Search results for: gender specific data

Authors: S. AlBustan, B. AlGhannam

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This oral presentation discusses a proposal for a study that evaluates the usability of an evidence based application named ProxTalker App. The significance of this study will inform administration and faculty staff at the Department of Communication Sciences Disorders (CDS), College of Life Sciences, Kuwait University whether the app is a suitable tool to use for CDS students. A case study will be used involving a sample of CDS students taking practicum and internship courses during the academic year 2018/2019. The study will follow a process used by previous study. The process of calculating SUS is well documented and will be followed. ProxTalker App is an alternative and augmentative tool that speech language pathologist (SLP) can use to customize boards for their clients. SLPs can customize different boards using this app for various activities. A board can be created by the SLP to improve and support receptive and expressive language. Using technology to support therapy can aid SLPs to integrate this ProxTalker App as part of their clients therapy. Supported tools, games and motivation are some advantages of incorporating apps during therapy sessions. A quantitative methodology will be used. It involves the utilization of a standard tool that was the was adapted to the Arabic language to accommodate native Arabic language users. The tool that will be utilized in this research is the Arabic Standard Usability Scale (A-SUS) questionnaire which is an adoption of System Usability Scale (SUS). Standard usability questionnaires are reliable, valid and their process is properly documented. This study builds upon the development of A-SUS, which is a psychometrically evaluated questionnaire that targets Arabic native speakers. Results of the usability will give preliminary indication of whether the ProxTalker App under investigation is appropriate to be integrated within the practicum and internship curriculum of CDS. The results of this study will inform the CDS department of this specific app is an appropriate tool to be used for our specific students within our environment because usability depends on the product, environment, and users.

Keywords: A-SUS, communication disorders practicum, evidence based app, Standard Usability Scale

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Authors: A. R. Manu, V. K. Agrawal, K. N. Balasubramanya Murthy

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Authentication is required in stored database systems so that only authorized users can access the data and related cloud infrastructures. This paper proposes an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. The proposed technique is likely to be more robust as the probability of breaking the password is extremely low. This framework uses a multi-modal biometric approach and SMS to enforce additional security measures with the conventional Login/password system. The robustness of the technique is demonstrated mathematically using a statistical analysis. This work presents the authentication system along with the user authentication architecture diagram, activity diagrams, data flow diagrams, sequence diagrams, and algorithms.

Keywords: design, implementation algorithms, performance, biometric approach

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Authors: Cyril Kaplan

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26 participants played 4 EEG neurofeedback (NF) games encouraged to find their strategies to control the specific NF parameter. Mixed method analysis of performance in the games and post-session interviews led to the identification of states of consciousness that correlated with success in the game. We found that increase in left frontal beta activity was facilitated by evoking interest in observed surroundings, by wondering what is happening behind the window or what lies in a drawer in front.

Keywords: EEG neurofeedback, states of consciousness, frontal beta activity, mixed methods

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Authors: Christian Perrin, Nicholas Blagden, Louise Allen, Sarah Impey

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Social workers in the UK and professionals globally are faced with a particular challenge when dealing with allegations of child sexual abuse (CSA) in the community. In the absence of a conviction or incontestable evidence, staff can often find themselves unable to take decisive action to remove a child from harm, even though there may be a credible threat to their welfare. Conversely, practitioners may over-calculate risk through fear of being accountable for harm. This is, in part, due to the absence of a structured and evidence-based risk assessment tool which can predict the likelihood of a person committing child sexual abuse. Such assessments are often conducted by forensic professionals who utilise offence-specific data and personal history information to calculate risk. In situations where only allegations underpin a case, this mode of assessment is not viable. There are further ethical issues surrounding the assessment of risk in this area which require expert consideration and sensitive planning. This paper explores this entangled problem extant in the wider call to prevent sexual and child sexual abuse in the community. To this end, 32 qualitative interviews were undertaken with social workers dealing with CSA cases. Results were analysed using thematic analysis and operationalised to formulate a risk and protection protocol for use in case management. This paper reports on the early findings associated with the initial indications of protocol reliability. Implications for further research and practice are discussed.

Keywords: sexual offending, child sexual offence, offender rehabilitation, risk assessment, offence prevention

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Authors: Suk-Hyun Yu, Heeyong Kwon

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Recently PM-10 has become a social and global issue. It is one of major air pollutants which affect human health. Therefore, it needs to be forecasted rapidly and precisely. However, PM-10 comes from various emission sources, and its level of concentration is largely dependent on meteorological and geographical factors of local and global region, so the forecasting of PM-10 concentration is very difficult. Neural network model can be used in the case. But, there are few cases of high concentration PM-10. It makes the learning of the neural network model difficult. In this paper, we suggest a simple input balancing method when the data distribution is uneven. It is based on the probability of appearance of the data. Experimental results show that the input balancing makes the neural networks’ learning easy and improves the forecasting rates.

Keywords: artificial intelligence, air quality prediction, neural networks, pattern recognition, PM-10

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Authors: Vahdetti̇n Sariyel, Bi̇rol Dağ

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In this research, growth and development parameters in Konya, a private company in Saanen kids reared in intensive conditions in the province were examined. Average birth weights were 3.42, 2.96, 3.57, 3.23 and 2.77 kg for male, female, single, twins and triplets kids. Average weaning weights (three months of age) were 12.65, 12.09, 12.80, 12.65 and 11.68 kg for male, female, single, twins and triplets kids. Average body weights at seven months of age were 20.55, 18.98, 20.12, 20.12 and 19.05 kg for male, female, single, twins and triplets kids respectively. Considering the gender of the live weight factors birth control and rule in favor of the first en ( P <0.01), the second control finally it disappeared statistically significant ( P> 0.05). Main age and the effect of birth weight in the first month, while significant (P < 0.01); The effect of the second month following the live weight of the kid was not significant.

