Search results for: VSS (Vector Space Similarity)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5211

Search results for: VSS (Vector Space Similarity)

2841 Analysis of Translational Ship Oscillations in a Realistic Environment

Authors: Chen Zhang, Bernhard Schwarz-Röhr, Alexander Härting

Abstract:

To acquire accurate ship motions at the center of gravity, a single low-cost inertial sensor is utilized and applied on board to measure ship oscillating motions. As observations, the three axes accelerations and three axes rotational rates provided by the sensor are used. The mathematical model of processing the observation data includes determination of the distance vector between the sensor and the center of gravity in x, y, and z directions. After setting up the transfer matrix from sensor’s own coordinate system to the ship’s body frame, an extended Kalman filter is applied to deal with nonlinearities between the ship motion in the body frame and the observation information in the sensor’s frame. As a side effect, the method eliminates sensor noise and other unwanted errors. Results are not only roll and pitch, but also linear motions, in particular heave and surge at the center of gravity. For testing, we resort to measurements recorded on a small vessel in a well-defined sea state. With response amplitude operators computed numerically by a commercial software (Seaway), motion characteristics are estimated. These agree well with the measurements after processing with the suggested method.

Keywords: extended Kalman filter, nonlinear estimation, sea trial, ship motion estimation

Procedia PDF Downloads 516
2840 Displaying of GnRH Peptides on Bacteriophage T7 and Its Immunogenicity in Mice Model

Authors: Hai Xu, Yiwei Wang, Xi Bao, Bihua Deng, Pengcheng Li, Yu Lu

Abstract:

T7 phage could be used as a perfect vector for peptides expression and haptens presentation. T7-3GnRH recombinant phage was constructed by inserting three copies of Gonadotrophin Releasing Hormone (GnRH) gene into the multiple cloning site of T7 Select 415-1b phage genome. The positive T7-3GnRH phage was selected by using polymerase chain reaction amplification, and the p10B-3GnRH fusion protein was verified by SDS-PAGE and Western-blotting assay. T7-3GnRH vaccine was made and immunized with 1010 pfu in 0.2 ml per dose in mice. Blood samples were collected at an interval in weeks, and anti-GnRH antibody and testosterone concentrations were detected by ELISA and radioimmunoassay, respectively. The results show that T7-3GnRH phage particles confer a high immunogenicity to the GnRH-derived epitope. Moreover, the T7-3GnRH vaccine induced higher level of anti-GnRH antibody than ImproVac®. However, the testosterone concentrations in both immunized groups were at a similar level, and the testis developments were significantly inhibited compared to controls. These findings demonstrated that the anti-GnRH antibody could neutralize the endogenous GnRH to down regulate testosterone level and limit testis development, highlighting the potential value of T7-3GnRH in the immunocastration vaccine research.

Keywords: Gonadotrophin Releasing Hormone (GnRH), Immunocastration, T7 phage, Phage vaccine

Procedia PDF Downloads 271
2839 Determination and Distribution of Formation Thickness Using Seismic and Well Data in Baga/Lake Sub-basin, Chad Basin Nigeria

Authors: Gabriel Efomeh Omolaiye, Olatunji Seminu, Jimoh Ajadi, Yusuf Ayoola Jimoh

Abstract:

The Nigerian part of the Chad Basin till date has been one of the few critically studied basins, with few published scholarly works, compared to other basins such as Niger Delta, Dahomey, etc. This work was undertaken by the integration of 3D seismic interpretations and the well data analysis of eight wells fairly distributed in block A, Baga/Lake sub-basin in Borno basin with the aim of determining the thickness of Chad, Kerri-Kerri, Fika, and Gongila Formations in the sub-basin. Da-1 well (type-well) used in this study was subdivided into stratigraphic units based on the regional stratigraphic subdivision of the Chad basin and was later correlated with other wells using similarity of observed log responses. The combined density and sonic logs were used to generate synthetic seismograms for seismic to well ties. Five horizons were mapped, representing the tops of the formations on the 3D seismic data covering the block; average velocity function with maximum error/residual of 0.48% was adopted in the time to depth conversion of all the generated maps. There is a general thickening of sediments from the west to the east, and the estimated thicknesses of the various formations in the Baga/Lake sub-basin are Chad Formation (400-750 m), Kerri-Kerri Formation (300-1200 m), Fika Formation (300-2200 m) and Gongila Formation (100-1300 m). The thickness of the Bima Formation could not be established because the deepest well (Da-1) terminates within the formation. This is a modification to the previous and widely referenced studies of over forty decades that based the estimation of formation thickness within the study area on the observed outcrops at different locations and the use of few well data.

