Search results for: methods of Lagrange multipliers
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 14926

Search results for: methods of Lagrange multipliers

13876 A Framework for Review Spam Detection Research

Authors: Mohammadali Tavakoli, Atefeh Heydari, Zuriati Ismail, Naomie Salim

Abstract:

With the increasing number of people reviewing products online in recent years, opinion sharing websites has become the most important source of customers’ opinions. Unfortunately, spammers generate and post fake reviews in order to promote or demote brands and mislead potential customers. These are notably destructive not only for potential customers but also for business holders and manufacturers. However, research in this area is not adequate, and many critical problems related to spam detection have not been solved to date. To provide green researchers in the domain with a great aid, in this paper, we have attempted to create a high-quality framework to make a clear vision on review spam-detection methods. In addition, this report contains a comprehensive collection of detection metrics used in proposed spam-detection approaches. These metrics are extremely applicable for developing novel detection methods.

Keywords: fake reviews, feature collection, opinion spam, spam detection

Procedia PDF Downloads 394
13875 ACBM: Attention-Based CNN and Bi-LSTM Model for Continuous Identity Authentication

Authors: Rui Mao, Heming Ji, Xiaoyu Wang

Abstract:

Keystroke dynamics are widely used in identity recognition. It has the advantage that the individual typing rhythm is difficult to imitate. It also supports continuous authentication through the keyboard without extra devices. The existing keystroke dynamics authentication methods based on machine learning have a drawback in supporting relatively complex scenarios with massive data. There are drawbacks to both feature extraction and model optimization in these methods. To overcome the above weakness, an authentication model of keystroke dynamics based on deep learning is proposed. The model uses feature vectors formed by keystroke content and keystroke time. It ensures efficient continuous authentication by cooperating attention mechanisms with the combination of CNN and Bi-LSTM. The model has been tested with Open Data Buffalo dataset, and the result shows that the FRR is 3.09%, FAR is 3.03%, and EER is 4.23%. This proves that the model is efficient and accurate on continuous authentication.

Keywords: keystroke dynamics, identity authentication, deep learning, CNN, LSTM

Procedia PDF Downloads 137
13874 In Vitro Antifungal Activity of Essential Oil Artemisia Absinthium

Authors: Bouchenak Fatima, Lmegharbi Abdelbaki, Houssem Degaichia, Benrebiha Fatima

Abstract:

The essential oil composition of the leaf of Artemisia absinthium from region of Cherchell (The south of Algeria) was investigated by GC, GC-MS. 27 constituents were identified correspond to 84, 63% of the total oil. The major components are Thujone (60, 82%), Chamazulènel (16, 62%), ρ-cymène (4, 29%) and 2-carène (4.25%). The antimicrobial activity of oil was tested in vitro by two methods (agar diffusion and microdilution) on three plant pathogenic fungi. This oil has been tested for antimicrobial activity against three pathogenic fungi (Botrytis cinerea, Fusarium culmorum and Helminthosporium Sp.).The study of activity was evaluated by two methods: Method of diffusion in gelose and the minimum inhibitory concentration MIC. This oil exhibited an interesting antimicrobial activity. A preliminary study showed that this oil presented high toxicity against this fungus. These results, although preliminary show a good antifungal activity, to limit and inhibit stop the development of those pathogen agent.

Keywords: artemisia absinthian, extraction process, chemical study, antifungal activity

Procedia PDF Downloads 462
13873 DeepOmics: Deep Learning for Understanding Genome Functioning and the Underlying Genetic Causes of Disease

Authors: Vishnu Pratap Singh Kirar, Madhuri Saxena

Abstract:

Advancement in sequence data generation technologies is churning out voluminous omics data and posing a massive challenge to annotate the biological functional features. With so much data available, the use of machine learning methods and tools to make novel inferences has become obvious. Machine learning methods have been successfully applied to a lot of disciplines, including computational biology and bioinformatics. Researchers in computational biology are interested to develop novel machine learning frameworks to classify the huge amounts of biological data. In this proposal, it plan to employ novel machine learning approaches to aid the understanding of how apparently innocuous mutations (in intergenic DNA and at synonymous sites) cause diseases. We are also interested in discovering novel functional sites in the genome and mutations in which can affect a phenotype of interest.

Keywords: genome wide association studies (GWAS), next generation sequencing (NGS), deep learning, omics

Procedia PDF Downloads 79
13872 Authentication of Physical Objects with Dot-Based 2D Code

Authors: Michał Glet, Kamil Kaczyński

Abstract:

Counterfeit goods and documents are a global problem, which needs more and more sophisticated methods of resolving it. Existing techniques using watermarking or embedding symbols on objects are not suitable for all use cases. To address those special needs, we created complete system allowing authentication of paper documents and physical objects with flat surface. Objects are marked using orientation independent and resistant to camera noise 2D graphic codes, named DotAuth. Based on the identifier stored in 2D code, the system is able to perform basic authentication and allows to conduct more sophisticated analysis methods, e.g., relying on augmented reality and physical properties of the object. In this paper, we present the complete architecture, algorithms and applications of the proposed system. Results of the features comparison of the proposed solution and other products are presented as well, pointing to the existence of many advantages that increase usability and efficiency in the means of protecting physical objects.

