Search results for: selection of support tenants

Authors: Adheesh Budree, Olaf Jacob, Louis CH Fourie, James Njenga, Gabriel D Hoffman

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Business Intelligence (BI) is implemented by organisations for many reasons and chief among these is improved data support, decision support and savings. The main purpose of this study is to determine BI requirements and availability within South African organisations. The study addresses the following areas as identified as part of a literature review; assessing BI practices in businesses over a range of industries, sectors and managerial functions, determining the functionality of BI (technologies, architecture and methods). It was found that the overall satisfaction with BI in larger organisations is low due to lack of ability to meet user requirements.

Keywords: business intelligence, business value, data management, South Africa

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Authors: Martin Lauzier, Benjamin Lafreniere-Carrier, Nathalie Delobbe

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Supervisor support is one of the main levers to foster transfer of training. Although past and current studies voice its effects, few have sought to identify the factors that may explain why supervisors offer support to their subordinates when they return from training. Based on Goal Orientation Theory and following the principles of supportive supervision, this study aims to improve our understanding of the factors that influence supervisors’ involvement in the transfer process. More specifically, this research seeks to verify the influence of supervisors’ goal orientation on the adoption of post-training support behaviors. This study also assesses the mediating role of the supervisors’ interest in subordinates’ development on this first relationship. Conducted in two organizations (Canadian: N₁ = 292; Belgian: N₂ = 80), the results of this study revealed three main findings. First, supervisors’ who adopt learning mastery goal orientation also tend to adopt more post-training supportive behaviors. Secondly, regression analyses (using the bootstrap method) show that supervisors' interest in developing their subordinates’ skills mediate the relationship between supervisors’ goal orientation and post-training supportive behaviors. Thirdly, the observed mediation effects are consistent in both samples, regardless of supervisors’ gender or age. Overall, this research is part of the limited number of studies that have focused on the determining factors supervisors’ involvement in the learning transfer process.

Keywords: supervisor support, transfer of training, goal orientation, interest in the development of subordinates’ skills

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Authors: Bianca Price, Jennifer Stokes

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Academic and social support systems are critical for students in enabling education; these support systems have the potential to enhance the student experience whilst also serving a vital role for student retention. In the context of international moves toward widening university participation, Australia has developed enabling programs designed to support underrepresented students to access to higher education. The purpose of this study is to examine the effectiveness of a mentor program based within an enabling course. This study evaluates how the mentor program supports new students to develop social networks, improve retention, and increase satisfaction with the student experience. Guided by Social Learning Theory (SLT), this study highlights the benefits that can be achieved when students engage in peer-to-peer based mentoring for both social and learning support. Whilst traditional peer mentoring programs are heavily based on face-to-face contact, the present study explores the difference between mentors who provide face-to-face mentoring, in comparison with mentoring that takes place through the virtual space, specifically via a virtual community in the shape of a Facebook group. This paper explores the differences between these two methods of mentoring within an enabling program. The first method involves traditional face-to-face mentoring that is provided by alumni students who willingly return to the learning community to provide social support and guidance for new students. The second method requires alumni mentor students to voluntarily join a Facebook group that is specifically designed for enabling students. Using this virtual space, alumni students provide advice, support and social commentary on how to be successful within an enabling program. Whilst vastly different methods, both of these mentoring approaches provide students with the support tools needed to enhance their student experience and improve transition into University. To evaluate the impact of each mode, this study uses mixed methods including a focus group with mentors, in-depth interviews, as well as engaging in netnography of the Facebook group ‘Wall’. Netnography is an innovative qualitative research method used to interpret information that is available online to better understand and identify the needs and influences that affect the users of the online space. Through examining the data, this research will reflect upon best practice for engaging students in enabling programs. Findings support the applicability of having both face-to-face and online mentoring available for students to assist enabling students to make a positive transition into University undergraduate studies.

Keywords: enabling education, mentoring, netnography, social learning theory

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Authors: Reshma Parvin Nuri, Heather Michelle Aldersey, Setareh Ghahari

