Search results for: decision support technique

Authors: Hussah Alotaishan

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In today’s globally-driven modern cities diverse groups of new visitors face various challenges when attempting to find their desired location if culture and language are barriers. The most common way-showing tools such as directional and identificational signs are the most problematic and their usefulness can be limited or even non-existent. It is argued new methods should be implemented that could support or replace such conventional literacy and language dependent way-finding aids. It has been concluded in recent research studies that local urban features in complex pedestrian spaces are worthy of further study in order to reveal if they do function as way-showing clues. Some researchers propose a more comprehensive approach to the complex perception of buildings, façade design and surface patterns, while some have been questioning whether we necessarily need directional signs or can other methods deliver the same message but in a clearer manner for a wider range of users. This study aimed to test to what extent do existent environmental and urban features through the city center area of Swansea in the UK facilitate the way-finding process of a first time visitor. The three-hour experiment was set to attempt to find 11 visitor attractions ranging from recreational, historical, educational and religious locations. The challenge was attempting to find as many as possible when no prior geographical knowledge of their whereabouts was established. The only clues were 11 pictures representing each of the locations that had been acquired from the city of Swansea official website. An iPhone and a heart-rate tracker wristwatch were used to record the route was taken and stress levels, and take record photographs of destinations or decision-making points throughout the journey. This paper addresses: current limitations in understanding the ways that the physical environment can be intentionally deployed to facilitate pedestrians while finding their way around, without or with a reduction in language dependent signage; investigates visitor perceptions of their surroundings by indicating what urban elements manifested an impact on the way-finding process. The initial findings support the view that building facades and street features, such as width, could facilitate the decision-making process if strategically employed. However, more importantly, the anticipated features of a specific place construed from a promotional picture can also be misleading and create confusion that may lead to getting lost.

Keywords: pedestrian way-finding, environmental features, urban way-showing, environmental affordance

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Authors: Maria Areias, Diogo Simões, Ana Figueiredo, Anishur Rahman, Filipa Figueiredo, João Nunes

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It is expected that close to 7 billion people will live in urban areas by 2050. In order to improve the sustainability of the territories and its transition towards circular economy, it’s necessary to understand its metabolism and promote and guide the entrepreneurship answer. The study of a macroeconomic metabolism involves the quantification of the inputs, outputs and storage of energy, water, materials and wastes for an urban region. This quantification and analysis representing one opportunity for the promotion of green entrepreneurship. There are several methods to assess the environmental impacts of an urban territory, such as human and environmental risk assessment (HERA), life cycle assessment (LCA), ecological footprint assessment (EF), material flow analysis (MFA), physical input-output table (PIOT), ecological network analysis (ENA), multicriteria decision analysis (MCDA) among others. However, no consensus exists about which of those assessment methods are best to analyze the sustainability of these complex systems. Taking into account the weaknesses and needs identified, the CiiM - Circular Innovation Inter-Municipality project aims to define an uniform and globally accepted methodology through the integration of various methodologies and dynamic approaches to increase the efficiency of macroeconomic metabolisms and promoting entrepreneurship in a circular economy. The pilot territory considered in CiiM project has a total area of 969,428 ha, comprising a total of 897,256 inhabitants (about 41% of the population of the Center Region). The main economic activities in the pilot territory, which contribute to a gross domestic product of 14.4 billion euros, are: social support activities for the elderly; construction of buildings; road transport of goods, retailing in supermarkets and hypermarkets; mass production of other garments; inpatient health facilities; and the manufacture of other components and accessories for motor vehicles. The region's business network is mostly constituted of micro and small companies (similar to the Central Region of Portugal), with a total of 53,708 companies identified in the CIM Region of Coimbra (39 large companies), 28,146 in the CIM Viseu Dão Lafões (22 large companies) and 24,953 in CIM Beiras and Serra da Estrela (13 large companies). For the construction of the database was taking into account data available at the National Institute of Statistics (INE), General Directorate of Energy and Geology (DGEG), Eurostat, Pordata, Strategy and Planning Office (GEP), Portuguese Environment Agency (APA), Commission for Coordination and Regional Development (CCDR) and Inter-municipal Community (CIM), as well as dedicated databases. In addition to the collection of statistical data, it was necessary to identify and characterize the different stakeholder groups in the pilot territory that are relevant to the different metabolism components under analysis. The CIIM project also adds the potential of a Geographic Information System (GIS) so that it is be possible to obtain geospatial results of the territorial metabolisms (rural and urban) of the pilot region. This platform will be a powerful visualization tool of flows of products/services that occur within the region and will support the stakeholders, improving their circular performance and identifying new business ideas and symbiotic partnerships.

Keywords: circular economy tools, life cycle assessment macroeconomic metabolism, multicriteria decision analysis, decision support tools, circular entrepreneurship, industrial and regional symbiosis

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Authors: Mikel Alonso López

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The early eighties saw the rise of a new research trend in several prestigious journals, mainly articles that related emotions with the decision-making processes of the consumer, and stopped treating them as external elements. That is why we ask questions such as: what are emotions? Are there different types of emotions? What components do they have? Which theories exist about them? In this study, we will review the main theories and components of emotion analysing the cognitive factor and the different emotional states that are generally recognizable with a focus in the classic debate as to whether they occur before the cognitive process or the affective process.

