Search results for: conceptual paper
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 25212

Search results for: conceptual paper

8622 A Qualitative Case Study Exploring Zambian Mathematics Teachers' Content Knowledge of Functions

Authors: Priestly Malambo, Sonja Van Putten, Hanlie Botha, Gerrit Stols

Abstract:

The relevance of what is content is taught in tertiary teacher training has long been in question. This study attempts to understand how advanced mathematics courses equip student teachers to teach functions at secondary school level. This paper reports on an investigation that was conducted in an African university, where preservice teachers were purposefully selected for participation in individual semi-structured interviews after completing a test on functions as taught at secondary school. They were asked to justify their reasoning in the test and to explain functions in a way that might bring about understanding of the topic in someone who did not know how functions work. These were final year preservice mathematics teachers who had studied advanced mathematics courses for three years. More than 50% of the students were not able to explain concepts or to justify their reasoning about secondary school functions in a coherent way. The results of this study suggest that the study of advanced mathematics does not automatically enable students to teach secondary school functions, and that, although these students were able to do advanced mathematics, they were unable to explain the working of functions in a way that would allow them to teach this topic successfully.

Keywords: secondary school, mathematical reasoning, student-teachers, functions

Procedia PDF Downloads 246
8621 Multi-Class Text Classification Using Ensembles of Classifiers

Authors: Syed Basit Ali Shah Bukhari, Yan Qiang, Saad Abdul Rauf, Syed Saqlaina Bukhari

Abstract:

Text Classification is the methodology to classify any given text into the respective category from a given set of categories. It is highly important and vital to use proper set of pre-processing , feature selection and classification techniques to achieve this purpose. In this paper we have used different ensemble techniques along with variance in feature selection parameters to see the change in overall accuracy of the result and also on some other individual class based features which include precision value of each individual category of the text. After subjecting our data through pre-processing and feature selection techniques , different individual classifiers were tested first and after that classifiers were combined to form ensembles to increase their accuracy. Later we also studied the impact of decreasing the classification categories on over all accuracy of data. Text classification is highly used in sentiment analysis on social media sites such as twitter for realizing people’s opinions about any cause or it is also used to analyze customer’s reviews about certain products or services. Opinion mining is a vital task in data mining and text categorization is a back-bone to opinion mining.

Keywords: Natural Language Processing, Ensemble Classifier, Bagging Classifier, AdaBoost

Procedia PDF Downloads 217
8620 Embedded Acoustic Signal Processing System Using OpenMP Architecture

Authors: Abdelkader Elhanaoui, Mhamed Hadji, Rachid Skouri, Said Agounad

Abstract:

In this paper, altera de1-SoC FPGA board technology is utilized as a distinguished tool for nondestructive characterization of an aluminum circular cylindrical shell of radius ratio b/a (a: outer radius; b: inner radius). The acoustic backscattered signal processing system has been developed using OpenMP architecture. The design is built in three blocks; it is implemented per functional block, in a heterogeneous Intel-Altera system running under Linux. The useful data to determine the performances of SoC FPGA is computed by the analytical method. The exploitation of SoC FPGA has lead to obtain the backscattering form function and resonance spectra. A0 and S0 modes of propagation in the tube are shown. The findings are then compared to those achieved from the Matlab simulation of analytical method. A good agreement has, therefore, been noted. Moreover, the detailed SoC FPGA-based system has shown that acoustic spectra are performed at up to 5 times faster than the Matlab implementation using almost the same data. This FPGA-based system implementation of processing algorithms is realized with a coefficient of correlation R and absolute error respectively about 0.962 and 5 10⁻⁵.

Keywords: OpenMP, signal processing system, acoustic backscattering, nondestructive characterization, thin tubes

Procedia PDF Downloads 77
8619 Website Appeal’s Impact on Brand Outcomes: The Mediated Effect of Emotional Attractiveness in the Relationship between Consistent Image and Brand Value

Authors: Salvador Treviño-Martinez, Christian Reich-Lopez

Abstract:

This paper investigates the relationship between website appeal and brand value outcomes (brand attraction, brand loyalty, brand relationship, and brand experience), considering the mediating effect of emotional attractiveness. Data were collected from 221 customers of a quick-service restaurant in Culiacan, Mexico, using an online survey distributed via WhatsApp, following the clients' navigation of the restaurant's website. The study employed PLS-SEM to test the proposed hypotheses and performed 5,000 bootstrapping subsamples to obtain results. The findings indicate that consistent image, a key component of website appeal, has a statistically significant direct and mediated effect (through emotional attractiveness) on the aforementioned brand outcomes. The study's limitations include the convenience sampling method and the single company client database used for the sample composition. This research contributes to the branding and website quality literature by testing nine hypotheses using the Stimuli-Organism-Response theoretical approach in an underexplored context: quick-service restaurants in Latin America.