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Objectives: Worldwide, it is well known that taking care of children with disabilities (CWD) can have a significant impact on the entire family unit. Over the last few decades, an increased number of studies have been conducted on families of CWD in higher income countries, and much of this research has identified family needs and strategies to meet those needs. However, family needs are incredibly under-studied in developing countries. Therefore, the aims of this study were to: (a) explore the needs of families of children with cerebral palsy (CP) in Bangladesh; (b) investigate how some of the family needs have been met and (c) identify the sources of supports that might help the families to meet their needs in the future. Methods: A face to face, semi-structured in-depth interview was conducted with 20 family members (12 mothers, 4 fathers, 1 sister, 2 grandmothers, and 1 aunt) who visited the Centre for the Rehabilitation of the Paralysed (CRP), Bangladesh between June and August 2016. Constant comparison method of grounded theory approach within the broader spectrum of qualitative study was used to analyze the data. Results: Participants identified five categories of needs: (a) financial needs, (b) access to disability-related services, (c) family and community cohesion, (d) informational needs, and (e) emotional needs. Participants overwhelmingly reported that financial need is their greatest family need. Participants noted that families encountered additional financial expenses for a child with CP, beyond what they would typically pay for their other children. Participants were seeing education as their non-primary need as they had no hope that their children would be physically able to go to school. Some participants also shared their needs for social inclusion and participation and receiving emotional support. Participants further expressed needs to receive information related to the child’s health condition and availability/accessibility of governmental support programs. Besides unmet needs, participants also highlighted that some of their needs have been met through formal and informal support systems. Formal support systems were mainly institution-based and run by non-governmental organizations, whereas participants identified informal support coming from family, friends and community members. Participants overwhelmingly reported that they receive little to no support from the government. However, participants identified the government as the key stakeholder who can play vital role in meeting their unmet needs. Conclusions: In the next phase of this research, the plan is to understand how the Government of the People’s Republic of Bangladesh is working to meet the needs of families of CWD. There is also need for further study on needs of families of children with conditions other than CP and those who live in the community and do not have access to the CRP Services. There is clear need to investigate ways to enable children with CP have better access to education in Bangladesh.

Keywords: Bangladesh, children with cerebral palsy, family needs, support

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Authors: Abdulaziz Omar Alsadhan, Mohd Mudasir Shafi

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Performance testing is done to prove the reliability of any software product. There are a number of tools available in the markets that are used to perform performance testing. In this paper we present a comparative study of the three most commonly used performance testing tools. These tools cover the major share of the performance testing market and are widely used. In this paper we compared the tools on five evaluation parameters which are; User friendliness, portability, tool support, compatibility and cost. The conclusion provided at the end of the paper is based on our study and does not support any tool or company.

Keywords: software development, software testing, quality assurance, performance testing, load runner, rational testing, silk performer

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Authors: Gehad S. Kaseb, Mona F. Ahmed

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Arabic Sentiment Analysis (SA) is one of the most common research fields with many open areas. Few studies apply SA to Arabic dialects. This paper proposes different pre-processing steps and a modified methodology to improve the accuracy using normal Support Vector Machine (SVM) classification. The paper works on two datasets, Arabic Sentiment Tweets Dataset (ASTD) and Extended Arabic Tweets Sentiment Dataset (Extended-AATSD), which are publicly available for academic use. The results show that the classification accuracy approaches 86%.

Keywords: Arabic, classification, sentiment analysis, tweets

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Authors: Sunanta Klibthong

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In view of the Thailand government policy creating increasing awareness of opportunity for children with special needs, the number of children with disabilities enrolled in kindergartens in Thailand has increased. This study explores early childhood teachers’ experiences and concerns of teaching children with disabilities in inclusive classrooms. The population of the study was private early childhood teachers who teach in inclusive classrooms in Thailand. Quantitative data obtained through a questionnaire were supplemented by early childhood teachers’ interviews to identify key experiences and concerns of the teachers when teaching children with and without disabilities in the same classrooms. The results of this study indicated that many teachers face challenges including lack of professional development opportunities, difficulty identifying the needs of all children and how to use effective strategies to support inclusive practices in their classrooms. Teachers also expressed concern about parents’ lack of willingness to accept children without disabilities studying together with those with disabilities in the same classrooms. Findings from this study can inform program support for parents and professional support needs of teachers in the provision of high-quality inclusive programs for all students.

Keywords: the concern, early childhood, experience, inclusive education, Thailand

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Authors: R. O. Osaseri, A. R. Usiobaifo

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The power transformer which is responsible for the voltage transformation is of great relevance in the power system and oil-immerse transformer is widely used all over the world. A prompt and proper maintenance of the transformer is of utmost importance. The dissolved gasses content in power transformer, oil is of enormous importance in detecting incipient fault of the transformer. There is a need for accurate prediction of the incipient fault in transformer oil in order to facilitate the prompt maintenance and reducing the cost and error minimization. Study on fault prediction and diagnostic has been the center of many researchers and many previous works have been reported on the use of artificial intelligence to predict incipient failure of transformer faults. In this study machine learning technique was employed by using gradient decent algorithms and Support Vector Machine (SVM) in predicting incipient fault diagnosis of transformer. The method focuses on creating a system that improves its performance on previous result and historical data. The system design approach is basically in two phases; training and testing phase. The gradient decent algorithm is trained with a training dataset while the learned algorithm is applied to a set of new data. This two dataset is used to prove the accuracy of the proposed model. In this study a transformer fault diagnostic model based on Support Vector Machine (SVM) and gradient decent algorithms has been presented with a satisfactory diagnostic capability with high percentage in predicting incipient failure of transformer faults than existing diagnostic methods.

