Search results for: RLS identification algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6295

Search results for: RLS identification algorithm

2455 Instant Fire Risk Assessment Using Artifical Neural Networks

Authors: Tolga Barisik, Ali Fuat Guneri, K. Dastan

Abstract:

Major industrial facilities have a high potential for fire risk. In particular, the indices used for the detection of hidden fire are used very effectively in order to prevent the fire from becoming dangerous in the initial stage. These indices provide the opportunity to prevent or intervene early by determining the stage of the fire, the potential for hazard, and the type of the combustion agent with the percentage values of the ambient air components. In this system, artificial neural network will be modeled with the input data determined using the Levenberg-Marquardt algorithm, which is a multi-layer sensor (CAA) (teacher-learning) type, before modeling the modeling methods in the literature. The actual values produced by the indices will be compared with the outputs produced by the network. Using the neural network and the curves to be created from the resulting values, the feasibility of performance determination will be investigated.

Keywords: artifical neural networks, fire, Graham Index, levenberg-marquardt algoritm, oxygen decrease percentage index, risk assessment, Trickett Index

Procedia PDF Downloads 133
2454 Video Foreground Detection Based on Adaptive Mixture Gaussian Model for Video Surveillance Systems

Authors: M. A. Alavianmehr, A. Tashk, A. Sodagaran

Abstract:

Modeling background and moving objects are significant techniques for video surveillance and other video processing applications. This paper presents a foreground detection algorithm that is robust against illumination changes and noise based on adaptive mixture Gaussian model (GMM), and provides a novel and practical choice for intelligent video surveillance systems using static cameras. In the previous methods, the image of still objects (background image) is not significant. On the contrary, this method is based on forming a meticulous background image and exploiting it for separating moving objects from their background. The background image is specified either manually, by taking an image without vehicles, or is detected in real-time by forming a mathematical or exponential average of successive images. The proposed scheme can offer low image degradation. The simulation results demonstrate high degree of performance for the proposed method.

Keywords: image processing, background models, video surveillance, foreground detection, Gaussian mixture model

Procedia PDF Downloads 513
2453 Numerical Analysis on Triceratops Restraining System: Failure Conditions of Tethers

Authors: Srinivasan Chandrasekaran, Manda Hari Venkata Ramachandra Rao

Abstract:

Increase in the oil and gas exploration in ultra deep-water demands an adaptive structural form of the platform. Triceratops has superior motion characteristics compared to that of the Tension Leg Platform and Single Point Anchor Reservoir platforms, which is well established in the literature. Buoyant legs that support the deck are position-restrained to the sea bed using tethers with high axial pretension. Environmental forces that act on the platform induce dynamic tension variations in the tethers, causing the failure of tethers. The present study investigates the dynamic response behavior of the restraining system of the platform under the failure of a single tether of each buoyant leg in high sea states. Using the rain-flow counting algorithm and the Goodman diagram, fatigue damage caused to the tethers is estimated, and the fatigue life is predicted. Results shows that under failure conditions, the fatigue life of the remaining tethers is quite alarmingly low.

Keywords: fatigue life, pm spectrum, rain flow counting, triceratops, failure analysis

Procedia PDF Downloads 129
2452 A Robust Optimization Model for the Single-Depot Capacitated Location-Routing Problem

Authors: Abdolsalam Ghaderi

Abstract:

In this paper, the single-depot capacitated location-routing problem under uncertainty is presented. The problem aims to find the optimal location of a single depot and the routing of vehicles to serve the customers when the parameters may change under different circumstances. This problem has many applications, especially in the area of supply chain management and distribution systems. To get closer to real-world situations, travel time of vehicles, the fixed cost of vehicles usage and customers’ demand are considered as a source of uncertainty. A combined approach including robust optimization and stochastic programming was presented to deal with the uncertainty in the problem at hand. For this purpose, a mixed integer programming model is developed and a heuristic algorithm based on Variable Neighborhood Search(VNS) is presented to solve the model. Finally, the computational results are presented and future research directions are discussed.

Keywords: location-routing problem, robust optimization, stochastic programming, variable neighborhood search

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2451 Resilience-Based Emergency Bridge Inspection Routing and Repair Scheduling under Uncertainty

Authors: Zhenyu Zhang, Hsi-Hsien Wei

Abstract:

Highway network systems play a vital role in disaster response for disaster-damaged areas. Damaged bridges in such network systems can impede disaster response by disrupting transportation of rescue teams or humanitarian supplies. Therefore, emergency inspection and repair of bridges to quickly collect damage information of bridges and recover the functionality of highway networks is of paramount importance to disaster response. A widely used measure of a network’s capability to recover from disasters is resilience. To enhance highway network resilience, plenty of studies have developed various repair scheduling methods for the prioritization of bridge-repair tasks. These methods assume that repair activities are performed after the damage to a highway network is fully understood via inspection, although inspecting all bridges in a regional highway network may take days, leading to the significant delay in repairing bridges. In reality, emergency repair activities can be commenced as soon as the damage data of some bridges that are crucial to emergency response are obtained. Given that emergency bridge inspection and repair (EBIR) activities are executed simultaneously in the response phase, the real-time interactions between these activities can occur – the blockage of highways due to repair activities can affect inspection routes which in turn have an impact on emergency repair scheduling by providing real-time information on bridge damages. However, the impact of such interactions on the optimal emergency inspection routes (EIR) and emergency repair schedules (ERS) has not been discussed in prior studies. To overcome the aforementioned deficiencies, this study develops a routing and scheduling model for EBIR while accounting for real-time inspection-repair interactions to maximize highway network resilience. A stochastic, time-dependent integer program is proposed for the complex and real-time interacting EBIR problem given multiple inspection and repair teams at locations as set post-disaster. A hybrid genetic algorithm that integrates a heuristic approach into a traditional genetic algorithm to accelerate the evolution process is developed. Computational tests are performed using data from the 2008 Wenchuan earthquake, based on a regional highway network in Sichuan, China, consisting of 168 highway bridges on 36 highways connecting 25 cities/towns. The results show that the simultaneous implementation of bridge inspection and repair activities can significantly improve the highway network resilience. Moreover, the deployment of inspection and repair teams should match each other, and the network resilience will not be improved once the unilateral increase in inspection teams or repair teams exceeds a certain level. This study contributes to both knowledge and practice. First, the developed mathematical model makes it possible for capturing the impact of real-time inspection-repair interactions on inspection routing and repair scheduling and efficiently deriving optimal EIR and ERS on a large and complex highway network. Moreover, this study contributes to the organizational dimension of highway network resilience by providing optimal strategies for highway bridge management. With the decision support tool, disaster managers are able to identify the most critical bridges for disaster management and make decisions on proper inspection and repair strategies to improve highway network resilience.