Keywords: Baga/Lake sub-basin, Chad basin, formation thickness, seismic, velocity

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2838 Modernizer'ness as Madness: A Comparative Historical Study of Emperor Tewodros II of Ethiopia and Sultan Selim III of Ottoman Turkey's Modernization Reforms

Authors: Seid Ahmed Mohammed, Nedim Yalansiz

Abstract:

Many historians hardly gave due attention for historical comparison as their methods of study. They were still stunt supporter of the use of their own historical research method in their studies. But this method lacks the way to analyze some worldwide dynamics of events in comparative perspectives. Some dynamics like revolution, modernization, societal change and transformation needs broader analysis for broadening our historical knowledge’s by comparing and contrasting of the causes, courses and consequences of such dynamics historical developments in the world at large. In this paper, our study focuses up on ‘the dynamics of modernization’ and the challenge of modernity of the old regimes. For instance, countries like Turkey, Ethiopia, China, Russia, Iran, Afghanistan and Thailand have almost the same dynamics in facing the challenge of modernity. In such countries, the old regimes tried to introduce modernization and ‘reform from the above’ in order to tackle the gradual decline of the empire that faced strong challenge from the outside world. The other similarity of them was that as the rulers attempted to introduce the modernization reforms the old traditional and the religious institutions strongly opposed the reforms as the reforms alienated the power and prestige of the traditional classes. Similarly, the rules introduced modernization for maintaining their own unique socio-cultural and religious dynamics not as borrowing and acculturation of the west by complete destruction of their own. Therefore, this paper attempted to give a comparative analysis of two modernizers Tewodros II (1855-1868) of Ethiopia and Sultan Selim III (1739-1808) of Ottoman Turkey who tried to modernize their empire unfortunately they paid their precious life as a result of modernization.

Keywords: comparative history, Ethiopia, modernization, Ottoman Turkey

Procedia PDF Downloads 189
2837 Lotus Mechanism: Validation of Deployment Mechanism Using Structural and Dynamic Analysis

Authors: Parth Prajapati, A. R. Srinivas

Abstract:

The purpose of this paper is to validate the concept of the Lotus Mechanism using Computer Aided Engineering (CAE) tools considering the statics and dynamics through actual time dependence involving inertial forces acting on the mechanism joints. For a 1.2 m mirror made of hexagonal segments, with simple harnesses and three-point supports, the maximum diameter is 400 mm, minimum segment base thickness is 1.5 mm, and maximum rib height is considered as 12 mm. Manufacturing challenges are explored for the segments using manufacturing research and development approaches to enable use of large lightweight mirrors required for the future space system.

Keywords: dynamics, manufacturing, reflectors, segmentation, statics

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2836 Molecular Diagnosis of Influenza Strains Was Carried Out on Patients of the Social Security Clinic in Karaj Using the RT-PCR Technique

Authors: A. Ferasat, S. Rostampour Yasouri

Abstract:

Seasonal flu is a highly contagious infection caused by influenza viruses. These viruses undergo genetic changes that result in new epidemics across the globe. Medical attention is crucial in severe cases, particularly for the elderly, frail, and those with chronic illnesses, as their immune systems are often weaker. The purpose of this study was to detect new subtypes of the influenza A virus rapidly using a specific RT-PCR method based on the HA gene (hemagglutinin). In the winter and spring of 2022_2023, 120 embryonated egg samples were cultured, suspected of seasonal influenza. RNA synthesis, followed by cDNA synthesis, was performed. Finally, the PCR technique was applied using a pair of specific primers designed based on the HA gene. The PCR product was identified after purification, and the nucleotide sequence of purified PCR products was compared with the sequences in the gene bank. The results showed a high similarity between the sequence of the positive samples isolated from the patients and the sequence of the new strains isolated in recent years. This RT-PCR technique is entirely specific in this study, enabling the detection and multiplication of influenza and its subspecies from clinical samples. The RT-PCR technique based on the HA gene, along with sequencing, is a fast, specific, and sensitive diagnostic method for those infected with influenza viruses and its new subtypes. Rapid molecular diagnosis of influenza is essential for suspected people to control and prevent the spread of the disease to others. It also prevents the occurrence of secondary (sometimes fatal) pneumonia that results from influenza and pathogenic bacteria. The critical role of rapid diagnosis of new strains of influenza is to prepare a drug vaccine against the latest viruses that did not exist in the community last year and are entirely new viruses.

Keywords: influenza, molecular diagnosis, patients, RT-PCR technique

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2835 A South African Perspective on Artificial Intelligence and Legal Personality

Authors: M. Naidoo

Abstract:

The concept of moral personhood extending from the moral status of an artificial intelligence system has been explored – but predominantly from a Western conception of personhood. African personhood, however, is distinctly different from Western personhood in that communitarianism is central to the underpinnings of personhood - rather than Western individualism. Personhood in the African context is not an inherent property that a human is born with; rather, it is an ontological journey that one goes on in his or her life with the hopes of attaining personhood. Given the decolonization, projects happening in Africa, and the law-making that is happening in this space within South Africa, it is of paramount importance to consider these views.

Keywords: artificial intelligence, bioethics, law, legal personality

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2834 Second Order Solitary Solutions to the Hodgkin-Huxley Equation

Authors: Tadas Telksnys, Zenonas Navickas, Minvydas Ragulskis

Abstract:

Necessary and sufficient conditions for the existence of second order solitary solutions to the Hodgkin-Huxley equation are derived in this paper. The generalized multiplicative operator of differentiation helps not only to construct closed-form solitary solutions but also automatically generates conditions of their existence in the space of the equation's parameters and initial conditions. It is demonstrated that bright, kink-type solitons and solitary solutions with singularities can exist in the Hodgkin-Huxley equation.

Keywords: Hodgkin-Huxley equation, solitary solution, existence condition, operator method

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2833 Componential Analysis on Defining Sustainable Furniture in Traditional Malay Houses of Melaka

Authors: Nabilah Zainal Abidin, Fawazul Khair Ibrahim, Raja Nafida Raja Shahminan

Abstract:

This paper discusses on how componential analysis is used in architecture, mainly in determining the absence and presence of furniture in Traditional Malay Houses. The house samples were retrieved from the reports archived by the Centre of Built Environment in the Malay World (KALAM) of Universiti Teknologi Malaysia (UTM). Findings from the analysis indicate that furniture available in the spaces of the houses is determined by the culture of the people and the availability of certain furniture is influenced by the activities that are carried out within the space.