Keywords: website appeal, branding, emotional attractiveness, consistent image, website quality

Procedia PDF Downloads 78
8618 Automatic Teller Machine System Security by Using Mobile SMS Code

Authors: Husnain Mushtaq, Mary Anjum, Muhammad Aleem

Abstract:

The main objective of this paper is used to develop a high security in Automatic Teller Machine (ATM). In these system bankers will collect the mobile numbers from the customers and then provide a code on their mobile number. In most country existing ATM machine use the magnetic card reader. The customer is identifying by inserting an ATM card with magnetic card that hold unique information such as card number and some security limitations. By entering a personal identification number, first the customer is authenticated then will access bank account in order to make cash withdraw or other services provided by the bank. Cases of card fraud are another problem once the user’s bank card is missing and the password is stolen, or simply steal a customer’s card & PIN the criminal will draw all cash in very short time, which will being great financial losses in customer, this type of fraud has increase worldwide. So to resolve this problem we are going to provide the solution using “Mobile SMS code” and ATM “PIN code” in order to improve the verify the security of customers using ATM system and confidence in the banking area.

Keywords: PIN, inquiry, biometric, magnetic strip, iris recognition, face recognition

Procedia PDF Downloads 347
8617 Optimizing the Scanning Time with Radiation Prediction Using a Machine Learning Technique

Authors: Saeed Eskandari, Seyed Rasoul Mehdikhani

Abstract:

Radiation sources have been used in many industries, such as gamma sources in medical imaging. These waves have destructive effects on humans and the environment. It is very important to detect and find the source of these waves because these sources cannot be seen by the eye. A portable robot has been designed and built with the purpose of revealing radiation sources that are able to scan the place from 5 to 20 meters away and shows the location of the sources according to the intensity of the waves on a two-dimensional digital image. The operation of the robot is done by measuring the pixels separately. By increasing the image measurement resolution, we will have a more accurate scan of the environment, and more points will be detected. But this causes a lot of time to be spent on scanning. In this paper, to overcome this challenge, we designed a method that can optimize this time. In this method, a small number of important points of the environment are measured. Hence the remaining pixels are predicted and estimated by regression algorithms in machine learning. The research method is based on comparing the actual values of all pixels. These steps have been repeated with several other radiation sources. The obtained results of the study show that the values estimated by the regression method are very close to the real values.

Keywords: regression, machine learning, scan radiation, robot

Procedia PDF Downloads 66
8616 Buckling Performance of Irregular Section Cold-Formed Steel Columns under Axially Concentric Loading

Authors: Chayanon Hansapinyo

Abstract:

This paper presents experimental investigation and finite element analysis on buckling behavior of irregular section cold-formed steel columns under axially concentric loading. For the experimental study, four different sections of columns were tested to investigate effect of stiffening and width-to-thickness ratio on buckling behavior. For each of the section, three lengths of 230, 950 and 1900 mm. were studied representing short, intermediate long and long columns, respectively. Then, nonlinear finite element analyses of the tested columns were performed. The comparisons in terms of load-deformation response and buckling mode show good agreement and hence the FEM models were validated. Parametric study of stiffening element and thickness of 1.0, 1.15, 1.2, 1.5, 1.6 and 2.0 mm. were analyzed. The test results showed that stiffening effect pays a large contribution to prevent distortional mode. The increase in wall thickness enhanced buckling stress beyond the yielding strength in short and intermediate columns, but not for the long columns.

Keywords: buckling behavior, irregular section, cold-formed steel, concentric loading

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8615 Complex Learning Tasks and Their Impact on Cognitive Engagement for Undergraduate Engineering Students

Authors: Anastassis Kozanitis, Diane Leduc, Alain Stockless

Abstract:

This paper presents preliminary results from a two-year funded research program looking to analyze and understand the relationship between high cognitive engagement, higher order cognitive processes employed in situations of complex learning tasks, and the use of active learning pedagogies in engineering undergraduate programs. A mixed method approach was used to gauge student engagement and their cognitive processes when accomplishing complex tasks. Quantitative data collected from the self-report cognitive engagement scale shows that deep learning approach is positively correlated with high levels of complex learning tasks and the level of student engagement, in the context of classroom active learning pedagogies. Qualitative analyses of in depth face-to-face interviews reveal insights into the mechanisms influencing students’ cognitive processes when confronted with open-ended problem resolution. Findings also support evidence that students will adjust their level of cognitive engagement according to the specific didactic environment.

