Search results for: quality management

Authors: Chung-Yu Wu, Chia-Chi Chang, Wei-Ming Chen, Pu-Wei Wu, Shih-Fan Chen, Po-Chun Chen

Abstract:

Electrostimulation medical devices for neural diseases require electroactive and biocompatible materials to transmit signals from electrodes to targeting tissues. Protection of surrounding tissues has become a great challenge for long-term implants. In this study, we designed back-end processes with compatible, efficient, and reliable advantages over the current state-of-the-art. We explored a hermetic packaging process with high quality of adhesion and uniformity as the biocompatible devices for long-term implantation. This approach is able to provide both excellent biocompatibility and protection to the biomedical electronic devices by performing conformal coating of biocompatible materials. We successfully developed a packaging process that is capable of exposing the stimulating electrode and cover all other faces of chip with high quality of protection to prevent leakage of devices and body fluid.

Keywords: biocompatible package, medical microelectronics, surface coating, long-term implantation

Procedia PDF Downloads 507

Authors: So-Ra Lee, Myung-Min Oh

Abstract:

Generally, plants growing on the earth are under the influence of natural electric fields and may even require exposure of the electric field to survive. Electric signals have been observed within plants and seem to play an important role on various metabolic processes, but their role is not fully understood. In this study, we attempted to explore the response of plants under external electric fields in kale (Brassica oleracea var. acephala). The plants were hydroponically grown for 28 days in a plant factory. Electric currents at 10, 50 and 100 mA were supplied to nutrient solution for 3 weeks. Additionally, some of the plants were cultivated in a Faraday cage to remove the natural electric field. Kale plants exposed to electric fields had higher fresh weight than the control and plants in Faraday cage. Absence of electric field caused a significant decrease in shoot dry weight and root growth. Leaf area also showed a similar response with shoot fresh weight. Supplying weak electric stimulation enhanced nutritional quality including total phenolic content and antioxidant capacity. This work provides basic information on the effects of electric fields on plants and is a meaningful attempt for developing a new economical technology to increase crop productivity and quality by applying an electric field. This work was supported by Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries (IPET) through Agriculture, Food and Rural Affairs Research Center Support Program, funded by Ministry of Agriculture, Food and Rural Affairs (MAFRA) (717001-07-02-HD240).

Keywords: electroculture, electric signal, faraday cage, electric field

Procedia PDF Downloads 278

Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 103

Authors: Halil Bas, Unal Demiray, Sukru Dursun

Abstract:

Water and ground water pollution at the most of the countries is important problem. Investigation of water pollution source must be carried out to save fresh water. Because fresh water sources are very limited and recent sources are not enough for increasing population of world. In this study, investigation was carried out on pollution factors effecting the quality of the groundwater in Çorum Stream Basin in Turkey. Effect of geological structure of the region and the interaction between the stream and groundwater was researched. For the investigation, stream and groundwater sampling were performed at rainy and dry seasons to see if there is a change on quality parameters. The results were evaluated by the computer programs and then graphics, distribution maps were prepared. Thus, degree of the quality and pollution were tried to understand. According to analysis results, because the results of streams and the ground waters are not so close to each other we can say that there is no interaction between the stream and the groundwater. As the irrigation water, the stream waters are generally in the range between C3S1 region and the ground waters are generally in the range between C3S1 and C4S2 regions according to US Salinity Laboratory Diagram. According to Wilcox diagram stream waters are generally good-permissible and ground waters are generally good permissible, doubtful to unsuitable and unsuitable type. Especially ground waters are doubtful to unsuitable and unsuitable types in dry season. It may be assumed that as the result of relative increase in concentration of salt minerals. Especially samples from groundwater wells bored close to gypsium bearing units have high hardness, electrical conductivity and salinity values. Thus for drinking and irrigation these waters are determined as unsuitable. As a result of these studies, it is understood that the groundwater especially was effected by the lithological contamination rather than the anthropogenic or the other types of pollution. Because the alluvium is covered by the silt and clay lithology it is not affected by the anthropogenic and the other foreign factors. The results of solid waste disposal site leachate indicate that this site would have a risk potential for pollution in the future. Although the parameters did not exceed the maximum dangerous values it does not mean that they will not be dangerous in the future, and this case must be taken into account.