Keywords: Saanen kids, growth, development, body weight

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Authors: Eunji Choi, Borang Park, Youngjae Choi, Jinwoo Moon

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In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.

Keywords: deep learning, indoor quality, metabolism, predictive model

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Authors: Emma E. Hellawell, Susan J. Hughes

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BBrownfield sites are currently being redeveloped for residential use. Information on soil contamination on these former industrial sites is collected as part of the planning process by the local government. This research project analyses this untapped resource of environmental data, using site investigation data submitted to a local Borough Council, in Surrey, UK. Over 150 site investigation reports were collected and interrogated to extract relevant information. This study involved three phases. Phase 1 was the development of a database for soil contamination information from local government reports. This database contained information on the source, history, and quality of the data together with the chemical information on the soil that was sampled. Phase 2 involved obtaining site investigation reports for development within the study area and extracting the required information for the database. Phase 3 was the data analysis and interpretation of key contaminants to evaluate typical levels of contaminants, their distribution within the study area, and relating these results to current guideline levels of risk for future site users. Preliminary results for a pilot study using a sample of the dataset have been obtained. This pilot study showed there is some inconsistency in the quality of the reports and measured data, and careful interpretation of the data is required. Analysis of the information has found high levels of lead in shallow soil samples, with mean and median levels exceeding the current guidance for residential use. The data also showed elevated (but below guidance) levels of potentially carcinogenic polyaromatic hydrocarbons. Of particular concern from the data was the high detection rate for asbestos fibers. These were found at low concentrations in 25% of the soil samples tested (however, the sample set was small). Contamination levels of the remaining chemicals tested were all below the guidance level for residential site use. These preliminary pilot study results will be expanded, and results for the whole local government area will be presented at the conference. The pilot study has demonstrated the potential for this extensive dataset to provide greater information on local contamination levels. This can help inform regulators and developers and lead to more targeted site investigations, improving risk assessments, and brownfield development.

Keywords: Brownfield development, contaminated land, local government planning data, site investigation

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Authors: Diana K. Kwok

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Despite the fact that Hong Kong government aims to develop an inclusive society, sexual minority students continue to encounter sexual prejudice without legal protection. They also have difficulties accessing relevant services from mental health and educational professionals, who do not receive systematic training to work with sexual minority students. Informed by the literature on sexual prejudice, heterosexual hegemony, genderism, as well as code of practice for frontline practitioners, the authors explored self-perceived knowledge of teachers and sexual minorities on sexuality and sexual prejudice, and how they perceive prejudice towards sexual minorities in Chinese cultural context. Semi-structure qualitative interviews were carried out with 31 school personnel informants (school teachers and counseling team members) and 25 sexual minority informants on their understanding of sexuality knowledge, their perception of sexual prejudice within school context in Hong Kong, as well as their suggested themes on teachers training on sexual prejudice reduction. This presentation specifically focuses on transcripts from sexual minority informants. Data analysis was carried out through NVivo, and followed the procedures spelt out in the qualitative research literature. Trustworthiness of the study was addressed through various strategies. Preliminary themes emerged from transcript content analysis: 1) A gap of knowledge between sexual minority informants and teachers; 2) Perception on sexual prejudice within cultural context; 3) Heterosexual hegemony and genderism within school system; 4) Needs for mandatory training: contents and strategies. The sexual minority informants found that teachers they encountered were predominantly adopted concepts of binary sex and dichotomous gender. Informants also indicated that the teachings of Confucianism cultural values, religiosity in Hong Kong might well be important cultural forces contributing to sexual prejudice manifested in school context. Although human rights and social justice concepts were embedded in professional code of practice of teachers and school helping professionals, informants found that teachers they encountered may face a dilemma when supporting sexual minority students navigating heterosexual hegemony and genderism in, as a consequence of their personal, institutional, cultural and religious backgrounds. Acknowledgments: The sexual prejudice project was funded by the Hong Kong Research Grant Council (ECS28401614), 2015 to 2017.

Keywords: sexual prejudice, Chinese teachers, Chinese sexual minorities, teacher training

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Authors: Suresh Vanguri, Suresh Palla, K. V. Kalyani, S. K. Chaturvedi, B. N. Mohapatra