Keywords: componential analysis, sustainable furniture, traditional malay house

Procedia PDF Downloads 581
2832 Predicting the Diagnosis of Alzheimer’s Disease: Development and Validation of Machine Learning Models

Authors: Jay L. Fu

Abstract:

Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients.

Keywords: Alzheimer's disease, clinical diagnosis, magnetic resonance imaging, machine learning prediction

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2831 A Study of Preliminary Findings of Behavioral Patterns under Captive Conditions in Chinkara (Gazella bennettii) with Prospects for Future Conservation

Authors: Muhammad Idnan, Arshad Javid, Muhammad Nadeem

Abstract:

The present study was conducted from April 2013 to March 2014 to observe the behavioral parameters of Chinkara (Gazella bennettii) under captive conditions by comparing the captive-born and wild-caught animals for conservation strategies. Understanding the behavioral conformations plays a significant role in captive management. Due to human population explosion and mechanized hunting, the captive breeding seems to be the best way for sports hunting, bush meat, for leather industry and horns for traditional medicinal usage. Primarily, captive management has been used on trial and error basis due to deficiency of ethology of this least concerned species. Behavior of [(20 wild-caught (WC) and 10 captive-bred (CB)] adult Chinkara was observed at captive breeding facilities for ungulates at Ravi Campus, University of Veterinary and Animal Sciences at Kasur district which is situated on southeast side of Lahore. The average annual rainfall is about 650 mm, with frequent raining during monsoon. A focal sample was used to observe the various behavioral patterns for CB and WC chinkara. A similarity was observed in behavioral parameters in WC and CB animals, however, when the differences were considered, WC male deer showed a significantly higher degree of agonistic interaction as compared to the CB male chinkara. These findings suggest that there is no immediate impact of captivity on behavior of chinkara nevertheless 10 generations of captivity. It is suggested that the Chinkara is not suitable for domestication and for successful deer farming, a further study is recommended for ethology of chinkara.

Keywords: Chinkara (Gazella bennettii), domestication, deer farming, ex-situ conservation

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2830 Evidence Theory Enabled Quickest Change Detection Using Big Time-Series Data from Internet of Things

Authors: Hossein Jafari, Xiangfang Li, Lijun Qian, Alexander Aved, Timothy Kroecker

Abstract:

Traditionally in sensor networks and recently in the Internet of Things, numerous heterogeneous sensors are deployed in distributed manner to monitor a phenomenon that often can be model by an underlying stochastic process. The big time-series data collected by the sensors must be analyzed to detect change in the stochastic process as quickly as possible with tolerable false alarm rate. However, sensors may have different accuracy and sensitivity range, and they decay along time. As a result, the big time-series data collected by the sensors will contain uncertainties and sometimes they are conflicting. In this study, we present a framework to take advantage of Evidence Theory (a.k.a. Dempster-Shafer and Dezert-Smarandache Theories) capabilities of representing and managing uncertainty and conflict to fast change detection and effectively deal with complementary hypotheses. Specifically, Kullback-Leibler divergence is used as the similarity metric to calculate the distances between the estimated current distribution with the pre- and post-change distributions. Then mass functions are calculated and related combination rules are applied to combine the mass values among all sensors. Furthermore, we applied the method to estimate the minimum number of sensors needed to combine, so computational efficiency could be improved. Cumulative sum test is then applied on the ratio of pignistic probability to detect and declare the change for decision making purpose. Simulation results using both synthetic data and real data from experimental setup demonstrate the effectiveness of the presented schemes.

Keywords: CUSUM, evidence theory, kl divergence, quickest change detection, time series data

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2829 Genetic Characterization of Acanthamoeba Isolates from Amoebic Keratitis Patients

Authors: Sumeeta Khurana, Kirti Megha, Amit Gupta, Rakesh Sehgal

Abstract:

Background: Amoebic keratitis is a painful vision threatening infection caused by a free living pathogenic amoeba Acanthamoeba. It can be misdiagnosed and very difficult to treat if not suspected early. The epidemiology of Acanthamoeba genotypes causing infection in our geographical area is not yet known to the best of our knowledge. Objective: To characterize Acanthamoeba isolates from amoebic keratitis patients. Methods: A total of 19 isolates obtained from patients with amoebic keratitis presenting to the Advanced Eye Centre at Postgraduate Institute of Medical Education and Research, a tertiary care centre of North India over a period of last 10 years were included. Their corneal scrapings, lens solution and lens case (in case of lens wearer) were collected for microscopic examination, culture and molecular diagnosis. All the isolates were maintained in the Non Nutrient agar culture medium overlaid with E.coli and 13 strains were axenised and maintained in modified Peptone Yeast Dextrose Agar. Identification of Acanthamoeba genotypes was based on amplification of diagnostic fragment 3 (DF3) region of the 18srRNA gene followed by sequencing. Nucleotide similarity search was performed by BLAST search of sequenced amplicons in GenBank database (http//www.ncbi.nlm.nih.gov/blast). Multiple Sequence alignments were determined by using CLUSTAL X. Results: Nine out of 19 Acanthamoeba isolates were found to belong to Genotype T4 followed by 6 isolates of genotype T11, 3 T5 and 1 T3 genotype. Conclusion: T4 is the predominant Acanthamoeba genotype in our geographical area. Further studies should focus on differences in pathogenicity of these genotypes and their clinical significance.

