Search results for: computerized decision support systems

Authors: Gabriela Ilie, Robert D. H. Rutledge

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A review of the literature reveals a need for longitudinal studies to properly understand the quality of life of prostate cancer survivors during their prostate cancer journey in order to identify opportunities for patient support and care during prostate cancer survivorship. In this study, mental health and relationship satisfaction were assessed longitudinally and by treatment modality among a population-based sample of Canadian adult men with a history of prostate cancer diagnosis. A total of 98 men, aged 51 or older with a history of prostate cancer completed an on-line 15-minute survey between May 2017 and February 2018, assessing mental health (Kessler Psychological Distress Scale) and relationship satisfaction (Dyadic Adjustment Scale) at baseline and at three months post-treatment with either active or nonactive prostate cancer treatment. Almost 1 in 6 men in this sample screened positive for mental health issues (17.34%, n=17) irrespective of treatment modality and most (n=11) were not currently on medication for depression, anxiety or both. Mental health outcomes were poorer for men with multimorbidity. For every instance of screening positive for mental health issues, 2.021 (95% CI:1.1 to 3.8) times more comorbidities were recorded. Relationship satisfaction and dyadic cohesion were statistically significantly lower from first assessment to 3 months for men who underwent multiple treatment modalities (surgery and radiation with hormonal therapy). Relationship satisfaction was also lower at 3 months for men who underwent radiation therapy. Almost 1 in 2 men in this sample (74%) indicated they did not attend a prostate cancer support group. Results suggest that treatment for mental health is underutilized in men with prostate cancer. Men who undergo multiple forms of active treatment appear more vulnerable to relationship dissatisfaction and feeling disconnected from their partner. Data points to important opportunities for patient education and care support during survivorship.

Keywords: prostate cancer survivorship, mental health, quality of life, relationship satisfaction

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Authors: Kriangkrai Maneerat, Chutima Prommak

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Indoor wireless localization systems have played an important role to enhance context-aware services. Determining the position of mobile objects in complex indoor environments, such as those in multi-floor buildings, is very challenging problems. This paper presents an effective floor estimation algorithm, which can accurately determine the floor where mobile objects located. The proposed algorithm is based on the confidence interval of the summation of online Received Signal Strength (RSS) obtained from the IEEE 802.15.4 Wireless Sensor Networks (WSN). We compare the performance of the proposed algorithm with those of other floor estimation algorithms in literature by conducting a real implementation of WSN in our facility. The experimental results and analysis showed that the proposed floor estimation algorithm outperformed the other algorithms and provided highest percentage of floor accuracy up to 100% with 95-percent confidence interval.

Keywords: floor estimation algorithm, floor determination, multi-floor building, indoor wireless systems

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Authors: Medagedara Kaushalya Sewwandi Supun Gunarathne

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This research explores the underlying motivations and consequences of individuals changing their sexual orientation as a response to sexual violence. The primary objective of the study is to unravel the psychological, emotional, and social factors that drive individuals, akin to Celie in Alice Walker’s ‘The Color Purple’, to contemplate and undergo changes in their sexual orientation following the trauma of sexual violence. Through an analytical and qualitative approach, the study employs in-depth textual and thematic analyses to scrutinize the complex interplay between sexual orientation and violence within the selected text. Through a close examination of Celie’s journey and experiences, the study reveals that her decision to switch sexual orientation arises from a desire for a more favorable and benevolent relationship driven by the absence of safety and refuge in her previous relationships. By establishing this bond between sexual orientation and violence, the research underscores how sexual violence can lead individuals to opt for a change in their sexual orientation. The findings highlight Celie’s transformation as a means to seek solace and security, thus concluding that sexual violence can prompt individuals to alter their sexual orientation. The ensuing discussion explores the implications of these findings, encompassing psychological, emotional, and social consequences, as well as the societal and cultural factors influencing the perception of sexual orientation. Additionally, it sheds light on the challenges and stigma faced by those who undergo such transformations. By comprehending the complex relationship between sexual violence and the decision to change sexual orientation, as exemplified by Celie in ‘The Color Purple’, a deeper understanding of the experiences of survivors who seek a safe haven through altering their sexual orientation can be attained.

Keywords: sexual violence, sexual orientation, refuge, transition

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Authors: Jane O`Halloran

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This research aims to identify the issues and challenges of teaching English as a Foreign Language to Japanese university students who have special learning needs. This study sought to investigate factors influencing the academic performance of students with special or additional needs in an inclusive education context. This study will focus on a consideration of the methods available to support those with hearing impairments. While the study population is limited, it is important to give classes to be inclusive places where all students receive equal access to content. Hearing impairments provide an obvious challenge to language learning and, therefore, second-language learning. However, strategies and technologies exist to support the instructor without specialist training. This paper aims to identify these and present them to other teachers of English as a second language who wish to provide the best possible learning experience for every student. Two case studies will be introduced to compare and contrast the experience of in-class teaching and the online option and to share the positives and negatives of the two approaches. While the study focuses on the situation in a university in Japan, the lessons learned by the author may have universal value to any classroom with a student with a hearing disability.

