Search results for: multiple sills emplacement

Authors: Tarek Kandil, Ameen Ali

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Distributed generation (DG) has recently gained a lot of momentum in power industry due to market deregulation and environmental concerns. One of the most technical challenges facing DGs is islanding of distributed generators. The current industry practice is to disconnect all distributed generators immediately after the occurrence of islands within 200 to 350 ms after loss of main supply. To achieve such goal, each DG must be equipped with an islanding detection device. Frequency relays are one of the most commonly used loss of mains detection method. However, distribution utilities may be faced with concerns related to false operation of these frequency relays due to improper settings. The commercially available frequency relays are considering standard tight setting. This paper investigates some factors related to relays internal algorithm that contribute to their different operating responses. Further, the relay operation in the presence of multiple distributed at the same network is analyzed. Finally, the relay setting can be accurately determined based on these investigation and analysis.

Keywords: frequency relay, distributed generation, islanding detection, relay setting

Procedia PDF Downloads 534

Authors: Vivek Mahadev, Manoj Kumar, Neelu Mathur, Brahm Dutt Pandey

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Perimeter guarding and protection of critical installations require prompt intrusion detection and assessment to take effective countermeasures. Currently, visual and electronic surveillance are the primary methods used for perimeter guarding. These methods can be costly and complicated, requiring careful planning according to the location and terrain. Moreover, these methods often struggle to detect stealthy and camouflaged insurgents. The object of the present work is to devise a surveillance technique using seismic sensors that overcomes the limitations of existing systems. The aim is to improve intrusion detection, assessment, and characterization by utilizing seismic sensors. Most of the similar systems have only two types of intrusion detection capability viz., human or vehicle. In our work we could even categorize further to identify types of intrusion activity such as walking, running, group walking, fence jumping, tunnel digging and vehicular movements. A virtual fence of 60 meters at GCNEP, Bahadurgarh, Haryana, India, was created by installing four underground geophones at a distance of 15 meters each. The signals received from these geophones are then processed to find unique seismic signatures called features. Various feature optimization and selection methodologies, such as LightGBM, Boruta, Random Forest, Logistics, Recursive Feature Elimination, Chi-2 and Pearson Ratio were used to identify the best features for training the machine learning models. The trained models were developed using algorithms such as supervised support vector machine (SVM) classifier, kNN, Decision Tree, Logistic Regression, Naïve Bayes, and Artificial Neural Networks. These models were then used to predict the category of events, employing weighted ensemble voting to analyze and combine their results. The models were trained with 1940 training events and results were evaluated with 831 test events. It was observed that using the weighted ensemble voting increased the efficiency of predictions. In this study we successfully developed and deployed the virtual fence using geophones. Since these sensors are passive, do not radiate any energy and are installed underground, it is impossible for intruders to locate and nullify them. Their flexibility, quick and easy installation, low costs, hidden deployment and unattended surveillance make such systems especially suitable for critical installations and remote facilities with difficult terrain. This work demonstrates the potential of utilizing seismic sensors for creating better perimeter guarding and protection systems using multiple machine learning models in weighted ensemble voting. In this study the virtual fence achieved an intruder detection efficiency of over 97%.

Keywords: geophone, seismic perimeter surveillance, machine learning, weighted ensemble method

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Authors: R. A. Temah, L. A. Nkengla-Asi

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Planning for future disasters sets the stage for a variety of activities that may trigger multiple recurring operations and expose the community to opportunities to minimize risks. Local communities are increasingly embracing the necessity for planning based on local risks, but are also significantly challenged to effectively plan and response to disasters. This research examines basic risk-based disaster planning model and compares it with advanced risk-based planning that introduces the identification and alignment of varieties of local capabilities within and out of the local community that can be pivotal to facilitate the management of local risks and cascading effects prior to a disaster. A critical review shows that the identification and alignment of capabilities can potentially enhance risk-based disaster planning. A tailored holistic approach to risk based disaster planning is pivotal to enhance collective action and a reduction in disaster collective cost.

