and 37.22 percent of the respondents had average knowledge at the processing stage regarding the usage of digital technologies. Nearly half of the respondents (47.50%) agreed with the usage of digital technologies, followed by strongly agreed (19.45%) and strongly disagreed (14.45%). A significant and positive relationship was found between independent variables and knowledge and of digital technologies at 5 percent level of significance. Therefore, the null hypothesis cannot be rejected. All the dependent variables, including knowledge and attitude, had a significant and positive relationship with z value at 5 percent level of significance, which showed that it is between -1.96 to +1.96; therefore, the data falls between the acceptance region, that’s why the null hypothesis is accepted.

Keywords: knowledge, attitude, digital technologies, significant, positive relationship

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Authors: F. Stephen Joe, V. Sathya Narayanan, V. R. Sanal Kumar

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A comprehensive review of the literature on photovoltaic cells has been carried out for exploring the better options for cost efficient technologies for future solar cell applications. Literature review reveals that the Bulk Heterojunction (BHJ) Polymer Solar cells offer special opportunities as renewable energy resources. It is evident from the previous studies that the device fabricated with TiOx layer shows better power conversion efficiency than that of the device without TiOx layer. In this paper, authors designed a controlled BHJ solar cell using a modified organic vapor spray deposition technique facilitated with a vertical-moving gun named as 'Stephen Joe Technique' for getting a desirable surface pattern over the substrate to improving its efficiency over the years for industrial applications. We comprehended that the efficient processing and the interface engineering of these solar cells could increase the efficiency up to 5-10 %.

Keywords: BHJ polymer solar cell, photovoltaic cell, solar cell, Stephen Joe technique

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Authors: Amara Rafik, Mostefa Belhadj Aissa

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Radar data is one of the many data sources used by ATM Air Traffic Management systems. These data come from air navigation radar antennas. These radars intercept signals emitted by the various aircraft crossing the controlled airspace and calculate the position of these aircraft and retransmit their positions to the Air Traffic Management System. For greater reliability, these radars are positioned in such a way as to allow their coverage areas to overlap. An aircraft will therefore be detected by at least one of these radars. However, the position coordinates of the same aircraft and sent by these different radars are not necessarily identical. Therefore, the ATM system must calculate a single position (radar track) which will ultimately be sent to the control position and displayed on the air traffic controller's monitor. There are several techniques for calculating the radar track. Furthermore, the geographical nature of the problem requires the use of a Geographic Information System (GIS), i.e. a geographical database on the one hand and geographical processing. The objective of this work is to propose a GIS for traffic simulation which reconstructs the evolution over time of aircraft positions from a multi-source radar data set and by applying these different techniques.

Keywords: ATM, GIS, radar data, simulation

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Authors: Zzibu Mark Brian

Abstract:

As software systems become increasingly complex, ensuring code security is a growing concern. Traditional vulnerability detection methods often rely on manual code reviews or static analysis tools, which can be time-consuming and prone to errors. This paper presents a distinct approach to enhancing code security by leveraging artificial intelligence (AI) and machine learning (ML) techniques. Our proposed system utilizes a combination of natural language processing (NLP) and deep learning algorithms to identify and classify vulnerabilities in real-world codebases. By analyzing vast amounts of open-source code data, our AI-powered tool learns to recognize patterns and anomalies indicative of security weaknesses. We evaluated our system on a dataset of over 10,000 open-source projects, achieving an accuracy rate of 92% in detecting known vulnerabilities. Furthermore, our tool identified previously unknown vulnerabilities in popular libraries and frameworks, demonstrating its potential for improving software security.

Keywords: AI, machine language, cord security, machine leaning

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Authors: Surabhi Maiti, Prajakta Tamhankar, Prachi Uttam Mehta

Abstract:

Since the accomplishment of the Human Genome Project, there has been an unparalled escalation in the sequencing of genomic data. This project has been the first major vault in the field of medical research, especially in genomics. This project won accolades by using a concept called Bigdata which was earlier, extensively used to gain value for business. Bigdata makes use of data sets which are generally in the form of files of size terabytes, petabytes, or exabytes and these data sets were traditionally used and managed using excel sheets and RDBMS. The voluminous data made the process tedious and time consuming and hence a stronger framework called Hadoop was introduced in the field of genetic sciences to make data processing faster and efficient. This paper focuses on using SPARK which is gaining momentum with the advancement of BigData technologies. Cloud Storage is an effective medium for storage of large data sets which is generated from the genetic research and the resultant sets produced from SPARK analysis.

