Search results for: Thermal Machine

Authors: Z. M. Najmi

Abstract:

Over the years, the question around Artificial Intelligence has always been one with many answers. Whether by means of use in business and industry or complicated algorithmic programming, management of these technologies has always been the core focus. More recently, technologies have been questioned in industry and society alike as to whether they have improved human-centred design, assisted choices and objectives, and had a hand in systematic processes across the board. With these questions the answer may lie within AI technologies, and the steps needed in removing common human error. Elements such as Machine Learning, Deep Learning, Recommender Systems and Natural Language Processing will all be features to consider moving forward. Our previous intervention with AI applications has resulted in increased productivity, however, raised concerns for the continuation of traditional human-centred occupations. Emerging technologies such as Augmented Reality and Virtual Reality have all played a part in this during AI’s prominent rise. As mentioned, AI has been constantly under the microscope; the benefits and drawbacks may seem endless is wide, but AI is something we must take notice of and adapt into our everyday lives. The aim of this paper is to give an overview of the technologies surrounding A.I. and its’ related technologies. A comprehensive review has been written as a timeline of the developing events and key points in the history of Artificial Intelligence. This research is gathered entirely from secondary research, academic statements of knowledge and gathered to produce an understanding of the timeline of AI.

Keywords: Artificial Intelligence, Deep Learning, Augmented Reality, Reinforcement Learning, Machine Learning, Supervised Learning.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 576

Authors: Kemal Polat

Abstract:

In this paper, an attribute weighting method called fuzzy C-means clustering based attribute weighting (FCMAW) for classification of Diabetes disease dataset has been used. The aims of this study are to reduce the variance within attributes of diabetes dataset and to improve the classification accuracy of classifier algorithm transforming from non-linear separable datasets to linearly separable datasets. Pima Indians Diabetes dataset has two classes including normal subjects (500 instances) and diabetes subjects (268 instances). Fuzzy C-means clustering is an improved version of K-means clustering method and is one of most used clustering methods in data mining and machine learning applications. In this study, as the first stage, fuzzy C-means clustering process has been used for finding the centers of attributes in Pima Indians diabetes dataset and then weighted the dataset according to the ratios of the means of attributes to centers of theirs. Secondly, after weighting process, the classifier algorithms including support vector machine (SVM) and k-NN (k- nearest neighbor) classifiers have been used for classifying weighted Pima Indians diabetes dataset. Experimental results show that the proposed attribute weighting method (FCMAW) has obtained very promising results in the classification of Pima Indians diabetes dataset.

Keywords: Fuzzy C-means clustering, Fuzzy C-means clustering based attribute weighting, Pima Indians diabetes dataset, SVM.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1763

Authors: Azadeh Golshan, Craig Evans, Phillip Geary, Abigail Morrow, Zoe Rogers, Marcel Maeder

Abstract:

22 physicochemical variables have been determined in water samples collected weekly from January to December in 2013 from three sampling stations located within a major drinking water reservoir. Classical Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) analysis was used to investigate the environmental factors associated with the physico-chemical variability of the water samples at each of the sampling stations. Matrix augmentation MCR-ALS (MA-MCR-ALS) was also applied, and the two sets of results were compared for interpretative clarity. Links between these factors, reservoir inflows and catchment land-uses were investigated and interpreted in relation to chemical composition of the water and their resolved geographical distribution profiles. The results suggested that the major factors affecting reservoir water quality were those associated with agricultural runoff, with evidence of influence on algal photosynthesis within the water column. Water quality variability within the reservoir was also found to be strongly linked to physical parameters such as water temperature and the occurrence of thermal stratification. The two methods applied (MCR-ALS and MA-MCR-ALS) led to similar conclusions; however, MA-MCR-ALS appeared to provide results more amenable to interpretation of temporal and geological variation than those obtained through classical MCR-ALS.

Keywords: Catchment management, drinking water reservoir, multivariate curve resolution alternating least squares, thermal stratification, water quality.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 921

Authors: Wafa' S.Al-Sharafat, Reyadh Naoum

Abstract:

Society has grown to rely on Internet services, and the number of Internet users increases every day. As more and more users become connected to the network, the window of opportunity for malicious users to do their damage becomes very great and lucrative. The objective of this paper is to incorporate different techniques into classier system to detect and classify intrusion from normal network packet. Among several techniques, Steady State Genetic-based Machine Leaning Algorithm (SSGBML) will be used to detect intrusions. Where Steady State Genetic Algorithm (SSGA), Simple Genetic Algorithm (SGA), Modified Genetic Algorithm and Zeroth Level Classifier system are investigated in this research. SSGA is used as a discovery mechanism instead of SGA. SGA replaces all old rules with new produced rule preventing old good rules from participating in the next rule generation. Zeroth Level Classifier System is used to play the role of detector by matching incoming environment message with classifiers to determine whether the current message is normal or intrusion and receiving feedback from environment. Finally, in order to attain the best results, Modified SSGA will enhance our discovery engine by using Fuzzy Logic to optimize crossover and mutation probability. The experiments and evaluations of the proposed method were performed with the KDD 99 intrusion detection dataset.