Keywords: cognitive engagement, deep and shallow strategies, engineering programs, higher order cognitive processes

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8614 Massively-Parallel Bit-Serial Neural Networks for Fast Epilepsy Diagnosis: A Feasibility Study

Authors: Si Mon Kueh, Tom J. Kazmierski

Abstract:

There are about 1% of the world population suffering from the hidden disability known as epilepsy and major developing countries are not fully equipped to counter this problem. In order to reduce the inconvenience and danger of epilepsy, different methods have been researched by using a artificial neural network (ANN) classification to distinguish epileptic waveforms from normal brain waveforms. This paper outlines the aim of achieving massive ANN parallelization through a dedicated hardware using bit-serial processing. The design of this bit-serial Neural Processing Element (NPE) is presented which implements the functionality of a complete neuron using variable accuracy. The proposed design has been tested taking into consideration non-idealities of a hardware ANN. The NPE consists of a bit-serial multiplier which uses only 16 logic elements on an Altera Cyclone IV FPGA and a bit-serial ALU as well as a look-up table. Arrays of NPEs can be driven by a single controller which executes the neural processing algorithm. In conclusion, the proposed compact NPE design allows the construction of complex hardware ANNs that can be implemented in a portable equipment that suits the needs of a single epileptic patient in his or her daily activities to predict the occurrences of impending tonic conic seizures.

Keywords: Artificial Neural Networks (ANN), bit-serial neural processor, FPGA, Neural Processing Element (NPE)

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8613 A Systamatic Review on Experimental, FEM Analysis and Simulation of Metal Spinning Process

Authors: Amol M. Jadhav, Sharad S. Chudhari, S. S. Khedkar

Abstract:

This review presents a through survey of research paper work on the experimental analysis, FEM Analysis & simulation of the metal spinning process. In this literature survey all the papers being taken from Elsevier publication and most of the from journal of material processing technology. In a last two decade or so, metal spinning process gradually used as chip less formation for the production of engineering component in a small to medium batch quantities. The review aims to provide include into the experimentation, FEM analysis of various components, simulation of metal spinning process and act as guide for research working on metal spinning processes. The review of existing work has several gaps in current knowledge of metal spinning processes. The evaluation of experiment is thickness strain, the spinning force, the twisting angle, the surface roughness of the conventional & shear metal spinning process; the evaluation of FEM of metal spinning to path definition with sufficient fine mesh to capture behavior of work piece; The evaluation of feed rate of roller, direction of roller,& type of roller stimulated. The metal spinning process has the more flexible to produce a wider range of product shape & to form more challenge material.

Keywords: metal spinning, FEM analysis, simulation of metal spinning, mechanical engineering

Procedia PDF Downloads 374
8612 The Trend of Epidemics in Population and Body Regulation in Iran (1850-1920)

Authors: Seyedfateh Moradi

Abstract:

Medical issues mark the beginning of a new form of epistemology in nineteenth-century Iran. The emergence of epidemic diseases led to the formation of a medical discourse and conflict over the body which displayed itself in the concept of health progress and development. The discourse attributed to this development in the health system defines the general structure of the given period. This discourse manifested itself in the conflict between the traditional and new medicine. The regulation and classification of body and population reveal the nature of this period. The government attempted to adapt itself to the modern and progressive discourse. This paper seeks to reveal part of this rupture and adaptation around epidemics and modern medical discourse. Also, accepting part of the traditional discourse in the new era, or adapting and integrating parts of it indicate a delegation of part of the power of traditional authorities. The delegation of power arose in the context of the discursive hegemony of Western modernism from which there was no escape. This provided the ground for the acceptance of government and emergence of other discourses. Finally, during the reign of Reza Shah (1922-1942), body and population planning changed into the key issues of government, which created serious tensions in society.

