Search results for: and model-based techniques

Authors: Yousif Mohamed Y. Abdallah, Razan Manofely, Rajab M. Ben Yousef

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X-Ray images are very popular as a first tool for diagnosis. Automating the process of analysis of such images is important in order to help physician procedures. In this practice, teeth segmentation from the radiographic images and feature extraction are essential steps. The main objective of this study was to study correction preprocessing of x-rays images using local adaptive filters in order to evaluate contrast enhancement pattern in different x-rays images such as grey color and to evaluate the usage of new nonlinear approach for contrast enhancement of soft tissues in x-rays images. The data analyzed by using MatLab program to enhance the contrast within the soft tissues, the gray levels in both enhanced and unenhanced images and noise variance. The main techniques of enhancement used in this study were contrast enhancement filtering and deblurring images using the blind deconvolution algorithm. In this paper, prominent constraints are firstly preservation of image's overall look; secondly, preservation of the diagnostic content in the image and thirdly detection of small low contrast details in diagnostic content of the image.

Keywords: enhancement, x-rays, pixel intensity values, MatLab

Procedia PDF Downloads 485

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

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This paper presents different methodology for an acoustic source sensing and localization in an unknown environment. The developed methodology includes an acoustic based sensing and localization system, a converging target localization based on the recursive direction of arrival (DOA) error minimization, and a regressive obstacle avoidance function. Our method is able to augment the existing proven localization techniques and improve results incrementally by utilizing robot locomotion and is capable of converging to a position estimate with greater accuracy using fewer measurements. The results also evinced the DOA error minimization at each iteration, improvement in time for reaching the destination and the efficiency of this target localization method as gradually converging to the real target position. Initially, the system is tested using Kinect mounted on turntable with DOA markings which serve as a ground truth and then our approach is validated using a FireBird VI (FBVI) mobile robot on which Kinect is used to obtain bearing information.

Keywords: acoustic source localization, acoustic sensing, recursive direction of arrival, robot locomotion

Procedia PDF Downloads 492

Authors: Benalia Kouini

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The basic idea of this study is to promote a polyethylene recycle and local vegetable fiber (alfa) in the development and characterization of a new composite material. In this work, different sizes of fiber alfa (<63 microns, between 63 and 125 microns, 125 and 250 microns) were incorporated into the blends (HDPE / recycled HDPE) with different methods elaboration (extruder twin-screw and twin-cylinder mixer). The fiber was modified by sodium hydroxide in order to evaluate the effect of alkaline treatment on the interfacial adhesion and therefore the properties of composites prepared. These were characterized by various techniques: mechanical (tensile and Charpy impact test), Rheological (melt flow), morphological (SEM). The demonstration of the effect of alkali treatment on alfa fiber was examined by FTIR spectroscopy and morphological analysis. The introduction of alfa treated fiber in the (HDPE/recycled HDPE) increased stress, impact strength and Young's modulus on the contrary, the elongation at break decreased. The results of the mechanical properties showed an improvement is better in extrusion twin-screw mixer than two cylinders.

Keywords: naturel fiber, alfa, recycling, blends, polyethylene

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Authors: Divya Dharshini Omprakash, Anjali Subramani

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Most of the tall structures are constructed using shear walls and tube systems in the recent decades. This makes the structure heavy and less resistant to lateral effects as the height of the structure goes up. This paper aims in the reduction of self-weight in tall structures by the use of Taper Cladding System (TCS) and also enumerates the construction techniques used in TCS. TCS has a tapering clad either fixed at the top or bottom of the structural core at the tapered end. This system eliminates the use of RC structural elements on the exterior of the structure and uses fewer columns only on the interior part to take up the gravity loads in order to reduce the self-weight of the structure. The self-weight reduction by TCS is 50% more compared to the present structural systems. The lateral loads on the hull will be taken care of by the tapered steel frame. Analysis were done to study the structural behaviour of taper cladded buildings subjected to lateral loads. TCS has a great impact in the construction of tall structures in seismic and dense urban areas. An effective construction management can be done by the use of Taper Cladding System. In this paper, sustainability, design considerations and implications of the system has also been discussed.