Keywords: MSSGBML, Network Intrusion Detection, SGA, SSGA.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1672

Authors: Areej Almalkawi, Sameer Hamadna, Parviz Soroushian, Nalin Darsana

Abstract:

The work on indigenous binders in this paper focused on the following indigenous raw materials: red clay, red lava and pumice (as primary aluminosilicate precursors), wood ash and gypsum (as supplementary minerals), and sodium sulfate and lime (as alkali activators). The experimental methods used for evaluation of these indigenous raw materials included laser granulometry, x-ray fluorescence (XRF) spectroscopy, and chemical reactivity. Formulations were devised for transforming these raw materials into alkali aluminosilicate-based hydraulic cements. These formulations were processed into hydraulic cements via simple heating and milling actions to render thermal activation, mechanochemical and size reduction effects. The resulting hydraulic cements were subjected to laser granulometry, heat of hydration and reactivity tests. These cements were also used to prepare mortar mixtures, which were evaluated via performance of compressive strength tests. The measured values of strength were correlated with the reactivity, size distribution and microstructural features of raw materials. Some of the indigenous hydraulic cements produced in this reporting period yielded viable levels of compressive strength. The correlation trends established in this work are being evaluated for development of simple and thorough methods of qualifying indigenous raw materials for use in production of indigenous hydraulic cements.

Keywords: One-part geopolymer cement, aluminosilicate precursors, thermal activation, mechanochemical.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 702

Authors: Vasudha Bansal, M. L. Singla, C. Ghanshyam

Abstract:

The effect of nonthermal pulsed electric field (PEF) and thermal treatment (90⁰C for 60s) was studied on quality parameters of emblica officinalis juice for the period of 6 weeks at 4⁰C using monopolar rectangular pulse of 1µs width. The PEF treatment was given using static chamber at 24kV/cm for 500µs. The quality of emblica officinalis juice was investigated in terms of non enzymatic browning index (NEBI), 5-hydroxymethyl-2-furfural (HMF), total polyphenol content and antioxidant capacity. ⁰Brix, pH and conductivity were evaluated as physical parameters. The aim of the work was to investigate the effect of PEF on the retention of bioactive compounds and retardation of browning activity. The results showed that conventional thermal treatment had led to a significant (p < 0.05) decrease of 48.15% in polyphenol content (129.56 mg of GAE L^-1), with higher NEBI and HMF formation (p < 0.05) whilst PEF suppressed NEBI and retained higher polyphenol compounds (168.59 mg GAE L^-1) with limiting the loss to 32.56% along maximum free radical scavenging activity (92.07%). However, pH, ⁰brix and electrical conductivity of treated juice samples remain unaffected. Therefore, PEF can be considered as an effective nonthermal treatment for retaining bioactive compounds along suppressing browning of emblica juice.

 

Keywords: Emblica officinalis juice, Free radical scavenging activity, Pulsed electric field, Total polyphenol content.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2731

Authors: J. P. Dubois, O. M. Abdul-Latif

Abstract:

Support Vector Machine (SVM) is a recent class of statistical classification and regression techniques playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM is applied to an infrared (IR) binary communication system with different types of channel models including Ricean multipath fading and partially developed scattering channel with additive white Gaussian noise (AWGN) at the receiver. The structure and performance of SVM in terms of the bit error rate (BER) metric is derived and simulated for these channel stochastic models and the computational complexity of the implementation, in terms of average computational time per bit, is also presented. The performance of SVM is then compared to classical binary signal maximum likelihood detection using a matched filter driven by On-Off keying (OOK) modulation. We found that the performance of SVM is superior to that of the traditional optimal detection schemes used in statistical communication, especially for very low signal-to-noise ratio (SNR) ranges. For large SNR, the performance of the SVM is similar to that of the classical detectors. The implication of these results is that SVM can prove very beneficial to IR communication systems that notoriously suffer from low SNR at the cost of increased computational complexity.

Keywords: Least square-support vector machine, on-off keying, matched filter, maximum likelihood detector, wireless infrared communication.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1953

Authors: Bassim Bachy, Joerg Franke

Abstract:

In this study, a three dimensional numerical heat transfer model has been used to simulate the laser structuring of polymer substrate material in the Three-Dimensional Molded Interconnect Device (3D MID) which is used in the advanced multifunctional applications. A finite element method (FEM) transient thermal analysis is performed using APDL (ANSYS Parametric Design Language) provided by ANSYS. In this model, the effect of surface heat source was modeled with Gaussian distribution, also the effect of the mixed boundary conditions which consist of convection and radiation heat transfers have been considered in this analysis. The model provides a full description of the temperature distribution, as well as calculates the depth and the width of the groove upon material removal at different set of laser parameters such as laser power and laser speed. This study also includes the experimental procedure to study the effect of laser parameters on the depth and width of the removal groove metal as verification to the modeled results. Good agreement between the experimental and the model results is achieved for a wide range of laser powers. It is found that the quality of the laser structure process is affected by the laser scan speed and laser power. For a high laser structured quality, it is suggested to use laser with high speed and moderate to high laser power.