Keywords: Çorum, environment, groundwater, hydrogeology, geology, pollution, quality, stream

Procedia PDF Downloads 483

Authors: Masoumeh Khailghi Sikaroudi, Mohsen Masoodi, Fazad Shidfar, Meghdad Sedaghat

Abstract:

Background: The hypertonicity of internal anal sphincter resting pressure is one of the main reasons for chronic anal fissures. The aim of this study is to assess the effect of oral administration of L-arginine on anal fissure symptom improvement by relaxation of the internal anal sphincter. Method: Seventy-six chronic anal fissure patients (age: 18-65 years) took part in this randomized, double-blind, placebo-controlled trial study from February 2019 to October 2020 at Rasoul-e-Akram Hospital, Tehran, Iran. Participants were allocated into treatment (L-arginine) or placebo groups. They took a 1000 mg capsule three times a day for one month and were followed up at the end of the first and third months after receiving the intervention. Clinical symptoms, anal sphincter resting pressure, and quality of life (QoL) were completed at baseline and the end of the study. Result: The analysis of data was shown significant improvement in bleeding, fissure size, and pain within each group; however, this effect was more seen in the arginine group compared to the control group at the end of the study (P-values<0.001). Following that, a significant increase in QoL was seen just in patients who were treated with arginine (P-value=0.006). Also, the comparison of anal pressures to baseline and between groups at the end of the study showed a significant reduction in sphincter pressure in treated patients (P-value<0.001, =0.049; respectively). Conclusion: Oral administration of 3000 mg L-arginine can heal chronic anal fissures by reducing anal internal sphincter pressure with fewer side effects. However, a long-term study with more follow-up is recommended.

Keywords: L-arginine, anal fissure, sphincter pressure, clinical symptoms, quality of life

Procedia PDF Downloads 60

Authors: Christos Stamopoulos

Abstract:

Nowadays, the technological evolution has brought changes and new requirements not only on human’s life but also on the environment in which they live. Cities have begun to be organized in new ways which comply with contemporary living standards. The aim of this paper was to present the characteristics and to introduce good construction strategies of smart cities around the world. Also, a case study of the city of Kalampaka and its residents was surveyed. More specifically, residents’ knowledge about smart cities and their opinion for future progress was examined. Statistical analysis showed that residents’ knowledge about smart cities was fairly good (48% knew the phrase 'smart city'). However, respondents believe that the appearance of the city of Kalampaka needs improvement in many areas (the 75% are disappointed with the current appearance of the city). Furthermore, regression analysis showed that the value of the environmental sustainability is greatly influenced by the energy saving, as well as, innovation has an impact on the level of quality of life, while older people seem satisfied with administration’s efforts for development.

Keywords: development, economy, environment, governance, quality of life, smart city

Procedia PDF Downloads 324

Authors: Hamed Saremi, Suzan Taghavy, Shahla Saremi

Abstract:

In today's competitive world, organizations are expected to surpass the competitors and benefit from the resources and benefits. Therefore, organizations need to improve the current performance is felt more than ever that this requires to identify organizational optimal strategies, and consider all strategies simultaneously. In this study, to enhance competitive advantage and according to customer requirements, alignment between business, production and marketing strategies, House of Quality (QFD) approach has been used and zero-one linear programming model has been studied. First, the alignment between production and marketing strategies with business strategy, independent weights of these strategies is calculated. Then with using QFD approach the aligned weights of optimal strategies in each production and marketing field will be obtained and finally the aligned marketing strategies selection with the purpose of allocating budget and specialist human resource to marketing functions will be done that lead to increasing competitive advantage and benefit.

Keywords: strategy alignment, house of quality deployment, production strategy, marketing strategy, business strategy

Procedia PDF Downloads 419

Authors: Marine Kobalava

Abstract:

Introduction. The paper substantiates the crucial role of anti-crisis PR in managing the image and reputation of companies. The critical situation caused by the Covid-19 virus in various countries of the world and the actions taken have had a significant negative impact on the image of companies and public groups. The mentioned circumstance has caused some problems for companies’ products in terms of customer demand. Accordingly, the main goal of PR has become to achieve the optimal relationship between companies and society with effective management. It should also be taken into account that the range of action of PR in crisis situations is much wider than that of advertising. In the paper, Public Relations is evaluated as a determining factor of the companies' prestige, its reliability, which has a decisive effect on the goodwill, trust, and general reputation of the public towards the company. The purpose of the study is to reveal the challenges of anti-crisis PR in Georgian companies and to develop recommendations on effective management mechanisms. Methodologies. Analysis, induction, synthesis, and other methods are used in the paper; Matrix and SWOT analysis are constructed. Ways of establishing and implementing an anti-crisis PR system in companies are proposed. The main aspects of anti-crisis management are identified by using the matrix of the choice of diversification strategy of the companies' activities, the possibilities of making adequate decisions using PR are studied according to the characteristics of the companies' activities and priority directions. Conclusion. The paper draws conclusions on modern problems of anti-crisis PR, offers recommendations on ways to solve it through PR strategies.

