Search results for: conflicting claim on credit of discovery of ridge regression

Authors: Neelam Rashid, Muhammad Zafar, Mushtaq Ahmad, Khafsa Malik, Syed Nasar Shah

Abstract:

The present study was conducted to study the role of medicinal plants used to cure different ailments in Azad Kashmir. Various ethno medicinal surveys were carried out during 2016 to enlist the uses of plants against various ailments by rural communities of the area. Information was obtained from 60 local people including 45 males (10 traditional health practitioners) and 15 females by semi structured interviews and group discussions. 65 plant species belonging to 45 families were reported. The dominant plant habit was herbaceous (56%) while decoction was the most common method of utilization (40%). The most cited turmoil was the gastrointestinal disorders. The data obtained were analyzed using ethno medicinal indices such as FL, UV, ICF, FC, and RFC. Results revealed that various species had numerous uses in curing of diseases. So conservation of biodiversity of these medicinal plants and traditional knowledge can play important role in improving the local health conditions of rural people and modern drug discovery and development.

Keywords: medicinal plants, ailments, drug, health, traditional

Procedia PDF Downloads 220

Authors: Anahita Farhang Ghahfarokhi, Alessandro Berti, Wil M.P. van der Aalst

Abstract:

Process mining provides ways to analyze business processes. Common process mining techniques consider the process as a whole. However, in real-life business processes, different behaviors exist that make the overall process too complex to interpret. Process comparison is a branch of process mining that isolates different behaviors of the process from each other by using process cubes. Process cubes organize event data using different dimensions. Each cell contains a set of events that can be used as an input to apply process mining techniques. Existing work on process cubes assume single case notions. However, in real processes, several case notions (e.g., order, item, package, etc.) are intertwined. Object-centric process mining is a new branch of process mining addressing multiple case notions in a process. To make a bridge between object-centric process mining and process comparison, we propose a process cube framework, which supports process cube operations such as slice and dice on object-centric event logs. To facilitate the comparison, the framework is integrated with several object-centric process discovery approaches.

Keywords: multidimensional process mining, mMulti-perspective business processes, OLAP, process cubes, process discovery, process mining

Procedia PDF Downloads 230

Authors: S. K. Ashiquer Rahman

Abstract:

the paper concentrations on the importance of hourly compensation, emphasizing the significance of the unemployment rate. There are the two most important factors of a nation these are its unemployment rate and hourly compensation. These are not merely statistics but they have profound effects on individual, families, and the economy. They are inversely related to one another. When we consider the unemployment rate that will probably decline as hourly compensations in manufacturing rise. But when we reduced the unemployment rates and increased job prospects could result from higher compensation. That’s why, the increased hourly compensation in the manufacturing sector that could have a favorable effect on job changing issues. Moreover, the relationship between hourly compensation and unemployment is complex and influenced by broader economic factors. In this paper, we use panel data regression models to evaluate the expected link between hourly compensation and unemployment rate in order to determine the effect of hourly compensation on unemployment rate. We estimate the fixed effects model, evaluate the error components, and determine which model (the FEM or ECM) is better by pooling all 60 observations. We then analysis and review the data by comparing 3 several countries (United States, Canada and the United Kingdom) using panel data regression models. Finally, we provide result, analysis and a summary of the extensive research on how the hourly compensation effects on the unemployment rate. Additionally, this paper offers relevant and useful informational to help the government and academic community use an econometrics and social approach to lessen on the effect of the hourly compensation on Unemployment rate to eliminate the problem.

Keywords: hourly compensation, Unemployment rate, panel data regression models, dummy variables, random effects model, fixed effects model, the linear regression model

Procedia PDF Downloads 51

Authors: Mai Ghazal, Ahmed Hammad

Abstract:

Cost overruns in construction projects are considered as worldwide challenges since the cost performance is one of the main measures of success along with schedule performance. To overcome this problem, studies were conducted to investigate the cost overruns' factors, also projects' historical data were analyzed to extract new and useful knowledge from it. This research is studying and analyzing the effect of some factors causing cost overruns using the historical data from completed construction projects. Then, using these factors to estimate the probability of cost overrun occurrence and predict its percentage for future projects. First, an intensive literature review was done to study all the factors that cause cost overrun in construction projects, then another review was done for previous researcher papers about mining process in dealing with cost overruns. Second, a proposed data warehouse was structured which can be used by organizations to store their future data in a well-organized way so it can be easily analyzed later. Third twelve quantitative factors which their data are frequently available at construction projects were selected to be the analyzed factors and suggested predictors for the proposed model.