Keywords: epidemic, population, body, cholera, plague

Procedia PDF Downloads 55
8611 Pavement Roughness Prediction Systems: A Bump Integrator Approach

Authors: Manish Pal, Rumi Sutradhar

Abstract:

Pavement surface unevenness plays a pivotal role on roughness index of road which affects on riding comfort ability. Comfort ability refers to the degree of protection offered to vehicle occupants from uneven elements in the road surface. So, it is preferable to have a lower roughness index value for a better riding quality of road users. Roughness is generally defined as an expression of irregularities in the pavement surface which can be measured using different equipment like MERLIN, Bump integrator, Profilometer etc. Among them Bump Integrator is quite simple and less time consuming in case of long road sections. A case study is conducted on low volume roads in West District in Tripura to determine roughness index (RI) using Bump Integrator at the standard speed of 32 km/h. But it becomes too tough to maintain the requisite standard speed throughout the road section. The speed of Bump Integrator (BI) has to lower or higher in some distinctive situations. So, it becomes necessary to convert these roughness index values of other speeds to the standard speed of 32 km/h. This paper highlights on that roughness index conversional model. Using SPSS (Statistical Package of Social Sciences) software a generalized equation is derived among the RI value at standard speed of 32 km/h and RI value at other speed conditions.

Keywords: bump integrator, pavement distresses, roughness index, SPSS

Procedia PDF Downloads 233
8610 Mindfulness Meditation in Higher Education

Authors: Steve Haberlin

Abstract:

United States college students are experiencing record-high stress and anxiety rates, and due to technological advances, there are more distractions in the classroom. With these challenges comes the need to explore additional, non-traditional pedagogical strategies that can help students de-stress, become centered, and feel more deeply connected to content. In addition, embedding contemplative practices, such as mindfulness meditation, in the higher education classroom could assist faculty in presenting a more holistic education that encourages students to develop self-awareness, emotional intelligence, compassion, interconnectedness, and other “non-academic” qualities. Brief meditation may help students de-stress, focus, and connect. A facilitation guide could also help faculty implement classroom meditation practices; however, additional research is needed to determine how to best train faculty, what meditation techniques work best with students, and how to handle resistance. In this paper, a two-phase study is presented that involves a mindfulness meditation intervention with 180 undergraduate students at a private college in the southeastern United States. Data were collected through qualitative surveys and journaling and analyzed for themes. Findings included a majority of students reporting improved calm, reduced stress, and increased focus and ability to transition to classroom instruction.

Keywords: college students, higher education, mindfulness meditation, stress

Procedia PDF Downloads 46
8609 Generalized Extreme Value Regression with Binary Dependent Variable: An Application for Predicting Meteorological Drought Probabilities

Authors: Retius Chifurira

Abstract:

Logistic regression model is the most used regression model to predict meteorological drought probabilities. When the dependent variable is extreme, the logistic model fails to adequately capture drought probabilities. In order to adequately predict drought probabilities, we use the generalized linear model (GLM) with the quantile function of the generalized extreme value distribution (GEVD) as the link function. The method maximum likelihood estimation is used to estimate the parameters of the generalized extreme value (GEV) regression model. We compare the performance of the logistic and the GEV regression models in predicting drought probabilities for Zimbabwe. The performance of the regression models are assessed using the goodness-of-fit tests, namely; relative root mean square error (RRMSE) and relative mean absolute error (RMAE). Results show that the GEV regression model performs better than the logistic model, thereby providing a good alternative candidate for predicting drought probabilities. This paper provides the first application of GLM derived from extreme value theory to predict drought probabilities for a drought-prone country such as Zimbabwe.

Keywords: generalized extreme value distribution, general linear model, mean annual rainfall, meteorological drought probabilities

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8608 Fuzzy Multi-Criteria Decision-Making Based on Ignatian Discernment Process

Authors: Pathinathan Theresanathan, Ajay Minj

Abstract:

Ignatian Discernment Process (IDP) is an intense decision-making tool to decide on life-issues. Decisions are influenced by various factors outside of the decision maker and inclination within. This paper develops IDP in the context of Fuzzy Multi-criteria Decision Making (FMCDM) process. Extended VIKOR method is a decision-making method which encompasses even conflict situations and accommodates weightage to various issues. Various aspects of IDP, namely three ways of decision making and tactics of inner desires, are observed, analyzed and articulated within the frame work of fuzzy rules. The decision-making situations are broadly categorized into two types. The issues outside of the decision maker influence the person. The inner feeling also plays vital role in coming to a conclusion. IDP integrates both the categories using Extended VIKOR method. Case studies are carried out and analyzed with FMCDM process. Finally, IDP is verified with an illustrative case study and results are interpreted. A confused person who could not come to a conclusion is able to take decision on a concrete way of life through IDP. The proposed IDP model recommends an integrated and committed approach to value-based decision making.