Keywords: anti-crisis PR, effective management, company, PR strategy

Procedia PDF Downloads 65

Authors: Majid Ali, Xinfang Jin, Victor Eniola, Henning Hoene

Abstract:

The performance of proton exchange membrane (PEM) fuel cells is sensitive to several factors, including power fluctuations, hydrogen utilization, and the quality orientation of the fuel cell stack. In this study, we investigate the impact of these factors on the performance of a PEM fuel cell. We start by analyzing the power fluctuations that are typical in renewable energy systems and their effects on the 50 Watt fuel cell's performance. Next, we examine the hydrogen utilization rate (0-1000 mL/min) and its impact on the cell's efficiency and durability. Finally, we investigate the quality orientation (three different positions) of the fuel cell stack, which can significantly affect the cell's lifetime and overall performance. The basis of our analysis is the utilization of experimental results, which have been further validated by comparing them with simulations and manufacturer results. Our results indicate that power fluctuations can cause significant variations in the fuel cell's voltage and current, leading to a reduction in its performance. Moreover, we show that increasing the hydrogen utilization rate beyond a certain threshold can lead to a decrease in the fuel cell's efficiency. Finally, our analysis demonstrates that the orientation of the fuel cell stack can affect its performance and lifetime due to non-uniform distribution of reactants and products. In summary, our study highlights the importance of considering power fluctuations, hydrogen utilization, and quality orientation in designing and optimizing PEM fuel cell systems. The findings of this study can be useful for researchers and engineers working on the development of fuel cell systems for various applications, including transportation, stationary power generation, and portable devices.

Keywords: fuel cell, proton exchange membrane, renewable energy, power fluctuation, experimental

Procedia PDF Downloads 113

Authors: Qi Xiu, Hiromu Hota, Yohsuke Ishii, Takuya Oda

Abstract:

Recently, collectable manufacturing data are rapidly increasing. On the other hand, mega recall is getting serious as a social problem. Under such circumstances, there are increasing needs for preventing mega recalls by defect analysis such as root cause analysis and abnormal detection utilizing manufacturing data. However, the time to classify strings in manufacturing data by traditional method is too long to meet requirement of quick defect analysis. Therefore, we present String Length Distribution Classification method (SLDC) to correctly classify strings in a short time. This method learns character features, especially string length distribution from Product ID, Machine ID in BOM and asset list. By applying the proposal to strings in actual manufacturing data, we verified that the classification time of strings can be reduced by 80%. As a result, it can be estimated that the requirement of quick defect analysis can be fulfilled.

Keywords: string classification, data quality, feature selection, probability distribution, string length

Procedia PDF Downloads 306

Authors: Brenda Margaret Behan

Abstract:

Kenya is a water-stressed country with highly varied socio-ecological environments in its devolved county system, and is currently implementing a polycentric water governance system; this paper examines the importance of social capital in community-based natural resource management and its role in supporting good water governance systems in the Kenya context. Through a robust literature review of theory and case studies, specific aspects of social capital are examined to determine their importance in the implementation of local community-based water management arrangements which support and complement the more formal institutions outlined in the 2002 and 2016 Water Acts of Kenya. Water is an increasingly important and scarce resource not only for Kenya, but for many communities across the globe, and lessons learned in the Kenya context can be useful for other countries and communities faced with similar challenges. Changing climates, increasing populations, and increased per capita consumption of water is contributing to a situation in which the management of water resources will be vital to community resilience. Community-based natural resource management is widely recognized as a building block and component of wider water resource management systems, and when properly conducted can provide a way to enable sustainable use of resources and empower communities. Greater attention to the social and cultural norms and traditional institutions associated with a community’s social capital can lead to better results for Kenya’s polycentric governance of water. The key findings and recommendations from this research show that in Kenya, traditional institutions need to be understood and integrated into governance systems; social values and cultural norms have a significant impact on the implementation of community-based water management efforts; and social capital is a dynamic concept which influences and is influenced by policies and practices. The community-based water management approach will continue to be a key cornerstone for Kenya’s polycentric water governance structure, especially in the more remote arid and semi-arid lands; thus, the successful integration of social capital aspects into planning and implementation will contribute to a strengthened, sustainable, and more equitable national water governance system. Specific observations and recommendations from this study will help practitioners and policymakers to better craft community-based interventions.