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Enhancing the fly ash utilization in the manufacture of cement is identified as one of the key areas to mitigate the Green House Gas emissions from the cement industry. Though increasing the fly ash content in cement has economic and environmental benefits, it results in a decrease in the compressive strength values, particularly at early ages. Quality of clinker and fly ash were identified as predominant factors that govern the extent of absorption of fly ash in the manufacturing of cement. This paper presents systematic investigations on the effect of clinker and fly ash quality on the properties of resultant cement. Since mechanical activation alters the physicochemical properties such as particle size distribution, surface area, phase morphology, understanding the variation of these properties with activation is required for its applications. The effect of mechanical activation on fly ash surface area, specific gravity, flow properties, lime reactivity, comparative compressive strength (CCS), reactive silica and mineralogical properties were also studied. The fineness of fly ash was determined by Blaine’s method, specific gravity, lime reactivity, CCS were determined as per the method IS 1727-1967. The phase composition of fly ash was studied using the X-ray Diffraction technique. The changes in the microstructure and morphology with activation were examined using the scanning electron microscope. The studies presented in this paper also include evaluation of Portland Pozzolana Cement (PPC), prepared using high volume fly ash. Studies are being carried out using clinker from cement plants located in different regions/clusters in India. Blends of PPC containing higher contents of activated fly ash have been prepared and investigated for their chemical and physical properties, as per Indian Standard procedures. Changes in the microstructure of fly ash with activation and mechanical properties of resultant cement containing high volumes of fly ash indicated the significance of optimization of the quality of clinker and fly ash fineness for better techno-economical benefits.

Keywords: flow properties, fly ash enhancement, lime reactivity, microstructure, mineralogy

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Authors: F. A. Al-Awadhi, D. Al-Hulail

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In this study, we applied the Bayesian hierarchical model to detect single and multiple change points for daily earthquake body wave magnitude. The change point analysis is used in both backward (off-line) and forward (on-line) statistical research. In this study, it is used with the backward approach. Different types of change parameters are considered (mean, variance or both). The posterior model and the conditional distributions for single and multiple change points are derived and implemented using BUGS software. The model is applicable for any set of data. The sensitivity of the model is tested using different prior and likelihood functions. Using Mb data, we concluded that during January 2002 and December 2003, three changes occurred in the mean magnitude of Mb in Kuwait and its vicinity.

Keywords: multiple change points, Markov Chain Monte Carlo, earthquake magnitude, hierarchical Bayesian mode

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Authors: John Allbutt, Andrew Murray, Jonathan Ling, Thomas M. Heffernan

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Ultra-endurance events place unique physical and psychological pressures on participants. In this study, we examined the psychologically challenging aspects of taking part in a 3000 mile transatlantic rowing race using a qualitative approach. To date, more people have been into space than have rowed an ocean and only one psychological study has been conducted on this experience which had a specific research focus. The current study was a qualitative study using semi-structured interviews. Participants were an opportunity sample of seven competitors from a recent ocean rowing race. Participants were asked about the psychological aspects of the event after it had finished. The data were analysed using thematic analysis. Several themes emerged from the analysis. These related to: 1) preparation; 2) bodily aches/pains, 3) race setbacks; 4) boat conditions; 5) interpersonal factors and communication; 6) strategies for managing stress and interpersonal tensions. While participants were generally very positive about the event, the analysis showed that they experienced significant psychological challenges during their voyage. Competitors paid considerable attention to preparing for the physical challenges of the event. However, not all prospective competitors gave the same time to preparing for psychological factors or were aware how they might play out during their voyage. All Atlantic rowing crews should be aware of the psychological challenges they face, and have strategies in place to help cope with the psychological strain of taking part.

Keywords: confinement experiences, ocean rowing, stress, ultra-endurance sport

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Authors: Elvis Enowbeyang Tarkang

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Background: Since students in high schools in Cameroon fall within the age group hardest hit by HIV/AIDS, it is assumed that these students might be exposed to sexual risk behaviours. Sexual risk behaviours include engaging in unprotected sexual intercourse, early sexual debut, multiple sexual partners and coerced or forced sex, and these behaviours might predispose youth to HIV transmission. However, little has been explored on the sexual risk behaviours of high school learners in Cameroon. This study aimed at examining the sexual risk behaviours of high school students in an urban town of Cameroon. Method: A quantitative cross sectional design was adopted, using a self-administered questionnaire to collect data from a disproportional stratified simple random sample of 480 (240 male and 240 female) grade 10 to grade 12 students from two participating secondary school in Limbe in the Southwest region of Cameroon August 2014. Descriptive and Chi square statistics were calculated using statistical Package for Social Sciences (SPSS) version 20 software program at the level 0.05. Results: Majority of the respondents, 63.4% reported being sexually active, of whom only 33.2% used condoms consistently. Up to 37% of the sexually active respondents had multiple sexual partners in the past one year before the study, while 23% had multiple sexual partners during the study period. The mean age of first sex was 15.4 years. Among Christians, Pentecostals, 17 (58.6%) were more likely to have experienced sexual coercion than non-Pentecostals, 111 (42.2%) (p= 0.000). Christians, 41 (10.3%) were more likely to have been forced into first sex than Muslims, 0 (0.0%); while among the Christians, Pentecostals, 6 (15.0%) were more likely to have been forced into first sex than non-Pentecostals, 35 (10.9%) (p=0.004). Among the Christians, Pentecostals, 16 (66.7%) were more likely to have experienced sex by age 16 years than non-Pentecostals, 125 (64.1%) (p= 0.000). Students who lived in rented places, 32 (22.7%) were more likely to have had multiple sexual partners than those who lived in their parents’ houses, 35 (18.1%) (p= 0.000). Males, 36 (16.0%) were likely to have had multiple concurrent sexual partners than females, 14 (6.0%) (p=0.002). Students who used condoms consistently, 25 (33.3%) were more likely to have a higher perception of risk of contracting HIV than those who did not use condoms consistently, 38 (29.9%) (p=0.002). Students who lived in their parents’ houses, 35 (35.4%) were more likely to use condoms consistently during sex, than those who lived in rented places, 31 (29.8%) (p=0.021). Students who passed their examinations, 57 (30.9%) were more likely to have used condoms consistently than those with low academic profiles, 24 (27.9%) (p= 0.034). Conclusions and Recommendations: Gender, lack of parental control, religion, academic profile, poverty, place of residence and perception of risk of HIV infection were the main factors associated with sexual risk behaviours among students in urban Cameroon. The findings indicate that sexual risk behaviours exist among high school students in Limbe urban town of Cameroon. There is need for campaigns and interventions to bring about sexual behaviour change.