Keywords: inclusive learning, special needs, hearing impairments, teaching strategies

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Authors: Nalini Chitanand

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Given the dynamic nature of the higher education landscape, induction programmes for new academics has become the norm nowadays to support academics negotiate these rough terrain. This study investigates an induction programme for new academics in a higher education institution to establish what difference it has made to participants. The findings revealed that the benefits ranged from creating safe spaces for collaboration and networking to fostering reflective practice and contributing to the scholarship of teaching and learning. The study also revealed that some of the intentions of the programme may not have been achieved, for example transformative learning. This led to questioning whether this intention is an appropriate one given the short duration of the programme and the long, drawn out process of transformation. It may be concluded that the academic induction programme in this study serves to sow the seeds for transformative learning through fostering critically reflective practice. Recommendations for further study could include long term impact of the programme on student learning and success, these being the core business of higher education. It is also recommended that in addition to an induction programme, the university invests in a mentoring programme for new staff and extend the support for academics in order to sustain critical reflection and which may contribute to transformative educational practice.

Keywords: induction programme, reflective practice, scholarship of teaching, transformative learning

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Authors: Selina Lin, Justin M Fan, Vincent Zhang, Cindy Chen, Daniel Lam, Jason Yan, Ning Zhang

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Depression is one of the most common mental disorders in the United States, and past studies have shown a concerning increase in the rates of depression in youth populations over time. Furthermore, depression is an especially important issue for Asian Americans because of the anti-Asian violence taking place during the COVID-19 pandemic. While Asian American adolescents are reluctant to seek help for mental health issues, past research has found a prevalence of depressive symptoms in them that have yet to be fully investigated. There have been studies conducted to understand and observe the impacts of multifarious factors influencing the mental well-being of Asian American adolescents; however, they have been generally limited to qualitative investigation, and very few have attempted to quantitatively evaluate the relationship between depression levels and a comprehensive list of factors for those levels at the same time. To better quantify these relationships, this project investigated the prevalence of depression in Asian American teenagers mainly from the Greater Philadelphia Region, aged 12 to 19, and, with an anonymous survey, asked participants 48 multiple-choice questions pertaining to demographic information, daily behaviors, school life, family life, depression levels (quantified by the PHQ-9 assessment), school and family support against depression. Each multiple-choice question was assigned as a factor and variable for statistical and dominance analysis to determine the most influential factors on depression levels of Asian American adolescents. The results were validated via Bootstrap analysis and t-tests. While certain influential factors identified in this survey are consistent with the literature, such as parent-child relationship and peer pressure, several dominant factors were relatively overlooked in the past. These factors include the parents’ relationship with each other, the satisfaction with body image, sex identity, support from the family and support from the school. More than 25% of participants desired more support from their families and schools in handling depression issues. This study implied that it is beneficial for Asian American parents and adolescents to take programs on parents’ relationships with each other, parent-child communication, mental health, and sexual identity. A culturally inclusive school environment and more accessible mental health services would be helpful for Asian American adolescents to combat depression. This survey-based study paved the way for further investigation of effective approaches for helping Asian American adolescents against depression.

Keywords: Asian American adolescents, depression, dominance analysis, t-test, bootstrap analysis

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Authors: P. L. D. N. M. de Silva, S. G. Edirisinghe, R. Weerasuriya

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High peak-to-average power ratio (PAPR) is a concern of orthogonal frequency division multiplexing (OFDM) based visible light communication (VLC) systems. Discrete Fourier Transform spread (DFT-s) OFDM is an alternative single carrier modulation scheme which would address this concern. Employing channel coding techniques is another mechanism to reduce the PAPR. Previous research has been conducted to study the impact of these techniques separately. However, to the best of the knowledge of the authors, no study has been done so far to identify the improvement which can be harnessed by hybridizing these two techniques for VLC systems. Therefore, this is a novel study area under this research. In addition, channel coding techniques such as Polar codes and Turbo codes have been tested in the VLC domain. However, other efficient techniques such as Hamming coding and Convolutional coding have not been studied too. Therefore, the authors present the impact of the hybrid of DFT-s OFDM and Channel coding (Hamming coding and Convolutional coding) on PAPR in VLC systems using Matlab simulations.

Keywords: convolutional coding, discrete Fourier transform spread orthogonal frequency division multiplexing, hamming coding, peak-to-average power ratio, visible light communications

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Authors: Kemal Efe Eseller, Göktuğ Yazici