Keywords: AHP, FMCDM, IDP, ignatian discernment, MCDM, VIKOR

Procedia PDF Downloads 242
8607 Segmentation Using Multi-Thresholded Sobel Images: Application to the Separation of Stuck Pollen Grains

Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

Abstract:

Being able to identify biological particles such as spores, viruses, or pollens is important for health care professionals, as it allows for appropriate therapeutic management of patients. Optical microscopy is a technology widely used for the analysis of these types of microorganisms, because, compared to other types of microscopy, it is not expensive. The analysis of an optical microscope slide is a tedious and time-consuming task when done manually. However, using machine learning and computer vision, this process can be automated. The first step of an automated microscope slide image analysis process is segmentation. During this step, the biological particles are localized and extracted. Very often, the use of an automatic thresholding method is sufficient to locate and extract the particles. However, in some cases, the particles are not extracted individually because they are stuck to other biological elements. In this paper, we propose a stuck particles separation method based on the use of the Sobel operator and thresholding. We illustrate it by applying it to the separation of 813 images of adjacent pollen grains. The method correctly separated 95.4% of these images.

Keywords: image segmentation, stuck particles separation, Sobel operator, thresholding

Procedia PDF Downloads 118
8606 Computational Fluid Dynamics Simulations of Thermal and Flow Fields inside a Desktop Personal Computer Cabin

Authors: Mohammad Salehi, Mohammad Erfan Doraki

Abstract:

In this paper, airflow analysis inside a desktop computer case is performed by simulating computational fluid dynamics. The purpose is to investigate the cooling process of the central processing unit (CPU) with thermal capacities of 80 and 130 watts. The airflow inside the computer enclosure, selected from the microATX model, consists of the main components of heat production such as CPU, hard disk drive, CD drive, floppy drive, memory card and power supply unit; According to the amount of thermal power produced by the CPU with 80 and 130 watts of power, two different geometries have been used for a direct and radial heat sink. First, the independence of the computational mesh and the validation of the solution were performed, and after ensuring the correctness of the numerical solution, the results of the solution were analyzed. The simulation results showed that changes in CPU temperature and other components linearly increased with increasing CPU heat output. Also, the ambient air temperature has a significant effect on the maximum processor temperature.

Keywords: computational fluid dynamics, CPU cooling, computer case simulation, heat sink

Procedia PDF Downloads 107
8605 Deep Learning for Recommender System: Principles, Methods and Evaluation

Authors: Basiliyos Tilahun Betru, Charles Awono Onana, Bernabe Batchakui

Abstract:

Recommender systems have become increasingly popular in recent years, and are utilized in numerous areas. Nowadays many web services provide several information for users and recommender systems have been developed as critical element of these web applications to predict choice of preference and provide significant recommendations. With the help of the advantage of deep learning in modeling different types of data and due to the dynamic change of user preference, building a deep model can better understand users demand and further improve quality of recommendation. In this paper, deep neural network models for recommender system are evaluated. Most of deep neural network models in recommender system focus on the classical collaborative filtering user-item setting. Deep learning models demonstrated high level features of complex data can be learned instead of using metadata which can significantly improve accuracy of recommendation. Even though deep learning poses a great impact in various areas, applying the model to a recommender system have not been fully exploited and still a lot of improvements can be done both in collaborative and content-based approach while considering different contextual factors.

Keywords: big data, decision making, deep learning, recommender system

Procedia PDF Downloads 458
8604 Role of Sodium Concentration, Waiting Time and Constituents’ Temperature on the Rheological Behavior of Alkali Activated Slag Concrete

Authors: Muhammet M. Erdem, Erdoğan Özbay, Ibrahim H. Durmuş, Mustafa Erdemir, Murat Bikçe, Müzeyyen Balçıkanlı

Abstract:

In this paper, rheological behavior of alkali activated slag concretes were investigated depending on the sodium concentration (SC), waiting time (WT) after production, and constituents’ temperature (CT) parameters. For this purpose, an experimental program was conducted with four different SCs of 1.85, 3.0, 4.15, and 5.30%, three different WT of 0 (just after production), 15, and 30 minutes and three different CT of 18, 30, and 40 °C. Solid precursors are activated by water glass and sodium hydroxide solutions with silicate modulus (Ms = SiO2/Na2O) of 1. Slag content and (water + activator solution)/slag ratio were kept constant in all mixtures. Yield stress and plastic viscosity values were defined for each mixture by using the ICAR rheometer. Test results were demonstrated that all of the three studied parameters have tremendous effect on the yield stress and plastic viscosity values of the alkali activated slag concretes. Increasing the SC, WT, and CT drastically augmented the rheological parameters. At the 15 and 30 minutes WT after production, most of the alkali activated slag concretes were set instantaneously, and rheological measurements were not performed.