Keywords: capabilities, disaster planning, hazards, local community, risk-based

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Authors: Gherbi Nabil

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Detection of ground targets in SAR radar images is an important area for radar information processing. In the literature, various algorithms have been discussed in this context. However, most of them are of low robustness and accuracy. To this end, we discuss target detection in SAR images based on compressive sensing. Firstly, traditional SAR image target detection algorithms are discussed, and their limitations are highlighted. Secondly, a compressive sensing method is proposed based on the sparsity of SAR images. Next, the detection problem is solved using Multiple Measurements Vector configuration. Furthermore, a robust Alternating Direction Method of Multipliers (ADMM) is developed to solve the optimization problem. Finally, the detection results obtained using raw complex data are presented. Experimental results on real SAR images have verified the effectiveness of the proposed algorithm.

Keywords: compressive sensing, raw complex data, synthetic aperture radar, ADMM

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Authors: Somchai Buaroong

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This research aims to investigating strong points and challenges in application of an online learning management system to an English course. Data were collected from observation, learners’ oral and written reports, and the teacher’s journals. A questionnaire was utilized as a tool to collect data. Statistics utilized in this research included frequency, percentage, mean, standard deviation, and multiple regression analysis. The findings show that the system was an additional channel to enhance English language learning through written class assignments that were digitally accessible by any group members, and through communication between the teacher and learners and among learners themselves. Thus, the learning management system could be a promising tool for foreign language teachers. Also revealed in the study were difficulties in its use. The article ends with discussions of findings of the system for foreign language classes in association to pedagogy are also included and in the level of signification.

Keywords: english course, foreign language system, online learning management system, teacher’s journals

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Authors: Animesh Pan, Geoffrey D. Bothun

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With the development of nanotechnology, research in multifunctional delivery systems has a new pace and dimension. An incipient challenge is to design an all-in-one delivery system that can be used for multiple purposes, including tumor targeting therapy, radio-frequency (RF-), near-infrared (NIR-), light-, or pH-induced controlled release, photothermal therapy (PTT), photodynamic therapy (PDT), and medical diagnosis. In this regard, various inorganic nanoparticles (NPs) are known to show great potential as the 'functional components' because of their fascinating and tunable physicochemical properties and the possibility of multiple theranostic modalities from individual NPs. Magnetic, luminescent, and plasmonic properties are the three most extensively studied and, more importantly biomedically exploitable properties of inorganic NPs. Although successful attempts of combining any two of them above mentioned functionalities have been made, integrating them in one system has remained challenge. Keeping those in mind, controlled designs of complex colloidal nanoparticle system are one of the most significant challenges in nanoscience and nanotechnology. Therefore, systematic and planned studies providing better revelation are demanded. We report a multifunctional delivery platform-based liposome loaded with drug, iron-oxide magnetic nanoparticles (MNPs), and a gold shell on the surface of liposomes, were synthesized using a lipid with polyelectrolyte (layersomes) templating technique. MNPs and the anti-cancer drug doxorubicin (DOX) were co-encapsulated inside liposomes composed by zwitterionic phophatidylcholine and anionic phosphatidylglycerol using reverse phase evaporation (REV) method. The liposomes were coated with positively charge polyelectrolyte (poly-L-lysine) to enrich the interface with gold anion, exposed to a reducing agent to form a gold nanoshell, and then capped with thio-terminated polyethylene glycol (SH-PEG2000). The core-shell nanostructures were characterized by different techniques like; UV-Vis/NIR scanning spectrophotometer, dynamic light scattering (DLS), transmission electron microscope (TEM). This multifunctional system achieves a variety of functions, such as radiofrequency (RF)-triggered release, chemo-hyperthermia, and NIR laser-triggered for photothermal therapy. Herein, we highlight some of the remaining major design challenges in combination with preliminary studies assessing therapeutic objectives. We demonstrate an efficient loading and delivery system to significant cell death of human cancer cells (A549) with therapeutic capabilities. Coupled with RF and NIR excitation to the doxorubicin-loaded core-shell nanostructure helped in securing targeted and controlled drug release to the cancer cells. The present core-shell multifunctional system with their multimodal imaging and therapeutic capabilities would be eminent candidates for cancer theranostics.