Keywords: emotion, consumer behaviour, feelings, decision making

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Authors: Yosep Chong, Yejin Kim, Jingyun Choi, Hwanjo Yu, Eun Jung Lee, Chang Suk Kang

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For the past decades, immunohistochemistry (IHC) has been playing an important role in the diagnosis of human neoplasms, by helping pathologists to make a clearer decision on differential diagnosis, subtyping, personalized treatment plan, and finally prognosis prediction. However, the IHC performed in various tumors of daily practice often shows conflicting and very challenging results to interpret. Even comprehensive diagnosis synthesizing clinical, histologic and immunohistochemical findings can be helpless in some twisted cases. Another important issue is that the IHC data is increasing exponentially and more and more information have to be taken into account. For this reason, we reached an idea to develop an expert supporting system to help pathologists to make a better decision in diagnosing human neoplasms with IHC results. We gave probabilistic decision tree algorithm and tested the algorithm with real case data of lymphoid neoplasms, in which the IHC profile is more important to make a proper diagnosis than other human neoplasms. We designed probabilistic decision tree based on Bayesian theorem, program computational process using MATLAB (The MathWorks, Inc., USA) and prepared IHC profile database (about 104 disease category and 88 IHC antibodies) based on WHO classification by reviewing the literature. The initial probability of each neoplasm was set with the epidemiologic data of lymphoid neoplasm in Korea. With the IHC results of 131 patients sequentially selected, top three presumptive diagnoses for each case were made and compared with the original diagnoses. After the review of the data, 124 out of 131 were used for final analysis. As a result, the presumptive diagnoses were concordant with the original diagnoses in 118 cases (93.7%). The major reason of discordant cases was that the similarity of the IHC profile between two or three different neoplasms. The expert supporting system algorithm presented in this study is in its elementary stage and need more optimization using more advanced technology such as deep-learning with data of real cases, especially in differentiating T-cell lymphomas. Although it needs more refinement, it may be used to aid pathological decision making in future. A further application to determine IHC antibodies for a certain subset of differential diagnoses might be possible in near future.

Keywords: database, expert supporting system, immunohistochemistry, probabilistic decision tree

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Authors: Teresa Leary Handy

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As awareness of the importance of diversity has increased in society, higher education has also begun to recognize the importance of supporting faculty of color. In the university setting, faculty women of color specifically encounter barriers that impact their level of job satisfaction, retention rates, and pedagogical practices. These barriers and challenges not only undermine faculty diversity efforts but also hinder the ability of colleges and universities to provide a supportive environment that fosters students' academic success and sense of belonging. Faculty who are marginalized and on the periphery in higher education institutions need support so that they can feel confident in building a student’s sense of belonging which can impact a student’s academic success and goal of earning a college degree. This study examined and sought to understand the importance of supporting faculty of color, specifically women faculty of color, and how this type of faculty support can impact student academic success and a student’s sense of belonging. The study furthered original research on strategies to move an institution forward on the equity spectrum to support belonging and inclusions as core culture elements.

Keywords: equity, inclusion, belonging, women, faculty support

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Authors: Preeti Nakhat, Neeta Sinha

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Career plays an indispensable role in shaping one’s outlook on life. Choosing right career adds 'feathers to the life' whereas wrong career decision 'takes a toll 'in one’s life. It is pivotal for the students to know the career opportunities related to their field where they can escalate and excel. With the aim to comprehend certainty and indecisiveness in career decision among college students, a study will be conducted. The study focuses to gain insight on decisiveness and indecisiveness of career among the students. The hypotheses for the study are (1) There is no relation between the medium of education (vernacular/English medium) and career decisiveness among the college students. (2) There is no relation between the faculty(science, commerce, arts)chosen and career decisiveness. (3)There is no relation between father’s qualification and career decisiveness. To test the aforementioned hypotheses, a survey questionnaire will be used. The questionnaire is 'Career decision scale' by Samuel H. Osipow. This study will include 200 college going students. The data will be collected from first, second, third, and fourth year students. Statistical analysis of the data collected with be done through SPSS/Excel calculation and then the hypotheses will be tested.

Keywords: career decisiveness, career indecisiveness, college students, career

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Authors: Guoqing Wang, Yanhua Zhao, Lina Zhang, Jingbin Bai, Ruican Zhu

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Friction stir welding with bobbin tool is a simple technique compared to conventional FSW since the backing fixture is no longer needed and assembling labor is reduced. It gets adopted more and more in the aerospace industry as a result. However, a post-weld problem, the left keyhole, has to be fixed by forced repair welding. To close the keyhole, the conventional fusion repair could be an option if the joint properties are not deteriorated; friction push plug welding, a forced repair, could be another except that a rigid support unit is demanded at the back of the weldment. Therefore, neither of the above ways is satisfaction in welding a large enclosed structure, like rocket propellant tank. Although friction pulls plug welding does not need a backing plate, the wide applications are still held back because of the disadvantages in respects of unappropriated tensile stress, (i.e. excessive stress causing neck shrinkage of plug that will bring about back defects while insufficient stress causing lack of heat input that will bring about face defects), complicated welding parameters (including rotation speed, transverse speed, friction force, welding pressure and upset)，short welding time (approx. 0.5 sec.), narrow windows and poor stability of process. In this research, an updated technique called inertia friction pull plug welding, and its equipment was developed. The influencing rules of technological parameters on joint properties of inertia friction pull plug welding were observed. The microstructure characteristics were analyzed. Based on the elementary performance data acquired, the conclusion is made that the uniform energy provided by an inertia flywheel will be a guarantee to a stable welding process. Meanwhile, due to the abandon of backing plate, the inertia friction pull plug welding is considered as a promising technique in repairing keyhole of bobbin tool FSW and point type defects of aluminium base material.

