Search results for: multiple deprivation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4868

Search results for: multiple deprivation

2828 A Modular Solution for Large-Scale Critical Industrial Scheduling Problems with Coupling of Other Optimization Problems

Authors: Ajit Rai, Hamza Deroui, Blandine Vacher, Khwansiri Ninpan, Arthur Aumont, Francesco Vitillo, Robert Plana

Abstract:

Large-scale critical industrial scheduling problems are based on Resource-Constrained Project Scheduling Problems (RCPSP), that necessitate integration with other optimization problems (e.g., vehicle routing, supply chain, or unique industrial ones), thus requiring practical solutions (i.e., modular, computationally efficient with feasible solutions). To the best of our knowledge, the current industrial state of the art is not addressing this holistic problem. We propose an original modular solution that answers the issues exhibited by the delivery of complex projects. With three interlinked entities (project, task, resources) having their constraints, it uses a greedy heuristic with a dynamic cost function for each task with a situational assessment at each time step. It handles large-scale data and can be easily integrated with other optimization problems, already existing industrial tools and unique constraints as required by the use case. The solution has been tested and validated by domain experts on three use cases: outage management in Nuclear Power Plants (NPPs), planning of future NPP maintenance operation, and application in the defense industry on supply chain and factory relocation. In the first use case, the solution, in addition to the resources’ availability and tasks’ logical relationships, also integrates several project-specific constraints for outage management, like, handling of resource incompatibility, updating of tasks priorities, pausing tasks in a specific circumstance, and adjusting dynamic unit of resources. With more than 20,000 tasks and multiple constraints, the solution provides a feasible schedule within 10-15 minutes on a standard computer device. This time-effective simulation corresponds with the nature of the problem and requirements of several scenarios (30-40 simulations) before finalizing the schedules. The second use case is a factory relocation project where production lines must be moved to a new site while ensuring the continuity of their production. This generates the challenge of merging job shop scheduling and the RCPSP with location constraints. Our solution allows the automation of the production tasks while considering the rate expectation. The simulation algorithm manages the use and movement of resources and products to respect a given relocation scenario. The last use case establishes a future maintenance operation in an NPP. The project contains complex and hard constraints, like on Finish-Start precedence relationship (i.e., successor tasks have to start immediately after predecessors while respecting all constraints), shareable coactivity for managing workspaces, and requirements of a specific state of "cyclic" resources (they can have multiple states possible with only one at a time) to perform tasks (can require unique combinations of several cyclic resources). Our solution satisfies the requirement of minimization of the state changes of cyclic resources coupled with the makespan minimization. It offers a solution of 80 cyclic resources with 50 incompatibilities between levels in less than a minute. Conclusively, we propose a fast and feasible modular approach to various industrial scheduling problems that were validated by domain experts and compatible with existing industrial tools. This approach can be further enhanced by the use of machine learning techniques on historically repeated tasks to gain further insights for delay risk mitigation measures.

Keywords: deterministic scheduling, optimization coupling, modular scheduling, RCPSP

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2827 Analysis of Lead Time Delays in Supply Chain: A Case Study

Authors: Abdel-Aziz M. Mohamed, Nermeen Coutry

Abstract:

Lead time is an important measure of supply chain performance. It impacts both customer satisfactions as well as the total cost of inventory. This paper presents the result of a study on the analysis of the customer order lead-time for a multinational company. In the study, the lead time was divided into three stages: order entry, order fulfillment, and order delivery. A sample of size 2,425 order lines from the company records were considered for this study. The sample data includes information regarding customer orders from the time of order entry until order delivery. Data regarding the lead time of each sage for different orders were also provided. Summary statistics on lead time data reveals that about 30% of the orders were delivered after the scheduled due date. The result of the multiple linear regression analysis technique revealed that component type, logistics parameter, order size and the customer type have significant impact on lead time. Data analysis on the stages of lead time indicates that stage 2 consumes over 50% of the lead time. Pareto analysis was made to study the reasons for the customer order delay in each of the 3 stages. Recommendation was given to resolve the problem.

Keywords: lead time reduction, customer satisfaction, service quality, statistical analysis

Procedia PDF Downloads 729
2826 Adaptive Anchor Weighting for Improved Localization with Levenberg-Marquardt Optimization

Authors: Basak Can

Abstract:

This paper introduces an iterative and weighted localization method that utilizes a unique cost function formulation to significantly enhance the performance of positioning systems. The system employs locators, such as Gateways (GWs), to estimate and track the position of an End Node (EN). Performance is evaluated relative to the number of locators, with known locations determined through calibration. Performance evaluation is presented utilizing low cost single-antenna Bluetooth Low Energy (BLE) devices. The proposed approach can be applied to alternative Internet of Things (IoT) modulation schemes, as well as Ultra WideBand (UWB) or millimeter-wave (mmWave) based devices. In non-line-of-sight (NLOS) scenarios, using four or eight locators yields a 95th percentile localization performance of 2.2 meters and 1.5 meters, respectively, in a 4,305 square feet indoor area with BLE 5.1 devices. This method outperforms conventional RSSI-based techniques, achieving a 51% improvement with four locators and a 52 % improvement with eight locators. Future work involves modeling interference impact and implementing data curation across multiple channels to mitigate such effects.