Keywords: Acanthamoeba, free living amoeba, keratitis, genotype, ocular

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2828 Comparative Parametric and Emission Characteristics of Single Cylinder Spark Ignition Engine Using Gasoline, Ethanol, and H₂O as Micro Emulsion Fuels

Authors: Ufaith Qadri, M Marouf Wani

Abstract:

In this paper, the performance and emission characteristics of a Single Cylinder Spark Ignition engine have been investigated. The research is based on micro emulsion application as fuel in a gasoline engine. We have analyzed many micro emulsion compositions in various proportions, for predicting the performance of the Spark Ignition engine. This new technology of fuel modifications is emerging very rapidly as lot of research is going on in the field of micro emulsion fuels in Compression Ignition engines, but the micro emulsion fuel used in a Gasoline engine is very rare. The use of micro emulsion as fuel in a Spark Ignition engine is virtually unexplored. So, our main goal is to see the performance and emission characteristics of micro emulsions as fuel, in Spark Ignition engines, and finding which composition is more efficient. In this research, we have used various micro emulsion fuels whose composition varies for all the three blends, and their performance and emission characteristic were predicted in AVL Boost software. Conventional Gasoline fuel 90%, 80% and 85% were blended with co-surfactant Ethanol in different compositions, and water was used as an additive for making it crystal clear transparent micro emulsion fuel, which is thermodynamically stable. By comparing the performances of engines, the power has shown similarity for micro emulsion fuel and conventional Gasoline fuel. On the other hand, Torque and BMEP shows increase for all the micro emulsion fuels. Micro emulsion fuel shows higher thermal efficiency and lower Specific Fuel Consumption for all the compositions as compared to the Gasoline fuel. Carbon monoxide and Hydro carbon emissions were also measured. The result shows that emissions decrease for all the composition of micro emulsion fuels, and proved to be the most efficient fuel both in terms of performance and emission characteristics.

Keywords: AVL Boost, emissions, microemulsions, performance, Spark Ignition (SI) engine

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2827 Modeling Pan Evaporation Using Intelligent Methods of ANN, LSSVM and Tree Model M5 (Case Study: Shahroud and Mayamey Stations)

Authors: Hamidreza Ghazvinian, Khosro Ghazvinian, Touba Khodaiean

Abstract:

The importance of evaporation estimation in water resources and agricultural studies is undeniable. Pan evaporation are used as an indicator to determine the evaporation of lakes and reservoirs around the world due to the ease of interpreting its data. In this research, intelligent models were investigated in estimating pan evaporation on a daily basis. Shahroud and Mayamey were considered as the studied cities. These two cities are located in Semnan province in Iran. The mentioned cities have dry weather conditions that are susceptible to high evaporation potential. Meteorological data of 11 years of synoptic stations of Shahrood and Mayamey cities were used. The intelligent models used in this study are Artificial Neural Network (ANN), Least Squares Support Vector Machine (LSSVM), and M5 tree models. Meteorological parameters of minimum and maximum air temperature (Tmax, Tmin), wind speed (WS), sunshine hours (SH), air pressure (PA), relative humidity (RH) as selected input data and evaporation data from pan (EP) to The output data was considered. 70% of data is used at the education level, and 30 % of the data is used at the test level. Models used with explanation coefficient evaluation (R2) Root of Mean Squares Error (RMSE) and Mean Absolute Error (MAE). The results for the two Shahroud and Mayamey stations showed that the above three models' operations are rather appropriate.

Keywords: pan evaporation, intelligent methods, shahroud, mayamey

Procedia PDF Downloads 65
2826 Effects of Allowance for Corporate Equity on the Financing Choices of Belgian Small and Medium-Sized Enterprises in a Crisis Context

Authors: O. Colot, M. Croquet, L. Cultrera, Y. Fandja Collince

Abstract:

The objective of our research is to evaluate the impact of the allowance for corporate equity (ACE) on the financial structure of Belgian SME in order to highlight the potential existence of a fiscal leverage. To limit the biases linked to the rationing of the capital further to the financial crisis, we compare first the dynamic evolution of the financial structure of the Belgian firms over the period 2006-2015 by focusing on three sub-periods: 2006-2008, 2009-2012 and 2013-2015. We give then an international size to this comparison by including SMEs from countries adjoining Belgium (France, Germany, Netherlands and the United Kingdom) and within which there is no ACE. This comparison allows better understanding the fiscal advantage linked to the ACE of firms evolving in a relatively unstable economic environment further to the financial crisis of 2008. This research is relevant given the economic and political context in which Belgium operates and the very uncertain future of the Belgian ACE. The originality of this research is twofold: the long study period and the consideration of the effects of the financial and economic crisis on the financing structure of Belgian SMEs. The results of this research, even though they confirm the existence of a positive fiscal leverage for the tax deduction for venture capital on the financing structure of Belgian SMEs, do not allow the extent of this leverage to be clearly quantified. The comparative evolution of financing structures over the period 2006-2015 of Belgian, French, German, Dutch and English SMEs shows a strong similarity in the overall evolution of their financing.

