Search results for: cointegration techniques

Authors: Om Prakash Bharti, Aanchal Verma, R. K. Saket

Abstract:

The Doubly-Fed Induction Generator (DFIG) is suggested for Wind Energy Conversion System (WECS) to extract wind power. DFIG is preferably employed due to its robustness towards variable wind and rotor speed. DFIG has the adaptable property because the system parameters are smoothly dealt with, including real power, reactive power, DC-link voltage, and the transient and dynamic responses, which are needed to analyze constantly. The analysis becomes more prominent during any unusual condition in the electrical power system. Hence, the study and improvement in the system parameters and transient response performance of DFIG are required to be accomplished using some controlling techniques. For fulfilling the task, the present work implements and compares the optimization methods for the design of the DFIG controller for WECS. The bio-inspired optimization techniques are applied to get the optimal controller design parameters for DFIG-based WECS. The optimized DFIG controllers are then used to retrieve the transient response performance of the six-order DFIG model with a step input. The results using MATLAB/Simulink show the betterment of the Firefly algorithm (FFA) over other control techniques when compared with the other controller design methods.

Keywords: doubly-fed induction generator, wind turbine, wind energy conversion system, induction generator, transfer function, proportional, integral, derivatives

Procedia PDF Downloads 93

Authors: Ahmed M. Jihad

Abstract:

The paper presents the concept of sustainable development, and the role of geographic techniques in the design, planning and presentation of maps of smart cities with geographical vision, and the identification of programs and tools, and models of maps of Arab cities, is the problem of research in how to apply, process and experience these programs? What is the role of geographic techniques in planning and mapping the optimal place for these cities? The paper proposes an addition to the designs of Iraqi cities, as it can be developed in the future to serve as a model for interactive smart cities by developing its services. The importance of this paper stems from the concept of sustainable development dynamic which has become a method of development imposed by the present era in rapid development to achieve social balance and specialized programs in draw paper argues that ensuring sustainable development is achieved through the use of information technology. The paper will follow the theoretical presentation of the importance of the concept of development, design tools and programs. The paper follows the method of analysis of modern systems (System Analysis Approach) through the latest programs will provide results can be said that the new Iraqi cities can be developed with smart technologies, like some of the Arab and European cities that were newly created through the introduction of international investment, and therefore Plans can be made to select the best programs in manufacturing and producing maps and smart cities in the future.

Keywords: geographic techniques, planning the cities, smart cities, sustainable development

Procedia PDF Downloads 210

Authors: Gholamreza Farrokhi, Behzad Sani

Abstract:

The goals of sustainable agricultural are development, improved nutrition, and food security. Sustainable agriculture must be developed that will meet today’s needs for food and other products, as well as preserving the vital natural resource base that will allow future generations to meet their needs. Sustainable development requires international cooperation and the effective use of technology. Access to sustainable sources of food will remain a preeminent challenge in the decades to come. Based upon current practice and consumption, agricultural production will have to increase by about 70% by 2050 to meet demand. Nuclear techniques are used in developing countries to increase production sustainably by breeding improved crops, enhancing livestock reproduction and nutrition, as well as controlling animal and plant pests and diseases. Post-harvest losses can be reduced and safety increased with nuclear technology. Soil can be evaluated with nuclear techniques to conserve and improve soil productivity and water management.

Keywords: food safety, food security, nuclear techniques, sustainable agriculture, sustainable future

Procedia PDF Downloads 357

Authors: Gurmail Singh

Abstract:

Effective supply chain is the main priority of every organization which is the outcome of strategic corporate investments with deliberate management action. Value-driven supply chain is defined through development, procurement and by configuring the appropriate resources, metrics and processes. However, responsiveness of the supply chain can be improved by proper coordination. So the Bullwhip effect (BWE) and Net stock amplification (NSAmp) values were anticipated and used for the control of inventory in organizations by both discrete wavelet transform-Artificial neural network (DWT-ANN) and Adaptive Network-based fuzzy inference system (ANFIS). This work presents a comparative methodology of forecasting for the customers demand which is non linear in nature for a multilevel supply chain structure using hybrid techniques such as Artificial intelligence techniques including Artificial neural networks (ANN) and Adaptive Network-based fuzzy inference system (ANFIS) and Discrete wavelet theory (DWT). The productiveness of these forecasting models are shown by computing the data from real world problems for Bullwhip effect and Net stock amplification. The results showed that these parameters were comparatively less in case of discrete wavelet transform-Artificial neural network (DWT-ANN) model and using Adaptive network-based fuzzy inference system (ANFIS).