Keywords: lateration, least squares, Levenberg-Marquardt algorithm, localization, path-loss, RMS error, RSSI, sensors, shadow fading, weighted localization

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2825 Operator Optimization Based on Hardware Architecture Alignment Requirements

Authors: Qingqing Gai, Junxing Shen, Yu Luo

Abstract:

Due to the hardware architecture characteristics, some operators tend to acquire better performance if the input/output tensor dimensions are aligned to a certain minimum granularity, such as convolution and deconvolution commonly used in deep learning. Furthermore, if the requirements are not met, the general strategy is to pad with 0 to satisfy the requirements, potentially leading to the under-utilization of the hardware resources. Therefore, for the convolution and deconvolution whose input and output channels do not meet the minimum granularity alignment, we propose to transfer the W-dimensional data to the C-dimension for computation (W2C) to enable the C-dimension to meet the hardware requirements. This scheme also reduces the number of computations in the W-dimension. Although this scheme substantially increases computation, the operator’s speed can improve significantly. It achieves remarkable speedups on multiple hardware accelerators, including Nvidia Tensor cores, Qualcomm digital signal processors (DSPs), and Huawei neural processing units (NPUs). All you need to do is modify the network structure and rearrange the operator weights offline without retraining. At the same time, for some operators, such as the Reducemax, we observe that transferring the Cdimensional data to the W-dimension(C2W) and replacing the Reducemax with the Maxpool can accomplish acceleration under certain circumstances.

Keywords: convolution, deconvolution, W2C, C2W, alignment, hardware accelerator

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2824 Enhancing the Effectiveness of Air Defense Systems through Simulation Analysis

Authors: F. Felipe

Abstract:

Air Defense Systems contain high-value assets that are expected to fulfill their mission for several years - in many cases, even decades - while operating in a fast-changing, technology-driven environment. Thus, it is paramount that decision-makers can assess how effective an Air Defense System is in the face of new developing threats, as well as to identify the bottlenecks that could jeopardize the security of the airspace of a country. Given the broad extent of activities and the great variety of assets necessary to achieve the strategic objectives, a systems approach was taken in order to delineate the core requirements and the physical architecture of an Air Defense System. Then, value-focused thinking helped in the definition of the measures of effectiveness. Furthermore, analytical methods were applied to create a formal structure that preliminarily assesses such measures. To validate the proposed methodology, a powerful simulation was also used to determine the measures of effectiveness, now in more complex environments that incorporate both uncertainty and multiple interactions of the entities. The results regarding the validity of this methodology suggest that the approach can support decisions aimed at enhancing the capabilities of Air Defense Systems. In conclusion, this paper sheds some light on how consolidated approaches of Systems Engineering and Operations Research can be used as valid techniques for solving problems regarding a complex and yet vital matter.

Keywords: air defense, effectiveness, system, simulation, decision-support

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2823 Analysis of Mechanisms for Design of Add-On Device to Assist in Stair Climbing of Wheelchairs

Authors: Manish Kumar Prajapat, Vishwajeet Sikchi

Abstract:

In the present scenario, many motorized stair climbing wheelchairs are available in the western countries which are significantly expensive and hence are not popular in developing countries. Also, such wheelchairs tend to be bulkier and heavy which makes their use for normal conditions difficult. Manually operated solutions are rarely explored in this space. Therefore, this project aims at developing a manually operated cost effective solution for the same. Differently abled people are not required to climb stairs frequently in their daily use. Because of this, carrying a stair climbing mechanism attached to the wheelchair permanently adds redundant weight to the wheelchair which reduces ease of use of the wheelchair. Hence, the idea of add-on device for stair climbing was envisaged wherein the wheelchair is mounted onto add-on only at the time when climbing the stairs is required. This work analyses in detail the mechanism for stair climbing of conventional wheelchair followed by analysis and iterations on multiple mechanisms to identify the most suitable mechanism for application in the add-on device. Further, this work imparts specific attention to optimize the force and time required for stair climbing of wheelchairs. The most suitable mechanism identified was validated by building and testing a prototype.

Keywords: add-on device, Rocker-Bogie, stair climbing, star wheel, y wheel

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2822 Factors Affecting the Readiness in the License Examination Testing of Nursing Students

Authors: Suwannee Sroisong, Angkhana Ruenkon, Ronnaphop Eimtab

Abstract:

The purpose of this study was twofold: First, to examine the relationship of the Readiness on the License Examination Testing (RLET) with factors namely achieved motivation, attitude on testing, self-perception, perception in testing among the nursing students at Baromarajonani College of Nursing, Buddhachinaraj, Thailand (BCNB); and secondly, to investigate the factors affecting the RLET of the nursing students. All data were collected from a set of 214 questionnaires of nursing students, second semester and in academic year 2010, at BCNB. As a set of variables in the questionnaire, it consisted of factors of readiness in testing, achieved motivation, attitude on testing, self-perception, and perception in testing. The following statistics were analyzed: frequency, percentage, means, standard deviation, and Stepwise-multiple regression correlation. Research results were as follows: 1) For the relationship among following factors, namely achieved motivation, attitude on testing, self-perception, perception in testing, there were positive correlation coefficients between .324 to .560 at the .05 level of significance; and 2) One crucial factor affecting the RLET of nursing students, namely achieved motivation, was found. The achieved motivation factor could explain the variance or predict the RLET of nursing students at 31.40 percent and at the .05 level of significance.