Keywords: disaster management, emergency bridge inspection and repair, highway network, resilience, uncertainty

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2450 Detecting and Secluding Route Modifiers by Neural Network Approach in Wireless Sensor Networks

Authors: C. N. Vanitha, M. Usha

Abstract:

In a real world scenario, the viability of the sensor networks has been proved by standardizing the technologies. Wireless sensor networks are vulnerable to both electronic and physical security breaches because of their deployment in remote, distributed, and inaccessible locations. The compromised sensor nodes send malicious data to the base station, and thus, the total network effectiveness will possibly be compromised. To detect and seclude the Route modifiers, a neural network based Pattern Learning predictor (PLP) is presented. This algorithm senses data at any node on present and previous patterns obtained from the en-route nodes. The eminence of any node is upgraded by their predicted and reported patterns. This paper propounds a solution not only to detect the route modifiers, but also to seclude the malevolent nodes from the network. The simulation result proves the effective performance of the network by the presented methodology in terms of energy level, routing and various network conditions.

Keywords: neural networks, pattern learning, security, wireless sensor networks

Procedia PDF Downloads 403
2449 Mechanical Characterization of Porcine Skin with the Finite Element Method Based Inverse Optimization Approach

Authors: Djamel Remache, Serge Dos Santos, Michael Cliez, Michel Gratton, Patrick Chabrand, Jean-Marie Rossi, Jean-Louis Milan

Abstract:

Skin tissue is an inhomogeneous and anisotropic material. Uniaxial tensile testing is one of the primary testing techniques for the mechanical characterization of skin at large scales. In order to predict the mechanical behavior of materials, the direct or inverse analytical approaches are often used. However, in case of an inhomogeneous and anisotropic material as skin tissue, analytical approaches are not able to provide solutions. The numerical simulation is thus necessary. In this work, the uniaxial tensile test and the FEM (finite element method) based inverse method were used to identify the anisotropic mechanical properties of porcine skin tissue. The uniaxial tensile experiments were performed using Instron 8800 tensile machine®. The uniaxial tensile test was simulated with FEM, and then the inverse optimization approach (or the inverse calibration) was used for the identification of mechanical properties of the samples. Experimentally results were compared to finite element solutions. The results showed that the finite element model predictions of the mechanical behavior of the tested skin samples were well correlated with experimental results.

Keywords: mechanical skin tissue behavior, uniaxial tensile test, finite element analysis, inverse optimization approach

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2448 Comparison of Loosely Coupled and Tightly Coupled INS/GNSS Architecture for Guided Rocket Navigation System

Authors: Rahmat Purwoko, Bambang Riyanto Trilaksono

Abstract:

This paper gives comparison of INS/GNSS architecture namely Loosely Coupled and Tightly Coupled using Hardware in the Loop Simulation in Guided Missile RKX-200 rocket model. INS/GNSS Tightly Coupled architecture requires pseudo-range, pseudo-range rate, and position and velocity of each satellite in constellation from GPS (Global Positioning System) measurement. The Loosely Coupled architecture use estimated position and velocity from GNSS receiver. INS/GNSS architecture also requires angular rate and specific force measurement from IMU (Inertial Measurement Unit). Loosely Coupled arhitecture designed using 15 states Kalman Filter and Tightly Coupled designed using 17 states Kalman Filter. Integration algorithm calculation using ECEF frame. Navigation System implemented Zedboard All Programmable SoC.

Keywords: kalman filter, loosely coupled, navigation system, tightly coupled

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2447 Evaluation of ROS Mediated Apoptosis Induced by Tuber Extract of Dioscorea Bulbifera on Human Breast Adenocarcinoma

Authors: Debasmita Dubey, Rajesh Kumar Meher, Smruti Pragya Samal, Pradeep Kumar Naik

Abstract:

Background: To determine antioxidant properties and anticancer activity by ROS and mitochondrial transmembrane potential mediated apoptosis against MCF7, MDA-MB-231, cell line. Methods: Leaf sample was extracted using methanol by microwave digestion technique. The antioxidant properties of the methanolic extract were determined by a DPPH scavenging assay. In vitro anticancer activity, mitochondrial transmembrane potential, apoptosis activity and DNA fragmentation study, as well as intracellular ROS activity of most potential leaf extract, were also determined by using the MDA-MB-231cell line. In vivo animal toxicity study was carried out using mice model. Results: Methanolic leaf extract has shown the highest antioxidant, as well as anticancer activity, is based on the assay conducted. For the identification of active phytochemicals from methanolic extract, High-resolution mass spectroscopy-LCMS was used. In vitro cytotoxicity study against MCF-7 and MDA-MB-231 cell line and IC 50 value was found to be 37.5µg/ml. From histopathological studies, no toxicity in liver and kidney tissue was identified. Conclusion: This plant tuber can be used as a regular diet to reduce the chance of breast cancer. Further, more studies should be conducted to isolate and identify the responsible compound.