Keywords: human genome project, Bigdata, genomic data, SPARK, cloud storage, Hadoop

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Authors: M. Hilani, B. Nassih

Abstract:

Phishing is one of the oldest and best known scams on the Internet. It can be defined as any type of telecommunications fraud that uses social engineering tricks to obtain confidential data from its victims. It’s a cybercrime aimed at stealing your sensitive information. Phishing is generally done via private email, so scammers impersonate large companies or other trusted entities to encourage victims to voluntarily provide information such as login credentials or, worse yet, credit card numbers. The COVID-19 theme is used by cybercriminals in multiple malicious campaigns like phishing. In this environment, messaging filtering solutions have become essential to protect devices that will now be used outside of the secure perimeter. Despite constantly updating methods to avoid these cyberattacks, the end result is currently insufficient. Many researchers are looking for optimal solutions to filter phishing emails, but we still need good results. In this work, we concentrated on solving the problem of detecting phishing emails using the different steps of NLP preprocessing, and we proposed and trained a model using one-dimensional CNN. Our study results show that our model obtained an accuracy of 99.99%, which demonstrates how well our model is working.

Keywords: phishing, e-mail, NLP preprocessing, CNN, e-mail filtering

Procedia PDF Downloads 126

Authors: Liana Lortkipanidze, Nino Amirezashvili, Nino Javashvili

Abstract:

The purpose of the grammatical dictionary is to provide information on the morphological and syntactic characteristics of the basic word in the dictionary entry. The electronic grammatical dictionaries are used as a tool of automated morphological analysis for texts processing. The Georgian Grammatical Dictionary should contain grammatical information for each word: part of speech, type of declension/conjugation, grammatical forms of the word (paradigm), alternative variants of basic word/lemma. In this paper, we present the system for compiling the Georgian Grammatical Dictionary automatically. We propose dictionary-based methods for extending grammatical lexicons. The input lexicon contains only a few number of words with identical grammatical features. The extension is based on similarity measures between features of words; more precisely, we add words to the extended lexicons, which are similar to those, which are already in the grammatical dictionary. Our dictionaries are corpora-based, and for the compiling, we introduce the method for lemmatization of unknown words, i.e., words of which neither full form nor lemma is in the grammatical dictionary.

Keywords: acquisition of lexicon, Georgian grammatical dictionary, lemmatization rules, morphological processor

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Authors: Omar Faruqe Hamim, M. Shamsul Hoque, Rich C. McIlroy, Katherine L. Plant, Neville A. Stanton

Abstract:

Road safety has become an alarming issue, especially in low-middle income developing countries. The traditional approaches lack the out of the box thinking, making engineers confined to applying usual techniques in making roads safer. A socio-technical approach has recently been introduced in improving road intersections through designing with intent. This Design With Intent (DWI) approach aims to give practitioners a more nuanced approach to design and behavior, working with people, people’s understanding, and the complexities of everyday human experience. It's a collection of design patterns —and a design and research approach— for exploring the interactions between design and people’s behavior across products, services, and environments, both digital and physical. Through this approach, it can be seen that how designing with people in behavior change can be applied to social and environmental problems, as well as commercially. It has a total of 101 cards across eight different lenses, such as architectural, error-proofing, interaction, ludic, perceptual, cognitive, Machiavellian, and security lens each having its own distinct characteristics of extracting ideas from the participant of this approach. For this research purpose, a three-legged accident blackspot intersection of a national highway has been chosen to perform the DWI workshop. Participants from varying fields such as civil engineering, naval architecture and marine engineering, urban and regional planning, and sociology actively participated for a day long workshop. While going through the workshops, the participants were given a preamble of the accident scenario and a brief overview of DWI approach. Design cards of varying lenses were distributed among 10 participants and given an hour and a half for brainstorming and generating ideas to improve the safety of the selected intersection. After the brainstorming session, the participants spontaneously went through roundtable discussions regarding the ideas they have come up with. According to consensus of the forum, ideas were accepted or rejected. These generated ideas were then synthesized and agglomerated to bring about an improvement scheme for the intersection selected in our study. To summarize the improvement ideas from DWI approach, color coding of traffic lanes for separate vehicles, channelizing the existing bare intersection, providing advance warning traffic signs, cautionary signs and educational signs motivating road users to drive safe, using textured surfaces at approach with rumble strips before the approach of intersection were the most significant one. The motive of this approach is to bring about new ideas from the road users and not just depend on traditional schemes to increase the efficiency, safety of roads as well and to ensure the compliance of road users since these features are being generated from the minds of users themselves.

Keywords: design with intent, road safety, human experience, behavior

Procedia PDF Downloads 139