Keywords: readiness, nursing, license examination testing, Thailand

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2821 Optimization of Machine Learning Regression Results: An Application on Health Expenditures

Authors: Songul Cinaroglu

Abstract:

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

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

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2820 Improved Multi-Channel Separation Algorithm for Satellite-Based Automatic Identification System Signals Based on Artificial Bee Colony and Adaptive Moment Estimation

Authors: Peng Li, Luan Wang, Haifeng Fei, Renhong Xie, Yibin Rui, Shanhong Guo

Abstract:

The applications of satellite-based automatic identification system (S-AIS) pave the road for wide-range maritime traffic monitoring and management. But the coverage of satellite’s view includes multiple AIS self-organizing networks, which leads to the collision of AIS signals from different cells. The contribution of this work is to propose an improved multi-channel blind source separation algorithm based on Artificial Bee Colony (ABC) and advanced stochastic optimization to perform separation of the mixed AIS signals. The proposed approach adopts modified ABC algorithm to get an optimized initial separating matrix, which can expedite the initialization bias correction, and utilizes the Adaptive Moment Estimation (Adam) to update the separating matrix by adjusting the learning rate for each parameter dynamically. Simulation results show that the algorithm can speed up convergence and lead to better performance in separation accuracy.

Keywords: satellite-based automatic identification system, blind source separation, artificial bee colony, adaptive moment estimation

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2819 IT Perspective of Service-Oriented e-Government Enterprise

Authors: Anu Paul, Varghese Paul

Abstract:

The focal aspire of e-Government (eGovt) is to offer citizen-centered service delivery. Accordingly, the citizenry consumes services from multiple government agencies through national portal. Thus, eGovt is an enterprise with the primary business motive of transparent, efficient and effective public services to its citizenry and its logical structure is the eGovernment Enterprise Architecture (eGEA). Since eGovt is IT oriented multifaceted service-centric system, EA doesn’t do much on an automated enterprise other than the business artifacts. Service-Oriented Architecture (SOA) manifestation led some governments to pertain this in their eGovts, but it limits the source of business artifacts. The concurrent use of EA and SOA in eGovt executes interoperability and integration and leads to Service-Oriented e-Government Enterprise (SOeGE). Consequently, agile eGovt system becomes a reality. As an IT perspective eGovt comprises of centralized public service artifacts with the existing application logics belong to various departments at central, state and local level. The eGovt is renovating to SOeGE by apply the Service-Orientation (SO) principles in the entire system. This paper explores IT perspective of SOeGE in India which encompasses the public service models and illustrated with a case study the Passport service of India.

Keywords: enterprise architecture, service-oriented e-Government enterprise, service interface layer, service model

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2818 The Role of Contextual Factors in the Sustainability Reporting of Australian and New Zealand Companies

Authors: Ramona Zharfpeykan

Abstract:

The concept of sustainability is generally considered as a key topic in many countries, and sustainability reporting is becoming an important tool for companies to communicate their sustainability plans and performance to their stakeholders. There have been various studies on factors that may influence sustainability reporting in companies. This study examines the possible effect of some of the organisational factors on corporate sustainability reporting. The organisational factors included in this study are a company’s type (public or private), industry, and size as well as managers’ perception of the level of importance of indicators in reporting these indicators. A survey was conducted from 240 Australian and New Zealand companies in various industries. They were asked about their perception of the importance of sustainability indicators in their performance and if they report these indicators. The GRI indicators used to develop the survey. A multiple regression model was developed using reporting strategy score as dependent and type, size, industry categorisation, and managers’ perception of the level of importance of the GRI indicators as independent factors. The results show that among all the factors included in the model, size of a company and the perception of managers of the level of importance of environmental and labour practice indicators can affect the sustainability scores of these companies.

Keywords: sustainability reporting, global reporting initiative, sustainability reporting strategy, organisational features

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2817 Nonlinear Impact Responses for a Damped Frame Supported by Nonlinear Springs with Hysteresis Using Fast FEA

Authors: T. Yamaguchi, M. Watanabe, M. Sasajima, C. Yuan, S. Maruyama, T. B. Ibrahim, H. Tomita

Abstract:

This paper deals with nonlinear vibration analysis using finite element method for frame structures consisting of elastic and viscoelastic damping layers supported by multiple nonlinear concentrated springs with hysteresis damping. The frame is supported by four nonlinear concentrated springs near the four corners. The restoring forces of the springs have cubic non-linearity and linear component of the nonlinear springs has complex quantity to represent linear hysteresis damping. The damping layer of the frame structures has complex modulus of elasticity. Further, the discretized equations in physical coordinate are transformed into the nonlinear ordinary coupled differential equations using normal coordinate corresponding to linear natural modes. Comparing shares of strain energy of the elastic frame, the damping layer and the springs, we evaluate the influences of the damping couplings on the linear and nonlinear impact responses. We also investigate influences of damping changed by stiffness of the elastic frame on the nonlinear coupling in the damped impact responses.