Keywords: anti-forgery, authentication, paper documents, security

Procedia PDF Downloads 118
13871 Efficacy of CAM Methods for Pain Reduction in Acute Non-specific Lower Back Pain

Authors: John Gaber

Abstract:

Objectives: Complementary and alternative medicine (CAM) is a medicine or health practice that is used alongside conventional practice. Nowadays, CAM is commonly used in North America and other countries, and there is a need for more scientific study to understand its efficacy in different clinical cases. This retrospective study explores the effectiveness and recovery time of CAMs such as cupping, acupuncture, and sotai to treat cases of non-specific low back pain (ANLBP). Methods: We assessed the effectiveness of acupuncture, cupping, and sotai methods on pain and for the treatment of ANLBP. We have compared the magnitude of pain relief using a pain scale assessment method to compare the efficacy of each treatment. The Face Pain Scale assessment was conducted before and 24 hours post-treatment. This retrospective study analyzed 40 patients and categorized them according to the treatment they received. The study included the control group, and the three intervention groups, each with ten patients. Each of the three intervention groups received one of the intervention methods. The first group received the cupping treatment, where cups were placed on the lower back of both sides on points: BL23, BL25, BL26, BL54, BL37, BL40, and BL57. After vacuuming, the cups will stay for 10-15 minutes under infrared light (IR) heating. IR heating is applied by an infrared heat lamp. The second group received the acupuncture treatment, placing needles on points: BL23, BL25, BL26, BL52BL54, GB30, BL37, BL40, BL57, BL59, BL60, and KI3. The needles will be simulated with IR light. The final group received the sotai treatment, a Japanese form of structural realignment that relieves pain, balance, and mobility -moving the body naturally and spontaneously towards a comfortable direction by focusing on the inner feeling and synchronizing with the patient’s breathing. The SPSS statistical software was used to analyze the data using repeated-measures ANOVA. The data collected demonstrates the change in the FPS assessment method value over the course of treatment. p<0.05 was considered statistically significant. Results: In the cupping, acupuncture, and sotai therapy groups, the mean of the FPS value reduced from 8.7±1.2, 8.8±1.2, 9.0±0.8 before the intervention to 3.5±1.4, 4.3±1.4, 3.3±1.3, 24 hours after the intervention, respectively. The data collected shows that the CAM methods included in this study all show improvements in pain relief 24 hours after treatment. Conclusion: Complementary and alternative medicine were developed to treat injuries and illnesses with the whole body in mind, designed to be used in addition to standard treatments. The data above shows that the use of these treatments can have a pain-relieving effect, but more research should be done on the matter, as finding CAM methods that are efficacious is crucial in the landscape of health sciences.

Keywords: acupuncture, cupping, alternative medicine, rehabilitation, acute injury

Procedia PDF Downloads 45
13870 Research on the Efficiency and Driving Elements of Manufacturing Transformation and Upgrading in the Context of Digitization

Authors: Chen Zhang; Qiang Wang

Abstract:

With the rapid development of the new generation of digital technology, various industries have created more and more value by using digital technology, accelerating the digital transformation of various industries. The economic form of human society has evolved with the progress of technology, and in this context, the power conversion, transformation and upgrading of the manufacturing industry in terms of quality, efficiency and energy change has become a top priority. Based on the digitalization background, this paper analyzes the transformation and upgrading efficiency of the manufacturing industry and evaluates the impact of the driving factors, which have very important theoretical and practical significance. This paper utilizes qualitative research methods, entropy methods, data envelopment analysis methods and econometric models to explore the transformation and upgrading efficiency of manufacturing enterprises and driving factors. The study shows that the transformation and upgrading efficiency of the manufacturing industry shows a steady increase, and regions rich in natural resources and social resources provide certain resources for transformation and upgrading. The ability of scientific and technological innovation has been improved, but there is still much room for progress in the transformation of scientific and technological innovation achievements. Most manufacturing industries pay more attention to green manufacturing and sustainable development. In addition, based on the existing problems, this paper puts forward suggestions for improving infrastructure construction, developing the technological innovation capacity of enterprises, green production and sustainable development.

Keywords: digitization, manufacturing firms, transformation and upgrading, efficiency, driving factors

Procedia PDF Downloads 49
13869 Evaluating the Permeability Coefficient of Sandy Soil for Grouting to Reinforce Soft Soil in Binh Duong, Vietnam

Authors: Trung Le Thanh

Abstract:

Soil permeability coefficient is an important parameter that affects the effectiveness of mortar restoration work to reinforce soft soil. Currently, there are many methods to determine the permeability coefficient of ground through laboratory and field experiments. However, the value of the permeability coefficient is determined very differently depending on the geology in general and the sand base in particular. This article presents how to determine the permeability coefficient of sand foundation in Phu My Ward, Tan Uyen City, Binh Duong. The author analyzes and evaluates the advantages and disadvantages of assessment methods based on the data and results obtained, and on that basis recommends a suitable method for determining the permeability coefficient for sand foundations. The research results serve the evaluation of the effectiveness of grouting to reinforce soft ground in general, and grouting of bored piles in particular.

