Search results for: random copolymers
1562 The Study of Effect the Number of Cluster in the Branch on Vegetative Characteristics of Pistacia vera
Authors: Seyeh Hassan Eftekhar Afzali, Hamid Mohammadi
Abstract:
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 4681561 Secure Optimized Ingress Filtering in Future Internet Communication
Authors: Bander Alzahrani, Mohammed Alreshoodi
Abstract:
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 1421560 Exploring the Benefits of Hiring Individuals with Disabilities in the Workplace
Authors: Rosilyn Sanders
Abstract:
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 501559 Study of Residents' Perception of Tourism: The Case Study of Chabahar City, Iran
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 4881558 Hotel Customers’ Attitudes towards Service Marketing Mix, Service Behavior, and Perceived Brand Value
Authors: Trikhun Rotkasem
Abstract:
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 4291557 Machine Learning for Disease Prediction Using Symptoms and X-Ray Images
Authors: Ravija Gunawardana, Banuka Athuraliya
Abstract:
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 1301556 Improved Imaging and Tracking Algorithm for Maneuvering Extended UAVs Using High-Resolution ISAR Radar System
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
Procedia PDF Downloads 691555 Memetic Algorithm for Solving the One-To-One Shortest Path Problem
Authors: Omar Dib, Alexandre Caminada, Marie-Ange Manier
Abstract:
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 4611554 Impact of Job Burnout on Job Satisfaction and Job Performance of Front Line Employees in Bank: Moderating Role of Hope and Self-Efficacy
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 1311553 Socio-Demographic, Cause, and Benefit of Internal and International Migration: A Case Study of Mazar-i-Sharif, Balkh Province, Afghanistan
Authors: Baqir Khawari
Abstract:
Migration has a long history in Afghanistan even before, but it has been exacerbated in the last decade. Using actual household data of 1060 in Mazar-i-Sharif, the capital of Balkh province, obtained from a strictly random process, the study examined to evaluate the main causes and benefits of the migration. It is found that the main reasons for internal migration are unemployment and income inequality, in addition to war and poverty as international parameters for migration. Furthermore, the study demonstrated that households receive benefits from their migrants through remittances to increase their income and smooth consumption. Thus, the study suggests that to manage migration in Afghanistan, the government and international organizations should work together for peace and reduction of poverty in Afghanistan otherwise, the crisis of migration will continue in the future as well.Keywords: migration, remittances, socio-demographic, household, Afghanistan
Procedia PDF Downloads 621552 Labor Productivity in the Construction Industry: Factors Influencing the Spanish Construction Labor Productivity
Authors: G. Robles, A. Stifi, José L. Ponz-Tienda, S. Gentes
Abstract:
This research paper aims to identify, analyze and rank factors affecting labor productivity in Spain with respect to their relative importance. Using a selected set of 35 factors, a structured questionnaire survey was utilized as the method to collect data from companies. Target population is comprised by a random representative sample of practitioners related with the Spanish construction industry. Findings reveal the top five ranked factors are as follows: (1) shortage or late supply of materials; (2) clarity of the drawings and project documents; (3) clear and daily task assignment; (4) tools or equipment shortages; (5) level of skill and experience of laborers. Additionally, this research also pretends to provide simple and comprehensive recommendations so that they could be implemented by construction managers for an effective management of construction labor forces.Keywords: construction management, factors, improvement, labor productivity, lean construction
Procedia PDF Downloads 2841551 Butterfly Diversity along Urban-Rural Gradient in Kolkata, India
Authors: Sushmita Chaudhuri, Parthiba Basu
Abstract:
Urbanization leads to habitat degradation and is responsible for the fast disappearance of native butterfly species. Random sampling of rural, suburban and urban sites in an around Kolkata metropolis revealed the presence of 28 species of butterfly belonging to 5 different families in winter (February-March). Butterfly diversity, species richness and abundance decreased with increase in urbanization. Psyche (Leptosia nina of family Pieridae) was the most predominant butterfly species found everywhere in Kolkata during the winter period. The most dominant family was Nymphalidae (11species), followed by Pieridae (6 species), Lycaenidae (5 species), Papilionidae (4 species) and Hesperiidae (2 species). The rural and suburban sites had butterfly species that were unique to those sites. Vegetation cover and flowering shrub density were significantly related to butterfly diversity.Keywords: butterfly, Kolkata metropolis, Shannon-Weiner diversity index, species diversity