Keywords: construction management, construction projects, cost overrun, cost performance, data mining, data warehousing, knowledge discovery, knowledge management

Procedia PDF Downloads 342

Authors: Florin Leon, Silvia Curteanu

Abstract:

Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: batch bulk methyl methacrylate polymerization, adaptive sampling, machine learning, large margin nearest neighbor regression

Procedia PDF Downloads 283

Authors: Taki Eddine Seghier, Mohd Hamdan Ahmad, Yaik-Wah Lim, Samuel Opeyemi Williams

Abstract:

The assessment of building sustainability to achieve a specific green benchmark and the preparation of the required documents in order to receive a green building certification, both are considered as major challenging tasks for green building design team. However, this labor and time-consuming process can take advantage of the available Building Information Modeling (BIM) features such as material take-off and scheduling. Furthermore, the workflow can be automated in order to track potentially achievable credit points and provide rating feedback for several design options by using integrated Visual Programing (VP) to handle the stored parameters within the BIM model. Hence, this study proposes a BIM-based tool that uses Green Building Index (GBI) rating system requirements as a unique input case to evaluate the building sustainability in the design stage of the building project life cycle. The tool covers two key models for data extraction, firstly, a model for data extraction, calculation and the classification of achievable credit points in a green template, secondly, a model for the generation of the required documents for green building certification. The tool was validated on a BIM model of residential building and it serves as proof of concept that building sustainability assessment of GBI certification can be automatically evaluated and documented through BIM.

Keywords: green building rating system, GBRS, building information modeling, BIM, visual programming, VP, sustainability assessment

Procedia PDF Downloads 305

Authors: Vani Singhal, Jitendra Parmar, Satyendra Singh Chouhan

Abstract:

Unseen class discovery has now become an important part of a machine-learning algorithm to judge new classes. Unseen classes are the classes on which the machine learning model is not trained on. With the advancement in technology and AI replacing humans, the amount of data has increased to the next level. So while implementing a model on real-world examples, we come across unseen new classes. Our aim is to find the number of unseen classes by using a hierarchical-based active learning algorithm. The algorithm is based on hierarchical clustering as well as active sampling. The number of clusters that we will get in the end will give the number of unseen classes. The total clusters will also contain some clusters that have unseen classes. Instead of first discovering unseen classes and then finding their number, we directly calculated the number by applying the algorithm. The dataset used is for intent classification. The target data is the intent of the corresponding query. We conclude that when the machine learning model will encounter real-world data, it will automatically find the number of unseen classes. In the future, our next work would be to label these unseen classes correctly.

Keywords: active sampling, hierarchical clustering, open world learning, unseen class discovery

Procedia PDF Downloads 143

Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

Abstract:

This study considers the selection of the most suitable in silico molecular descriptors that could be used for s-triazine pesticides characterization. Suitable descriptors among topological, geometrical and physicochemical are used for quantitative structure-retention relationships (QSRR) model establishment. Established models were obtained using linear regression (LR) and multiple linear regression (MLR) analysis. In this paper, MLR models were established avoiding multicollinearity among the selected molecular descriptors. Statistical quality of established models was evaluated by standard and cross-validation statistical parameters. For detection of similarity or dissimilarity among investigated s-triazine pesticides and their classification, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used and gave similar grouping. This study is financially supported by COST action TD1305.

Keywords: chemometrics, classification analysis, molecular descriptors, pesticides, regression analysis

Procedia PDF Downloads 367

Authors: Laidi Maamar, Achwak Madani, Abdellah El Ahdj Abdellah

Abstract:

The aim of this work is to use Support Vector regression (SVR) combined with dragonfly, firefly, Bee Colony and particle swarm Optimization algorithm to predict global solar radiation on horizontal surfaces in some cities in Algeria. Combining these optimization algorithms with SVR aims principally to enhance accuracy by fine-tuning the parameters, speeding up the convergence of the SVR model, and exploring a larger search space efficiently; these parameters are the regularization parameter (C), kernel parameters, and epsilon parameter. By doing so, the aim is to improve the generalization and predictive accuracy of the SVR model. Overall, the aim is to leverage the strengths of both SVR and optimization algorithms to create a more powerful and effective regression model for various cities and under different climate conditions. Results demonstrate close agreement between predicted and measured data in terms of different metrics. In summary, SVM has proven to be a valuable tool in modeling global solar radiation, offering accurate predictions and demonstrating versatility when combined with other algorithms or used in hybrid forecasting models.

Keywords: support vector regression (SVR), optimization algorithms, global solar radiation prediction, hybrid forecasting models

Procedia PDF Downloads 10

Authors: Tathagatha Khan, Smruti Sourava Mohapatra

Abstract:

Median openings are provided in raised median of multilane roads to facilitate U-turn movement. The U-turn movement is a highly complex and risky maneuver because U-turning vehicle (minor stream) makes 180° turns at median openings and merge with the approaching through traffic (major stream). A U-turning vehicle requires a suitable gap in the major stream to merge, and during this process, the possibility of merging conflict develops. Therefore, these median openings are potential hot spot of conflict and posses concern pertaining to safety. The traffic at the median openings could be managed efficiently with enhanced safety when the capacity of a traffic facility has been estimated correctly. The capacity of U-turns at median openings is estimated by Harder’s formula, which requires three basic parameters namely critical gap, follow up time and conflict flow rate. The estimation of conflicting flow rate under mixed traffic condition is very much complicated due to absence of lane discipline and discourteous behavior of the drivers. The understanding of placement of major stream vehicles at median opening is very much important for the estimation of conflicting traffic faced by U-turning movement. The placement data of major stream vehicles at different section in 4-lane and 6-lane divided multilane roads were collected. All the test sections were free from the effect of intersection, bus stop, parked vehicles, curvature, pedestrian movements or any other side friction. For the purpose of analysis, all the vehicles were divided into 6 categories such as motorized 2W, autorickshaw (3-W), small car, big car, light commercial vehicle, and heavy vehicle. For the collection of placement data of major stream vehicles, the entire road width was divided into sections of 25 cm each and these were numbered seriatim from the pavement edge (curbside) to the end of the road. The placement major stream vehicle crossing the reference line was recorded by video graphic technique on various weekdays. The collected data for individual category of vehicles at all the test sections were converted into a frequency table with a class interval of 25 cm each and the placement frequency curve. Separate distribution fittings were tried for 4- lane and 6-lane divided roads. The variation of major stream traffic volume on the placement characteristics of major stream vehicles has also been explored. The findings of this study will be helpful to determine the conflict volume at the median openings. So, the present work holds significance in traffic planning, operation and design to alleviate the bottleneck, prospect of collision and delay at median opening in general and at median opening in developing countries in particular.

Keywords: median opening, U-turn, conflicting traffic, placement, mixed traffic

Procedia PDF Downloads 116

Authors: Apollinaire Barme, Simon Tamayo, Arthur Gaudron

Abstract:

This paper presents a statistical approach to identify explanatory variables linearly related to e-commerce sales. The proposed methodology allows specifying a regression model in order to quantify the relevance between openly available data (economic and demographic) and national e-commerce sales. The proposed methodology consists in collecting data, preselecting input variables, performing regressions for choosing variables and models, testing and validating. The usefulness of the proposed approach is twofold: on the one hand, it allows identifying the variables that influence e- commerce sales with an accessible approach. And on the other hand, it can be used to model future sales from the input variables. Results show that e-commerce is linearly dependent on 11 economic and demographic indicators.

Keywords: e-commerce, statistical modeling, regression, empirical research

Procedia PDF Downloads 203

Authors: Naod Mekonnen Anega

Abstract:

The very objective of this paper was to empirically identify technology tailored determinants to the adoption and adoption intensity (extent of use) of agricultural water management technologies in Meda Welabu Woreda, Oromia regional state, Ethiopia. Meda Welabu Woreda which is one of the administrative Woredas of the Oromia regional state was selected purposively as this Woreda is one of the Woredas in the region where small scale irrigation practices and the use of agricultural water management technologies can be found among smallholders. Using the existence water management practices (use of water management technologies) and land use pattern as a criterion Genale Mekchira Kebele is selected to undergo the study. A total of 200 smallholders were selected from the Kebele using the technique developed by Krejeie and Morgan. The study employed the Logit and Tobit models to estimate and identify the economic, social, geographical, household, institutional, psychological, technological factors that determine adoption and adoption intensity of water management technologies. The study revealed that while 55 of the sampled households are adopters of agricultural water management technology the rest 140 were non adopters of the technologies. Among the adopters included in the sample 97% are using river diversion technology (traditional) with traditional canal while the rest 7% percent are using pond with treadle pump technology. The Logit estimation reveled that while adoption of river diversion is positively and significantly affected by membership to local institutions, active labor force, income, access to credit and land ownership, adoption of treadle pump technology is positively and significantly affected by family size, education level, access to credit, extension contact, income, access to market, and slope. The Logit estimation also revealed that whereas, group action requirement, distance to farm, and size of active labor force negative and significantly influenced adoption of river diversion, age and perception has negatively and significantly influenced adoption decision of treadle pump technology. On the other hand, the Tobit estimation reveled that while adoption intensity (extent of use) of agricultural water management is positively and significantly affected by education, credit, and extension contact, access to credit, access to market and income. This study revealed that technology tailored study on adoption of Agricultural water management technologies (AWMTs) should be considered to indentify and scale up best agricultural water management practices. In fact, in countries like Ethiopia, where there is difference in social, economic, cultural, environmental and agro ecological conditions even within the same Kebele technology tailored study that fit the condition of each Kebele would help to identify and scale up best practices in agricultural water management.