Keywords: permeability coefficient, soft soil, shaft grouting, post grouting, jet grouting

Procedia PDF Downloads 55
13868 Measuring Technology of Airship Propeller Thrust and Torque in China Academy of Aerospace Aerodynamics

Authors: Ma Hongqiang, Yang Hui, Wen Haoju, Feng Jiabo, Bi Zhixian, Nie Ying

Abstract:

In order to measure thrust and torque of airship propeller, a two-component balance and data acquisition system was developed in China Academy of Aerospace Aerodynamics(CAAA) in early time. During the development, some problems were encountered. At first, the measuring system and its protective parts made the weight of whole system increase significantly. Secondly, more parts might induce more failures, so the reliability of the system was decreased. In addition, the rigidity of the system was lowered, and the structure was more possible to vibrate. Therefore, CAAA and the Academy of Opto-Electronics, Chinese Academy of Science(AOECAS) developed a new technology, use the propeller supporting rack as a spring element, attach strain gages onto it, sum up as a generalized balance. And new math models, new calibration methods and new load determining methods were developed.

Keywords: airship, propeller, thrust and torque, flight test

Procedia PDF Downloads 329
13867 Assessment of the Energy Balance Method in the Case of Masonry Domes

Authors: M. M. Sadeghi, S. Vahdani

Abstract:

Masonry dome structures had been widely used for covering large spans in the past. The seismic assessment of these historical structures is very complicated due to the nonlinear behavior of the material, their rigidness, and special stability configuration. The assessment method based on energy balance concept, as well as the standard pushover analysis, is used to evaluate the effectiveness of these methods in the case of masonry dome structures. The Soltanieh dome building is used as an example to which two methods are applied. The performance points are given from superimposing the capacity, and demand curves in Acceleration Displacement Response Spectra (ADRS) and energy coordination are compared with the nonlinear time history analysis as the exact result. The results show a good agreement between the dynamic analysis and the energy balance method, but standard pushover method does not provide an acceptable estimation.

Keywords: energy balance method, pushover analysis, time history analysis, masonry dome

Procedia PDF Downloads 266
13866 Implementation of a Virtual Testbed for Secure IoT Firmware Update Using Blockchain

Authors: Tarun Chand, Michael Jurczyk

Abstract:

With the increasing need and popularity of IoT devices and how integrated they are becoming in our daily lives and industries, these devices make for a very lucrative target for malicious actors. And since these devices have such limited resources, the implementation of robust security features is a tradeoff to be made for the actual functionality the device was intended for. This makes them an easy target with high returns. Several frameworks for the secure firmware update of these devices have been recently proposed in the literature. They focus on methods such as blockchains and distributed file systems to secure firmware updates, but do not go into the details of the actual implementation of these frameworks and the lower-level interactions among these methods used. This work integrates some of these security measures into one overall framework and details the actual lower-level implementation of this framework in a virtual dockerized testbed running on AWS.

Keywords: blockchain, Ethereum, Geth, IPFS, secure IoT-firmware update, virtual testbed development

Procedia PDF Downloads 46
13865 The Impact of Cooperative Learning on Numerical Methods Course

Authors: Sara Bilal, Abdi Omar Shuriye, Raihan Othman

Abstract:

Numerical Methods is a course that can be conducted using workshops and group discussion. This study has been implemented on undergraduate students of level two at the Faculty of Engineering, International Islamic University Malaysia. The Numerical Method course has been delivered to two Sections 1 and 2 with 44 and 22 students in each section, respectively. Systematic steps have been followed to apply the student centered learning approach in teaching Numerical Method course. Initially, the instructor has chosen the topic which was Euler’s Method to solve Ordinary Differential Equations (ODE) to be learned. The students were then divided into groups with five members in each group. Initial instructions have been given to the group members to prepare their subtopics before meeting members from other groups to discuss the subtopics in an expert group inside the classroom. For the time assigned for the classroom discussion, the setting of the classroom was rearranged to accommodate the student centered learning approach. Teacher strength was by monitoring the process of learning inside and outside the class. The students have been assessed during the migrating to the expert groups, recording of a video explanation outside the classroom and during the final examination. Euler’s Method to solve the ODE was set as part of Question 3(b) in the final exam. It is observed that none of the students from both sections obtained a zero grade in Q3(b), compared to Q3(a) and Q3(c). Also, for Section 1(44 students), 29 students obtained the full mark of 7/7, while only 10 obtained 7/7 for Q3(a) and no students obtained 6/6 for Q3(c). Finally, we can recommend that the Numerical Method course be moved toward more student-centered Learning classrooms where the students will be engaged in group discussion rather than having a teacher one man show.