Procedia PDF Downloads 2841550 Optimization of HfO₂ Deposition of Cu Electrode-Based RRAM Device
Authors: Min-Hao Wang, Shih-Chih Chen
Abstract:
Recently, the merits such as simple structure, low power consumption, and compatibility with complementary metal oxide semiconductor (CMOS) process give an advantage of resistive random access memory (RRAM) as a promising candidate for the next generation memory, hafnium dioxide (HfO2) has been widely studied as an oxide layer material, but the use of copper (Cu) as both top and bottom electrodes has rarely been studied. In this study, radio frequency sputtering was used to deposit the intermediate layer HfO₂, and electron beam evaporation was used. For the upper and lower electrodes (cu), using different AR: O ratios, we found that the control of the metal filament will make the filament widely distributed, causing the current to rise to the limit current during Reset. However, if the flow ratio is controlled well, the ON/OFF ratio can reach 104, and the set voltage is controlled below 3v.Keywords: RRAM, metal filament, HfO₂, Cu electrode
Procedia PDF Downloads 461549 Wally Feelings Test: Validity and Reliability Study
Authors: Gökhan Kayili, Ramazan Ari
Abstract:
In this research, it is aimed to be adapted Wally Feelings Test to Turkish children and performed the reliability and validity analysis of the test. The sampling of the research was composed of three to five year-old 699 Turkish preschoolers who are attending official and private nursery school. The schools selected with simple random sampling method by considering different socio economic conditions and different central district in Konya. In order to determine reliability of Wally Feelings Test, internal consistency coefficients (KR-20), split-half reliability and test- retest reliability analysis have been performed. During validation process construct validity, content/scope validity and concurrent/criterion validity were used. When validity and reliability of the test examined, it is seen that Wally Feelings Test is a valid and reliable instrument to evaluate three to five year old Turkish children’s understanding feeling skills.Keywords: reliability, validity, wally feelings test, social sciences
Procedia PDF Downloads 5291548 Diagnosis of Diabetes Using Computer Methods: Soft Computing Methods for Diabetes Detection Using Iris
Authors: Piyush Samant, Ravinder Agarwal
Abstract:
Complementary and Alternative Medicine (CAM) techniques are quite popular and effective for chronic diseases. Iridology is more than 150 years old CAM technique which analyzes the patterns, tissue weakness, color, shape, structure, etc. for disease diagnosis. The objective of this paper is to validate the use of iridology for the diagnosis of the diabetes. The suggested model was applied in a systemic disease with ocular effects. 200 subject data of 100 each diabetic and non-diabetic were evaluated. Complete procedure was kept very simple and free from the involvement of any iridologist. From the normalized iris, the region of interest was cropped. All 63 features were extracted using statistical, texture analysis, and two-dimensional discrete wavelet transformation. A comparison of accuracies of six different classifiers has been presented. The result shows 89.66% accuracy by the random forest classifier.Keywords: complementary and alternative medicine, classification, iridology, iris, feature extraction, disease prediction
Procedia PDF Downloads 3921547 Bayesian Structural Identification with Systematic Uncertainty Using Multiple Responses
Authors: André Jesus, Yanjie Zhu, Irwanda Laory
Abstract:
Structural health monitoring is one of the most promising technologies concerning aversion of structural risk and economic savings. Analysts often have to deal with a considerable variety of uncertainties that arise during a monitoring process. Namely the widespread application of numerical models (model-based) is accompanied by a widespread concern about quantifying the uncertainties prevailing in their use. Some of these uncertainties are related with the deterministic nature of the model (code uncertainty) others with the variability of its inputs (parameter uncertainty) and the discrepancy between a model/experiment (systematic uncertainty). The actual process always exhibits a random behaviour (observation error) even when conditions are set identically (residual variation). Bayesian inference assumes that parameters of a model are random variables with an associated PDF, which can be inferred from experimental data. However in many Bayesian methods the determination of systematic uncertainty can be problematic. In this work systematic