Keywords: allowance for corporate equity, Belgium, financial structure, small and medium sized firms

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2825 The Effectiveness of Virtual Reality Training for Improving Interpersonal Communication Skills: An Experimental Study

Authors: Twinkle Sara Joseph

Abstract:

Virtual reality technology has emerged as a revolutionary power that can transform the education sector in many ways. VR environments can break the boundaries of the traditional classroom setting by immersing the students in realistic 3D environments where they can interact with virtual characters without fearing being judged. Communication skills are essential for every profession, and studies suggest the importance of implementing basic-level communication courses at both the school and graduate levels. Interpersonal communication is a skill that gains prominence as it is required in every profession. Traditional means of training have limitations for trainees as well as participants. The fear of being judged, the audience interaction, and other factors can affect the performance of a participant in a traditional classroom setting. Virtual reality offers a unique opportunity for its users to participate in training that does not set any boundaries that prevent the participants from performing in front of an audience. Specialised applications designed in VR headsets offer a range of training and exercises for participants without any time, space, or audience limitations. The present study aims at measuring the effectiveness of VR training in improving interpersonal communication skills among students. The study uses a mixed-method approach, in which a pre-and post-test will be designed to measure effectiveness. A preliminary selection process involving a questionnaire and a screening test will identify suitable candidates based on their current communication proficiency levels. Participants will undergo specialised training through the VR application Virtual Speech tailored for interpersonal communication and public speaking, designed to operate without the traditional constraints of time, space, or audience. The training's impact will subsequently be measured through situational exercises to engage the participants in interpersonal communication tasks, thereby assessing the improvement in their skills. The significance of this study lies in its potential to provide empirical evidence supporting VR technology's role in enhancing communication skills, thereby offering valuable insights for integrating VR-based methodologies into educational frameworks to prepare students more effectively for their professional futures.

Keywords: virtual reality, VR training, interpersonal communication, communication skills, 3D environments

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2824 Real-Time Demonstration of Visible Light Communication Based on Frequency-Shift Keying Employing a Smartphone as the Receiver

Authors: Fumin Wang, Jiaqi Yin, Lajun Wang, Nan Chi

Abstract:

In this article, we demonstrate a visible light communication (VLC) system over 8 meters free space transmission based on a commercial LED and a receiver in connection with an audio interface of a smart phone. The signal is in FSK modulation format. The successful experimental demonstration validates the feasibility of the proposed system in future wireless communication network.

Keywords: visible light communication, smartphone communication, frequency shift keying, wireless communication

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2823 Development of Prediction Models of Day-Ahead Hourly Building Electricity Consumption and Peak Power Demand Using the Machine Learning Method

Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

Abstract:

To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: building energy prediction, data mining, demand response, electricity market

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2822 Application Difference between Cox and Logistic Regression Models

Authors: Idrissa Kayijuka

Abstract:

The logistic regression and Cox regression models (proportional hazard model) at present are being employed in the analysis of prospective epidemiologic research looking into risk factors in their application on chronic diseases. However, a theoretical relationship between the two models has been studied. By definition, Cox regression model also called Cox proportional hazard model is a procedure that is used in modeling data regarding time leading up to an event where censored cases exist. Whereas the Logistic regression model is mostly applicable in cases where the independent variables consist of numerical as well as nominal values while the resultant variable is binary (dichotomous). Arguments and findings of many researchers focused on the overview of Cox and Logistic regression models and their different applications in different areas. In this work, the analysis is done on secondary data whose source is SPSS exercise data on BREAST CANCER with a sample size of 1121 women where the main objective is to show the application difference between Cox regression model and logistic regression model based on factors that cause women to die due to breast cancer. Thus we did some analysis manually i.e. on lymph nodes status, and SPSS software helped to analyze the mentioned data. This study found out that there is an application difference between Cox and Logistic regression models which is Cox regression model is used if one wishes to analyze data which also include the follow-up time whereas Logistic regression model analyzes data without follow-up-time. Also, they have measurements of association which is different: hazard ratio and odds ratio for Cox and logistic regression models respectively. A similarity between the two models is that they are both applicable in the prediction of the upshot of a categorical variable i.e. a variable that can accommodate only a restricted number of categories. In conclusion, Cox regression model differs from logistic regression by assessing a rate instead of proportion. The two models can be applied in many other researches since they are suitable methods for analyzing data but the more recommended is the Cox, regression model.

Keywords: logistic regression model, Cox regression model, survival analysis, hazard ratio

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2821 Negotiating Autonomy in Women’s Political Participation: The Case of Elected Women’s Representatives from Jharkhand

