Search results for: random deviation

Authors: Edlira Donefski, Lorenc Ekonomi, Tina Donefski

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Edgeworth approximation is one of the most important statistical methods that has a considered contribution in the reduction of the sum of standard deviation of the independent variables’ coefficients in a Quantile Regression Model. This model estimates the conditional median or other quantiles. In this paper, we have applied approximating statistical methods in an economical problem. We have created and generated a quantile regression model to see how the profit gained is connected with the realized sales of the cosmetic products in a real data, taken from a local business. The Linear Regression of the generated profit and the realized sales was not free of autocorrelation and heteroscedasticity, so this is the reason that we have used this model instead of Linear Regression. Our aim is to analyze in more details the relation between the variables taken into study: the profit and the finalized sales and how to minimize the standard errors of the independent variable involved in this study, the level of realized sales. The statistical methods that we have applied in our work are Edgeworth Approximation for Independent and Identical distributed (IID) cases, Bootstrap version of the Model and the Edgeworth approximation for Bootstrap Quantile Regression Model. The graphics and the results that we have presented here identify the best approximating model of our study.

Keywords: bootstrap, edgeworth approximation, IID, quantile

Procedia PDF Downloads 159

Authors: Hameed Olalekan Bolaji

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The digital natives are driving the trends of literacy in the use of electronic devices for learning purposes. This has reconfigured the context of learning in the exploration of knowledge in a social learning environment. This study explores the impact of Ubiquitous Collaborative Mobile Learning (UCML) instructional design model in a quantitative designed-based research approach. The UCML model was a synergetic blend of four models that are relevant to the design of instructional content for a social learning environment. The UCML model serves as the treatment and instructions were transmitted via mobile device based on the principle of ‘bring your own device’ (BYOD) to promote social learning. Three research questions and two hypotheses were raised to guide the conduct of this study. A researcher-designed questionnaire was used to collate data and the it was subjected to reliability of Cronbach Alpha which yielded 0.91. Descriptive statistics of mean and standard deviation were used to answer research questions while inferential statistics of independent sample t-test was used to analyze the hypotheses. The findings reveal that the UCML model was adequately evolved and it promotes social learning its design principles through the use of mobile devices.

Keywords: collaboration, mobile device, social learning, ubiquitous

Procedia PDF Downloads 157

Authors: Mobina Bagherianlemraski, Parastoo Namdar

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Background: The ongoing coronavirus disease has affected most countries. This virus has high transmission power. Due to the closure of most dental clinics, millions of orthodontic patients missed their appointments during the COVID-19 pandemic. Methods: A questionnaire was developed and sent to patients receiving orthodontic treatment at a public or private clinic. Results: A total of 200 responses were analyzed: These included 153 women (76.5%) and 47 men (23.5%). The mean and standard deviation of their age was 18.92±7.23 years, with an age range of 8 to 40 years. One hundred eighty-nine patients (94.5%) had fixed appliances, and 11 patients (5.5%) had removable appliances. Of all participants, 35% (70) missed their appointments. The highest and lowest reasons for stopping appointments were concerned about the spread of COVID-19 with 28 cases (40%) and the closure of the clinic with 15 cases (21.4%). Of the 53 patients who contacted their orthodontists, 86.8 % (46) communicated via office phone and 5.7% (3) through social media. Conclusion: This study determined that the coronavirus pandemic and quarantine have had an important impact on orthodontic treatments. The greatest concern of orthodontic patients was increasing in treatment duration. Patients who used fixed appliances reported missing dental appointments more than others. Therefore, during COVID 19 Pandemic, orthodontists should prepare patients to solve their problems linked to orthodontic appliances when possible.

Keywords: orthodontic patients, coronavirus pandemic, appointments, COVID-19

Procedia PDF Downloads 138

Authors: Priscilla Eng Lian Murphy

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This study examines the nature of student conceptions of mathematics in higher education using quantitative research methods. This study validates the Short Form of Conception of Mathematics survey as well as reveals the epistemological nature of student conceptions of mathematics. Using a random sample of mathematics students in Australia and New Zealand (N=274), this paper highlighted three key findings, of relevance to lecturers in higher education. Firstly, descriptive data shows that mathematics students in Australia and New Zealand reported that mathematics is about numbers and components, models and life. Secondly, models conceptions of mathematics predicted strong examination performances using regression analyses; and thirdly, there is a positive correlation between high mathematics examination scores and cohesive conceptions of mathematics.

