Search results for: PU decision

Authors: Shiva Hashemi, Azizan Marzuki, S. Kiumarsi

Abstract:

In recent years, conference destinations have been highly competitive; therefore, it is necessary to know about the behaviours of conference participants such as the process of their decision-making and the assessment of perceived conference quality. A conceptual research framework based on the Theory of Planned Behaviour model is presented in this research to get better understanding factors that influence it. This research study highlights key factors presented in previous studies in which behaviour intentions of participants are affected by the quality of conference. Therefore, this study is believed to provide an idea that conference participants should be encouraged to contribute to the quality and behaviour intention of the conference.

Keywords: conference, attendees, service quality, perceives value, trust, behavioural intention.

Procedia PDF Downloads 300

Authors: Yuko Ishiwaka, Tomohiro Yoshida, Tadateru Itoh

Abstract:

Human makes preparation called readiness potential unconsciously (RP) before awareness of their own decision. For example, when recognizing a button and pressing the button, the RP peaks are observed 200 ms before the initiation of the movement. It has been known that the preparatory movements are acquired before actual movements, but it has not been still well understood how humans can obtain the RP during their growth. On the proposition of why the brain must respond earlier, we assume that humans have to adopt the dangerous environment to survive and then obtain the behavior to cover the various time lags distributed in the body. Without RP, humans cannot take action quickly to avoid dangerous situations. In taking action, the brain makes decisions, and signals are transmitted through the Spinal Cord to the muscles to the body moves according to the laws of physics. Our research focuses on the time lag of the neuron signal transmitting from a brain to muscle via a spinal cord. This time lag is one of the essential factors for readiness potential. We propose a firing pattern controller model of a motor nerve system considered innervation and jitter, which produces time lag. In our simulation, we adopt innervation and jitter in our proposed muscle-skeleton model, because these two factors can create infinitesimal time lag. Q10 Hodgkin Huxley model to calculate action potentials is also adopted because the refractory period produces a more significant time lag for continuous firing. Keeping constant power of muscle requires cooperation firing of motor neurons because a refractory period stifles the continuous firing of a neuron. One more factor in producing time lag is slow or fast-twitch. The Expanded Hill Type model is adopted to calculate power and time lag. We will simulate our model of muscle skeleton model by controlling the firing pattern and discuss the relationship between the time lag of physics and neurons. For our discussion, we analyze the time lag with our simulation for knee bending. The law of inertia caused the most influential time lag. The next most crucial time lag was the time to generate the action potential induced by innervation and jitter. In our simulation, the time lag at the beginning of the knee movement is 202ms to 203.5ms. It means that readiness potential should be prepared more than 200ms before decision making.

Keywords: firing patterns, innervation, jitter, motor nerve system, readiness potential

Procedia PDF Downloads 815

Authors: Marta Fernández Batalla, José María Santamaría García, Maria Lourdes Jiménez Rodríguez, Roberto Barchino Plata, Adriana Cercas Duque, Enrique Monsalvo San Macario

Abstract:

Background: Primary Care Nursing is taking more autonomy in clinical decisions. One of the most frequent therapies to solve is related to the problems of maintaining a sufficient supply of food. Nursing diagnoses related to food are addressed by the nurse-family and community as the first responsible. Objectives and interventions are set according to each patient. To improve the goal setting and the treatment of these care problems, a technological tool is developed to help nurses. Objective: To evaluate the computational tool developed to support the clinical decision in feeding problems. Material and methods: A cross-sectional descriptive study was carried out at the Meco Health Center, Madrid, Spain. The study population consisted of four specialist nurses in primary care. These nurses tested the tool on 30 people with ‘need for nutritional therapy’. Subsequently, the usability of the tool and the satisfaction of the professional were sought. Results: A simple and convenient computational tool is designed for use. It has 3 main entrance fields: age, size, sex. The tool returns the following information: BMI (Body Mass Index) and caloric consumed by the person. The next step is the caloric calculation depending on the activity. It is possible to propose a goal of BMI or weight to achieve. With this, the amount of calories to be consumed is proposed. After using the tool, it was determined that the tool calculated the BMI and calories correctly (in 100% of clinical cases). satisfaction on nutritional assessment was ‘satisfactory’ or ‘very satisfactory’, linked to the speed of operations. As a point of improvement, the options of ‘stress factor’ linked to weekly physical activity. Conclusion: Based on the results, it is clear that the computational tools of decision support are useful in the clinic. Nurses are not only consumers of computational tools, but can develop their own tools. These technological solutions improve the effectiveness of nutrition assessment and intervention. We are currently working on improvements such as the calculation of protein percentages as a function of protein percentages as a function of stress parameters.

Keywords: feeding behavior health, nutrition therapy, primary care nursing, technology assessment

Procedia PDF Downloads 220

Authors: Mumtaz Ipek, Burak Erkayman

Abstract:

Due date is assigned as an input for scheduling problems. At the same time, due date is selected as a decision variable for real time scheduling applications. Correct determination of due dates increases shop floor performance and number of jobs completed on time. This subject has been mentioned widely in the literature. Moreover rules for due date determination have been developed from analytical analysis. When a job arrives to the shop floor, a due date is assigned for delivery. Various due date determination methods are used in the literature. In this study six different due date methods are implemented for a hypothetical dynamic job shop and the performances of the due date methods are compared.

