Search results for: maternity care model

Authors: Shen Jian, Hu Jie, Zhu Guo Niu, Peng Ying Hong

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There are two issues exited in the traditional visual prosthesis: lacking systematic method and the low level of humanization. To tackcle those obstacles, a visual prosthesis design method based on biologically inspired design is proposed. Firstly, a constrained FBS knowledge cell model is applied to construct the functional model of visual prosthesis in biological field. Then the clustering results of engineering domain are ob-tained with the use of the cross-domain knowledge cell clustering algorithm. Finally, a prototype system is designed to support the bio-logically inspired design where the conflict is digested by TRIZ and other tools, and the validity of the method is verified by the solution scheme

Keywords: knowledge-based engineering, visual prosthesis, biologically inspired design, biomedical engineering

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Authors: Si Chen, Quanhong Jiang

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In the increasingly mature posture recognition technology, human movement information is widely used in sports rehabilitation, human-computer interaction, medical health, human posture assessment, and other fields today; this project uses the most original ideas; it is proposed to use the collection equipment for the collection of myoelectric data, reflect the muscle posture change on a degree of freedom through data processing, carry out data-muscle three-dimensional model joint adjustment, and realize basic pose recognition. Based on this, bionic aids or medical rehabilitation equipment can be further developed with the help of robotic arms and cutting-edge technology, which has a bright future and unlimited development space.

Keywords: pose recognition, 3D animation, electromyography, machine learning, bionics

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Authors: Rachid Zentar, Mokrane Bala, Pascal Boustingorry

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The prediction of the rheological behavior of concrete is at the center of current concerns of the concrete industry for different reasons. The shortage of good quality standard materials combined with variable properties of available materials imposes to improve existing models to take into account these variations at the design stage of concrete. The main reasons for improving the predictive models are, of course, saving time and cost at the design stage as well as to optimize concrete performances. In this study, we will highlight the different properties of the granular mixtures that affect the rheological properties of concrete. Our objective is to identify the intrinsic parameters of the aggregates which make it possible to predict the yield stress of concrete. The work was done using two typologies of grains: crushed and rolled aggregates. The experimental results have shown that the rheology of concrete is improved by increasing the packing density of the granular mixture using rolled aggregates. The experimental program realized allowed to model the yield stress of concrete by a modified model of Chateau et al. through a dimensionless parameter following Krieger-Dougherty law. The modelling confirms that the yield stress of concrete depends not only on the properties of cement paste but also on the packing density of the granular skeleton and the shape of grains.

Keywords: crushed aggregates, intrinsic viscosity, packing density, rolled aggregates, slump, yield stress of concrete

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Authors: Leen Sulaimani, Maryam Hafiz, Naba Ali, Roba Alsharif

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One of Amazon’s most crucial online systems is artificial intelligence. Amazon would not have a worldwide successful online store, an easy and secure way of payment, and other services if it weren’t for artificial intelligence and machine learning. Amazon uses AI to expand its operations and enhance them by upgrading the website daily; having a strong base of artificial intelligence in a worldwide successful business can improve marketing, decision-making, feedback, and more qualities. Aiming to have a rational AI system in one’s business should be the start of any process; that is why Amazon is fortunate that they keep taking care of the base of their business by using modern artificial intelligence, making sure that it is stable, reaching their organizational goals, and will continue to thrive more each and every day. Artificial intelligence is used daily in our current world and is still being amplified more each day to reach consumer satisfaction and company short and long-term goals.

Keywords: artificial intelligence, Amazon, business, customer, decision making

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Authors: I. Mnafeg, A. Abichou, L. Beji

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Traditional mechanical control systems in thrust vectoring are efficient in rocket thrust guidance but their costs and their weights are excessive. The fluidic injection in the nozzle divergent constitutes an alternative procedure to achieve the goal. In this paper, we present a 3D analytical model for fluidic injection in a supersonic nozzle integrating an orifice. The fluidic vectoring uses a sonic secondary injection in the divergent. As a result, the flow and interaction between the main and secondary jet has built in order to express the pressure fields from which the forces and thrust vectoring are deduced. Under various separation criteria, the present analytical model results are compared with the existing numerical and experimental data from the literature.

Keywords: flow separation, fluidic thrust vectoring, nozzle, secondary jet, shock wave

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Authors: Ujjal Chattaraj, M. Raviteja, Chaitanya Aemala

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Over the years vehicular traffic has been given priority over pedestrian traffic. With the increase of population in cities, pedestrian traffic is increasing day by day. Pedestrian safety has become a matter of concern for the Traffic Engineers. Pedestrian comfort is primary important for the Engineers who design different pedestrian facilities. Pedestrian comfort and safety can be measured in terms of different level of service (LOS) of the facilities. In this study video data on pedestrian movement have been collected from different railway foot over bridges (FOB) in India. The level of service of those facilities has been analyzed. A cellular automata based model has been formulated to mimic the route choice behaviour of the pedestrians on the foot over bridges.