Keywords: human breast adenocarcinoma, ROS, mitochondrial transmembrane, apoptosis

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2446 Patient Progression at Discharge: A Communication, Coordination, and Accountability Gap among Hospital Teams

Authors: Nana Benma Osei

Abstract:

Patient discharge can be a hectic process. Patients are sometimes sent to the wrong location or forgotten in lounges in the waiting room. This ends up compromising patient care because the delay in picking the patients can affect how they adhere to medication. Patients may fail to take their medication, and this will lead to negative outcomes. The situation highlights the demands of modern-day healthcare, and the use of technology can help in reducing such challenges and in enhancing the patient’s experience, leading to greater satisfaction with the care provided. The paper contains the proposed changes to a healthcare facility by introducing the clinical decision support system, which will be needed to improve coordination and communication during patient discharge. This will be done under Kurt Lewin’s Change Management Model, which recognizes the different phases in the change process. A pilot program is proposed initially before the program can be implemented in the entire organization. This allows for the identification of challenges and ways of managing them. The paper anticipates some of the possible challenges that may arise during implementation, and a multi-disciplinary approach is considered the most effective. Opposition to the change is likely to arise because staff members may lack information on how the changes will affect them and the skills they will need to learn to use the new system. Training will occur before the technology can be implemented. Every member will go for training, and adequate time is allocated for training purposes. A comparison of data will determine whether the project has succeeded.

Keywords: patient discharge, clinical decision support system, communication, collaboration

Procedia PDF Downloads 100
2445 Implementation of Lean Management in Non-Governmental Organizations: A Case Study on WrocłAw Food Bank

Authors: Maciej Pieńkowski

Abstract:

Lean Management is nowadays one of the most dominating management concepts within industrial and service environment, providing compelling business benefits to many companies. At the same time, its application in the non-governmental organizations has not been extensively researched yet. Filling this gap will address clear necessity of efficient management system in NGO environment and significantly improve operational performance of many organizations. The goal of the research is to verify effectiveness of Lean Management implementation in the non-governmental organizations, based on Wrocław Food Bank case study. The case study describes a Lean Management implementation project within analyzed organization. During the project, Wrocław Food Bank went through full 5-step Lean Thinking processes, which consist of value identification, value stream mapping, creation of flow, establishing pull and seeking perfection. The research contains a detailed summary of each of those steps and provides with information regarding results of their implementation. The major findings of the study indicate, that application of Lean Management in NGO environment is possible, however physical implementation of its guidelines can be strongly impeded by multiple constraints, which non-governmental organizations are facing. Due to challenges like limited resources, project based activities and lack of traditional supplier-customer relationship, many NGOs may fail in their efforts to implement Lean Management. Successful Lean application requires therefore strong leadership commitment, which would drive transformation to remove barriers and obstacles.

Keywords: lean management, non-governmental organizations, continuous improvement, lean thinking

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2444 Identification and Evaluation of Landscape Mosaics of Kutlubeyyazıcılar Campus, Bartın University, Turkey

Authors: Y. Sarı Nayim, B. N. Nayim

Abstract:

This research proposal includes the defining and evaluation of the semi-natural and cultural ecosystems at Bartın University main campus in Turkey in terms of landscape mosaics. The ecosystem mosaic of the main campus was divided into zones based on ecological classification technique. Based on the results from the study, it was found that 6 different ecosystem mosaics should be used as a base in the planning and design of the existing and future landscape planning of Kutlubeyyazıcılar campus. The first landscape zone involves the 'social areas'. These areas include yards, dining areas, recreational areas and lawn areas. The second landscape zone is 'main vehicle and pedestrian areas'. These areas include vehicle access to the campus landscape, moving in the campus with vehicles, parking and pedestrian walk ways. The third zone is 'landscape areas with high visual landscape quality'. These areas will be the places where attractive structural and plant landscape elements will be used. Fourth zone will be 'landscapes of building borders and their surroundings.' The fifth and important zone that should be survived in the future is 'Actual semi-natural forest and bush areas'. And the last zone is 'water landscape' which brings ecological value to landscape areas. While determining the most convenient areas in the planning and design of the campus, these landscape mosaics should be taken into consideration. This zoning will ensure that the campus landscape is protected and living spaces in the campus apart from the areas where human activities are carried out will be used properly.

Keywords: campus landscape planning and design, landscape ecology, landscape mosaics, Bartın

Procedia PDF Downloads 362
2443 Destination Port Detection For Vessels: An Analytic Tool For Optimizing Port Authorities Resources

Authors: Lubna Eljabu, Mohammad Etemad, Stan Matwin

Abstract:

Port authorities have many challenges in congested ports to allocate their resources to provide a safe and secure loading/ unloading procedure for cargo vessels. Selecting a destination port is the decision of a vessel master based on many factors such as weather, wavelength and changes of priorities. Having access to a tool which leverages AIS messages to monitor vessel’s movements and accurately predict their next destination port promotes an effective resource allocation process for port authorities. In this research, we propose a method, namely, Reference Route of Trajectory (RRoT) to assist port authorities in predicting inflow and outflow traffic in their local environment by monitoring Automatic Identification System (AIS) messages. Our RRoT method creates a reference route based on historical AIS messages. It utilizes some of the best trajectory similarity measure to identify the destination of a vessel using their recent movement. We evaluated five different similarity measures such as Discrete Fr´echet Distance (DFD), Dynamic Time Warping (DTW), Partial Curve Mapping (PCM), Area between two curves (Area) and Curve length (CL). Our experiments show that our method identifies the destination port with an accuracy of 98.97% and an fmeasure of 99.08% using Dynamic Time Warping (DTW) similarity measure.