Keywords: cancer thernostics, multifunctional nanostructure, photothermal therapy, radiofrequency targeting

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Authors: Chiau Yuan Lim, Hayyiratul Fatimah Mohd Zaid, Fai Kait Chong

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Deep Eutectic Solvent (DES) is used in various applications due to its simplicity in synthesis procedure, biodegradable, inexpensive and easily available chemical ingredients. Graphene Oxide is a popular catalyst that being used in various processes due to its stacking carbon sheets in layer which theoretically rapid up the catalytic processes. In this study, choline chloride based DESs were synthesized and ChCl-PEG(1:4) was found to be the most effective DES in performing desulfurization, which it is able to remove up to 47.4% of the sulfur content in the model oil in just 10 minutes, and up to 95% of sulfur content after repeat the process for six times. ChCl-PEG(1:4) able to perform up to 32.7% desulfurization on real diesel after 6 multiple stages. Thus, future research works should focus on removing the impurities on real diesel before utilising DESs in petroleum field.

Keywords: choline chloride, deep eutectic solvent, fuel desulfurization, graphene oxide

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Authors: Rosa L. Figueroa, Christopher A. Flores, Qing Zeng-Treitler

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A regular expression consists of sequence characters which allow describing a text path. Usually, in clinical research, regular expressions are manually created by programmers together with domain experts. Lately, there have been several efforts to investigate how to generate them automatically. This article presents a text classification algorithm based on regexes. The algorithm named REX was designed, and then, implemented as a simplified method to create regexes to classify Spanish text automatically. In order to classify ambiguous cases, such as, when multiple labels are assigned to a testing example, REX includes an information gain method Two sets of data were used to evaluate the algorithm’s effectiveness in clinical text classification tasks. The results indicate that the regular expression based classifier proposed in this work performs statically better regarding accuracy and F-measure than Support Vector Machine and Naïve Bayes for both datasets.

Keywords: information gain, regular expressions, smith-waterman algorithm, text classification

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Authors: Haojie Wang, Xun Li, Rui Yin

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In order to solve the memorization overfitting in the model-agnostic meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to an exponential growth of computation, this paper also proposes a key data extraction method that only extract part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: mutex task generation, data augmentation, meta-learning, text classification.

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Authors: Natina Roberts, Hanhee Lee

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The existing and emerging refugee research reports unfavorable resettlement outcomes in multiple domains. The proposed paper highlights trends in refugee research in which empirical studies investigate resettlement of former refugees from individual and culturally homogeneous perspectives. The proposed paper then aims to examine the reality of the lived experience of resettlement from family and cross-cultural viewpoints. Proponents for this focus include the United Nations High Commissioner for Refugees (UNHCR). The UNHCR is responsible for leading resettlement efforts for refugees through the durable solutions of repatriation, local integration and resettlement. Life experiences with refugee families, and a report of literary findings on former refugee resettlement from various cultural backgrounds – that highlight similarities and differences among various ethnic groups, will be discussed. The proposed paper is expected to frame underrepresented refugee perspectives, and review policy implications in healthcare, education, and public support systems.

Keywords: refugee, cross-cultural, families, resettlement policy

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Authors: Elisabeth Brandenburg, Robert Woll, Rainer Stark

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This paper presents how smart glasses and voice commands can be used for improving the maintenance process of industrial gas turbines. It presents the process of inspecting a gas turbine’s combustion chamber and how it is currently performed using a set of paper-based documents. In order to improve this process, a portable hands-free process assistance system has been conceived. In the following, it will be presented how the approach of user-centered design and the method of paper prototyping have been successfully applied in order to design a user interface and a corresponding workflow model that describes the possible interaction patterns between the user and the interface. The presented evaluation of these results suggests that the assistance system could help the user by rendering multiple manual activities obsolete, thus allowing him to work hands-free and to save time for generating protocols.