Keywords: cellular automata model, foot over bridge, level of service, pedestrian

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Authors: Shun-Qi Zhang, Shu-Yang Zhang, Min Chen

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Applying strong electric field on piezoelectric actuators, on one hand very significant electroelastic material nonlinear effects will occur, on the other hand piezo plates and shells may undergo large displacements and rotations. In order to give a precise prediction of piezolaminated smart structures under large electric field, this paper develops a finite element (FE) model accounting for both electroelastic material nonlinearity and geometric nonlinearity with large rotations based on the first order shear deformation (FSOD) hypothesis. The proposed FE model is applied to analyze a piezolaminated semicircular shell structure.

Keywords: smart structures, piezolamintes, material nonlinearity, strong electric field

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Authors: Taimaz Larimian, Negin Sadeghi

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Very little is known about the impacts of urban security on the level of social sustainability within the cities of developing countries. Urban security is still struggling to find its position in the social sustainability agenda, despite the significant role of safety and security on different aspects of peoples’ lives. This paper argues that urban safety and security should be better integrated within the social sustainability framework. With this aim, this study investigates the hypothesized relationship between social sustainability and Crime Prevention through Environmental Design (CPTED) approach at the neighborhood scale. This study proposes a model of key influential dimensions of CPTED analyzed into localized factors and sub-factors. These factors are then prioritized using pairwise comparison logic and fuzzy group Analytic Hierarchy Process (AHP) method in order to determine the relative importance of each factor on achieving social sustainability. The proposed model then investigates social sustainability in six case study neighborhoods of Isfahan city based on residents’ perceptions of safety within their neighborhood. Mixed method of data collection is used by using a self-administered questionnaire to explore the residents’ perceptions of social sustainability in their area of residency followed by an on-site observation to measure the CPTED construct. In all, 150 respondents from selected neighborhoods were involved in this research. The model indicates that CPTED approach has a significant direct influence on increasing social sustainability in neighborhood scale. According to the findings, among different dimensions of CPTED, ‘activity support’ and ‘image/ management’ have the most influence on people’s feeling of safety within studied areas. This model represents a useful designing tool in achieving urban safety and security during the development of more socially sustainable and user-friendly urban areas.

Keywords: crime prevention through environmental design (CPTED), developing countries, fuzzy analytic hierarchy process (FAHP), social sustainability

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Authors: Nacera Yassa, Abdelmalek Saidoune, Ghania Ouadfel, Hamza Houassine

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The rapid advancement in electrical technologies has underscored the increasing importance of multiphase machines across various industrial sectors. These machines offer significant advantages in terms of efficiency, compactness, and reliability compared to their single-phase counterparts. However, early detection and diagnosis of electrical faults remain critical challenges to ensure the durability and safety of these complex systems. This paper presents an advanced analytical model for multiphase machines, with a particular focus on dual stator asynchronous machines. The primary objective is to develop a robust diagnostic tool capable of effectively detecting and locating electrical faults in these machines, including short circuits, winding faults, and voltage imbalances. The proposed methodology relies on an analytical approach combining electrical machine theory, modeling of magnetic and electrical circuits, and advanced signal analysis techniques. By employing detailed analytical equations, the developed model accurately simulates the behavior of multiphase machines in the presence of electrical faults. The effectiveness of the proposed model is demonstrated through a series of case studies and numerical simulations. In particular, special attention is given to analyzing the dynamic behavior of machines under different types of faults, as well as optimizing diagnostic and recovery strategies. The obtained results pave the way for new advancements in the field of multiphase machine diagnostics, with potential applications in various sectors such as automotive, aerospace, and renewable energies. By providing precise and reliable tools for early fault detection, this research contributes to improving the reliability and durability of complex electrical systems while reducing maintenance and operation costs.

Keywords: faults, diagnosis, modelling, multiphase machine

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Authors: Aishvarya Gupta, Keerthana Anand, Sasirekha Rengaraj, Latha Chathurvedula