Keywords: bullwhip effect, hybrid techniques, net stock amplification, supply chain flexibility

Procedia PDF Downloads 127

Authors: R. Rama Kishore, Sunesh Malik

Abstract:

Development in the usage of internet for different purposes in recent times creates great threat for the copy right protection of the digital images. Digital watermarking is the best way to rescue from the said problem. This paper presents detailed review of the different watermarking techniques, latest trends in the field and categorized like spatial and transform domain, blind and non-blind methods, visible and non visible techniques etc. It also discusses the different optimization techniques used in the field of watermarking in order to improve the robustness and imperceptibility of the method. Different measures are discussed to evaluate the performance of the watermarking algorithm. At the end, this paper proposes a watermarking algorithm using (k.n) shares of halftone visual cryptography (HVC) instead of (2, 2) share cryptography. (k,n) shares visual cryptography improves the security of the watermark. As halftone is a method of reprographic, it helps in improving the visual quality of watermark image. The proposed method uses fractional transformation to improve the robustness of the copyright protection of the method.

Keywords: digital watermarking, fractional transform, halftone, visual cryptography

Procedia PDF Downloads 355

Authors: B. Kirubakaran, C. Rajasekaran

Abstract:

Reconfigurable techniques are used in many engineering and industrial applications for the efficient data transmissions through the wireless sensor networks. Nowadays most of the industrial applications are work for try to minimize the size and cost. During runtime the reconfigurable technique avoid the unwanted hang and delay in the system performance. In recent world Field Programmable Gate Array (FPGA) as one of the most efficient reconfigurable device and widely used for most of the hardware and software reconfiguration applications. In this paper, the work deals with whatever going to make changes in the hardware and software during runtime it’s should not affect the current running process that’s the main objective of the paper our changes be done in a parallel manner at the same time concentrating the cost and power transmission problems during data trans-receiving. Analog sensor (Temperature) as an input for the controller (PIC) through that control the FPGA digital sensors in generalized manner.

Keywords: field programmable gate array, peripheral interrupt controller, runtime reconfigurable techniques, wireless sensor networks

Procedia PDF Downloads 407

Authors: Amara Rafik, Mostefa Belhadj Aissa

Abstract:

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

Procedia PDF Downloads 117

Authors: Hadeer M. Sayed, Hesham E. El Deeb, Shereen A. Taie

Abstract:

In the big data era, we are facing a diversity of datasets from different sources in different domains that describe a single life event. These datasets consist of multiple modalities, each of which has a different representation, distribution, scale, and density. Multimodal fusion is the concept of integrating information from multiple modalities in a joint representation with the goal of predicting an outcome through a classification task or regression task. In this paper, multimodal fusion techniques are classified into two main classes: model-agnostic techniques and model-based approaches. It provides a comprehensive study of recent research in each class and outlines the benefits and limitations of each of them. Furthermore, the audiovisual speech recognition task is expressed as a case study of multimodal data fusion approaches, and the open issues through the limitations of the current studies are presented. This paper can be considered a powerful guide for interested researchers in the field of multimodal data fusion and audiovisual speech recognition particularly.

Keywords: multimodal data, data fusion, audio-visual speech recognition, neural networks

Procedia PDF Downloads 111

Authors: Rashid Mahmood, Muhammad Junaid Sarwar

Abstract:

Mobile ad hoc networks (MANETs) use has been well-known from the last few years in the many applications, like mission critical applications. In the (MANETS) prevention method is not adequate as the security concerned, so the detection method should be added to the security issues in (MANETs). The authentication and encryption is considered the first solution of the MANETs problem where as now these are not sufficient as MANET use is increasing. In this paper we are going to present the concept of intrusion detection and then survey some of major intrusion detection techniques in MANET and aim to comparing in some important fields.