Keywords: water management technology, adoption, adoption intensity, smallholders, technology tailored approach

Procedia PDF Downloads 415

Authors: Maria Elisabete Costa Ferreira

Abstract:

Domestic violence is a serious social issue in which victims are mostly women. Domestic violence develops in cycles, starting with the building of tension, passing through the incident of abuse and ending with reconciliation, also known as honeymoon. As time goes by, the shorter these phases become, and the greater and more severe the attacks, rarely leading to the death of the victim of abuse. Sometimes, the victim stops the abuse by killing the aggressor, usually after the immediate aggression has taken place. This poses an important obstacle to the claim of self-defense by the victim of domestic violence pending trial for the homicide of her long-time abuser. The main problem with self-defense claims in such cases is that the law requires the act of aggression to be present or imminent (imminent threat or immediate danger) so that it permits the victim to take her defense into her own hands. If the episode of aggression has already taken place, this general requirement for the admissibility of self-defense is not satisfied. This paper sheds new light on the concept of the actuality of the aggression, understanding that, since domestic violence is a permanent offense, for as long as the victim stays under the domain of the aggressor, imminent threat will be present, allowing the self-defense claim of a woman who kills her abuser in such circumstances to be admissible. An actualist interpretation of the requirement of the necessity of the means used in self-defense will be satisfied when evaluated from the subjective perspective of the intimate partner victim. Necessity will be satisfied if it is reasonable for the victim to perceive the use of lethal force as the only means to release herself from the abuser.

Keywords: domestic violence, homicide, self-defense, imminent threat, necessity of lethal force

Procedia PDF Downloads 44

Authors: Dileep Kumar Gupta, Rajendra Prasad, Pradeep Kumar, Varun Narayan Mishra, Ajeet Kumar Vishwakarma, Prashant K. Srivastava

Abstract:

An approach was evaluated for the retrieval of soil moisture of bare soil surface using bistatic scatterometer data in the angular range of 200 to 700 at VV- and HH- polarization. The microwave data was acquired by specially designed X-band (10 GHz) bistatic scatterometer. The linear regression analysis was done between scattering coefficients and soil moisture content to select the suitable incidence angle for retrieval of soil moisture content. The 250 incidence angle was found more suitable. The support vector regression analysis was used to approximate the function described by the input-output relationship between the scattering coefficient and corresponding measured values of the soil moisture content. The performance of support vector regression algorithm was evaluated by comparing the observed and the estimated soil moisture content by statistical performance indices %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE). The values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 2.9451, 1.0986, and 0.9214, respectively at HH-polarization. At VV- polarization, the values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 3.6186, 0.9373, and 0.9428, respectively.

Keywords: bistatic scatterometer, soil moisture, support vector regression, RMSE, %Bias, NSE

Procedia PDF Downloads 398

Authors: Kalbende Krunal Ramesh

Abstract:

The Carbon Capture and Storage Technology (CCS) provides a veritable platform to bridge the gap between the seemingly irreconcilable twin global challenges of ensuring a secure, reliable and diversified energy supply and mitigating climate change by reducing atmospheric emissions of carbon dioxide. Making its proper regulatory policy and making it flexible for the government and private company by law to regulate, also exploring the opportunity in this sector is the main aim of this paper. India's total annual emissions was 1725 Mt CO2 in 2011, which comprises of 6% of total global emission. It is very important to control the greenhouse gas emission for the environment protection. This paper discusses the various regulatory policy and technology adopted by some of the countries for successful using CCS technology. The brief geology of sedimentary basins in India is studied, ranging from the category I to category IV and deep water and potential for mature technology in CCS is reviewed. Areas not suitable for CO2 storage using presently mature technologies were over viewed. CSS and Clean development mechanism was developed for India, considering the various aspects from research and development, project appraisal, approval and validation, implementation, monitoring and verification, carbon credit issued, cap and trade system and its storage potential. The opportunities in oil and gas operations, power sector, transport sector is discussed briefly.

Keywords: carbon credit issued, cap and trade system, carbon capture and storage technology, greenhouse gas

Procedia PDF Downloads 411

Authors: Alaaeddeen M. Seufi

Abstract:

Many have been published on therapeutic derivatives from living organisms including insects. In addition to traditional maggot therapy, more than 900 therapeutic products were isolated from insects. Most people look at insects as enemies and others believe that insects are friends. Many beneficial insects rather than Honey Bees, Silk Worms and Shellac insect could insure human-insect friendship. In addition, insects could be MicroFactories, Biosensors or Bioreactors. InsectFarm is an amazing example of the applied research that transfers insects from laboratory to market by Prof Mircea Ciuhrii and co-workers. They worked for 18 years to derive therapeutics from insects. Their research resulted in production of more than 30 commercial medications derived from insects (e.g. Imunomax, Noblesse, etc.). Two general approaches were followed to discover drugs from living organisms. Some laboratories preferred biochemical approach to purify components of the innate immune system of insects and insect metabolites as well. Then the purified components could be tested for many therapeutic trials. Other researchers preferred molecular approach based on proteomic studies. Components of the innate immune system of insects were then tested for their medical activities. Our Laboratory team preferred to induce insect immune system (using oral, topical and injection routes of administration), then a transcriptomic study was done to discover the induced genes and to identify specific biomarkers that can help in drug discovery. Biomarkers play an important role in medicine and in drug discovery and development as well. Optimum biomarker development and application will require a team approach because of the multifaceted nature of biomarker selection, validation, and application. This team uses several techniques such as pharmacoepidemiology, pharmacogenomics, and functional proteomics; bioanalytical development and validation; modeling and simulation to improve and refine drug development. Our Achievements included the discovery of four components of the innate immune system of Spodoptera littoralis and Musca domestica. These components were designated as SpliDef (defesin), SpliLec (lectin), SpliCec (cecropin) and MdAtt (attacin). SpliDef, SpliLec and MdAtt were confirmed as antimicrobial peptides, while SpliCec was additionally confirmed as anticancer peptide. Our current research is going on to achieve something in antioxidants and anticoagulants from insects. Our perspective is to achieve something in the mass production of prototypes of our products and to reach it to the commercial level. These achievements are the integrated contributions of everybody in our team staff.