Keywords: dynamic response, nonlinear impact response, finite element analysis, numerical analysis

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2816 Problem, Policy and Polity in Agenda Setting: Analyzing Safe Motherhood Program in India

Authors: Vanita Singh

Abstract:

In developing countries, there are conflicting political agendas; policy makers have to prioritize issues from a list of issues competing for the limited resources. Thus, it is imperative to understand how some issues gain attention, and others lose in the policy circles. Multiple-Streams Theory of Kingdon (1984) is among the influential theories that help to understand the public policy process and is utilitarian for health policy makers to understand how certain health issues emerge on the policy agendas. The issue of maternal mortality was long standing in India and was linked with high birth rate thus the focus of maternal health policy was on family planning since India’s independence. However, a paradigm shift was noted in the maternal health policy in the year 1992 with the launch of Safe Motherhood Programme and then in the year 2005, when the agenda of maternal health policy became universalizing institutional deliveries and phasing-out of Traditional Birth Attendants (TBAs) from the health system. There were many solutions proposed by policy communities other than universalizing of institutional deliveries, including training of TBAs and improving socio-economic conditions of pregnant women. However, Government of India favored medical community, which was advocating for the policy of universalizing institutional delivery, and neglected the solutions proposed by other policy communities. It took almost 15 years for the advocates of institutional delivery to transform their proposed solution into a program - the Janani Suraksha Yojana (JSY), a safe-motherhood program promoting institutional delivery through cash incentives to pregnant women. Thus, the case of safe motherhood policy in India is worth studying to understand how certain issues/problems gain political attention and how advocacy work in policy circles. This paper attempts to understand the factors that favored the agenda of safe-motherhood in the policy circle in India, using John Kingdon’s Multiple-Stream model of agenda-setting. Through document analysis and literature review, the paper traces the evolution of safe motherhood program and maternal health policy. The study has used open source documents available on the website of Ministry of Health and Family Welfare, media reports (Times of India Archive) and related research papers. The documents analyzed include National health policy-1983, National Health Policy-2002, written reports of Ministry of Health and Family Welfare Department, National Rural Health Mission (NRHM) document, documents related to Janani Suraksha Yojana and research articles related to maternal health programme in India. The study finds that focusing events and credible indicators coupled with media attention has the potential to recognize a problem. The political elites favor clearly defined and well-accepted solutions. The trans-national organizations affect the agenda-setting process in a country through conditional resource provision. The closely-knit policy communities and political entrepreneurship are required for advocating solutions high on agendas. The study has implications for health policy makers in identifying factors that have the potential to affect the agenda-setting process for a desired policy agenda and identify the challenges in generating political priorities.

Keywords: agenda-setting, focusing events, Kingdon’s model, safe motherhood program India

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2815 The Effect of Cognitively-Induced Self-Construal and Direct Behavioral Mimicry on Prosocial Behavior

Authors: Czar Matthew Gerard Dayday, Danielle Marie Estrera, Philippe Jefferson Galban, Gabrielle Marie Heredia

Abstract:

The study aimed to examine the effects of self-construal and direct mimicry on prosocial behavior. The study made use of a 2 (Self-construal: independent or interdependent) x 2 (Mimicry: mimicry or non-mimicry) between subjects factorial design where effects of self-construal was cognitively-induced through a story with varying pronouns (We, Us, Ourselves vs. Me, I, Myself), and prosocial behavior was measured with the amount of money donated to a fabricated advocacy. The research was conducted with a convenience sampling comprised of 88 undergraduate students (58 Females, 33 Males) aged 16 to 26 years olds from the University of the Philippines, Diliman. Results from the experiment show that both factors do not have significant main effects on prosocial behavior. Additionally, their interaction also does not have a significant effect to prosocial behavior with No Mimicry x Independent ranking highest in amount of money donated and Mimicry x Interdependent ranking lowest. These results can be attributed to multiple factors, which include the collectivist orientation and sense of kapwa of Filipinos, a role reversal in the methodology and the lack of Chameleon Effect, and a weak priming of self-construal with respect to self-relatedness.

Keywords: behavior, mimicry, prosocial, self-construal

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2814 Assessment of Energy Use and Energy Efficiency in Two Portuguese Slaughterhouses

Authors: M. Feliciano, F. Rodrigues, A. Gonçalves, J. M. R. C. A. Santos, V. Leite

Abstract:

With the objective of characterizing the profile and performance of energy use by slaughterhouses, surveys and audits were performed in two different facilities located in the northeastern region of Portugal. Energy consumption from multiple energy sources was assessed monthly, along with production and costs, for the same reference year. Gathered data was analyzed to identify and quantify the main consuming processes and to estimate energy efficiency indicators for benchmarking purposes. Main results show differences between the two slaughterhouses concerning energy sources, consumption by source and sector, and global energy efficiency. Electricity is the most used source in both slaughterhouses with a contribution of around 50%, being essentially used for meat processing and refrigeration. Natural gas, in slaughterhouse A, and pellets, in slaughterhouse B, used for heating water take the second place, with a mean contribution of about 45%. On average, a 62 kgoe/t specific energy consumption (SEC) was found, although with differences between slaughterhouses. A prominent negative correlation between SEC and carcass production was found specially in slaughterhouse A. Estimated Specific Energy Cost and Greenhouse Gases Intensity (GHGI) show mean values of about 50 €/t and 1.8 tCO2e/toe, respectively. Main results show that there is a significant margin for improving energy efficiency and therefore lowering costs in this type of non-energy intensive industries.

Keywords: meat industry, energy intensity, energy efficiency, GHG emissions

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2813 Enhancing Knowledge Graph Convolutional Networks with Structural Adaptive Receptive Fields for Improved Node Representation and Information Aggregation

Authors: Zheng Zhihao

Abstract:

Recently, Knowledge Graph Framework Network (KGCN) has developed powerful capabilities in knowledge representation and reasoning tasks. However, traditional KGCN often uses a fixed weight mechanism when aggregating information, failing to make full use of rich structural information, resulting in a certain expression ability of node representation, and easily causing over-smoothing problems. In order to solve these challenges, the paper proposes an new graph neural network model called KGCN-STAR (Knowledge Graph Convolutional Network with Structural Adaptive Receptive Fields). This model dynamically adjusts the perception of each node by introducing a structural adaptive receptive field. wild range, and a subgraph aggregator is designed to capture local structural information more effectively. Experimental results show that KGCN-STAR shows significant performance improvement on multiple knowledge graph data sets, especially showing considerable capabilities in the task of representation learning of complex structures.