uncertainty is associated with a discrepancy function. The numerical model and discrepancy function are approximated by Gaussian processes (surrogate model). Finally, to avoid the computational burden of a fully Bayesian approach the parameters that characterise the Gaussian processes were estimated in a four stage process (modular Bayesian approach). The proposed methodology has been successfully applied on fields such as geoscience, biomedics, particle physics but never on the SHM context. This approach considerably reduces the computational burden; although the extent of the considered uncertainties is lower (second order effects are neglected). To successfully identify the considered uncertainties this formulation was extended to consider multiple responses. The efficiency of the algorithm has been tested on a small scale aluminium bridge structure, subjected to a thermal expansion due to infrared heaters. Comparison of its performance with responses measured at different points of the structure and associated degrees of identifiability is also carried out. A numerical FEM model of the structure was developed and the stiffness from its supports is considered as a parameter to calibrate. Results show that the modular Bayesian approach performed best when responses of the same type had the lowest spatial correlation. Based on previous literature, using different types of responses (strain, acceleration, and displacement) should also improve the identifiability problem. Uncertainties due to parametric variability, observation error, residual variability, code variability and systematic uncertainty were all recovered. For this example the algorithm performance was stable and considerably quicker than Bayesian methods that account for the full extent of uncertainties. Future research with real-life examples is required to fully access the advantages and limitations of the proposed methodology.Keywords: bayesian, calibration, numerical model, system identification, systematic uncertainty, Gaussian process
Procedia PDF Downloads 3211546 Jungle Justice on Emotional Health Challenges of Residents in Lagos Metropolis
Authors: Aaron Akinloye
Abstract:
this research focuses on the impact of jungle justice on the emotional health challenges experienced by residents in the Lagos metropolitan city in Nigeria. Jungle justice refers to the practice of individuals taking the law into their own hands and administering punishment without proper legal procedures. The aim of this study is to investigate the influence of jungle justice on the emotional challenges faced by residents in Lagos. The specific objectives of the study are to examine the effects of jungle justice on trauma, pressure, fear, and depression among residents. The study adopts a descriptive survey research design and uses a questionnaire as the research instrument. The population of the study consisted of residents in the three senatorial districts that make up Lagos State. A simple random sampling technique was used to select two Local Government Areas (Yaba and Shomolu) from each of the three senatorial districts of Lagos State. Also, a simple random sampling technique was used to select fifty (50) residents from each of the chosen Local Government Areas to make three hundred (300) residents that formed the sample of the study. Accidental sampling technique is employed to select a sample of 300 residents. Data on the variables of interest is collected using a self-developed questionnaire. The research instrument undergoes validation through face, content, and construct validation processes. The reliability coefficient of the instrument is found to be 0.84. The study reveals that jungle justice significantly influences trauma, pressure, fear, and depression among residents in Lagos metropolitan city. The statistical analysis shows significant relationships between jungle justice and these emotional health challenges (df (298) t= 2.33, p< 0.05; df (298) t= 2.16, p< 0.05; df (298) t= 2.20, p< 0.05; df (298) t= 2.14, p< 0.05). This study contributes to the literature by highlighting the negative effects of jungle justice on the emotional well-being of residents. It emphasizes the importance of addressing this issue and implementing measures to prevent such vigilante actions. Data is collected through the administration of the self-developed questionnaire to the selected residents. The collected data is then analyzed using inferential statistics, specifically mean analysis, to examine the relationships between jungle justice and the emotional health challenges experienced by the residents. The main question addressed in this study is how jungle justice affects the emotional health challenges faced by residents in Lagos metropolitan city. Conclusion: The study concludes that jungle justice has a significant influence on trauma, pressure, fear, and depression among residents. To address this issue, recommendations are made, including the implementation of comprehensive awareness campaigns, improvement of law enforcement agencies, development of support systems for victims, and revision of the legal framework to effectively address jungle justice. Overall, this research contributes to the understanding of the consequences of jungle justice and provides recommendations for intervention to protect the emotional well-being of residents in Lagos metropolitan city.Keywords: jungle justice, emotional health, depression, anger