Keywords: scheduling, dynamic job shop, due date assignment, management engineering

Procedia PDF Downloads 543

Authors: Younghoon Kim, Seoung Bum Kim

Abstract:

One-class classification plays an important role in detecting outlier and abnormality from normal observations. In the previous research, several attempts were made to extend the scope of application of the one-class classification techniques to statistical process control problems. For most previous approaches, such as support vector data description (SVDD) control chart, the design of the control limits is commonly based on the assumption that the proportion of abnormal observations is approximately equal to an expected Type I error rate in Phase I process. Because of the limitation of the one-class classification techniques based on convex optimization, we cannot make the proportion of abnormal observations exactly equal to expected Type I error rate: controlling Type I error rate requires to optimize constraints with integer decision variables, but convex optimization cannot satisfy the requirement. This limitation would be undesirable in theoretical and practical perspective to construct effective control charts. In this work, to address the limitation of previous approaches, we propose the one-class classification algorithm based on the mixed integer programming technique, which can solve problems formulated with continuous and integer decision variables. The proposed method minimizes the radius of a spherically shaped boundary subject to the number of normal data to be equal to a constant value specified by users. By modifying this constant value, users can exactly control the proportion of normal data described by the spherically shaped boundary. Thus, the proportion of abnormal observations can be made theoretically equal to an expected Type I error rate in Phase I process. Moreover, analogous to SVDD, the boundary can be made to describe complex structures by using some kernel functions. New multivariate control chart applying the effectiveness of the algorithm is proposed. This chart uses a monitoring statistic to characterize the degree of being an abnormal point as obtained through the proposed one-class classification. The control limit of the proposed chart is established by the radius of the boundary. The usefulness of the proposed method was demonstrated through experiments with simulated and real process data from a thin film transistor-liquid crystal display.

Keywords: control chart, mixed integer programming, one-class classification, support vector data description

Procedia PDF Downloads 166

Authors: Fatema Akram, Mohammad G. Rasul, M. Masud K. Khan, M. Sharif I. I. Amir

Abstract:

Australia is a country of some 7,700 million square kilometres with a population of about 22.6 million. At present water security is a major challenge for Australia. In some areas the use of water resources is approaching and in some parts it is exceeding the limits of sustainability. A focal point of proposed national water conservation programs is the recycling of both urban storm-water and treated wastewater. But till now it is not widely practiced in Australia, and particularly storm-water is neglected. In Australia, only 4% of storm-water and rainwater is recycled, whereas less than 1% of reclaimed wastewater is reused within urban areas. Therefore, accurately monitoring, assessing and predicting the availability, quality and use of this precious resource are required for better management. As storm-water is usually of better quality than untreated sewage or industrial discharge, it has better public acceptance for recycling and reuse, particularly for non-potable use such as irrigation, watering lawns, gardens, etc. Existing storm-water recycling practice is far behind of research and no robust technologies developed for this purpose. Therefore, there is a clear need for using modern technologies for assessing feasibility of storm-water harvesting and reuse. Numerical modelling has, in recent times, become a popular tool for doing this job. It includes complex hydrological and hydraulic processes of the study area. The hydrologic model computes storm-water quantity to design the system components, and the hydraulic model helps to route the flow through storm-water infrastructures. Nowadays water quality module is incorporated with these models. Integration of Geographic Information System (GIS) with these models provides extra advantage of managing spatial information. However for the overall management of a storm-water harvesting project, Decision Support System (DSS) plays an important role incorporating database with model and GIS for the proper management of temporal information. Additionally DSS includes evaluation tools and Graphical user interface. This research aims to critically review and discuss all the aspects of storm-water harvesting and reuse such as available guidelines of storm-water harvesting and reuse, public acceptance of water reuse, the scopes and recommendation for future studies. In addition to these, this paper identifies, understand and address the importance of modern technologies capable of proper management of storm-water harvesting and reuse.

Keywords: storm-water management, storm-water harvesting and reuse, numerical modelling, geographic information system, decision support system, database

Procedia PDF Downloads 357

Authors: Thomas Rockstuhl, Kok Yee Ng, Guido Gianasso, Soon Ang

Abstract:

Two meta-analyses show that intercultural experience is not related to intercultural adaptation or performance in international assignments. These findings have prompted calls for a deeper grounding of research on international experience in the phenomenon of global work. Two issues, in particular, may limit current understanding of the relationship between international experience and global work performance. First, intercultural experience is too broad a construct that may not sufficiently capture the essence of global work, which to a large part involves sensemaking and managing intercultural conflicts. Second, the psychological mechanisms through which intercultural experience affects performance remains under-explored, resulting in a poor understanding of how experience is translated into learning and performance outcomes. Drawing on recognition primed decision-making (RPD) research, the current study advances a cognitive processing model to highlight the importance of intercultural conflict familiarity. Compared to intercultural experience, intercultural conflict familiarity is a more targeted construct that captures individuals’ previous exposure to dealing with intercultural conflicts. Drawing on RPD theory, we argue that individuals’ intercultural conflict familiarity enhances their ability to make accurate judgments and generate effective responses when intercultural conflicts arise. In turn, the ability to make accurate situation judgements and effective situation responses is an important predictor of global work performance. A relocation program within a multinational enterprise provided the context to test these hypotheses using a time-lagged, multi-source field study. Participants were 165 employees (46% female; with an average of 5 years of global work experience) from 42 countries who relocated from country to regional offices as part a global restructuring program. Within the first two weeks of transfer to the regional office, employees completed measures of their familiarity with intercultural conflicts, cultural intelligence, cognitive ability, and demographic information. They also completed an intercultural situational judgment test (iSJT) to assess their situation judgment and situation response. The iSJT comprised four validated multimedia vignettes of challenging intercultural work conflicts and prompted employees to provide protocols of their situation judgment and situation response. Two research assistants, trained in intercultural management but blind to the study hypotheses, coded the quality of employee’s situation judgment and situation response. Three months later, supervisors rated employees’ global work performance. Results using multilevel modeling (vignettes nested within employees) support the hypotheses that greater familiarity with intercultural conflicts is positively associated with better situation judgment, and that situation judgment mediates the effect of intercultural familiarity on situation response quality. Also, aggregated situation judgment and situation response quality both predicted supervisor-rated global work performance. Theoretically, our findings highlight the important but under-explored role of familiarity with intercultural conflicts; a shift in attention from the general nature of international experience assessed in terms of number and length of overseas assignments. Also, our cognitive approach premised on RPD theory offers a new theoretical lens to understand the psychological mechanisms through which intercultural conflict familiarity affects global work performance. Third, and importantly, our study contributes to the global talent identification literature by demonstrating that the cognitive processes engaged in resolving intercultural conflicts predict actual performance in the global workplace.