Keywords: Laser Structuring, Simulation, Finite element analysis, Thermal modeling.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4345

Authors: Arun Goel

Abstract:

The present paper attempts to investigate the prediction of air entrainment rate and aeration efficiency of a free overfall jets issuing from a triangular sharp crested weir by using regression based modelling. The empirical equations, Support vector machine (polynomial and radial basis function) models and the linear regression techniques were applied on the triangular sharp crested weirs relating the air entrainment rate and the aeration efficiency to the input parameters namely drop height, discharge, and vertex angle. It was observed that there exists a good agreement between the measured values and the values obtained using empirical equations, Support vector machine (Polynomial and rbf) models and the linear regression techniques. The test results demonstrated that the SVM based (Poly & rbf) model also provided acceptable prediction of the measured values with reasonable accuracy along with empirical equations and linear regression techniques in modelling the air entrainment rate and the aeration efficiency of a free overfall jets issuing from triangular sharp crested weir. Further sensitivity analysis has also been performed to study the impact of input parameter on the output in terms of air entrainment rate and aeration efficiency.

Keywords: Air entrainment rate, dissolved oxygen, regression, SVM, weir.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1956

Authors: Maíra O. Palm, Cintia Marangoni, Ozair Souza, Noeli Sellin

Abstract:

Wastes from a vegetal extracts industry (cocoa, oak, Guarana and mate) were characterized by particle size, proximate and ultimate analysis, lignocellulosic fractions, high heating value, thermal analysis (Thermogravimetric analysis – TGA, and Differential thermal analysis - DTA) and energy density to evaluate their potential as biomass in the form of briquettes for power generation. All wastes presented adequate particle sizes to briquettes production. The wastes showed high moisture content, requiring previous drying for use as briquettes. Cocoa and oak wastes had the highest volatile matter contents with maximum mass loss at 310 ºC and 450 ºC, respectively. The solvents used in the aroma extraction process influenced in the moisture content of the wastes, which was higher for mate due to water has been used as solvent. All wastes showed an insignificant loss mass after 565 °C, hence resulting in low ash content. High carbon and hydrogen contents and low sulfur and nitrogen contents were observed ensuring a low generation of sulfur and nitrous oxides. Mate and cocoa exhibited the highest carbon and lignin content, and high heating value. The dried wastes had high heating value, from 17.1 MJ/kg to 20.8 MJ/kg. The results indicate the energy potential of wastes for use as fuel in power generation.

Keywords: Agro-industrial waste, biomass, briquettes, combustion.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1038

Authors: Sharifah Mousli, Sona Taheri, Jiayuan He

Abstract:

Autism spectrum disorder (ASD) is a complex developmental condition involving persistent difficulties with social communication, restricted interests, and repetitive behavior. The challenges associated with ASD can interfere with an affected individual’s ability to function in social, academic, and employment settings. Although there is no effective medication known to treat ASD, to our best knowledge, early intervention can significantly improve an affected individual’s overall development. Hence, an accurate diagnosis of ASD at an early phase is essential. The use of machine learning approaches improves and speeds up the diagnosis of ASD. In this paper, we focus on the application of unsupervised clustering methods in ASD, as a large volume of ASD data generated through hospitals, therapy centers, and mobile applications has no pre-existing labels. We conduct a comparative analysis using seven clustering approaches, such as K-means, agglomerative hierarchical, model-based, fuzzy-C-means, affinity propagation, self organizing maps, linear vector quantisation – as well as the recently developed optimization-based clustering (COMSEP-Clust) approach. We evaluate the performances of the clustering methods extensively on real-world ASD datasets encompassing different age groups: toddlers, children, adolescents, and adults. Our experimental results suggest that the COMSEP-Clust approach outperforms the other seven methods in recognizing ASD with well-separated clusters.