Keywords: spatial temporal data mining, trajectory mining, trajectory similarity, resource optimization

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2442 Kurma (Kerma Culture) at Nubia: Migration to Dholavira (Indus Valley Civilization)

Authors: Dhanpat Singh Dhania

Abstract:

Kurma-avatara and the Kachchhapraj is the name of the same person. Tortoise is called Kurma in Kerma valley (Nubia) and also called Kachchhap in India. Wherever a culture migrates, its faiths and beliefs remain intact. The tortoise culture of Kurma valley migrated to Dholavira, and its cultural symbolism remained the same as Kurma, the tortoise. Culture is known by burial traditions, pottery formations, language use, faiths, and beliefs. Following the cultural identification methodology, the Kurma culture buried their dead in circular burials found during excavation at Toshka, Nubia, and built their houses the type of tortoise shell. The Nubian tortoise of a specific species had a triangular on the shell found to be extinct was the cultural symbolism of the culture found on the excavated pottery. Kurma cultural head known as the Seth was known as Kurma-avatara. The Seth of Egypt came to know when the combined efforts of the Seth and the Osiris defeated the Egyptian 1st dynastic rule in about 2775 BCE. Osiris became the king of the 2nd dynastic Egypt. It annoyed Seth. He killed the Osiris and went to Rann of Kachchh and declared him as the Chachchhapraj, the king of Kachchh (now Gujarat, India). The Kurma (Kachchhap) culture migration at Dholavira (Gujarat) attested by the Dholavira signboard found during excavation and deciphered as the ‘Chakradhar’, the eighth incarnation of Kurma-avatara.

Keywords: Kurma, Egyptian, Kachchhap, Dholavira, Harappan

Procedia PDF Downloads 74
2441 Hierarchical Tree Long Short-Term Memory for Sentence Representations

Authors: Xiuying Wang, Changliang Li, Bo Xu

Abstract:

A fixed-length feature vector is required for many machine learning algorithms in NLP field. Word embeddings have been very successful at learning lexical information. However, they cannot capture the compositional meaning of sentences, which prevents them from a deeper understanding of language. In this paper, we introduce a novel hierarchical tree long short-term memory (HTLSTM) model that learns vector representations for sentences of arbitrary syntactic type and length. We propose to split one sentence into three hierarchies: short phrase, long phrase and full sentence level. The HTLSTM model gives our algorithm the potential to fully consider the hierarchical information and long-term dependencies of language. We design the experiments on both English and Chinese corpus to evaluate our model on sentiment analysis task. And the results show that our model outperforms several existing state of the art approaches significantly.

Keywords: deep learning, hierarchical tree long short-term memory, sentence representation, sentiment analysis

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2440 Cataphora in English and Chinese Conversation: A Corpus-based Contrastive Study

Authors: Jun Gao

Abstract:

This paper combines the corpus-based and contrastive approaches, seeking to provide a systematic account of cataphora in English and Chinese natural conversations. Based on spoken corpus data, the first part of the paper examines a range of characteristics of cataphora in the two languages, including frequency of occurrence, patterns, and syntactic features. On the basis of this exploration, cataphora in the two languages are contrasted in a structured way. The analysis shows that English and Chinese share a similar distribution of cataphora in natural conversations in terms of frequency of occurrence, with repeat identification cataphora higher than first mention cataphora and intra-sentential cataphora much higher than inter-sentential cataphora. In terms of patterns, three types are identified in English, i.e. P+N, Ø+N, and it+Clause, while in Chinese, two types are identified, i.e., P+N and Ø+N. English and Chinese are similar in terms of syntactic features, i.e., cataphor and postcedent in the intra-sentential cataphora mainly occur in the initial subject position of the same clause, with postcedent immediately followed or delayed, and cataphor and postcedent are mostly in adjacent sentences in inter-sentential cataphora. In the second part of the paper, the motivations of cataphora are investigated. It is found that cataphora is primarily motivated by the speaker and hearer’s different knowledge states with regard to the referent. Other factors are also involved, such as interference, word search, and the tension between the principles of Economy and Clarity.

Keywords: cataphora, contrastive study, motivation, pattern, syntactic features

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2439 Review Architectural Standards in Design and Development Children's Educational Centers

Authors: Ahmad Torkaman, Suogol Shomtob, Hadi Akbari Seddigh

Abstract:

In this paper it has been attempted to investigate the lack of attention to how specific spatial characteristics of the children except existing places such as nurseries. In order to achieve the standard center to faster children understanding their mentality is the first issue that must be studied. Exploring the spiritual characteristics and complexities of children cannot be possible except in accordance with the different aspects and background of their growth in various age periods. In order to achieving the standard center for fostering children, the first issue that must be studied understands their mentality. Exploring the spiritual qualities and complexities of children are not provided except in accordance with the characteristics and their different growth backgrounds in different age periods. According to previous researches game or playing is the most important activity that helps children to communicate and educate and sometimes therapy in specific fields. Investigating game as a proper way to train, the variety of games, the various kind of play environment and how to treat some abnormalities thereby are the issues discussed in recent research. Another consideration concerns the importance of artistic activities among children which is very evident in studying identification of their abnormalities. At the end of this study after investigating how to understand child and communicate with him/her, aiming to recognize Specific spatial characteristics for better training children, the physical and physiological criteria and characteristics is Reviewed and ends up to a list of required spaces and dimensional characteristic of spaces and needed children's equipment.