Keywords: community-based natural resource management, social capital, traditional institutions, water governance

Procedia PDF Downloads 153

Authors: Rasouli Divkalaee Zeinab, Kalteh Safa, Roudbari Aliakbar

Abstract:

Introduction: Medical waste can lead to the generation and transmission of many infectious and contagious diseases due to the presence of pathogenic agents, thereby necessitating the need for special management to collect, decontaminate, and finally dispose of such products. This study aimed to design a centralized health care (medical) waste management program for the cities of Semnan, Mahdishahr, and Shahmirzad. Methods: This descriptive-analytical study was conducted for six months in the cities of Semnan, Mahdishahr, and Shahmirzad. In this study, the quantitative and qualitative characteristics of the generated wastes were determined by taking samples from all medical waste production centers. Then, the equipment, devices, and machines required for separate collection of the waste from the production centers and for their subsequent decontamination were estimated. Next, the investment costs, current costs, and working capital required for collection, decontamination, and final disposal of the wastes were determined. Finally, the payment for proper waste management of each category of medical waste-producing centers was determined. Results: 1021 kilograms of medical waste are produced daily in the cities of Semnan, Mahdishahr, and Shahmirzad. It was estimated that a 1000-liter autoclave, a machine for collecting medical waste, four 60-liter bins, four 120-liter bins, and four 1200-liter bins were required for implementing the study plan. Also, the estimated total annual medical waste management costs for Semnan City were determined (23,283,903,720 Iranian Rials). Conclusion: The study results showed that establishing a proper management system for medical wastes generated in the three studied cities will cost between 334,280 and 1,253,715 Iranian Rials in fees for the medical centers. The findings of this study provided comprehensive data regarding medical wastes from the generation point to the landfill site, which is vital for the government and the private sector.

Keywords: clinics, decontamination, management, medical waste

Procedia PDF Downloads 67

Authors: Cinthia G. P. Calou, Franz J. Antezana, Ana I. O. Nicolau, Eveliny S. Martins, Paula R. A. L. Soares, Glauberto S. Quirino, Dayanne R. Oliveira, Priscila S. Aquino, Régia C. M. B. Castro, Ana K. B. Pinheiro

Abstract:

Introduction: As an integral part of the health-disease process, gestation is a period in which the social insertion of women can influence, in a positive or negative way, the course of the pregnancy-puerperal cycle. Thus, evaluating the quality of life of this population can redirect the implementation of innovative practices in the quest to make them more effective and real for the promotion of a more humanized care. This study explores the associations between the obstetric factors with affected areas of health-related quality of life of pregnant women with habitual risk. Methods: This is a cross-sectional, quantitative study conducted in three public facilities and a private service that provides prenatal care in the city of Fortaleza, Ceara, Brazil. The sample consisted of 261 pregnant women who underwent low-risk prenatal care and were interviewed from September to November 2014. The collection instruments were a questionnaire containing socio-demographic and obstetric variables, in addition to the Brazilian version of the Mother scale Generated Index (MGI) characterized by being a specific and objective instrument, consisting of a single sheet and subdivided into three stages. It allows identifying the areas of life of the pregnant woman that are most affected, which could go unnoticed by the pre-formulated measurement instruments. The obstetric data, as well as the data concerning the application of the MGI scale, were compiled and analyzed through the statistical program Statistical Package for the Social Sciences (SPSS), version 20.0. After the compilation, a descriptive analysis was carried out. Then, associations were made between some variables. The tests applied were the Pearson Chi-Square and the Fisher's exact test. The odds ratio was also calculated. These associations were considered statistically significant when the p (probability) value was less than or equal to a level of 5% (α = 0.05) in the tests performed. Results: The variables that negatively reflected the quality of life of the pregnant women and presented a significant association with the polaciuria were: gestational age (p = 0.022) and parity (p = 0.048). Episodes of nausea and vomiting also showed significant with gestational age correlation (p = 0.0001). Evaluating the crossing of stress, we observed a significant association with parity (p = 0.0001). In turn, emotional lability revealed dependence on the variable type of delivery (p = 0.009). Conclusion: The health professionals involved in the assistance to the pregnant woman can understand how the process of gestation is experienced, considering all its peculiar transformations; to meet their individual needs, stimulating their autonomy and their power of choice, envisaging the achievement of a better quality of life related to health in the perspective of health promotion.