Keywords: knowledge graph, graph neural networks, structural adaptive receptive fields, information aggregation

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2812 The Relationship Between Inspirational Leadership Style and Perceived Social Capital by Mediation of the Development of Organizational Knowledge Resources

Authors: Farhad Shafiepour Motlagh, Narges Salehi

Abstract:

The aim of the present study was to investigate the relationship between inspirational leadership style and perceived social capital through the mediation of organizational knowledge resource development. The research method was descriptive-correlational. The statistical population consisted of all 3537 secondary school teachers in Isfahan. Sample selection was based on Cochran's formula volume formula for 338 people and multi-stage random sampling. The research instruments included a researcher-made inspirational leadership style questionnaire, a perceived social capital questionnaire (Putnam, 1999), and a researcher-made questionnaire of perceived organizational knowledge resources. Kolmogorov statistical tests, Pearson correlation, stepwise multiple regression, and structural equation modeling were used to analyze the data. In general, the results showed that there is a significant relationship between inspirational leadership style and the use of perceived social capital at the level of P <0.05. Also, the development of organizational knowledge resources mediates the relationship between inspirational leadership style and the use of perceived social capital at the level of P <0.05.

Keywords: inspirational leadership style, perceived social capital, perceived organizational knowledge

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2811 Optimizing Resource Allocation and Indoor Location Using Bluetooth Low Energy

Authors: Néstor Álvarez-Díaz, Pino Caballero-Gil, Héctor Reboso-Morales, Francisco Martín-Fernández

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The recent tendency of "Internet of Things" (IoT) has developed in the last years, causing the emergence of innovative communication methods among multiple devices. The appearance of Bluetooth Low Energy (BLE) has allowed a push to IoT in relation to smartphones. In this moment, a set of new applications related to several topics like entertainment and advertisement has begun to be developed but not much has been done till now to take advantage of the potential that these technologies can offer on many business areas and in everyday tasks. In the present work, the application of BLE technology and smartphones is proposed on some business areas related to the optimization of resource allocation in huge facilities like airports. An indoor location system has been developed through triangulation methods with the use of BLE beacons. The described system can be used to locate all employees inside the building in such a way that any task can be automatically assigned to a group of employees. It should be noted that this system cannot only be used to link needs with employees according to distances, but it also takes into account other factors like occupation level or category. In addition, it has been endowed with a security system to manage business and personnel sensitive data. The efficiency of communications is another essential characteristic that has been taken into account in this work.

Keywords: bluetooth low energy, indoor location, resource assignment, smartphones

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2810 Evaluating Factors Impacting Functioning Management Control Systems Becoming Dysfunctional Beyond Intra-Organizational Boundaries

Authors: Martin Kartomo

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Though Management Control Systems (MCS) research has evolved beyond intra-organizational boundaries, there is limited understanding of the impact of a functioning MCS being functional beyond intra-organizational boundaries. The purpose of this research is to investigate factors that have an impact on functioning management Control Systems (MCS)becoming (dys-)functional beyond its intra-organizational boundaries. To bridge the theoretical gap, a systematic literature review is conducted to identify inter-and extra-organizational factors that are purposely suggested or unintendingly mentioned by MCS researchers to evaluate functioning MCS becoming (dys-)functional. A conceptual map is rationalized and constructed from five contingent inter-and extra-organizational MCS frameworks illuminating under-investigated MSC research areas and allowing new research avenues based on academically known factors. A multiple case study followed by a co-researcher discussion group with the purpose of identifying academically unknown factors for evaluating MCS (dys-)functionality beyond its intra-organizational boundaries. The study's result will help bridge the gap between what academics know and not know of evaluating MCS being functional beyond intra-organizational boundaries with the opportunity to develop better, more complete theories. Furthermore, it will help organizations to evaluate the impact of their activities beyond intra-organizational boundaries.

Keywords: management control systems, management control systems evaluation, management controls, control system

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2809 Computational Study of Chromatographic Behavior of a Series of S-Triazine Pesticides Based on Their in Silico Biological and Lipophilicity Descriptors

Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

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In this paper, quantitative structure-retention relationships (QSRR) analysis was applied in order to correlate in silico biological and lipophilicity molecular descriptors with retention values for the set of selected s-triazine herbicides. In silico generated biological and lipophilicity descriptors were discriminated using generalized pair correlation method (GPCM). According to this method, the significant difference between independent variables can be noticed regardless almost equal correlation with dependent variable. Using established multiple linear regression (MLR) models some biological characteristics could be predicted. Established MLR models were evaluated statistically and the most suitable models were selected and ranked using sum of ranking differences (SRD) method. In this method, as reference values, average experimentally obtained values are used. Additionally, using SRD method, similarities among investigated s-triazine herbicides can be noticed. These analysis were conducted in order to characterize selected s-triazine herbicides for future investigations regarding their biodegradability. This study is financially supported by COST action TD1305.