Keywords: MANET, IDS, intrusions, signature, detection, prevention

Procedia PDF Downloads 378

Authors: Md. Qamruzzaman, Wei Jianguo

Abstract:

Over the decade, it is observed that financial development, through financial innovation, not only accelerated development of efficient and effective financial system but also act as a catalyst in the economic development process. In this study, we try to explore insight about how financial innovation causes economic growth in Bangladesh by using Vector Error Correction Model (VECM) for the period of 1990-2014. Test of Cointegration confirms the existence of a long-run association between financial innovation and economic growth. For investigating directional causality, we apply Granger causality test and estimation explore that long-run growth will be affected by capital flow from non-bank financial institutions and inflation in the economy but changes of growth rate do not have any impact on Capital flow in the economy and level of inflation in long-run. Whereas, growth and Market capitalization, as well as market capitalization and capital flow, confirm feedback hypothesis. Variance decomposition suggests that any innovation in the financial sector can cause GDP variation fluctuation in both long run and short run. Financial innovation promotes efficiency and cost in financial transactions in the financial system, can boost economic development process. The study proposed two policy recommendations for further development. First, innovation friendly financial policy should formulate to encourage adaption and diffusion of financial innovation in the financial system. Second, operation of financial market and capital market should be regulated with implementation of rules and regulation to create conducive environment.

Keywords: financial innovation, economic growth, GDP, financial institution, VECM

Procedia PDF Downloads 271

Authors: Mikel Alonso López

Abstract:

In the first decade of the twenty-first century, advanced imaging techniques began to be applied for neuroscience research. The Functional Magnetic Resonance Imaging (fMRI) is one of the most important and most used research techniques for the investigation of emotions, because of its ease to observe the brain areas that oxygenate when performing certain tasks. In this research, we make a review about the main research carried out on the influence of the emotions in the decision-making process that is exposed by using the fMRI.

Keywords: decision making, emotions, fMRI, consumer behaviour

Procedia PDF Downloads 479

Authors: Ahlam Elkilani, Bayan Elsheikh Ali, Rasha Abu Romman, Amjed Al-mousa, Belal Sababha

Abstract:

The amount of energy the world uses doubles every 20 years. Green homes play an important role in reducing the residential energy demand. This paper presents a platform that is intended to learn the behavior of home residents and build a profile about their habits and actions. The proposed resident aware home controller intervenes in the operation of home appliances in order to save energy without compromising the convenience of the residents. The presented platform can be used to simulate the actions and movements happening inside a home. The paper includes several optimization techniques that are meant to save energy in the home. In addition, several test scenarios are presented that show how the controller works. Moreover, this paper shows the computed actual savings when each of the presented techniques is implemented in a typical home. The test scenarios have validated that the techniques developed are capable of effectively saving energy at homes.

Keywords: green home, resident aware, resident profile, activity learning, machine learning

Procedia PDF Downloads 389

Authors: C. Manjula, Lilly Florence

Abstract:

Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: decision tree, genetic algorithm, machine learning, software defect prediction

Procedia PDF Downloads 329

Authors: Syeda Mainaaz Unnisa, Deepa Suresh

Abstract:

Due to the increase in usage of public domain channels, such as the internet, and communication technology, there is a concern about the protection of intellectual property and security threats. This interest has led to growth in researching and implementing techniques for information hiding. Steganography is the art and science of hiding information in a private manner such that its existence cannot be recognized. Communication using steganographic techniques makes not only the secret message but also the presence of hidden communication, invisible. Steganalysis is the art of detecting the presence of this hidden communication. Parallel to steganography, steganalysis is also gaining prominence, since the detection of hidden messages can prevent catastrophic security incidents from occurring. Steganalysis can also be incredibly helpful in identifying and revealing holes with the current steganographic techniques, which makes them vulnerable to attacks. Through the formulation of new effective steganalysis methods, further research to improve the resistance of tested steganography techniques can be developed. Feature-based steganalysis method for JPEG images calculates the features of an image using the L1 norm of the difference between a stego image and the calibrated version of the image. This calibration can help retrieve some of the parameters of the cover image, revealing the variations between the cover and stego image and enabling a more accurate detection. Applying this method to various steganographic schemes, experimental results were compared and evaluated to derive conclusions and principles for more protected JPEG steganography.

Keywords: cover image, feature-based steganalysis, information hiding, steganalysis, steganography

Procedia PDF Downloads 216

Authors: Zaynab El Khattabi, Youness Tabii, Abdelhamid Benkaddour

Abstract:

Nowadays, huge amount of multimedia repositories make the browsing, retrieval and delivery of video contents very slow and even difficult tasks. Video summarization has been proposed to improve faster browsing of large video collections and more efficient content indexing and access. In this paper, we focus on approaches to video summarization. The video summaries can be generated in many different forms. However, two fundamentals ways to generate summaries are static and dynamic. We present different techniques for each mode in the literature and describe some features used for generating video summaries. We conclude with perspective for further research.