Keywords: intercultural conflict familiarity, job performance, judgment and decision making, situational judgment test

Procedia PDF Downloads 167

Authors: Poornima Gupta, Sadaf Siraj

Abstract:

The study examined the organizational causes of organizational stress in women executives and entrepreneurs in India. This was done so that mediation strategies could be developed to combat the organizational stress experienced by them, in order to retain the female employees as well as attract quality talent. The data for this research was collected through the self- administered survey, from the women executives across various industries working at different levels in management. The research design of the study was descriptive and cross-sectional. It was carried out through a self-administered questionnaire filled in by the women executives and entrepreneurs in the NCR region. Multistage sampling involving stratified random sampling was employed. A total of 1000 questionnaires were distributed out of which 450 were returned and after cleaning the data 404 were fit to be considered for analyses. The overall findings of the study suggested that there were various job-related factors that induce stress. Fourteen factors were identified which were a major cause of stress among the working women by applying Factor analysis. The study also assessed the demographic factors which influence the stress in women executives across various industries. The findings show that the women, no doubt, were stressed by organizational factors. The mean stress score was 153 (out of a possible score of 196) indicating high stress. There appeared to be an inverse relationship between the marital status, age, education, work experience, and stress. Married women were less stressed compared to single women employees. Similarly, female employees 29 years or younger experienced more stress at work. Women having education up to 12th standard or less were more stressed compared to graduates and post graduates. Women who had spent more than two years in the same organization perceived more stress compared to their counterparts. Family size and income, interestingly, had no significant impact on stress. The study also established that the level of stress experienced by women across industries differs considerably. Banking sector emerged as the industry where the women experienced the most stress followed by Entrepreneurs, Medical, BPO, Advertising, Government, Academics, and Manufacturing, in that order. The results contribute to the better understanding of the personal and economic factors surrounding job stress and working women. It concludes that the organizations need to be sensitive to the women’s needs. Organizations are traditionally designed around men with the rules made by the men for the men. Involvement of women in top positions, decision making, would make them feel more useful and less stressed. The invisible glass ceiling causes more stress than realized among women. Less distinction between the men and women colleagues in terms of giving responsibilities, involvement in decision making, framing policies, etc. would go a long way to reduce stress in women.

Keywords: women, stress, gender in management, women in management

Procedia PDF Downloads 247

Authors: Seyed Habib A. Rahmati, Mohamad Hasan Sadeghpour, Parsa Fallah Sheikhlari

Abstract:

Location quotient (LQ) is a comparison technique that represents emphasized economic structure of single zone versus the standard area to identify specialty for every zone. In another words, the exact calculation of this metric can show the main core competencies and critical capabilities of an area to the decision makers. This research focus on the exact calculation of the LQ for an Iranian Province called Qazvin and within a case study introduces LQ of the capable industries of Qazvin. Finally, through different graphs and tables, it creates an opportunity to compare the recognized capabilities.

Keywords: location quotient, case study, province analysis, core competency

Procedia PDF Downloads 642

Authors: Stefan Ninković

Abstract:

The main purpose of this paper is to examine the different theoretical approaches and relevant empirical evidence and thus, recognize some of the most pressing challenges faced by school leaders. This paper starts from the fact that the new mission of the school is characterized by the need for stronger coordination among students' academic, social and emotional learning. In this sense, school leaders need to focus their commitment, vision and leadership on the issues of students' attitudes, language, cultural and social background, and sexual orientation. More specifically, they should know what a good teaching is for student’s at-risk, students whose first language is not dominant in school, those who’s learning styles are not in accordance with usual teaching styles, or who are stigmatized. There is a rather wide consensus around the fact that the traditionally popular concept of instructional leadership of the school principal is no longer sufficient. However, in a number of "pro-leadership" circles, including certain groups of academic researchers, consultants and practitioners, there is an established tendency of attributing school principal an extraordinary influence towards school achievements. On the other hand, the situation in which all employees in the school are leaders is a utopia par excellence. Although leadership obviously can be efficiently distributed across the school, there are few findings that speak about sources of this distribution and factors making it sustainable. Another idea that is not particularly new, but has only recently gained in importance is related to the fact that the collective capacity of the school is an important resource that often remains under-cultivated. To understand the nature and power of collaborative school cultures, it is necessary to know that these operate in a way that they make their all collective members' tacit knowledge explicit. In this sense, the question is how leaders in schools can shape collaborative culture and create social capital in the school. Pressure exerted on schools to systematically collect and use the data has been accompanied by the need for school leaders to develop new competencies. The role of school leaders is critical in the process of assessing what data are needed and for what purpose. Different types of data are important: test results, data on student’s absenteeism, satisfaction with school, teacher motivation, etc. One of the most important tasks of school leaders are data-driven decision making as well as ensuring transparency of the decision-making process. Finally, the question arises whether the existing models of school leadership are compatible with the current social and economic trends. It is necessary to examine whether and under what conditions schools are in need for forms of leadership that are different from those that currently prevail. Closely related to this issue is also to analyze the adequacy of different approaches to leadership development in the school.