Keywords: Cameroon, high school students, HIV/AIDS, Limbe urban town, sexual risk behaviours

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Authors: Roxana D. Maiorescu-Murphy

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Companies have recently embraced political activism as an alleged responsibility toward the communities they operate in. As a result of its recency, there is little understanding of the impact of corporate activism on consumers. In addition, embracing corporate activism engenders polarizing opinions, potentially leading to a crisis of morality shown in past literature to flourish in online settings. The present study contributes to the literature on communication management, which currently lacks research on stakeholder perceptions toward corporate activism in general and from the perspective of the stakeholders’ emotions of brand hate versus a love that they display before a specific corporate act of activism. For this purpose, the study analyzed online reactions on Twitter following Disney’s stance against Florida’s House Bill 1577 enacted in April 2022. Dubbed the “Don’t Say Gay Bill” by the left wing and the “Parental Rights Bill” by the conservative movement, the legislation triggered polarizing opinions in society and among Disney’s stakeholders, as the company announce it was taking action against it. Given the scarcity of research on corporate political activism and crises of morality, the current study enacted the case study methodology. Consequently, it answered to the research questions of how online stakeholders responded to Disney’s stance as well as why they formed such an opinion. The data were collected from Twitter over a seven-day period of analysis, namely from March 28- April 3, 2022. The period of analysis started on the day Disney announced its stance (March 28, 2022) until the reactions to its announcement petered out significantly (April 3, 2022). The final sample of analysis consisted of N=1,344 and represented Twitter comments in response to the company’s political announcement. The data were analyzed using the grounded theory methodology, which implied multiple exposures to the text and the undertaking of an inductive-deductive approach that led to the emergence of several recurrent themes. The findings revealed that the stakeholders’ prior emotions toward the company (brand hate versus brand love) did not play a greater role in their (dis)agreement with the latter’s activism than the users’ political stances. Specifically, whether they despised or hated Disney prior to this incident was less significant than their personal political stances. Above all, users were more inclined to transition from brand love to brand hate and vice versa based on the political side they viewed Disney to fall under.

Keywords: corporate political advocacy, crisis management, brand hate, brand love

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Authors: Pierre F. Gerard, Frederic F. Leymarie, William Latham

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Architects have developed a series of objective evaluations, using spatial analysis tools such as Isovist, that show how certain spatial qualities are beneficial to specific human activities hosted in the built environments. In return, they can build more adapted environments by tuning those spatial qualities in their design. In parallel, virtual reality technologies have been developed by engineers with the dream of creating a system that immerses users in a new form of spatial experiences. They already have demonstrated a useful range of benefits not only in simulating critical events to assist people in acquiring new skills, but also to enhance memory retention, to name just a few. This paper investigates the effects of two spatial qualities, openness, and complexity, on cognitive performance within immersive virtual environments. Isovist measure is used to design a series of room settings with different levels of each spatial qualities. In an empirical study, each room was then used by every participant to solve a navigational puzzle game and give a rating of their spatial experience. They were then asked to fill in a questionnaire before solving the visual-spatial memory quiz, which addressed how well they remembered the different rooms. Findings suggest that those spatial qualities have an effect on some of the measures, including navigation performance and memory retention. In particular, there is an order effect for the navigation puzzle game. Participants tended to spend a longer time in the complex room settings. Moreover, there is an interaction effect while with more open settings, participants tended to perform better when in a simple setting; however, with more closed settings, participants tended to perform better in a more complex setting. For the visual-spatial memory quiz, participants performed significantly better within the more open rooms. We believe this is a first step in using virtual environments to enhance participant cognitive performances through better use of specific spatial qualities.

Keywords: architecture, navigation, spatial cognition, virtual reality

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Authors: Soheila Sadeghi

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In the dynamic landscape of project management, scope changes are an inevitable reality that can significantly impact project performance. These changes, whether initiated by stakeholders, external factors, or internal project dynamics, can lead to cost overruns and schedule delays. Accurately predicting the consequences of these changes is crucial for effective project control and informed decision-making. This study aims to develop predictive models to estimate the impact of scope changes on project cost and schedule using machine learning techniques. The research utilizes a comprehensive dataset containing detailed information on project tasks, including the Work Breakdown Structure (WBS), task type, productivity rate, estimated cost, actual cost, duration, task dependencies, scope change magnitude, and scope change timing. Multiple machine learning models are developed and evaluated to predict the impact of scope changes on project cost and schedule. These models include Linear Regression, Decision Tree, Ridge Regression, Random Forest, Gradient Boosting, and XGBoost. The dataset is split into training and testing sets, and the models are trained using the preprocessed data. Cross-validation techniques are employed to assess the robustness and generalization ability of the models. The performance of the models is evaluated using metrics such as Mean Squared Error (MSE) and R-squared. Residual plots are generated to assess the goodness of fit and identify any patterns or outliers. Hyperparameter tuning is performed to optimize the XGBoost model and improve its predictive accuracy. The feature importance analysis reveals the relative significance of different project attributes in predicting the impact on cost and schedule. Key factors such as productivity rate, scope change magnitude, task dependencies, estimated cost, actual cost, duration, and specific WBS elements are identified as influential predictors. The study highlights the importance of considering both cost and schedule implications when managing scope changes. The developed predictive models provide project managers with a data-driven tool to proactively assess the potential impact of scope changes on project cost and schedule. By leveraging these insights, project managers can make informed decisions, optimize resource allocation, and develop effective mitigation strategies. The findings of this research contribute to improved project planning, risk management, and overall project success.