Procedia PDF Downloads 641545 Survey of Personality Characteristics in Adolescents under the Care of Tehran Juvenile Detention Center
Authors: Jamal Shokrzadehmadiyeh, Kambiz Kamkari, Shohreh Shokrzadeh
Abstract:
According to the research topic, the purpose of the current paper is to research personality characteristics in adolescents under the care of the Tehran Juvenile Detention Centre, and a survey research method has been used. In this regard, through systematic random sampling, 120 people from the research population were selected as a sample, who were referred to Tehran Juvenile Detention Centre after the decision was reached by the court. Data collection was carried out by separate examination using NEO-PI-III personality inventory, and statistical analysis was done using a one-sample t-test. Finally, the results of the research revealed that the level of neuroticism is higher than the average level, the level of conscientiousness is lower than the average level, and the level of extraversion, agreeableness, and openness are at the average level.Keywords: personality characteristics, adolescents, Juvenile Detention Center, Tehran city
Procedia PDF Downloads 971544 Analysis of Selected Hematological Variables during Three Different Menstrual Phases between Sedentary and Sports Women
Authors: G. Vasanthi
Abstract:
The purpose of the study was to analyse the red blood cells and white blood cells during three different menstrual phases between sedentary and sports women. To achieve this purpose, fifteen female sedentary post graduate students (M.A., M.Sc.) and fifteen students of Master of Physical Education and Sports (M.P.Ed.) women who regularly involved in vigouous sports training and participated in sports competition on different games were selected by adopting random sampling method. All the students were hostelers and their age group was between 20 to 22 years. The blood sample were collected during the mid-period of the three different phases to calculate the red blood cells and white blood cells. The data collected were treated statistically by using analysis of variance. The results reveal that the RBC and WBC is found to be significant between sedentary and sports women during the three different menstrual phases.Keywords: RBC, WBC, menstrual, proliferative, secretary, sedentary women, sports women
Procedia PDF Downloads 4981543 Optimal Production and Maintenance Policy for a Partially Observable Production System with Stochastic Demand
Authors: Leila Jafari, Viliam Makis
Abstract:
In this paper, the joint optimization of the economic manufacturing quantity (EMQ), safety stock level, and condition-based maintenance (CBM) is presented for a partially observable, deteriorating system subject to random failure. The demand is stochastic and it is described by a Poisson process. The stochastic model is developed and the optimization problem is formulated in the semi-Markov decision process framework. A modification of the policy iteration algorithm is developed to find the optimal policy. A numerical example is presented to compare the optimal policy with the policy considering zero safety stock.Keywords: condition-based maintenance, economic manufacturing quantity, safety stock, stochastic demand
Procedia PDF Downloads 4561542 Employer Branding and Its Influence in Employee Retention in the Non Governmental Organizations in Jordan
Authors: Wasfi Alrawabdeh
Abstract:
Abstract The prime purpose of this study was to investigate whether employers use branding in their organizations, and how employer branding influence the attraction and retention of employees in the Non Governmental Organizations (NGOs) in Jordan. The descriptive survey design was adopted for the study. 500 random NGOs employees', including junior and senior staff were conveniently sampled for the study. Data was analyzed using both descriptive and inferential statistics. The results of the study suggest that organizations use employer-branding processes in their business to attract employees and customers. It was also found that brand names of organizations might significantly influence the decision of employees to join and stay in the organizations. It was therefore suggested that employers need to create conducive work environment with conditions to enable employees feel comfortable and remain in the organization.Keywords: Employer branding, Employee attraction , and retention , Trust , Satisfaction.