Keywords: Lateral Loads Resistance, reduction of self-weight, sustainable, taper clads

Procedia PDF Downloads 289

Authors: Ghofrane Rehaiem, Hamza Gharsellaoui, Samir Benahmed

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In this study, Artificial Neural Networks (ANNs) were used for modeling the parameters that allow the real-time scheduling of embedded systems under resources constraints designed for real-time applications running. The objective of this work is to implement a neural networks based approach for real-time scheduling of embedded systems in order to handle real-time constraints in execution scenarios. In our proposed approach, many techniques have been proposed for both the planning of tasks and reducing energy consumption. In fact, a combination of Dynamic Voltage Scaling (DVS) and time feedback can be used to scale the frequency dynamically adjusting the operating voltage. Indeed, we present in this paper a hybrid contribution that handles the real-time scheduling of embedded systems, low power consumption depending on the combination of DVS and Neural Feedback Scheduling (NFS) with the energy Priority Earlier Deadline First (PEDF) algorithm. Experimental results illustrate the efficiency of our original proposed approach.

Keywords: optimization, neural networks, real-time scheduling, low-power consumption

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Authors: Dong-Hyun Ha, Young-Min Ko, Chang-Bin Ha, Hyoung-Kyu Song

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In Heterogeneous network (HetNet) can provide high quality of a service in a wireless communication system by composition of small cell networks. The composition of small cell networks improves cell coverage and capacity to the mobile users.Recently, various techniques using small cell networks have been researched in the wireless communication system. In this paper, the cooperative scheme obtaining high reliability is proposed in the small cell networks. The proposed scheme suggests a cooperative small cell system and the new signal transmission technique in the proposed system model. The new signal transmission technique applies a cyclic delay diversity (CDD) scheme based on the multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) system to obtain improved performance. The improved performance of the proposed scheme is confirmed by the simulation results.

Keywords: adaptive transmission, cooperative communication, diversity gain, OFDM

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Authors: Jafar W. Al-Badarneh, Abdalkareem R. Al-Hawary, Abdulmalik M. Morghem, Mostafa Z. Ali, Rami S. Al-Gharaibeh

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Archeological heritage is at the heart of each country’s national glory. Moreover, it could develop into a source of national income. Heritage management requires socially-responsible marketing that achieves high visitor satisfaction while maintaining high site conservation. We have developed an Augmented Reality (AR) experience for heritage and cultural reservation at Dar-As-Saraya museum in Jordan. Our application of this notion relied on markerless-based tracking approach. This approach uses keypoints extraction technique where features of the environment are identified and defined into the system as keypoints. A set of these keypoints forms a tracker for an augmented object to be displayed and overlaid with a real scene at Dar As-Saraya museum. We tested and compared several techniques for markerless tracking and then applied the best technique to complete a mosaic artifact with AR content. The successful results from our application open the door for applications in open archeological sites where markerless tracking is mostly needed.

Keywords: augmented reality, cultural heritage, keypoints extraction, virtual recreation

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Authors: Su-Hyun Cho, Chang-U Chae

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Environmental impact assessment techniques have been developed as a result of the worldwide efforts to reduce the environmental impact of global warming. By using the quantification method in the construction industry, it is now possible to manage the greenhouse gas is to systematically evaluate the impact on the environment over the entire construction process. In particular, the proportion of greenhouse gas emissions at the production stage of construction material occupied is high, and efforts are needed in particular in the construction field. In this study, intended for concrete products for the construction materials, by using the LCA evaluation method, we compared the results of environmental impact assessment and carbon emissions of developing products that have been applied low-carbon technologies compared to existing products. As a results, by introducing a raw material of industrial waste, showed carbon reduction. Through a comparison of the carbon emission reduction effect of low-carbon technologies, it is intended to provide academic data for the evaluation of greenhouse gases in the construction sector and the development of low-carbon technologies of the future.