Keywords: cost impact, machine learning, predictive modeling, schedule impact, scope changes

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Authors: Ryspek Usubamatov, Tan San Chin, Sarken Kapaeva

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Productivity of the manufacturing systems depends on technological processes, a technical data of machines and a structure of systems. Technology is presented by the machining mode and data, a technical data presents reliability parameters and auxiliary time for discrete production processes. The term structure of manufacturing systems includes the number of serial and parallel production machines and links between them. Structures of manufacturing systems depend on the complexity of technological processes. Mathematical models of productivity rate for manufacturing systems are important attributes that enable to define best structure by criterion of a productivity rate. These models are important tool in evaluation of the economical efficiency for production systems.

Keywords: productivity, structure, manufacturing systems, structural design

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Authors: Bahadir Aydin

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It is difficult to access accurate knowledge because of mass data. This huge data make environment more and more caotic. Data are main piller of intelligence. The affiliation between intelligence and knowledge is quite significant to understand underlying truths. The data gathered from different sources can be modified, interpreted and classified by using intelligence cycle process. This process is applied in order to progress to wisdom as well as intelligence. Within this process the effect of tacit knowledge is crucial. Knowledge which is classified as explicit and tacit knowledge is the key element for any purpose. Tacit knowledge can be seen as "the tip of the iceberg”. This tacit knowledge accounts for much more than we guess in all intelligence cycle. If the concept of intelligence cycle is scrutinized, it can be seen that it contains risks, threats as well as success. The main purpose of all organizations is to be successful by eliminating risks and threats. Therefore, there is a need to connect or fuse existing information and the processes which can be used to develop it. Thanks to this process the decision-makers can be presented with a clear holistic understanding, as early as possible in the decision making process. Altering from the current traditional reactive approach to a proactive intelligence cycle approach would reduce extensive duplication of work in the organization. Applying new result-oriented cycle and tacit knowledge intelligence can be procured and utilized more effectively and timely.

Keywords: information, intelligence cycle, knowledge, tacit Knowledge

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Authors: Ismail Celik, Gulgun Ayhan Kilcigil, Berna Guven, Zumra Kara, Arzu Onay-Besikci

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Epidermal Growth Factor Receptor is the cell-surface receptor of the ErbB (erythroblastic leukemia viral oncogene homologue receptors) family of tyrosine kinases. It plays a vital role in regulating the proliferation and differentiation of cells. However, a variety of mechanisms, such as EGFR expression, mutation, and ligand-dependent receptor dimerization, are associated with the development of various activated EGFR tumors. EGFR is highly expressed in most solid tumors, including breast, head and neck cancer, non-small cell lung cancer (NSCLC), renal, ovarian, and colon cancers. Thus, specific EGFR inhibition plays one of the key roles in cancer treatment. The compounds used in the treatment as tyrosine kinase inhibitors are known to contain the benzimidazole isosterium indole, pazopanib, and axitinibin indazole rings. In addition, benzimidazoles have been shown to exhibit protein kinase inhibitory activity in addition to their different biological activities.Based on these data, it was planned and synthesized of some oxadiazole bearing benzimidazole derivatives [N-cyclohexyl-5-((2-phenyl/substitutedphenyl-1H-benzo[d]imidazole-1-yl) methyl)-1,3,4-oxadiazole-2-amine]. EGFR kinase inhibitory efficiency of the synthesized compounds was determined by comparing them with a known kinase inhibitor erlotinib in vitro, and two of the compounds bearing phenyl (19a) and 3,4-dibenzyloxyphenyl (21a) ring exhibited significant activities.

Keywords: benzimidazole, EGFR kinase inhibitory, oxadiazole, synthesis

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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Digitalisation in production technology is a driver for the application of machine learning methods. Through the application of predictive quality, the great potential for saving necessary quality control can be exploited through the data-based prediction of product quality and states. However, the serial use of machine learning applications is often prevented by various problems. Fluctuations occur in real production data sets, which are reflected in trends and systematic shifts over time. To counteract these problems, data preprocessing includes rule-based data cleaning, the application of dimensionality reduction techniques, and the identification of comparable data subsets to extract stable features. Successful process control of the target variables aims to centre the measured values around a mean and minimise variance. Competitive leaders claim to have mastered their processes. As a result, much of the real data has a relatively low variance. For the training of prediction models, the highest possible generalisability is required, which is at least made more difficult by this data availability. The implementation of a machine learning application can be interpreted as a production process. The CRoss Industry Standard Process for Data Mining (CRISP-DM) is a process model with six phases that describes the life cycle of data science. As in any process, the costs to eliminate errors increase significantly with each advancing process phase. For the quality prediction of hydraulic test steps of directional control valves, the question arises in the initial phase whether a regression or a classification is more suitable. In the context of this work, the initial phase of the CRISP-DM, the business understanding, is critically compared for the use case at Bosch Rexroth with regard to regression and classification. The use of cross-process production data along the value chain of hydraulic valves is a promising approach to predict the quality characteristics of workpieces. Suitable methods for leakage volume flow regression and classification for inspection decision are applied. Impressively, classification is clearly superior to regression and achieves promising accuracies.