Keywords: teacher centered learning, student centered learning, mathematic, numerical methods

Procedia PDF Downloads 348
13864 Optimization of Personnel Selection Problems via Unconstrained Geometric Programming

Authors: Vildan Kistik, Tuncay Can

Abstract:

From a business perspective, cost and profit are two key factors for businesses. The intent of most businesses is to minimize the cost to maximize or equalize the profit, so as to provide the greatest benefit to itself. However, the physical system is very complicated because of technological constructions, rapid increase of competitive environments and similar factors. In such a system it is not easy to maximize profits or to minimize costs. Businesses must decide on the competence and competence of the personnel to be recruited, taking into consideration many criteria in selecting personnel. There are many criteria to determine the competence and competence of a staff member. Factors such as the level of education, experience, psychological and sociological position, and human relationships that exist in the field are just some of the important factors in selecting a staff for a firm. Personnel selection is a very important and costly process in terms of businesses in today's competitive market. Although there are many mathematical methods developed for the selection of personnel, unfortunately the use of these mathematical methods is rarely encountered in real life. In this study, unlike other methods, an exponential programming model was established based on the possibilities of failing in case the selected personnel was started to work. With the necessary transformations, the problem has been transformed into unconstrained Geometrical Programming problem and personnel selection problem is approached with geometric programming technique. Personnel selection scenarios for a classroom were established with the help of normal distribution and optimum solutions were obtained. In the most appropriate solutions, the personnel selection process for the classroom has been achieved with minimum cost.

Keywords: geometric programming, personnel selection, non-linear programming, operations research

Procedia PDF Downloads 253
13863 Genetic Algorithm and Multi Criteria Decision Making Approach for Compressive Sensing Based Direction of Arrival Estimation

Authors: Ekin Nurbaş

Abstract:

One of the essential challenges in array signal processing, which has drawn enormous research interest over the past several decades, is estimating the direction of arrival (DOA) of plane waves impinging on an array of sensors. In recent years, the Compressive Sensing based DoA estimation methods have been proposed by researchers, and it has been discovered that the Compressive Sensing (CS)-based algorithms achieved significant performances for DoA estimation even in scenarios where there are multiple coherent sources. On the other hand, the Genetic Algorithm, which is a method that provides a solution strategy inspired by natural selection, has been used in sparse representation problems in recent years and provides significant improvements in performance. With all of those in consideration, in this paper, a method that combines the Genetic Algorithm (GA) and the Multi-Criteria Decision Making (MCDM) approaches for Direction of Arrival (DoA) estimation in the Compressive Sensing (CS) framework is proposed. In this method, we generate a multi-objective optimization problem by splitting the norm minimization and reconstruction loss minimization parts of the Compressive Sensing algorithm. With the help of the Genetic Algorithm, multiple non-dominated solutions are achieved for the defined multi-objective optimization problem. Among the pareto-frontier solutions, the final solution is obtained with the multiple MCDM methods. Moreover, the performance of the proposed method is compared with the CS-based methods in the literature.

Keywords: genetic algorithm, direction of arrival esitmation, multi criteria decision making, compressive sensing

Procedia PDF Downloads 134
13862 Study of the Performances of an Environmental Concrete Based on Recycled Aggregates and Marble Waste Fillers Addition

Authors: Larbi Belagraa, Miloud Beddar, Abderrazak Bouzid

Abstract:

The needs of the construction sector still increasing for concrete. However, the shortage of natural resources of aggregate could be a problem for the concrete industry, in addition to the negative impact on the environment due to the demolition wastes. Recycling aggregate from construction and demolition (C&D) waste presents a major interest for users and researchers of concrete since this constituent can occupies more than 70% of concrete volume. The aim of the study here in is to assess the effect of sulfate resistant cement combined with the local mineral addition of marble waste fillers on the mechanical behavior of a recycled aggregate concrete (RAC). Physical and mechanical properties of RAC including the density, the flexural and the compressive strength were studied. The non destructive test methods (pulse-velocity, rebound hammer) were performed . The results obtained were compared to crushed aggregate concrete (CAC) using the normal compressive testing machine test method. The optimal content of 5% marble fillers showed an improvement for both used test methods (compression, flexion and NDT). Non-destructive methods (ultrasonic and rebound hammer test) can be used to assess the strength of RAC, but a correction coefficient is required to obtain a similar value to the compressive strength given by the compression tests. The study emphasizes that these waste materials can be successfully and economically utilized as additional inert filler in RAC formulation within similar performances compared to a conventional concrete.