Keywords: diagnostic model, gradient decent, machine learning, support vector machine (SVM), transformer fault

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Authors: Ek-Uma Imkome, Jintana Yunibhand, Waraporn Chaiyawat

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Background: Persons with schizophrenia patient and misusing methamphetamines suffering from social dysfunction that impact on their quality of life. Knowledge of factors related to social dysfunction will guide the effective intervention. Objectives: To determine the direct effect, indirect effect and total effect of an acerbate Psychotics’ Symptoms, Social Support, Stressful life events, Medication use self-efficacy impact on social dysfunction in Thai schizophrenic patient and methamphetamine misuse. Methods: Data were collected from schizophrenic and methamphetamine misuse patient by self report. A linear structural relationship was used to test the hypothesized path model. Results: The hypothesized model was found to fit the empirical data and explained 54% of the variance of the psychotic symptoms (X² = 114.35, df = 92, p-value = 0.05, X² /df = 1.24, GFI = 0.96, AGFI = 0.92, CFI = 1.00, NFI = 0.99, NNFI = 0.99, RMSEA = 0.02). The highest total effect on social dysfunction was psychotic symptoms (0.67, p<0.05). Medication use self-efficacy had a direct effect on psychotic symptoms (-0.25, p<0.01), and social support had direct effect on medication use self efficacy (0.36, p <0.01). Conclusions: Psychotic symptoms and stressful life events were the significance factors that influenced direct on social dysfunctioning. Therefore, interventions that are designed to manage these factors are crucial in order to enhance social functioning in this population.

Keywords: psychotic symptoms, methamphetamine, schizophrenia, stressful life events, social dysfunction, social support, medication use self efficacy

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Authors: Jessica Hemberg, Amanda Sundqvist, Yulia Korzhina, Lillemor Östman, Sofia Gylfe, Frida Gädda, Lisbet Nyström, Henrik Groundstroem, Pia Nyman-Kurkiala

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Purpose: There are large gaps in the literature on COVID-19 pandemic-related mental health outcomes and after-effects specific to adolescents and young adults. The study's aim was to explore adolescents’ and young adults’ experiences of well-being, health, and loneliness during the COVID-19 pandemic. Method: A qualitative exploratory design with qualitative content analysis was used. Twenty-three participants (aged 19-27; four men and 19 women) were interviewed. Results: Four themes emerged: Changed social networks – fewer and closer contacts, changed mental and physical health, increased physical and social loneliness, well-being, internal growth, and need for support. Conclusion: Adolescents’ and young adults’ experiences of well-being, health, and loneliness are subtle and complex. Participants experienced changed social networks, mental and physical health, and well-being. Also, internal growth, need for support, and increased loneliness were seen. Clear information on how to seek help and support from professionals should be made available.

Keywords: adolescents, COVID-19 pandemic, health, interviews, loneliness, qualitative, well-being, young adults

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Authors: Michael Airton

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This case study examines the development of a new service delivery model for prisons that focuses on using NGO’s to provide more effective case management and post release support functions. The model includes the co-design of the service delivery model and innovative commercial agreements that encourage embedded service providers within the prison and continuity of services post release with outcomes based payment mechanisms. The collaboration of prison staff, probation and parole officers and NGO’s is critical to the success of the model and its ability to deliver value and positive outcomes in relation to desistance from offending.

Keywords: collaborative service delivery, desistance, non-government organisations, post release support services

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Authors: S. Cobos-Guzman

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This paper presents the results of a mechatronic design based on a 4-wheel omnidirectional mobile robot that can be used in indoor logistic applications. The low-level control has been selected using two open-source hardware (Raspberry Pi 3 Model B+ and Arduino Mega 2560) that control four industrial motors, four ultrasound sensors, four optical encoders, a vision system of two cameras, and a Hokuyo URG-04LX-UG01 laser scanner. Moreover, the system is powered with a lithium battery that can supply 24 V DC and a maximum current-hour of 20Ah.The Robot Operating System (ROS) has been implemented in the Raspberry Pi and the performance is evaluated with the selection of the sensors and hardware selected. The mechatronic system is evaluated and proposed safe modes of power distribution for controlling all the electronic devices based on different tests. Therefore, based on different performance results, some recommendations are indicated for using the Raspberry Pi and Arduino in terms of power, communication, and distribution of control for different devices. According to these recommendations, the selection of sensors is distributed in both real-time controllers (Arduino and Raspberry Pi). On the other hand, the drivers of the cameras have been implemented in Linux and a python program has been implemented to access the cameras. These cameras will be used for implementing a deep learning algorithm to recognize people and objects. In this way, the level of intelligence can be increased in combination with the maps that can be obtained from the laser scanner.