Keywords: paper prototyping, smart glasses, turbine maintenance, user centered design

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Authors: Phornpat Chewasoonthorn, Surat Kwanmuang

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Indoor positioning technologies have been evolved rapidly. They augment the Global Positioning System (GPS) which requires line-of-sight to the sky to track the location of people or objects. This study developed an error correction method for an indoor real-time location system (RTLS) based on an ultra-wideband (UWB) sensor from Decawave. Multiple stationary nodes (anchor) were installed throughout the workspace. The distance between stationary and moving nodes (tag) can be measured using a two-way-ranging (TWR) scheme. The result has shown that the uncorrected ranging error from the sensor system can be as large as 1 m. To reduce ranging error and thus increase positioning accuracy, This study purposes an online correction algorithm using the Kalman filter. The results from experiments have shown that the system can reduce ranging error down to 5 cm.

Keywords: indoor positioning, ultra-wideband, error correction, Kalman filter

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Authors: Salwa Mohamed Salah Eldin, Howida Kamal Ibrahim

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Introduction: Major depressive disorder affects high proportion of the world’s population presenting cost load in health care. Extended release venlafaxine is more convenient and could reduce discontinuation syndrome. The once daily dosing also reduces the potential for adverse events such as nausea due to reduced Cmax. Venlafaxine is an effective first-line agent in the treatment of depression. A once daily formulation was designed to enhance patient compliance. Complexing with a resin was suggested to improve loading of the water soluble drug. The formulated systems were thoroughly evaluated in vitro to prove superiority to previous trials and were compared to the commercial extended release product in experimental animals. Materials and Methods: Venlafaxine-resinates were prepared using Dowex®50WX4-400 and Dowex®50WX8-100 at drug to resin weight ratio of 1: 1. The prepared resinates were evaluated for their drug content, particle shape and surface properties and in vitro release profile in gradient pH. The release kinetics and mechanism were evaluated. Venlafaxine-Dowex® resinates were encapsulated using O/W solvent evaporation technique. Poly-ε-caprolactone, Poly(D, L-lactide-co-glycolide) ester, Poly(D, L-lactide) ester and Eudragit®RS100 were used as coating polymers alone and in combination. Drug-resinate microcapsules were evaluated for morphology, entrapment efficiency and in-vitro release profile. The selected formula was tested in rabbits using a randomized, single-dose, 2-way crossover study against Effexor-XR tablets under fasting condition. Results and Discussion: The equilibrium time was 30 min for Dowex®50WX4-400 and 90 min for Dowex®50WX8-100. The percentage drug loaded was 93.96 and 83.56% for both resins, respectively. Both drug-Dowex® resintes were efficient in sustaining venlafaxine release in comparison to the free drug (up to 8h.). Dowex®50WX4-400 based venlafaxine-resinate was selected for further encapsulation to optimize the release profile for once daily dosing and to lower the burst effect. The selected formula (coated with a mixture of Eudragit RS and PLGA in a ratio of 50/50) was chosen by applying a group of mathematical equations according to targeted values. It recorded the minimum burst effect, the maximum MDT (Mean dissolution time) and a Q24h (percentage drug released after 24 hours) between 95 and 100%. The 90% confidence intervals for the test/reference mean ratio of the log-transformed data of AUC0–24 and AUC0−∞ are within (0.8–1.25), which satisfies the bioequivalence criteria. Conclusion: The optimized formula could be a promising extended release form of the water soluble, short half lived venlafaxine. Being a multiple unit formulation, it lowers the probability of dose dumping and reduces the inter-subject variability in absorption.

Keywords: biodegradable polymers, cation-exchange resin, microencapsulation, venlafaxine hcl

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Authors: Hui-Yu Peng, Hsiu-I Hsueh, Li-Ming Chen

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Most studies focused on bullying behaviors among students, however few research concerns about teachers’ bullying behaviors against students. In order to have more understandings and reduce teacher bullying, it is important to examine what factors may affect teachers’ bullying behaviors. This study aimed to explore the connections between different psychological variables and teacher bullying. Four variables, neuroticism, extraversion, teacher-student relationship, and belief in a just world for others (BJW-others), were selected in this study. Four hundred and five elementary and secondary school teachers in Taiwan endorsed the self-reported surveys. Multiple regression method was used to analyze data. Results revealed that teachers’ BJW-others and extraversion did not have significant correlations with teacher bullying scores. However, closed teacher-student relationship and neuroticism can negatively and positively predict teachers’ bullying behaviors against students, respectively. Implications for preventing teacher bullying were discussed at the end of this study.