Authors: Rajeshwari Balasubramanian, Margit Van Wessel, Nandini Deo

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The participation of women in local bodies witnessed a rise after the implementation of 73rd and 74th Amendments to the Indian Constitution which created quotas for women representatives. However, even when participation increased, it did not translate into meaningful contributions by women in local bodies. This led some civil society organisations (CSOs) to begin working with women panchayat representatives in various states to build their capacity for political participation. The focus of this paper is to study capacity building training by CSOs in Jharkhand. The paper maps how the training helps women elected representatives to negotiate their autonomy at multiple levels. The paper describes the capacity building program conducted by an international feminist organisation along with its seven local partners in Jharkhand. The central question that the study asks is: How does capacity building training by CSOs in Jharkhand impact the autonomy of elected women representatives? It uses a qualitative research methodology based on empirical data gathered through field visits in four districts of Jharkhand (Chatra, Hazaribagh, East Singhbum and Ranchi) where the program was implemented for three years. The study found that women elected representatives had to develop strategies to negotiate their choice to move out of their homes and attend the training conducted by CSOs. The ability to participate in the training programs itself was a significant achievement of personal autonomy for many women. The training provided them a platform to voice their opinion and appreciate their own value as panchayat leaders. This realization allowed them to negotiate their presence and a space for themselves in Gram panchayats. A Foucauldian approach to analyze capacity building workshops might lead us to see them as systems in which CSOs impose a form of governmentality on rural elected representatives. Instead, what we see here is a much more complex negotiation of agency in which the CSO creates spaces and practices that allow women to achieve their own forms of autonomy. The study concludes that the impact of the training on the autonomy of these women is based on their everyday negotiations of time, space and mobility. Autonomy for these elected women representatives is also contextual and relative, as they seem to realize it during the training process. The training allows the women to not only negotiate their participation in panchayats but also challenge everyday practices that are rooted in patriarchy.

Keywords: autonomy, feminist organization, local bodies, political participation

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2820 Mental Health Diagnosis through Machine Learning Approaches

Authors: Md Rafiqul Islam, Ashir Ahmed, Anwaar Ulhaq, Abu Raihan M. Kamal, Yuan Miao, Hua Wang

Abstract:

Mental health of people is equally important as of their physical health. Mental health and well-being are influenced not only by individual attributes but also by the social circumstances in which people find themselves and the environment in which they live. Like physical health, there is a number of internal and external factors such as biological, social and occupational factors that could influence the mental health of people. People living in poverty, suffering from chronic health conditions, minority groups, and those who exposed to/or displaced by war or conflict are generally more likely to develop mental health conditions. However, to authors’ best knowledge, there is dearth of knowledge on the impact of workplace (especially the highly stressed IT/Tech workplace) on the mental health of its workers. This study attempts to examine the factors influencing the mental health of tech workers. A publicly available dataset containing more than 65,000 cells and 100 attributes is examined for this purpose. Number of machine learning techniques such as ‘Decision Tree’, ‘K nearest neighbor’ ‘Support Vector Machine’ and ‘Ensemble’, are then applied to the selected dataset to draw the findings. It is anticipated that the analysis reported in this study would contribute in presenting useful insights on the attributes contributing in the mental health of tech workers using relevant machine learning techniques.

Keywords: mental disorder, diagnosis, occupational stress, IT workplace

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2819 Fabrication of Hybrid Scaffolds Consisting of Cell-laden Electrospun Micro/Nanofibers and PCL Micro-structures for Tissue Regeneration

Authors: MyungGu Yeo, JongHan Ha, Gi-Hoon Yang, JaeYoon Lee, SeungHyun Ahn, Hyeongjin Lee, HoJun Jeon, YongBok Kim, Minseong Kim, GeunHyung Kim

Abstract:

Tissue engineering is a rapidly growing interdisciplinary research area that may provide options for treating damaged tissues and organs. As a promising technique for regenerating various tissues, this technology requires biomedical scaffolds, which serve as an artificial extracellular matrix (ECM) to support neotissue growth. Electrospun micro/nanofibers have been used widely in tissue engineering because of their high surface-area-to-volume ratio and structural similarity to extracellular matrix. However, low mechanical sustainability, low 3D shape-ability, and low cell infiltration have been major limitations to their use. In this work, we propose new hybrid scaffolds interlayered with cell-laden electrospun micro/nano fibers and poly(caprolactone) microstructures. Also, we applied various concentrations of alginate and electric field strengths to determine optimal conditions for the cell-electrospinning process. The combination of cell-laden bioink (2 ⅹ 10^5 osteoblast-like MG63 cells/mL, 2 wt% alginate, 2 wt% poly(ethylene oxide), and 0.7 wt% lecithin) and a 0.16 kV/mm electric field showed the highest cell viability and fiber formation in this process. Using these conditions and PCL microstructures, we achieved mechanically stable hybrid scaffolds. In addition, the cells embedded in the fibrous structure were viable and proliferated. We suggest that the cell-embedded hybrid scaffolds fabricated using the cell-electrospinning process may be useful for various soft- and hard-tissue regeneration applications.

Keywords: bioink, cell-laden scaffold, micro/nanofibers, poly(caprolactone)

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2818 From the Local to the Global: New Terrorism

Authors: Shamila Ahmed

Abstract:

The paper examines how the fluidity between the local level and the global level is an intrinsic feature of new terrorism. Through using cosmopolitanism, the narratives of the two opposing sides of ISIS and the ‘war on terrorism’ response are explored. It is demonstrated how the fluidity between these levels facilitates the radicalisation process through exploring how groups such as ISIS highlight the perceived injustices against Muslims locally and globally and therefore exploit the globalisation process which has reduced the space between these levels. Similarly, it is argued that the ‘war on terror’ involves the intersection of fear, security, threat, risk and social control as features of both the international ‘war on terror’ and intra state policies.