Keywords: classification, CRISP-DM, machine learning, predictive quality, regression

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Authors: Ali Aqa Mohammad Jawad

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Taking a relational approach, this paper analyzes the causal mechanisms associated with successful mobilization and rapid demobilization of the Enlightening Movement in post-2001 Afghanistan. The movement emerged after the state-owned Da Afghan Bereshna Sherkat (DABS) decided to divert the route for the Turkmenistan-Uzbekistan-Tajikistan-Afghanistan-Pakistan (TUTAP) electricity project. The grid was initially planned to go through the Hazara-inhabited province of Bamiyan, according to Afghanistan’s Power Sector Master Plan. The reroute served as an aide-mémoire of historical subordination to other ethno-religious groups for the Hazara community. It was also perceived as deprivation from post-2001 development projects, financed by international aid. This torched the accumulated grievances, which then gave birth to the Enlightening Movement. The movement had a successful mobilization. However, it demobilized after losing much of its mobilizing capabilities through an amalgamation of external and internal relational factors. The successful mobilization yet rapid demobilization constitutes the puzzle of this paper. From the theoretical perspective, this paper is significant as it establishes the applicability of contentious politics theory to protest mobilizations that occurred in Afghanistan, a context-specific, characterized by ethnic politics. Both primary and secondary data are utilized to address the puzzle. As for the primary resources, media coverage, interviews, reports, public media statements of the movement, involved in contentious performances, and data from Social Networking Services (SNS) are used. The covered period is from 2001-2018. As for the secondary resources, published academic articles and books are used to give a historical account of contentious politics. For data analysis, a qualitative comparative historical method is utilized to uncover the causal mechanisms associated with successful mobilization and rapid demobilization of the Movement. In this pursuit, both mobilization and demobilization are considered as larger political processes that could be decomposed to constituent mechanisms. Enlightening Movement’s framing and campaigns are first studied to uncover the associated mechanisms. Then, to avoid introducing some ad hoc mechanisms, the recurrence of mechanisms is checked against another case. Mechanisms qualify as robust if they are “recurrent” in different episodes of contention. Checking the recurrence of causal mechanisms is vital as past contentious events tend to reinforce future events. The findings of this paper suggest that the public sphere in Afghanistan is drastically different from Western democracies known as the birthplace of social movements. In Western democracies, when institutional politics did not respond, movement organizers occupied the public sphere, undermining the legitimacy of the government. In Afghanistan, the public sphere is ethicized. Considering the inter- and intra-relational dynamics of ethnic groups in Afghanistan, the movement reduced to an erosive inter- and intra-ethnic conflict. This undermined the cohesiveness of the movement, which then kicked-off its demobilization process.

Keywords: enlightening movement, contentious politics, mobilization, demobilization

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Authors: Dwipa Rizki Utama, Hanief Ibrahim

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The development of industry retail in Indonesia is very fast, various strategy was undertaken to boost the customer satisfaction and the productivity purchases to boost the profit, one of which is implementing strategies layout. The purpose of this study is to determine the layout of Qita supermarket, a retail industry in Indonesia, in order to improve customer satisfaction and to maximize the rate of products’ sale as a whole, so as the infrequently purchased products will be purchased. This research uses a literature study method, and one of the data mining methods is association rule which applied in market basket analysis. Data were tested amounted 100 from 160 after pre-processing data, so then the distribution department and 26 departments corresponding to the data previous layout will be obtained. From those data, by the association rule method, customer behavior when purchasing items simultaneously can be studied, so then the layout of the supermarket based on customer behavior can be determined. Using the rapid miner software by the minimal support 25% and minimal confidence 30% showed that the 14th department purchased at the same time with department 10, 21st department purchased at the same time with department 13, 15th department purchased at the same time with department 12, 14th department purchased at the same time with department 12, and 10th department purchased at the same time with department 14. From those results, a better supermarket layout can be arranged than the previous layout.

Keywords: industry retail, strategy, association rule, supermarket

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Authors: Abdulraaof H. Alqaili, Hamad A. Alsoliman

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Through progress in pavement design developments, a pavement design method was developed, which is titled the Mechanistic Empirical Pavement Design Guide (MEPDG). Nowadays, the evolution in roads network and highways is observed in Saudi Arabia as a result of increasing in traffic volume. Therefore, the MEPDG currently is implemented for flexible pavement design by the Saudi Ministry of Transportation. Implementation of MEPDG for local pavement design requires the calibration of distress models under the local conditions (traffic, climate, and materials). This paper aims to prepare data for calibration of MEPDG in Central Saudi Arabia. Thus, the first goal is data collection for the design of flexible pavement from the local conditions of the Riyadh region. Since, the modifying of collected data to input data is needed; the main goal of this paper is the analysis of collected data. The data analysis in this paper includes processing each: Trucks Classification, Traffic Growth Factor, Annual Average Daily Truck Traffic (AADTT), Monthly Adjustment Factors (MAFi), Vehicle Class Distribution (VCD), Truck Hourly Distribution Factors, Axle Load Distribution Factors (ALDF), Number of axle types (single, tandem, and tridem) per truck class, cloud cover percent, and road sections selected for the local calibration. Detailed descriptions of input parameters are explained in this paper, which leads to providing of an approach for successful implementation of MEPDG. Local calibration of MEPDG to the conditions of Riyadh region can be performed based on the findings in this paper.