Keywords: Autism spectrum disorder, clustering, optimization, unsupervised machine learning.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 417

Authors: Kubra Sayin, Derya Arslan

Abstract:

Red pepper (Capsicum annum L.) has long been recognized as a good source of antioxidants, being rich in ascorbic acid and other phytochemicals. In Turkish cuisine red pepper is sometimes consumed raw in salads and baked as a garnish, but its most wide consumption type is red pepper paste. The processing of red pepper into pepper paste includes various thermal treatment steps such as heating and pasteurizing. There are reports demonstrating an enhancement or reduction in antioxidant activity of vegetables after thermal treatment. So this study was conducted to investigate the total phenolic, ascorbic acid and total carotenoids as well as free radical scavenging activity of raw red pepper and various red pepper pastes obtainable on the market. The samples were analyzed for radical-scavenging activity (RSA) and total polyphenol (TP) content using 1,1-diphenyl-2-picrylhydrazyl (DPPH) and Folin-Ciocalteu methods, respectively. Total carotenoids and ascorbic acid contents were determined spectrophotometrically. Results suggest that hot pepper paste contained significantly (P<0.05) higher concentrations of TP than sweet pepper paste. However there is no significant (P>0.05) difference in RSA, ascorbic acid and total carotenoids content between sweet and hot red pepper paste products. It is concluded that the red pepper paste, that has a wide range of consumption in Turkish cuisine, presents a good dose of phenolic compounds and antioxidant capacity and it should be regarded as a functional food.

Keywords: Antioxidant properties, Red pepper paste, Total carotenoids, Total phenolic content.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2503

Authors: Sayed Ahmed E. Sayed Ahmed, Emad Z. Ibrahiem, Osama M. Mesalhy, Mohamed A. Abdelatief

Abstract:

An experimental and numerical study has been conducted to clarify heat transfer characteristics and effectiveness of a cross-flow heat exchanger employing staggered wing-shaped tubes at different angels of attack. The water-side Rew and the air-side Rea were at 5 x 102 and at from 1.8 x 103 to 9.7 x 103, respectively. The tubes arrangements were employed with various angles of attack θ1,2,3 from 0° to 330° at the considered Rea range. Correlation of Nu, St, as well as the heat transfer per unit pumping power (ε) in terms of Rea, design parameters for the studied bundle were presented. The temperature fields around the staggered wing-shaped tubes bundle were predicted by using commercial CFD FLUENT 6.3.26 software package. Results indicated that the heat transfer was increased by increasing the angle of attack from 0° to 45°, while the opposite was true for angles of attack from 135° to 180°. The best thermal performance and hence η of studied bundle was occurred at the lowest Rea and/or zero angle of attack. Comparisons between the experimental and numerical results of the present study and those, previously, obtained for similar available studies showed good agreements.

Keywords: Wing-shaped tubes, Cross-flow cooling, Staggered arrangement, and CFD.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2084

Authors: Nuawi M. Z., Lamin F., Ismail A. R., Abdullah S., Wahid Z.

Abstract:

A filter is used to remove undesirable frequency information from a dynamic signal. This paper shows that the Znotch filter filtering technique can be applied to remove the noise nuisance from a machining signal. In machining, the noise components were identified from the sound produced by the operation of machine components itself such as hydraulic system, motor, machine environment and etc. By correlating the noise components with the measured machining signal, the interested components of the measured machining signal which was less interfered by the noise, can be extracted. Thus, the filtered signal is more reliable to be analysed in terms of noise content compared to the unfiltered signal. Significantly, the I-kaz method i.e. comprises of three dimensional graphical representation and I-kaz coefficient, Z∞ could differentiate between the filtered and the unfiltered signal. The bigger space of scattering and the higher value of Z∞ demonstrated that the signal was highly interrupted by noise. This method can be utilised as a proactive tool in evaluating the noise content in a signal. The evaluation of noise content is very important as well as the elimination especially for machining operation fault diagnosis purpose. The Z-notch filtering technique was reliable in extracting noise component from the measured machining signal with high efficiency. Even though the measured signal was exposed to high noise disruption, the signal generated from the interaction between cutting tool and work piece still can be acquired. Therefore, the interruption of noise that could change the original signal feature and consequently can deteriorate the useful sensory information can be eliminated.

Keywords: Digital signal filtering, I-kaz method, Machiningmonitoring, Noise Cancelling, Sound

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1884

Authors: J. P. Dubois, Omar M. Abdul-Latif

Abstract:

Support Vector Machine (SVM) is a statistical learning tool developed to a more complex concept of structural risk minimization (SRM). In this paper, SVM is applied to signal detection in communication systems in the presence of channel noise in various environments in the form of Rayleigh fading, additive white Gaussian background noise (AWGN), and interference noise generalized as additive color Gaussian noise (ACGN). The structure and performance of SVM in terms of the bit error rate (BER) metric is derived and simulated for these advanced stochastic noise models and the computational complexity of the implementation, in terms of average computational time per bit, is also presented. The performance of SVM is then compared to conventional binary signaling optimal model-based detector driven by binary phase shift keying (BPSK) modulation. We show that the SVM performance is superior to that of conventional matched filter-, innovation filter-, and Wiener filter-driven detectors, even in the presence of random Doppler carrier deviation, especially for low SNR (signal-to-noise ratio) ranges. For large SNR, the performance of the SVM was similar to that of the classical detectors. However, the convergence between SVM and maximum likelihood detection occurred at a higher SNR as the noise environment became more hostile.