Procedia PDF Downloads 1531541 The Relationship of Television Viewers with Brand Awareness and Brand Loyalty: A Case Study of Bangkok, Thailand
Authors: Natnicha Hasoontree
Abstract:
The purposes of this research was to study the relationship of television viewers with brand awareness and brand loyalty from the perspective of customers in Bangkok. A probability random sampling of 482 television viewers was utilized. A Likert-five-scale questionnaire was designed to collect the data and small in-depth interviews were also used to obtain their opinions. The findings revealed that the majority of respondents reported a positive relationship between time of viewing television and brand awareness and brand loyalty. The more they watched the advertisement of a particular brand, the more positive the information was perceived and thereby increasing brand loyalty. Finally, the findings from the in-depth interviews with small group of television producers revealed that they are convinced that advertising exposure had a positive impact on brand awareness and brand loyalty.Keywords: brand awareness, brand loyalty, television viewers, advertisement
Procedia PDF Downloads 3021540 Antimicrobial Nanocompositions Made of Amino Acid Based Biodegradable Polymers
Authors: Nino Kupatadze, Mzevinar Bedinashvili, Tamar Memanishvili, Manana Gurielidze, David Tugushi, Ramaz Katsarava
Abstract:
Bacteria easily colonize the surfaces of tissues, surgical devices (implants, orthopedics, catheters, etc.), and instruments causing surgical device related infections. Therefore, the battle against bacteria and the prevention of surgical devices from biofilm formation is one of the main challenges of biomedicine today. Our strategy to the solution of this problem consists in using antimicrobial polymeric coatings as effective “shields” to protect surfaces from bacteria’s colonization and biofilm formation. As one of the most promising approaches look be the use of antimicrobial bioerodible polymeric nanocomposites containing silver nanoparticles (AgNPs). We assume that the combination of an erodible polymer with a strong bactericide should put obstacles to bacteria to occupy the surface and to form biofilm. It has to be noted that this kind of nanocomposites are also promising as wound dressing materials to treat infected superficial wounds. Various synthetic and natural polymers were used for creating biocomposites containing AgNPs as both particles' stabilizers and matrices forming elastic films at surfaces. One of the most effective systems to fabricate AgNPs is an ethanol solution of polyvinylpyrrolidone(PVP) with dissolved AgNO3–ethanol serves as a AgNO3 reductant and PVP as AgNPs stabilizer (through the interaction of nanoparticles with nitrogen atom of the amide group). Though PVP is biocompatible and film-forming polymer, it is not a good candidate to design either "biofilm shield" or wound dressing material because of a high solubility in water – though the solubility of PVP provides the desirable release of AgNPs from the matrix, but the coating is easily washable away from the surfaces. More promising as matrices look water insoluble but bioerodible polymers that can provide the release of AgNPs and form long-lasting coatings at the surfaces. For creating bioerodible water-insoluble antimicrobial coatings containing AgNPs, we selected amino acid based biodegradable polymers(AABBPs)–poly(ester amide)s, poly(ester urea)s, their copolymers containing amide and related groups capable to stabilize AgNPs. Among a huge variety of AABBPs reported we selected the polymers soluble in ethanol. For preparing AgNPs containing nanocompositions AABBPs and AgNO3 were dissolved in ethanol and subjected to photochemical reduction using daylight-irradiation. The formation of AgNPs was observed visually by coloring the solutions in brownish-red. The obtained AgNPs were characterized by UV-spectroscopy, transmission electron microscopy(TEM), and dynamic light scattering(DLS). According to the UV and TEM data, the photochemical reduction resulted presumably in spherical AgNPs with rather high contribution of the particles below 10 nm that are known as responsible for the antimicrobial activity. DLS study showed that average size of nanoparticles formed after photo-reduction in ethanol solution ranged within 50 nm. The in vitro antimicrobial activity study of the new nanocomposite material is in progress now.Keywords: nanocomposites, silver nanoparticles, polymer, biodegradable
Procedia PDF Downloads 3911539 DeepNIC a Method to Transform Each Tabular Variable into an Independant Image Analyzable by Basic CNNs
Authors: Nguyen J. M., Lucas G., Ruan S., Digonnet H., Antonioli D.