Keywords: descriptors, generalized pair correlation method, pesticides, sum of ranking differences

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2808 Sustainable Design of Coastal Bridge Networks in the Presence of Multiple Flood and Earthquake Risks

Authors: Riyadh Alsultani, Ali Majdi

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It is necessary to develop a design methodology that includes the possibility of seismic events occurring in a region, the vulnerability of the civil hydraulic structure, and the effects of the occurrence hazard on society, environment, and economy in order to evaluate the flood and earthquake risks of coastal bridge networks. This paper presents a design approach for the assessment of the risk and sustainability of coastal bridge networks under time-variant flood-earthquake conditions. The social, environmental, and economic indicators of the network are used to measure its sustainability. These consist of anticipated loss, downtime, energy waste, and carbon dioxide emissions. The design process takes into account the possibility of happening in a set of flood and earthquake scenarios that represent the local seismic activity. Based on the performance of each bridge as determined by fragility assessments, network linkages are measured. The network's connections and bridges' damage statuses after an earthquake scenario determine the network's sustainability and danger. The sustainability measures' temporal volatility and the danger of structural degradation are both highlighted. The method is shown using a transportation network in Baghdad, Iraq.

Keywords: sustainability, Coastal bridge networks, flood-earthquake risk, structural design

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2807 Getting Out: A Framework for Exiting/Escaping Sex Trafficking

Authors: Amanda Noble

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The process of exiting/escaping situations of sex trafficking can be arduous and fraught with numerous barriers. In this paper the results of a national Canadian study on escaping situations of sex trafficking is discussed. Surveys and focus groups were conducted with 201 stakeholders in 8 cities, including 50 survivors of sex trafficking, service providers, health care providers and police. The results show that survivors are both vulnerable to being exploited and experience barriers to exiting as a result of structural factors such as colonialism, poverty, and discrimination based on race and gender. Survivors also face numerous barriers within various systems such as child welfare and the legal system. In addition, survivors contend with multiple psychological and psychosocial factors when exiting including the trauma bond, complex trauma and mental health concerns, substance use, isolation, and adjusting to ‘mainstream’ life. In light of these factors, the service needs of survivors escaping sex trafficking are discussed, and promising practices, such as trauma-informed practice and working from a stages of change model are outlined. This paper is useful for service providers that work with survivors, policy makers, or anyone who has ever wondered why survivors that are not being physically detained don’t ‘just leave’ or escape their exploitative situations.

Keywords: Barriers, Exiting, Promising Practices, Sex Trafficking

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2806 Detecting Manipulated Media Using Deep Capsule Network

Authors: Joseph Uzuazomaro Oju

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The ease at which manipulated media can be created, and the increasing difficulty in identifying fake media makes it a great threat. Most of the applications used for the creation of these high-quality fake videos and images are built with deep learning. Hence, the use of deep learning in creating a detection mechanism cannot be overemphasized. Any successful fake media that is being detected before it reached the populace will save people from the self-doubt of either a content is genuine or fake and will ensure the credibility of videos and images. The methodology introduced in this paper approaches the manipulated media detection challenge using a combo of VGG-19 and a deep capsule network. In the case of videos, they are converted into frames, which, in turn, are resized and cropped to the face region. These preprocessed images/videos are fed to the VGG-19 network to extract the latent features. The extracted latent features are inputted into a deep capsule network enhanced with a 3D -convolution dynamic routing agreement. The 3D –convolution dynamic routing agreement algorithm helps to reduce the linkages between capsules networks. Thereby limiting the poor learning shortcoming of multiple capsule network layers. The resultant output from the deep capsule network will indicate a media to be either genuine or fake.

Keywords: deep capsule network, dynamic routing, fake media detection, manipulated media

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2805 Prevalence of Microalbuminuria and Its Relation with Various Risk Factors in Type 1 Diabetes Mellitus

Authors: Singh Baljinder, Sharma Navneet

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Microalbuminuria is the earliest detectable marker of diabetic nephropathy. We planned to evaluate the prevalence of microalbuminuria in type 1 diabetics and correlate with various risk factor. We randomly selected 100 type 1 diabetic patients after inclusion and exclusion criteria from DCRC, S. P. Medical College, Bikaner. Clinical examinations for anthropometeric parameters, hypertension, retinopathy, glycaemic status, lipid profile were done and microalbuminuria was estimated by micral test. Microalbuminuria was seen in 38% patients. The mean urinary albumin concentration was 96.61 mg/l in microalbuminuria positive cases, 134 mg/L in hypertensive patients while 74.5 mg/L in normal patients. Mean diabetic duration was 6.43 years in microalbuminurics. Albumin excretion increased significantly with age at onset of 10-18 years and declined thereafter. Microalbuminuria cases exhibited mean cholesterol 181.63 mg%, TG 130.94 mg%, LDL 109.87 mg%, HDL 57.5 mg% and VLDL 30.64 mg%. Mean urinary albumin concentration in patients with retinopathy was 160.52 mg/L while 78.66 mg/L without retinopathy. In multiple stepwise logistic regression analysis, a strong positive association was seen between microalbuminuria and hypertension (OR=5.087, CI=2.1319-12.101), fasting blood sugar (OR=3. 491, CI=1.138-10.70), duration of diabetes (OR=3.41, CI=1.360-8.55) and HbA1c (OR=2.381, CI-=1.1-5.64). The present study indicates that microalbuminuria is a common complication of type 1 diabetes mellitus and can be prevented by careful management of risk factors.