Keywords: higher education, learning mathematics, mathematics performances, student conceptions of mathematics

Procedia PDF Downloads 264

Authors: Saghir Ahmad, Abid Hussain Ch, Misbah Malik, Ayesha Batool

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Terrorism is the marvel in which dreadful circumstance is made by a gathering of individuals who view themselves as abused by society. Terrorism is the unlawful utilization of power or viciousness by a man or a sorted out gathering by the general population or property with the aim of intimidation or compulsion of social orders or governments frequently for ideological or political reasons. Terrorism is as old as people. The main aim of the study was to find out the causes of terrorism through the perceptions of the universities students of teacher training institutions. This study was quantitative in nature. Survey method was used to collect data. A sample of two hundred and sixty seven students was selected from public universities. A five point Likert scale was used to collect data. Mean, Standard deviation, independent sample t-test, and One Way ANOVA were applied to analyze the data. The major findings of the study indicated that students perceived the main causes of terrorism are poverty, foreign interference, wrong concept of Islamization, and social injustice. It is also concluded that mostly, students think that drone attacks are promoting the terrorist activities. The education is key to eliminate the terrorism. There is need to educate the people and specially youngsters to bring the peace in the world.

Keywords: dreadful circumstance, governments, power, students, terrorism

Procedia PDF Downloads 548

Authors: Larry Hawkins, Scott K. Sakakura, Michael J. Salopek

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The Marshall Space Flight Center is designing and building a next-generation CO₂ removal system, the Four Bed Carbon Dioxide Scrubber (4BCO₂), which will use the International Space Station (ISS) as a testbed. The current ISS CO2 removal system has faced many challenges in both performance and reliability. Given that CO2 removal is an integral Environmental Control and Life Support System (ECLSS) subsystem, the 4BCO2 Scrubber has been designed to eliminate the shortfalls identified in the current ISS system. One of the key required upgrades was to improve the performance and reliability of the blower that provides the airflow through the CO₂ sorbent beds. A magnetically levitated blower, capable of higher airflow and pressure than the previous system, was developed to meet this need. The design and qualification testing of this next-generation blower are described here. The new blower features a high-efficiency permanent magnet motor, a five-axis, active magnetic bearing system, and a compact controller containing both a variable speed drive and a magnetic bearing controller. The blower uses a centrifugal impeller to pull air from the inlet port and drive it through an annular space around the motor and magnetic bearing components to the exhaust port. Technical challenges of the blower and controller development include survival of the blower system under launch random vibration loads, operation in microgravity, packaging under strict size and weight requirements, and successful operation during 4BCO₂ operational changeovers. An ANSYS structural dynamic model of the controller was used to predict response to the NASA defined random vibration spectrum and drive minor design changes. The simulation results are compared to measurements from qualification testing the controller on a vibration table. Predicted blower performance is compared to flow loop testing measurements. Dynamic response of the system to valve changeovers is presented and discussed using high bandwidth measurements from dynamic pressure probes, magnetic bearing position sensors, and actuator coil currents. The results presented in the paper show that the blower controller will survive launch vibration levels, the blower flow meets the requirements, and the magnetic bearings have adequate load capacity and control bandwidth to maintain the desired rotor position during the valve changeover transients.

Keywords: blower, carbon dioxide removal, environmental control and life support system, magnetic bearing, permanent magnet motor, validation testing, vibration

Procedia PDF Downloads 136

Authors: Wen-Chung Wang, Xue-Lan Qiu

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Ipsative tests have been widely used in vocational and career counseling (e.g., the Jackson Vocational Interest Survey). Pairwise-comparison items are a typical item format of ipsative tests. When the two statements in a pairwise-comparison item measure two different constructs, the item is referred to as a multidimensional pairwise-comparison (MPC) item. A typical MPC item would be: Which activity do you prefer? (A) playing with young children, or (B) working with tools and machines. These two statements aim at the constructs of social interest and investigative interest, respectively. Recently, new item response theory (IRT) models for ipsative tests with MPC items have been developed. Among them, the Rasch ipsative model (RIM) deserves special attention because it has good measurement properties, in which the log-odds of preferring statement A to statement B are defined as a competition between two parts: the sum of a person’s latent trait to which statement A is measuring and statement A’s utility, and the sum of a person’s latent trait to which statement B is measuring and statement B’s utility. The RIM has been extended to polytomous responses, such as preferring statement A strongly, preferring statement A, preferring statement B, and preferring statement B strongly. To promote the new initiatives, in this study we developed computerized adaptive testing algorithms for MFC items and evaluated their performance using simulations and two real tests. Both the RIM and its polytomous extension are multidimensional, which calls for multidimensional computerized adaptive testing (MCAT). A particular issue in MCAT for MPC items is the within-person statement exposure (WPSE); that is, a respondent may keep seeing the same statement (e.g., my life is empty) for many times, which is certainly annoying. In this study, we implemented two methods to control the WPSE rate. In the first control method, items would be frozen when their statements had been administered more than a prespecified times. In the second control method, a random component was added to control the contribution of the information at different stages of MCAT. The second control method was found to outperform the first control method in our simulation studies. In addition, we investigated four item selection methods: (a) random selection (as a baseline), (b) maximum Fisher information method without WPSE control, (c) maximum Fisher information method with the first control method, and (d) maximum Fisher information method with the second control method. These four methods were applied to two real tests: one was a work survey with dichotomous MPC items and the other is a career interests survey with polytomous MPC items. There were three dependent variables: the bias and root mean square error across person measures, and measurement efficiency which was defined as the number of items needed to achieve the same degree of test reliability. Both applications indicated that the proposed MCAT algorithms were successful and there was no loss in measurement proficiency when the control methods were implemented, and among the four methods, the last method performed the best.