Keywords: mechanistic-empirical pavement design guide (MEPDG), traffic characteristics, materials properties, climate, Riyadh

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Authors: Nurliani, Ida Rosada

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The national rice consumption keeps increasing along with raising income of the households and the rapid growth of population. However, food availability, particularly rice, is limited. Impacts of rice-field conversion have run cumulatively, as we can see on potential losses of rice and crops production, as well as work opportunity that keeps increasing year-by-year. Therefore, it requires policy recommendation to control rice-field conversion through economic, social, and ecological approaches. The research was a survey method intended to: (1) Identify internal factors; quality and productivity of the land as the cause of land conversion, (2) Identify external factors of land conversion, value of the rice-field and the competitor’s land, workforce absorption, and regulation, as well as (3) Formulate strategies in controlling rice-field conversion. Population of the research was farmers who applied land conversion at Pangkep Regency, South Sulawesi. Samples were determined using the incidental sampling method. Data analysis used productivity analysis, land quality analysis, total economic value analysis, and SWOT analysis. Results of the research showed that the quality of rice-field was low as well as productivity of the grains (unhulled-rice). So that, average productivity of the grains and quality of rice-field were low as well. Total economic value of rice-field was lower than the economic value of the embankment. Workforce absorption value on rice-field was higher than on the embankment. Strategies in controlling such rice-field conversion can be done by increasing rice-field productivity, improving land quality, applying cultivation technique of specific location, improving the irrigation lines, and socializing regulation and sanction about the transfer of land use.

Keywords: land conversion, quality of rice-field, productivity, land economic value.

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Authors: K. Sekulová, M. Šimon

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The article demonstrates on a case study how it is possible to identify MSD risk. It is based on a dissertation risk identification model of occupational diseases formation in relation to the work activity that determines what risk can endanger workers who are exposed to the specific risk factors. It is evaluated based on statistical calculations. These risk factors are main cause of upper-extremities musculoskeletal disorders.

Keywords: case study, upper-extremity musculoskeletal disorders, ergonomics, risk identification

Procedia PDF Downloads 503

Authors: Samar Swaid

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Today, corporates are moving toward the adoption of Design-Thinking techniques to develop products and services, putting their consumer as the heart of the development process. One of the leading companies in Design-Thinking, IDEO (Innovation, Design, Engineering Organization), defines Design-Thinking as an approach to problem-solving that relies on a set of multi-layered skills, processes, and mindsets that help people generate novel solutions to problems. Design thinking may result in new ideas, narratives, objects or systems. It is about redesigning systems, organizations, infrastructures, processes, and solutions in an innovative fashion based on the users' feedback. Tim Brown, president and CEO of IDEO, sees design thinking as a human-centered approach that draws from the designer's toolkit to integrate people's needs, innovative technologies, and business requirements. The application of design thinking has been witnessed to be the road to developing innovative applications, interactive systems, scientific software, healthcare application, and even to utilizing Design-Thinking to re-think business operations, as in the case of Airbnb. Recently, there has been a movement to apply design thinking to machine learning and artificial intelligence to ensure creating the "wow" effect on consumers. The Association of Computing Machinery task force on Data Science program states that" Data scientists should be able to implement and understand algorithms for data collection and analysis. They should understand the time and space considerations of algorithms. They should follow good design principles developing software, understanding the importance of those principles for testability and maintainability" However, this definition hides the user behind the machine who works on data preparation, algorithm selection and model interpretation. Thus, the Data Science program includes design thinking to ensure meeting the user demands, generating more usable machine learning tools, and developing ways of framing computational thinking. Here, describe the fundamentals of Design-Thinking and teaching modules for data science programs.

Keywords: data science, design thinking, AI, currculum, transformation

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Authors: Marc Sango, Olimpia Hoinaru, Christophe Gransart, Laurence Duchien

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Ontologies offer a means for representing and sharing information in many domains, particularly in complex domains. For example, it can be used for representing and sharing information of System Requirement Specification (SRS) of complex systems like the SRS of ERTMS/ETCS written in natural language. Since this system is a real-time and critical system, generic ontologies, such as OWL and generic ERTMS ontologies provide minimal support for modeling temporal information omnipresent in these SRS documents. To support the modeling of temporal information, one of the challenges is to enable representation of dynamic features evolving in time within a generic ontology with a minimal redesign of it. The separation of temporal information from other information can help to predict system runtime operation and to properly design and implement them. In addition, it is helpful to provide a reasoning and querying techniques to reason and query temporal information represented in the ontology in order to detect potential temporal inconsistencies. Indeed, a user operation, such as adding a new constraint on existing planning constraints can cause temporal inconsistencies, which can lead to system failures. To address this challenge, we propose a lightweight 3-layer temporal Quality of Service (QoS) ontology for representing, reasoning and querying over temporal and non-temporal information in a complex domain ontology. Representing QoS entities in separated layers can clarify the distinction between the non QoS entities and the QoS entities in an ontology. The upper generic layer of the proposed ontology provides an intuitive knowledge of domain components, specially ERTMS/ETCS components. The separation of the intermediate QoS layer from the lower QoS layer allows us to focus on specific QoS Characteristics, such as temporal or integrity characteristics. In this paper, we focus on temporal information that can be used to predict system runtime operation. To evaluate our approach, an example of the proposed domain ontology for handover operation, as well as a reasoning rule over temporal relations in this domain-specific ontology, are given.