Keywords: defect repairing, equipment, inertia friction pull plug welding, technological parameters

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Authors: Florenda B. Cardinoza

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This study was conducted to determine the determinants of Grade III and grade VI pupils’ performance in the National Achievement Test in the Division of Cavite City, School Year 2011-2012. Specifically, the research aimed to: (1) describe the demographic profile of the respondents in terms of age, sex, birth order, family size, family income, and occupation of parents; (2) determine the level of attitude towards NAT; and (3) describe the degree of relationship between the following variables: school support, teachers’ support, and lastly family support for the pupils’ performance in 2012 NAT. The study used the descriptive-correlation research method to investigate the determinants of pupils’ performance in the National Achievement Test of Public Elementary Schools in the Division of Cavite City. The instrument used in data gathering was a self-structured survey. The NAT result for SY 2011-2012 provided by NETRC and DepEd Cavite City was also utilized. The statistical tools used to process and analyze the data were frequency distribution, percentage, mean, standard deviation, Kruskall Wallis, Mann-Whitney, t-test for independent samples, One-way ANOVA, and Spearman Rank Correlational Coefficient. Results revealed that there were more female students than males in the Division of Cavite City; out of 659 respondents, 345 were 11 years old and above; 390 were females; 283 were categorized as first child in the family; 371 of the respondents were from small family; 327 had Php5000 and below family income; 450 of the fathers’ respondents were non professionals; and 431 of the mothers respondents had no occupation. The attitude towards NAT, with a mean of 1.65 and SD of .485, shows that respondents considered NAT important. The school support towards NAT, with a mean of 1.89 and SD of .520, shows that respondents received school support. The pupils had a very high attitude towards teachers’ support in NAT with a mean of 1.60 and SD of .572. Family support, with t-test of 16.201 with a p-value of 0.006, shows significant at 5 percent level. Thus, the determinants of pupils’ performance in NAT in terms of family support for NAT preparation is not significant according to their family income. The grade level, with the t-test is 4.420 and a p-value of 0.000, is significant at 5 percent level. Therefore, the determinants of pupils’ performance in NAT in terms of grade level for NAT preparation vary according to their grade level. For the determinants of pupils’ performance of NAT sample test for attitude towards NAT, school support, teachers’ support, and family support were noted highly significant with a p value of 0.000.

Keywords: achievement, determinants, national, performance, public, pupils', test

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Authors: Muhammad Yousaf Sadiq

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The complexity arises in defining the construction quality due to its perception, based on inherent market conditions and their requirements, the diversified stakeholders itself and their desired output. An quantitative survey based approach was adopted in this constructive study. A questionnaire-based survey was conducted for the assessment of construction Quality perception and expectations in the context of quality improvement technique. The survey feedback of professionals of the leading construction organizations/companies of Pakistan construction industry were analyzed. The financial capacity, organizational structure, and construction experience of the construction firms formed basis for their selection. The quality perception was found to be project-scope-oriented and considered as an excess cost for a construction project. Any quality improvement technique was expected to maximize the profit for the employer, by improving the productivity in a construction project. The study is beneficial for the construction professionals to assess the prevailing construction quality perception and the expectations from implementation of any quality improvement technique in construction projects.

Keywords: construction quality, expectation, improvement, perception

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Authors: Helen Nelly Naiga, Christopher Garimoi Orach

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Introduction: Long-acting reversible contraceptive (LARC) methods are highly effective. However, LARC use in Uganda is low (13%). We assessed the factors associated with the use of long-acting reversible contraceptives among women of reproductive age (15-49 yrs) in Jinja District. Methods: We conducted a facility-based cross-sectional study. A total of 314 women aged 15–49 years attending public health facilities (1 hospital and 3 health center IV) in Jinja district, were randomly selected. A total of 6 key informants and 6 in-depth interviews were conducted. Logistic regression analysis was conducted using Stata version 14. Qualitative data were analysed using thematic analysis. Results: The study found that 40.45% of the respondents had ever used LARC. The commonest LARC method used was implanting (38.22%). The factors significantly associated with use of LARC were employment (AOR =2.91; 95% CI (1.05-8.08), access to LARC methods (AOR =4.48; 95% CI (1.24-16.21), husband support (AOR =4.90; 95% CI (1.56-15.41), and experience of no side effects (AOR =3.48; 95% CI (1.00-12.19). Conclusion and recommendations: The study showed that 4 in 10 women of reproductive age in Jinja District were using LARC. The factors associated with LARC use were employment, husband support, access to LARC methods, and the lack of side effects. There is a need to strengthen client education, improve accessibility to LARC methods at all levels of health centers, improve male partner’s decision-making in LARC use and manage the side effects effectively.