Keywords: CO₂ emissions, CO₂ reduction, ready-mixed concrete, environmental impact assessment

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Authors: Mehrdad Ebrahimi, Oliver Schmitz, Axel Schmidt, Peter Czermak

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“Produced water” (PW) is any fossil water that is brought to the surface along with crude oil or natural gas. By far, PW is the largest waste stream by volume associated with oil and gas production operations. Due to the increasing volume of waste all over the world in the current decade, the outcome and effect of discharging PW on the environment has lately become a significant issue of environmental concerns. Therefore, there is a need for new technologies for PW treatment due to increase focus on water conservation and environmental regulation. The use of membrane processes for treatment of PW has several advantages over many of the traditional separation techniques. In oilfield produced water treatment with ceramic membranes, process efficiency is characterized by the specific permeate flux and by the oil separation performance. Apart from the membrane properties, the permeate flux during filtration of oily wastewaters is known to be strongly dependent on the constituents of the feed solution, as well as on process conditions, e.g. trans-membrane pressure (TMP) and cross-flow velocity (CFV). The research project presented in these report describes the application of different ceramic membrane filtration technologies for the efficient treatment of oil-field produced water and different model oily solutions.

Keywords: ceramic membrane, membrane fouling, oil rejection, produced water treatment

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Authors: S. H. Kazmi, T. Ahmed, K. Javed, A. Ghani

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In this paper static scheme of under-frequency based load shedding is considered for chemical and petrochemical industries with islanded distribution networks relying heavily on the primary commodity to ensure minimum production loss, plant downtime or critical equipment shutdown. A simplistic methodology is proposed for in-house implementation of this scheme using underfrequency relays and a step by step guide is provided including the techniques to calculate maximum percentage overloads, frequency decay rates, time based frequency response and frequency based time response of the system. Case study of FFL electrical system is utilized, presenting the actual system parameters and employed load shedding settings following the similar series of steps. The arbitrary settings are then verified for worst overload conditions (loss of a generation source in this case) and comprehensive system response is then investigated.

Keywords: islanding, under-frequency load shedding, frequency rate of change, static UFLS

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Authors: Mohammad Ali Karimi, Hossein Tavallali, Abdolhamid Hatefi-Mehrjardi

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Pollen extract of in vitro plants raised of Citrus aurantium as reducer and stabilizer was assessed for the green synthesis of silver nanoparticles (AgNPs). The synthesis of AgNPs was performed at room temperature assisting in solutions by reduction takes place rapidly for 10 min. Surface plasmon resonance (SPR) peaks in UV–Vis spectra indicated the formation of polydispersive AgNPs. Silver ions concentration, pH, temperature and reaction time were optimized in the synthesis of AgNPs. The nanoparticles obtained were characterized by UV-Vis spectrophotometer, transmission electron microscopy (TEM). X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy techniques. The synthesized AgNPs were mostly spherical in shape with an average size of 15 nm. XRD study shows that the AgNPs are crystalline in nature with face-centered cubic (fcc) geometry. It shows the significant antibacterial efficacy against Gram-positive (Staphylococcus aureus) and Gram-negative bacteria (Escherichia coli) by disk diffusion method using Mueller-Hinton Agar.

Keywords: green synthesis, Citrus aurantium, silver nanoparticles, antibacterial activity

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Authors: Laila H. Abdel-Rahman, Mohamed Shaker S. Adam, Ahmed M. Abu-Dief, Hanan El-Sayed Ahmed

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In this investigation, Cu(II), Pd(II) and Ag(I) complexes with the tetra-dentate DSPH Schiff base ligand were synthesized. The DSPH Schiff base and its complexes were characterized by using different physicochemical and spectral analysis. The results revealed that the metal ions coordinated with DSPH ligand through azomethine nitrogen and phenolic oxygen. Cu(II), Pd(II) and Ag(I) complexes are present in a 1:1 molar ratio. Pd(II) and Ag(I) complexes have square planar geometries while, Cu(II) has a distorted octahedral (Oh) geometry. All investigated complexes are nonelectrolytes. The investigated compounds were tested against different strains of bacteria and fungi. Both prepared compounds showed good results of inhibition against the selected pathogenic microorganism. Moreover, the interaction of investigated complexes with CT-DNA was studied via various techniques and the binding modes are mainly intercalative and grooving modes. Operating Environment MOE package was used to do docking studies for the investigated complexes to explore the potential binding mode and energy. Furthermore, the growth inhibitory effect of the investigated compounds was examined on some cancer cells lines.