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Introduction: Advances in assisted reproductive technology and increase in the proportion of infertile couples have both contributed to the steep increase in the incidence of twin pregnancies in past decades. Maternal and perinatal complications are higher in twins than in singleton pregnancies. Studies comparing the maternal and perinatal outcomes of ART twin pregnancies versus spontaneously conceived twin pregnancies report heterogeneous results making it unclear whether the complications are due to twin gestation per se or because of assisted reproductive techniques. The present study aims to compare both maternal and perinatal outcomes in twin pregnancies which are spontaneously conceived and after assisted conception methods, so that targeted steps can be undertaken in order to improve maternal and perinatal outcome of twins. Objectives: To study perinatal and maternal outcome in twin pregnancies conceived spontaneously as well as with assisted methods and compare the outcomes between the two groups. Setting: Women delivering at JIPMER (tertiary care institute), Pondicherry. Population: 380 women with twin pregnancies who delivered in JIPMER between June 2015 and March 2017 were included in the study. Methods: The study population was divided into two cohorts – one conceived by spontaneous conception and other by assisted reproductive methods. Association of various maternal and perinatal outcomes with the method of conception was assessed using chi square test or Student's t test as appropriate. Multiple logistic regression analysis was done to assess the independent association of assisted conception with maternal outcomes after adjusting for age, parity and BMI. Multiple logistic regression analysis was done to assess the independent association of assisted conception with perinatal outcomes after adjusting for age, parity, BMI, chorionicity, gestational age at delivery and presence of hypertension or gestational diabetes in the mother. A p value of < 0.05 was considered as significant. Result: There was increased proportion of women with GDM (21% v/s 4.29%) and premature rupture of membranes (35% v/s 22.85%) in the assisted conception group and more anemic women in the spontaneous group (71.27% v/s 55.1%). However assisted conception per se increased the incidence of GDM among twin gestations (OR 3.39, 95% CI 1.34 – 8.61) and did not influence any of the other maternal outcomes. Among the perinatal outcomes, assisted conception per se increased the risk of having very preterm (<32 weeks) neonates (OR 3.013, 95% CI 1.432 – 6.337). The mean birth weight did not significantly differ between the two groups (p = 0.429). Though there were higher proportion of babies admitted to NICU in the assisted conception group (48.48% v/s 36.43%), assisted conception per se did not increase the risk of admission to NICU (OR 1.23, 95% CI 0.76 – 1.98). There was no significant difference in perinatal mortality rates between the two groups (p = 0.829). Conclusion: Assisted conception per se increases the risk of developing GDM in women with twin gestation and increases the risk of delivering very preterm babies. Hence measures should be taken to ensure appropriate screening methods for GDM and suitable neonatal care in such pregnancies.

Keywords: assisted conception, maternal outcomes, perinatal outcomes, twin gestation

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Authors: Hilary Rutto

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The investigation was aimed at determining the extent at which the zinc will be extracted from secondary sources generated from galvanising process using dilute sulphuric acid under controlled laboratory conditions of temperature, solid-liquid ratio, and agitation rate. The leaching experiment was conducted for a period of 2 hours and to total zinc extracted calculated in relation to the amount of zinc dissolved at a unit time in comparison to the initial zinc content of the zinc ash. Sulphuric acid was found to be an effective leaching agent with an overall extraction of 91.1% when concentration is at 2M, and solid/liquid ratio kept at 1g/200mL leaching solution and temperature set at 65ᵒC while slurry agitation is at 450rpm. The leaching mechanism of zinc ash with sulphuric acid was conformed well to the shrinking core model.

Keywords: leaching, kinetics, shrinking core model, zinc slag

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Authors: Onder Yakut, Oguzhan Timus, Emine Dogru Bolat

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Health diseases have a vital significance affecting human being's life and life quality. Sudden death events can be prevented owing to early diagnosis and treatment methods. Electrical signals, taken from the human being's body using non-invasive methods and showing the heart activity is called Electrocardiogram (ECG). The ECG signal is used for following daily activity of the heart by clinicians. Heart Rate Variability (HRV) is a physiological parameter giving the variation between the heart beats. ECG data taken from MITBIH Arrhythmia Database is used in the model employed in this study. The detection of arrhythmic heart beats is aimed utilizing the features extracted from the HRV time domain parameters. The developed model provides a satisfactory performance with ~89% accuracy, 91.7 % sensitivity and 85% specificity rates for the detection of arrhythmic beats.

Keywords: arrhythmic beat detection, ECG, HRV, kNN classifier

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Authors: Bin Bian, Liang Wang

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A hydraulic spherical motion mechanism (HSMM) is proposed. Unlike traditional systems using serial or parallel mechanisms for multi-DOF rotations, the HSMM is capable of implementing continuous 2-DOF rotational motions in a single joint without the intermediate transmission mechanisms. It has some advantages of compact structure, low inertia and high stiffness. However, as HSMM is a nonlinear and multivariable system, it is very complicate to realize accuracy control. Therefore, an augmented active disturbance rejection controller (ADRC) is proposed in this paper. Compared with the traditional PD control method, three compensation items, i.e., dynamics compensation term, disturbance compensation term and nonlinear error elimination term, are added into the proposed algorithm to improve the control performance. The ADRC algorithm aims at offsetting the effects of external disturbance and realizing accurate control. Euler angles are applied to describe the orientation of rotor. Lagrange equations are utilized to establish the dynamic model of the HSMM. The stability of this algorithm is validated with detailed derivation. Simulation model is formulated in Matlab/Simulink. The results show that the proposed control algorithm has better competence of trajectory tracking in the presence of uncertainties.