Keywords: video summarization, static summarization, video skimming, semantic features

Procedia PDF Downloads 400

Authors: Amandeep Kaur

Abstract:

Digital Image processing is a fundamental tool to perform various operations on the digital images for pattern recognition, noise removal and feature extraction. In this paper noise removal technique has been described for various types of noises. This paper comprises discussion about various noises available in the image due to different environmental, accidental factors. In this paper, various de-noising approaches have been discussed that utilize different wavelets and filters for de-noising. By analyzing various papers on image de-noising we extract that wavelet based de-noise approaches are much effective as compared to others.

Keywords: de-noising techniques, edges, image, image processing

Procedia PDF Downloads 336

Authors: Imalka Wasana Rathnayaka, Rasheda Khanam, Mohammad Mafizur Rahman

Abstract:

TheCOVID-19 pandemic has created unprecedented challenges to both the health and economic states in countries around the world. This study aims to evaluate the effectiveness of governments' decisions to mitigate the risks of COVID-19 through proposing policy directions to reduce its magnitude. The study is motivated by the ongoing coronavirus outbreaks and comprehensive policy responses taken by countries to mitigate the spread of COVID-19 and reduce death rates. This study contributes to filling the knowledge by exploiting the long-term efficacy of extensive plans of governments. This study employs a Panel autoregressive distributed lag (ARDL) framework. The panels incorporate both a significant number of variables and fortnightly observations from22 countries. The dependent variables adopted in this study are the fortnightly death rates and the rates of the spread of COVID-19. Mortality rate and the rate of infection data were computed based on the number of deaths and the number of new cases per 10000 people.The explanatory variables are fortnightly values of indexes taken to investigate the efficacy of government interventions to control COVID-19. Overall government response index, Stringency index, Containment and health index, and Economic support index were selected as explanatory variables. The study relies on the Oxford COVID-19 Government Measure Tracker (OxCGRT). According to the procedures of ARDL, the study employs (i) the unit root test to check stationarity, (ii) panel cointegration, and (iii) PMG and ARDL estimation techniques. The study shows that the COVID-19 pandemic forced immediate responses from policymakers across the world to mitigate the risks of COVID-19. Of the four types of government policy interventions: (i) Stringency and (ii) Economic Support have been most effective and reveal that facilitating Stringency and financial measures has resulted in a reduction in infection and fatality rates, while (iii) Government responses are positively associated with deaths but negatively with infected cases. Even though this positive relationship is unexpected to some extent in the long run, social distancing norms of the governments have been broken by the public in some countries, and population age demographics would be a possible reason for that result. (iv) Containment and healthcare improvements reduce death rates but increase the infection rates, although the effect has been lower (in absolute value). The model implies that implementation of containment health practices without association with tracing and individual-level quarantine does not work well. The policy implication based on containment health measures must be applied together with targeted, aggressive, and rapid containment to extensively reduce the number of people infected with COVID 19. Furthermore, the results demonstrate that economic support for income and debt relief has been the key to suppressing the rate of COVID-19 infections and fatality rates.

Keywords: COVID-19, infection rate, deaths rate, government response, panel data

Procedia PDF Downloads 76

Authors: Abiodun Ladanu Ajala, Wuyi Oke

Abstract:

Mathematical simulation and optimization models packaged within interactive computer programs provide a common way for planners and managers to predict the behaviour of any proposed water resources system design or management policy before it is implemented. Modeling presents a principal technique of predicting the behaviour of the proposed infrastructural designs or management policies. Models can be developed and used to help identify specific alternative plans that best meet those objectives. This study discusses various types of models, their development, architecture, data requirements, and applications in the field of engineering. It also outlines the advantages and limitations of each the optimization and simulation models presented. The techniques explored in this review include; dynamic programming, linear programming, fuzzy optimization, evolutionary algorithms and finally artificial intelligence techniques. Previous studies carried out using some of the techniques mentioned above were reviewed, and most of the results from different researches showed that indeed optimization and simulation provides viable alternatives and predictions which form a basis for decision making in building engineering structures and also in engineering planning and management.