Abstract:
Introduction: Deep Learning (DL) is a very powerful tool for analyzing image data. But for tabular data, it cannot compete with machine learning methods like XGBoost. The research question becomes: can tabular data be transformed into images that can be analyzed by simple CNNs (Convolutional Neuron Networks)? Will DL be the absolute tool for data classification? All current solutions consist in repositioning the variables in a 2x2 matrix using their correlation proximity. In doing so, it obtains an image whose pixels are the variables. We implement a technology, DeepNIC, that offers the possibility of obtaining an image for each variable, which can be analyzed by simple CNNs. Material and method: The 'ROP' (Regression OPtimized) model is a binary and atypical decision tree whose nodes are managed by a new artificial neuron, the Neurop. By positioning an artificial neuron in each node of the decision trees, it is possible to make an adjustment on a theoretically infinite number of variables at each node. From this new decision tree whose nodes are artificial neurons, we created the concept of a 'Random Forest of Perfect Trees' (RFPT), which disobeys Breiman's concepts by assembling very large numbers of small trees with no classification errors. From the results of the RFPT, we developed a family of 10 statistical information criteria, Nguyen Information Criterion (NICs), which evaluates in 3 dimensions the predictive quality of a variable: Performance, Complexity and Multiplicity of solution. A NIC is a probability that can be transformed into a grey level. The value of a NIC depends essentially on 2 super parameters used in Neurops. By varying these 2 super parameters, we obtain a 2x2 matrix of probabilities for each NIC. We can combine these 10 NICs with the functions AND, OR, and XOR. The total number of combinations is greater than 100,000. In total, we obtain for each variable an image of at least 1166x1167 pixels. The intensity of the pixels is proportional to the probability of the associated NIC. The color depends on the associated NIC. This image actually contains considerable information about the ability of the variable to make the prediction of Y, depending on the presence or absence of other variables. A basic CNNs model was trained for supervised classification. Results: The first results are impressive. Using the GSE22513 public data (Omic data set of markers of Taxane Sensitivity in Breast Cancer), DEEPNic outperformed other statistical methods, including XGBoost. We still need to generalize the comparison on several databases. Conclusion: The ability to transform any tabular variable into an image offers the possibility of merging image and tabular information in the same format. This opens up great perspectives in the analysis of metadata.Keywords: tabular data, CNNs, NICs, DeepNICs, random forest of perfect trees, classification
Procedia PDF Downloads 1081538 Participation, Network, Women’s Competency, and Government Policy Affecting on Community Development
Authors: Nopsarun Vannasirikul
Abstract:
The purposes of this research paper were to study the current situations of community development, women’s potentials, women’s participation, network, and government policy as well as to study the factors influencing women’s potentials, women’s participation, network, and government policy that have on the community development. The population included the women age of 18 years old who were living in the communities of Bangkok areas. This study was a mix research method of quantitative and qualitative method. A simple random sampling method was utilized to obtain 400 sample groups from 50 districts of Bangkok and to perform data collection by using questionnaire. Also, a purposive sampling method was utilized to obtain 12 informants for an in-depth interview to gain an in-sight information for quantitative method.Keywords: community development, participation, network, women’s right, management
Procedia PDF Downloads 1631537 Micromechanical Modeling of Fiber-Matrix Debonding in Unidirectional Composites
Authors: M. Palizvan, M. T. Abadi, M. H. Sadr
Abstract:
Due to variations in damage mechanisms in the microscale, the behavior of fiber-reinforced composites is nonlinear and difficult to model. To make use of computational advantages, homogenization method is applied to the micro-scale model in order to minimize the cost at the expense of detail of local microscale phenomena. In this paper, the effective stiffness is calculated using the homogenization of nonlinear behavior of a composite representative volume element (RVE) containing fiber-matrix debonding. The damage modes for the RVE are considered by using cohesive elements and contacts for the cohesive behavior of the interface between fiber and matrix. To predict more realistic responses of composite materials, different random distributions of fibers are proposed besides square and hexagonal arrays. It was shown that in some cases, there is quite different damage behavior in different fiber distributions. A comprehensive comparison has been made between different graphs.Keywords: homogenization, cohesive zone model, fiber-matrix debonding, RVE
Procedia PDF Downloads 1601536 The Effect of Aerobics and Yogic Exercise on Selected Physiological and Psychological Variables of Middle-Aged Women
Authors: A. Pallavi, N. Vijay Mohan
Abstract:
A nation can be economically progressive only when the citizens have sufficient capacity to work efficiently to increase the productivity. So, good health must be regarded as a primary need of the community. This helps the growth and development of the body and the mind, which in turn leads to progress and prosperity of the nation. An optimum growth is a necessity for an efficient existence in a biologically adverse and economically competitive world. It is also necessary for the execution of daily routine work. Yoga is a method or a system for the complete development of the personality in a human being. It can be further elaborated as an all-around and complete development of the body, mind, morality, intellect and soul of a being. Sri Aurobindo defines yoga as 'a methodical effort towards self-perfection by the development of the potentialities in the individual.' Aerobic exercise as any activity that uses large muscle groups, can be maintained continuously, and is rhythmic I nature. It is a type of exercise that overloads the heart and lungs and causes them to work harder than at rest. The important idea behind aerobic exercise today, is to get up and get moving. There are more activities that ever to choose from, whether it is a new activity or an old one. Find something you enjoy doing that keeps our heart rate elevated for a continuous time period and get moving to a healthier life. Middle aged selected and served as the subjects for the purpose of this study. The selected subjects were in the age group of 30 to 40 years. By going through the literature and after consulting the experts in yoga and aerobic training, the investigator had chosen the variables which are specifically related to the middle-aged men. The selected physiological variables are pulse rate, diastolic blood pressure, systolic blood pressure; percent body fat and vital capacity. The selected psychological variables are job anxiety, occupational stress. The study was formulated as a random group design consisting of aerobic exercise and yogic exercises groups. The subjects (N=60) were at random divided into three equal groups of twenty middle-aged men each. The groups were assigned the names as follows: 1. Experimental group I- aerobic exercises group, 2. Experimental group II- yogic exercises, 3. Control group. All the groups were subjected to pre-test prior to the experimental treatment. The experimental groups participated in their respective duration of twenty-four weeks, six days in a week throughout the study. The various tests administered were: prior to training (pre-test), after twelfth week (second test) and twenty-fourth weeks (post-test) of the training schedule.Keywords: pulse rate, diastolic blood pressure, systolic blood pressure; percent body fat and vital capacity, psychological variables, job anxiety, occupational stress, aerobic exercise, yogic exercise
Procedia PDF Downloads 4401535 Mechanical Qualification Test Campaign on the Demise Observation Capsule
Authors: B. Tiseo, V. Quaranta, G. Bruno, R. Gardi, T. Watts, S. Dussy
Abstract:
This paper describes the qualification test campaign performed on the Demise Observation Capsule DOC-EQM as part of the Future Launch Preparatory Program FLPP3. The mechanical environment experienced during launch ascent and separation phase was first identified and then replicated in terms of sine, random and shock vibration. The loads identification is derived by selecting the worst possible case. Vibration and shock qualification test performed at CIRA Space Qualification laboratory is herein described. Mechanical fixtures’ design and validation, carried out by means of FEM, is also addressed due to its fundamental role in the vibrational test campaign. The Demise Observation Capsule (DOC) successfully passed the qualification test campaign. Functional test and resonance search have not been point any fault and damages of the capsule.Keywords: capsule, demise, demise observation capsule, DOC, launch environment, re-ntry, qualification
Procedia PDF Downloads 1381534 Brand Placement Practices in the Movies and Their Importance on Brand Recall
Authors: Elif Esiyok
Abstract:
Brand placement practices have become a popular advertising strategy, which is widely used in movies. Whether these brands are remembered by the audience after the film, or if they affect the purchasing preferences of the consumers has become one of the most important topics in the field of advertising. From this point, in this study, the "Devil Wears Prada" movie which includes high amount of brand placements is chosen. The movie watched to the undergraduate students in Turkey to measure the impact of brand placements on the attitudes of the consumers relating with a specific brand. In total 100 students were the subjects of this study. The participants were selected through using a simple random sampling method. The findings revealed that there is a significant difference between male and females in terms of brand recall. Female students were remembered the fashion brands more than the males, whereas males generally recalled the automotive brands and restaurant names.Keywords: brand placement, brand recall, advertising, media
Procedia PDF Downloads 1541533 Me and My Selfie: Identity Building Through Self Representation in Social Media
Authors: Revytia Tanera
Abstract:
This research is a pilot study to examine the rise of selfie trend in dealing with individual self representation and identity building in social media. The symbolic interactionism theory is used as the concept of the desired self image, and Cooley’s looking glass-self concept is used to analyze the mechanical reflection of ourselves; how do people perform their “digital self” in social media. In-depth interviews were conducted in the study with a non-random sample who owns a smartphone with a front camera feature and are active in social media. This research is trying to find out whether the selfie trend brings any influence on identity building on each individual. Through analysis of interview results, it can be concluded that people take selfie photos in order to express themselves and to boost their confidence. This study suggests a follow up and more in depth analysis on identity and self representation from various age groups.Keywords: self representation, selfie, social media, symbolic interaction, looking glass-self
Procedia PDF Downloads 290