Keywords: health-related quality of life, obstetric nursing, pregnant women, prenatal care

Procedia PDF Downloads 277

Authors: T. Elrazaz

Abstract:

This paper examines accrual and real earnings management by publicly listed targets around mergers and acquisitions. Prior literature shows that earnings management around mergers and acquisitions can have a significant economic impact because of the associated wealth transfers among stakeholders. More importantly, acting on behalf of their shareholders or pursuing their self-interests, managers of both targets and acquirers may be equally motivated to manipulate earnings prior to an acquisition to generate higher gains for their shareholders or themselves. Building on the grounds of information asymmetry, agency conflicts, stewardship theory, and the revelation principle, this study addresses the question of whether takeover targets employ accrual and real earnings management in the periods prior to the announcement of Mergers and Acquisitions (M&A). Additionally, this study examines whether acquirers are able to detect targets’ earnings management, and in response, adjust the acquisition premium paid in order not to face the risk of overpayment. This study uses an aggregate accruals approach in estimating accrual earnings management as proxied by estimated abnormal accruals. Additionally, real earnings management is proxied for by employing widely used models in accounting and finance literature. The results of this study indicate that takeover targets manipulate their earnings using accruals in the second year with an earnings release prior to the announcement of the M&A. Moreover, in partitioning the sample of targets according to the method of payment used in the deal, the results are restricted only to targets of stock-financed deals. These results are consistent with the argument that targets of cash-only or mixed-payment deals do not have the same strong motivations to manage their earnings as their stock-financed deals counterparts do additionally supporting the findings of prior studies that the method of payment in takeovers is value relevant. The findings of this study also indicate that takeover targets manipulate earnings upwards through cutting discretionary expenses the year prior to the acquisition while they do not do so by manipulating sales or production costs. Moreover, in partitioning the sample of targets according to the method of payment used in the deal, the results are restricted only to targets of stock-financed deals, providing further robustness to the results derived under the accrual-based models. Finally, this study finds evidence suggesting that acquirers are fully aware of the accrual-based techniques employed by takeover targets and can unveil such manipulation practices. These results are robust to alternative accrual and real earnings management proxies, as well as controlling for the method of payment in the deal.

Keywords: accrual earnings management, acquisition premium, real earnings management, takeover targets

Procedia PDF Downloads 99

Authors: Adegoriola Mayowa I., Lai Joseph H. K., Yung Esther H. K., Chan Edwin H. K.

Abstract:

Heritage buildings (HBs) as structures with historical and architectural relevance that form an integral part of contemporary society. These buildings deserve to be protected for as long as possible to retain their significance. Therefore, the need to prioritize HB maintenance management is pertinent. However, the decision-making process of HBMM can be relatively daunting. The decision-making challenge may be attributed to the multiple 'stakeholders' expectation and requirement which needs to be met. To this end, professionals in the built environment have identified the need to apply the strategic concept of facilities management (FM) in decision making. Furthermore, the different maintenance dimensions have been applied to maintenance management of residential, commercial, and health facilities. Unfortunately, these different maintenance approaches, such as FM, sustainable FM, urban FM, green FM, and strategic FM, are yet to be fully explored in the decision-making process of HBMM. To bridge this gap, this study focuses on developing a framework for strategic decision-making HBMM, which helps achieve HBMM sustainability. At the study's inception, relevant works of literature in the domains of HBMM and FM were conducted. This review helped in the identification of contemporary maintenance practices and their applicability to HBMM. Afterward, a conceptual framework to aid decision-making in HBMM was developed. This framework integrated the concept of FM scope (people, place, process, and technology) while ensuring that decisions plans were made at strategic, tactical, and operational levels. Also, the different characteristics of HBs and stakeholders' requirements were considered in the framework. The conceptual framework presents a holistic guide for professionals in HBMM to ensure that decision processes and outcomes are practical and efficient. It also contributes to the existing body of knowledge on the integration of FM in HBMM. Furthermore, it will serve as a basis for future studies by applying the conceptualized framework in actual cases.