Keywords: belief in a just world for others, big five personality traits, teacher bullying, teacher-student relationship

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Authors: Darren Zou

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Forecasting the stock market is a very challenging task. Various economic indicators such as GDP, exchange rates, interest rates, and unemployment have a substantial impact on the stock market. Time series models are the traditional methods used to predict stock market changes. In this paper, a machine learning method, Bayesian Additive Regression Tree (BART) is used in predicting stock market indexes based on multiple economic indicators. BART can be used to model heterogeneous treatment effects, and thereby works well when models are misspecified. It also has the capability to handle non-linear main effects and multi-way interactions without much input from financial analysts. In this research, BART is proposed to provide a reliable prediction on day-to-day stock market activities. By comparing the analysis results from BART and with time series method, BART can perform well and has better prediction capability than the traditional methods.

Keywords: BART, Bayesian, predict, stock

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Authors: M. Lesage, G. Raîche, M. Riopel, F. Fortin, D. Sebkhi

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This paper describes a Web server implementation of the hierarchical aggregate assessment process in the field of education. This process describes itself as a field of teamwork assessment where teams can have multiple levels of hierarchy and supervision. This process is applied everywhere and is part of the management, education, assessment and computer science fields. The E-Assessment website named “Cluster” records in its database the students, the course material, the teams and the hierarchical relationships between the students. For the present research, the hierarchical relationships are team member, team leader and group administrator appointments. The group administrators have the responsibility to supervise team leaders. The experimentation of the application has been performed by high school students in geology courses and Canadian army cadets for navigation patrols in teams. This research extends the work of Nance that uses a hierarchical aggregation process similar as the one implemented in the “Cluster” application.

Keywords: e-learning, e-assessment, teamwork assessment, hierarchical aggregate assessment

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Authors: Rugang Tian

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In this study, we generated whole-genome sequence (WGS) data from110 native cattle. Together with whole-genome sequences from world-wide cattle populations, we estimated the genetic diversity and population genetic structure of different cattle populations. Our findings revealed clustering of cattle groups in line with their geographic locations. We identified noticeable genetic diversity between indigenous cattle breeds and commercial populations. Among all studied cattle groups, lower genetic diversity measures were found in commercial populations, however, high genetic diversity were detected in some local cattle, particularly in Rashoki and Mongolian breeds. Our search for potential genomic regions under selection in native cattle revealed several candidate genes related with immune response and cold shock protein on multiple chromosomes such as TRPM8, NMUR1, PRKAA2, SMTNL2 and OXR1 that are involved in energy metabolism and metabolic homeostasis.

Keywords: cattle, whole-genome, population structure, adaptation

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Authors: Chung-Chun Hsiao, Yu-Kai, Ting, Kai-Yuan Liu, Pang-Wei Yen, Jia-Ying Tu

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In this paper, a new design of spherical robotic system based on the concepts of gimbal structure and gyro dynamics is presented. Robots equipped with multiple wheels and complex steering mechanics may increase the weight and degrade the energy transmission efficiency. In addition, the wheeled and legged robots are relatively vulnerable to lateral impact and lack of lateral mobility. Therefore, the proposed robotic design uses a spherical shell as the main body for ground locomotion, instead of using wheel devices. Three spherical shells are structured in a similar way to a gimbal device and rotate like a gyro system. The design and mechanism of the proposed robotic system is introduced. In addition, preliminary results of the dynamic model based on the principles of planar rigid body kinematics and Lagrangian equation are included. Simulation results and rig construction are presented to verify the concepts.