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Laser-induced breakdown spectroscopy (LIBS) is a rapid optical atomic emission spectroscopy which is used for material identification and analysis with the advantages of in-situ analysis, elimination of intensive sample preparation, and micro-destructive properties for the material to be tested. LIBS delivers short pulses of laser beams onto the material in order to create plasma by excitation of the material to a certain threshold. The plasma characteristics, which consist of wavelength value and intensity amplitude, depends on the material and the experiment’s environment. In the present work, medicine samples’ spectrum profiles were obtained via LIBS. Medicine samples’ datasets include two different concentrations for both paracetamol based medicines, namely Aferin and Parafon. The spectrum data of the samples were preprocessed via filling outliers based on quartiles, smoothing spectra to eliminate noise and normalizing both wavelength and intensity axis. Statistical information was obtained and principal component analysis (PCA) was incorporated to both the preprocessed and raw datasets. The machine learning models were set based on two different train-test splits, which were 70% training – 30% test and 80% training – 20% test. Cross-validation was preferred to protect the models against overfitting; thus the sample amount is small. The machine learning results of preprocessed and raw datasets were subjected to comparison for both splits. This is the first time that all supervised machine learning classification algorithms; consisting of Decision Trees, Discriminant, naïve Bayes, Support Vector Machines (SVM), k-NN(k-Nearest Neighbor) Ensemble Learning and Neural Network algorithms; were incorporated to LIBS data of paracetamol based pharmaceutical samples, and their different concentrations on preprocessed and raw dataset in order to observe the effect of preprocessing.

Keywords: machine learning, laser-induced breakdown spectroscopy, medicines, principal component analysis, preprocessing

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Authors: Woo Young Jung, Min Ho Kwon, Bu Seog Ju

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A failure of the non-structural component can cause significant damages in critical facilities such as nuclear power plants and hospitals. Historically, it was reported that the damage from the leakage of sprinkler systems, resulted in the shutdown of hospitals for several weeks by the 1971 San Fernando and 1994 North Ridge earthquakes. In most cases, water leakages were observed at the cross joints, sprinkler heads, and T-joint connections in piping systems during and after the seismic events. Hence, the primary objective of this study was to understand the seismic performance of T-joint connections and to develop an analytical Finite Element (FE) model for the T-joint systems of 2-inch fire protection piping system in hospitals subjected to seismic ground motions. In order to evaluate the FE models of the piping systems using OpenSees, two types of materials were used: 1) Steel 02 materials and 2) Pinching 4 materials. Results of the current study revealed that the nonlinear moment-rotation FE models for the threaded T-joint reconciled well with the experimental results in both FE material models. However, the system-level fragility determined from multiple nonlinear time history analyses at the threaded T-joint was slightly different. The system-level fragility at the T-joint, determined by Pinching 4 material was more conservative than that of using Steel 02 material in the piping system.

Keywords: fragility, t-joint, piping, leakage, sprinkler

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Authors: C. S. Subhashini, H. L. Premaratne

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Landslides are the most recurrent and prominent disaster in Sri Lanka. Sri Lanka has been subjected to a number of extreme landslide disasters that resulted in a significant loss of life, material damage, and distress. It is required to explore a solution towards preparedness and mitigation to reduce recurrent losses associated with landslides. Artificial Neural Networks (ANNs) and Hidden Markov Model (HMMs) are now widely used in many computer applications spanning multiple domains. This research examines the effectiveness of using Artificial Neural Networks and Hidden Markov Model in landslides predictions and the possibility of applying the modern technology to predict landslides in a prominent geographical area in Sri Lanka. A thorough survey was conducted with the participation of resource persons from several national universities in Sri Lanka to identify and rank the influencing factors for landslides. A landslide database was created using existing topographic; soil, drainage, land cover maps and historical data. The landslide related factors which include external factors (Rainfall and Number of Previous Occurrences) and internal factors (Soil Material, Geology, Land Use, Curvature, Soil Texture, Slope, Aspect, Soil Drainage, and Soil Effective Thickness) are extracted from the landslide database. These factors are used to recognize the possibility to occur landslides by using an ANN and HMM. The model acquires the relationship between the factors of landslide and its hazard index during the training session. These models with landslide related factors as the inputs will be trained to predict three classes namely, ‘landslide occurs’, ‘landslide does not occur’ and ‘landslide likely to occur’. Once trained, the models will be able to predict the most likely class for the prevailing data. Finally compared two models with regards to prediction accuracy, False Acceptance Rates and False Rejection rates and This research indicates that the Artificial Neural Network could be used as a strong decision support system to predict landslides efficiently and effectively than Hidden Markov Model.

Keywords: landslides, influencing factors, neural network model, hidden markov model

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Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

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Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

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Authors: S. Toufigh Bararpour, Davood Karami, Nader Mahinpey