Keywords: educational changes, leaders, leadership, school

Procedia PDF Downloads 329

Authors: Catherine Bradshaw

Abstract:

Educators often report difficulty managing behavior problems and other mental health concerns that students display at school. These concerns also interfere with the learning process and can create distraction for teachers and other students. As such, schools play an important role in both preventing and intervening with students who experience these types of challenges. A number of models have been proposed to serve as a framework for delivering prevention and early intervention services in schools. One such model is called Positive Behavioral Interventions and Supports (PBIS), which has been scaled-up to over 26,000 schools in the U.S. and many other countries worldwide. PBIS aims to improve a range of student outcomes through early detection of and intervention related to behavioral and mental health symptoms. PBIS blends and applies social learning, behavioral, and organizational theories to prevent disruptive behavior and enhance the school’s organizational health. PBIS focuses on creating and sustaining tier 1 (universal), tier 2 (selective), and tier 3 (individual) systems of support. Most schools using PBIS have focused on the core elements of the tier 1 supports, which includes the following critical features. The formation of a PBIS team within the school to lead implementation. Identification and training of a behavioral support ‘coach’, who serves as a on-site technical assistance provider. Many of the individuals identified to serve as a PBIS coach are also trained as a school psychologist or guidance counselor; coaches typically have prior PBIS experience and are trained to conduct functional behavioral assessments. The PBIS team also identifies a set of three to five positive behavioral expectations that are implemented for all students and by all staff school-wide (e.g., ‘be respectful, responsible, and ready to learn’); these expectations are posted in all settings across the school, including in the classroom, cafeteria, playground etc. All school staff define and teach the school-wide behavioral expectations to all students and review them regularly. Finally, PBIS schools develop or adopt a school-wide system to reward or reinforce students who demonstrate those 3-5 positive behavioral expectations. Staff and administrators create an agreed upon system for responding to behavioral violations that include definitions about what constitutes a classroom-managed vs. an office-managed discipline problem. Finally, a formal system is developed to collect, analyze, and use disciplinary data (e.g., office discipline referrals) to inform decision-making. This presentation provides a brief overview of PBIS and reports findings from a series of four U.S. based longitudinal randomized controlled trials (RCTs) documenting the impacts of PBIS on school climate, discipline problems, bullying, and academic achievement. The four RCTs include 80 elementary, 40 middle, and 58 high schools and results indicate a broad range of impacts on multiple student and school-wide outcomes. The session will highlight lessons learned regarding PBIS implementation and scale-up. We also review the ways in which PBIS can help educators and school leaders engage in data-based decision-making and share data with other decision-makers and stakeholders (e.g., students, parents, community members), with the overarching goal of increasing use of evidence-based programs in schools.

Keywords: positive behavioral interventions and supports, mental health, randomized trials, school-based prevention

Procedia PDF Downloads 221

Authors: Wissal Ben Arfi, Jean-Michel Sahut

Abstract:

The purpose of this paper is to provide a deeper understanding of the succession process from a knowledge management perspective. By doing that, succession process in family businesses, as an environment for creating and sharing knowledge, was explored. Design/Methodology/Approach: To support our reasoning, we collected qualitative data through 16 in-depth interviews conducted with all decision makers involved in the family businesses succession process in France. These open-ended responses were subsequently exposed to thematic discourse analysis. Findings: Central to this exhibit is the nature and magnitude of knowledge creation and sharing among the actors within the family succession context and how can tacit knowledge sharing facilitate the succession process. We also identified factors that inhibit down the knowledge creation and sharing processes. The sharing and creation of knowledge among members of a family business appear to be a complex process that must be part of a strategy for change. This implies that it requests trust and takes a certain amount of time because it requires organizational change and a clear and coherent strategic vision that is accepted and assimilated by all the members. Professional and leadership skills are of particular importance in knowledge sharing and creation processes. In most cases, tacit knowledge is crucial when it is shared and accumulated collectively. Our findings reveal that managers should find ways of implementing knowledge sharing and creation processes while acknowledging the succession process within family firms. This study highlights the importance of generating knowledge strategies in order to enhance the performance and the success of intergenerational succession. The empirical outcomes contribute to enrich the field of succession management process and enhance the role of knowledge in shaping family performance and longevity. To a large extent, the lessons learned from the study of succession processes in family-owned businesses are that when there is a deliberate effort to introduce a knowledge-based approach, this action becomes a seminal event in the life of the organization. Originality/Value: The paper contributes to the deep understanding of interactions among actors by examining the knowledge creation and sharing processes since current researches in family succession focused on aspects such as personal development of potential, intra-family succession intention, decision-making processes in family businesses. Besides, as succession is one of the key factors that determine the longevity and the performance of family businesses, it also contributes to literature by examining how tacit knowledge is transferred, shared and created in family businesses and how this can facilitate the intergenerational succession process.

Keywords: family-owned businesses, succession process, knowledge, performance

Procedia PDF Downloads 199

Authors: Jaime A. Palma-Mendoza

Abstract:

A supply chain consists of different processes and when conducting supply chain re-design is necessary to identify the relevant processes and select a target for re-design. A solution was developed which consists to identify first the relevant processes using the Supply Chain Operations Reference (SCOR) model, then to use Analytical Hierarchy Process (AHP) for target process selection. An application was conducted in an Airline MRO supply chain re-design project which shows this combination can clearly aid the identification of relevant supply chain processes and the selection of a target process for re-design.