Keywords: linear programming, mutation, optimization, simulation

Procedia PDF Downloads 589

Authors: Deepak Singh, Rail Kuliev

Abstract:

This research article explores the significance of advanced data visualization techniques in enhancing decision-making processes within the oil and gas exploration and production domain. With the oil and gas industry facing numerous challenges, effective interpretation and analysis of vast and diverse datasets are crucial for optimizing exploration strategies, production operations, and risk assessment. The article highlights the importance of data visualization in managing big data, aiding the decision-making process, and facilitating communication with stakeholders. Various advanced data visualization techniques, including 3D visualization, augmented reality (AR), virtual reality (VR), interactive dashboards, and geospatial visualization, are discussed in detail, showcasing their applications and benefits in the oil and gas sector. The article presents case studies demonstrating the successful use of these techniques in optimizing well placement, real-time operations monitoring, and virtual reality training. Additionally, the article addresses the challenges of data integration and scalability, emphasizing the need for future developments in AI-driven visualization. In conclusion, this research emphasizes the immense potential of advanced data visualization in revolutionizing decision-making processes, fostering data-driven strategies, and promoting sustainable growth and improved operational efficiency within the oil and gas exploration and production industry.

Keywords: augmented reality (AR), virtual reality (VR), interactive dashboards, real-time operations monitoring

Procedia PDF Downloads 86

Authors: Ibtihal D. Mustafa, Mawia A. Hassan

Abstract:

Tumor segmentation from MRI image is important part of medical images experts. This is particularly a challenging task because of the high assorting appearance of tumor tissue among different patients. MRI images are advance of medical imaging because it is give richer information about human soft tissue. There are different segmentation techniques to detect MRI brain tumor. In this paper, different procedure segmentation methods are used to segment brain tumors and compare the result of segmentations by using correlation and structural similarity index (SSIM) to analysis and see the best technique that could be applied to MRI image.

Keywords: MRI, segmentation, correlation, structural similarity

Procedia PDF Downloads 410

Authors: Devatha Kalyan Kumar, Aravindraj D., Sadathulla A.

Abstract:

Big data are now rapidly expanding in all engineering and science and many other domains. The potential of large or massive data is undoubtedly significant, make sense to require new ways of thinking and learning techniques to address the various big data challenges. Machine learning is continuously unleashing its power in a wide range of applications. In this paper, the latest advances and advancements in the researches on machine learning for big data processing. First, the machine learning techniques methods in recent studies, such as deep learning, representation learning, transfer learning, active learning and distributed and parallel learning. Then focus on the challenges and possible solutions of machine learning for big data.

Keywords: active learning, big data, deep learning, machine learning

Procedia PDF Downloads 445

Authors: S. Abera, T. Gidey, W. Terefe

Abstract:

Introduction: Testing for HIV is the key entry point to HIV prevention, treatment, and care and support services. Hence, predictive data mining techniques can greatly benefit to analyze and discover new patterns from huge datasets like that of EDHS 2011 data. Objectives: The objective of this study is to build a predictive modeling for HIV testing and identify determinants of HIV testing for adults with age above fourteen years using data mining techniques. Methods: Cross-Industry Standard Process for Data Mining (CRISP-DM) was used to predict the model for HIV testing and explore association rules between HIV testing and the selected attributes among adult Ethiopians. Decision tree, Naïve-Bayes, logistic regression and artificial neural networks of data mining techniques were used to build the predictive models. Results: The target dataset contained 30,625 study participants; of which 16, 515 (53.9%) were women. Nearly two-fifth; 17,719 (58%), have never been tested for HIV while the rest 12,906 (42%) had been tested. Ethiopians with higher wealth index, higher educational level, belonging 20 to 29 years old, having no stigmatizing attitude towards HIV positive person, urban residents, having HIV related knowledge, information about family planning on mass media and knowing a place where to get testing for HIV showed an increased patterns with respect to HIV testing. Conclusion and Recommendation: Public health interventions should consider the identified determinants to promote people to get testing for HIV.