Keywords: family planning, implants, intrauterine device, long-acting reversible contraceptives (LARC)

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Authors: Birgit Reime, Sonja Gscheidle, Toni Hübener, Lara Hübener

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Suicide in individuals under 30 years is a global public health concern. The objective of this study was to identify strategies for the prevention of suicide and suicidal behavior preferred by adolescents and young adults who are vulnerable to suicidal behavior and by relevant experts. Using semi-structured interviews with n= 17 adolescents and young adults (18-25 years of age) and with n= 11 experts from relevant fields, we have applied an inductive approach and applied thematic content analysis. Six strategies for suicide prevention in young individuals were reported. These were digital solutions with appealing designs, anonymous support, trained peer support, spiritual support, improving existing structures, and raising suicide literacy. Accessibility of anonymous digital support may contribute to suicide prevention in young people.

Keywords: suicide prevention, adolescents, E-health, Germany

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Authors: Kasra Majbouri Yazdi, Adel Majbouri Yazdi, Saeid Khodayi, Jingyu Hou, Wanlei Zhou, Saeed Saedy

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Fake news and false information are big challenges of all types of media, especially social media. There is a lot of false information, fake likes, views and duplicated accounts as big social networks such as Facebook and Twitter admitted. Most information appearing on social media is doubtful and in some cases misleading. They need to be detected as soon as possible to avoid a negative impact on society. The dimensions of the fake news datasets are growing rapidly, so to obtain a better result of detecting false information with less computation time and complexity, the dimensions need to be reduced. One of the best techniques of reducing data size is using feature selection method. The aim of this technique is to choose a feature subset from the original set to improve the classification performance. In this paper, a feature selection method is proposed with the integration of K-means clustering and Support Vector Machine (SVM) approaches which work in four steps. First, the similarities between all features are calculated. Then, features are divided into several clusters. Next, the final feature set is selected from all clusters, and finally, fake news is classified based on the final feature subset using the SVM method. The proposed method was evaluated by comparing its performance with other state-of-the-art methods on several specific benchmark datasets and the outcome showed a better classification of false information for our work. The detection performance was improved in two aspects. On the one hand, the detection runtime process decreased, and on the other hand, the classification accuracy increased because of the elimination of redundant features and the reduction of datasets dimensions.

Keywords: clustering, fake news detection, feature selection, machine learning, social media, support vector machine

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Authors: Hiesik Kim, Yong-Beom Kim, Jaheon Gu

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Internet of Things (IoT) applications are widely serviced and spread worldwide. Local wireless data transmission technique must be developed to rate up with some technique. Bluetooth wireless data communication is wireless technique is technique made by Special Inter Group (SIG) using the frequency range 2.4 GHz, and it is exploiting Frequency Hopping to avoid collision with a different device. To implement experiment, equipment for experiment transmitting measured data is made by using Arduino as open source hardware, gas sensor, and Bluetooth module and algorithm controlling transmission rate is demonstrated. Experiment controlling transmission rate also is progressed by developing Android application receiving measured data, and controlling this rate is available at the experiment result. It is important that in the future, improvement for communication algorithm be needed because a few error occurs when data is transferred or received.

Keywords: Arduino, Bluetooth, gas sensor, IoT, transmission

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Authors: Jisun Mo, Paola Boarin

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The impact of common buildings on climate and environment has prompted people to get involved in the green building standards aimed at implementing rating tools or certifications. Thus, green building rating systems were introduced to the construction industry, and the demand for certified green buildings has increased gradually and succeeded considerably in enhancing people’s environmental awareness. However, the existing certification process has been unsatisfactory in attracting stakeholders and/or professionals who are actively engaged in adopting a rating system. It is because they have faced recurring barriers regarding limited information in understanding the rating process, time-consuming procedures and higher costs, which have a direct influence on pursuing green building rating systems. To promote the achievement of green building certifications within the building industry more successfully, this paper aims at designing a Pre-Assessment Tool (PAT) framework that can help stakeholders and/or professionals engaged in the construction industry to clarify their basic knowledge, timeframe and extra costs needed to activate a green building certification. First, taking the first steps towards the rating tool seems to be complicated because of upfront commitment to understanding the overall rating procedure is required. This conceptual PAT framework can increase basic knowledge of the rating tool and the certification process, mainly in terms of all resources or information of each credit requirements. Second, the assessment process of rating tools is generally known as a “lengthy and time-consuming system”, contributing to unenthusiastic reactions concerning green building projects. The proposed framework can predict the timeframe needed to identify how long it will take for a green project to process each credit requirement and the documentation required from the beginning of the certification process to final approval. Finally, most people often have the initial perception that pursuing green building certification costs more than constructing a non-green building, which makes it more difficult to execute rating tools. To overcome this issue, this PAT will help users to estimate the extra expenses such as certification fees and third-party contributions based on the track of the amount of time it takes to implement the rating tool throughout all the related stages. Also, it can prevent unexpected or hidden costs occurring in the process of assessment. Therefore, this proposed PAT framework can be recommended as an effective method to support the decision-making of inexperienced users and play an important role in promoting green building certification.

Keywords: green building rating tools, Pre-Occupancy Evaluation (PrOE), client’s decision-making, certification

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Authors: Siri-Orn Champatong

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The objectives of this research were to study the attitude of service marketing mix that affected the decision making behavior to use fitness service in case of the fitness in Thailand. This study employed by survey research and questionnaire was used to collect the data from 400 of consumers who have used the service and interested in using the service in the future. The descriptive statistics and multiple regression analysis were used to analyze data. The results revealed that the attitude toward overall marketing mix was at moderate level. For particulars, attitude toward product and service aspects were at good level, however, attitude toward price, place, promotion, people, physical evidence and service quality aspects were at moderate level. The hypothesis testing results showed that attitude toward each aspect affected word of mouth, however, attitude toward product and service, place, promotion, people and physical evidence affected tendency to use fitness service at .05 statistically significant level.