Keywords: hydraulic spherical motion mechanism, dynamic model, active disturbance rejection control, trajectory tracking

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Authors: Divvela Vishnu Sai Kumar, Deepak Arora, Sheenu Rizvi

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Forecasting a cyclone through satellite images consists of the estimation of the intensity of the cyclone and predicting it before a cyclone comes. This research work can help people to take safety measures before the cyclone comes. The prediction of the intensity of a cyclone is very important to save lives and minimize the damage caused by cyclones. These cyclones are very costliest natural disasters that cause a lot of damage globally due to a lot of hazards. Authors have proposed five different CNN (Convolutional Neural Network) models that estimate the intensity of cyclones through INSAT-3D IR images. There are a lot of techniques that are used to estimate the intensity; the best model proposed by authors estimates intensity with a root mean squared error (RMSE) of 10.02 kts.

Keywords: estimating cyclone intensity, deep learning, convolution neural network, prediction models

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Authors: Jatin Gupta, Bishakh Bhattacharya

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With the aging process, many people start suffering from the problem of weak limbs resulting in mobility disorders and loss of sensory and motor function of limbs. Wearable robotic devices are viable solutions to help people suffering from these issues by augmenting their strength. These robotic devices, popularly known as exoskeletons aides user by providing external power and controlling the dynamics so as to achieve desired motion. Present work studies a simplified dynamic model of the human gait. A four link open chain kinematic model is developed to describe the dynamics of Single Support Phase (SSP) of the human gait cycle. The dynamic model is developed integrating mathematical models of the motion of inverted and triple pendulums. Stance leg is modeled as inverted pendulum having single degree of freedom and swing leg as triple pendulum having three degrees of freedom viz. thigh, knee, and ankle joints. The kinematic model is formulated using forward kinematics approach. Lagrangian approach is used to formulate governing dynamic equation of the model. For a system of nonlinear differential equations, numerical method is employed to obtain system response. Reference trajectory is generated using human body simulator, LifeMOD. For optimal mechanical design and controller design of exoskeleton system, it is imperative to study parameter sensitivity of the system. Six different parameters viz. thigh, shank, and foot masses and lengths are varied from 85% to 115% of the original value for the present work. It is observed that hip joint of swing leg is the most sensitive and ankle joint of swing leg is the least sensitive one. Changing link lengths causes more deviation in system response than link masses. Also, shank length and thigh mass are most sensitive parameters. Finally, the present study gives an insight on different factors that should be considered while designing a lower extremity exoskeleton.

Keywords: lower limb exoskeleton, multibody dynamics, energy based formulation, optimal design

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Authors: Nagham Ismail, Djamel Ouahrani

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Thermal resilience in the built environment reflects the building's capacity to adapt to extreme climate changes. In hot climates, power outages in office buildings pose risks to the health and productivity of workers. Therefore, it is of interest to quantify the thermal resilience of office buildings by developing a user-friendly simplified model. This simplified model begins with creating an assessment metric of thermal resilience that measures the duration between the power outage and the point at which the thermal habitability condition is compromised, considering different power interruption times (morning, noon, and afternoon). In this context, energy simulations of an office building are conducted for Qatar's summer weather by changing different parameters that are related to the (i) wall characteristics, (ii) glazing characteristics, (iii) load, (iv) orientation and (v) air leakage. The simulation results are processed using SPSS to derive linear regression equations, aiding stakeholders in evaluating the performance of commercial buildings during different power interruption times. The findings reveal the significant influence of glazing characteristics on thermal resilience, with the morning power outage scenario posing the most detrimental impact in terms of the shortest duration before compromising thermal resilience.

Keywords: thermal resilience, thermal envelope, energy modeling, building simulation, thermal comfort, power disruption, extreme weather

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Authors: Qisheng Hu, Jianglei Han, Yue Yang, My Hoa Ha

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When a company is considering purchasing software for commercial use, contract risk assessment is critical to identify risks to mitigate the potential adverse business impact, e.g., security, financial and regulatory risks. Contract risk assessment requires reviewers with specialized knowledge and time to evaluate the legal documents manually. Specifically, validating contracts for a software vendor requires the following steps: manual screening, interpreting legal documents, and extracting risk-prone segments. To automate the process, we proposed a framework to assist legal contract document risk identification, leveraging pre-trained deep learning models and natural language processing techniques. Given a set of pre-defined risk evaluation problems, our framework utilizes the pre-trained transformer-based models for question-answering to identify risk-prone sections in a contract. Furthermore, the question-answering model encodes the concatenated question-contract text and predicts the start and end position for clause extraction. Due to the limited labelled dataset for training, we leveraged transfer learning by fine-tuning the models with the CUAD dataset to enhance the model. On a dataset comprising 287 contract documents and 2000 labelled samples, our best model achieved an F1 score of 0.687.