Keywords: decision-making, facility management, strategy, sustainability, heritage building, maintenance

Procedia PDF Downloads 116

Authors: Hela Gargouri, Nizar Moalla, Hassen Hadj Kacem

Abstract:

Meat adulteration affecting the safety and quality of food is becoming one of the main concerns of public interest across the world. The drastic consequences on the meat industry highlighted the urgent necessity to control the products' quality and to point out the complexity of both supply and processing circuits. Due to the expansion of this problem, the authentic testing of foods, particularly meat and its products, is deemed crucial to avoid unfair market competition and to protect consumers from fraudulent practices of meat adulteration. The adoption of authentication methods by the food quality-control laboratories is becoming a priority issue. However, in some developing countries, the number of food tests is still insignificant, although a variety of processed and traditional meat products are widely consumed. Little attention has been paid to provide an easy, fast, reproducible, and low-cost molecular test, which could be conducted in a basic laboratory. In the current study, the 359 bp fragment of the cytochrome-b gene was mapped by PCR-RFLP using firstly fresh biological supports (DNA and meat) and then turkey salami as an example of commercial processed meat. This technique has been established through several optimizations, namely: the selection of restriction enzymes. The digestion with BsmAI, SspI, and TaaI succeed to identify the seven included animal species when meat is formed by individual species and when the meat is a mixture of different origin. In this study, the PCR-RFLP technique using universal primer succeed to meet our needs by providing an indirect sequencing method identifying by restriction enzymes the specificities characterizing different species on the same amplicon reducing the number of potential tests.

Keywords: adulteration, animal species, authentication, meat, mtDNA, PCR-RFLP

Procedia PDF Downloads 98

Authors: Nazli Akhlaghinia, Ali Rajabzadeh Ghatari

Abstract:

In today's world, with increasing environmental awareness, firms are facing severe pressure from various stakeholders, including the government and customers, to reduce their harmful effects on the environment. Over the past few decades, the increasing effects of global warming, climate change, waste, and air pollution have increased the global attention of experts to the issue of the green supply chain and led them to the optimal solution for greenery. Green supply chain management (GSCM) plays an important role in motivating the sustainability of the organization. With increasing environmental concerns, the main objective of the research is to use system thinking methodology and Vensim software for designing a dynamic system model for green supply chain and observing behaviors. Using this methodology, we look for the effects of a green supply chain structure on the behavioral dynamics of output variables. We try to simulate the complexity of GSCM in a period of 30 months and observe the complexity of behaviors of variables including sustainability, providing green products, and reducing energy consumption, and consequently reducing sample pollution.

Keywords: supply chain management, green supply chain management, system dynamics, energy consumption

Procedia PDF Downloads 126

Authors: Najeebah Almahmeed

Abstract:

Risk Management is an evolving subject among organizations that include corporations, governments, non-governmental organizations, and not-for-profit corporations. In order to enhance awareness around the importance of Risk Management and make sure everyone is using it in their day-to-day job, the Risk Culture topic has emerged and gained importance not only in the Finance Sector but also in the National Oil Companies in Kuwait. Risk Culture can be defined as the shared beliefs, attitudes, and behaviors within a company that guide its approach to managing risks. It acts as a connecting force that links policies, procedures, and individuals, influencing how risks are understood and tackled through activities. In this research, benefits of Risk Culture are shared, guidelines are presented to promote a risk aware culture, and fully embed and enforce Risk-based processes and procedures. Moreover, this research demonstrates methodologies of measuring the Risk Culture using specific dimensions and clusters.

Keywords: clusters, dimensions, national oil companies, risk culture, risk management

Procedia PDF Downloads 64

Authors: Nuraeni, Suryanti, Saida, Annas Boceng

Abstract:

Farm forestry is a forest where farmers or landowners do cultivation and farming activities on their land. This study aims to determine the dimensions of sustainable development of farm forestry and to analyze the leverage factors to improve the sustainability status of farm forestry management in Bulukumba Regency. This research was conducted in Kajang District, Bulukumba Regency. The analysis of the sustainability of farm forestry management applied Multi-Dimensional Scaling (MDS), a modification of the Rapid Appraisal of The Status of Farming (RAPFARM). The index value of farm forestry sustainability was by 62.01% for ecological dimension, 51.54% for economic dimension, 61.00% for the social and cultural dimension, and 63.24% for legal and institutional dimension with sustainable enough category status. Meanwhile, the index value for the technology and infrastructure was by 47.16% of less sustainable category status. The result of leverage analysis of attributes for the dimensions of ecological, economic, social and cultural, legal and institutional as well as infrastructure and technology afforded twenty-two (22) leverage sensitive factors that influence the sustainability of farm forestry.

