Application of Artificial Intelligence declarative methods for Solving Operating Room Scheduling problems in Hospital Environments

Digital health is a relatively new but already important field in which digitalization meets the need to automatically and efficiently solve problems in healthcare to improve the quality of life for patients. The need to efficiently solve some of these problems has become even more pressing due to the Covid-19 pandemic that significantly increased stress and demand on hospitals. Hospitals have long waiting lists, surgery cancellations, and even worse, resource overload—issues that negatively impact the level of patient satisfaction and the quality of care provided. Within every hospital, operating rooms (ORs) are an important unit. The Operating Room Scheduling (ORS) problem is the task of assigning patients to operating rooms, taking into account different specialties, lengths and priority scores of each planned surgery, operating room session durations, and the availability of beds for the entire length of stay both in the Intensive Care Unit and in the wards. A proper solution to the ORS problem is of primary importance for the quality of healthcare service and the satisfaction of patients in hospital environments. In this thesis, we provide several contributions to the ORS problem. We first present a solution to the problem based on Knowledge Representation and Reasoning via modeling and solving approaches using Answer Set Programming (ASP). This first basic solution builds on a previous solution but takes into account explicitly beds and ICU units because in the pandemic we understood how important and limiting they were. Moreover, we also present an ASP solution for the rescheduling problem, i.e., when the off-line schedule cannot be completed for some reasons, and a further extension where surgical teams are also considered. Another technical contribution is a second solution for the basic ORS problem with beds and an ICU unit, whose modeling departs from the guidelines previously used and shows efficiency improvements. Finally, we introduce a web framework for managing ORS problems via ASP that allows a user to insert the main parameters of the problem, solve a specific instance, and show results graphically in real time

RUTTING AND MOISTURE SUSCEPTIBILITY ASSESSMENT OF ASPHALT WEARING COURSE GRADATIONS

This research focused the impact of various aggregate gradations on permanent deformation and moisture susceptibility of asphalt concrete mixtures. Five wearing course of different gradation, namely NHA-A, NHA-B, SP-1, SP-2 and MS-2, were adopted. Two paving grade bitumen i.e. 40/50 and 60/70 were used. Hamburg Wheel Tracking Test (HWTT) and Modified Lottman test were performed to assess rutting propensity and moisture damage of asphalt mixtures. The results indicated the superior performance of NRL 40/50 binder in HWTT while mixes prepared with Parco 60/70 showed better resistance against moisture. In HWTT, NHA-A performed well followed by NHA-B and SP-2 while MS-2 and SP-1 failed the minimum rut depth criteria. All the mixtures passed the minimum benchmark for Tensile Strength Ratio (TSR). Aggregate gradation SP-1 given in Superpave guidelines provided greater resistance to moisture damage due to compact nature of the blend. Rutting tendency of the mixtures increased with increasing TSR and decreasing Indirect Tensile Strength (ITS)

Mediating Role of Moral Identity in the Relationship between Ethical Leadership and Unethical Behavior of Employees: Evidence from the Oil and Gas Sector of Pakistan

This study draws on social identity, social learning, and trait-activation theories to probe if moral identity mediates the relationship between ethical leadership and unethical behavior. It investigates how ethical leadership serves as a predictor of employees’ unethical behavior and moral identity as a mediator between ethical leadership and employees’ unethical behavior. Together, these variables influence the self-reported unethical behavior of employees. The findings of this study are based on a sample of 297 oil and gas sector employees in Pakistan. For this purpose, data was analyzed through SPSS and AMOS. Consistent with trait-activation and social learning theories, employees on seeing their leaders behaving ethically develop a positive sense of the moral identity and report fewer incidences of unethical behavior. Furthermore, the findings suggested thatmoral identity and ethical leadership behavior are vital for predicting organizational outcomes. Thus, the originality of this study lies in the fact that it analyzed the influence of moral identity as a mediating variable. &nbsp

Leakage analysis of gasketed flange joints under combined internap pressure and thermal loading

Leakage in Gasketed Flanged Joints (GFJs) have always been a great problem for the process industry. The sealing performance of a GFJ depends on its installation and applied loading conditions. This paper aims to finding the leak rate through ANSI class#150 flange joints using a compressed asbestos sheet (CAS) gasket under combined structural and thermal transient loading conditions using two different leak rate models and two different bolt-up levels. The first model is a Gasket Compressive Strain model in which strains are determined using finite element analysis. The other model is based on Porous Media Theory in which gasket is considered as porous media. Leakage rates are determined using both leak rate models and are compared against appropriate tightness classes and the effectiveness of each approach is presented

Positive Stereotyping Could Be Reasoned to Workplace Intergenerational Retention: A Study of Three Generations in the Health Sector of Pakistan

Purpose: The research on intergenerational work environment has attracted researchers in past decades variously and seems valuable in the present time era. The purpose of the present research is to examine the effect of positive stereotyping on intergenerational retention while organizational commitment plays mediating role in this relationship. Methodology: The sample consisted of 206 nurses from hospitals operating under the Punjab health department and the convenience sampling technique was used based on the cross-sectional design. The quantitative survey was conducted to assess the role of organizational commitment between positive stereotypes and workplace inter-generational retention. Findings: The results of the current study were analyzed on SMART PLS 3.2.2 software to predict reliability, assess the structural model, and hypothesized relationships between variables. Obtained results show that positive stereotyping has a significant direct effect on intergenerational retentions. Further organizational commitment significant positively mediates this relationship. Conclusion: Drawing upon generational cohort theory the research highlights the positive role of stereotyping among various generations at the workplace and recommends to the retention of educators is more positive stereotyping among various age group employee