Keywords: autonomous, indoor robot, mechatronic, omnidirectional robot

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Authors: Muhammad Ali

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Cyber-attacks and anomaly detection on the Internet of Things (IoT) infrastructure is emerging concern in the domain of data-driven intrusion. Rapidly increasing IoT risk is now making headlines around the world. denial of service, malicious control, data type probing, malicious operation, DDos, scan, spying, and wrong setup are attacks and anomalies that can affect an IoT system failure. Everyone talks about cyber security, connectivity, smart devices, and real-time data extraction. IoT devices expose a wide variety of new cyber security attack vectors in network traffic. For further than IoT development, and mainly for smart and IoT applications, there is a necessity for intelligent processing and analysis of data. So, our approach is too secure. We train several machine learning models that have been compared to accurately predicting attacks and anomalies on IoT systems, considering IoT applications, with ANOVA-based feature selection with fewer prediction models to evaluate network traffic to help prevent IoT devices. The machine learning (ML) algorithms that have been used here are KNN, SVM, NB, D.T., and R.F., with the most satisfactory test accuracy with fast detection. The evaluation of ML metrics includes precision, recall, F1 score, FPR, NPV, G.M., MCC, and AUC & ROC. The Random Forest algorithm achieved the best results with less prediction time, with an accuracy of 99.98%.

Keywords: machine learning, analysis of variance, Internet of Thing, network security, intrusion detection

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Authors: O. Sunantha, S. Zhenfeng, S. Phattraporn, A. Zeeshan

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The decline of soil organic carbon (SOC) in global agriculture is a critical issue requiring rapid and accurate estimation for informed policymaking. While it is recognized that SOC predictors vary significantly when derived from remote sensing data and environmental variables, identifying the specific parameters most suitable for accurately estimating SOC in diverse agricultural areas remains a challenge. This study utilizes remote sensing data to precisely estimate SOC and identify influential factors in diverse agricultural areas, such as paddy, corn, sugarcane, cassava, and perennial crops. Extreme gradient boosting (XGBoost), random forest (RF), and support vector regression (SVR) models are employed to analyze these factors' impact on SOC estimation. The results show key factors influencing SOC estimation include slope, vegetation indices (EVI), spectral reflectance indices (red index, red edge2), temperature, land use, and surface soil moisture, as indicated by their averaged importance scores across XGBoost, RF, and SVR models. Therefore, using different machine learning algorithms for SOC estimation reveals varying influential factors from remote sensing data and environmental variables. This approach emphasizes feature selection, as different machine learning algorithms identify various key factors from remote sensing data and environmental variables for accurate SOC estimation.

Keywords: factors influencing SOC estimation, remote sensing data, environmental variables, machine learning

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Authors: Chen Wang, Chun Liang

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Microsatellite instability (MSI) is characterized by high degree of polymorphism in microsatellite (MS) length due to a deficiency in mismatch repair (MMR) system. MSI is associated with several tumor types and its status can be considered as an important indicator for tumor prognostic. Conventional clinical diagnosis of MSI examines PCR products of a panel of MS markers using electrophoresis (MSI-PCR) which is laborious, time consuming, and less reliable. MSIpred, a python 2 package for automatic classification of MSI was released by this study. It computes important somatic mutation features from files in mutation annotation format (MAF) generated from paired tumor-normal exome sequencing data, subsequently using these to predict tumor MSI status with a support vector machine (SVM) classifier trained by MAF files of 1074 tumors belonging to four types. Evaluation of MSIpred on an independent 358-tumor test set achieved overall accuracy of over 98% and area under receiver operating characteristic (ROC) curve of 0.967. These results indicated that MSIpred is a robust pan-cancer MSI classification tool and can serve as a complementary diagnostic to MSI-PCR in MSI diagnosis.