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Dependence of global economics on fossil fuels has led to a large growth in the emission of greenhouse gases (GHGs). Among the various GHGs, carbon dioxide is the main contributor to the greenhouse effect due to its huge emission amount. To mitigate the threatening effect of CO₂, carbon capture and sequestration (CCS) technologies have been studied widely in recent years. For the combustion processes, three main CO₂ capture techniques have been proposed such as post-combustion, pre-combustion and oxyfuel combustion. Post-combustion is the most commonly used CO₂ capture process as it can be readily retrofit into the existing power plants. Multiple advantages have been reported for the post-combustion by solid sorbents such as high CO₂ selectivity, high adsorption capacity, and low required regeneration energy. Chemical adsorption of CO₂ over alkali-metal-based solid sorbents such as K₂CO₃ is a promising method for the selective capture of diluted CO₂ from the huge amount of nitrogen existing in the flue gas. To improve the CO₂ capture performance, K₂CO₃ is supported by a stable and porous material. Al₂O₃ has been employed commonly as the support and enhanced the cyclic CO₂ capture efficiency of K₂CO₃. Different phases of alumina can be obtained by setting the calcination temperature of boehmite at 300, 600 (γ-alumina), 950 (δ-alumina) and 1200 °C (α-alumina). By increasing the calcination temperature, the regeneration capacity of alumina increases, while the surface area reduces. However, sorbents with lower surface areas have lower CO₂ capture capacity as well (except for the sorbents prepared by hydrophilic support materials). To resolve this issue, a highly efficient alumina-aerogel support was synthesized with a BET surface area of over 2000 m²/g and then calcined at a high temperature. The synthesized alumina-aerogel was impregnated on K₂CO₃ based on 50 wt% support/K₂CO₃, which resulted in the preparation of a sorbent with remarkable CO₂ capture performance. The effect of synthesis conditions such as types of alcohols, solvent-to-co-solvent ratios, and aging times was investigated on the performance of the support. The best support was synthesized using methanol as the solvent, after five days of aging time, and at a solvent-to-co-solvent (methanol-to-toluene) ratio (v/v) of 1/5. Response surface methodology was used to investigate the effect of operating parameters such as carbonation temperature and H₂O-to-CO₂ flowrate ratio on the CO₂ capture capacity. The maximum CO₂ capture capacity, at the optimum amounts of operating parameters, was 7.2 mmol CO₂ per gram K₂CO₃. Cyclic behavior of the sorbent was examined over 20 carbonation and regenerations cycles. The alumina-aerogel-supported K₂CO₃ showed a great performance compared to unsupported K₂CO₃ and γ-alumina-supported K₂CO₃. Fundamental performance analyses and long-term thermal and chemical stability test will be performed on the sorbent in the future. The applicability of the sorbent for a bench-scale process will be evaluated, and a corresponding process model will be established. The fundamental material knowledge and respective process development will be delivered to industrial partners for the design of a pilot-scale testing unit, thereby facilitating the industrial application of alumina-aerogel.

Keywords: alumina-aerogel, CO₂ capture, K₂CO₃, optimization

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Authors: Yingxiao Ye, Christopher Doehring, Angelos Georghiou, Hugh Robinson, Phebe Vayanos

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Human development is a threat to biodiversity, and conservation organizations (COs) are purchasing land to protect areas for biodiversity preservation. However, COs have limited budgets and thus face hard prioritization decisions that are confounded by uncertainty in future human land use. This research proposes a data-driven sequential planning model to help COs choose land parcels that minimize the uncertain human impact on biodiversity. The proposed model is robust to uncertain development, and the sequential decision-making process is adaptive, allowing land purchase decisions to adapt to human land use as it unfolds. The cellular automata model is leveraged to simulate land use development based on climate data, land characteristics, and development threat index from NASA Socioeconomic Data and Applications Center. This simulation is used to model uncertainty in the problem. This research leverages state-of-the-art techniques in the robust optimization literature to propose a computationally tractable reformulation of the model, which can be solved routinely by off-the-shelf solvers like Gurobi or CPLEX. Numerical results based on real data from the Jaguar in Central and South America show that the proposed method reduces conservation loss by 19.46% on average compared to standard approaches such as MARXAN used in practice for biodiversity conservation. Our method may better help guide the decision process in land acquisition and thereby allow conservation organizations to maximize the impact of limited resources.

Keywords: data-driven robust optimization, biodiversity conservation, uncertainty simulation, adaptive sequential planning

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Authors: Zolani Metu

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The death of more than 140 psychiatric patients who were unethically deinstitutionalized from the Life Esidimeni hospital Johannesburg, in 2016, shined a light on South Africa’s failing public mental healthcare system. Compounded by insufficient research evidence on African deinstitutionalization, this necessitates inquiries into deinstitutionalized mental healthcare, reintegration and community-based mental healthcare within the South African context. This study employed a quantitative research approach which utilized a cross-sectional research design, to investigate experiences with the reintegration of institutionalized forensic mental health service users into communities in the Western Cape, South Africa. A convenience sample of 100 mental health care workers from different occupational and organizational backgrounds in the Western Cape was purposively selected using the Western Cape Health Directorate as a sampling frame. A self-administered questionnaire (SAQ) was used as the data collection instrument. The results of the study indicate that criminogenic factors such as substance use, history of violent behaviour, criminal history and disruptive social behaviour complicate the reintegration of forensic mental health service users into communities. The current extent of reintegration of forensic mental health service users was found to be 'poor' (46%; n= 46); and financial difficulties, criminogenic factors and limited Community-Based Care (CBC) facilities were identified as key barriers to the reintegration process. 56% of all job applications for forensic mental health service users were unsuccessful, and 53% of all applications for their admission into CBC facilities were declined. Although social support (informal) was found to be essential for successful reintegration, institutional support (formal) through assertive community treatment (35%; n= 35) and CBC facilities (21%) and the disability grant (DG=50%) was found to be more important for family coping and reintegration. Moreover, 72% of respondents had positive perceptions about the process of reintegration; no statistically significant relationship was found between years of experience and perceptions about reintegration (P-value = 0.062); and perceptions were not found to be a barrier to reintegration. No statistically significant relationship was found between years of working experience and understanding the legislative framework of deinstitutionalization (P-Value =.0.061). However, using a Chi-square test, a significant relationship (P-value = 0.021) was found between sex and understanding the legal framework involved in the process of reintegration. The study recommends a post-2020 deinstitutionalization agenda that factors-in criminogenic realities associated with forensic mental health service users, and affirms the strengthening of PHC and community based care systems as precedents of successful deinstitutionalization and reintegration of mental health service users.