Keywords: AMPs, insect, innate immunitty, therappeutics

Procedia PDF Downloads 346

Authors: Shasline Gedeon, Tiffany W. Ardley, Ying Wang, Nathan J. Gesmundo, Katarina A. Sarris, Ana L. Aguirre

Abstract:

Drug discovery and delivery involve drug targeting, an approach that helps find a drug against a chosen target through high throughput screening and other methods by way of identifying the physical properties of the potential lead compound. Physical properties of potential drug candidates have been an imperative focus since the unveiling of Lipinski's Rule of 5 for oral drugs. Throughout a compound's journey from discovery, clinical phase trials, then becoming a classified drug on the market, the desirable properties are optimized while minimizing/eliminating toxicity and undesirable properties. In the pharmaceutical industry, the ability to generate molecules in parallel with maximum efficiency is a substantial factor achieved through sp²-sp² carbon coupling reactions, e.g., Suzuki Coupling reactions. These reaction types allow for the increase of aromatic fragments onto a compound. More recent literature has found benefits to decreasing aromaticity, calling for more sp³-sp² carbon coupling reactions instead. The objective of this project is to provide a comparison between various sp³-sp² carbon coupling methods and reaction conditions, collecting data on production of the desired product. There were four different coupling methods being tested amongst three cores and 4-5 installation groups per method; each method ran under three distinct reaction conditions. The tested methods include the Photoredox Decarboxylative Coupling, the Photoredox Potassium Alkyl Trifluoroborate (BF3K) Coupling, the Photoredox Cross-Electrophile (PCE) Coupling, and the Weix Cross-Electrophile (WCE) Coupling. The results concluded that the Decarboxylative method was very difficult in yielding product despite the several literature conditions chosen. The BF3K and PCE methods produced competitive results. Amongst the two Cross-Electrophile coupling methods, the Photoredox method surpassed the Weix method on numerous accounts. The results will be used to build future libraries.

Keywords: drug discovery, high throughput chemistry, photoredox chemistry, sp³-sp² carbon coupling methods

Procedia PDF Downloads 114

Authors: Mina Adel Shokry Fahim, Jūratė Sužiedelytė Visockienė

Abstract:

With the growing concern over air pollution (AP), it is clear that this has gained more prominence than ever before. The level of consciousness has increased and a sense of knowledge now has to be forwarded as a duty by those enlightened enough to disseminate it to others. This realisation often comes after an understanding of how poor air quality indices (AQI) damage human health. The study focuses on assessing air pollution prediction models specifically for Lithuania, addressing a substantial need for empirical research within the region. Concentrating on Vilnius, it specifically examines particulate matter concentrations 10 micrometers or less in diameter (PM10). Utilizing Gaussian Process Regression (GPR) and Regression Tree Ensemble, and Regression Tree methodologies, predictive forecasting models are validated and tested using hourly data from January 2020 to December 2022. The study explores the classification of AP data into anthropogenic and natural sources, the impact of AP on human health, and its connection to cardiovascular diseases. The study revealed varying levels of accuracy among the models, with GPR achieving the highest accuracy, indicated by an RMSE of 4.14 in validation and 3.89 in testing.

Keywords: air pollution, anthropogenic and natural sources, machine learning, Gaussian process regression, tree ensemble, forecasting models, particulate matter

Procedia PDF Downloads 30

Authors: Leo Carlo B. Rondina

Abstract:

Self-image is an important factor to improve the self-esteem of the personnel. The purpose of the study is to determine the self-image of the police. The respondents were the 503 policemen assigned in different Police Station in Davao City, and they were chosen with the used of random sampling. With the used of Exploratory Factor Analysis (EFA), latent construct variables of police image were identified as follows; professionalism, obedience, morality and justice and fairness. Further, ordinal regression indicates statistical characteristics on ages 21-40 which means the age of the respondent statistically improves self-image.