Keywords: microsatellite instability, pan-cancer classification, somatic mutation, support vector machine

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Authors: H. J. Hong

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Sporting organizations are arguably responsible for encouraging high-performance athletes to balance their life and identity during their sporting career; sporting organizations can establish the motivational climate for high-performance athletes using athlete career development and management programs. The purpose of this article to provide an overview of career development and management programs in 20 countries and to examine the following seven features of the programs: (1) Which government-funded sporting organizations provide career development and management programs? (2) Which athletes are eligible to access the programs? (3) What are the aims and objectives of the programs? (4) What are the activities and content of the programs? (5) Who is responsible for the delivery of the programs within organizations (e.g., advisors, coordinators, service providers, counsellors, etc.)? (6) Do the sporting organizations have training and development programs for support services providers? and (7) Do the sporting organizations assess the programs in terms of the programs’ impact on high-performance athletes’ career development and management skills? Web-based data collection was conducted first. The author contacted the sporting organizations to clarify information as required by requesting further information via emails, international calls, video calls on Skype, and by visiting the sporting organizations and meeting with the practitioners (Fiji, Ireland, Korea, Scotland, Singapore, and Spain). By selecting comparable career development and management programs, the present study reviews programs across the world, identifying similarities, differences, and difficulties, so that sporting organizations and practitioners may enhance the quality of their programs. Since international comparisons of career development and management programs remain scarce, the findings deepen the knowledge of high-performance athletes’ career development, management, and transitions in the areas of organizational support programs.

Keywords: athletes' career development and management, athletes' psychological preparation, organizational support, sport career transition

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Authors: Shara Toibayeva, Irbulat Utepbergenov, Lyazzat Issabekova, Aidana Bodesova

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The article discusses the importance of quality assessment as a strategic tool in business and emphasizes the significance of the effectiveness of quality management systems (QMS) for enterprises. The evaluation of these systems takes into account the specificity of quality indicators, the multilevel nature of the system, and the need for optimal selection of the number of indicators and evaluation of the system state, which is critical for making rational management decisions. Methods and models of automated enterprise quality management are proposed, including an intelligent automated quality management system integrated with the Management Information and Control System. These systems make it possible to automate the implementation and support of QMS, increasing the validity, efficiency, and effectiveness of management decisions by automating the functions performed by decision makers and personnel. The paper also emphasizes the use of recurrent neural networks to improve automated quality management. Recurrent neural networks (RNNs) are used to analyze and process sequences of data, which is particularly useful in the context of document quality assessment and non-conformance detection in quality management systems. These networks are able to account for temporal dependencies and complex relationships between different data elements, which improves the accuracy and efficiency of automated decisions. The project was supported by a grant from the Ministry of Education and Science of the Republic of Kazakhstan under the Zhas Galym project No. AR 13268939, dedicated to research and development of digital technologies to ensure consistency of QMS regulatory documents.

Keywords: automated control system, quality management, document structure, formal language

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Authors: Fayiz Saifurahman, Noori Fida Mohammad

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Afghanistan produces the highest rate of wheat, it is the first source of food, and food security in Afghanistan is dependent on the availability of wheat. Although Afghanistan is the main producer of wheat, on the other hand, Afghanistan is the largest importers of flour. The objective of this study is to assess the structure and dynamics of the wheat market in Afghanistan, can compute with foreign markets, and increase the level of production. To complete this, a broad series of secondary data was complied with, group discussions and interviews with farmers, agricultural and market experts. The research findings propose that; the government should adopt different policies to support the local market. The government should distribute the seed, support financially and technically to increase wheat production.

Keywords: Afghanistan, wheat, production , import

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Authors: P. Joris, E. Lombard, X. Cameleyre, G. Navarro, A. Paillet, N. Gorret, S. E. Guillouet

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Today, on the international space station, multiple supplies are needed per year to supply food and spare parts and to take out waste. But as it is planned to go longer and further into space these supplies will no longer be possible. The astronaut life support system must be able of continuously transform waste into valuable compounds. Two types of production were identified as critical and could be be supplemented by microorganisms. On the one hand, since microgravity causes rapid muscle loss, single cell proteins (SCPs) could be used as protein rich feed or food. On the other hand, having enough building materials to build an advanced habitat will not be possible only by transporting space goods from earth to mars for example. The bacterium Cupriavidus. necator is well known for its ability to produce a large amount of proteins or of polyhydroxyalkanoate biopolymers (PHAs) depending on its implementation. By coupling the life support system to a 3D-printer, astronauts could be supplied with an unlimited amount of building materials. Additionally, based on the design of the life support system, waste streams have been identified: urea from the crew urine and volatile fatty acids (VFAs) from a first stage of organic waste (excrement and food waste) treatment through anaerobic digestion. Thus, the objective of this, within the Spaceship.Fr project, was to demonstrate the feasibility of producing SCPs and PHAs from VFAs and urea in bioreactor. Because life support systems operate continuously as loops, continuous culture experiments were chosen and the effect of the bioreactor dilution rate on biomass composition was investigated. Total transformation of the carbon source into biomass with high SCP or PHA content was achieved in all cases. We will present the transformation performances of VFAs and urea by the bacteria in bioreactor in terms of titers, yields and productivities but also in terms of the quality of SCP and PHA produced, nucleic acid content. We will further discuss the envisioned integration of our process within life support systems.