Keywords: tetradentate, antimicrobial, CT-DNA interaction, docking, anticancer

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Authors: Muhammad Ayoub, Abrar Inayat, Bhajan Lal, Sintayehu Mekuria Hailegiorgis

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Biodiesel which comes from pure renewable resources provide an alternative fuel option for future because of limited fossil fuel resources as well as environmental concerns. The transesterification of vegetable oils for biodiesel production is a promising process to overcome this future crises of energy. The use of heterogeneous catalysts greatly simplifies the technological process by facilitating the separation of the post-reaction mixture. The purpose of the present work was to examine a heterogeneous catalyst, in particular, Mg-Al modified K-10 clay, to produce methyl esters of palm oil. The prepared catalyst was well characterized by different latest techniques. In this study, the transesterification of palm oil with methanol was studied in a heterogeneous system in the presence of Mg-Al modified K-10 clay as solid base catalyst and then optimized these results with the help of Design of Experiments software. The results showed that methanol is the best alcohol for this reaction condition. The best results was achieved for optimization of biodiesel process. The maximum conversion of triglyceride (88%) was noted after 8 h of reaction at 60 ̊C, with a 6:1 molar ratio of methanol to palm oil and 3 wt % of prepared catalyst.

Keywords: palm oil, transestrefication, clay, biodiesel, mesoporous clay, K-10

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Authors: Hector G. Perez-Gonzalez, Miriam Vazquez-Escalante, Sandra E. Nava-Muñoz, 
 Francisco E. Martinez-Perez, Alberto S. Nunez-Varela

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The software engineering teaching process has been the subject of many studies. To improve this process, researchers have proposed merely illustrative techniques in the classroom, such as topic presentations and dynamics between students on one side or attempts to involve students in real projects with companies and institutions to bring them to a real software development problem on the other hand. Simulators and serious games have been used as auxiliary tools to introduce students to topics that are too abstract when these are presented in the traditional way. Most of these tools cover a limited area of the huge software engineering scope. To address this problem, we have developed D6tions, an educational serious game that simulates the software engineering process and is designed to experiment the different stages a software engineer (playing roles as project leader or as a developer or designer) goes through, while participating in a software project. We describe previous approaches to this problem, how D6tions was designed, its rules, directions, and the results we obtained of the use of this game involving undergraduate students playing the game.

Keywords: serious games, software engineering, software engineering education, software engineering teaching process

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Authors: Nawaporn Srisarankullawong

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This research is about the creating the design by the inspiration of the flowers, which were once planted in Suan Sunandha Palace. The researcher have conducted the research regarding the history of Suan Sunandha Palace and the flowers which have been planted in the palace’s garden, in order to use this research to create the new designs in the future. The objective are as follows; 1. To study the shape and the pattern of the flowers in Suan Sunandha Palace, in order to select a few of them as the model to create the new design. 2. In order to create the flower design from the flowers in Suan Sunandha Palace by using the current photograph of the flowers which were once used to be planted inside the palace and using adobe Illustrator and Adobe Photoshop programs to create the patterns and the model. The result of the research: From the research, the researcher had selected three types of flowers to crate the pattern model; they are Allamanda, Orchids and Flamingo Plant. The details of the flowers had been reduced in order to show the simplicity and create the pattern model to use them for models, so three flowers had created three pattern models and they had been developed into six patterns, using universal artist techniques, so the pattern created are modern and they can be used for further decoration.

Keywords: patterns design, Suan Sunandha Palace, pattern of the flowers, visual arts and design

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Authors: Awatef Hicheur Cairns, Billel Gueni, Hind Hafdi, Christian Joubert, Nasser Khelifa

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Given the ever changing needs of the job markets, education and training centers are increasingly held accountable for student success. Therefore, education and training centers have to focus on ways to streamline their offers and educational processes in order to achieve the highest level of quality in curriculum contents and managerial decisions. Educational process mining is an emerging field in the educational data mining (EDM) discipline, concerned with developing methods to discover, analyze and provide a visual representation of complete educational processes. In this paper, we present our distributed computation platform which allows different education centers and institutions to load their data and access to advanced data mining and process mining services. To achieve this, we present also a comparative study of the different clustering techniques developed in the context of process mining to partition efficiently educational traces. Our goal is to find the best strategy for distributing heavy analysis computations on many processing nodes of our platform.