Keywords: forensic mental health, deinstitutionalization, reintegration, mental health service users

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Authors: Julius Steinkopf, Eric Rost, Aike Hessel, Sonia Lippke

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Objective: This study examined possible determinants of return to work (RTW) in individuals who participated in a medical rehabilitation program longitudinally over a time period of six months. Design/methodology/approach: N=1,044 rehabilitants were included in the baseline measurement in terms of completing a questionnaire during their medical rehabilitation. About 30% (n=350) have remained in the study in terms of participating in computer-assisted telephone interviewing (CATI) six months later. Frequency analyses and Regression analyses were run. Findings: About 70% of the rehabilitants returned to work six months after rehabilitation. Regression analyses revealed that the RTW rates were significantly predicted by gender (OR=0.12, men were more likely to return), perceived social support (OR=3.01) and current physical functioning (OR=1.25). Furthermore RTW motives, like expected monetary rewards (OR=25.2) and feelings of being needed (OR=0.18) same as motives for not returning to work (nRTW), like the wish to stop working in order to spend time with the spouse (OR=0.13) or a lack of enjoyment of work (OR=3.81), significantly predicted return to work rates. Life satisfaction, self-efficacy beliefs, mental health, current income, educational background or age did not significantly increase explained variance (all ps > .05). Practical implications: Taking theses predictors into account provides options to increase the effectiveness of interventions aiming at increasing RTW: Medical rehabilitations should not only aim at improving the physical functioning but also to enhance beneficial motives and social support as well as support women specifically in order to improve the effectiveness of medical rehabilitation and public health interventions. Originality/value: Illness-caused work absences are related to high financial costs and individual burden. Despite of the public health and societal implications, this is one of the very few studies investigating systematically fitness and health for the return to work.

Keywords: gender, fitness, health, physical functioning

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Authors: Hamid Saremi, Shida Hanafi

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In an age of technology and economics, human capital has important and axial role in the organization and human resource accounting has a wide perception to key resources of organization i.e. human resources. Human resources accounting is new branch of accounting that has Short-lived and generally deals to a range of policies and measures that are related to various aspects of human resources and It gives importance to an organization's most important asset is its human resources and human resource management is the key to success in an organization and to achieve this important matter must review and evaluation of human resources data be with knowledge of accounting based on empirical studies and methods of measurement and reporting of human resources accounting information. Undoubtedly human resource management without information cannot be done and take decision and human resources accounting is practical way to inform the decision makers who are committed to harnessing human resources,, human resources accounting with applying accounting principles in the organization and is with conducting basic research on the extent of the of human resources accounting information" effect of employees' personal performance. In human resource accounting analysis and criteria and valuation of cost and manpower valuating is as the main resource in each Institute. Protection of human resources is a process that according to human resources accounting is for organization profitability. In fact, this type of accounting can be called as a major source in measurement and trends of costs and human resources valuation in each institution. What is the economic value of such assets? What is the amount of expenditures for education and training of professional individuals to value in asset account? What amount of funds spent should be considered as lost opportunity cost? In this paper, according to the literature of human resource accounting we have studied the human resources matter and its objectives and topic of the importance of human resource valuation on employee performance review and method of reporting of human resources according to different models.

Keywords: human resources, human resources, accounting, human capital, human resource management, valuation and cost of human resources, employees, performance, organization

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Authors: Y. Ates, A. R. Boynuegri, M. Uzunoglu, A. Karakas

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The recent interest in alternative and renewable energy systems results in increased installed capacity ratio of such systems in total energy production of the world. Specifically, wind energy conversion systems (WECS) draw significant attention among possible alternative energy options, recently. On the contrary of the positive points of penetrating WECS in all over the world in terms of environment protection, energy independence of the countries, etc., there are significant problems to be solved for the grid connection of large scale WECS. The reactive power regulation, voltage variation suppression, etc. can be presented as major issues to be considered in this regard. Thus, this paper evaluates the application of a Static VAr Compensator (SVC) unit for the reactive power regulation and operation continuity of WECS during a fault condition. The system is modeled employing the IEEE 13 node test system. Thus, it is possible to evaluate the system performance with an overall grid simulation model close to real grid systems. The overall simulation model is developed in MATLAB/Simulink/SimPowerSystems® environments and the obtained results effectively match the target of the provided study.