Keywords: police image, exploratory factor analysis, ordinal regression, Galatea effect

Procedia PDF Downloads 260

Authors: Tao Zhang

Abstract:

Job stress appears nearly everywhere especially in the hospitality industry because employees in this industry usually have to work long time and try to meet conflicting demands of their customers, managers, and company. To reduce job stress, employees of casino hotels try to perform leisure activities or tourism. However, casino employees often meet many obstacles or constraints when they plan to travel. Until now, there is little understanding as to why casino hotel employees often face many travel constraints or leisure barriers. What is more, few studies explore the relationship between travel constraints and job stress of casino employees. Therefore, this study is to explore the construct of casino hotel employees' travel constraints and the relationship among job stress, travel constraints, and job satisfaction. Using convenient sampling method, this study planned to investigate 500 front line employees and managers of ten casino hotels in Macau. A total of 500 questionnaires were distributed, and 414 valid questionnaires were received. The return rate of valid questionnaires is 82.8%. Several statistical techniques such as factor analysis, t-test, one-way ANOVA, and regression analysis were applied to analyze the collected data. The findings of this study are as follows. Firstly, by using factor analysis, this study found the travel constraints of casino employees include intrapersonal constraints, interpersonal constraints, and structural constraints. Secondly, by using regression analysis, the study found travel constraints are positively related with job stress while negatively related with job satisfaction. This means reducing travel constraints may create a chance for casino employees to travel so that they could reduce job stress, therefore raise their job satisfaction. Thirdly, this research divided the research samples into three groups by the degree of job stress. The three groups are low satisfaction group, medium satisfaction group, and high satisfaction group. The means values of these groups were compared by t-test. Results showed that there are significant differences of the means values of interpersonal constraints between low satisfaction group and high satisfaction group. This suggests positive interpersonal relationship especially good family member relationship reduce not only job stress but also travel constraints of casino employees. Interestingly, results of t-test showed there is not a significant difference of the means values of structural constraints between low satisfaction group and high satisfaction group. This suggests structural constraints are outside variables which may be related with tourism destination marketing. Destination marketing organizations (DMO) need use all kinds of tools and techniques to promote their tourism destinations so as to reduce structural constraints of casino employees. This research is significant for both theoretical and practical fields. From the theoretical perspective, the study found the internal relationship between travel constraints, job stress, and job satisfaction and the different roles of three dimensions of travel constraints. From the practical perspective, the study provides useful methods to reduce travel constraints and job stress, therefore, raise job satisfaction of casino employees.

Keywords: hotel, job satisfaction, job stress, travel constraints

Procedia PDF Downloads 234

Authors: Mehdi Moeinaddini, Zohreh Asadi-Shekari, Muhammad Zaly Shah, Amran Hamzah

Abstract:

Currently, planners try to have more green travel options to decrease economic, social and environmental problems. Therefore, this study tries to find significant urban travel factors to be used to increase the usage of alternative urban travel modes. This paper attempts to identify the relationship between prominent urban mobility indicators and daily trips by public transport in 30 cities from various parts of the world. Different travel modes, infrastructures and cost indicators were evaluated in this research as mobility indicators. The results of multi-linear regression analysis indicate that there is a significant relationship between mobility indicators and the daily usage of public transport.

Keywords: green travel modes, urban travel indicators, daily trips by public transport, multi-linear regression analysis

Procedia PDF Downloads 526

Authors: A. Ishag Mohamed, A. A. Rabah

Abstract:

The objective of this research is to develop a generalized correlation for the prediction of thermal conductivity of n-Alkanes and Alkenes. There is a minority of research and lack of correlation for thermal conductivity of liquids in the open literature. The available experimental data are collected covering the groups of n-Alkanes and Alkenes.The data were assumed to correlate to temperature using Filippov correlation. Nonparametric regression of Grace Algorithm was used to develop the generalized correlation model. A spread sheet program based on Microsoft Excel was used to plot and calculate the value of the coefficients. The results obtained were compared with the data that found in Perry's Chemical Engineering Hand Book. The experimental data correlated to the temperature ranged "between" 273.15 to 673.15 K, with R2 = 0.99.The developed correlation reproduced experimental data that which were not included in regression with absolute average percent deviation (AAPD) of less than 7 %. Thus the spread sheet was quite accurate which produces reliable data.

Keywords: N-Alkanes, N-Alkenes, nonparametric, regression

Procedia PDF Downloads 635

Authors: Michio Kurosu

Abstract:

Alterations in glycosylation not only directly impact cell growth and survival but also facilitate tumor-induced immunomodulation and eventual metastasis. Identification of cell type-specific glycoconjugates (tumor markers) has led to the discovery of new assay systems for certain cancers via immunodetection reagents. N- and O-linked glycans are the most abundant forms of glycoproteins. Recent studies of cancer immunotherapy are based on the immunogenicity of truncated O-glycan chains (e.g., Tn, sTn, T, and sLea/x). The prevalence of N-linked glycan changes in the development of tumor cells is known; however, therapeutic antibodies against N-glycans have not yet been developed. This is due to the lack of specificity of N-linked glycans between normal/healthy and cancer cells. Abnormal branching of N-linked glycans has been observed, particularly in solid cancer cells. While the discovery of drug-like glycosyltransferase inhibitors that block the biosynthesis of specific branching has a very low likelihood of success, altered glycosylation levels can be exploited by suppressing N-glycan biosynthesis through the inhibition of dolichyl-phosphate N-acetylglucosaminephosphotransferase1 (DPAGT1) activity. Inhibition of DPAGT1 function leads to changes of O-glycosylation on proteins associated with mitochondria and zinc finger binding proteins (indirect effects). On the basis of dynamic crosstalk between DPAGT1 and Snail/Slung/ZEB1 (a family of transcription factors that promote the repression of the adhesion molecules), we have developed pharmacologically acceptable selective DPAGT1 inhibitors. Tunicamycin kills a wide range of cancer and healthy cells in a non-selective manner. In sharp contrast, our DPAGT1 inhibitors display strong cytostatic effects against 16 solid cancers, which require the overexpression of DPAGT1 in their progression but do not affect the cell viability of healthy cells. The identified DPAGT1 inhibitors possess impressive anti-metastatic ability in various solid cancer cell lines and induce their mitochondrial structural changes, resulting in apoptosis. A prototype DPAGT1 inhibitor, APPB has already been proven to shrink solid tumors (e.g., pancreatic cancers, triple-negative breast cancers) in vivo while suppressing metastases and has strong synergistic effects when combined with current cytotoxic drugs (e.g., paclitaxel). At this conference, our discovery of selective DPAGT1 inhibitors with drug-like properties and proof-of-pharmaceutical concept studies of a novel DPAGT1 inhibitor are presented.

Keywords: DPAGT1 inhibitors, anti-metastatic drugs, natural product based drug designs, cytostatic effects

Procedia PDF Downloads 51

Authors: Jiabei Zhang

Abstract:

Online programs developed for preparing qualified teachers have significantly increased over the years in the United States of America (USA). However, no online graduate programs for training adapted physical education (APE) teachers for children with significant developmental disabilities are currently available in the USA. The purpose of this study was to develop an online master’s degree program for the preparation of APE teachers to serve children with significant developmental disabilities. The characteristics demonstrated by children with significant developmental disabilities, the competencies required for certified APE teachers, and the evidence-based positive behavioral interventions (PBI) documented for teaching children with significant developmental disabilities were fully reviewed in this study. An online graduate program with 14 courses for 42 credit hours (3 credit hours per course) was then developed for training APE teachers to serve children with significant developmental disabilities. Included in this online program are five components: (a) 2 capstone courses, (b) 4 APE courses, (c) 4 PBI course, (d) 2 elective courses, and (e) 2 capstone courses. All courses will be delivered online through Desire2Learn administered by the Extended University Programs at Western Michigan University (WMU). An applicant who has a bachelor’s degree in physical education or special education is eligible for this proposed program. A student enrolled in this program is expected to complete all courses in 2.5 years while staying in their local area. This program will be submitted to the WMU curriculum committee for approval in the fall of 2018.

Keywords: adapted physical education, online program, teacher preparation, and significant disabilities

Procedia PDF Downloads 126

Authors: Alexis Thouki

Abstract:

In our post-Christian societies, ecclesiastical heritage acquired a new extrovert profile aiming to reach out an increasingly diverse audience. In this context, the various motivations, interests, personalities and cultural exchanges, found in the ‘post-modern pilgrimage’, bequeath a hybrid and multidimensional character to religious tourism education. In consequence, churches have acquired the challenging role of enriching visitors cultural and spiritual capital. Despite this promising diversification to relate, reveal and provoke constructive discourses, due to the various ‘conflicting interests’, practitioners attempt to tame the rich in symbolism and meanings religious environment through ‘neutral interpretations’. This paper aims to present the results of an ongoing developing strategy related to the presentation of contentious meanings in English churches. The paper will explore some of the underlying issues related to the capacity of ‘neutrality’ to spark, downplay or eliminate contentious conversations relating to the cultural, religious, and social dimension of Christian cultural heritage thematology. In an effort to understand this issue, the paper examines the concept of neutrality and what it stands for, executing a discourse analysis in the semantic context in which the theological lexicon is interwoven with the cultural and social meanings of sacred sites. Following that, the paper examines whether the preferable interpretive strategies meet the post-modern interpretative framework which is marked by polysemy and critical active engagement. The ultimate aim of the paper is to investigate the hypothesis that the preferable neutral strategies, managing the ‘conflicting’ demands of worshippers and visitors, result in the uneven treatment of both, the religious and historical spirit of the place.

Keywords: contentious dialogue, interpretation, meaning making, religious tourism

Procedia PDF Downloads 139

Authors: S. Bangphan, P. Bangphan, C. Ketsombun, T. Sammana

Abstract:

Optimization of response surface methodology (RSM) was employed to study the effects of three factor (rubber of clearance, spindle of speed, and rice of moisture) in brown rice peeling machine of the optimal good rice yield (99.67, average of three repeats). The optimized composition derived from RSM regression was analyzed using Regression analysis and Analysis of Variance (ANOVA). At a significant level α=0.05, the values of Regression coefficient, R2 adjust were 96.55% and standard deviation were 1.05056. The independent variables are initial rubber of clearance, spindle of speed and rice of moisture parameters namely. The investigating responses are final rubber clearance, spindle of speed and moisture of rice.