Keywords: marble waste fillers, mechanical strength, natural aggregate, non-destructive testing (NDT), recycled aggregate concrete

Procedia PDF Downloads 295
13861 Different Methods of Producing Bioemulsifier by Bacillus licheniformis Strains

Authors: Saba Pajuhan, Afshin Farahbakhsh, S. M. M. Dastgheib

Abstract:

Biosurfactants and bioemulsifiers are a structurally diverse group of surface-active molecules synthesized by microorganisms, they are amphipathic molecules which reduce surface and interfacial tensions and widely used in pharmaceutical, cosmetic, food and petroleum industries. In this paper, several methods of bioemulsifer synthesis and purification by Bacillus licheniformis strains (namely ACO1, PTCC 1595 and ACO4) were investigated. Strains were grown in nutrient broth with different conditions in order to get maximum production of bioemulsifer. The purification of bio emulsifier and the quality evaluation of the product was done by adding sulfuric acid (H₂SO₄) (98%), Ethanol or HCl to the solution followed by centrifuging. To determine the optimal conditions yielding the highest bioemulsifier production, the effect of various carbon and nitrogen sources, temperature, NaCl concentration, pH, O₂ levels, incubation time are indispensable and all of them were highly effective in bioemulsifiers production.

Keywords: biosurfactant, bioemulsifier, purification, surface tension, interfacial tension

Procedia PDF Downloads 255
13860 Use of Artificial Intelligence in Teaching Practices: A Meta-Analysis

Authors: Azmat Farooq Ahmad Khurram, Sadaf Aslam

Abstract:

This meta-analysis systematically examines the use of artificial intelligence (AI) in instructional methods across diverse educational settings through a thorough analysis of empirical research encompassing various disciplines, educational levels, and regions. This study aims to assess the effects of AI integration on teaching methodologies, classroom dynamics, teachers' roles, and student engagement. Various research methods were used to gather data, including literature reviews, surveys, interviews, and focus group discussions. Findings indicate paradigm shifts in teaching and education, identify emerging trends, practices, and the application of artificial intelligence in learning, and provide educators, policymakers, and stakeholders with guidelines and recommendations for effectively integrating AI in educational contexts. The study concludes by suggesting future research directions and practical considerations for maximizing AI's positive influence on pedagogical practices.

Keywords: artificial intelligence, teaching practices, meta-analysis, teaching-learning

Procedia PDF Downloads 43
13859 Climate Change in Awash River Basin of Ethiopia: A Projection Study Using Global and Regional Climate Model Simulations

Authors: Mahtsente Tadese, Lalit Kumar, Richard Koech

Abstract:

The aim of this study was to project and analyze climate change in the Awash River Basin (ARB) using bias-corrected Global and Regional Climate Model simulations. The analysis included a baseline period from 1986-2005 and two future scenarios (the 2050s and 2070s) under two representative concentration pathways (RCP4.5 and RCP8.5). Bias correction methods were evaluated using graphical and statistical methods. Following the evaluation of bias correction methods, the Distribution Mapping (DM) and Power Transformation (PT) were used for temperature and precipitation projection, respectively. The 2050s and 2070s RCP4 simulations showed an increase in precipitation during half of the months with 32 and 10%, respectively. Moreover, the 2050s and 2070s RCP8.5 simulation indicated a decrease in precipitation with 18 and 26%, respectively. The 2050s and 2070s RCP8.5 simulation indicated a significant decrease in precipitation in four of the months (February/March to May) with the highest decreasing rate of 34.7%. The 2050s and 2070s RCP4.5 simulation showed an increase of 0.48-2.6 °C in maximum temperature. In the case of RCP8.5, the increase rate reached 3.4 °C and 4.1 °C in the 2050s and 2070s, respectively. The changes in precipitation and temperature might worsen the water stress, flood, and drought in ARB. Moreover, the critical focus should be given to mitigation strategies and management options to reduce the negative impact. The findings of this study provide valuable information on future precipitation and temperature change in ARB, which will help in the planning and design of sustainable mitigation approaches in the basin.

Keywords: variability, climate change, Awash River Basin, precipitation

Procedia PDF Downloads 157
13858 A Supervised Face Parts Labeling Framework

Authors: Khalil Khan, Ikram Syed, Muhammad Ehsan Mazhar, Iran Uddin, Nasir Ahmad

Abstract:

Face parts labeling is the process of assigning class labels to each face part. A face parts labeling method (FPL) which divides a given image into its constitutes parts is proposed in this paper. A database FaceD consisting of 564 images is labeled with hand and make publically available. A supervised learning model is built through extraction of features from the training data. The testing phase is performed with two semantic segmentation methods, i.e., pixel and super-pixel based segmentation. In pixel-based segmentation class label is provided to each pixel individually. In super-pixel based method class label is assigned to super-pixel only – as a result, the same class label is given to all pixels inside a super-pixel. Pixel labeling accuracy reported with pixel and super-pixel based methods is 97.68 % and 93.45% respectively.