Keywords: computerized adaptive testing, ipsative tests, item response theory, pairwise comparison

Procedia PDF Downloads 246

Authors: Sara Mensou, Ahmed Essadki, Issam Minka, Tamou Nasser, Badr Bououlid Idrissi

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In this paper we present a contribution for the modeling and control of wind energy conversion system based on a Doubly Fed Induction Generator (DFIG). Since the wind speed is random the system has to produce an optimal electrical power to the Network and ensures important strength and stability. In this work, the Backstepping controller is used to control the generator via two converter witch placed a DC bus capacitor and connected to the grid by a Filter R-L, in order to optimize capture wind energy. All is simulated and presented under MATLAB/Simulink Software to show performance and robustness of the proposed controller.

Keywords: wind turbine, doubly fed induction generator, MPPT control, backstepping controller, power converter

Procedia PDF Downloads 189

Authors: Masahiro Takahashi, Kosuke Harada, Shihomi Nakao, Mitsuhiro Higashihata, Hiroshi Ikenoue, Daisuke Nakamura, Tatsuo Okada

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Zinc oxide (ZnO) is one of the light emitting materials in ultraviolet (UV) region. In addition, ZnO nanostructures are also attracting increasing research interest as building blocks for UV optoelectronic applications. We have succeeded in synthesizing vertically-aligned ZnO nanostructures by laser interference patterning, which is catalyst-free and non-contact technique. In this study, vertically-aligned ZnO nanowall arrays were synthesized using two-beam interference. The maximum height and average thickness of the ZnO nanowalls were about 4.5 µm and 200 nm, respectively. UV lasing from a piece of the ZnO nanowall was obtained under the third harmonic of a Q-switched Nd:YAG laser excitation, and the estimated threshold power density for lasing was about 150 kW/cm2. Furthermore, UV lasing from the vertically-aligned ZnO nanowall was also achieved. The results indicate that ZnO nanowalls can be applied to random laser.

Keywords: zinc oxide, nanowall, interference laser, UV lasing

Procedia PDF Downloads 504

Authors: Somtop Keawchuer

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This research aims to study (1) the relationship between competency-based learning and learning efficiency of new media communication students at Suan Sunandha University (2) the demographic factor effect on learning efficiency of students at Suan Sunandha University. This research method will use quantitative research; data was collected by questionnaires distributed to students from new media communication in management science faculty of Suan Sunandha Rajabhat University for 1340 sample by purposive sampling method. Data was analyzed by descriptive statistic including percentage, mean, standard deviation and inferential statistic including T-test, ANOVA and Pearson correlation for hypothesis testing. The results showed that the competency-based learning in term of ability to communicate, ability to think and solve the problem, life skills and ability to use technology has a significant relationship with learning efficiency in term of the cognitive domain, psychomotor domain and affective domain at the 0.05 level and which is in harmony with the research hypotheses.

Keywords: competency-based learning, learning efficiency, new media communication students, Suan Sunandha Rajabhat University

Procedia PDF Downloads 243

Authors: Seyeh Hassan Eftekhar Afzali, Hamid Mohammadi

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Pistachio is like almond but the second cycle of growth (third phase) has rather fast growth. This is caused to add final mass of product. When the germ grows, it and its cover are reached to the final size during six week period. As starting the second phase, the lignifications of pericarp is begun and continued for 4 or 6 weeks. Physiological maturity or easy separation of green from scutum is specified. This test was done according to random blocks of 6 orchards in the type of Ahmad Aghaie with 4 iterations. Vegetative properties of branch are investigated. The results of the bunch numbers on the growth of branch in current year are shown that the most growth of branch is happened by trimming of one and two bunches of the branch and the most diameter of the branch is happened by trimming of one to four bunches of branch. Trimming of a bunch is caused the most number of pistachio products in the bunch.