Keywords: alkali activation, slag, rheology, yield stress, plastic viscosity

Procedia PDF Downloads 276
8603 Sustainable Development Variables to Assess Transport Infrastructure in Remote Destinations

Authors: Dimitrios J. Dimitriou, Maria F. Sartzetaki

Abstract:

The assessment variables of the accessibility and the sustainability of access infrastructure for remote regions may vary significant by location and a wide range of factors may affect the decision process. In this paper, the environmental disturbance implications of transportation system to key demand and supply variables impact the economic system in remote destination are descripted. According to a systemic approach, the key sustainability variables deals with decision making process that have to be included in strategic plan for the critical transport infrastructure development and their relationship to regional socioeconomic system are presented. The application deals with the development of railway in remote destinations, where the traditional CBA not include the external cost generated by the environmental impacts that may have a range of diverse impacts on transport infrastructure and services. The analysis output provides key messages to decision and policy makers towards sustainable development of transport infrastructure, especially for remote destinations where accessibility is a key factor of regional economic development and social stability. The key conclusion could be essential useful for relevant applications in remote regions in the same latitude.

Keywords: sustainable development in remote regions, transport infrastructure, strategic planning, sustainability variables

Procedia PDF Downloads 334
8602 Estimation of Population Mean Using Characteristics of Poisson Distribution: An Application to Earthquake Data

Authors: Prayas Sharma

Abstract:

This paper proposed a generalized class of estimators, an exponential class of estimators based on the adaption of Sharma and Singh (2015) and Solanki and Singh (2013), and a simple difference estimator for estimating unknown population mean in the case of Poisson distributed population in simple random sampling without replacement. The expressions for mean square errors of the proposed classes of estimators are derived from the first order of approximation. It is shown that the adapted version of Solanki and Singh (2013), the exponential class of estimator, is always more efficient than the usual estimator, ratio, product, exponential ratio, and exponential product type estimators and equally efficient to simple difference estimator. Moreover, the adapted version of Sharma and Singh's (2015) estimator is always more efficient than all the estimators available in the literature. In addition, theoretical findings are supported by an empirical study to show the superiority of the constructed estimators over others with an application to earthquake data of Turkey.

Keywords: auxiliary attribute, point bi-serial, mean square error, simple random sampling, Poisson distribution

Procedia PDF Downloads 138
8601 The Impact of Board Structure to the Roles of Board of Commissioners in Implementing Good Corporate Governance at Indonesian State-Owned Enterprises

Authors: Synthia Atas Sari, Engkos Achmad Kuncoro, Haryadi Sarjono

Abstract:

The purpose of this paper is to examine the impact of reward system which is determined by government over the work of Board of Commissioners in implementing good corporate governance in Indonesian state-owned enterprises. To do so, this study analyses the adequacy of the remuneration, the job attractiveness, and the board commitment and dedication with the remuneration system. Qualitative method used to examine the significant features and challenges to the government policy over the remuneration determination for the board of commissioners to their roles. Data are gathered through semi-structure in-depth interview to the 21 participants over 10 Indonesian stated-owned enterprises and written documents. Findings in this study indicate that government policies over the remuneration system is not effective to increase the performance of board of commissioners in implementing good corporate governance in Indonesian state-owned enterprises due to unattractiveness of the remuneration amount, demotivate active members, and conflict interest over members of the remuneration committee.

Keywords: reward system, board of commissioners, state-owned enterprises, good corporate governance

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8600 Solving the Wireless Mesh Network Design Problem Using Genetic Algorithm and Simulated Annealing Optimization Methods

Authors: Moheb R. Girgis, Tarek M. Mahmoud, Bahgat A. Abdullatif, Ahmed M. Rabie

Abstract:

Mesh clients, mesh routers and gateways are components of Wireless Mesh Network (WMN). In WMN, gateways connect to Internet using wireline links and supply Internet access services for users. We usually need multiple gateways, which takes time and costs a lot of money set up, due to the limited wireless channel bit rate. WMN is a highly developed technology that offers to end users a wireless broadband access. It offers a high degree of flexibility contrasted to conventional networks; however, this attribute comes at the expense of a more complex construction. Therefore, a challenge is the planning and optimization of WMNs. In this paper, we concentrate on this challenge using a genetic algorithm and simulated annealing. The genetic algorithm and simulated annealing enable searching for a low-cost WMN configuration with constraints and determine the number of used gateways. Experimental results proved that the performance of the genetic algorithm and simulated annealing in minimizing WMN network costs while satisfying quality of service. The proposed models are presented to significantly outperform the existing solutions.