Keywords: face labeling, semantic segmentation, classification, face segmentation

Procedia PDF Downloads 238
13857 A Heart Arrhythmia Prediction Using Machine Learning’s Classification Approach and the Concept of Data Mining

Authors: Roshani S. Golhar, Neerajkumar S. Sathawane, Snehal Dongre

Abstract:

Background and objectives: As the, cardiovascular illnesses increasing and becoming cause of mortality worldwide, killing around lot of people each year. Arrhythmia is a type of cardiac illness characterized by a change in the linearity of the heartbeat. The goal of this study is to develop novel deep learning algorithms for successfully interpreting arrhythmia using a single second segment. Because the ECG signal indicates unique electrical heart activity across time, considerable changes between time intervals are detected. Such variances, as well as the limited number of learning data available for each arrhythmia, make standard learning methods difficult, and so impede its exaggeration. Conclusions: The proposed method was able to outperform several state-of-the-art methods. Also proposed technique is an effective and convenient approach to deep learning for heartbeat interpretation, that could be probably used in real-time healthcare monitoring systems

Keywords: electrocardiogram, ECG classification, neural networks, convolutional neural networks, portable document format

Procedia PDF Downloads 57
13856 Enabling Quantitative Urban Sustainability Assessment with Big Data

Authors: Changfeng Fu

Abstract:

Sustainable urban development has been widely accepted a common sense in the modern urban planning and design. However, the measurement and assessment of urban sustainability, especially the quantitative assessment have been always an issue obsessing planning and design professionals. This paper will present an on-going research on the principles and technologies to develop a quantitative urban sustainability assessment principles and techniques which aim to integrate indicators, geospatial and geo-reference data, and assessment techniques together into a mechanism. It is based on the principles and techniques of geospatial analysis with GIS and statistical analysis methods. The decision-making technologies and methods such as AHP and SMART are also adopted to address overall assessment conclusions. The possible interfaces and presentation of data and quantitative assessment results are also described. This research is based on the knowledge, situations and data sources of UK, but it is potentially adaptable to other countries or regions. The implementation potentials of the mechanism are also discussed.

Keywords: urban sustainability assessment, quantitative analysis, sustainability indicator, geospatial data, big data

Procedia PDF Downloads 344
13855 Analysis of Splicing Methods for High Speed Automated Fibre Placement Applications

Authors: Phillip Kearney, Constantina Lekakou, Stephen Belcher, Alessandro Sordon

Abstract:

The focus in the automotive industry is to reduce human operator and machine interaction, so manufacturing becomes more automated and safer. The aim is to lower part cost and construction time as well as defects in the parts, sometimes occurring due to the physical limitations of human operators. A move to automate the layup of reinforcement material in composites manufacturing has resulted in the use of tapes that are placed in position by a robotic deposition head, also described as Automated Fibre Placement (AFP). The process of AFP is limited with respect to the finite amount of material that can be loaded into the machine at any one time. Joining two batches of tape material together involves a splice to secure the ends of the finishing tape to the starting edge of the new tape. The splicing method of choice for the majority of prepreg applications is a hand stich method, and as the name suggests requires human input to achieve. This investigation explores three methods for automated splicing, namely, adhesive, binding and stitching. The adhesive technique uses an additional adhesive placed on the tape ends to be joined. Binding uses the binding agent that is already impregnated onto the tape through the application of heat. The stitching method is used as a baseline to compare the new splicing methods to the traditional technique currently in use. As the methods will be used within a High Speed Automated Fibre Placement (HSAFP) process, this meant the parameters of the splices have to meet certain specifications: (a) the splice must be able to endure a load of 50 N in tension applied at a rate of 1 mm/s; (b) the splice must be created in less than 6 seconds, dictated by the capacity of the tape accumulator within the system. The samples for experimentation were manufactured with controlled overlaps, alignment and splicing parameters, these were then tested in tension using a tensile testing machine. Initial analysis explored the use of the impregnated binding agent present on the tape, as in the binding splicing technique. It analysed the effect of temperature and overlap on the strength of the splice. It was found that the optimum splicing temperature was at the higher end of the activation range of the binding agent, 100 °C. The optimum overlap was found to be 25 mm; it was found that there was no improvement in bond strength from 25 mm to 30 mm overlap. The final analysis compared the different splicing methods to the baseline of a stitched bond. It was found that the addition of an adhesive was the best splicing method, achieving a maximum load of over 500 N compared to the 26 N load achieved by a stitching splice and 94 N by the binding method.

Keywords: analysis, automated fibre placement, high speed, splicing

Procedia PDF Downloads 137
13854 Optimization of Process Parameters for Rotary Electro Discharge Machining Using EN31 Tool Steel: Present and Future Scope

Authors: Goutam Dubey, Varun Dutta

Abstract:

In the present study, rotary-electro discharge machining of EN31 tool steel has been carried out using a pure copper electrode. Various response variables such as Material Removal Rate (MRR), Tool Wear Rate (TWR), and Machining Rate (MR) have been studied against the selected process variables. The selected process variables were peak current (I), voltage (V), duty cycle, and electrode rotation (N). EN31 Tool Steel is hardened, high carbon steel which increases its hardness and reduces its machinability. Reduced machinability means it not economical to use conventional methods to machine EN31 Tool Steel. So, non-conventional methods play an important role in machining of such materials.