Keywords: Colour noise, Doppler shift, innovation filter, least square-support vector machine, matched filter, Rayleigh fading, Wiener filter.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1813

Authors: Teuku Rihayat, Suryani

Abstract:

Polyurethanes (PURs) are very versatile polymeric materials with a wide range of physical and chemical properties. PURs have desirable properties such as high abrasion resistance, tear strength, shock absorption, flexibility and elasticity. Although they have relatively poor thermal stability, this can be improved by using treated clay. Polyurethane/clay nanocomposites have been synthesized from renewable sources. A polyol for the production of polyurethane by reaction with an isocyanate was obtained by the synthesis of palm oil-based oleic acid with glycerol. Dodecylbenzene sulfonic acid (DBSA) was used as catalyst and emulsifier. The unmodified clay (kunipia-F) was treated with cetyltrimethyl ammonium bromide (CTAB-mont) and octadodecylamine (ODAmont). The d-spacing in CTAB-mont and ODA-mont were 1.571 nm and 1.798 nm respectively and larger than that of the pure-mont (1.142 nm). The organoclay was completely intercalated in the polyurethane, as confirmed by a wide angle x-ray diffraction (WAXD) pattern. The results showed that adding clay demonstrated better thermal stability in comparison with the virgin polyurethane. Onset degradation of pure PU is at 200oC, and is lower than that of the CTAB-mont PU and ODA-mont PU which takes place at about 318oC and 330oC, respectively. The mechanical properties (including the dynamic mechanical properties) of pure polyurethane (PU) and PU/clay nanocomposites, were measured. The modified organoclay had a remarkably beneficial effect on the strength and elongation at break of the nanocomposites, which both increased with increasing clay content with the increase of the tensile strength of more than 214% and 267% by the addition of only 5 wt% of the montmorillonite CTAB-mont PU and ODA-mont PU, respectively.

Keywords: Polyurethane, Clay nanocomposites, Biobase

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2602

Authors: Michael G. Pantelyat

Abstract:

Fundamental basics of pure and applied research in the area of magneto-thermo-mechanical numerical analysis and design of innovative electromagnetic devices (modern induction heaters, novel thermoelastic actuators, rotating electrical machines, induction cookers, electrophysical devices) are elaborated. Thus, mathematical models of magneto-thermo-mechanical processes in electromagnetic devices taking into account main interactions of interrelated phenomena are developed. In addition, graphical representation of coupled (multiphysics) phenomena under consideration is proposed. Besides, numerical techniques for nonlinear problems solution are developed. On this base, effective numerical algorithms for solution of actual problems of practical interest are proposed, validated and implemented in applied 2D and 3D computer codes developed. Many applied problems of practical interest regarding modern electrical engineering devices are numerically solved. Investigations of the influences of various interrelated physical phenomena (temperature dependences of material properties, thermal radiation, conditions of convective heat transfer, contact phenomena, etc.) on the accuracy of the electromagnetic, thermal and structural analyses are conducted. Important practical recommendations on the choice of rational structures, materials and operation modes of electromagnetic devices under consideration are proposed and implemented in industry.

Keywords: Electromagnetic devices, multiphysics, numerical analysis, simulation and design.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1721

Authors: N. Türkmenoğlu Bayraktar, E. Kishalı

Abstract:

Campus buildings are educational facilities where various amount of energy consumption for lighting, heating, cooling and ventilation occurs. Some of the new universities in Turkey, where this investigation takes place, still continue their educational activities in existing buildings primarily designed for different architectural programs and converted to campus buildings via changes of function, space organizations and structural interventions but most of the time without consideration of appropriate micro climatic conditions. Reducing energy consumption in these structures not only contributes to the national economy but also mitigates the negative effects on environment. Furthermore, optimum thermal comfort conditions should be provided during the refurbishment of existing campus structures and their building envelope. Considering this issue, the first step is to investigate the climatic performance of building elements regarding refurbishment process. In the context of the study Kocaeli University, Faculty of Design and Architecture building constructed in 1980s in Anıtpark campus located in the central part of Kocaeli, Turkey was investigated. Climatic factors influencing thermal conditions; the deteriorations on building envelope; temperature distribution; heat losses from façade elements observed by thermography were presented in order to improve strategies for retrofit process for the building envelope. Within the scope of the survey, refurbishment strategies towards providing optimum climatic comfort conditions, increasing energy efficiency of building envelope were proposed.