Keywords: pistachio, cluster, bud, fruit, branch

Procedia PDF Downloads 476

Authors: Bander Alzahrani, Mohammed Alreshoodi

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Information-centric networking (ICN) using architectures such as the Publish-Subscribe Internet Technology (PURSUIT) has been proposed as a new networking model that aims at replacing the current used end-centric networking model of the Internet. This emerged model focuses on what is being exchanged rather than which network entities are exchanging information, which gives the control plane functions such as routing and host location the ability to be specified according to the content items. The forwarding plane of the PURSUIT ICN architecture uses a simple and light mechanism based on Bloom filter technologies to forward the packets. Although this forwarding scheme solve many problems of the today’s Internet such as the growth of the routing table and the scalability issues, it is vulnerable to brute force attacks which are starting point to distributed- denial-of-service (DDoS) attacks. In this work, we design and analyze a novel source-routing and information delivery technique that keeps the simplicity of using Bloom filter-based forwarding while being able to deter different attacks such as denial of service attacks at the ingress of the network. To achieve this, special forwarding nodes called Edge-FW are directly attached to end user nodes and used to perform a security test for malicious injected random packets at the ingress of the path to prevent any possible attack brute force attacks at early stage. In this technique, a core entity of the PURSUIT ICN architecture called topology manager, that is responsible for finding shortest path and creating a forwarding identifiers (FId), uses a cryptographically secure hash function to create a 64-bit hash, h, over the formed FId for authentication purpose to be included in the packet. Our proposal restricts the attacker from injecting packets carrying random FIds with a high amount of filling factor ρ, by optimizing and reducing the maximum allowed filling factor ρm in the network. We optimize the FId to the minimum possible filling factor where ρ ≤ ρm, while it supports longer delivery trees, so the network scalability is not affected by the chosen ρm. With this scheme, the filling factor of any legitimate FId never exceeds the ρm while the filling factor of illegitimate FIds cannot exceed the chosen small value of ρm. Therefore, injecting a packet containing an FId with a large value of filling factor, to achieve higher attack probability, is not possible anymore. The preliminary analysis of this proposal indicates that with the designed scheme, the forwarding function can detect and prevent malicious activities such DDoS attacks at early stage and with very high probability.

Keywords: forwarding identifier, filling factor, information centric network, topology manager

Procedia PDF Downloads 154

Authors: Dominic Winston Kaku

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The academic performance of students is an area of great concern in education to the various stakeholders of education. This is because the academic performance of students is widely used as a measure of the success of the educational process. There are several factors, such as school-related factors, teachers related factors, pupils or students’ factors, and many others determining their academic performance. It appears that the management role of head teachers as a determining factor of pupils’ academic achievement is not much investigated. The management role of head teachers is an essential element in the educational process that has a huge influence on students’ academic performance. The aim of the research was to examine the management role of head teachers in improving the academic performance of students. The study employed a descriptive survey and was conducted among Junior High Schools in the Ellembelle District of the Western Region of Ghana. The respondents for the study were mainly all the head teachers, teachers, and some selected basic school pupils (JHS) in four-selected public basic schools in the Ellembelle district in the Western part of Ghana. A questionnaire was used to collect primary data from a sampling size of 252 persons, including 226 JHS pupils, all JHS teachers, and head teachers of all four selected schools. Descriptive statistics, specifically frequencies, percentages, pie charts, bar charts, means, and standard deviation, were used to analyse the data, and that formed the basis of the presentation of findings. The study discovered that planning academic activities, fostering relationships between the school and the community, supervising lessons, staff motivation, and punishing students who go wrong are some of the activities the head teachers participate in to help improve students’ academic performance. The academic performance of students is an area of great concern in education to the various stakeholders of education. This is because the academic performance of students is widely used as a measure of the success of the educational process. There are several factors, such as school-related factors, teachers related factors, pupils or students’ factors, and many others determining their academic performance. It appears that the management role of head teachers as a determining factor of pupils’ academic achievement is not much investigated. The management role of head teachers is an essential element in the educational process that has a huge influence on students’ academic performance. The aim of the research was to examine the management role of head teachers in improving the academic performance of students. The study employed a descriptive survey and was conducted among Junior High Schools in the Ellembelle District of the Western Region of Ghana. The respondents for the study were mainly all the head teachers, teachers, and some selected basic school pupils (JHS) in four-selected public basic schools in the Ellembelle district in the Western part of Ghana. A questionnaire was used to collect primary data from a sampling size of 252 persons, including 226 JHS pupils, all JHS teachers, and head teachers of all four selected schools. Descriptive statistics, specifically frequencies, percentages, pie charts, bar charts, means, and standard deviation, were used to analyse the data, and that formed the basis of the presentation of findings. The study discovered that planning academic activities, fostering relationships between the school and the community, supervising lessons, staff motivation, and punishing students who go wrong are some of the activities the head teachers participate in to help improve students’ academic performance.

Keywords: supervision, head teacher, academic performance, planning, motivation, relationships

Procedia PDF Downloads 64

Authors: Arpit Patil, Atharav Bhagwat, Rajas Bhope, Pramod Bide

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This research integrates IoT and ML to predict heart failure risks, utilizing the Framingham dataset. IoT devices gather real-time physiological data, focusing on heart rate dynamics, while ML, specifically Random Forest, predicts heart failure. Rigorous feature selection enhances accuracy, achieving over 90% prediction rate. This amalgamation marks a transformative step in proactive healthcare, highlighting early detection's critical role in cardiovascular risk mitigation. Challenges persist, necessitating continual refinement for improved predictive capabilities.