Keywords: decision support systems, multiple criteria analysis, supply chain management

Procedia PDF Downloads 480

Authors: Razi Khalafi

Abstract:

Brain is the information processing center of the human body. Stimuli in form of information are transferred to the brain and then brain makes the decision on how to respond to them. In this research we propose a new partial differential equation which analyses the EEG signals and make a relationship between the incoming stimuli and the brain response to them. In order to test the proposed model, a set of external stimuli applied to the model and the model’s outputs were checked versus the real EEG data. The results show that this model can model the EEG signal well. The proposed model is useful not only for modeling of the EEG signal in case external stimuli but it can be used for the modeling of brain response in case of internal stimuli.

Keywords: Brain, stimuli, partial differential equation, response, eeg signal

Procedia PDF Downloads 417

Authors: Nur Azha Putra Abdul Azim, Denise Cheong, S. Nivedita

Abstract:

Currently, there are no nuclear power reactors among the Association of Southeast Asian Nations (ASEAN) member states (AMS) but there are seven operational nuclear research reactors, and Indonesia is about to construct the region’s first experimental power reactor by the end of the decade. If successful, the experimental power reactor will lay the foundation for the country’s and region’s first nuclear power plant. Despite projecting confidence during the period of nuclear power renaissance in the region in the last decade, none of the AMS has committed to a political decision on the use of nuclear energy and this is largely due to the Fukushima nuclear power accident in 2011. Of the ten AMS, Vietnam, Indonesia and Malaysia have demonstrated the most progress in developing nuclear energy based on the nuclear power infrastructure development assessments made by the International Atomic Energy Agency. Of these three states, Vietnam came closest to building its first nuclear power plant but decided to delay construction further due to safety and security concerns. Meanwhile, Vietnam along with Indonesia and Malaysia continue with their nuclear power infrastructure development and the remaining SEA states, with the exception of Brunei and Singapore, continue to build their expertise and capacity for nuclear power energy. At the current rate of progress, Indonesia is expected to make a national decision on the use of nuclear power by 2023 while Malaysia, the Philippines, and Thailand have included the use of nuclear power in their mid to long-term power development plans. Vietnam remains open to nuclear power but has not placed a timeline. The medium to short-term power development projection in the region suggests that the use of nuclear energy in the region is a matter of 'when' rather than 'if'. In lieu of the prospects for nuclear energy in Southeast Asia (SEA), this presentation will review the literature on ASEAN radiological emergency and preparedness response (EPR) plans and examine ASEAN’s disaster management and emergency framework. Through a combination of institutional mapping and stakeholder analysis methods, which we examine in the context of the international EPR, and nuclear safety and security regimes, we will identify the issues and challenges in developing a regional radiological EPR framework in the SEA. We will conclude with the observation that ASEAN faces serious structural, institutional and governance challenges due to the AMS inherent political structures and history of interstate conflicts, and propose that ASEAN should either enlarge the existing scope of its disaster management and response framework or that its radiological EPR framework should exist as a separate entity.

Keywords: nuclear power, nuclear accident, ASEAN, Southeast Asia

Procedia PDF Downloads 138

Authors: Mina Sadat Orooje, Mohammad Mehdi Latifi, Behnam Fereydooni Eftekhari

Abstract:

The integration of cutting-edge Internet of Things (IoT) technologies with advanced Artificial Intelligence (AI) systems is revolutionizing healthcare facility management. However, the current landscape of hospital building maintenance suffers from slow, repetitive, and disjointed processes, leading to significant financial, resource, and time losses. Additionally, the potential of Building Information Modeling (BIM) in facility maintenance is hindered by a lack of data within digital models of built environments, necessitating a more streamlined data collection process. This paper presents a robust framework that harmonizes AI with BIM-IoT technology to elevate healthcare Facility Maintenance Management (FMM) and address these pressing challenges. The methodology begins with a thorough literature review and requirements analysis, providing insights into existing technological landscapes and associated obstacles. Extensive data collection and analysis efforts follow to deepen understanding of hospital infrastructure and maintenance records. Critical AI algorithms are identified to address predictive maintenance, anomaly detection, and optimization needs alongside integration strategies for BIM and IoT technologies, enabling real-time data collection and analysis. The framework outlines protocols for data processing, analysis, and decision-making. A prototype implementation is executed to showcase the framework's functionality, followed by a rigorous validation process to evaluate its efficacy and gather user feedback. Refinement and optimization steps are then undertaken based on evaluation outcomes. Emphasis is placed on the scalability of the framework in real-world scenarios and its potential applications across diverse healthcare facility contexts. Finally, the findings are meticulously documented and shared within the healthcare and facility management communities. This framework aims to significantly boost maintenance efficiency, cut costs, provide decision support, enable real-time monitoring, offer data-driven insights, and ultimately enhance patient safety and satisfaction. By tackling current challenges in healthcare facility maintenance management it paves the way for the adoption of smarter and more efficient maintenance practices in healthcare facilities.

Keywords: artificial intelligence, building information modeling, healthcare facility maintenance, internet of things integration, maintenance efficiency

Procedia PDF Downloads 40

Authors: Jie Liu, Xudong Luo, Pingping Lin, Yifan Fan

Abstract:

Facebook, Twitter, Weibo, and other social media and significant e-commerce sites generate a massive amount of online texts, which can be used to analyse people’s opinions or sentiments for better decision-making. So, sentiment analysis, especially fine-grained sentiment analysis, is a very active research topic. In this paper, we survey various methods for fine-grained sentiment analysis, including traditional sentiment lexicon-based methods, machine learning-based methods, and deep learning-based methods in aspect/target/attribute-based sentiment analysis tasks. Besides, we discuss their advantages and problems worthy of careful studies in the future.