Keywords: Building envelope, IRT, refurbishment, non-destructive test.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 887

Authors: Viacheslav Shkuratskyy, Aminu Bello Usman, Michael O’Dea, Mujeeb Ur Rehman, Saifur Rahman Sabuj

Abstract:

This paper examines relationships between solar activity and earthquakes, it applied machine learning techniques: K-nearest neighbour, support vector regression, random forest regression, and long short-term memory network. Data from the SILSO World Data Center, the NOAA National Center, the GOES satellite, NASA OMNIWeb, and the United States Geological Survey were used for the experiment. The 23rd and 24th solar cycles, daily sunspot number, solar wind velocity, proton density, and proton temperature were all included in the dataset. The study also examined sunspots, solar wind, and solar flares, which all reflect solar activity, and earthquake frequency distribution by magnitude and depth. The findings showed that the long short-term memory network model predicts earthquakes more correctly than the other models applied in the study, and solar activity is more likely to effect earthquakes of lower magnitude and shallow depth than earthquakes of magnitude 5.5 or larger with intermediate depth and deep depth

.

Keywords: K-Nearest Neighbour, Support Vector Regression, Random Forest Regression, Long Short-Term Memory Network, earthquakes, solar activity, sunspot number, solar wind, solar flares.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 202

Authors: Larry Powell, Seth Polsley, Drew Casey, Tracy Hammond

Abstract:

Human activity recognition (HAR) systems have shown positive performance when recognizing repetitive activities like walking, running, and sleeping. Water-based activities are a reasonably new area for activity recognition. However, water-based activity recognition has largely focused on supporting the elite and competitive swimming population, which already has amazing coordination and proper form. Beginner swimmers are not perfect, and activity recognition needs to support the individual motions to help beginners. Activity recognition algorithms are traditionally built around short segments of timed sensor data. Using a time window input can cause performance issues in the machine learning model. The window’s size can be too small or large, requiring careful tuning and precise data segmentation. In this work, we present a method that uses a time window as the initial segmentation, then separates the data based on the change in the sensor value. Our system uses a multi-phase segmentation method that pulls all peaks and valleys for each axis of an accelerometer placed on the swimmer’s lower back. This results in high recognition performance using leave-one-subject-out validation on our study with 20 beginner swimmers, with our model optimized from our final dataset resulting in an F-Score of 0.95.

Keywords: Time window, peak/valley segmentation, feature extraction, beginner swimming, activity recognition.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 205

Authors: Deeman Yousif Mahmood, Mohammed Abdullah Hussein

Abstract:

The goal of a network-based intrusion detection system is to classify activities of network traffics into two major categories: normal and attack (intrusive) activities. Nowadays, data mining and machine learning plays an important role in many sciences; including intrusion detection system (IDS) using both supervised and unsupervised techniques. However, one of the essential steps of data mining is feature selection that helps in improving the efficiency, performance and prediction rate of proposed approach. This paper applies unsupervised K-means clustering algorithm with information gain (IG) for feature selection and reduction to build a network intrusion detection system. For our experimental analysis, we have used the new NSL-KDD dataset, which is a modified dataset for KDDCup 1999 intrusion detection benchmark dataset. With a split of 60.0% for the training set and the remainder for the testing set, a 2 class classifications have been implemented (Normal, Attack). Weka framework which is a java based open source software consists of a collection of machine learning algorithms for data mining tasks has been used in the testing process. The experimental results show that the proposed approach is very accurate with low false positive rate and high true positive rate and it takes less learning time in comparison with using the full features of the dataset with the same algorithm.

Keywords: Information Gain (IG), Intrusion Detection System (IDS), K-means Clustering, Weka.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2776

Authors: Xiaoqing Wang, Junfeng Wang, Xiaolan Zhu

Abstract:

Android operating system has been recognized by most application developers because of its good open-source and compatibility, which enriches the categories of applications greatly. However, it has become the target of malware attackers due to the lack of strict security supervision mechanisms, which leads to the rapid growth of malware, thus bringing serious safety hazards to users. Therefore, it is critical to detect Android malware effectively. Generally, the permissions declared in the AndroidManifest.xml can reflect the function and behavior of the application to a large extent. Since current Android system has not any restrictions to the number of permissions that an application can request, developers tend to apply more than actually needed permissions in order to ensure the successful running of the application, which results in the abuse of permissions. However, some traditional detection methods only consider the requested permissions and ignore whether it is actually used, which leads to incorrect identification of some malwares. Therefore, a machine learning detection method based on the actually used permissions combination and API calls was put forward in this paper. Meanwhile, several experiments are conducted to evaluate our methodology. The result shows that it can detect unknown malware effectively with higher true positive rate and accuracy while maintaining a low false positive rate. Consequently, the AdaboostM1 (J48) classification algorithm based on information gain feature selection algorithm has the best detection result, which can achieve an accuracy of 99.8%, a true positive rate of 99.6% and a lowest false positive rate of 0.