Keywords: type 1 diabetes, microalbuminuria, diabetic nephropathy, retinopathy, hypertension

Procedia PDF Downloads 445
2804 Deciphering Tumor Stroma Interactions in Retinoblastoma

Authors: Rajeswari Raguraman, Sowmya Parameswaran, Krishnakumar Subramanian, Jagat Kanwar, Rupinder Kanwar

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Background: Tumor microenvironment has been implicated in several cancers to regulate cell growth, invasion and metastasis culminating in outcome of therapy. Tumor stroma consists of multiple cell types that are in constant cross-talk with the tumor cells to favour a pro-tumorigenic environment. Not much is known about the existence of tumor microenvironment in the pediatric intraocular malignancy, Retinoblastoma (RB). In the present study, we aim to understand the multiple stromal cellular subtypes and tumor stromal interactions expressed in RB tumors. Materials and Methods: Immunohistochemistry for stromal cell markers CD31, CD68, alpha-smooth muscle (α-SMA), vimentin and glial fibrillary acidic protein (GFAP) was performed on formalin fixed paraffin embedded tissues sections of RB (n=12). The differential expression of stromal target molecules; fibroblast activation protein (FAP), tenascin-C (TNC), osteopontin (SPP1), bone marrow stromal antigen 2 (BST2), stromal derived factor 2 and 4 (SDF2 and SDF4) in primary RB tumors (n=20) and normal retina (n=5) was studied by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) and Western blotting. The differential expression was correlated with the histopathological features of RB. The interaction between RB cell lines (Weri-Rb-1, NCC-RbC-51) and Bone marrow stromal cells (BMSC) was also studied using direct co-culture and indirect co-culture methods. The functional effect of the co-culture methods on the RB cells was evaluated by invasion and proliferation assays. Global gene expression was studied by using Affymetrix 3’ IVT microarray. Pathway prediction was performed using KEGG and the key molecules were validated using qRT-PCR. Results: The immunohistochemistry revealed the presence of several stromal cell types such as endothelial cells (CD31+;Vim+/-); macrophages (CD68+;Vim+/-); Fibroblasts (Vim+; CD31-;CD68- );myofibroblasts (α-SMA+/ Vim+) and invading retinal astrocytes/ differentiated retinal glia (GFAP+; Vim+). A characteristic distribution of these stromal cell types was observed in the tumor microenvironment, with endothelial cells predominantly seen in blood vessels and macrophages near actively proliferating tumor or necrotic areas. Retinal astrocytes and glia were predominant near the optic nerve regions in invasive tumors with sparse distribution in tumor foci. Fibroblasts were widely distributed with rare evidence of myofibroblasts in the tumor. Both gene and protein expression revealed statistically significant (P<0.05) up-regulation of FAP, TNC and BST2 in primary RB tumors compared to the normal retina. Co-culture of BMSC with RB cells promoted invasion and proliferation of RB cells in direct and indirect contact methods respectively. Direct co-culture of RB cell lines with BMSC resulted in gene expression changes in ECM-receptor interaction, focal adhesion, IL-8 and TGF-β signaling pathways associated with cancer. In contrast, various metabolic pathways such a glucose, fructose and amino acid metabolism were significantly altered under the indirect co-culture condition. Conclusion: The study suggests that the close interaction between RB cells and the stroma might be involved in RB tumor invasion and progression which is likely to be mediated by ECM-receptor interactions and secretory factors. Targeting the tumor stroma would be an attractive option for redesigning treatment strategies for RB.

Keywords: gene expression profiles, retinoblastoma, stromal cells, tumor microenvironment

Procedia PDF Downloads 384
2803 Proposing an Architecture for Drug Response Prediction by Integrating Multiomics Data and Utilizing Graph Transformers

Authors: Nishank Raisinghani

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Efficiently predicting drug response remains a challenge in the realm of drug discovery. To address this issue, we propose four model architectures that combine graphical representation with varying positions of multiheaded self-attention mechanisms. By leveraging two types of multi-omics data, transcriptomics and genomics, we create a comprehensive representation of target cells and enable drug response prediction in precision medicine. A majority of our architectures utilize multiple transformer models, one with a graph attention mechanism and the other with a multiheaded self-attention mechanism, to generate latent representations of both drug and omics data, respectively. Our model architectures apply an attention mechanism to both drug and multiomics data, with the goal of procuring more comprehensive latent representations. The latent representations are then concatenated and input into a fully connected network to predict the IC-50 score, a measure of cell drug response. We experiment with all four of these architectures and extract results from all of them. Our study greatly contributes to the future of drug discovery and precision medicine by looking to optimize the time and accuracy of drug response prediction.

Keywords: drug discovery, transformers, graph neural networks, multiomics

Procedia PDF Downloads 153
2802 Relationships between Actors within Business Ecosystems That Adopt Circular Strategies: A Systematic Literature Review

Authors: Sophia Barquete, Adriana H. Trevisan, Janaina Mascarenhas

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The circular economy (CE) aims at the cycling of resources through restorative and regenerative strategies. To achieve circularity, coordination of several actors who have different responsibilities is necessary. The interaction among multiple actors allows the connection between the CE and business ecosystem research fields. Although fundamental, the relationships between actors within an ecosystem to foster circularity are not deeply explored in the literature. The objective of this study was to identify the possibilities of cooperation, competition, or even coopetition among the members of business ecosystems that adopt circular strategies. In particular, the motivations that make these actors interact to achieve a circular economy were investigated. A systematic literature review was adopted to select business ecosystem cases that adopt circular strategies. As a result, several motivations were identified for actors to engage in relationships within ecosystems, such as sharing knowledge and infrastructure, developing products with a circular design, promoting reverse logistics, among others. The results suggest that partnerships between actors are, in fact, important for the implementation of circular strategies. In order to achieve a complete and circular solution, actors must be able to clearly understand their roles and relationships within the network so that they can establish new partnerships or reframe those already established.