Keywords: contract risk assessment, NLP, transfer learning, question answering

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Authors: Kakhaber Djakeli

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For market leadership, iconic brands already start to establish their unique digital avatars into Metaverse and offer Non Fungible Tokens to their fans. Metaverse can be defined as an evolutionary step of Internet development. So if companies and brands use the internet, logically, they can find new solutions for them and their customers in Metaverse. Marketing and Management today must learn how to combine physical world activities with those either entitled as digital, virtual, and immersive. A “Phygital” Solution uniting physical and digital competitive activities of the company covering the questions about how to use virtual worlds for Brand Development and Non Fungible Tokens for more attractiveness soon will be most relevant question for Branding. Thinking comprehensively, we can entitle this type of branding as an Immersive one. As we see, the Immersive Brands give customers more mesmerizing feelings than traditional ones. Accordingly, the Branding can be divided by the company in its own understanding into two models: traditional and immersive. Immersive Branding being more directed to Sensorial challenges of Humans will be big job for International Universities in near future because they target the Generation - Z. To try to help those International Universities opening the door to the mesmerizing, immersive branding, the Marketing Research have been undertaken. The main goal of the study was to establish the model for Immersive Branding at International Universities and answer on many questions what logically arises in university life. The type of Delphi Surveys entitled as an Expert Studies was undertaken for one great mission, to help International Universities to open the opportunities to Phygital activities with reliable knowledge with Model of Immersive Branding. The Questionnaire sent to Experts of Education were covering professional type of questions from education to segmentation of customers, branding, attitude to students, and knowledge to Immersive Marketing. The research results being very interesting and encouraging enough to make author to establish the New Model of Immersive Experiential Branding for International Universities.

Keywords: branding, immersive marketing, students, university

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Authors: Abdullah A. AlShaher

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In this paper, we demonstrate how regression curves can be used to recognize 2D non-rigid handwritten shapes. Each shape is represented by a set of non-overlapping uniformly distributed landmarks. The underlying models utilize 2^nd order of polynomials to model shapes within a training set. To estimate the regression models, we need to extract the required coefficients which describe the variations for a set of shape class. Hence, a least square method is used to estimate such modes. We then proceed by training these coefficients using the apparatus Expectation Maximization algorithm. Recognition is carried out by finding the least error landmarks displacement with respect to the model curves. Handwritten isolated Arabic characters are used to evaluate our approach.

Keywords: character recognition, regression curves, handwritten Arabic letters, expectation maximization algorithm

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Authors: Duangsamorn Rungsawanpho

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The objectives of this paper are to explore the corporate cultures management as determinants of employee retention company in Thailand. This study using mixed method methodology. Data collection using questionnaires and in-depth interviews. The statistics used for data analysis were percentage, mean, standard deviation and inferential statistics will include. The results show that the corporate management culture is perfect for any organization but it depends on the business and the industry because the situations or circumstances that corporate executives are met is different. Because the finding explained that the employees of the company determine the achievement of value-oriented by the corporate culture and international relations is perceived most value for their organizations. In additional we found the employees perceiving with participation can be interpreted as a positive example, many employees feel that they are part of management because they care about their opinions or ideas related with their work.

Keywords: corporate culture, employee retention, retention of employees, management approaches

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Authors: Akram Hatami, Naser Firoozi, Vesa Puhakka

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Ethics and responsibility are rapidly becoming a distinguishing feature of organizations. In this paper, we analyze ethics and responsibility in shadow factories in China. We engage ourselves with Bauman’s moral impulse perspective because his idea can contextualize ethics and responsibility. Moral impulse is a feeling of a selfless, infinite and unconditional responsibility towards, and care for, Others. We analyze a case study from a secondary data source because, for such a critical phenomenon as business ethics in shadow factories, collecting primary data is difficult, since they are unregistered factories. We argue that there has not been enough attention given to the ethics and responsibility in shadow factories in China. Our main goal is to demonstrate that, considering the Other, more importantly the employees, in ethical decision-making is a simple instruction beyond the narrow version of ethics by ethical codes and rules.