Keywords: system requirement specification, ERTMS/ETCS, temporal ontologies, domain ontologies

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Authors: Henry Hexmoor, Kailash Yelasani

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We present vehicular platooning as a special case of crowd-sensing framework where sharing sensory information among a crowd is used for their collective benefit. After offering an abstract policy that governs processes involving a vehicular platoon, we review several common scenarios and components surrounding vehicular platooning. We then present a simulated prototype that illustrates efficiency of road usage and vehicle travel time derived from platooning. We have argued that one of the paramount benefits of platooning that is overlooked elsewhere, is the substantial computational savings (i.e., economizing benefits) in acquisition and processing of sensory data among vehicles sharing the road. The most capable vehicle can share data gathered from its sensors with nearby vehicles grouped into a platoon.

Keywords: cloud network, collaboration, internet of things, social network

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Authors: Panagiota Katsikouli, William Hamilton Byrne, Thomas Gammeltoft-Hansen, Tijs Slaats

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An individual who demonstrates a well-founded fear of persecution or faces real risk of being subjected to torture is eligible for asylum. In Danish law, the exact legal thresholds reflect those established by international conventions, notably the 1951 Refugee Convention and the 1950 European Convention for Human Rights. These international treaties, however, remain largely silent when it comes to how states should assess asylum claims. As a result, national authorities are typically left to determine an individual’s legal eligibility on a narrow basis consisting of an oral testimony, which may itself be hampered by several factors, including imprecise language interpretation, insecurity or lacking trust towards the authorities among applicants. The leaky ground, on which authorities must assess their subjective perceptions of asylum applicants' credibility, questions whether, in all cases, adjudicators make the correct decision. Moreover, the subjective element in these assessments raises questions on whether individual asylum cases could be afflicted by implicit biases or stereotyping amongst adjudicators. In fact, recent studies have uncovered significant correlations between decision outcomes and the experience and gender of the assigned judge, as well as correlations between asylum outcomes and entirely external events such as weather and political elections. In this study, we analyze a publicly available dataset containing approximately 8,000 summaries of asylum cases, initially rejected, and re-tried by the Refugee Appeals Board (RAB) in Denmark. First, we look for variations in the recognition rates, with regards to a number of applicants’ features: their country of origin/nationality, their identified gender, their identified religion, their ethnicity, whether torture was mentioned in their case and if so, whether it was supported or not, and the year the applicant entered Denmark. In order to extract those features from the text summaries, as well as the final decision of the RAB, we applied natural language processing and regular expressions, adjusting for the Danish language. We observed interesting variations in recognition rates related to the applicants’ country of origin, ethnicity, year of entry and the support or not of torture claims, whenever those were made in the case. The appearance (or not) of significant variations in the recognition rates, does not necessarily imply (or not) bias in the decision-making progress. None of the considered features, with the exception maybe of the torture claims, should be decisive factors for an asylum seeker’s fate. We therefore investigate whether the decision can be predicted on the basis of these features, and consequently, whether biases are likely to exist in the decisionmaking progress. We employed a number of machine learning classifiers, and found that when using the applicant’s country of origin, religion, ethnicity and year of entry with a random forest classifier, or a decision tree, the prediction accuracy is as high as 82% and 85% respectively. tentially predictive properties with regards to the outcome of an asylum case. Our analysis and findings call for further investigation on the predictability of the outcome, on a larger dataset of 17,000 cases, which is undergoing.

Keywords: asylum adjudications, automated decision-making, machine learning, text mining

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Authors: Zahid Ahmad, Nosheen Imran, Nauman Ali, Farah Amir

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The objective of the study is to forecast the US Dollar and Pak Rupee exchange rate by using time series models. For this purpose, daily exchange rates of US and Pakistan for the period of January 01, 2007 - June 2, 2017, are employed. The data set is divided into in sample and out of sample data set where in-sample data are used to estimate as well as forecast the models, whereas out-of-sample data set is exercised to forecast the exchange rate. The ADF test and PP test are used to make the time series stationary. To forecast the exchange rate ARIMA model and GARCH model are applied. Among the different Autoregressive Integrated Moving Average (ARIMA) models best model is selected on the basis of selection criteria. Due to the volatility clustering and ARCH effect the GARCH (1, 1) is also applied. Results of analysis showed that ARIMA (0, 1, 1 ) and GARCH (1, 1) are the most suitable models to forecast the future exchange rate. Further the GARCH (1,1) model provided the volatility with non-constant conditional variance in the exchange rate with good forecasting performance. This study is very useful for researchers, policymakers, and businesses for making decisions through accurate and timely forecasting of the exchange rate and helps them in devising their policies.

Keywords: exchange rate, ARIMA, GARCH, PAK/USD

Procedia PDF Downloads 566