Keywords: farm forestry, South Sulawesi, management, sustainability

Procedia PDF Downloads 356

Authors: Denise Levy

Abstract:

Nuclear technology is part of our everyday life and its beneficial applications help to improve the quality of our lives. Nevertheless, in Brazil, most often the media and social networks tend to associate radiation to nuclear weapons and major accidents, and there is still great misunderstanding about the peaceful applications of nuclear science. The Educational Portal Radioatividades (Radioactivities) is a corporate social responsibility initiative that takes advantage of the growing impact of Internet to offer high quality scientific information for teachers and students throughout Brazil. This web-based initiative focusses on the positive applications of nuclear technology, presenting the several contributions of ionizing radiation in different contexts, such as nuclear medicine, agriculture techniques, food safety and electric power generation, proving nuclear technology as part of modern life and a must to improve the quality of our lifestyle. This educational project aims to contribute for democratization of scientific education and social inclusion, approaching society to scientific knowledge, promoting critical thinking and inspiring further reflections. The website offers a wide variety of ludic activities such as curiosities, interactive exercises and short courses. Moreover, teachers are offered free web-based material with full instructions to be developed in class. Since year 2013, the project has been developed and improved according to a comprehensive study about the realistic scenario of ICTs infrastructure in Brazilian schools and in full compliance with the best e-learning national and international recommendations.

Keywords: information and communication technologies, nuclear technology, science communication, society and education

Procedia PDF Downloads 306

Authors: Mustafa M. Bob, Norhan Rahman, Abdalla Elamin, Saud Taher

Abstract:

The objective of this study was to assess the suitability of Madinah city groundwater for irrigation purposes. Of the twenty three wells that were drilled in different locations in the city for the purposes of this study, twenty wells were sampled for water quality analyses. The United States Department of Agriculture (USDA) classification of irrigation water that is based on Sodium hazard (SAR) and salinity hazard was used for suitability assessment. In addition, the residual sodium carbonate (RSC) was calculated for all samples and also used for irrigation suitability assessment. Results showed that all groundwater samples are in the acceptable quality range for irrigation based on RSC values. When SAR and salinity hazard were assessed, results showed that while all groundwater samples (except one) fell in the acceptable range of SAR, they were either in the high or very high salinity zone which indicates that care should be taken regarding the type of soil and crops in the study area.

Keywords: irrigation suitability, TDS, salinity, SAR

Procedia PDF Downloads 360

Authors: Ruchi B. Semwal, Deepak K. Semwal, Thobile A. N. Nkosi, Alvaro M. Viljoen

Abstract:

The use of Lawsonia inermis L. (Lythraeae), commonly known as henna, has many medicinal benefits and is used as a remedy for the treatment of diarrhoea, cancer, inflammation, headache, jaundice and skin diseases in folk medicine. Although widely used for hair dyeing and temporary tattooing, henna body art has popularized over the last 15 years and changed from being a traditional bridal and festival adornment to an exotic fashion accessory. The naphthoquinone, lawsone, is one of the main constituents of the plant and responsible for its dyeing property. Henna leaves typically contain 1.8–1.9% lawsone, which is used as a marker compound for the quality control of henna products. Adulteration of henna with various toxic chemicals such as p-phenylenediamine, p-methylaminophenol, p-aminobenzene and p-toluenodiamine to produce a variety of colours, is very common and has resulted in serious health problems, including allergic reactions. This study aims to assess the quality of henna products collected from different parts of the world by determining the lawsone content, as well as the concentrations of any adulterants present. Ultra high performance liquid chromatography-mass spectrometry (UPLC-MS) was used to determine the lawsone concentrations in 172 henna products. Separation of the chemical constituents was achieved on an Acquity UPLC BEH C18 column using gradient elution (0.1% formic acid and acetonitrile). The results from UPLC-MS revealed that of 172 henna products, 11 contained 1.0-1.8% lawsone, 110 contained 0.1-0.9% lawsone, whereas 51 samples did not contain detectable levels of lawsone. High performance thin layer chromatography was investigated as a cheaper, more rapid technique for the quality control of henna in relation to the lawsone content. The samples were applied using an automatic TLC Sampler 4 (CAMAG) to pre-coated silica plates, which were subsequently developed with acetic acid, acetone and toluene (0.5: 1.0: 8.5 v/v). A Reprostar 3 digital system allowed the images to be captured. The results obtained corresponded to those from UPLC-MS analysis. Vibrational spectroscopy analysis (MIR or NIR) of the powdered henna, followed by chemometric modelling of the data, indicates that this technique shows promise as an alternative quality control method. Principal component analysis (PCA) was used to investigate the data by observing clustering and identifying outliers. Partial least squares (PLS) multivariate calibration models were constructed for the quantification of lawsone. In conclusion, only a few of the samples analysed contain lawsone in high concentrations, indicating that they are of poor quality. Currently, the presence of adulterants that may have been added to enhance the dyeing properties of the products, is being investigated.