Keywords: sentiment analysis, fine-grained, machine learning, deep learning

Procedia PDF Downloads 243

Authors: M. Abdullah, Al-Wadud

Abstract:

Sensor-based activity recognition systems usually accounts which sensors have been activated to perform an activity. The system then combines the conditional probabilities of those sensors to represent different activities and takes the decision based on that. However, the information about the sensors which are not activated may also be of great help in deciding which activity has been performed. This paper proposes an approach where the sensory data related to both usage and non-usage of objects are utilized to make the classification of activities. Experimental results also show the promising performance of the proposed method.

Keywords: Naïve Bayesian, based classification, activity recognition, sensor data, object-usage model

Procedia PDF Downloads 313

Authors: Sumit Kumar

Abstract:

The present study aims to identify the factors responsible for the internal migration of students other than push & pull factors; associated with the source region and destination region, respectively, as classified in classical geography. But in this classification of factors responsible for the migration of students, an agency of individual and the family he/she belongs to, have not been recognized which has later become the centre of the argument for describing and analyzing migration in New Economic theory of migration and New Economics of labour migration respectively. In this backdrop, the present study aims to understand the agency of an individual and the family members regarding one’s migration for higher education. Therefore, this study draws upon New Economic theory of migration and New Economics of labour migration for identifying the agency of individual or family in the context of migration. Further, migration for higher education consists not only the decision to migrate but also where to migrate (location), which university, which college and which course to pursue, also. In order to understand the role of various individuals at various stage of student migration, present study seeks help from the social networking approach for migration which identifies the individuals who facilitate the process of migration by reducing negative externalities of migration through sharing information and various other sorts of help to the migrant. Furthermore, this study also aims to rank those individuals who have helped migrants at various stages of migration for higher education in taking a decision, along with the factors responsible for their migration on the basis of their perception. In order to fulfill the above mentioned objectives of this study, quantification of qualitative data (perception of respondents) has been done employing through frequency distribution analysis. Qualitative data has been collected at two levels but questionnaire survey was the tool for data collection at both the occasions. Twenty five students who have migrated to other state for the purpose of higher education have been approached for pre-questionnaire survey consisting open-ended questions while one hundred students belonging to the same clientele have been approached for questionnaire survey consisting close-ended questions. This study has identified social pressure, peer group pressure and parental pressure; variables not constituting push & pull factors, very important for students’ migration. They have been even assigned better ranked by the respondents than push factors. Further, self (migrant themselves) have been ranked followed by parents by the respondents when it comes to take various decisions attached with the process of migration. Therefore, it can be said without sounding cynical that there are other factors other than push & pull factors which do facilitate the process of migration for higher education not only at the level to migrate but also at other levels intrinsic to the process of migration for higher education.

Keywords: agency, migration for higher education, perception, push and pull factors

Procedia PDF Downloads 227

Authors: Benjamin Mugisha Bugingo

Abstract:

Healthcare staffhas been considered as asignificant pillar to the health care system. However, the contest of human resources for health in terms of the turnover of health workers in Uganda has been more distinct in the latest years. The objective of the paper, therefore, were to investigate the influence Role Human resource management functions in on employeeperformance of professional health workers in public district hospitals in Kampala. The study objectives were: to establish the effect of performance management function, financialincentives, non-financial incentives, participation, and involvement in the decision-making on the employee performance of professional health workers in public district hospitals in Kampala. The study was devised in the social exchange theory and the equity theory. This study adopted a descriptive research design using quantitative approaches. The study used a cross-sectional research design with a mixed-methods approach. With a population of 402 individuals, the study considered a sample of 252 respondents, including doctors, nurses, midwives, pharmacists, and dentists from 3 district hospitals. The study instruments entailed a questionnaire as a quantitative data collection tool and interviews and focus group discussions as qualitative data gathering tools. To analyze quantitative data, descriptive statistics were used to assess the perceived status of Human resource management functions and the magnitude of intentions to stay, and inferential statistics were used to show the effect of predictors on the outcome variable by plotting a multiple linear regression. Qualitative data were analyzed in themes and reported in narrative and verbatim quotes and were used to complement descriptive findings for a better understanding of the magnitude of the study variables. The findings of this study showed a significant and positive effect of performance management function, financialincentives, non-financial incentives, and participation and involvement in decision-making on employee performance of professional health workers in public district hospitals in Kampala. This study is expected to be a major contributor for the improvement of the health system in the country and other similar settings as it has provided the insights for strategic orientation in the area of human resources for health, especially for enhanced employee performance in relation with the integrated human resource management approach

Keywords: human resource functions, employee performance, employee wellness, profecial workers

Procedia PDF Downloads 81

Authors: Haji Mohammad Zulfan Farhi Bin Haji Sulaini, Mohammad Azeezudde’en Bin Mohd Ismaon

Abstract:

The demands placed on military athletes extend beyond physical prowess to encompass cognitive resilience in high-stress environments. This study investigates the effects of resilience training on the cognitive performance of military athletes, shedding light on the potential benefits and implications for optimizing their overall readiness. In a rapidly evolving global landscape, armed forces worldwide are recognizing the importance of cognitive resilience alongside physical fitness. The study employs a mixed-methods approach, incorporating quantitative cognitive assessments and qualitative data from military athletes undergoing resilience training programs. Cognitive performance is evaluated through a battery of tests, including measures of memory, attention, decision-making, and reaction time. The participants, drawn from various branches of the military, are divided into experimental and control groups. The experimental group undergoes a comprehensive resilience training program, while the control group receives traditional physical training without a specific focus on resilience. The initial findings indicate a substantial improvement in cognitive performance among military athletes who have undergone resilience training. These improvements are particularly evident in domains such as attention and decision-making. The experimental group demonstrated enhanced situational awareness, quicker problem-solving abilities, and increased adaptability in high-stress scenarios. These results suggest that resilience training not only bolsters mental toughness but also positively impacts cognitive skills critical to military operations. In addition to quantitative assessments, qualitative data is collected through interviews and surveys to gain insights into the subjective experiences of military athletes. Preliminary analysis of these narratives reveals that participants in the resilience training program report higher levels of self-confidence, emotional regulation, and an improved ability to manage stress. These psychological attributes contribute to their enhanced cognitive performance and overall readiness. Moreover, this study explores the potential long-term benefits of resilience training. By tracking participants over an extended period, we aim to assess the durability of cognitive improvements and their effects on overall mission success. Early results suggest that resilience training may serve as a protective factor against the detrimental effects of prolonged exposure to stressors, potentially reducing the risk of burnout and psychological trauma among military athletes. This research has significant implications for military organizations seeking to optimize the performance and well-being of their personnel. The findings suggest that integrating resilience training into the training regimen of military athletes can lead to a more resilient and cognitively capable force. This, in turn, may enhance mission success, reduce the risk of injuries, and improve the overall effectiveness of military operations. In conclusion, this study provides compelling evidence that resilience training positively impacts the cognitive performance of military athletes. The preliminary results indicate improvements in attention, decision-making, and adaptability, as well as increased psychological resilience. As the study progresses and incorporates long-term follow-ups, it is expected to provide valuable insights into the enduring effects of resilience training on the cognitive readiness of military athletes, contributing to the ongoing efforts to optimize military personnel's physical and mental capabilities in the face of ever-evolving challenges.

Keywords: military athletes, cognitive performance, resilience training, cognitive enhancement program

Procedia PDF Downloads 67

Authors: Arindam Chaudhuri

Abstract:

Classification of data has been actively used for most effective and efficient means of conveying knowledge and information to users. The prima face has always been upon techniques for extracting useful knowledge from data such that returns are maximized. With emergence of huge datasets the existing classification techniques often fail to produce desirable results. The challenge lies in analyzing and understanding characteristics of massive data sets by retrieving useful geometric and statistical patterns. We propose a supervised parallel fuzzy rough support vector machine (PFRSVM) for data classification in cloud environment. The classification is performed by PFRSVM using hyperbolic tangent kernel. The fuzzy rough set model takes care of sensitiveness of noisy samples and handles impreciseness in training samples bringing robustness to results. The membership function is function of center and radius of each class in feature space and is represented with kernel. It plays an important role towards sampling the decision surface. The success of PFRSVM is governed by choosing appropriate parameter values. The training samples are either linear or nonlinear separable. The different input points make unique contributions to decision surface. The algorithm is parallelized with a view to reduce training times. The system is built on support vector machine library using Hadoop implementation of MapReduce. The algorithm is tested on large data sets to check its feasibility and convergence. The performance of classifier is also assessed in terms of number of support vectors. The challenges encountered towards implementing big data classification in machine learning frameworks are also discussed. The experiments are done on the cloud environment available at University of Technology and Management, India. The results are illustrated for Gaussian RBF and Bayesian kernels. The effect of variability in prediction and generalization of PFRSVM is examined with respect to values of parameter C. It effectively resolves outliers’ effects, imbalance and overlapping class problems, normalizes to unseen data and relaxes dependency between features and labels. The average classification accuracy for PFRSVM is better than other classifiers for both Gaussian RBF and Bayesian kernels. The experimental results on both synthetic and real data sets clearly demonstrate the superiority of the proposed technique.

Keywords: FRSVM, Hadoop, MapReduce, PFRSVM

Procedia PDF Downloads 481

Authors: Shougi Suliman Abosuliman, Arun Kumar, Firoz Alam

Abstract:

Disaster preparedness is a key success factor for any effective disaster management practices. This paper evaluates the disaster preparedness and management in Saudi Arabia using an empirical investigation approach. It presents the results of the survey conducted by interviewing representatives of the Saudi decision-makers and administrators responsible for disaster control in Jeddah before, during and after flooding in 2009 and 2010. First, demographics of the respondents are presented, followed by quantitative analysis of their views and experiences regarding the Kingdom’s readiness before and after each flood. This is shown as a series of dependent and independent variables. Following this is a list of respondents’ priorities for disaster preparation in the Kingdom.

Keywords: disaster response policy, crisis management, effective service delivery, Jeddah

Procedia PDF Downloads 449

Authors: M. V. Shivaani, P. K. Jain, Surendra S. Yadav

Abstract:

Public Sector Undertakings (PSUs), being government-owned organizations have commitments for the economic and social wellbeing of the society; this commitment needs to be reflected in their risk-taking, decision-making and governance structures. Therefore, the primary objective of the study is to suggest measures that may lead to improvement in performance of PSUs. To achieve this objective two normative frameworks (one relating to risk levels and other relating to governance structure) are being put forth. The risk index is based on nine risks, such as, solvency risk, liquidity risk, accounting risk, etc. and each of the risks have been scored on a scale of 1 to 5. The governance index is based on eleven variables, such as, board independence, diversity, risk management committee, etc. Each of them are scored on a scale of 1 to five. The sample consists of 39 PSUs that featured in Nifty 500 index and, the study covers a 10 year period from April 1, 2005 to March, 31, 2015. Return on assets (ROA) and return on equity (ROE) have been used as proxies of firm performance. The control variables used in the model include, age of firm, growth rate of firm and size of firm. A dummy variable has also been used to factor in the effects of recession. Given the panel nature of data and possibility of endogeneity, dynamic panel data- generalized method of moments (Diff-GMM) regression has been used. It is worth noting that the corporate governance index is positively related to both ROA and ROE, indicating that with the improvement in governance structure, PSUs tend to perform better. Considering the components of CGI, it may be suggested that (i). PSUs ensure adequate representation of women on Board, (ii). appoint a Chief Risk Officer, and (iii). constitute a risk management committee. The results also indicate that there is a negative association between risk index and returns. These results not only validate the framework used to develop the risk index but also provide a yardstick to PSUs benchmark their risk-taking if they want to maximize their ROA and ROE. While constructing the CGI, certain non-compliances were observed, even in terms of mandatory requirements, such as, proportion of independent directors. Such infringements call for stringent penal provisions and better monitoring of PSUs. Further, if the Securities and Exchange Board of India (SEBI) and Ministry of Corporate Affairs (MCA) bring about such reforms in the PSUs and make mandatory the adherence to the normative frameworks put forth in the study, PSUs may have more effective and efficient decision-making, lower risks and hassle free management; all these ultimately leading to better ROA and ROE.

Keywords: PSU, risk governance, diff-GMM, firm performance, the risk index

Procedia PDF Downloads 150

Authors: Faris Algahtani

Abstract:

The COVID 19 pandemic and associated public health measures have disrupted the lives of peoplearound the world, including children. There is little knowledge about how pandemic measures have affected children in the Kingdom of Saudi Arabia (KSA). The aim and objectives of this qualitative study was to learn about the outcomes and impacts of the pandemic on children ages 0-8 in KSA. The study was based on 40 in-depth interviews that were conducted with experts in health, social protection, education, and early learning, children with special needs, and economics, including decision makers as well as specialists in service provision. The interviews were recorded and translated from Arabic to English into summary notes. The narrative was coded and analyzed following a thematic analysis.

Keywords: disabilities, COVID-19, families, children

Procedia PDF Downloads 197

Authors: Gabriel Andrade

Abstract:

Background: Ramadan is a time of intense religious salience in the Islamic world. Apart from ritual engagement, it is also a time for reflection on devotion and shared humanity. This prompts the issue if Ramadan has an effect on moral integrity and decision-making. Methods: The present study seeks to answer that question. A group of Muslim students in the United Arab Emirates (UAE) were assessed on moral integrity both during and after Ramadan. Results: Results came out showing that Ramadan has no significant effect on participants’ moral integrity. Conclusion: It is concluded that Ramadan has no effect on participants’ moral behavior, and this is potentially explained by the UAE’s increased secularization in recent decades.

Keywords: Ramadan, United Arab Emirates, moral integrity, secularization, trolley dilemmas

Procedia PDF Downloads 21

Authors: Byron Joseph A. Hallar, Annjeannette Alain D. Galang, Maria Visitacion N. Gumabay

Abstract:

One of the unique challenges provided by the twenty-first century to Philippine higher education is the utilization of Big Data. The higher education system in the Philippines is generating burgeoning amounts of data that contains relevant data that can be used to generate the information and knowledge needed for accurate data-driven decision making. This study examines the status, relevance and future of Big Data and Analytics in Philippine higher education. The insights gained from the study may be relevant to other developing nations similarly situated as the Philippines.

Keywords: big data, data analytics, higher education, republic of the philippines, assessment

Procedia PDF Downloads 331

Authors: Mehran Dizbadi, Daniyal Safarzadeh, Behrooz Arastoo, Ansgar Brunn

Abstract:

Rapid and uncontrolled expansion of cities has led to unplanned aerial development. In this way, modeling and predicting the urban growth of a city helps decision-makers. In this study, the aspect of sustainable urban development has been studied for the city of Mashhad. In general, the prediction of urban aerial development is one of the most important topics of modern town management. In this research, using the Cellular Automaton (CA) model developed for geo data of Geographic Information Systems (GIS) and presenting a simple and powerful model, a simulation of complex urban processes has been done.

Keywords: urban modeling, sustainable development, fuzzy cellular automaton, geo-information system

Procedia PDF Downloads 117

Authors: Mona Almansoori, Ahmed Mustafa, Ahmad Elshamy

Abstract:

Wireless nodes in a sensor network gather and process critical information designed to process and communicate, information flooding through such network is critical for decision making and data processing, the integrity of such data is one of the most critical factors in wireless security without compromising the processing and transmission capability of the network. This paper presents mechanism to securely transmit data over a chain of sensor nodes without compromising the throughput of the network utilizing available battery resources available at the sensor node.

Keywords: hybrid protocol, data integrity, lightweight encryption, neighbor based key sharing, sensor node data processing, Z-MAC

Procedia PDF Downloads 137

Authors: Vincent Chumbu

Abstract:

This study examines the impact of decentralization on development and government in Malawi. Decentralization has been a key element in Malawi's attempts to alter its political system since the early 1990s. This study uses both qualitative and quantitative methods to look into how well devolution promotes local development, improves service delivery, and supports effective governance. The findings suggest that while devolution has resulted in particular improvements in local government or service provision, significant challenges persist. Limited financial decentralization, inadequate local competency, and governmental meddling in local decision-making processes are some of these difficulties. The paper concludes with recommendations for strengthening Malawi's decentralization initiatives to better promote good governance and sustainable development.

Keywords: governance, development, malawi, local government

Procedia PDF Downloads 43