Keywords: moral impulse, responsibility, shadow factories, Bauman’s moral impulse

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Authors: Seyede Sanaz Seyedebrahimi, Shima Rahimi, Shohreh Fakhari, Ali Jalili

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Background: CXCR4, as a chemokine receptor, plays well-known roles in various types of cancers. Several studies have been conducted to overcome CXCR4 axis acts in multiple myeloma (MM) pathogenesis and progression. Dexamethasone, a standard treatment for multiple myeloma, has been shown to increase CXCR4 levels in multiple myeloma cell lines. Herein, we focused on the effects of metformin and dexamethasone on CXCR4 at the cellular level and the migration rate of cell lines after exposure to a combination compared to single-agent models. Materials and Method: Multiple myeloma cell lines (U266 and RPMI8226) were cultured with different metformin and dexamethasone concentrations in single-agent and combination models. The simultaneous combination doses were calculated by CompuSyn software. Cell surface and mRNA expression of CXCR4 were determined using flow cytometry and the quantitative reverse transcription-polymerase chain reaction (qRT-PCR) assay, respectively. The Transwell cell migration assay evaluated the migration ability. Results: In concurred with previous studies, our results showed a dexamethasone up-regulation effect on CXCR4 in a dose-dependent manner. Although, the metformin single-agent model could reduce CXCR4 expression of U266 and RPMI8226 in cell surface and mRNA expression level. Moreover, the administration of metformin and dexamethasone simultaneously exerted a higher suppression effect on CXCR4 expression than the metformin single-agent model. The migration rate through the combination model's matrigel membrane was remarkably lower than the metformin and dexamethasone single-agent model. Discussion: According to our findings, the combination of metformin and dexamethasone effectively inhibited dexamethasone-induced CXCR4 expression in multiple myeloma cell lines. As a result, metformin may be counted as an alternative medicine combined with other chemotherapies to combat multiple myeloma. However, more research is required.

Keywords: CXCR4, dexamethasone, metformin, migration, multiple myeloma

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Authors: Yasser F. Hassan

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The reduction or removal of noise in a color image is an essential part of image processing, whether the final information is used for human perception or for an automatic inspection and analysis. This paper describes the modeling system based on the rough neural network model to adaptive cellular automata for various image processing tasks and noise remover. In this paper, we consider the problem of object processing in colored image using rough neural networks to help deriving the rules which will be used in cellular automata for noise image. The proposed method is compared with some classical and recent methods. The results demonstrate that the new model is capable of being trained to perform many different tasks, and that the quality of these results is comparable or better than established specialized algorithms.

Keywords: rough sets, rough neural networks, cellular automata, image processing

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Authors: Muhammad Azeem Qureshi, Hammad Tahir, Fawwad Mahmood Butt

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Purpose: This study examines empirically the effect of brand satisfaction, brand trust and brand experience on brand loyalty which can be helpful to retain and increase customer base and satisfying customer needs as well. Methodology: Data has been collected on convenient sampling method and cause and effect among variables has been measured by applying regression analysis technique. Findings: Finding of this study have supported the proposed hypotheses and results show that brand loyalty is significantly explained by brand satisfaction, brand trust and brand experience. Practical Implications: The outcome of this study provides a useful framework and importance of brand loyalty culture in Pakistan. Marketers can be benefited trough the findings of this study.

Keywords: brand experience, brand satisfaction, brand trust, brand loyalty, hair-care products

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Authors: Cheyenne Johnson, Samantha Robinson, Christina Chant, Ann M. Mitchell, Carol Price, Carmel Clancy, Adam Searby, Deborah S. Finnell

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Introduction: Substance use along the continuum from at-risk use to a substance use disorder (SUD) contributes substantially to the burden of disease and related harms worldwide. There is a growing body of literature that highlights the lack of substance use related content in nursing curricula. Furthermore, there is also a lack of consensus on key competencies necessary for entry-level nurses. Globally, there is a lack of established nursing competencies related to prevention, health promotion, harm reduction and treatment of at-risk substance use and SUDs. At a critical time in public health, this gap in nursing curricula contributes to a lack of preparation for entry-level nurses to support people along the continuum of substance use. Thus, in practice, early opportunities for screening, support, and interventions may be missed. To address this gap, an international committee was convened to develop international entry-level nursing competencies specifying the knowledge, skills, and abilities that all nurses should possess in order to address the continuum of substance use. Methodology: An international steering committee, including representation from Canada, United States, United Kingdom, and Australia was established to lead this work over a one-year time period. The steering committee conducted a scoping review, undertaken to examine nursing competency frameworks, and to inform a competency structure that would guide this work. The next steps were to outline key competency areas and establish leaders for working groups to develop the competencies. In addition, a larger international committee was gathered to contribute to competency working groups, review the collective work and concur on the final document. Findings: A comprehensive framework was developed with competencies covering a wide spectrum of substance use across the lifespan and in the context of prevention, health promotion, harm reduction and treatment, including special populations. The development of this competency-based framework meets an identified need to provide guidance for universities, health authorities, policy makers, nursing regulators and other organizations that provide and support nursing education which focuses on care for patients and families with at-risk substance use and SUDs. Conclusion: Utilizing these global competencies as expected outcomes of an educational and skill building curricula for entry-level nurses holds great promise for incorporating evidence-informed training in the care and management of people across the continuum of substance use.