Keywords: life support system, space travel, waste treatment, single cell proteins, polyhydroxyalkanoates, bioreactor

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Authors: Heri Hermansyah, Annisa Kurnia, A. Vania Anisya, Adi Surjosatyo, Yopi Sunarya, Rita Arbianti, Tania Surya Utami

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Lipase is one of biocatalyst which is applied commercially for the process in industries, such as bioenergy, food, and pharmaceutical industry. Nowadays, biocatalysts are preferred in industries because they work in mild condition, high specificity, and reduce energy consumption (high pressure and temperature). But, the usage of lipase for industry scale is limited by economic reason due to the high price of lipase and difficulty of the separation system. Immobilization of lipase is one of the solutions to maintain the activity of lipase and reduce separation system in the process. Therefore, we conduct a study about lipase immobilization with the adsorption-cross linking method using glutaraldehyde because this method produces high enzyme loading and stability. Lipase is immobilized on different kind of resin with the various functional group. Highest enzyme loading (76.69%) was achieved by lipase immobilized on anion macroporous which have anion functional group (OH^‑). However, highest activity (24,69 U/g support) through olive oil emulsion method was achieved by lipase immobilized on anion macroporous-chitosan which have amino (NH₂) and anion (OH^-) functional group. In addition, it also success to produce biodiesel until reach yield 50,6% through interesterification reaction and after 4 cycles stable 63.9% relative with initial yield. While for Aspergillus, niger lipase immobilized on anion macroporous-kitosan have unit activity 22,84 U/g resin and yield biodiesel higher than commercial lipase (69,1%) and after 4 cycles stable reach 70.6% relative from initial yield. This shows that optimum functional group on support for immobilization with adsorption-cross linking is the support that contains amino (NH₂) and anion (OH^-) functional group because they can react with glutaraldehyde and binding with enzyme prevent desorption of lipase from support through binding lipase with a functional group on support.

Keywords: adsorption-cross linking, immobilization, lipase, resin

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Authors: Ugur Choban, Aruzhan Zhaksylyk, Assylbek Nurgabdeshov

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In recent years, there has been an increasing understanding of the value of encouraging entrepreneurial attitudes in university students. This is motivated by the belief that stimulating entrepreneurship not only promotes economic growth but also fosters innovation. This study looks at the complex link and addresses critical gaps between psychological capital and entrepreneurial intention among university students, with a specific emphasis on how contextual factors like academic support and past business experience impact this dynamic. Using a quantitative research method, data were gathered from a broad sample of 300 university students drawn from several faculties. The study used a questionnaire that included the Psychological Capital Questionnaire (PCQ) to assess psychological capital and a validated scale for entrepreneurial intention, as well as binary measures of academic support and prior entrepreneurial experience. Statistical investigations, including multigroup analyses performed with SmartPLS software, provided interesting insights into the effect of contextual factors on the relationship between psychological capital and entrepreneurial intention. The findings highlight that psychological capital had a strong favorable influence on university students' entrepreneurial inclinations. Furthermore, the study found that academic support enhances the influence of psychological capital on entrepreneurial intentions, emphasizing the significance of institutional backing in fostering entrepreneurial mindsets. Furthermore, students with prior entrepreneurial experience had a stronger propensity for entrepreneurship, showing a synergistic link between psychological capital and entrepreneurial background. These findings have both theoretical and practical implications. By explaining the mechanisms by which psychological capital promotes entrepreneurial intentions, the study contributes to the establishment of focused entrepreneurship education programs and support activities that are suited to student requirements. Policymakers may use these findings to create policies that encourage student entrepreneurship, ultimately encouraging economic development and innovation.

Keywords: academic support, entrepreneurial intentions, higher education institutions, psychological capital, prior entrepreneurial experience

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Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

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We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: autonomous surveillance, Bayesian reasoning, decision support, interventions, patterns of life, predictive analytics, predictive insights