Keywords: data mining, HIV, testing, ethiopia

Procedia PDF Downloads 496

Authors: Samira Karimi-Mansoub, Rahem Abri

Abstract:

Currently, users expect high quality and personalized information from search results. To satisfy user’s needs, personalized approaches to web search have been proposed. These approaches can provide the most appropriate answer for user’s needs by using user context and incorporating information about query provided by combining search technologies. To carry out personalized web search, there is a need to make different techniques on whole of user search process. There are the number of possible deployment of personalized approaches such as personalized web search, personalized recommendation, personalized summarization and filtering systems and etc. but the common feature of all approaches in various domains is that user modeling is utilized to provide personalized information from the Web. So the most important work in personalized approaches is user model mining. User modeling applications and technologies can be used in various domains depending on how the user collected information may be extracted. In addition to, the used techniques to create user model is also different in each of these applications. Since in the previous studies, there was not a complete survey in this field, our purpose is to present a survey on applications and techniques of user modeling from the viewpoint of improvement in search results by considering the existing literature and researches.

Keywords: filtering systems, personalized web search, user modeling, user search behavior

Procedia PDF Downloads 279

Authors: Neşe Taşci, Soner Çubuk, Ece Kök Yetimoğlu, M. Vezir Kahraman

Abstract:

Bisphenol-A (BPA), 2,2-bis(4-hydroxyphenly)propane, is one of the highest usage volume chemicals in the world. Studies showed that BPA maybe has negative effects on the central nervous system, immune and endocrine systems. Several of analytical methods for the analysis of BPA have been reported including electrochemical processes, chemical oxidation, ozonization, spectrophotometric, chromatographic techniques. Compared with other conventional analytical techniques, optic sensors are reliable, providing quick results, low cost, easy to use, stands out as a much more advantageous method because of the high precision and sensitivity. In this work, a new photocured polymeric fluorescence sensor was prepared and characterized for Bisphenol-A (BPA) analysis. Characterization of the membrane was carried out by Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR) and Scanning Electron Microscope (SEM) techniques. The response characteristics of the sensor including dynamic range, pH effect and response time were systematically investigated. Acknowledgment: This work was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under Grant 115Y469.

Keywords: bisphenol-a, fluorescence, photopolymerization, polymeric sensor

Procedia PDF Downloads 235

Authors: Mustapha Yakubu, Ahmed Usman, Hashim Ambursa

Abstract:

This paper presents the findings of a research which sought to investigate techniques used to improve cost and time control of construction projects management practice in Nigeria. However, there is limited research on issues surrounding the practical usage of these techniques. Data were collected through a questionnaire distributed to construction experts through a survey conducted on the 100 construction organisations and 50 construction consultancy firms in the Nigeria aimed at identifying common project cost and time control practices and factors inhibiting effective project control in practice. The study reveals that despite the vast application of control techniques a high proportion of respondents still experienced cost and time overruns on a significant proportion of their projects. Analysis of the survey results concluded that more effort should be geared at the management of the identified top project control inhibiting factors. This paper has outlined some measures for mitigating these inhibiting factors so that the outcome of project time and cost control can be improved in practice.

Keywords: construction project, cost control, Nigeria, time control

Procedia PDF Downloads 312

Authors: V. K. Banga

Abstract:

Robots are now playing a very promising role in industries. Robots are commonly used in applications in repeated operations or where operation by human is either risky or not feasible. In most of the industrial applications, robotic arm manipulators are widely used. Robotic arm manipulator with two link or three link structures is commonly used due to their low degrees-of-freedom (DOF) movement. As the DOF of robotic arm increased, complexity increases. Instrumentation involved with robotics plays very important role in order to interact with outer environment. In this work, optimal control for movement of various DOFs of robotic arm using various soft computing techniques has been presented. We have discussed about different robotic structures having various DOF robotics arm movement. Further stress is on kinematics of the arm structures i.e. forward kinematics and inverse kinematics. Trajectory planning of robotic arms using soft computing techniques is demonstrating the flexibility of this technique. The performance is optimized for all possible input values and results in optimized movement as resultant output. In conclusion, soft computing has been playing very important role for achieving optimized movement of robotic arm. It also requires very limited knowledge of the system to implement soft computing techniques.

Keywords: artificial intelligence, kinematics, robotic arm, neural networks, fuzzy logic

Procedia PDF Downloads 297

Authors: Khadijat T. Bamigbade, Olufade F. W. Onifade

Abstract:

The field of automatic facial expression analysis has been an active research area in the last two decades. Its vast applicability in various domains has drawn so much attention into developing techniques and dataset that mirror real life scenarios. Many techniques such as Local Binary Patterns and its variants (CLBP, LBP-TOP) and lately, deep learning techniques, have been used for facial expression recognition. However, the problem of occlusion has not been sufficiently handled, making their results not applicable in real life situations. This paper develops a simple, yet highly efficient method tagged Local Binary Pattern-Histogram of Gradient (LBP-HOG) with occlusion detection in face image, using a multi-class SVM for Action Unit and in turn expression recognition. Our method was evaluated on three publicly available datasets which are JAFFE, CK, SFEW. Experimental results showed that our approach performed considerably well when compared with state-of-the-art algorithms and gave insight to occlusion detection as a key step to handling expression in wild.