Keywords: decision making behavior, fitness, marketing mix, marketing service

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Authors: Humaira Mujeeb, Farah Qadir

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The present study aimed to explore the association between interpersonal relationship and postpartum depression with a special focus on gender of the infant among women in Gilgit, Gilgit-Baltistan, Pakistan. The research was quantitative in nature. It was a correlation study with a cross-sectional study design. The target population was women between six weeks to six months after the delivery of a baby. The sample size of 158 women has been computed by using G*Power (3.0.10 version). The sample was taken through quota sampling technique which was used to gather data according to the specifically predefined groups (79 women with female infants and 79 women with male infants). The sample was selected non-randomly according to the fixed quota. A protocol which had demographic and interpersonal relationship variables alongside with the Urdu version Edinburgh postnatal depression scale was used to collect the relevant data. The data was analyzed by using SPSS 16.0 software package. A statistically significant association between the attachment with husband in women who had a female infant and postpartum depression has been found. The association between the husband’s emotional and physical support in women who had a female infant and postpartum depression had also been found significant. In case of women with a male infant, the association between support of in-laws and postpartum depression is statistically significant. An association between the violence/discrimination based on the basis of infant's gender in women who had a female infant and postpartum depression is also found. These findings points out that when studying the correlates of postpartum depression, it is imperative to carry out an analysis in the context of gender by considering gender of the infant especially in societies where strict gender preferences exists.

Keywords: infant, gender, attachment, husband, in-laws, support, violence, discrimination, Edinburgh postnatal depression scale, Gilgit, Pakistan

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Authors: Alanoud Moraya Aldalan, Abdulaziz Almaleh

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A crucial component of maintaining a customer-oriented business as in the telecom industry is understanding the reasons and factors that lead to customer churn. Competition between telecom companies has greatly increased in recent years. It has become more important to understand customers’ needs in this strong market of telecom industries, especially for those who are looking to turn over their service providers. So, predictive churn is now a mandatory requirement for retaining those customers. Machine learning can be utilized to accomplish this. Churn Prediction has become a very important topic in terms of machine learning classification in the telecommunications industry. Understanding the factors of customer churn and how they behave is very important to building an effective churn prediction model. This paper aims to predict churn and identify factors of customers’ churn based on their past service usage history. Aiming at this objective, the study makes use of feature selection, normalization, and feature engineering. Then, this study compared the performance of four different machine learning algorithms on the Orange dataset: Logistic Regression, Random Forest, Decision Tree, and Gradient Boosting. Evaluation of the performance was conducted by using the F1 score and ROC-AUC. Comparing the results of this study with existing models has proven to produce better results. The results showed the Gradients Boosting with feature selection technique outperformed in this study by achieving a 99% F1-score and 99% AUC, and all other experiments achieved good results as well.

Keywords: machine learning, gradient boosting, logistic regression, churn, random forest, decision tree, ROC, AUC, F1-score

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Authors: Sabrina Neururer, Marco Schweitzer, Werner Hackl, Bernhard Tilg, Patrick Raudaschl, Andreas Huber, Bernhard Pfeifer

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History and the current outbreak of Covid-19 have shown the deadly potential of infectious diseases. However, infectious diseases also have a serious impact on areas other than health and healthcare, such as the economy or social life. These areas are strongly codependent. Therefore, disease control measures, such as social distancing, quarantines, curfews, or lockdowns, have to be adopted in a very considerate manner. Infectious disease modeling can support policy and decision-makers with adequate information regarding the dynamics of the pandemic and therefore assist in planning and enforcing appropriate measures that will prevent the healthcare system from collapsing. In this work, an agent-based simulation package named “survival” for simulating infectious diseases is presented. A special focus is put on SARS-Cov-2. The presented simulation package was used in Austria to model the SARS-Cov-2 outbreak from the beginning of 2020. Agent-based modeling is a relatively recent modeling approach. Since our world is getting more and more complex, the complexity of the underlying systems is also increasing. The development of tools and frameworks and increasing computational power advance the application of agent-based models. For parametrizing the presented model, different data sources, such as known infections, wastewater virus load, blood donor antibodies, circulating virus variants and the used capacity for hospitalization, as well as the availability of medical materials like ventilators, were integrated with a database system and used. The simulation result of the model was used for predicting the dynamics and the possible outcomes and was used by the health authorities to decide on the measures to be taken in order to control the pandemic situation. The survival package was implemented in the programming language Java and the analytics were performed with R Studio. During the first run in March 2020, the simulation showed that without measures other than individual personal behavior and appropriate medication, the death toll would have been about 27 million people worldwide within the first year. The model predicted the hospitalization rates (standard and intensive care) for Tyrol and South Tyrol with an accuracy of about 1.5% average error. They were calculated to provide 10-days forecasts. The state government and the hospitals were provided with the 10-days models to support their decision-making. This ensured that standard care was maintained for as long as possible without restrictions. Furthermore, various measures were estimated and thereafter enforced. Among other things, communities were quarantined based on the calculations while, in accordance with the calculations, the curfews for the entire population were reduced. With this framework, which is used in the national crisis team of the Austrian province of Tyrol, a very accurate model could be created on the federal state level as well as on the district and municipal level, which was able to provide decision-makers with a solid information basis. This framework can be transferred to various infectious diseases and thus can be used as a basis for future monitoring.