Keywords: terrorism, war on terror, cosmopolitanism, global level terrorism

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2817 Predictive Analytics of Student Performance Determinants

Authors: Mahtab Davari, Charles Edward Okon, Somayeh Aghanavesi

Abstract:

Every institute of learning is usually interested in the performance of enrolled students. The level of these performances determines the approach an institute of study may adopt in rendering academic services. The focus of this paper is to evaluate students' academic performance in given courses of study using machine learning methods. This study evaluated various supervised machine learning classification algorithms such as Logistic Regression (LR), Support Vector Machine, Random Forest, Decision Tree, K-Nearest Neighbors, Linear Discriminant Analysis, and Quadratic Discriminant Analysis, using selected features to predict study performance. The accuracy, precision, recall, and F1 score obtained from a 5-Fold Cross-Validation were used to determine the best classification algorithm to predict students’ performances. SVM (using a linear kernel), LDA, and LR were identified as the best-performing machine learning methods. Also, using the LR model, this study identified students' educational habits such as reading and paying attention in class as strong determinants for a student to have an above-average performance. Other important features include the academic history of the student and work. Demographic factors such as age, gender, high school graduation, etc., had no significant effect on a student's performance.

Keywords: student performance, supervised machine learning, classification, cross-validation, prediction

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2816 Waste Management in a Hot Laboratory of Japan Atomic Energy Agency – 1: Overview and Activities in Chemical Processing Facility

Authors: Kazunori Nomura, Hiromichi Ogi, Masaumi Nakahara, Sou Watanabe, Atsuhiro Shibata

Abstract:

Chemical Processing Facility of Japan Atomic Energy Agency is a basic research field for advanced back-end technology developments with using actual high-level radioactive materials such as irradiated fuels from the fast reactor, high-level liquid waste from reprocessing plant. In the nature of a research facility, various kinds of chemical reagents have been offered for fundamental tests. Most of them were treated properly and stored in the liquid waste vessel equipped in the facility, but some were not treated and remained at the experimental space as a kind of legacy waste. It is required to treat the waste in safety. On the other hand, we formulated the Medium- and Long-Term Management Plan of Japan Atomic Energy Agency Facilities. This comprehensive plan considers Chemical Processing Facility as one of the facilities to be decommissioned. Even if the plan is executed, treatment of the “legacy” waste beforehand must be a necessary step for decommissioning operation. Under this circumstance, we launched a collaborative research project called the STRAD project, which stands for Systematic Treatment of Radioactive liquid waste for Decommissioning, in order to develop the treatment processes for wastes of the nuclear research facility. In this project, decomposition methods of chemicals causing a troublesome phenomenon such as corrosion and explosion have been developed and there is a prospect of their decomposition in the facility by simple method. And solidification of aqueous or organic liquid wastes after the decomposition has been studied by adding cement or coagulants. Furthermore, we treated experimental tools of various materials with making an effort to stabilize and to compact them before the package into the waste container. It is expected to decrease the number of transportation of the solid waste and widen the operation space. Some achievements of these studies will be shown in this paper. The project is expected to contribute beneficial waste management outcome that can be shared world widely.

Keywords: chemical processing facility, medium- and long-term management plan of JAEA facilities, STRAD project, treatment of radioactive waste

Procedia PDF Downloads 138
2815 Blended Learning Instructional Approach to Teach Pharmaceutical Calculations

Authors: Sini George

Abstract:

Active learning pedagogies are valued for their success in increasing 21st-century learners’ engagement, developing transferable skills like critical thinking or quantitative reasoning, and creating deeper and more lasting educational gains. 'Blended learning' is an active learning pedagogical approach in which direct instruction moves from the group learning space to the individual learning space, and the resulting group space is transformed into a dynamic, interactive learning environment where the educator guides students as they apply concepts and engage creatively in the subject matter. This project aimed to develop a blended learning instructional approach to teaching concepts around pharmaceutical calculations to year 1 pharmacy students. The wrong dose, strength or frequency of a medication accounts for almost a third of medication errors in the NHS therefore, progression to year 2 requires a 70% pass in this calculation test, in addition to the standard progression requirements. Many students were struggling to achieve this requirement in the past. It was also challenging to teach these concepts to students of a large class (> 130) with mixed mathematical abilities, especially within a traditional didactic lecture format. Therefore, short screencasts with voice-over of the lecturer were provided in advance of a total of four teaching sessions (two hours/session), incorporating core content of each session and talking through how they approached the calculations to model metacognition. Links to the screencasts were posted on the learning management. Viewership counts were used to determine that the students were indeed accessing and watching the screencasts on schedule. In the classroom, students had to apply the knowledge learned beforehand to a series of increasingly difficult set of questions. Students were then asked to create a question in group settings (two students/group) and to discuss the questions created by their peers in their groups to promote deep conceptual learning. Students were also given time for question-and-answer period to seek clarifications on the concepts covered. Student response to this instructional approach and their test grades were collected. After collecting and organizing the data, statistical analysis was carried out to calculate binomial statistics for the two data sets: the test grade for students who received blended learning instruction and the test grades for students who received instruction in a standard lecture format in class, to compare the effectiveness of each type of instruction. Student response and their performance data on the assessment indicate that the learning of content in the blended learning instructional approach led to higher levels of student engagement, satisfaction, and more substantial learning gains. The blended learning approach enabled each student to learn how to do calculations at their own pace freeing class time for interactive application of this knowledge. Although time-consuming for an instructor to implement, the findings of this research demonstrate that the blended learning instructional approach improves student academic outcomes and represents a valuable method to incorporate active learning methodologies while still maintaining broad content coverage. Satisfaction with this approach was high, and we are currently developing more pharmacy content for delivery in this format.