Keywords: electric discharge machining, EDM, tool steel, tool wear rate, optimization techniques

Procedia PDF Downloads 187
13853 Improving Enhanced Oil Recovery by Using Alkaline-Surfactant-Polymer Injection and Nanotechnology

Authors: Amir Gerayeli, Babak Moradi

Abstract:

The continuously declining oil reservoirs and reservoirs aging have created a huge demand for utilization of Enhanced Oil Recovery (EOR) methods recently. Primary and secondary oil recovery methods have various limitations and are not practical for all reservoirs. Therefore, it is necessary to use chemical methods to improve oil recovery efficiency by reducing oil and water surface tension, increasing sweeping efficiency, and reducing displacer phase viscosity. One of the well-known methods of oil recovery is Alkaline-Surfactant-Polymer (ASP) flooding that shown to have significant impact on enhancing oil recovery. As some of the biggest oil reservoirs including those of Iran’s are fractional reservoirs with substantial amount of trapped oil in their fractures, the use of Alkaline-Surfactant-Polymer (ASP) flooding method is increasingly growing, the method in which the impact of several parameters including type and concentration of the Alkaline, Surfactant, and polymer are particularly important. This study investigated the use of Nano particles to improve Enhanced Oil Recovery (EOR). The study methodology included performing several laboratory tests on drill cores extracted from Karanj Oil field Asmary Formation in Khuzestan, Iran. In the experiments performed, Sodium dodecyl benzenesulfonate (SDBS) and 1-dodecyl-3-methylimidazolium chloride ([C12mim] [Cl])) were used as surfactant, hydrolyzed polyacrylamide (HPAM) and guar gum were used as polymer, Sodium hydroxide (NaOH) as alkaline, and Silicon dioxide (SiO2) and Magnesium oxide (MgO) were used as Nano particles. The experiment findings suggest that water viscosity increased from 1 centipoise to 5 centipoise when hydrolyzed polyacrylamide (HPAM) and guar gum were used as polymer. The surface tension between oil and water was initially measured as 25.808 (mN/m). The optimum surfactant concentration was found to be 500 p, at which the oil and water tension surface was measured to be 2.90 (mN/m) when [C12mim] [Cl] was used, and 3.28 (mN/m) when SDBS was used. The Nano particles concentration ranged from 100 ppm to 1500 ppm in this study. The optimum Nano particle concentration was found to be 1000 ppm for MgO and 500 ppm for SiO2.

Keywords: alkaline-surfactant-polymer, ionic liquids, relative permeability, reduced surface tension, tertiary enhanced oil recovery, wettability change

Procedia PDF Downloads 139
13852 Nonparametric Estimation of Risk-Neutral Densities via Empirical Esscher Transform

Authors: Manoel Pereira, Alvaro Veiga, Camila Epprecht, Renato Costa

Abstract:

This paper introduces an empirical version of the Esscher transform for risk-neutral option pricing. Traditional parametric methods require the formulation of an explicit risk-neutral model and are operational only for a few probability distributions for the returns of the underlying. In our proposal, we make only mild assumptions on the pricing kernel and there is no need for the formulation of the risk-neutral model for the returns. First, we simulate sample paths for the returns under the physical distribution. Then, based on the empirical Esscher transform, the sample is reweighted, giving rise to a risk-neutralized sample from which derivative prices can be obtained by a weighted sum of the options pay-offs in each path. We compare our proposal with some traditional parametric pricing methods in four experiments with artificial and real data.

Keywords: esscher transform, generalized autoregressive Conditional Heteroscedastic (GARCH), nonparametric option pricing

Procedia PDF Downloads 474
13851 Effects of Climate Change on Hydraulic Design Methods of Railway Infrastructures

Authors: Chiara Cesali

Abstract:

The effects of climate change are increasingly evident: increases in temperature (i.e. global warming), greater frequency of extreme weather events, i.e. storms, floods, which often affect transport infrastructures. Large-scale climatological models with long-term horizons (up to 2100) show the possibility of significant increases in precipitation in the future, according to the greenhouse gas emissions scenarios from IPCC. Consequently, the insufficiency of existing hydraulic works (i.e. bridges, culverts, drainage systems) may be more frequent, or those currently being designed may become insufficient in the future. Thus, the hydraulic design methods of transport infrastructure must begin to take into account the influence of climate change. To this purpose, criteria for applying to the hydraulic design of a railway infrastructure some of the approaches currently available for determining design rainfall intensity and/or peak discharge flow on the basis of possible climate change scenarios are defined and proposed in the paper. Some application cases are also described.