Keywords: IEEE 13 bus distribution system, reactive power regulation, static VAr compensator, wind energy conversion system

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Authors: Manel Brichni, Abdelhak-Djamel Seriai

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Systems are increasingly complex. To reduce their complexity, an abstract view of the system can simplify its development. To overcome this problem, we propose a method to decompose systems into subsystems while reducing their coupling. These subsystems represent components. Consisting of an existing object-oriented systems, the main idea of our approach is based on modelling as graphs all entities of an oriented object source code. Such modelling is easy to handle, so we can apply restructuring algorithms based on graph metrics. The particularity of our approach consists in integrating in addition to standard metrics, such as coupling and cohesion, some graph metrics giving more precision during the components identication. To treat this problem, we relied on the ROMANTIC approach that proposed a component-based software architecture recovery from an object oriented system.

Keywords: software reengineering, software component and interfaces, metrics, graphs

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Authors: N. Ben Si Ali, N. Benalia, N. Zarzouri

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Speed sensorless systems are intensively studied during recent years; this is mainly due to their economical benefit and fragility of mechanical sensors and also the difficulty of installing this type of sensor in many applications. These systems suffer from instability problems and sensitivity to parameter mismatch at low speed operation. In this paper an analysis of adaptive observer stability with stator resistance estimation is given.

Keywords: motor drive, sensorless control, adaptive observer, stator resistance estimation

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Authors: Nurul Bin Ibrahim

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Advancements in neural networks have offered valuable insights into Fluid Dynamics, notably in addressing turbulence-related challenges. In this research, we introduce multiple applications of models of neural networks, namely Feed-Forward and Recurrent Neural Networks, to explore the relationship between jet formations and stratified turbulence within stochastically excited Boussinesq systems. Using machine learning tools like TensorFlow and PyTorch, the study has created models that effectively mimic and show the underlying features of the complex patterns of jet formation and stratified turbulence. These models do more than just help us understand these patterns; they also offer a faster way to solve problems in stochastic systems, improving upon traditional numerical techniques to solve stochastic differential equations such as the Euler-Maruyama method. In addition, the research includes a thorough comparison with the Statistical State Dynamics (SSD) approach, which is a well-established method for studying chaotic systems. This comparison helps evaluate how well neural networks can help us understand the complex relationship between jet formations and stratified turbulence. The results of this study underscore the potential of neural networks in computational physics and fluid dynamics, opening up new possibilities for more efficient and accurate simulations in these fields.

Keywords: neural networks, machine learning, computational fluid dynamics, stochastic systems, simulation, stratified turbulence

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Authors: Shreya Mishra, Manosi Chaudhuri, Ajoy K. Dey

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Workplace bullying is a social phenomenon which has proved to be hazardous not only for employees’ well-being but also organizations. Despite being prevalent across geographical boundaries, Indian organizations have failed to acknowledge its vices. This paper aims to understand targets’ perception on what makes bullying nurture in organizations. The paper suggests that person-led Indian work settings give birth to bullying behavior as it lacks professional acumen and systems. An analysis of 13 in-depth interviews of employees from the organized sector suggests that organizations, where decision making lies with single individual, may be a hub of hostile behavior due to the culture which promotes ‘yesmanship’, ‘authoritarianism’ and/or blind belief of leaders on certain set of employees. The study used constructivist grounded theory approach, and the data was analyzed using R Based Qualitative Data Analysis (RQDA) software. Respondents reported that bullying behavior is taken lightly by the management with 'just ignore it' attitude. According to the respondents, the behavior prolong as the perpetrator have a direct approach to the top authority. The study concludes that person-led organizations may create a family-like environment which is favored by employees; however, authoritative leaders are unable to gain the trust of employees. Also, employees who are close to the leader may either be a perpetrator or a target of bullying. It is recommended that leaders in such organizations need to acknowledge the presence of bullying which affects an employees’ commitment towards their job and/or organization. They need to have an assertive check on individuals who hide behind ‘yesman’ attitude. This may help employees feel safe in such work settings.

Keywords: constructivist grounded theory, person-led organization, RQDA, workplace bullying

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Authors: Risna Wijayanti, Sumiati, Hanif Iswari

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This study aims to analyze the role of financial risk attitude as a mediation between financial knowledge and business growth. The ability of human resources in managing capital (financial literacy) can be a major milestone for a company's business to grow and build its competitive advantage. This study analyzed the important role of financial risk attitude in bringing about financial knowledge on corporate growth. There have been many discussions arguing that financial knowledge is one of the main abilities of corporate managers in determining the success of managing a company. However, a contrary argument of other scholars also enlightened that financial knowledge did not have a significant influence on corporate growth. This study used literatures' review to analyze whether there is another variable that can mediate the effect of financial knowledge toward corporate growth. Research mapping was conducted to analyze the concept of risk tolerance. This concept was related to people's risk aversion effects when making a decision under risk and the role of financial knowledge on changes in financial income. Understanding and managing risks and investments are complicated, in particular for corporate managers, who are always demanded to maintain their corporate growth. Substantial financial knowledge is extremely needed to identify and take accurate information for corporate financial decision-making. By reviewing several literature, this study hypothesized that financial knowledge of corporate managers would be meaningless without manager's courage to bear risks for taking favorable business opportunities. Therefore, the level of risk aversion from corporate managers will determine corporate action, which is a reflection of corporate-level investment behavior leading to attain corporate success or failure for achieving the company's expected growth rate.