Keywords: modelling, simulation, agent-based, SARS-Cov-2, COVID-19

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Authors: Matthew Fleet, Savannah Elliott

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Background: This study investigates the use of teaching and learning to meet the needs of deaf children in the UK PE curriculum. Research has illustrated that deaf students in mainstream schools do not receive sufficient support from teachers in lessons. This research examines the impact of different types of hearing loss and its implications within Physical Education (PE) in secondary schools. Purpose: The purpose of this study is to highlight challenges PE teachers face and make recommendations for more inclusive learning environments for deaf students. The aims and objectives of this research are: to critically analyse the current situation for deaf students accessing the PE curriculum, by identifying barriers deaf students face; to identify the challenges for PE teachers in providing appropriate support for deaf students; to provide recommendations for deaf awareness training, to enhance PE teachers’ understanding and knowledge. Method: Semi-structured interviews collected data from both PE teachers and deaf students, to examine: the support available and coping mechanisms deaf students use when they do not receive support; strategies PE teachers use to provide support for deaf students; areas for improvement and potential strategies PE teachers can apply to their practice. Results & Conclusion: The findings from the study concluded that PE teachers were inconsistent in providing appropriate support for deaf students in PE lessons. Evidence illustrated that PE teachers had limited exposure to deaf awareness training. This impacted on their ability to support deaf students effectively. Communication was a frequent barrier for deaf students, affecting their ability to retain and learn information. Also, the use of assistive technology was found to be compromised in practical PE lessons.

Keywords: physical education, deaf, inclusion, education

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Authors: Souha Bouagila, Soufiene Ilahi

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Photothermal deflection technique PTD have been employed to study the impact of thermal annealing on minority carrier in GaInAsSb grown on GaSb substarte, which used as an active layer for Vertical Cavity Surface Emitting laser (VCSEL). Photothermal defelction technique is nondescructive and accurate technique for electronics parameters determination. The measure of non-radiative recombination, electronic diffusivity, surface and interface recombination are effectuated by fitting the theoretical PTD signal to the experimental ones. As a results, we have found that Non-radiative lifetime increases from 3.8 µs (± 3, 9 %) for not annealed GaInAsSb to the 7.1 µs (± 5, 7%). In fact, electronic diffusivity D increased from 60.1 (± 3.9 %) to 89.6 cm2 / s (± 2.7%) for the as grown to that annealed for 60 min respectively. We have remarked that surface recombination velocity (SRV) decreases from 7963 m / s (± 6.3%) to 1450 m / s (± 3.6).

Keywords: nonradiative lifetime, mobility of minority carrier, diffusion length, Surface and interface recombination velocity.GaInAsSb active layer

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Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

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The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

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Authors: Walaa M.Abd-Elhafiez, Wajeb Gharibi

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In this paper a novel color image compression technique for efficient storage and delivery of data is proposed. The proposed compression technique started by RGB to YCbCr color transformation process. Secondly, the canny edge detection method is used to classify the blocks into edge and non-edge blocks. Each color component Y, Cb, and Cr compressed by discrete cosine transform (DCT) process, quantizing and coding step by step using adaptive arithmetic coding. Our technique is concerned with the compression ratio, bits per pixel and peak signal to noise ratio, and produce better results than JPEG and more recent published schemes (like, CBDCT-CABS and MHC). The provided experimental results illustrate the proposed technique which is efficient and feasible in terms of compression ratio, bits per pixel and peak signal to noise ratio.

Keywords: image compression, color image, q-coder, quantization, edge-detection

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Authors: S. Alyami, S. Mohammad

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These Risk management practices have a significant impact on construction SMEs. The effective utilisation of these practices depends on culture change in order to optimise decision making for critical activities within construction projects. Thus, successful implementation of empowerment strategies would enhance operational employees to participate in effective decision making. However, there remain many barriers to individuals and organisations within empowerment strategies that require empirical investigation before the industry can benefit from their implementation. Gaps in understanding the relationship between employee empowerment and risk management practices still exist. This research paper aims to examine the impact of the structural empowerment on risk management practices in construction SMEs. The questionnaire has been distributed to participants (162 employees) that involve projects and civil engineers within a case study from Saudi construction SMEs. Partial least squares based structural equation modeling (PLS-SEM) was utilised to perform analysis. The results reveal a positive relationship between empowerment and risk management practices. The study shows how structural empowerment contributes to operational employees in risk management practices through involving activities such as decision making, self-efficiency, and autonomy. The findings of this study will contribute to close the current gaps in the construction SMEs context.