Keywords: gyro, gimbal, lagrange equation, spherical robots

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Authors: F.Sadoughi, A. Sarsarshahi, L, Eerfannia, S.M.A. Khatami

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Hospital information systems with lots of ability would lead to health care quality improvement. Evaluation of this system has done according different method and criteria. The main goal of present study is to prioritize the most important factors which are influence these systems evaluation. At the first step, according relevant literature, three main factor and 29 subfactors extracted. Then, study framework was designed. Based on analytical hierarchical process (AHP), 28 paired comparisons with Saaty range, in a questionnaire format obtained. Questionnaires were filled by 10 experts in health information management and medical informatics field. Human factors with weight of 0.55 were ranked as the most important. Organization (0.25) and technology (0.14) were in next place. It seems MADM methods such as AHP have enough potential to use in health research and provide positive opportunities for health domain decision makers.

Keywords: Analytical hierarchy process, Multiple criteria decision-making (MCDM), Hospital information system, Evaluation factors

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Authors: Mamdouh Y. Saleh, Gaber El Enany, Medhat H. Elzahar, Moustafa H. Omran

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The discharge limits of industrial waste water effluents are subjected to regulations which are getting more restricted with time. A former research occurred in Port Said city studied the efficiency of treating industrial wastewater using the first stage (A-stage) of the multiple-stage plant (AB-system).From the results of this former research, the effluent treated wastewater has high rates of total dissolved solids (TDS) and chemical oxygen demand (COD). The purpose of this paper is to improve the treatment process in removing TDS and COD. Thus, a pilot plant was constructed at wastewater pump station in the industrial area in the south of Port Said. Experimental work was divided into several groups adding activated carbon with different dosages to waste water, and for each group waste water was filtered after being mixed with activated carbon. pH and TSS as variables were also studied. At the end of this paper, a comparison was made between the efficiency of using activated carbon and the efficiency of using limestone in the same circumstances.

Keywords: adsorption, COD removal, filtration, TDS removal

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Authors: Sannikumar Patel, Brian Nolan, Markus Hofmann, Philip Owende, Kunjan Patel

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Sentiment analysis and opinion mining have become emerging topics of research in recent years but most of the work is focused on data in the English language. A comprehensive research and analysis are essential which considers multiple languages, machine translation techniques, and different classifiers. This paper presents, a comparative analysis of different approaches for multilingual sentiment analysis. These approaches are divided into two parts: one using classification of text without language translation and second using the translation of testing data to a target language, such as English, before classification. The presented research and results are useful for understanding whether machine translation should be used for multilingual sentiment analysis or building language specific sentiment classification systems is a better approach. The effects of language translation techniques, features, and accuracy of various classifiers for multilingual sentiment analysis is also discussed in this study.

Keywords: cross-language analysis, machine learning, machine translation, sentiment analysis

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Authors: Gagandeep Singh, Navdeep Singh

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Due to limited battery of sensor nodes, so energy efficiency found to be main constraint in WSN. Therefore the main focus of the present work is to find the ways to minimize the energy consumption problem and will results; enhancement in the network stability period and life time. Many researchers have proposed different kind of the protocols to enhance the network lifetime further. This paper has evaluated the issues which have been neglected in the field of the WSNs. WSNs are composed of multiple unattended ultra-small, limited-power sensor nodes. Sensor nodes are deployed randomly in the area of interest. Sensor nodes have limited processing, wireless communication and power resource capabilities Sensor nodes send sensed data to sink or Base Station (BS). I-LEACH gives adaptive clustering mechanism which very efficiently deals with energy conservations. This paper ends up with the shortcomings of various adaptive clustering based WSNs protocols.

Keywords: WSN, I-Leach, MATLAB, sensor

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Authors: Aluisius Pratono, Deddy Marciano, Suyanto Suyanto

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The emerging model of community development social enterprise is one of the social enterprise models. However, a precise view of the community development enterprise is still lacking. Hence, this study was aimed at deepening the concept of the community development social enterprise model at the place management and development context. Multiple case studies in Indonesia context were observed to explore the typical criteria of the community development enterprise model in place-making practices. The research paradigm used interpretative approach, which involves dialectic process between the researchers and research participants. This study highlights some principles in the community-development enterprise, which cover an entrepreneurial dimension, social goals, participatory governance, and co-management. The result makes a contribution to conceptual literature occurs at the criteria of social enterprises by highlighting the typology of community development enterprise.