Keywords: business ecosystem, circular economy, cooperation, coopetition, competition

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2801 Strategies in Customer Relationship Management and Customers’ Behavior in Making Decision on Buying Car Insurance of Southeast Insurance Co. Ltd. in Bangkok

Authors: Nattapong Techarattanased, Paweena Sribunrueng

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The objective of this study is to investigate strategies in customer relationship management and customers’ behavior in making decision on buying car insurance of Southeast Insurance Co. Ltd. in Bangkok. Subjects in this study included 400 customers with the age over 20 years old to complete questionnaires. The data were analyzed by arithmetic mean and multiple regressions. The results revealed that the customers’ opinions on the strategies in customer relationship management, i.e. customer relationship, customer feedback, customer follow-up, useful service suggestions, customer communication, and service channels were in moderate level but on the customer retention was in high level. Moreover, the strategy in customer relationship management, i.e. customer relationship, and customer feedback had an influence on customers’ buying decision on buying car insurance. The two factors above can be used for the prediction at the rate of 34%. In addition, the strategy in customer relationship management, i.e. customer retention, customer feedback, and useful service suggestions had an influence on the customers’ buying decision on period of being customers. The three factors could be used for the prediction at the rate of 45%.

Keywords: strategies, customer relationship management, behavior in buying decision, car insurance

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2800 Cloud-Based Multiresolution Geodata Cube for Efficient Raster Data Visualization and Analysis

Authors: Lassi Lehto, Jaakko Kahkonen, Juha Oksanen, Tapani Sarjakoski

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The use of raster-formatted data sets in geospatial analysis is increasing rapidly. At the same time, geographic data are being introduced into disciplines outside the traditional domain of geoinformatics, like climate change, intelligent transport, and immigration studies. These developments call for better methods to deliver raster geodata in an efficient and easy-to-use manner. Data cube technologies have traditionally been used in the geospatial domain for managing Earth Observation data sets that have strict requirements for effective handling of time series. The same approach and methodologies can also be applied in managing other types of geospatial data sets. A cloud service-based geodata cube, called GeoCubes Finland, has been developed to support online delivery and analysis of most important geospatial data sets with national coverage. The main target group of the service is the academic research institutes in the country. The most significant aspects of the GeoCubes data repository include the use of multiple resolution levels, cloud-optimized file structure, and a customized, flexible content access API. Input data sets are pre-processed while being ingested into the repository to bring them into a harmonized form in aspects like georeferencing, sampling resolutions, spatial subdivision, and value encoding. All the resolution levels are created using an appropriate generalization method, selected depending on the nature of the source data set. Multiple pre-processed resolutions enable new kinds of online analysis approaches to be introduced. Analysis processes based on interactive visual exploration can be effectively carried out, as the level of resolution most close to the visual scale can always be used. In the same way, statistical analysis can be carried out on resolution levels that best reflect the scale of the phenomenon being studied. Access times remain close to constant, independent of the scale applied in the application. The cloud service-based approach, applied in the GeoCubes Finland repository, enables analysis operations to be performed on the server platform, thus making high-performance computing facilities easily accessible. The developed GeoCubes API supports this kind of approach for online analysis. The use of cloud-optimized file structures in data storage enables the fast extraction of subareas. The access API allows for the use of vector-formatted administrative areas and user-defined polygons as definitions of subareas for data retrieval. Administrative areas of the country in four levels are available readily from the GeoCubes platform. In addition to direct delivery of raster data, the service also supports the so-called virtual file format, in which only a small text file is first downloaded. The text file contains links to the raster content on the service platform. The actual raster data is downloaded on demand, from the spatial area and resolution level required in each stage of the application. By the geodata cube approach, pre-harmonized geospatial data sets are made accessible to new categories of inexperienced users in an easy-to-use manner. At the same time, the multiresolution nature of the GeoCubes repository facilitates expert users to introduce new kinds of interactive online analysis operations.

Keywords: cloud service, geodata cube, multiresolution, raster geodata

Procedia PDF Downloads 135
2799 Employability Skills: Students' Perspectives Post Work Placement Experience

Authors: Mamie Y. Griffin, Pedro Coelhoso

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Employability skills of university graduates remain an ongoing topic for discussion and debate. Numerous studies highlight the expressed concerns of governments and industries about higher education’s ability to develop workforce-ready graduates. An often cited solution is the use of internships to equip students with necessary employability skills. The literature is well documented with studies from the perspectives of multiple entities including employers and university faculty, mostly in the western world. Fewer studies examine the perception of students, and even fewer studies are based on students in Gulf countries. This paper assesses the status of employability skills from the perspective of students within a United Arab Emirates (UAE) institution based on their completion of a semester-long work placement experience. Using a largely qualitative instrument, students reported the essential skills needed in the workplace, classroom activities that most prepared students to use such skills in the workplace, and the various challenges they encountered. Implications for academic and professional practitioners are discussed. Findings and recommendations are informative for curriculum development as well as economic and workforce development agencies.

Keywords: employability skills, work placement experience, Gulf countries, workforce preparedness, work placement

Procedia PDF Downloads 349