Keywords: Android, permissions combination, API calls, machine learning.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1915

Authors: Brandon Foggo, Nanpeng Yu

Abstract:

Power distribution circuits undergo frequent network topology changes that are often left undocumented. As a result, the documentation of a circuit’s connectivity becomes inaccurate with time. The lack of reliable circuit connectivity information is one of the biggest obstacles to model, monitor, and control modern distribution systems. To enhance the reliability and efficiency of electric power distribution systems, the circuit’s connectivity information must be updated periodically. This paper focuses on one critical component of a distribution circuit’s topology - the secondary transformer to phase association. This topology component describes the set of phase lines that feed power to a given secondary transformer (and therefore a given group of power consumers). Finding the documentation of this component is call Phase Identification, and is typically performed with physical measurements. These measurements can take time lengths on the order of several months, but with supervised learning, the time length can be reduced significantly. This paper compares several such methods applied to Phase Identification for a large range of real distribution circuits, describes a method of training data selection, describes preprocessing steps unique to the Phase Identification problem, and ultimately describes a method which obtains high accuracy (> 96% in most cases, > 92% in the worst case) using only 5% of the measurements typically used for Phase Identification.

Keywords: Distribution network, machine learning, network topology, phase identification, smart grid.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1074

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

Abstract:

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

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

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2053

Authors: Avinash Chandra, R. P. Chhabra

Abstract:

Natural convection heat transfer from a heated horizontal semi-circular cylinder (flat surface upward) has been investigated for the following ranges of conditions; Grashof number, and Prandtl number. The governing partial differential equations (continuity, Navier-Stokes and energy equations) have been solved numerically using a finite volume formulation. In addition, the role of the type of the thermal boundary condition imposed at cylinder surface, namely, constant wall temperature (CWT) and constant heat flux (CHF) are explored. Natural convection heat transfer from a heated horizontal semi-circular cylinder (flat surface upward) has been investigated for the following ranges of conditions; Grashof number, and Prandtl number, . The governing partial differential equations (continuity, Navier-Stokes and energy equations) have been solved numerically using a finite volume formulation. In addition, the role of the type of the thermal boundary condition imposed at cylinder surface, namely, constant wall temperature (CWT) and constant heat flux (CHF) are explored. The resulting flow and temperature fields are visualized in terms of the streamline and isotherm patterns in the proximity of the cylinder. The flow remains attached to the cylinder surface over the range of conditions spanned here except that for and ; at these conditions, a separated flow region is observed when the condition of the constant wall temperature is prescribed on the surface of the cylinder. The heat transfer characteristics are analyzed in terms of the local and average Nusselt numbers. The maximum value of the local Nusselt number always occurs at the corner points whereas it is found to be minimum at the rear stagnation point on the flat surface. Overall, the average Nusselt number increases with Grashof number and/ or Prandtl number in accordance with the scaling considerations. The numerical results are used to develop simple correlations as functions of Grashof and Prandtl number thereby enabling the interpolation of the present numerical results for the intermediate values of the Prandtl or Grashof numbers for both thermal boundary conditions.

Keywords: Constant heat flux, Constant surface temperature, Grashof number, natural convection, Prandtl number, Semi-circular cylinder

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3415

Authors: Abdulbasit G. A. Abdulsayid

Abstract:

The main focus of the work was concerned with hydrodynamic and thermal analysis of the plate heat exchanger channel with corrugation patterns suggested to be triangular, sinusoidal, and square corrugation. This study was to numerically model and validate the triangular corrugated channel with dimensions/parameters taken from open literature, and then model/analyze both sinusoidal, and square corrugated channel referred to the triangular model. Initially, 2D modeling with local extensive analysis for triangular corrugated channel was carried out. By that, all local pressure drop, wall shear stress, friction factor, static temperature, heat flux, Nusselt number, and surface heat coefficient, were analyzed to interpret the hydrodynamic and thermal phenomena occurred in the flow. Furthermore, in order to facilitate confidence in this model, a comparison between the values predicted, and experimental results taken from literature for almost the same case, was done. Moreover, a holistic numerical study for sinusoidal and square channels together with global comparisons with triangular corrugation under the same condition, were handled. Later, a comparison between electric, and fluid cooling through varying the boundary condition was achieved. The constant wall temperature and constant wall heat flux boundary conditions were employed, and the different resulted Nusselt numbers as a consequence were justified. The results obtained can be used to come up with an optimal design, a 'compromise' between heat transfer and pressure drop.