Keywords: financial knowledge, financial risk attitude, corporate growth, risk tolerance

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Authors: Omer Oral, Y. Emre Yilmaz

Abstract:

Topology optimization is an approach that optimizes material distribution within a given design space for a certain load and boundary conditions by providing performance goals. It uses various restrictions such as boundary conditions, set of loads, and constraints to maximize the performance of the system. It is different than size and shape optimization methods, but it reserves some features of both methods. In this study, interior structures of the parts were optimized by using SIMP (Solid Isotropic Material with Penalization) method. The volume of the part was preassigned parameter and minimum deflection was the objective function. The basic idea behind the theory was considered, and different methods were discussed. Rhinoceros 3D design tool was used with Grasshopper and TopOpt plugins to create and optimize parts. A Grasshopper algorithm was designed and tested for different beams, set of arbitrary located forces and support types such as pinned, fixed, etc. Finally, 2.5D shapes were obtained and verified by observing the changes in density function.

Keywords: Grasshopper, lattice structure, microstructures, Rhinoceros, solid isotropic material with penalization method, TopOpt, topology optimization

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Authors: David C. Ni

Abstract:

In the previous efforts, we constructed N-Body Systems by an extended Blaschke product (EBP), which represents a non-temporal and nonlinear extension of Lorentz transformation. In this construction, we rely only on two parameters, nonlinear degree, and relative momentum to characterize the systems. We further explored root computation via iteration with an algorithm extended from Jenkins-Traub method. The solution sets demonstrate a form of σ+ i [-t, t], where σ and t are the real numbers, and the [-t, t] shows various canonical distributions. In this paper, we correlate the convergent sets in the original domain with solution sets, which demonstrating large-deviation distributions in the codomain. We proceed to compare our approach with the formula or principles, such as Donsker-Varadhan and Wentzell-Freidlin theories. The deterministic model based on this construction allows us to explore applications in the areas of finance and statistical mechanics.

Keywords: nonlinear Lorentz transformation, Blaschke equation, iteration solutions, root computation, large deviation distribution, deterministic model

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Authors: Adandé Belarmain Fandohan

Abstract:

Climate change has become a major concern globally, particularly in rural communities that have to find rapid coping solutions. Several vulnerability assessment approaches have been developed in the last decades. This comes along with a higher risk for different methods to result in different conclusions, thereby making comparisons difficult and decision-making non-consistent across areas. The effect of methods and computational approaches on estimates of people’s vulnerability was assessed using data collected from the Gambia. Twenty-four indicators reflecting vulnerability components: (exposure, sensitivity, and adaptive capacity) were selected for this purpose. Data were collected through household surveys and key informant interviews. One hundred and fifteen respondents were surveyed across six communities and two administrative districts. Results were compared over three computational approaches: the maximum value transformation normalization, the z-score transformation normalization, and simple averaging. Regardless of the approaches used, communities that have high exposure to climate change and extreme events were the most vulnerable. Furthermore, the vulnerability was strongly related to the socio-economic characteristics of farmers. The survey evidenced variability in vulnerability among communities and administrative districts. Comparing output across approaches, overall, people in the study area were found to be highly vulnerable using the simple average and maximum value transformation, whereas they were only moderately vulnerable using the z-score transformation approach. It is suggested that assessment approach-induced discrepancies be accounted for in international debates to harmonize/standardize assessment approaches to the end of making outputs comparable across regions. This will also likely increase the relevance of decision-making for adaptation policies.

Keywords: maximum value transformation, simple averaging, vulnerability assessment, West Africa, z-score transformation

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Authors: Hailyie Tekleselase

Abstract:

Deep learning is increasingly used as a building block of security systems. However, neural networks are hard to interpret and typically solid to the practitioner. This paper presents a detail survey of computing methods in cyber security, and analyzes the prospects of enhancing the cyber security capabilities by suggests that of accelerating the intelligence of the security systems. There are many AI-based applications used in industrial scenarios such as Internet of Things (IoT), smart grids, and edge computing. Machine learning technologies require a training process which introduces the protection problems in the training data and algorithms. We present machine learning techniques currently applied to the detection of intrusion, malware, and spam. Our conclusions are based on an extensive review of the literature as well as on experiments performed on real enterprise systems and network traffic. We conclude that problems can be solved successfully only when methods of artificial intelligence are being used besides human experts or operators.