Keywords: wireless mesh networks, genetic algorithms, simulated annealing, topology design

Procedia PDF Downloads 442
8599 Study of Effect of Gear Tooth Accuracy on Transmission Mount Vibration

Authors: Kalyan Deepak Kolla, Ketan Paua, Rajkumar Bhagate

Abstract:

Transmission dynamics occupy major role in customer perception of the product in both senses of touch and quality of sound. The quantity and quality of sound perceived is more concerned with the whine noise of the gears engaged. Whine noise is tonal in nature and tonal noises cause fatigue and irritation to customers, which in turn affect the quality of the product. Transmission error is the usual suspect for whine noise, which can be caused due to misalignments, tolerances, manufacturing variabilities. In-cabin noise is also more sensitive to the gear design. As the details of the gear tooth design and manufacturing are in microns, anything out of the tolerance zone, either in design or manufacturing, will cause a whine noise. This will also cause high variation in stress and deformation due to change in the load and leads to the fatigue failure of the gears. Hence gear design and development take priority in the transmission development process. This paper aims to study such variability by considering five pairs of helical spur gears and their effect on the transmission error, contact pattern and vibration level on the transmission.

Keywords: gears, whine noise, manufacturing variability, mount vibration variability

Procedia PDF Downloads 138
8598 Design and Simulation High Sensitive MEMS Capacitive Pressure Sensor with Small Size for Glaucoma Treatment

Authors: Yadollah Hezarjaribi, Mahdie Yari Esboi

Abstract:

In this paper, a novel MEMS capacitive pressure sensor with small size and high sensitivity is presented. This sensor has the separated clamped square diaphragm and the movable plate. The diaphragm material is polysilicon. The movable and fixed plates and mechanical coupling are gold. The substrate and diaphragm are pyrex glass and polysilicon, respectively. In capacitive sensor the sensitivity is proportional to deflection and capacitance changes with pressure for this reason with this design is improved the capacitance and sensitivity with small size. This sensor is designed for low pressure between 0-60 mmHg that is used for medical application such as treatment of an incurable disease called glaucoma. The size of this sensor is 350×350 µm2 and the thickness of the diaphragm is 2µm with 1μ air gap. This structure is designed by intellisuite software. In this MEMS capacitive pressure sensor the sensor sensitivity, diaphragm mechanical sensitivity for polysilicon diaphragm are 0.0469Pf/mmHg, 0.011 μm/mmHg, respectively. According to the simulating results for low pressure, the structure with polysilicon diaphragm has more change of the displacement and capacitance, this leads to high sensitivity than other diaphragms.

Keywords: glaucoma, MEMS capacitive pressure sensor, square clamped diaphragm, polysilicon

Procedia PDF Downloads 297
8597 Slip Suppression Sliding Mode Control with Various Chattering Functions

Authors: Shun Horikoshi, Tohru Kawabe

Abstract:

This study presents performance analysis results of SMC (Sliding mode control) with changing the chattering functions applied to slip suppression problem of electric vehicles (EVs). In SMC, chattering phenomenon always occurs through high frequency switching of the control inputs. It is undesirable phenomenon and degrade the control performance, since it causes the oscillations of the control inputs. Several studies have been conducted on this problem by introducing some general saturation function. However, study about whether saturation function was really best and the performance analysis when using the other functions, weren’t being done so much. Therefore, in this paper, several candidate functions for SMC are selected and control performance of candidate functions is analyzed. In the analysis, evaluation function based on the trade-off between slip suppression performance and chattering reduction performance is proposed. The analyses are conducted in several numerical simulations of slip suppression problem of EVs. Then, we can see that there is no difference of employed candidate functions in chattering reduction performance. On the other hand, in slip suppression performance, the saturation function is excellent overall. So, we conclude the saturation function is most suitable for slip suppression sliding mode control.