Keywords: cardiovascular diseases, internet of things, machine learning, cardiac risk assessment, heart failure prediction, early detection, cardio data analysis

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Authors: Rosilyn Sanders

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This qualitative study examined the impact of hiring people with intellectual disabilities (ID). The research questions were: What defines a disability? What accommodations are needed to ensure the success of a person with a disability? As a leader, what benefits do people with intellectual disabilities bring to the organization? What are the benefits of hiring people with intellectual disabilities in retail organizations? Moreover, how might people with intellectual disabilities contribute to the organizational culture of retail organizations? A narrative strength approach was used as a theoretical framework to guide the discussion and uncover the benefits of hiring individuals with intellectual disabilities in various retail organizations. Using qualitative interviews, the following themes emerged: diversity and inclusion, accommodations, organizational culture, motivation, and customer service. These findings put to rest some negative stereotypes and perceptions of persons with ID as being unemployable or unable to perform tasks when employed, showing instead that persons with ID can work efficiently when given necessary work accommodations and support in an enabling organizational culture. All participants were recruited and selected through various forms of electronic communication via social media, email invitations, and phone; this was conducted through the methodology of snowball sampling with the following demographics: age, ethnicity, gender, number of years in retail, number of years in management, and number of direct reports. The sample population was employed in several retail organizations throughout Arkansas and Texas. The small sample size for qualitative research in this study helped the researcher develop, build, and maintain close relationships that encouraged participants to be forthcoming and honest with information (Clow & James, 2014 ). Participants were screened to ensure they met the researcher's study; and screened to ensure that they were over 18 years of age. Participants were asked if they recruit, interview, hire, and supervise individuals with intellectual disabilities. Individuals were given consent forms via email to indicate their interest in participating in this study. Due to COVID-19, all interviews were conducted via teleconferencing (Zoom or Microsoft Teams) that lasted approximately 1 hour, which were transcribed, coded for themes, and grouped based on similar responses. Further, the participants were not privy to the interview questions beforehand, and demographic questions were asked at the end, including questions concerning age, education level, and job status. Each participant was assigned random numbers using an app called ‘The Random Number Generator ‘to ensure that all personal or identifying information of participants were removed. Regarding data storage, all documentation was stored on a password-protected external drive, inclusive of consent forms, recordings, transcripts, and researcher notes.

Keywords: diversity, positive psychology, organizational development, leadership

Procedia PDF Downloads 67

Authors: Majid Omidikhankahdani, Maryam Omidikhankahdani

Abstract:

Chabahar city located southeast of Iran and is one of strategic regional port in Oman sea aim of this study was measuring Chabahar city resident perceptions about tourism positive and negative effect. 322 participants selected via random sampling and fill questionnaire about their attitude toward tourism economic, social cultural and environment positive and negative impact. the result showed perspective of resident tourism have more positive effect than negative effect, also pair sample t test showed significant difference between positive and negative effect of tourism in favor positive effect.

Keywords: tourism economic effect, tourism environment, residents attitude, tourism social-cultural

Procedia PDF Downloads 496

Authors: Kriangkrai Vathanalaoha

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Misery generates fear and anxiety in readers through its intense plot associated with the unpredictable emotional states of the nurse, Annie Wilkes. At the same time, she mentally and physically abuses the novelist victim, Paul Sheldon. The suspense is not only at the story level, where the violent expressions are used but also at the discourse level, where the linguistic structures may intentionally cause the reader to view language as disturbing performative. This performativity could be reflected through linguistic choices where the writer triggers a new imaginative world through experiential metafunction and schema disruption. This study explores striking excerpts from the fiction through mind style and transitivity analysis to demonstrate how the horrific experience contrasts when the protagonist and the antagonist converse extensively. The results reveal that stylistic deviation can be found at the syntactic levels, where the intensity of emotions can be apparent when the protagonist is verbally abused. In addition, transitivity can flesh out how the protagonist is expressed chiefly through the internalized process, whereas the antagonist is eminent with the externalized process. The findings suggest that the application of cognitive stylistics, such as mind style and transitivity analysis, could contribute to the mental representation of horrific reality.

Keywords: horror, mind style, misery, stylistics, transitivity

Procedia PDF Downloads 141

Authors: Trikhun Rotkasem

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This research paper aimed to investigate hotel customers’ attitudes towards the service marketing, service behavior and perceived brand value. The focus of the study was on the Suan Sunandha Rajabhat University’s hotel. It is a small hotel which aims to provide service to mainly university’s guests. A simple random sampling technique was conducted to obtain a sample group that included 200 respondents. The research question was established as follows: What are customers’ attitudes towards the service marketing mix of hotel customers? The findings revealed the respondents’ attitudes towards the service marketing mix indicated high level in the area of product, place or distribution channel, people, and physical evidence, whereas, the respondents’ attitude towards the service marketing mix indicated medium level in the area of price, promotion, and process.