Keywords: automatic facial expression analysis, local binary pattern, LBP-HOG, occlusion detection

Procedia PDF Downloads 169

Authors: Mohammad Javad Seddighi, Avar Almukhtar

Abstract:

The occurrence of natural disasters, such as floods and earthquakes, can cause significant damage to heritage sites and surrounding areas. In Iran, the city of Bam was devastated by an earthquake in 2003, which had a major impact on the rivers and watercourses around the city. This study aims to investigate the environmental design techniques and sustainable hazard mitigation strategies that can be employed to preserve heritage sites in the face of natural disasters, using the Bam experience as a case study. The research employs a mixed-methods approach, combining both qualitative and quantitative data collection and analysis methods. The study begins with a comprehensive literature review of recent publications on environmental design techniques and sustainable hazard mitigation strategies in heritage conservation. This is followed by a field study of the rivers and watercourses around Bam, including the Adoori River (Talangoo) and other watercourses, to assess the current conditions and identify potential hazards. The data collected from the field study is analysed using statistical methods and GIS mapping techniques. The findings of this study reveal the importance of sustainable hazard mitigation strategies and environmental design techniques in preserving heritage sites during natural disasters. The study suggests that these techniques can be used to prevent the outbreak of another natural disaster in Bam and the surrounding areas. Specifically, the study recommends the establishment of a comprehensive early warning system, the creation of flood-resistant landscapes, and the use of eco-friendly building materials in the reconstruction of heritage sites. These findings contribute to the current knowledge of sustainable hazard mitigation and environmental design in heritage conservation.

Keywords: natural disasters, heritage conservation, sustainable hazard mitigation, environmental design, landscape architecture, flood management, disaster resilience

Procedia PDF Downloads 88

Authors: Michael Salib, Samer Ezeldin, Ahmed Waly

Abstract:

There are numerous challenges and problems facing the construction industry in several countries in the Middle East, as a result of numerous economic and political effects. As an example in Egypt, several construction companies have shut down and left the market since 2016. The closure of these companies occurred, as they did not respond with the suitable techniques and strategies that will enable them to survive during this economic turmoil period. A research is conducted in order to identify adequate strategies to be implemented by the Egyptian contractors that could allow them survive and keep competing during such economic hardship period. Two different techniques were used in order to identify these startegies. First, a deep research were conducted on the companies located in countries that suffered similar economic harship to identify the strategies they used in order to survive. Second, interviews were conducted with experts in the construction field in order to list the effective strategies they used that allowed them to survive. Moreover, at the end of each interview, the experts were asked to rate the applicability of the previously identified strategies used in the foreign countries, then the efficiency of each strategy if used in Egypt. A framework model is developed in order to assist the construction companies in choosing the suitable techniques to their company size, through identifying the top ranked strategies and techniques that should be adopted by the company based on the parameters given to the model. In order to verify this framework, the financial statements of two leading companies in the Egyptian construction market were studied. The first Contractor has applied nearly all the top ranked strategies identified in this paper, while the other contractor has applied only few of the identified top ranked strategies. Finally, another expert interviews were conducted in order to validate the framework. These experts were asked to test the model and rate through a questionnaire its applicability and effectiveness.

Keywords: construction management, economic hardship, recession, survive

Procedia PDF Downloads 126

Authors: Mohammad Alqahtani, Eric Atwell

Abstract:

This paper reviews and classifies most of the important types of search techniques that have been applied on the holy Quran. Then, it addresses the limitations in these techniques. Additionally, this paper surveys most existing Quranic ontologies and what are their deficiencies. Finally, it explains a new search tool called: A semantic search tool for Al Quran based on Qur’anic ontologies. This tool will overcome all limitations in the existing Quranic search applications.

Keywords: holy Quran, natural language processing (NLP), semantic search, information retrieval (IR), ontology

Procedia PDF Downloads 572