Keywords: sliding mode control, chattering function, electric vehicle, slip suppression, performance analysis

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8596 Collaboration and Automatic Tutoring as a Learning Strategy: A Case Study in Programming Courses

Authors: Luis H. Gonzalez-Guerra, Armandina J. Leal-Flores

Abstract:

Students attending classrooms nowadays are habituated to use digital devices all the time and for multiple things. They have been familiar with digital technology throughout their lives so they have developed skills that should be naturally adopted as part of their study strategies. New learning styles require taking in consideration the use of models that support and promote student motivation for learning and development of their creative thinking skills. To achieve student learning in programming courses, different strategies are used. One of them is a collaboration between students, which is a tool which faculty can take advantage of when teaching these kinds of courses. Moreover, cooperation is an essential skill that society should reinforce in order to promote a healthy social environment and cohabitation. Nevertheless, students will still require support and advice to get a complete and correct programming solution to successfully address and solve the problems given throughout the course. This paper present a model where collaboration between students is associated with an automatic tutoring platform providing an excellent approach for the individual learning in collaborative activities in programming courses, and also motivates students to increase their knowledge regarding the topics covered in the classroom.

Keywords: automatic tutoring, collaboration learning, creative thinking, motivation

Procedia PDF Downloads 254
8595 Neural Network Analysis Applied to Risk Prediction of Early Neonatal Death

Authors: Amanda R. R. Oliveira, Caio F. F. C. Cunha, Juan C. L. Junior, Amorim H. P. Junior

Abstract:

Children deaths are traumatic events that most often can be prevented. The technology of prevention and intervention in cases of infant deaths is available at low cost and with solid evidence and favorable results, however, with low access cover. Weight is one of the main factors related to death in the neonatal period, so the newborns of low birth weight are a population at high risk of death in the neonatal period, especially early neonatal period. This paper describes the development of a model based in neural network analysis to predict the mortality risk rating in the early neonatal period for newborns of low birth weight to identify the individuals of this population with increased risk of death. The neural network applied was trained with a set of newborns data obtained from Brazilian health system. The resulting network presented great success rate in identifying newborns with high chances of death, which demonstrates the potential for using this tool in an integrated manner to the health system, in order to direct specific actions for improving prognosis of newborns.

Keywords: low birth weight, neonatal death risk, neural network, newborn

Procedia PDF Downloads 436
8594 The Politics of Renewable Energy Generation and Its Challenges: A Case Study of Iran

Authors: Naresh Kumar Verma

Abstract:

Nuclear energy being adapted as a renewable energy source and its production by developing countries has turned into a major strategic concern and politics by the developed world. The West seem to be the sole proprietor of such energy source and any country opting for such energy production either face significant hurdles or geopolitical challenges in developing such energy source. History of West Asia is full of interference by external powers which has been integral in the incessant conflict in the region. Whether it was the creation of Israel, the Gulf war of 1991, or the invasion of Iraq in 2003, and more recently the Iranian nuclear conundrum, the soil of West Asia has always been a witness to the play of extra regional powers game. Iran, being a theocratic state has been facing such threats and challenges, regarding its intentions and its capability in such energy production. The paper will try to assess the following issues: -Politics of Renewable Energy Generation. -Geographical and strategic significance of Iran’s nuclear programme. -Challenges in the path of Iran developing nuclear energy as a RE source. -The interests of the regional and extra-regional actors in challenging Iranian Nuclear Programme.

Keywords: developing countries, geopolitics, Iran, nuclear energy, renewable energy

Procedia PDF Downloads 619
8593 Application of Flexi-Wall in Noise Barriers Renewal

Authors: B. Daee, H. M. El Naggar

Abstract:

This paper presents an experimental study on structural performance of an innovative noise barrier consisting of poly-block, light polyurethane foam (LPF) and polyurea. This wall system (flexi-wall) is intended to be employed as a vertical extension to existing sound barriers in an accelerated construction method. To aid in the wall design, several mechanical tests were conducted on LPF specimens and two full-scale walls were then fabricated employing the same LPF material. The full-scale walls were subjected to lateral loading in order to establish their lateral resistance. A cyclic fatigue test was also performed on a full-scale flexi-wall in order to evaluate the performance of the wall under a repetitive loading condition. The result of the experiments indicated the suitability of flexi-wall in accelerated construction and confirmed that the structural performance of the wall system under lateral loading is satisfactory for the sound barrier application. The experimental results were discussed and a preliminary design procedure for application of flexi-wall in sound barrier applications was also developed.

Keywords: noise barrier, polyurethane foam, accelerated construction, full-scale experiment

Procedia PDF Downloads 281