Keywords: children, space, interior design, development, growth

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2438 The Customization of 3D Last Form Design Based on Weighted Blending

Authors: Shih-Wen Hsiao, Chu-Hsuan Lee, Rong-Qi Chen

Abstract:

When it comes to last, it is regarded as the critical foundation of shoe design and development. Not only the last relates to the comfort of shoes wearing but also it aids the production of shoe styling and manufacturing. In order to enhance the efficiency and application of last development, a computer aided methodology for customized last form designs is proposed in this study. The reverse engineering is mainly applied to the process of scanning for the last form. Then the minimum energy is used for the revision of surface continuity, the surface of the last is reconstructed with the feature curves of the scanned last. When the surface of a last is reconstructed, based on the foundation of the proposed last form reconstruction module, the weighted arithmetic mean method is applied to the calculation on the shape morphing which differs from the grading for the control mesh of last, and the algorithm of subdivision is used to create the surface of last mesh, thus the feet-fitting 3D last form of different sizes is generated from its original form feature with functions remained. Finally, the practicability of the proposed methodology is verified through later case studies.

Keywords: 3D last design, customization, reverse engineering, weighted morphing, shape blending

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2437 Degradation of Acetaminophen with Fe3O4 and Fe2+ as Activator of Peroxymonosulfate

Authors: Chaoqun Tan, Naiyun Gao, Xiaoyan Xin

Abstract:

Perxymonosulfate (PMS)-based oxidation processes, as an alternative of hydrogen peroxide-based oxidation processes, are more and more popular because of reactive radical species (SO4-•, OH•) produced in systems. Magnetic nano-scaled particles Fe3O4 and ferrous anion (Fe2+) were studied for the activation of PMS for degradation of acetaminophen (APAP) in water. The Fe3O4 MNPs were found to effectively catalyze PMS for APAP and the reactions well followed a pseudo-first-order kinetics pattern (R2 > 0.95), while the degradation of APAP in PMS-Fe2+ system proceeds through two stages: a fast stage and a much slower stage. Within 5 min, approximately 7% and 18% of 10 ppm APAP was accomplished by 0.2 mM PMS in Fe3O4 (0.8g/L) and Fe2+ (0.1mM) activation process. However, as reaction proceed to 120 min, approximately 75% and 35% of APAP was removed in Fe3O4 activation process and Fe2+ activation process, respectively. Within 120 min, the mineralization of APAP was about 7.5% and 5.0% (initial APAP of 10 ppm and [PMS]0 of 0.2 mM) in Fe3O4-PMS and Fe2+-PMS system, while the mineralization could be greatly increased to about 31% and 40% as [PMS]0 increased to 2.0 mM in in Fe3O4-PMS and Fe2+-PMS system, respectively. At last, the production of reactive radical species were validated directly from Electron Paramagnetic Resonance (ESR) tests with 0.1 M 5,5-dimethyl-1-pyrrolidine N-oxide (DMPO). Plausible mechanisms on the radical generation from Fe3O4 and Fe2+ activation of PMS are proposed on the results of radial identification tests. The results demonstrated that Fe3O4 MNPs activated PMS and Fe2+ anion activated PMS systems are promising technologies for water pollution caused by contaminants such as pharmaceutical. Fe3O4-PMS system is more suitable for slowly remediation, while Fe2+-PMS system is more suitable for fast remediation.

Keywords: acetaminophen, peroxymonosulfate, radicals, Fe3O4

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2436 Amharic Text News Classification Using Supervised Learning

Authors: Misrak Assefa

Abstract:

The Amharic language is the second most widely spoken Semitic language in the world. There are several new overloaded on the web. Searching some useful documents from the web on a specific topic, which is written in the Amharic language, is a challenging task. Hence, document categorization is required for managing and filtering important information. In the classification of Amharic text news, there is still a gap in the domain of information that needs to be launch. This study attempts to design an automatic Amharic news classification using a supervised learning mechanism on four un-touch classes. To achieve this research, 4,182 news articles were used. Naive Bayes (NB) and Decision tree (j48) algorithms were used to classify the given Amharic dataset. In this paper, k-fold cross-validation is used to estimate the accuracy of the classifier. As a result, it shows those algorithms can be applicable in Amharic news categorization. The best average accuracy result is achieved by j48 decision tree and naïve Bayes is 95.2345 %, and 94.6245 % respectively using three categories. This research indicated that a typical decision tree algorithm is more applicable to Amharic news categorization.

Keywords: text categorization, supervised machine learning, naive Bayes, decision tree

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2435 Encoded Fiber Optic Sensors for Simultaneous Multipoint Sensing

Authors: C. Babu Rao, Pandian Chelliah

Abstract:

Owing to their reliability, a number of fluorescent spectra based fiber optic sensors have been developed for detection and identification of hazardous chemicals such as explosives, narcotics etc. In High security regions, such as airports, it is important to monitor simultaneously multiple locations. This calls for deployment of a portable sensor at each location. However, the selectivity and sensitivity of these techniques depends on the spectral resolution of the spectral analyzer. The better the resolution the larger the repertoire of chemicals that can be detected. A portable unit will have limitations in meeting these requirements. Optical fibers can be employed for collecting and transmitting spectral signal from the portable sensor head to a sensitive central spectral analyzer (CSA). For multipoint sensing, optical multiplexing of multiple sensor heads with CSA has to be adopted. However with multiplexing, when one sensor head is connected to CSA, the rest may remain unconnected for the turn-around period. The larger the number of sensor heads the larger this turn-around time will be. To circumvent this imitation, we propose in this paper, an optical encoding methodology to use multiple portable sensor heads connected to a single CSA. Each portable sensor head is assigned an unique address. Spectra of every chemical detected through this sensor head, are encoded by its unique address and can be identified at the CSA end. The methodology proposed is demonstrated through a simulation using Matlab SIMULINK.