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Authors: Kamal Kumar Gupta

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The present research work was carried out on Dysdercus koenigii to understand various aspects of reproductive behavior such as mate finding and recognition, mate selection and mating preference, mating receptivity, and prolonged copulation. The studies carried out on mate searching and courtship behaviour of Dysdercus reflected the courtship behaviour in Dysdercus was brief. The opposite sexes are brought together by the pheromone. The males responded to female sex pheromones by showing directional movements toward the sex partners. Change in mating receptivity pattern of female Dysdercus was ascertained using three parameters of mating behaviour i.e. numbers of male’s encounter, the time taken to mate successfully and per cent females responding to mating. It was seen that a receptive female responded positively to the courting males and a high percentage of females mate usually in a very short time span. The females of Dysdercus showed continued mating receptivity throughout their life. The studies pertaining to mate selection by females showed that females generally do not discriminate among males and usually mate with any male they encountered first. The adults of Dysdercus remain in continuous copula up to 72hr. and mate 5-7 time in their life span. Studies pertaining to significance of prolonged mating in the life time reproductive success of the female Dysdercus indicated that fecundity and fertility and oviposition behavior of the female Dysdercus was related to duration of mating. In order to understand sperm precedence, the sterilized males were produced by exposing them to Gamma radiation. Our studies indicated that a dose of 50 Gy of Gamma radiations induced 95% sterility but does not impair the mating behaviour drastically. To understand role of sperms which were transfer during second mating in fertilizing the subsequent egg batches the sperm utilization pattern of doubly mated female was assessed. The females were mated with normal male or sterilized male in a combination. The sperm utilization pattern was determined by P2 value, our studies indicated a very high P2 value of 0.966, and indicated that sperms of last mating were utilized by the female for fertilization. In light of some of the unique reproductive behaviour of Dysdercus koenigii, such as brief courtship behavior, generalized mate selection by the female, continued mating receptivity and a prolonged pre oviposition period, the present studies on sperm precedence provides an explanation to an unusually prolonged copulation in Dysdercus.

Keywords: dysdercus koenigii, mating behaviour, reproductive performance, entomology

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Authors: Songul Cinaroglu

Abstract:

Machine learning regression methods are recommended as an alternative to classical regression methods in the existence of variables which are difficult to model. Data for health expenditure is typically non-normal and have a heavily skewed distribution. This study aims to compare machine learning regression methods by hyperparameter tuning to predict health expenditure per capita. A multiple regression model was conducted and performance results of Lasso Regression, Random Forest Regression and Support Vector Machine Regression recorded when different hyperparameters are assigned. Lambda (λ) value for Lasso Regression, number of trees for Random Forest Regression, epsilon (ε) value for Support Vector Regression was determined as hyperparameters. Study results performed by using 'k' fold cross validation changed from 5 to 50, indicate the difference between machine learning regression results in terms of R², RMSE and MAE values that are statistically significant (p < 0.001). Study results reveal that Random Forest Regression (R² ˃ 0.7500, RMSE ≤ 0.6000 ve MAE ≤ 0.4000) outperforms other machine learning regression methods. It is highly advisable to use machine learning regression methods for modelling health expenditures.

Keywords: machine learning, lasso regression, random forest regression, support vector regression, hyperparameter tuning, health expenditure

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Authors: Khitam Ibrahem Shlash Mohammad

Abstract:

Background: Postnatal depression is a focus of considerable research attention, but little is known about the pattern of stress across this period. Objective: to investigate the prevalence of stress after childbirth for Jordanian women and identify associated risk factors. Method: Design: A descriptive cross-sectional study. Participants were recruited six to eight weeks postpartum, provided personal, social and obstetric information, and completed the stress subscale of Depression Anxiety and Stress Scale (DASS-S), the Maternity Social Support Scale (MSSS), and Perceived Self-Efficacy Scale (PSES). Setting: maternal and child health care clinics in four health care centres in Maan city in Southern Jordan. Participants: Arabic speaking women (n = 324) between the ages of 18 and 45 years, six to eight weeks postpartum, primiparous or multiparous at low risk for obstetric complications. Data collection took place between October 2015 and January 2016. Ethical clearance was obtained prior to data collection. Results: The prevalence of postpartum stress among Jordanian women was 39.8 %. A regression analysis revealed that occupation, low social support, financial problems, difficult marital relationships, difficult relationship with family-in-law, giving birth to a female baby, difficult childbirth, and low self-efficacy were associated with postpartum stress. Conclusions and implications for practice: Jordanian women need support during pregnancy, during and after childbirth. Postpartum emotional support and assessment of symptoms of stress need to be incorporated into routine practice. The opportunity for open discussion along with increased awareness and clarification of common misconceptions about postpartum stress is necessary.

Keywords: prevalence, postpartum, stress, Jordanian women

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Authors: Fawaz Saad, Hamid Alalwany

Abstract:

Sweden has succeeded to maintain a high level of growth and development and has managed to sustain highly ranked position among the world’s developed countries. In this regard, Swedish universities are playing a vital role in supporting innovation and entrepreneurship at all levels and developing Swedish knowledge economy. This paper is aiming to draw on the experiences of two leading Swedish universities, addressing their transformation approach to create entrepreneurial universities and fulfilling their objectives in the era of knowledge economy. The objectives of the paper include: (1) Introducing the Swedish higher education and its characteristics. (2) Examining the infrastructure elements for innovation and Entrepreneurship at two of the Swedish entrepre-neurial universities. (3) Addressing the key aspects of support systems in the initiatives of both Chalmers and Gothenburg universities to support innovation and advance entrepreneurial practices. The paper will contribute to two discourses: (1) Examining the relationship between support systems for innovation and entrepreneurship and the Universities’ policies and practices. (2) Lessons for University leaders to assist the development and implementation of effective innovation and en-trepreneurship policies and practices.