Keywords: addiction nursing, addiction nursing curriculum, competencies, substance use

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Authors: Marine Hascoet, Valentina Giaconi, Ludivine Jamain

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The aim of our study is to examine if the family socio-economic status (SES) has an influence on students’ academic achievement. We first make the hypothesis that the more their families have financial and social resources, the more students succeed at school. We second make the hypothesis that this family SES has also an impact on parents’ expectations about their children educational outcomes. Moreover, we want to study if that parents’ expectations play the role of mediator between parents’ socio-economic status and the student’ self-concept and academic outcome. We test this model with a longitudinal design thanks to the census-based assessment from the System of Measurement of the Quality of Education (SIMCE). The SIMCE tests aim to assess all the students attending to regular education in a defined level. The sample used in this study came from the SIMCE assessments done three times: in 4th, 8th and 11th grade during the years 2007, 2011 and 2014 respectively. It includes 156.619 students (75.084 boys and 81.535 girls) that had valid responses for the three years. The family socio-economic status was measured at the first assessment (in 4th grade). The parents’ educational expectations and the students’ self-concept were measured at the second assessment (in 8th grade). The achievement score was measured twice; once when children were in 4th grade and a second time when they were in 11th grade. To test our hypothesis, we have defined a structural equation model. We found that our model fit well the data (CFI = 0.96, TLI = 0.95, RMSEA = 0.05, SRMR = 0.05). Both family SES and prior achievements predict parents’ educational expectations and effect of SES is important in comparison to the other coefficients. These expectations predict students’ achievement three years later (with prior achievement controlled) but not their self-concept. Our model explains 51.9% of the achievement in the 11th grade. Our results confirm the importance of the parents’ expectations and the significant role of socio-economic status in students’ academic achievement in Chile.

Keywords: Chilean context, parent’s expectations, school achievement, self-concept, socio-economic status

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Authors: Godwin Chigozie Okpara

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This paper using standard GARCH, EGARCH, and TARCH models on day of the week return series (of 246 days) from the Nigerian Stock market estimated the model variants’ VaR. An asymmetric return distribution and fat-tail phenomenon in financial time series were considered by estimating the models with normal, student t and generalized error distributions. The analysis based on Akaike Information Criterion suggests that the EGARCH model with student t innovation distribution can furnish more accurate estimate of VaR. In the light of this, we apply the likelihood ratio tests of proportional failure rates to VaR derived from EGARCH model in order to determine the short and long positions VaR performances. The result shows that as alpha ranges from 0.05 to 0.005 for short positions, the failure rate significantly exceeds the prescribed quintiles while it however shows no significant difference between the failure rate and the prescribed quantiles for long positions. This suggests that investors and portfolio managers in the Nigeria stock market have long trading position or can buy assets with concern on when the asset prices will fall. Precisely, the VaR estimates for the long position range from -4.7% for 95 percent confidence level to -10.3% for 99.5 percent confidence level.

Keywords: downside risk, value-at-risk, failure rate, kupiec LR tests, GARCH models

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Authors: Lisa Rudolfsson

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Socio-cognitive factors, such as social support and attribution of blame, influence the victim’s psychological adjustment after the abuse. Furthermore, the response from the person that the victim first confides to effect adjustment following the abuse. In Sweden, although police are investigating most of the reported cases of rape, very few rape-cases leads to trial and sentence. For many women who have been raped, contact with the police officer when reporting the crime will, therefore, be the most notable experience of how representatives for the Swedish society regard and handle what has happened. Hence, it seems urgent to gather information about these initial meetings. This study is part of a three-year research project, titled 'Female rape victims: Quality of initial police and medical care contact', funded by the Swedish Crime Victim and Support Authority. The focus of this study was on police officers in Sweden: their thoughts and experiences of meeting with raped women. Forthcoming are interviews with raped women about their experiences of meeting with police. Sixteen police officers participated in three focus groups and one interview. The participants consisted of five men and eleven women. Focus groups and interview were audio recorded and transcribed verbatim. The material was analyzed using thematic analysis. Participants described how violence against women was not a priority in Swedish society or within the Police Authority. They talked about rape cases as a Sisyphean work-task that put high demands on them, while they also lacked training and support. They expressed a wish to offer the woman some kind of restoration, and they talked about their work as potentially making a difference for the woman – even if she did not get juridical justice. However, participants also described that they did not feel validated in their hard work. They talked about working rape cases as causing them a great deal of frustration - directed towards the Police Authority, the juridical system, colleagues, and sometimes towards the woman. Participants also described how meeting with raped women was a work that affected them in a personal manner. Listening to stories about sexual violence made the participants sad, and they described it as a struggle to understand. They described wondering how the woman’s life turned out and how they sometimes questioned if they had done enough. Some of the conclusions concern the lack of prerequisites needed for police officers to be able to offer a good-enough treatment of raped women, as well as the lack of tools needed for police officers to care for themselves. In lack of training, validation, and support, the knowledge of how to offer a good- enough treatment of raped women becomes a task learned by doing. Attempts to offer, if not legal justice, then at least some kind of restoration becomes a personal task, dependent on individual police officers. It seems urgent that we address the risk of police officers’ frustration building up to be detrimental for both the crime victim and the officer her/himself.