Keywords: optical encoding, fluorescence, multipoint sensing

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2434 A Model to Assess Sustainability Using Multi-Criteria Analysis and Geographic Information Systems: A Case Study

Authors: Antonio Boggia, Luisa Paolotti, Gianluca Massei, Lucia Rocchi, Elaine Pace, Maria Attard

Abstract:

The aim of this paper is to present a methodology and a computer model for sustainability assessment based on the integration of Multi-criteria Decision Analysis (MCDA) with a Geographic Information System (GIS). It presents the result of a study for the implementation of a model for measuring sustainability to address the policy actions for the improvement of sustainability at territory level. The aim is to rank areas in order to understand the specific technical and/or financial support that is required to develop sustainable growth. Assessing sustainable development is a multidimensional problem: economic, social and environmental aspects have to be taken into account at the same time. The tool for a multidimensional representation is a proper set of indicators. The set of indicators must be integrated into a model, that is an assessment methodology, to be used for measuring sustainability. The model, developed by the Environmental Laboratory of the University of Perugia, is called GeoUmbriaSUIT. It is a calculation procedure developed as a plugin working in the open-source GIS software QuantumGIS. The multi-criteria method used within GeoUmbriaSUIT is the algorithm TOPSIS (Technique for Order Preference by Similarity to Ideal Design), which defines a ranking based on the distance from the worst point and the closeness to an ideal point, for each of the criteria used. For the sustainability assessment procedure, GeoUmbriaSUIT uses a geographic vector file where the graphic data represent the study area and the single evaluation units within it (the alternatives, e.g. the regions of a country, or the municipalities of a region), while the alphanumeric data (attribute table), describe the environmental, economic and social aspects related to the evaluation units by means of a set of indicators (criteria). The use of the algorithm available in the plugin allows to treat individually the indicators representing the three dimensions of sustainability, and to compute three different indices: environmental index, economic index and social index. The graphic output of the model allows for an integrated assessment of the three dimensions, avoiding aggregation. The presence of separate indices and graphic output make GeoUmbriaSUIT a readable and transparent tool, since it doesn’t produce an aggregate index of sustainability as final result of the calculations, which is often cryptic and difficult to interpret. In addition, it is possible to develop a “back analysis”, able to explain the positions obtained by the alternatives in the ranking, based on the criteria used. The case study presented is an assessment of the level of sustainability in the six regions of Malta, an island state in the middle of the Mediterranean Sea and the southernmost member of the European Union. The results show that the integration of MCDA-GIS is an adequate approach for sustainability assessment. In particular, the implemented model is able to provide easy to understand results. This is a very important condition for a sound decision support tool, since most of the time decision makers are not experts and need understandable output. In addition, the evaluation path is traceable and transparent.

Keywords: GIS, multi-criteria analysis, sustainability assessment, sustainable development

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2433 The Role of DNA Evidence in Determining Paternity in India: A Study of Cases from the Legal and Scientific Perspective

Authors: Pratyusha Das

Abstract:

A paradigm shift has been noticed in the interpretation of DNA evidence for determining paternity. Sometimes DNA evidence has been accepted while sometimes it was rejected by the Indian Courts. Courts have forwarded various justifications for acceptance and rejection of such evidence through legal and scientific means. Laws have also been changed to accommodate the necessities of society. Balances between both the legal and scientific approaches are required, to make the best possible use of DNA evidence for the well-being of the society. Specifications are to be framed as to when such evidence can be used in the future by pointing out the pros and cons. Judicial trend is to be formulated to find out the present situation. The study of cases of superior courts of India using an analytical and theoretical approach is driving the questions regarding the shared identity of the legal and scientific approaches. To assimilate the differences between the two approaches, the basic differences between them have to be formulated. Revelations are required to access the favorable decisions using the DNA evidence. Reasons are to be forwarded for the unfavorable decisions and the approach preferred in such cases. The outcome of the two methods has to be assessed in relation to the parties to the dispute, the society at large, the researcher and from the judicial point of view. The dependability of the two methods is to be studied in relation to the justice delivery system. A highlight of the chronological study of cases along with the changes in the laws with the aid of presumptions will address the questions of necessity of a method according to the facts and situations. Address is required in this respect whether the legal and scientific forces converge somewhere pushing the traditional identification of paternity towards a fundamental change.

Keywords: cases, evidence, legal, scientific

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2432 Characterization of Agroforestry Systems in Burkina Faso Using an Earth Observation Data Cube

Authors: Dan Kanmegne

Abstract:

Africa will become the most populated continent by the end of the century, with around 4 billion inhabitants. Food security and climate changes will become continental issues since agricultural practices depend on climate but also contribute to global emissions and land degradation. Agroforestry has been identified as a cost-efficient and reliable strategy to address these two issues. It is defined as the integrated management of trees and crops/animals in the same land unit. Agroforestry provides benefits in terms of goods (fruits, medicine, wood, etc.) and services (windbreaks, fertility, etc.), and is acknowledged to have a great potential for carbon sequestration; therefore it can be integrated into reduction mechanisms of carbon emissions. Particularly in sub-Saharan Africa, the constraint stands in the lack of information about both areas under agroforestry and the characterization (composition, structure, and management) of each agroforestry system at the country level. This study describes and quantifies “what is where?”, earliest to the quantification of carbon stock in different systems. Remote sensing (RS) is the most efficient approach to map such a dynamic technology as agroforestry since it gives relatively adequate and consistent information over a large area at nearly no cost. RS data fulfill the good practice guidelines of the Intergovernmental Panel On Climate Change (IPCC) that is to be used in carbon estimation. Satellite data are getting more and more accessible, and the archives are growing exponentially. To retrieve useful information to support decision-making out of this large amount of data, satellite data needs to be organized so to ensure fast processing, quick accessibility, and ease of use. A new solution is a data cube, which can be understood as a multi-dimensional stack (space, time, data type) of spatially aligned pixels and used for efficient access and analysis. A data cube for Burkina Faso has been set up from the cooperation project between the international service provider WASCAL and Germany, which provides an accessible exploitation architecture of multi-temporal satellite data. The aim of this study is to map and characterize agroforestry systems using the Burkina Faso earth observation data cube. The approach in its initial stage is based on an unsupervised image classification of a normalized difference vegetation index (NDVI) time series from 2010 to 2018, to stratify the country based on the vegetation. Fifteen strata were identified, and four samples per location were randomly assigned to define the sampling units. For safety reasons, the northern part will not be part of the fieldwork. A total of 52 locations will be visited by the end of the dry season in February-March 2020. The field campaigns will consist of identifying and describing different agroforestry systems and qualitative interviews. A multi-temporal supervised image classification will be done with a random forest algorithm, and the field data will be used for both training the algorithm and accuracy assessment. The expected outputs are (i) map(s) of agroforestry dynamics, (ii) characteristics of different systems (main species, management, area, etc.); (iii) assessment report of Burkina Faso data cube.

Keywords: agroforestry systems, Burkina Faso, earth observation data cube, multi-temporal image classification

Procedia PDF Downloads 140
2431 An Integrated Lightweight Naïve Bayes Based Webpage Classification Service for Smartphone Browsers

Authors: Mayank Gupta, Siba Prasad Samal, Vasu Kakkirala

Abstract:

The internet world and its priorities have changed considerably in the last decade. Browsing on smart phones has increased manifold and is set to explode much more. Users spent considerable time browsing different websites, that gives a great deal of insight into user’s preferences. Instead of plain information classifying different aspects of browsing like Bookmarks, History, and Download Manager into useful categories would improve and enhance the user’s experience. Most of the classification solutions are server side that involves maintaining server and other heavy resources. It has security constraints and maybe misses on contextual data during classification. On device, classification solves many such problems, but the challenge is to achieve accuracy on classification with resource constraints. This on device classification can be much more useful in personalization, reducing dependency on cloud connectivity and better privacy/security. This approach provides more relevant results as compared to current standalone solutions because it uses content rendered by browser which is customized by the content provider based on user’s profile. This paper proposes a Naive Bayes based lightweight classification engine targeted for a resource constraint devices. Our solution integrates with Web Browser that in turn triggers classification algorithm. Whenever a user browses a webpage, this solution extracts DOM Tree data from the browser’s rendering engine. This DOM data is a dynamic, contextual and secure data that can’t be replicated. This proposal extracts different features of the webpage that runs on an algorithm to classify into multiple categories. Naive Bayes based engine is chosen in this solution for its inherent advantages in using limited resources compared to other classification algorithms like Support Vector Machine, Neural Networks, etc. Naive Bayes classification requires small memory footprint and less computation suitable for smartphone environment. This solution has a feature to partition the model into multiple chunks that in turn will facilitate less usage of memory instead of loading a complete model. Classification of the webpages done through integrated engine is faster, more relevant and energy efficient than other standalone on device solution. This classification engine has been tested on Samsung Z3 Tizen hardware. The Engine is integrated into Tizen Browser that uses Chromium Rendering Engine. For this solution, extensive dataset is sourced from dmoztools.net and cleaned. This cleaned dataset has 227.5K webpages which are divided into 8 generic categories ('education', 'games', 'health', 'entertainment', 'news', 'shopping', 'sports', 'travel'). Our browser integrated solution has resulted in 15% less memory usage (due to partition method) and 24% less power consumption in comparison with standalone solution. This solution considered 70% of the dataset for training the data model and the rest 30% dataset for testing. An average accuracy of ~96.3% is achieved across the above mentioned 8 categories. This engine can be further extended for suggesting Dynamic tags and using the classification for differential uses cases to enhance browsing experience.

Keywords: chromium, lightweight engine, mobile computing, Naive Bayes, Tizen, web browser, webpage classification

Procedia PDF Downloads 162
2430 Effect of BaO-Bi₂O₃-P₂O₅ Glass Additive on Structural and Dielectric Properties of BaTiO₃ Ceramics

Authors: El Mehdi Haily, Lahcen Bih, Mohammed Azrour, Bouchaib Manoun

Abstract:

The effects of xBi₂O₃-yBaO-zP₂O₅ (BBP) glass addition on the sintering, structural, and dielectric properties of BaTiO₃ ceramic (BT) are studied. The BT ceramic was synthesized by the conventional solid-state reaction method while the glasses BaO-Bi₂O₃-P₂O₅ (BBP) were elaborated by melting and quenching process. Different composites BT-xBBP were formed by mixing the BBP glasses with BT ceramic. For each glass composition, where the ratio (x:y:z) is maintained constant, we have developed three composites with different glass weight percentage (x = 2.5, 5, and 7.5 wt %). Addition of the glass helps in better sintering at lower temperatures with the presence of liquid phase at the respective sintering temperatures. The results showed that the sintering temperature decreased from more than 1300°C to 900°C. Density measurements of the composites are performed using the standard Archimedean method with water as medium liquid. It is found that their density and molar volume decrease and increase with glass content, respectively. Raman spectroscopy is used to characterize their structural approach. This technique has allowed the identification of different structural units of phosphate and the characteristic vibration modes of the BT. The electrical properties of the composite samples are carried out by impedance spectroscopy in the frequency range of 10 Hz to 1 MHz under various temperatures from 300 to 473 K. The obtained results show that their dielectric properties depend both on the content of the glass in the composite and the Bi/P ratio in the glasses.