Keywords: Entrepreneurial University, Chalmers University, Gothenburg University, innovation and entrepreneurship policies, entrepreneurial transformation

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Authors: Wadea Ameen

Abstract:

Rapid prototyping (RP) technology, such as fused deposition modeling (FDM), is gaining popularity because it can produce functioning components with intricate geometric patterns in a reasonable amount of time. A multitude of process variables influences the quality of manufactured parts. In this study, four important process parameters such as layer thickness, model interior fill style, support fill style and orientation are considered. Their influence on three responses, such as build time, model material, and support material, is studied. Experiments are conducted based on factorial design, and the results are presented.

Keywords: fused deposition modeling, factorial design, optimization, 3D printing

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Authors: Maeng-Hwan Hyun, Dae-Man Do, Young-Bok Choi

Abstract:

Around the world, there are frequent incidents of natural disasters, such as earthquakes, tsunamis, floods, and snowstorms, as well as man made disasters such as fires, arsons, and acts of terror. These diverse and unpredictable adversities have resulted in a number of fatalities and injuries. If disaster occurrence can be assessed quickly and information such as the exact location of the disaster and evacuation routes can be provided, victims can promptly move to safe locations, minimizing losses. This paper proposes a behavior analysis method based on a nine degrees-of-freedom (9-DOF) sensor that is effective for the emergency rescue evacuation support system (ERESS), which is being researched with an objective of providing evacuation support during disasters. Based on experiments performed using the acceleration sensor and the gyroscope sensor in the 9-DOF sensor, data are analyzed for human behavior regarding stationary position, walking, running, and during emergency situation to suggest guidelines for system judgment. Using the results of the experiments performed to determine disaster occurrence, it was confirmed that the proposed method quickly determines whether a disaster has occurred.

Keywords: behavior analysis, nine degrees of freedom sensor, emergency rescue, disaster

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Authors: Kevin Molina, Daniel Ortega, Manuel Martinez, Andres Gonzalez-Estrada, William Pinto

Abstract:

Due to the increasing environmental impact, the wind energy is getting strong. This research studied the relationship between the power produced by a horizontal axis wind turbine (HAWT) and the aerodynamic profiles used for its construction. The analysis is studied using the Computational Fluid Dynamic (CFD), presenting the parallel between the energy generated by a turbine designed with selected profiles and another one optimized. For the study, a selection process was carried out from profile NACA 6 digits recommended by the National Renewable Energy Laboratory (NREL) for the construction of this type of turbines. The selection was taken into account different characteristics of the wind (speed and density) and the profiles (aerodynamic coefficients Cl and Cd to different Reynolds and incidence angles). From the selected profiles, was carried out a sensitivity analysis optimization process between its geometry and the aerodynamic forces that are induced on it. The 3D model of the turbines was realized using the Blade Element Momentum method (BEM) and both profiles. The flow fields on the turbines were simulated, obtaining the forces induced on the blade, the torques produced and an increase of 3% in power due to the optimized profiles. Therefore, the results show that the sensitivity analysis optimization process can assist to increment the wind turbine power.

Keywords: blade element momentum, blade, fluid structure interaction, horizontal axis wind turbine, profile design

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Authors: Ahmed Mahmoud Ahmed Abouelmagd

Abstract:

The diversity is the usual remedy of the transmitted signal level variations (Fading phenomena) in radio frequency channels. Diversity techniques utilize two or more copies of a signal and combine those signals to combat fading. The basic concept of diversity is to transmit the signal via several independent diversity branches to get independent signal replicas via time – frequency - space - and polarization diversity domains. Coding and decoding processes can be an alternative remedy for fading phenomena, it cannot increase the channel capacity, but it can improve the error performance. In this paper we propose the use of replication decoding with BCH code class, and Viterbi decoding algorithm with convolution coding; as examples of coding and decoding processes. The results are compared to those obtained from two optimized selection space diversity techniques. The performance of Rayleigh fading channel, as the model considered for radio frequency channels, is evaluated for each case. The evaluation results show that the coding and decoding approaches, especially the BCH coding approach with replication decoding scheme, give better performance compared to that of selection space diversity optimization approaches. Also, an approach for combining the coding and decoding diversity as well as the space diversity is considered, the main disadvantage of this approach is its complexity but it yields good performance results.

Keywords: Rayleigh fading, diversity, BCH codes, Replication decoding, ‎convolution coding, viterbi decoding, space diversity

Procedia PDF Downloads 443