Keywords: artificial intelligence, machine learning, deep learning, cyber security, big data

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Authors: Rahmat Ali, Inamullah Khan, Amjad Naseer, Abid A. Shah

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Hydronic Heating and Cooling systems in concrete slab based buildings are increasingly becoming a popular substitute to conventional heating and cooling systems. In exploring the materials, techniques employed, and their relative performance measures, a fair bit of uncertainty exists. This research has identified the simplest method of determining the thermal field of a single hydronic pipe when acting as a part of a concrete slab, based on which the spacing and positioning of pipes for a best thermal performance and surface temperature control are determined. The pipe material chosen is the commonly used PEX pipe, which has an all-around performance and thermal characteristics with a thermal conductivity of 0.5W/mK. Concrete Test samples were constructed and their thermal fields tested under varying input conditions. Temperature sensing devices were embedded into the wet concrete at fixed distances from the pipe and other touch sensing temperature devices were employed for determining the extent of the thermal field and validation studies. In the first stage, it was found that the temperature along a specific distance was the same and that heat dissipation occurred in well-defined layers. The temperature obtained in concrete was then related to the different control parameters including water supply temperature. From the results, the temperature of water required for a specific temperature rise in concrete is determined. The thermally effective area is also determined which is then used to calculate the pipe spacing and positioning for the desired level of thermal comfort.

Keywords: thermally activated building systems, concrete slab temperature, thermal field, energy efficiency, thermal comfort, pipe spacing

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Authors: Ankit Nagar, Dinesh Kumar Nauriyal, Sukhpal Singh

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This paper examines the key determinants of farmers’ access to agricultural extension services, sources of agricultural extension services preferred and accessed by the farmers. An ordered logistic regression model was used to analyse the data of the 360 sample households based on a primary survey conducted in western Uttar Pradesh, India. The study finds that farmers' decision to engage in the agricultural extension programme is significantly influenced by factors such as education level, gender, farming experience, social group, group membership, farm size, credit access, awareness about the extension scheme, farmers' perception, and distance from extension sources. The most intriguing finding of this study is that the progressive farmers, which have long been regarded as a major source of knowledge diffusion, are the most distrusted sources of information as they are suspected of withholding vital information from potential beneficiaries. The positive relationship between farm size and ‘Access’ underlines that the extension services should revisit their strategies for targeting more marginal and small farmers constituting over 85 percent of the agricultural households by incorporating their priorities in their outreach programs. The study suggests that marginal and small farmers' productive potential could still be greatly augmented by the appropriate technology, advisory services, guidance, and improved market access. Also, the perception of poor quality of the public extension services can be corrected by initiatives aimed at building up extension workers' capacity.

Keywords: agriculture, access, extension services, ordered logistic regression

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Authors: S. Pushkar, O. Verbitsky

Abstract:

Currently, green rating systems are mainly utilized for correctly sizing mechanical and electrical systems, which have short lifetime expectancies. In these systems, passive solar and bio-climatic architecture, which have long lifetime expectancies, are neglected. Urban rating systems consider buildings and services in addition to neighborhoods and public transportation as integral parts of the built environment. The main goal of this study was to develop a more consistent point allocation system for urban building standards by using six different lifetime shearing layers: Site, Structure, Skin, Services, Space, and Stuff, each reflecting distinct environmental damages. This shearing-layer concept was applied to internationally well-known rating systems: Leadership in Energy and Environmental Design (LEED) for Neighborhood Development, BRE Environmental Assessment Method (BREEAM) for Communities, and Comprehensive Assessment System for Building Environmental Efficiency (CASBEE) for Urban Development. The results showed that LEED for Neighborhood Development and BREEAM for Communities focused on long-lifetime-expectancy building designs, whereas CASBEE for Urban Development gave equal importance to the Building and Service Layers. Moreover, although this rating system was applied using a building-scale assessment, “Urban Area + Buildings” focuses on a short-lifetime-expectancy system design, neglecting to improve the architectural design by considering bio-climatic and passive solar aspects.

Keywords: green rating system, urban community, sustainable design, standardization, shearing-layer concept, passive solar architecture

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Authors: Moustafa Osman Mohammed

Abstract:

This paper will explore formation of HCl aerosol at atmospheric boundary layers and encourages the uptake of environmental modeling systems (EMSs) as a practice evaluation of gaseous emissions (“framework measures”) from small and medium-sized enterprises (SMEs). The conceptual model predicts greenhouse gas emissions to ecological points beyond landfill site operations. It focuses on incorporation traditional knowledge into baseline information for both measurement data and the mathematical results, regarding parameters influence model variable inputs. The paper has simplified parameters of aerosol processes based on the more complex aerosol process computations. The simple model can be implemented to both Gaussian and Eulerian rural dispersion models. Aerosol processes considered in this study were (i) the coagulation of particles, (ii) the condensation and evaporation of organic vapors, and (iii) dry deposition. The chemical transformation of gas-phase compounds is taken into account photochemical formulation with exposure effects according to HCl concentrations as starting point of risk assessment. The discussion set out distinctly aspect of sustainability in reflection inputs, outputs, and modes of impact on the environment. Thereby, models incorporate abiotic and biotic species to broaden the scope of integration for both quantification impact and assessment risks. The later environmental obligations suggest either a recommendation or a decision of what is a legislative should be achieved for mitigation measures of landfill gas (LFG) ultimately.

Keywords: air pollution, landfill emission, environmental management, monitoring/methods and impact assessment

Procedia PDF Downloads 315