Keywords: educational process mining, distributed process mining, clustering, distributed platform, educational data mining, ProM

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Authors: Tugba Altin

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In an era where the impacts of climate change resonate more pronouncedly than ever, communities globally grapple with events bearing both tangible and intangible ramifications. Situating this within the evolving landscapes of Psychological and Behavioral Sciences, this research probes the profound psychological and behavioral responses evoked by such events. The Lytton Creek Fire of 2021 epitomizes these challenges. While tangible destruction is immediate and evident, the intangible repercussions—emotional distress, disintegration of cultural landscapes, and disruptions in place attachment (PA)—require meticulous exploration. PA, emblematic of the emotional and cognitive affiliations individuals nurture with their environments, emerges as a cornerstone for comprehending how environmental cataclysms influence cultural identity and bonds to land. This study, harmonizing the core tenets of an interpretive phenomenological approach with a hermeneutic framework, underscores the pivotal nature of this attachment. It delves deep into the realm of individuals' experiences post the Lytton Creek Fire, unraveling the intricate dynamics of PA amidst such calamity. The study's methodology deviates from conventional paradigms. Instead of traditional interview techniques, it employs walking audio sessions and photo elicitation methods, granting participants the agency to immerse, re-experience, and vocalize their sentiments in real-time. Such techniques shed light on spatial narratives post-trauma and capture the otherwise elusive emotional nuances, offering a visually rich representation of place-based experiences. Central to this research is the voice of the affected populace, whose lived experiences and testimonies form the nucleus of the inquiry. As they renegotiate their bonds with transformed environments, their narratives reveal the indispensable role of cultural landscapes in forging place-based identities. Such revelations accentuate the necessity of integrating both tangible and intangible trauma facets into community recovery strategies, ensuring they resonate more profoundly with affected individuals. Bridging the domains of environmental psychology and behavioral sciences, this research accentuates the intertwined nature of tangible restoration with the imperative of emotional and cultural recuperation post-environmental disasters. It advocates for adaptation initiatives that are rooted in the lived realities of the affected, emphasizing a holistic approach that recognizes the profundity of human connections to landscapes. This research advocates the interdisciplinary exchange of ideas and strategies in addressing post-disaster community recovery strategies. It not only enriches the climate change discourse by emphasizing the human facets of disasters but also reiterates the significance of an interdisciplinary approach, encompassing psychological and behavioral nuances, for fostering a comprehensive understanding of climate-induced traumas. Such a perspective is indispensable for shaping more informed, empathetic, and effective adaptation strategies.

Keywords: place attachment, community recovery, disaster response, restorative landscapes, sensory response, visual methodologies

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Authors: Fahd Sabry Esmail, M. Badr Senousy, Mohamed Ragaie

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In recent years, there has been an explosion in the rate of using technology that help discovering the diseases. For example, DNA microarrays allow us for the first time to obtain a "global" view of the cell. It has great potential to provide accurate medical diagnosis, to help in finding the right treatment and cure for many diseases. Various classification algorithms can be applied on such micro-array datasets to devise methods that can predict the occurrence of Leukemia disease. In this study, we compared the classification accuracy and response time among eleven decision tree methods and six rule classifier methods using five performance criteria. The experiment results show that the performance of Random Tree is producing better result. Also it takes lowest time to build model in tree classifier. The classification rules algorithms such as nearest- neighbor-like algorithm (NNge) is the best algorithm due to the high accuracy and it takes lowest time to build model in classification.

Keywords: data mining, classification techniques, decision tree, classification rule, leukemia diseases, microarray data

Procedia PDF Downloads 321

Authors: Anurag Jain, Rajneesh Kumar

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Cloud computing is the outcome of rapid growth of internet. Due to elastic nature of cloud computing and unpredictable behavior of user, load balancing is the major issue in cloud computing paradigm. An efficient load balancing technique can improve the performance in terms of efficient resource utilization and higher customer satisfaction. Load balancing can be implemented through task scheduling, resource allocation and task migration. Various parameters to analyze the performance of load balancing approach are response time, cost, data processing time and throughput. This paper demonstrates a two level load balancer approach by combining join idle queue and join shortest queue approach. Authors have used cloud analyst simulator to test proposed two level load balancer approach. The results are analyzed and compared with the existing algorithms and as observed, proposed work is one step ahead of existing techniques.