Keywords: marketing mix, perceived brand value, service behavior, hotel customers

Procedia PDF Downloads 442

Authors: Umar Farouk Abbas, Danjuma Mustapha, Hamisu Idi

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It is now a known fact that quality is an important issue in manufacturing industries. A control chart is an integrated and powerful tool in statistical process control (SPC). The mean µ and standard deviation σ parameters are estimated. In general, the multivariate exponentially weighted moving average (MEWMA) and multivariate cumulative sum (MCUSUM) are used in the detection of small shifts in joint monitoring of several correlated variables; the charts used information from past data which makes them sensitive to small shifts. The aim of the paper is to compare the performance of Shewhart xbar, MEWMA, and MCUSUM control charts in terms of their false rates when parameters are estimated with autocorrelation. A simulation was conducted in R software to generate the average run length (ARL) values of each of the charts. After the analysis, the results show that a comparison of the false alarm rates of the charts shows that MEWMA chart has lower false alarm rates than the MCUSUM chart at various levels of parameter estimated to the number of ARL0 (in control) values. Also noticed was that the sample size has an advert effect on the false alarm of the control charts.

Keywords: average run length, MCUSUM chart, MEWMA chart, false alarm rate, parameter estimation, simulation

Procedia PDF Downloads 222

Authors: M. Tarawneh

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This work is an experimental study on the heat transfer characteristics and pressure drop of different refrigerants during the condensation and evaporation processes in porous media. Four different refrigerants (R134a, R407C, 600a, R290), with different porosities were used to reach a real understanding of the actual heat transfer characteristics and pressure drop when using porous material inside the condenser and evaporator. Steel balls were used as porous media with different porosities (38%, 43%, 48%). The main goal of this project is to enhance the heat transfer coefficient during the condensation and evaporation processes when using different refrigerants and different porosities. Different correlations for the heat transfer coefficient and the pressure drop of the different refrigerants were developed. Also a generalized empirical correlation was developed for the different refrigerants. The experimental and predicted heat transfer coefficients and pressure drops were compared. It was found that, the Absolute standard deviation for the heat transfer coefficient and the pressure drop not exceeded values of 15% and 20%, respectively.

Keywords: condensation, evaporation, porous media, horizontal tubes, heat transfer coefficient, propane, butane

Procedia PDF Downloads 538

Authors: Lourdes I. Meriño, Viatcheslav Kafarov, Maria Gómez

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Fuel gas used in the burner receives as contributors other gases from different processes and this result in variability in the composition, which may cause an incomplete combustion. The burners are designed to operate in a certain curve, the calorific power dependent on the pressure and gas burners. When deviation of propane and C5+ is huge, there is a large release of energy, which causes it to work out the curves of the burners, because less pressure is required to force curve into operation. That increases the risk of explosion in an oven, besides of a higher environmental impact. There should be flame detection systems, and instrumentation equipment, such as local pressure gauges located at the entrance of the gas burners, to permit verification by the operator. Additionally, distributed control systems must be configured with different combustion instruments associated with respective alarms, as well as its operational windows, and windows control guidelines of integrity, leaving the design information of this equipment. Therefore, it is desirable to analyze when a plant is taken out of service and make good operational analysis to determine the impact of changes in fuel gas streams contributors, by varying the calorific power. Hence, poor combustion is one of the cause instability in the flame of the burner and having a great impact on process safety, the integrity of individuals and teams and environment.

Keywords: combustion process, fuel composition, safety, fuel gas

Procedia PDF Downloads 490

Authors: Ravija Gunawardana, Banuka Athuraliya

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Machine learning has emerged as a powerful tool for disease diagnosis and prediction. The use of machine learning algorithms has the potential to improve the accuracy of disease prediction, thereby enabling medical professionals to provide more effective and personalized treatments. This study focuses on developing a machine-learning model for disease prediction using symptoms and X-ray images. The importance of this study lies in its potential to assist medical professionals in accurately diagnosing diseases, thereby improving patient outcomes. Respiratory diseases are a significant cause of morbidity and mortality worldwide, and chest X-rays are commonly used in the diagnosis of these diseases. However, accurately interpreting X-ray images requires significant expertise and can be time-consuming, making it difficult to diagnose respiratory diseases in a timely manner. By incorporating machine learning algorithms, we can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The study utilized the Mask R-CNN algorithm, which is a state-of-the-art method for object detection and segmentation in images, to process chest X-ray images. The model was trained and tested on a large dataset of patient information, which included both symptom data and X-ray images. The performance of the model was evaluated using a range of metrics, including accuracy, precision, recall, and F1-score. The results showed that the model achieved an accuracy rate of over 90%, indicating that it was able to accurately detect and segment regions of interest in the X-ray images. In addition to X-ray images, the study also incorporated symptoms as input data for disease prediction. The study used three different classifiers, namely Random Forest, K-Nearest Neighbor and Support Vector Machine, to predict diseases based on symptoms. These classifiers were trained and tested using the same dataset of patient information as the X-ray model. The results showed promising accuracy rates for predicting diseases using symptoms, with the ensemble learning techniques significantly improving the accuracy of disease prediction. The study's findings indicate that the use of machine learning algorithms can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The model developed in this study has the potential to assist medical professionals in diagnosing respiratory diseases more accurately and efficiently. However, it is important to note that the accuracy of the model can be affected by several factors, including the quality of the X-ray images, the size of the dataset used for training, and the complexity of the disease being diagnosed. In conclusion, the study demonstrated the potential of machine learning algorithms for disease prediction using symptoms and X-ray images. The use of these algorithms can improve the accuracy of disease diagnosis, ultimately leading to better patient care. Further research is needed to validate the model's accuracy and effectiveness in a clinical setting and to expand its application to other diseases.