Keywords: community development enterprise, social purposes, economic project, participatory governance

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Authors: Brayden Mi

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Reverse time migration has been widely used in the Petroleum exploration industry to reveal subsurface images and to detect rock and fluid properties since the early 1980s. The seismic technology involves the construction of a velocity model through interpretive model construction, seismic tomography, or full waveform inversion, and the application of the reverse-time propagation of acquired seismic data and the original wavelet used in the acquisition. The methodology has matured from 2D, simple media to present-day to handle full 3D imaging challenges in extremely complex geological conditions. Conventional Ultrasound computed tomography (USCT) utilize travel-time-inversion to reconstruct the velocity structure of an organ. With the velocity structure, USCT data can be migrated with the “bend-ray” method, also known as migration. Its seismic application counterpart is called Kirchhoff depth migration, in which the source of reflective energy is traced by ray-tracing and summed to produce a subsurface image. It is well known that ray-tracing-based migration has severe limitations in strongly heterogeneous media and irregular acquisition geometries. Reverse time migration (RTM), on the other hand, fully accounts for the wave phenomena, including multiple arrives and turning rays due to complex velocity structure. It has the capability to fully reconstruct the image detectable in its acquisition aperture. The RTM algorithms typically require a rather accurate velocity model and demand high computing powers, and may not be applicable to real-time imaging as normally required in day-to-day medical operations. However, with the improvement of computing technology, such a computational bottleneck may not present a challenge in the near future. The present-day (RTM) algorithms are typically implemented from a flat datum for the seismic industry. It can be modified to accommodate any acquisition geometry and aperture, as long as sufficient illumination is provided. Such flexibility of RTM can be conveniently implemented for the application in USCT imaging if the spatial coordinates of the transmitters and receivers are known and enough data is collected to provide full illumination. This paper proposes an implementation of a full 3D RTM algorithm for USCT imaging to produce an accurate 3D acoustic image based on the Phase-shift-plus-interpolation (PSPI) method for wavefield extrapolation. In this method, each acquired data set (shot) is propagated back in time, and a known ultrasound wavelet is propagated forward in time, with PSPI wavefield extrapolation and a piece-wise constant velocity model of the organ (breast). The imaging condition is then applied to produce a partial image. Although each image is subject to the limitation of its own illumination aperture, the stack of multiple partial images will produce a full image of the organ, with a much-reduced noise level if compared with individual partial images.

Keywords: illumination, reverse time migration (RTM), ultrasound computed tomography (USCT), wavefield extrapolation

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Authors: Nora El-Bilawia

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This paper discovers the challenges and/or opportunities to implementing multiple intelligence (MI) practices in English as foreign language (EFL) classrooms at Egyptian public schools as part of the government’s educational reform plan. It is found that Egyptian EFL teachers value the use of MI’s ways of teaching as means for active and higher order thinking. However, teachers believed they were underprivileged, as the government did not provide appropriate trainings, tools, or means to integrate MI in their daily lessons. They also conferred challenges they face due to some Egyptian schooling cultural practices. At the end of this chapter, a proposed need for a paradigm shift in the schooling culture in Egypt to implement practical changes in schools to promote hope in education such as the use of MI teaching tools. This study promotes cross-cultural understanding of educational opportunities and efforts for equal learning outcomes around the globe.

Keywords: professional development, schooling culture, acculturation, equitable education

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Authors: Nagi Mekhiel

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Many applications use vector operations by applying single instruction to multiple data that map to different locations in conventional memory. Transferring data from memory is limited by access latency and bandwidth affecting the performance gain of vector processing. We present a memory system that makes all of its content available to processors in time so that processors need not to access the memory, we force each location to be available to all processors at a specific time. The data move in different orbits to become available to other processors in higher orbits at different time. We use this memory to apply parallel vector operations to data streams at first orbit level. Data processed in the first level move to upper orbit one data element at a time, allowing a processor in that orbit to apply another vector operation to deal with serial code limitations inherited in all parallel applications and interleaved it with lower level vector operations.