Keywords: climate change, hydraulic design, precipitation, railway

Procedia PDF Downloads 154
13850 Molecular Interaction of Acetylcholinesterase with Flavonoids Involved in Neurodegenerative Diseases

Authors: W. Soufi, F. Boukli Hacene, S. Ghalem

Abstract:

Alzheimer's disease (AD) is a neurodegenerative disease that leads to a progressive and permanent deterioration of nerve cells. This disease is progressively accompanied by an intellectual deterioration leading to psychological manifestations and behavioral disorders that lead to a loss of autonomy. It is the most frequent of degenerative dementia. Alzheimer's disease (AD), which affects a growing number of people, has become a major public health problem in a few years. In the context of the study of the mechanisms governing the evolution of AD disease, we have found that natural flavonoids are good acetylcholinesterase inhibitors that reduce the rate of ßA secretion in neurons. This work is to study the inhibition of acetylcholinesterase (AChE) which is an enzyme involved in Alzheimer's disease, by methods of molecular modeling. These results will probably help in the development of an effective therapeutic tool in the fight against the development of Alzheimer's disease. Our goal of the research is to study the inhibition of acetylcholinesterase (AChE) by molecular modeling methods.

Keywords: Alzheimer's disease, acetylcholinesterase, flavonoids, molecular modeling

Procedia PDF Downloads 85
13849 Tumor Detection of Cerebral MRI by Multifractal Analysis

Authors: S. Oudjemia, F. Alim, S. Seddiki

Abstract:

This paper shows the application of multifractal analysis for additional help in cancer diagnosis. The medical image processing is a very important discipline in which many existing methods are in search of solutions to real problems of medicine. In this work, we present results of multifractal analysis of brain MRI images. The purpose of this analysis was to separate between healthy and cancerous tissue of the brain. A nonlinear method based on multifractal detrending moving average (MFDMA) which is a generalization of the detrending fluctuations analysis (DFA) is used for the detection of abnormalities in these images. The proposed method could make separation of the two types of brain tissue with success. It is very important to note that the choice of this non-linear method is due to the complexity and irregularity of tumor tissue that linear and classical nonlinear methods seem difficult to characterize completely. In order to show the performance of this method, we compared its results with those of the conventional method box-counting.

Keywords: irregularity, nonlinearity, MRI brain images, multifractal analysis, brain tumor

Procedia PDF Downloads 430
13848 Cadmium Separation from Aqueous Solutions by Natural Biosorbents

Authors: Z. V. P. Murthy, Preeti Arunachalam, Sangeeta Balram

Abstract:

Removal of metal ions from different wastewaters has become important due to their effects on living beings. Cadmium is one of the heavy metals found in different industrial wastewaters. There are many conventional methods available to remove heavy metals from wastewaters like adsorption, membrane separations, precipitation, electrolytic methods, etc. and all of them have their own advantages and disadvantages. The present work deals with the use of natural biosorbents (chitin and chitosan) to separate cadmium ions from aqueous solutions. The adsorption data were fitted with different isotherms and kinetics models. Amongst different adsorption isotherms used to fit the adsorption data, the Freundlich isotherm showed better fits for both the biosorbents. The kinetics data of adsorption of cadmium showed better fit with pseudo-second order model for both the biosorbents. Chitosan, the derivative from chitin, showed better performance than chitin. The separation results are encouraging.

Keywords: chitin, chitosan, cadmium, isotherm, kinetics

Procedia PDF Downloads 396
13847 Trade and Economic Relations between Georgia and Germany – the Impediments Caused by the Pandemic and Future Prospects

Authors: Tamar Lazariashvili

Abstract:

There are a number of factors that determine the growth and development of the country's economy; however, trade and economic relations with other countries are the most important of all these factors. The paper analyzes the trade and economic relations between Georgia and Germany, identifies the impediments caused by the Covid pandemic, and substantiates the need for further economic cooperation between the countries. Research objectives. The objective of the research is to develop recommendations and reveal the prospects of further cooperation between Georgia and Germany based on identifying the problems in the field of trade and economy in the post-crisis situation. The research object is Georgian German economic relations. Germany is Georgia's largest trading partner in the European Union. Georgia and Germany actively cooperate within the framework of international organizations as well. The paper analyzes the multilateral and intensive economic relations between Germany and Georgia; evaluates the investments of German companies in Georgia and the activities of Georgian companies in Germany. Research methods. The paper uses general and specific research methods; in particular, analysis, synthesis, induction, deduction, comparison, statistical (selection, grouping, observation, trend), and other research methods.SWOT analysis is used to determine development opportunities between countries. As a result of the research economic ranking of Georgia and Germany are determined according to the above criteria, the causes of the impediments due to the pandemic are studied; the main problems in the field of trade and economy are identified. The paper provides conclusions on the problems in the trade relations between Georgia and Germany and suggests recommendations regarding the prospects for improving these relations.

Keywords: georgia-germany, trade and economic relations, economic ranking, perspective directions

Procedia PDF Downloads 141