Keywords: K-nearest neighbor, mask R-CNN, random forest, support vector machine

Procedia PDF Downloads 156

Authors: G. Eom, H. Kim, A. Hwang, T. Kang, B. Kim

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Telomerase activity is overexpressed in over 85% of human cancers while suppressed in normal somatic cells. Telomerase has been attracted as a universal cancer biomarker. Therefore, the development of effective telomerase activity detection methods is urgently demanded in cancer diagnosis and therapy. Herein, we report a nanogap-rich Au nanowire (NW) surface-enhanced Raman scattering (SERS) sensor for detection of human telomerase activity. The nanogap-rich Au NW SERS sensors were prepared simply by uniformly depositing nanoparticles (NPs) on single-crystalline Au NWs. We measured SERS spectra of methylene blue (MB) from 60 different nanogap-rich Au NWs and obtained the relative standard deviation (RSD) of 4.80%, confirming the superb reproducibility of nanogap-rich Au NW SERS sensors. The nanogap-rich Au NW SERS sensors enable us to detect telomerase activity in 0.2 cancer cells/mL. Furthermore, telomerase activity is detectable in 7 different cancer cell lines whereas undetectable in normal cell lines, which suggest the potential applicability of nanogap-rich Au NW SERS sensor in cancer diagnosis. We expect that the present nanogap-rich Au NW SERS sensor can be useful in biomedical applications including a diverse biomarker sensing.

Keywords: cancer biomarker, nanowires, surface-enhanced Raman scattering, telomerase

Procedia PDF Downloads 349

Authors: Mohamed Barbary, Mohamed H. Abd El-Azeem

Abstract:

Maneuvering extended object tracking (M-EOT) using high-resolution inverse synthetic aperture radar (ISAR) observations has been gaining momentum recently. This work presents a new robust implementation of the multiple models (MM) multi-Bernoulli (MB) filter for M-EOT, where the M-EOT’s ISAR observations are characterized using a skewed (SK) non-symmetrically normal distribution. To cope with the possible abrupt change of kinematic state, extension, and observation distribution over an extended object when a target maneuvers, a multiple model technique is represented based on MB-track-before-detect (TBD) filter supported by SK-sub-random matrix model (RMM) or sub-ellipses framework. Simulation results demonstrate this remarkable impact.

Keywords: maneuvering extended objects, ISAR, skewed normal distribution, sub-RMM, MM-MB-TBD filter

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Authors: Suresh Palla

Abstract:

This research paper presents the results of the study on the estimation of fly ash, slag and cement contents in blended and composite cements by novel selective dissolution method. Types of cement samples investigated include OPC with fly ash as performance improver, OPC with slag as performance improver, PPC, PSC and Composite cement confirming to respective Indian Standards. Slag and OPC contents in PSC were estimated by selectively dissolving OPC in stage 1 and selectively dissolving slag in stage 2. In the case of composite cement sample, the percentage of cement, slag and fly ash were estimated systematically by selective dissolution of cement, slag and fly ash in three stages. In the first stage, cement dissolved and separated by leaving the residue of slag and fly ash, designated as R1. The second stage involves gravimetric estimation of fractions of OPC, residue and selective dissolution of fly ash and slag contents. Fly ash content, R2 was estimated through gravimetric analysis. Thereafter, the difference between the R1 and R2 is considered as slag content. The obtained results of cement, fly ash and slag using selective dissolution method showed 10% of standard deviation with the corresponding percentage of respective constituents. The results suggest that this novel selective dissolution method can be successfully used for estimation of OPC and SCMs contents in different types of cements.

Keywords: selective dissolution method , fly ash, ggbfs slag, edta

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Authors: Yadchol Tawetanawanich

Abstract:

Depression of elderly is a mental health problem that impacts tremendously on the elderly themselves, their family, and society. the purposes of this descriptive research were to examine prevalence rate of elderly depression and to study factors related to depression in elderly including 1) individual factors: sex, education, marital status, 2) economic factors: occupation, adequate income 3) health factors: chronic illnesses , disability, 4) social factors: family relationship, community relationship, 5) knowledge of depression, and 6) self-care behavior. The subject in this study included 273 elderly in Ladboakao sub-district, Banpong district, Ratchaburi province, Thailand. Data were collected through questionnaires and were analyzed using percentage, mean, standard deviation, chi-square, and one-way ANOVA. The results of the study revealed that: The prevalence rate of elderly depression were 21.61%, factors included economic factors, health factors, knowledge about depression, and self-care behavior were statistically significant positively related to depression of elderly (p<0.05), but individual factors and social factors were not significantly related to depression. It is also important for nurses to assess factors related to depression of the elderly in order to develop the model of care and use self-care strategies to contribute the positive outcomes.