Keywords: construction SMEs, culture, decision making, empowerment, risk management

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Authors: Martha E. Aguiar-Barrera, Humberto Gutierrez-Pulido, Veronica Vargas-Alejo

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Identifying and modeling random phenomena is a fundamental cognitive process to understand and transform reality. Recognizing situations governed by chance and giving them a scientific interpretation, without being carried away by beliefs or intuitions, is a basic training for citizens. Hence the importance of generating teaching-learning processes, supported using technology, paying attention to model creation rather than only executing mathematical calculations. In order to develop the student's knowledge about basic probability distributions and decision making; in this work a model eliciting activity (MEA) is reported. The intention was applying the Model and Modeling Perspective to design an activity related to civil engineering that would be understandable for students, while involving them in its solution. Furthermore, the activity should imply a decision-making challenge based on sample data, and the use of the computer should be considered. The activity was designed considering the six design principles for MEA proposed by Lesh and collaborators. These are model construction, reality, self-evaluation, model documentation, shareable and reusable, and prototype. The application and refinement of the activity was carried out during three school cycles in the Probability and Statistics class for Civil Engineering students at the University of Guadalajara. The analysis of the way in which the students sought to solve the activity was made using audio and video recordings, as well as with the individual and team reports of the students. The information obtained was categorized according to the activity phase (individual or team) and the category of analysis (sample, linearity, probability, distributions, mechanization, and decision-making). With the results obtained through the MEA, four obstacles have been identified to understand and apply the binomial distribution: the first one was the resistance of the student to move from the linear to the probabilistic model; the second one, the difficulty of visualizing (infering) the behavior of the population through the sample data; the third one, viewing the sample as an isolated event and not as part of a random process that must be viewed in the context of a probability distribution; and the fourth one, the difficulty of decision-making with the support of probabilistic calculations. These obstacles have also been identified in literature on the teaching of probability and statistics. Recognizing these concepts as obstacles to understanding probability distributions, and that these do not change after an intervention, allows for the modification of these interventions and the MEA. In such a way, the students may identify themselves the erroneous solutions when they carrying out the MEA. The MEA also showed to be democratic since several students who had little participation and low grades in the first units, improved their participation. Regarding the use of the computer, the RStudio software was useful in several tasks, for example in such as plotting the probability distributions and to exploring different sample sizes. In conclusion, with the models created to solve the MEA, the Civil Engineering students improved their probabilistic knowledge and understanding of fundamental concepts such as sample, population, and probability distribution.

Keywords: linear model, models and modeling, probability, randomness, sample

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Authors: Tamara Trček Pečak, Andrej Mohar, Denis Trček

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This article investigates the latest technological means, which deploy smart structures that are based on (advanced) wireless sensors technologies and ubiquitous computing in general in order to support the above mentioned decision making. Based on two years of in-field research experiences it gives their analysis for these kinds of purposes and provides appropriate architectures and architectural solutions. Moreover, the directions for future research are stated, because these technologies are currently the most promising ones to enable cost-effective preservation of cultural heritage not only in uncontrolled places, but also in general.

Keywords: smart structures, wireless sensors, sensors networks, green computing, cultural heritage preservation, monitoring, cost effectiveness

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Authors: Guldana Zhigerbayeva, Ming Yang

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Transportation of hazardous materials (HAZMAT) is inevitable in the process industries. The statistics show a significant number of accidents has occurred during the transportation of HAZMAT. This makes risk management of HAZMAT transportation an important topic. The tree-based methods including fault-trees, event-trees and cause-consequence analysis, and Bayesian network, have been applied to risk management of HAZMAT transportation. However, there is limited work on the development of a systematic approach. The existing approaches fail to build up the linkages between the regulatory requirements and the safety measures development. The analysis of historical data from the past accidents’ report databases would limit our focus on the specific incidents and their specific causes. Thus, we may overlook some essential elements in risk management, including regulatory compliance, field expert opinions, and suggestions. A systematic approach is needed to translate the regulatory requirements of HAZMAT transportation into specified safety measures (both technical and administrative) to support the risk management process. This study aims to first adapt the House of Quality (HoQ) to House of Safety (HoS) and proposes a new approach- Safety Function Deployment (SFD). The results of SFD will be used in a multi-criteria decision-support system to develop find an optimal route for HazMats transportation. The proposed approach will be demonstrated through a hypothetical transportation case in Kazakhstan.

Keywords: hazardous materials, risk assessment, risk management, quality function deployment

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Authors: Bidzina Matsaberidze, Anna Sikharulidze, Gia Sirbiladze, Bezhan Ghvaberidze

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In the modern world emergency management decision support systems are actively used by state organizations, which are interested in extreme and abnormal processes and provide optimal and safe management of supply needed for the civil and military facilities in geographical areas, affected by disasters, earthquakes, fires and other accidents, weapons of mass destruction, terrorist attacks, etc. Obviously, these kinds of extreme events cause significant losses and damages to the infrastructure. In such cases, usage of intelligent support technologies is very important for quick and optimal location-transportation of emergency service in order to avoid new losses caused by these events. Timely servicing from emergency service centers to the affected disaster regions (response phase) is a key task of the emergency management system. Scientific research of this field takes the important place in decision-making problems. Our goal was to create an expert knowledge-based intelligent support system, which will serve as an assistant tool to provide optimal solutions for the above-mentioned problem. The inputs to the mathematical model of the system are objective data, as well as expert evaluations. The outputs of the system are solutions for Fuzzy Multi-Objective Emergency Location-Transportation Problem (FMOELTP) for disasters’ regions. The development and testing of the Intelligent Support System were done on the example of an experimental disaster region (for some geographical zone of Georgia) which was generated using a simulation modeling. Four objectives are considered in our model. The first objective is to minimize an expectation of total transportation duration of needed products. The second objective is to minimize the total selection unreliability index of opened humanitarian aid distribution centers (HADCs). The third objective minimizes the number of agents needed to operate the opened HADCs. The fourth objective minimizes the non-covered demand for all demand points. Possibility chance constraints and objective constraints were constructed based on objective-subjective data. The FMOELTP was constructed in a static and fuzzy environment since the decisions to be made are taken immediately after the disaster (during few hours) with the information available at that moment. It is assumed that the requests for products are estimated by homeland security organizations, or their experts, based upon their experience and their evaluation of the disaster’s seriousness. Estimated transportation times are considered to take into account routing access difficulty of the region and the infrastructure conditions. We propose an epsilon-constraint method for finding the exact solutions for the problem. It is proved that this approach generates the exact Pareto front of the multi-objective location-transportation problem addressed. Sometimes for large dimensions of the problem, the exact method requires long computing times. Thus, we propose an approximate method that imposes a number of stopping criteria on the exact method. For large dimensions of the FMOELTP the Estimation of Distribution Algorithm’s (EDA) approach is developed.