Keywords: active learning, blended learning, deep conceptual learning, instructional approach, metacognition, pharmaceutical calculations

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2814 The Collective Memory, Node Reconstruction and Local Belongingness in the Settlement of Outlying Islands: By Taking the Important Architectural Complex of Wang-an Hua-Zhai Settlement as an Example

Authors: Shu-Yen Wang, Shyh-Huei Hwang

Abstract:

Designated as an important architectural complex of settlement by the Ministry of Culture, Hua-Zhai Settlement located in Wang-An Township, Peng-Hu County, of Taiwan has been progressively restored year by year and is now at the revitalization and reutilization stage. Over the last 5 years, YunTech has participated in the restoration project while being in compliance with the Bureau of Cultural Heritage’s spirit of 'Living Heritage Conservation'. In this study, reflections have been made to evaluate the contemporariness of traditional settlement development from the aspects of revitalization and reutilization. On the one hand, the connection between settlers’ experiences and emotions have been clarified through the living nodes, collective memory, and social-cultural connotation. On the other hand, activity design has promoted the reconstruction of living nodes and facilitated the reconnection of collective memory, enabling us to explore the contemporariness of living nodes after the reconstruction. With the adoption of literature review, participant observation, and interview analysis methods, this study concludes the following results: 1) The node reconstruction brings back the memories and makes emotional connections: the spatial collective memory is composed of different components. During the reconstruction of node space, villagers participated not only in the narration of the history but also in the restoration of the space. This process enables villagers to bring back their memories and make emotional connections thereto. 2) Villagers’ understanding towards revitalization has been facilitated through node reconstruction: as a medium of this project, activity design has facilitated node reconstruction by offering villagers a natural environment to build up emotional connections to the settlement. This also enables us to better understand the meaning of settlement activation for the local community. 3) New connections are established in life between villagers and the university through the construction of living nodes: through the local implementation of node reconstruction, new connections have been established in life between villagers who participated in the project and the university. In the meantime, the university’s entrance to the community has also been revalued.

Keywords: collective memory, local sense of belonging, reconstruction of living nodes, the important architectural complex of Wang-An Hua-Zhai settlement

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2813 Mutational and Evolutionary Analysis of Interleukin-2 Gene in Four Pakistani Goat Breeds

Authors: Tanveer Hussain, Misbah Hussain, Masroor Ellahi Babar, Muhammad Traiq Pervez, Fiaz Hussain, Sana Zahoor, Rashid Saif

Abstract:

Interleukin 2 (IL-2) is a cytokine which is produced by activated T cells, play important role in immune response against antigen. It act in both autocrine and paracrine manner. It can stimulate B cells and various other phagocytic cells like monocytes, lymphokine-activated killer cells and natural killer cells. Acting in autocrine fashion, IL-2 protein plays a crucial role in proliferation of T cells. IL-2 triggers the release of pro and anti- inflammatory cytokines by activating several pathways. In present study, exon 1 of IL-2 gene of four local Pakistani breeds (Dera Din Panah, Beetal, Nachi and Kamori) from two provinces was amplified by using reported Ovine IL-2 primers, yielding PCR product of 501 bp. The sequencing of all samples was done to identify the polymorphisms in amplified region of IL-2 gene. Analysis of sequencing data resulted in identification of one novel nucleotide substitution (T→A) in amplified non-coding region of IL-2 gene. Comparison of IL-2 gene sequence of all four breeds with other goat breeds showed high similarity in sequence. While phylogenetic analysis of our local breeds with other mammals showed that IL-2 is a variable gene which has undergone many substitutions. This high substitution rate can be due to the decreased or increased changed selective pressure. These rapid changes can also lead to the change in function of immune system. This pioneering study of Pakistani goat breeds urge for further studies on immune system of each targeted breed for fully understanding the functional role of IL-2 in goat immunity.

Keywords: interleukin 2, mutational analysis, phylogeny, goat breeds, Pakistan

Procedia PDF Downloads 597
2812 Recognizing an Individual, Their Topic of Conversation and Cultural Background from 3D Body Movement

Authors: Gheida J. Shahrour, Martin J. Russell

Abstract:

The 3D body movement signals captured during human-human conversation include clues not only to the content of people’s communication but also to their culture and personality. This paper is concerned with automatic extraction of this information from body movement signals. For the purpose of this research, we collected a novel corpus from 27 subjects, arranged them into groups according to their culture. We arranged each group into pairs and each pair communicated with each other about different topics. A state-of-art recognition system is applied to the problems of person, culture, and topic recognition. We borrowed modeling, classification, and normalization techniques from speech recognition. We used Gaussian Mixture Modeling (GMM) as the main technique for building our three systems, obtaining 77.78%, 55.47%, and 39.06% from the person, culture, and topic recognition systems respectively. In addition, we combined the above GMM systems with Support Vector Machines (SVM) to obtain 85.42%, 62.50%, and 40.63% accuracy for person, culture, and topic recognition respectively. Although direct comparison among these three recognition systems is difficult, it seems that our person recognition system performs best for both GMM and GMM-SVM, suggesting that inter-subject differences (i.e. subject’s personality traits) are a major source of variation. When removing these traits from culture and topic recognition systems using the Nuisance Attribute Projection (NAP) and the Intersession Variability Compensation (ISVC) techniques, we obtained 73.44% and 46.09% accuracy from culture and topic recognition systems respectively.

Keywords: person recognition, topic recognition, culture recognition, 3D body movement signals, variability compensation

Procedia PDF Downloads 527