Keywords: cloud analyst, cloud computing, join idle queue, join shortest queue, load balancing, task scheduling

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Authors: F. H. Abanda, B. Kamsu-Foguem, J. H. M. Tah

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Construction cost estimation is one of the most important aspects of construction project design. For generations, the process of cost estimating has been manual, time-consuming and error-prone. This has partly led to most cost estimates to be unclear and riddled with inaccuracies that at times lead to over- or under-estimation of construction cost. The development of standard set of measurement rules that are understandable by all those involved in a construction project, have not totally solved the challenges. Emerging Building Information Modelling (BIM) technologies can exploit standard measurement methods to automate cost estimation process and improves accuracies. This requires standard measurement methods to be structured in ontologically and machine readable format; so that BIM software packages can easily read them. Most standard measurement methods are still text-based in textbooks and require manual editing into tables or Spreadsheet during cost estimation. The aim of this study is to explore the development of an ontology based on New Rules of Measurement (NRM) commonly used in the UK for cost estimation. The methodology adopted is Methontology, one of the most widely used ontology engineering methodologies. The challenges in this exploratory study are also reported and recommendations for future studies proposed.

Keywords: BIM, construction projects, cost estimation, NRM, ontology

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Authors: Ahmad Yame, Ahad Ali, Badih Jawad, Daw Al-Werfalli Mohamed Nasser, Sabah Abro

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Industries in general have a lot of waste. Wool textile company, Baniwalid, Libya has many complex problems that led to enormous waste generated due to the lack of lean strategies, expertise, technical support and commitment. To successfully address waste at wool textile company, this study will attempt to develop a methodical approach that integrates lean manufacturing tools to optimize performance characteristics such as lead time and delivery. This methodology will utilize Value Stream Mapping (VSM) techniques to identify the process variables that affect production. Once these variables are identified, Design of Experiments (DOE) Methodology will be used to determine the significantly influential process variables, these variables are then controlled and set at their optimal to achieve optimal levels of productivity, quality, agility, efficiency and delivery to analyze the outputs of the simulation model for different lean configurations. The goal of this research is to investigate how the tools of lean manufacturing can be adapted from the discrete to the continuous manufacturing environment and to evaluate their benefits at a specific industrial.

Keywords: lean manufacturing, DOE, value stream mapping, textiles

Procedia PDF Downloads 455

Authors: O. Guellati, A. Harat, F. Djefaflia, N. Habib, A. Nait-Merzoug, J. El Haskouri, D. Momodu, N. Manyala, D. Bégin, M. Guerioune

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We report a facile and low-cost free-template synthesis method was used to synthesize mesoporous smart multifunctional nanohybrids based on Graphene/PANI nanofibers micro/nanostructures with very interesting physic-chemical properties and faradic electrochemical behavior of these products was investigated. These nanohybrid products have been characterized quantitatively and qualitatively using different techniques, such as XRD / FTIR, Raman, XPS spectroscopy, Field Emission SEM and High-Resolution TEM microscopy, BET textural analysis, electrochemical measurements (CV, CD, EIS). Moreover, the electrochemical measurements performed in a 6 M KOH aqueous electrolyte depicted excellent electrochemical performance ascribed to the optimized composition of hydroxides et PANI nanofibers. An exceptionally notable specific capacitance between 800  and 2000 F. g-1 was obtained at 5  mV. s-1 scan rate for these synthesized products depends on the optimized growth conditions. We found much better nanohybrids by reinforcing hydroxides or conduction polymer nanofibers with carbonaceous nanomaterials depicting their potential as suitable materials for energy storage devices.