Keywords: focus groups, police, raped women, restoration

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Authors: Taekyun Hur, Yoonyoung Kim, Junkyu Lim

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Previous works on leisure activities had been categorizing activities arbitrarily and subjectively while focusing on a single dimension (e.g. active-passive, individual-group). To overcome these problems, this study proposed a Korean leisure activities’ matrix model that considered multidimensional features of leisure activities, which was comprised of 3 main factors and 6 sub factors: (a) Active (physical, mental), (b) Relational (quantity, quality), (c) Expert (entry barrier, possibility of improving). We developed items for measuring the degree of each dimension for every leisure activity. Using the developed Leisure Activities Dimensions (LAD) questionnaire, we investigated the presented dimensions of a total of 78 leisure activities which had been enjoyed by most Koreans recently (e.g. watching movie, taking a walk, watching media). The study sample consisted of 1348 people (726 men, 658 women) ranging in age from teenagers to elderlies in their seventies. This study gathered 60 data for each leisure activity, a total of 4860 data, which were used for statistical analysis. First, this study compared 3-factor model (Activity, Relation, Expertise) fit with 6-factor model (physical activity, mental activity, relational quantity, relational quality, entry barrier, possibility of improving) fit by using confirmatory factor analysis. Based on several goodness-of-fit indicators, the 6-factor model for leisure activities was a better fit for the data. This result indicates that it is adequate to take account of enough dimensions of leisure activities (6-dimensions in our study) to specifically apprehend each leisure attributes. In addition, the 78 leisure activities were cluster-analyzed with the scores calculated based on the 6-factor model, which resulted in 8 leisure activity groups. Cluster 1 (e.g. group sports, group musical activity) and Cluster 5 (e.g. individual sports) had generally higher scores on all dimensions than others, but Cluster 5 had lower relational quantity than Cluster 1. In contrast, Cluster 3 (e.g. SNS, shopping) and Cluster 6 (e.g. playing a lottery, taking a nap) had low scores on a whole, though Cluster 3 showed medium levels of relational quantity and quality. Cluster 2 (e.g. machine operating, handwork/invention) required high expertise and mental activity, but low physical activity. Cluster 4 indicated high mental activity and relational quantity despite low expertise. Cluster 7 (e.g. tour, joining festival) required not only moderate degrees of physical activity and relation, but low expertise. Lastly, Cluster 8 (e.g. meditation, information searching) had the appearance of high mental activity. Even though clusters of our study had a few similarities with preexisting taxonomy of leisure activities, there was clear distinctiveness between them. Unlike the preexisting taxonomy that had been created subjectively, we assorted 78 leisure activities based on objective figures of 6-dimensions. We also could identify that some leisure activities, which used to belong to the same leisure group, were included in different clusters (e.g. filed ball sports, net sports) because of different features. In other words, the results can provide a different perspective on leisure activities research and be helpful for figuring out what various characteristics leisure participants have.

Keywords: leisure, dimensional model, activity, relationship, expertise

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Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Daniyal Haider, Xiaodong Yang

Abstract:

Chest X-rays are instrumental in the detection and monitoring of a wide array of diseases, including viral infections such as COVID-19, tuberculosis, pneumonia, lung cancer, and various cardiac and pulmonary conditions. To enhance the accuracy of diagnosis, artificial intelligence (AI) algorithms, particularly deep learning models like Convolutional Neural Networks (CNNs), are employed. However, these deep learning models demand a substantial and varied dataset to attain optimal precision. Generative Adversarial Networks (GANs) can be employed to create new data, thereby supplementing the existing dataset and enhancing the accuracy of deep learning models. Nevertheless, GANs have their limitations, such as issues related to stability, convergence, and the ability to distinguish between authentic and fabricated data. In order to overcome these challenges and advance the detection and classification of CXR normal and abnormal images, this study introduces a distinctive technique known as DCWGAN (Diverse Conditional Wasserstein GAN) for generating synthetic chest X-ray (CXR) images. The study evaluates the effectiveness of this Idiosyncratic DCWGAN technique using the ResNet50 model and compares its results with those obtained using the traditional GAN approach. The findings reveal that the ResNet50 model trained on the DCWGAN-generated dataset outperformed the model trained on the classic GAN-generated dataset. Specifically, the ResNet50 model utilizing DCWGAN synthetic images achieved impressive performance metrics with an accuracy of 0.961, precision of 0.955, recall of 0.970, and F1-Measure of 0.963. These results indicate the promising potential for the early detection of diseases in CXR images using this Inimitable approach.

Keywords: CNN, classification, deep learning, GAN, Resnet50

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