Keywords: associated factors, depression, elderly, self-care

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Authors: Nieves M. C. Talavera-Prieto, Abel G. M. Ferreira, António T. G. Portugal, Rui J. Moreira, Jaime B. Santos

Abstract:

The knowledge of biodiesel density over large ranges of temperature and pressure is important for predicting the behavior of fuel injection and combustion systems in diesel engines, and for the optimization of such systems. In this study, cottonseed oil was transesterified into biodiesel and its density was measured at temperatures between 288 K and 358 K and pressures between 0.1 MPa and 30 MPa, with expanded uncertainty estimated as ±1.6 kg.m^-3. Experimental pressure-volume-temperature (pVT) cottonseed data was used along with literature data relative to other 18 biodiesels, in order to build a database used to test the correlation of density with temperarure and pressure using the Goharshadi–Morsali–Abbaspour equation of state (GMA EoS). To our knowledge, this is the first that density measurements are presented for cottonseed biodiesel under such high pressures, and the GMA EoS used to model biodiesel density. The new tested EoS allowed correlations within 0.2 kg•m-3 corresponding to average relative deviations within 0.02%. The built database was used to develop and test a new full predictive model derived from the observed linear relation between density and degree of unsaturation (DU), which depended from biodiesel FAMEs profile. The average density deviation of this method was only about 3 kg.m-3 within the temperature and pressure limits of application. These results represent appreciable improvements in the context of density prediction at high pressure when compared with other equations of state.

Keywords: biodiesel density, correlation, equation of state, prediction

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Authors: Muhammad Maisam Abbas, Salman Tariq, Usama Riaz, Muhammad Tanveer, Humaira Abdul Ghafoor

Abstract:

Autism Spectrum Disorder (ASD) refers to a developmental disorder that impairs an individual's communication and interaction ability. Individuals feel difficult to read facial expressions while communicating or interacting. Facial Expression Recognition (FER) is a unique method of classifying basic human expressions, i.e., happiness, fear, surprise, sadness, disgust, neutral, and anger through static and dynamic sources. This paper conducts a comprehensive comparison and proposed optimal method for a continued research project—a system that can assist people who have Autism Spectrum Disorder (ASD) in recognizing facial expressions. Comparison has been conducted on three supervised learning algorithms EigenFace, FisherFace, and LBPH. The JAFFE, CK+, and TFEID (I&II) datasets have been used to train and test the algorithms. The results were then evaluated based on variance, standard deviation, and accuracy. The experiments showed that FisherFace has the highest accuracy for all datasets and is considered the best algorithm to be implemented in our system.

Keywords: autism spectrum disorder, ASD, EigenFace, facial expression recognition, FisherFace, local binary pattern histogram, LBPH

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Authors: Omar Dib, Alexandre Caminada, Marie-Ange Manier

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The purpose of this study is to introduce a novel approach to solve the one-to-one shortest path problem. A directed connected graph is assumed in which all edges’ weights are positive. Our method is based on a memetic algorithm in which we combine a genetic algorithm (GA) and a variable neighborhood search method (VNS). We compare our approximate method with two exact algorithms Dijkstra and Integer Programming (IP). We made experimentations using random generated, complete and real graph instances. In most case studies, numerical results show that our method outperforms exact methods with 5% average gap to the optimality. Our algorithm’s average speed is 20-times faster than Dijkstra and more than 1000-times compared to IP. The details of the experimental results are also discussed and presented in the paper.

Keywords: shortest path problem, Dijkstra’s algorithm, integer programming, memetic algorithm

Procedia PDF Downloads 467

Authors: Huma Khan, Faiza Akhtar

Abstract:

The present study investigates the effects of burnout toward job performance and job satisfaction with the moderating role of hope and self-efficacy. Findings from 310 frontline employees of Pakistani commercial banks (Lahore, Karachi & Islamabad) disclosed burnout has negative significant effects on job performance and job satisfaction. Simple random sampling technique was used to collect data and inferential statistics were applied to analyzed the data. However, results disclosed no moderation effect of hope on burnout, job performance or with job satisfaction. Moreover, Data significantly supported the moderation effect of self-efficacy. Study further shed light on the development of psychological capital. Importance of the implication of the current finding is discussed.

Keywords: burnout, hope, job performance, job satisfaction, psychological capital, self-efficacy

Procedia PDF Downloads 142