Keywords: nanohybrid materials, conducting polymers, carbonaceous nanomaterials, supercapacitors, energy storage

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Authors: Gihan Mosaad, Bakr Gomaa, Rana Elbadri

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Modern parts of Alexandria city lack in vibrancy, causing a number of problems such as urban areas with poor security measures as well as weak economic state. Vibrancy provides a livable, attractive and secure environments; it also boosts the city’s economy and social life. Vibrant city is a city full of energy and life. To achieve this, a number of resources are needed; namely specific urban density, the availability of alternative modes of transportation and finally diversity of land-uses. Literature review shows no comprehensive study that assesses vibrancy in the streets of modern Alexandria. This study aims to measure the vibrancy potential in Sidi-Gaber station area thought the assessment of existing resources performance. Methods include literature reviews, surveying of existing case, questionnaire as well as GIS techniques. Expected results include GIS maps defining the vibrancy potentials in land use, density and statistical study regarding public transportation use in the area.

Keywords: Alexandria, density, mixed use, transportation, vibrancy

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Authors: Tiago do Carmo Nogueira, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, Matheus Rudolfo Diedrich Ullmann

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Generating automatic image descriptions through natural language is a challenging task. Image captioning is a task that consistently describes an image by combining computer vision and natural language processing techniques. To accomplish this task, cutting-edge models use encoder-decoder structures. Thus, Convolutional Neural Networks (CNN) are used to extract the characteristics of the images, and Recurrent Neural Networks (RNN) generate the descriptive sentences of the images. However, cutting-edge approaches still suffer from problems of generating incorrect captions and accumulating errors in the decoders. To solve this problem, we propose a model based on the encoder-decoder structure, introducing a module that generates the weights according to the importance of the word to form the sentence, using the part-of-speech (PoS). Thus, the results demonstrate that our model surpasses state-of-the-art models.

Keywords: gated recurrent units, caption generation, convolutional neural network, part-of-speech

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Authors: Uma Kanth, Amy Cook

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Conceptual Metaphor Theory (CMT) proposes that metaphor is fundamental to human thought. CMT utilizes embodied cognition, in that emotions are conceptualized as effects on the body because of a coupling of one’s bodily experiences and one’s somatosensory system. Time perception is a function of embodied cognition and conceptual metaphor in that one’s experience of time is inextricably dependent on one’s perception of the world around them. A hallmark of depressive disorders is the distortion in one’s perception of time, such as neurological dysfunction and psychomotor retardation, and yet, to the author’s best knowledge, previous studies have not before linked CMT, embodied cognition, and depressive disorders. Therefore, the focus of this paper is the investigation of how the applications of CMT and embodied cognition (especially regarding time perception) have promise in improving current techniques to treat depressive disorders. This paper aimed to extend, through a thorough review of literature, the theoretical basis required to further research into CMT and embodied cognition’s application in treating time distortion related symptoms of depressive disorders. Future research could include the development of brain training technologies that capitalize on the principles of CMT, with the aim of promoting cognitive remediation and cognitive activation to mitigate symptoms of depressive disorder.

Keywords: depression, conceptual metaphor theory, embodied cognition, time

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Authors: Ren Moses

Abstract:

The process of classifying vehicles on a highway is hereby viewed as a pattern recognition problem in which connectionist techniques such as artificial neural networks (ANN) can be used to assign vehicles to their correct classes and hence to establish optimum axle spacing thresholds. In the United States, vehicles are typically classified into 13 classes using a methodology commonly referred to as “Scheme F”. In this research, the ANN model was developed, trained, and applied to field data of vehicles. The data comprised of three vehicular features—axle spacing, number of axles per vehicle, and overall vehicle weight. The ANN reduced the classification error rate from 9.5 percent to 6.2 percent when compared to an existing classification algorithm that is not ANN-based and which uses two vehicular features for classification, that is, axle spacing and number of axles. The inclusion of overall vehicle weight as a third classification variable further reduced the error rate from 6.2 percent to only 3.0 percent. The promising results from the neural networks were used to set up new thresholds that reduce classification error rate.