Keywords: phosphate, glasses, composite, Raman spectroscopy, dielectric properties

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2429 Identifying Knowledge Gaps in Incorporating Toxicity of Particulate Matter Constituents for Developing Regulatory Limits on Particulate Matter

Authors: Ananya Das, Arun Kumar, Gazala Habib, Vivekanandan Perumal

Abstract:

Regulatory bodies has proposed limits on Particulate Matter (PM) concentration in air; however, it does not explicitly indicate the incorporation of effects of toxicities of constituents of PM in developing regulatory limits. This study aimed to provide a structured approach to incorporate toxic effects of components in developing regulatory limits on PM. A four-step human health risk assessment framework consists of - (1) hazard identification (parameters: PM and its constituents and their associated toxic effects on health), (2) exposure assessment (parameters: concentrations of PM and constituents, information on size and shape of PM; fate and transport of PM and constituents in respiratory system), (3) dose-response assessment (parameters: reference dose or target toxicity dose of PM and its constituents), and (4) risk estimation (metric: hazard quotient and/or lifetime incremental risk of cancer as applicable). Then parameters required at every step were obtained from literature. Using this information, an attempt has been made to determine limits on PM using component-specific information. An example calculation was conducted for exposures of PM2.5 and its metal constituents from Indian ambient environment to determine limit on PM values. Identified data gaps were: (1) concentrations of PM and its constituents and their relationship with sampling regions, (2) relationship of toxicity of PM with its components.

Keywords: air, component-specific toxicity, human health risks, particulate matter

Procedia PDF Downloads 308
2428 Separation, Identification, and Measuring Gossypol in the Cottonseed Oil and Investigating the Performance of Drugs Prepared from the Combination of Plant Extract and Oil in the Treatment of Cutaneous Leishmaniasis Resistant to Drugs

Authors: Sara Taghdisi, M. Mirmohammadi, M. Mokhtarian

Abstract:

In 2013, the World Health Organization announced the cases of Cutaneous leishmaniasis infection in Iran between 69,000 to 113,000. The most common chemical drugs for Cutaneous leishmaniasis treatment are sodium stibogluconate, and meglumine antimonate, which not only have relatively many side effects, but also some species of the Leishmania genus have become resistant to them .The most prominent compound existing in different parts of the cotton plant is a yellow polyphenol called Gossypol. Gossypol is an extremely valuable compound and has anti-cancer properties. In the current project, Gossypol was extracted with a liquid-liquid extraction method in 120 minutes in the presence of Phosphoric acid from the cotton seed oil of Golestan beach varieties, then got crystallized in darkness using Acetic acid and isolated as Gossypol Acetic acid. The efficiency of the extracted crystal was obtained at 0.12+- 1.28. the cotton plant could be efficient in the treatment of Cutaneous leishmaniasis. The extract of the green-leaf cotton boll of Jargoyeh varieties was tested as an ointment on the target group of patients suffering from Cutaneous leishmaniasis resistant to drugs esistant to drugs by our colleagues in the research team. The results showed the Pearson's correlation coefficient of 0.72 between the two variables of wound diameter and the extract use over time which indicated the positive effect of this extract on the treatment of Cutaneous leishmaniasis was resistant to drugs.

Keywords: cottonseed oil, crystallization, gossypol, green-leaf

Procedia PDF Downloads 104
2427 The Fit of the Partial Pair Distribution Functions of BaMnFeF7 Fluoride Glass Using the Buckingham Potential by the Hybrid RMC Simulation

Authors: Sidi Mohamed Mesli, Mohamed Habchi, Arslane Boudghene Stambouli, Rafik Benallal

Abstract:

The BaMnMF7 (M=Fe,V, transition metal fluoride glass, assuming isomorphous replacement) have been structurally studied through the simultaneous simulation of their neutron diffraction patterns by reverse Monte Carlo (RMC) and by the Hybrid Reverse Monte Carlo (HRMC) analysis. This last is applied to remedy the problem of the artificial satellite peaks that appear in the partial pair distribution functions (PDFs) by the RMC simulation. The HRMC simulation is an extension of the RMC algorithm, which introduces an energy penalty term (potential) in acceptance criteria. The idea of this work is to apply the Buckingham potential at the title glass by ignoring the van der Waals terms, in order to make a fit of the partial pair distribution functions and give the most possible realistic features. When displaying the partial PDFs, we suggest that the Buckingham potential is useful to describe average correlations especially in similar interactions.

Keywords: fluoride glasses, RMC simulation, hybrid RMC simulation, Buckingham potential, partial pair distribution functions

Procedia PDF Downloads 500
2426 Specified Human Motion Recognition and Unknown Hand-Held Object Tracking

Authors: Jinsiang Shaw, Pik-Hoe Chen

Abstract:

This paper aims to integrate human recognition, motion recognition, and object tracking technologies without requiring a pre-training database model for motion recognition or the unknown object itself. Furthermore, it can simultaneously track multiple users and multiple objects. Unlike other existing human motion recognition methods, our approach employs a rule-based condition method to determine if a user hand is approaching or departing an object. It uses a background subtraction method to separate the human and object from the background, and employs behavior features to effectively interpret human object-grabbing actions. With an object’s histogram characteristics, we are able to isolate and track it using back projection. Hence, a moving object trajectory can be recorded and the object itself can be located. This particular technique can be used in a camera surveillance system in a shopping area to perform real-time intelligent surveillance, thus preventing theft. Experimental results verify the validity of the developed surveillance algorithm with an accuracy of 83% for shoplifting detection.

Keywords: Automatic Tracking, Back Projection, Motion Recognition, Shoplifting

Procedia PDF Downloads 329