Keywords: brown rice, response surface methodology (RSM), peeling machine, optimization, paddy husker

Procedia PDF Downloads 550

Authors: S. Nandagopalan, N. Pradeep

Abstract:

The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.

Keywords: active contour, Bayesian, echocardiographic image, feature vector

Procedia PDF Downloads 420

Authors: Mehravar Javid

Abstract:

This article delves straight into the fascinating role of dream interpretation in psychotherapy, particularly in the context of trauma and healing. By applying a detailed case study of a 19-year-old Iranian woman who has been undergoing therapy, it can explore to what extent her vivid and symbolic dreams – featuring mermaids, hanging fetuses, and themes of control and domination – serve as a reflection of her innermost fears, unresolved traumas, and struggles with identity and sexuality. Another fact to be highlighted is that the dreams, rich in metaphor and symbolism, offer a unique outlook into the patient's subconscious mind, revealing layers of her psychological state that might otherwise remain obscured and vague. On the other hand, the article examines how the therapist navigates these dreamscapes by utilizing them as a tool to understand and address the patient's deep-seated emotional conflicts, traumatic experiences, and identity issues. By analyzing these dreams, we can demonstrate how such dreams can be a crucial part of the healing process, providing insights that facilitate emotional recovery and self-discovery. This discovery underscores the significance of dreams in psychotherapy, highlighting their potential as a powerful medium for unraveling the complexities of the human psyche and aiding in the journey toward mental health and recovery.

Keywords: dream, interpreting, trauma, healing

Procedia PDF Downloads 49

Authors: Alyona Cerfontyne, Levita D'Souza, Lefteris Patlamazoglou

Abstract:

Unlike adoption and donor-assisted reproduction, misattributed paternity occurring within the context of spontaneous conception and outside of formally recognised practices of having a child remains largely an understudied phenomenon. In adulthood, to discover misattributed paternity, i.e., that the man you call your father is not related to you genetically, can have profound implications for everyone affected. Until the advent of direct-to-consumer DNA testing 20 years ago, such discoveries were relatively rare. Despite the growing number of individuals uncovering their biogenetic paternity through genetic testing, there is very limited research on misattributed paternity from the perspective of adult children affected by it. No research exists on how to support these individuals through counselling post-discovery. Framed as insider action research, this study aimed to explore the perceived psychosocial consequences of misattributed paternity discoveries and coping strategies used by individuals who discover their misattributed paternity status in adulthood. In total, 12 individuals with misattributed paternity participated in semi-structured interviews in July-August 2022. The collected data was analysed using reflexive thematic analysis. The study’s results indicate that discovering misattributed paternity in adulthood can be likened to a watershed moment forever changing the trajectory of one’s life. Psychological experiences consistent with trauma, as well as grief and loss, re-evaluation of close family relationships, reestablishment of one’s identity, as well as experiencing a profound need to belong are the key themes emerging from the analysis of psychosocial experiences. Post-discovery, individuals with misattributed paternity employ a wide range of emotional and problem-focused coping strategies, amongst which seeking connection with those who understand, searching for information on the new biogenetic family and finding new meanings to life are most prominent. The study contributes both to the academic and practical knowledge of experiences of misattributed paternity and highlights the importance of further research on the topic.

Keywords: discovery of misattributed paternity, misattributed paternity, paternal discrepancy, psychosocial consequences, coping

Procedia PDF Downloads 62

Authors: Rania Mousa, Peterson Ozili

Abstract:

A key agenda of policymakers in developed and developing countries is to increase the level of financial inclusion. Microlending institutions have been recognized as important agents of financial inclusion, which have the potential to achieve this objective and help move toward a more accessible, inclusive, and equitable path to financial sustainability. In that respect, this case study attempts to identify and assess the key initiatives undertaken by Grameen America as it responded to the COVID-19 pandemic within the framework of selected United Nations’ Sustainability Development Goals (UN’s SD Goals). This study goes beyond the stated objective by using the vulnerable group theory and special agent theory of financial inclusion to support the analysis of financial and non-financial information collected from Grameen America’s Annual Reports and audited financial statements. The study follows a qualitative content analysis method to precisely gauge the shift in Grameen’s strategy and focus, as well as to assess the impact of its initiatives on the small business community before and after the pandemic. The findings showcase that Grameen’s longstanding mission to alleviate poverty is in line with the UN’s Sustainability Development Goal 1. Furthermore, Grameen’s commitment to creating partnerships with external organizations to offer credit and non-credit services and support is consistent with UN’s Sustainability Development Goal 17. The study suggests that policymakers should foster the creation of more member-based financial and non-financial institutions which are ethically and morally responsible to their members in both good and bad times.

Keywords: COVID-19, financial inclusion, microfinance, sustainable development, microlending

Procedia PDF Downloads 53