Keywords: artificial neural networks, vehicle classification, traffic flow, traffic analysis, and highway opera-tions

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Authors: Azlinda Saadon

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This paper provides detail review on river bank erosion studies with respect to their processes, methods of measurements and factors governing river bank erosion. Bank erosion processes are commonly associated with river changes initiation and development, through width adjustment and planform evolution. It consists of two main types of erosion processes; basal erosion due to fluvial hydraulic force and bank failure under the influence of gravity. Most studies had only focused on one factor rather than integrating both factors. Evidences of previous works have shown integration between both processes of fluvial hydraulic force and bank failure. Bank failure is often treated as probabilistic phenomenon without having physical characteristics and the geotechnical aspects of the bank. This review summarizes the findings of previous investigators with respect to measurement techniques and prediction rates of river bank erosion through field investigation, physical model and numerical model approaches. Factors governing river bank erosion considering physical characteristics of fluvial erosion are defined.

Keywords: river bank erosion, bank erosion, dimensional analysis, geotechnical aspects

Procedia PDF Downloads 435

Authors: Thota Sai Prakash, B. Yaswanth, Jhade Bhuvaneswar, Marreddy Divakar Reddy, Shyam Ji Gupta

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Across the globe, there are a lot of chronic diseases, and heart disease stands out as one of the most perilous. Sadly, many lives are lost to this condition, even though early intervention could prevent such tragedies. However, identifying heart disease in its initial stages is not easy. To address this challenge, we propose an automated system aimed at predicting the presence of heart disease using advanced techniques. By doing so, we hope to empower individuals with the knowledge needed to take proactive measures against this potentially fatal illness. Our approach towards this problem involves meticulous data preprocessing and the development of predictive models utilizing classification algorithms such as Support Vector Machines (SVM), Decision Tree, and Random Forest. We assess the efficiency of every model based on metrics like accuracy, ensuring that we select the most reliable option. Additionally, we conduct thorough data analysis to reveal the importance of different attributes. Among the models considered, Random Forest emerges as the standout performer with an accuracy rate of 96.04% in our study.

Keywords: support vector machines, decision tree, random forest

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Authors: Vahid Bayrami Rad

Abstract:

In recent years, the use of artificial intelligence techniques, tools, and methods in processing medical images and health-related applications has been highlighted and a lot of research has been done in this regard. For example, colonoscopy and diagnosis of colon lesions are some cases in which the process of diagnosis of lesions can be improved by using image processing and artificial intelligence algorithms, which help doctors a lot. Due to the lack of accurate measurements and the variety of injuries in colonoscopy images, the process of diagnosing the type of lesions is a little difficult even for expert doctors. Therefore, by using different software and image processing, doctors can be helped to increase the accuracy of their observations and ultimately improve their diagnosis. Also, by using automatic methods, the process of diagnosing the type of disease can be improved. Therefore, in this paper, a deep learning framework called KCBA is proposed to classify colonoscopy lesions which are composed of several methods such as K-means clustering, a bag of features and deep auto-encoder. Finally, according to the experimental results, the proposed method's performance in classifying colonoscopy images is depicted considering the accuracy criterion.

Keywords: colorectal cancer, colonoscopy, region of interest, narrow band imaging, texture analysis, bag of feature

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Authors: Kharisma Utomo Mulyodinoto, Suwarno, A. Abu-Siada

Abstract:

Dissolved Gas Analysis is one of impressive technique to detect and predict internal fault of transformers by using gas generated by transformer oil sample. A number of methods are used to interpret the dissolved gas from transformer oil sample: Doernenberg Ratio Method, IEC (International Electrotechnical Commission) Ratio Method, and Duval Triangle Method. While the assessment of dissolved gas within transformer oil samples has been standardized over the past two decades, analysis of the results is not always straight forward as it depends on personnel expertise more than mathematical formulas. To get over this limitation, this paper is aimed at improving the interpretation of Doernenberg Ratio Method, IEC Ratio Method, and Duval Triangle Method using Two Stages Adaptive Neuro-Fuzzy Inference System (ANFIS). Dissolved gas analysis data from 520 faulty transformers was analyzed to establish the proposed ANFIS model. Results show that the developed ANFIS model is accurate and can standardize the dissolved gas interpretation process with accuracy higher than 90%.

Keywords: ANFIS, dissolved gas analysis, Doernenberg ratio method, Duval triangular method, IEC ratio method, transformer

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