Analytical and numerical assessment of the effect of highly conductive inclusions distribution on the thermal conductivity of particulate composites

Highly conductive composites have found applications in thermal management, and the effective thermal conductivity plays a vital role in understanding the thermo-mechanical behavior of advanced composites. Experimental studies show that when highly conductive inclusions embedded in a polymeric matrix the particle forms conductive chain that drastically increase the effective thermal conductivity of two-phase particulate composites. In this study, we introduce a random network three dimensional (3D) percolation model which closely represent the experimentally observed scenario of the formation of the conductive chain by spherical particles. The prediction of the effective thermal conductivity obtained from percolation models is compared with the conventional micromechanical models of particulate composites having the cubical arrangement, the hexagonal arrangement and the random distribution of the spheres. In addition to that, the capabilities of predicting the effective thermal conductivity of a composite by different analytical models, micromechanical models, and, numerical models are also discussed and compared with the experimental data available in the literature. The results showed that random network percolation models give reasonable estimates of the effective thermal conductivity of the highly conductive particulate composites only in some cases. It is found that the developed percolation models perfectly represent the case of conduction through a composite containing randomly suspended interacting spheres and yield effective thermal conductivity results close to Jeffery's model. It is concluded that a more refined random network percolation model with the directional conductive chain of spheres should be developed to predict the effective thermal conductivity of advanced composites containing highly conductive inclusions

The role of dynamic response parameters in damage prediction

This article presents a literature review of published methods for damage identification and prediction in mechanical structures. It discusses ways which can identify and predict structural damage from dynamic response parameters such as natural frequencies, mode shapes, and vibration amplitudes. There are many structural applications in which dynamic loads are coupled with thermal loads. Hence, a review on those methods, which have discussed structural damage under coupled loads, is also presented. Structural health monitoring with other techniques such as elastic wave propagation, wavelet transform, modal parameter, and artificial intelligence are also discussed. The published research is critically analyzed and the role of dynamic response parameters in structural health monitoring is discussed. The conclusion highlights the research gaps and future research direction

EXPLORING THE BARRIERS TO FEMALE-LITERACY FROM PARENTS AND TEACHERS’ PERSPECTIVE: A REVIEW STUDY OF SCATTERED LITERATURE

The article was a review study. This is an approach which allows the researcher to understand the phenomenon in depth (Karamustafaoglu, 2009). The researchers have adopted the literature review approach to investigate the problem in depth. The structures of literature have been analyzed through the handbooks mostly in the field of teacher education on literacy terms. This was a review study about exploring barriers to literacy from parents and teachers’ perspective. This was linked to the current literature in understanding about the phenomenon which was investigated. This study, therefore, relied on different kinds of literature such as published articles, theses and, books. Majority of them were obtained from research databases such as Web of Science and Google Scholar. Namamba and Rao (2017), and Manzar-Abbas and Lu (2013) followed the same method of review in conducting their review studies. In order to obtain relevant literature, search words such as “barriers to literacy” and “parents and teachers’ perspective” were used. In addition, books on teacher education were also consulted. All the obtained literature was summarized according to the search words of the study. All the obtained literature was cited properly in text and in the list. This allowed the researchers to extract and incorporate key information about exploring barriers to literacy from parents and teachers’ perspective into this article. The studies drawn in this review article reflect the learning about barriers to literacy from parents and teachers’ perspective in diverse directions.  Article visualizations

Response of Gaussian-modulated guided wave in aluminum: An analytical, numerical, and experimental study

The application of guided-wave ultrasonic testing in structural health monitoring has been widely accepted. Comprehensive experimental works have been performed in the past but their validation with possible analytical and numerical solutions still requires serious efforts. In this paper, behavior and detection of the Gaussian-modulated sinusoidal guided-wave pulse traveling in an aluminum plate are presented. An analytical solution is derived for sensing guided wave at a given distance from the actuator. This solution can predict the primary wave modes separately. Numerical analysis is also carried out in COMSOL® Multiphysics software. An experimental setup comprising piezoelectric transducers is used for the validation. Comparison of experimental results with those obtained from analytical and numerical solutions shows close agreement

Fracture life estimation of Al-1050 thin beams using empirical data and a numerical approach

A technique based on empirical data and finite element (FE) analysis to predict the fracture life of Al-1050 beams with the help of its fundamental mode is presented in this study. Experiments were performed on a non-prismatic beam vibrating with a constant value of the amplitude at the fixed end until the complete fracture of the specimen was achieved. The beam was vibrating at its fundamental mode to achieve fracture in less time. A power law model was used to acquire the possible trends between the values of natural frequencies and the number of cycles recorded during these experiments. These trends were further compared with a numerically modelled specimen but with artificial cracks. FE modal analysis was used for this comparison. An error of less than 1% was observed in the estimated number of total cycles obtained through the power law model before fracture, compared to those obtained using the numerical approach. Using this approach, the fracture life was also predicted for specimens of different lengths