Keywords: Corrugated Channel, CFD, Heat Exchanger, Heat Enhancement.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3176

Authors: M. V. G. Silva, J. Gazzola, I. M. Dal Fabbro, A. C. L. Lino

Abstract:

Computer aided design accounts with the support of parametric software in the design of machine components as well as of any other pieces of interest. The complexities of the element under study sometimes offer certain difficulties to computer design, or ever might generate mistakes in the final body conception. Reverse engineering techniques are based on the transformation of already conceived body images into a matrix of points which can be visualized by the design software. The literature exhibits several techniques to obtain machine components dimensional fields, as contact instrument (MMC), calipers and optical methods as laser scanner, holograms as well as moiré methods. The objective of this research work was to analyze the moiré technique as instrument of reverse engineering, applied to bodies of nom complex geometry as simple solid figures, creating matrices of points. These matrices were forwarded to a parametric software named SolidWorks to generate the virtual object. Volume data obtained by mechanical means, i.e., by caliper, the volume obtained through the moiré method and the volume generated by the SolidWorks software were compared and found to be in close agreement. This research work suggests the application of phase shifting moiré methods as instrument of reverse engineering, serving also to support farm machinery element designs.

Keywords: Reverse engineering, Moiré technique, three dimensional image generation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3457

Authors: H. K. G. K. D. K. Hapuhinna, R. D. Gunaratne, H. M. J. C. Pitawala

Abstract:

Hydroxyapatite is a bioceramic which can be used for applications in orthopedics and dentistry due to its structural similarity with the mineral phase of mammalian bones and teeth. In this study, it was synthesized, chemically changing natural Eppawala chloroapatite mineral as a value-added product. Sol-gel approach and solid state sintering were used to synthesize products using diluted nitric acid, ethanol and calcium hydroxide under different conditions. Synthesized Eppawala hydroxyapatite powder was characterized using X-ray Fluorescence (XRF), X-ray Powder Diffraction (XRD), Fourier-transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), Thermogravimetric Analysis (TGA) and Differential Scanning Calorimetry (DSC) in order to find out its composition, crystallinity, presence of functional groups, bonding type, surface morphology, microstructural features, and thermal dependence and stability, respectively. The XRD results reflected the formation of a hexagonal crystal structure of hydroxyapatite. Elementary composition and microstructural features of products were discussed based on the XRF and SEM results of the synthesized hydroxyapatite powder. TGA and DSC results of synthesized products showed high thermal stability and good material stability in nature. Also, FTIR spectroscopy results confirmed the formation of hydroxyapatite from apatite via the presence of hydroxyl groups. Those results coincided with the FTIR results of mammalian bones including human bones. The study concludes that there is a possibility of producing hydroxyapatite using commercially available Eppawala chloroapatite in Sri Lanka.

Keywords: Dentistry, eppawala chloroapatite, hydroxyapatite, orthopedics.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 817

Authors: Mohammad Hasan Raouf, Ahmad Rouhani, Mohammad Abedini, Ebrahim Rasooli Anarmarzi

Abstract:

In this paper the application of a hierarchical fuzzy system (HFS) based on MPSS and SVC in multi-machine environment is studied. Also the effect of communication lines active power variance signal between two ΔP_Tie-line regions, as one of the inputs of hierarchical fuzzy multi-input PSS and SVC (HFMPSS & SVC), on the increase of low frequency oscillation damping is examined. In the MPSS, to have better efficiency an auxiliary signal of reactive power deviation (ΔQ) is added with ΔP+ Δω input type PSS. The number of rules grows exponentially with the number of variables in a classic fuzzy system. To reduce the number of rules the HFS consists of a number of low-dimensional fuzzy systems in a hierarchical structure. Phasor model of SVC is described and used in this paper. The performances of MPSS and ΔP_Tie-line based HFMPSS and also the proposed method in damping inter-area mode of oscillation are examined in response to disturbances. The efficiency of the proposed model is examined by simulating a four-machine power system. Results show that the proposed method is performing satisfactorily within the whole range of disturbances and reduces the cost of system.

Keywords: Communication lines active power variance signal, Hierarchical fuzzy system (HFS), Multi-input power system stabilizer (MPSS), Static VAR compensator (SVC).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1670

Authors: Sachin Kumar, Vivek Tiwari, Goutam Dutta

Abstract:

The paper investigates parallel channel instabilities of natural circulation boiling water reactor. A thermal-hydraulic model is developed to simulate two-phase flow behavior in the natural circulation boiling water reactor (NCBWR) with the incorporation of ex-core components and recirculation loop such as steam separator, down-comer, lower-horizontal section and upper-horizontal section and then, numerical analysis is carried out for parallel channel instabilities of the reactor undergoing both in-phase and out-of-phase modes of oscillations. To analyze the relative effect on stability of the reactor due to inclusion of various ex-core components and recirculation loop, marginal stable point is obtained at a particular inlet enthalpy of the reactor core without the inclusion of ex-core components and recirculation loop and then with the inclusion of the same. Numerical simulations are also conducted to determine the relative dominance between two modes of oscillations i.e. in-phase and out-of-phase. Simulations are also carried out when the channels are subjected to asymmetric power distribution keeping the inlet enthalpy same.

Keywords: Asymmetric power distribution, Density wave oscillations, In-phase and out-of-phase modes of instabilities, Natural circulation boiling water reactor

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2260