Keywords: epsilon-constraint method, estimation of distribution algorithm, fuzzy multi-objective combinatorial programming problem, fuzzy multi-objective emergency location/transportation problem

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Authors: Tracey Estriplet-Adams

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This paper focuses on the influence of maternal-fetal bonding by examining attachment theory, psycho-social-cultural influences/adaptations, and maternal well-being. A systematic review methodology was used to synthesize research results to summarize current evidence that can contribute to evidence-based practices. It explores the relationship between attachment styles, prenatal attachment, and perceptions of maternal-infant bonding/attachment six weeks postpartum. It also examines the protective factors of maternal-fetal attachment development. The research explores Bowlby's attachment theory and its relevance to maternal-fetal bonding with a Black Feminist Theory lens. Additionally, it discusses the impact of perceived stress, social support, and ecological models on maternal-fetal attachment. The relationship between maternal well-being, maternal-fetal attachment, and early postpartum bonding is reviewed. Moreover, the paper specifically addresses black mothers and maternal-fetal bonding, exploring the intersectionality of race, ethnicity, class, geographic location, cultural identities, and immigration status. It considers the role of familial and partner support, as well as the relationship between maternal attachment style and maternal-fetal bonding, within the framework of attachment theory and black feminist theory. Therefore, it is imperative to center Black women's voices in research, policy, and healthcare practices. Black women are experts in their own experiences and advocate for their autonomy in decision-making regarding maternal-fetal health. By amplifying their voices, we can ensure that interventions are grounded in their lived experiences.

Keywords: maternal-fetal bonding, infant well-being, maternal-infant attachment, black mothers

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Authors: Ritesh K. Shukla

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Degradation of biological samples in terms of macromolecules (DNA, RNA, and protein) are the major challenges in the forensic investigation which misleads the result interpretation. Currently, there are no precise methods available to circumvent this problem. Therefore, at the preliminary level, some methods are urgently needed to solve this issue. In this order, Comet assay is one of the most versatile, rapid and sensitive molecular biology technique to assess the DNA degradation. This technique helps to assess DNA degradation even at very low amount of sample. Moreover, the expedient part of this method does not require any additional process of DNA extraction and isolation during DNA degradation assessment. Samples directly embedded on agarose pre-coated microscopic slide and electrophoresis perform on the same slide after lysis step. After electrophoresis microscopic slide stained by DNA binding dye and observed under fluorescent microscope equipped with Komet software. With the help of this technique extent of DNA degradation can be assessed which can help to screen the sample before DNA fingerprinting, whether it is appropriate for DNA analysis or not. This technique not only helps to assess degradation of DNA but many other challenges in forensic investigation such as time since deposition estimation of biological fluids, repair of genetic material from degraded biological sample and early time since death estimation could also be resolved. With the help of this study, an attempt was made to explore the application of well-known molecular biology technique that is Comet assay in the field of forensic science. This assay will open avenue in the field of forensic research and development.

Keywords: comet assay, DNA degradation, forensic, molecular biology

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Authors: Guoqian Ren, Haijiang Li, Jisong Zhang

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Over the past 40 years, urban development has undergone large-scale, high-speed expansion, beyond what was previously considered normal and in a manner not proportionally related to population growth or physical considerations. With more scientific and refined decision-making in the urban construction process, new urbanization approaches, aligned with public-private partnerships (PPPs) which evolved in the early 1990s, have become acceptable and, in some situations, even better solutions to outstanding urban municipal construction projects, especially in developing countries. However, as the main driving force to deal with urban public services, PPPs are still problematic regarding value for money (VFM) process in most large-scale construction projects. This paper therefore reviews recent PPP articles in popular project management journals and relevant toolkits, published in the last 10 years, to identify the indicators that influence VFM within PPPs across regions. With increasing concerns about profitability and environmental and social impacts, the current PPP structure requires a more integrated platform to manage multi-performance project life cycles. Building information modelling (BIM), a popular approach to the procurement process in AEC sectors, provides the potential to ensure VFM while also working in tandem with the semantic approach to holistically measure life cycle costs (LCC) and achieve better sustainability. This paper suggests that BIM applied to the entire PPP life cycle could support holistic decision-making regarding VFM processes and thus meet service targets.

Keywords: public-private partnership, value for money, building information modelling, semantic approach

Procedia PDF Downloads 209