Keywords: Memory Organization, Parallel Processors, Serial Code, Vector Processing

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Authors: Janaína F. Guidolini, Jean P. H. B. Ometto, Angélica Giarolla, Peter M. Toledo, Carlos A. Valera

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The water crisis, a major problem of the 21^st century, occurs mainly due to poor management. The central issue that should govern the management is the integration of the various aspects that interfere with the use of water resources and their protection, supported by legal basis. A watershed is a unit of water interacting with the physical, biotic, social, economic and cultural variables. The Brazilian law recognized river basin as the territorial management unit. Based on the diagnosis of the current situation of the water resources of the Rio Grande Basin, a discussion informed in the Brazilian legal basis was made to propose measures to fight or mitigate damages and environmental degradation in the Basin. To manage water resources more efficiently, conserve water and optimize their multiple uses, the integration of acquired scientific knowledge and management is essential. Moreover, it is necessary to monitor compliance with environmental legislation.

Keywords: conservation of soil and water, environmental laws, river basin, sustainability

Procedia PDF Downloads 279

Authors: V. Sacca, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

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In the last few years, resting-state functional MRI (rs-fMRI) was widely used to investigate the architecture of brain networks by investigating the Blood Oxygenation Level Dependent response. This technique represented an interesting, robust and reliable approach to compare pathologic and healthy subjects in order to investigate neurodegenerative diseases evolution. On the other hand, the elaboration of rs-fMRI data resulted to be very prone to noise due to confounding factors especially the head motion. Head motion has long been known to be a source of artefacts in task-based functional MRI studies, but it has become a particularly challenging problem in recent studies using rs-fMRI. The aim of this work was to evaluate in MS patients a well-known motion correction algorithm from the FMRIB's Software Library - MCFLIRT - that could be applied to minimize the head motion distortions, allowing to correctly interpret rs-fMRI results.

Keywords: head motion correction, MCFLIRT algorithm, multiple sclerosis, resting state fMRI

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Authors: Moeen Naseer Butt

Abstract:

Clustering –geographic concentrations of entities– has recently received more attention in marketing research and has been shown to affect multiple outcomes. This study investigates the impact of intrabrand clustering (clustering of same-brand outlets) on an outlet’s quality performance. Further, it assesses the moderating effects of interbrand clustering (clustering of other-brand outlets) and firm size. An examination of approximately 21,000 food service establishments in New York State in 2019 finds that the impact of intrabrand clustering on an outlet’s quality performance is context-dependent. Specifically, intrabrand clustering decreases, whereas interbrand clustering and firm size help increase the outlet’s performance. Additionally, this study finds that the role of firm size is more substantial than interbrand clustering in mitigating the adverse effects of intrabrand clustering on outlet quality performance.

Keywords: intraband clustering, interbrand clustering, firm size, brand competition, outlet performance, quality violations

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Authors: Sol Girouard, Zona Kostic

Abstract:

A home is often the largest and most expensive purchase a person makes. Whether the decision leads to a successful outcome will be determined by a combination of critical factors. In this paper, we propose a method that efficiently handles all the factors in residential real estate and performs predictions given a feature space with high dimensionality while controlling for overfitting. The proposed method was built on gradient descent and boosting algorithms and uses a mixed optimizing technique to improve the prediction power. Usually, a single model cannot handle all the cases thus our approach builds multiple models based on different subsets of the predictors. The algorithm was tested on 3 million homes across the U.S., and the experimental results demonstrate the efficiency of this approach by outperforming techniques currently used in forecasting prices. With everyday changes on the real estate market, our proposed algorithm capitalizes from new events allowing more efficient predictions.

Keywords: real estate prediction, gradient descent, boosting, ensemble methods, active learning, training

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