Keywords: Lawsonia inermis, paraphenylenediamine, temporary tattooing, lawsone

Procedia PDF Downloads 444

Authors: Mokgata Matjie, Sibo Mayime

Abstract:

The 4IR brought with it an inevitable need for change in all organisations, regardless of sector. As a member of the global community, South African organisations are bound to experience the 4IR pressure, and the need to digitize becomes unavoidable. The South African government sector has various departments, of which one of them is the land administration solely responsible for the registration, management, and maintenance of the property registry of South Africa. For the past many years, the registration of deeds was done manually, ranging from 7-10 days, with lots and loads of paperwork handled manually by conveyancers and Registry Clerks. Some information might get lost during the registration period, thus delaying the whole process. This conceptual paper proposes ways to digitalize the land administration office by consulting all relevant literature and ultimately developing a theoretical change management framework for all public sector organisations in South Africa. Change is inevitable, but careful consideration is necessary in terms of consulting all relevant stakeholders for their buy-in and successful implementation of digitalization. The developed framework will serve as a theoretical basis for the empirical research envisaged as a PhD study.

Keywords: stakeholders, engagement, change management, land administration, digitalisation, South African public sector

Procedia PDF Downloads 90

Authors: Monika Chuchro

Abstract:

This paper presents a preliminary attempt to apply classification of time series using meta-clusters in order to improve the quality of regression models. In this case, clustering was performed as a method to obtain a subgroups of time series data with normal distribution from inflow into waste water treatment plant data which Composed of several groups differing by mean value. Two simple algorithms: K-mean and EM were chosen as a clustering method. The rand index was used to measure the similarity. After simple meta-clustering, regression model was performed for each subgroups. The final model was a sum of subgroups models. The quality of obtained model was compared with the regression model made using the same explanatory variables but with no clustering of data. Results were compared by determination coefficient (R2), measure of prediction accuracy mean absolute percentage error (MAPE) and comparison on linear chart. Preliminary results allows to foresee the potential of the presented technique.

Keywords: clustering, data analysis, data mining, predictive models

Procedia PDF Downloads 453

Authors: Sima Aznavi, Poria Fajri, Hanif Livani

Abstract:

Smart homes are small energy systems which may be equipped with renewable energy sources, storage devices, and loads. Energy management strategy plays a main role in the efficient operation of smart homes. Effective energy scheduling of the renewable energy sources and storage devices guarantees efficient energy management in households while reducing the energy imports from the grid. Nevertheless, despite such strategies, independently day ahead energy schedules for multiple households can cause undesired effects such as high power exchange with the grid at certain times of the day. Therefore, the interactions between multiple smart home day ahead energy projections is a challenging issue in a smart grid system and if not managed appropriately, the imported energy from the power network can impose additional burden on the distribution grid. In this paper, a central energy management strategy for a network consisting of multiple households each equipped with renewable energy sources, storage devices, and Plug-in Electric Vehicles (PEV) is proposed. The decision-making strategy alongside the smart home energy management system, minimizes the energy purchase cost of the end users, while at the same time reducing the stress on the utility grid. In this approach, the smart home energy management system determines different operating scenarios based on the forecasted household daily load and the components connected to the household with the objective of minimizing the end user overall cost. Then, selected projections for each household that are within the same cost range are sent to the central decision-making system. The central controller then organizes the schedules to reduce the overall peak to average ratio of the total imported energy from the grid. To validate this approach simulations are carried out for a network of five smart homes with different load requirements and the results confirm that by applying the proposed central energy management strategy, the overall power demand from the grid can be significantly flattened. This is an effective approach to alleviate the stress on the network by distributing its energy to a network of multiple households over a 24- hour period.

Keywords: energy management, renewable energy sources, smart grid, smart home

Procedia PDF Downloads 228

Authors: Lalith Edirisinghe, Zhihong Jin, A.W. Wijeratne, Hansa Edirisinghe, Lakshmi Ranwala Rashika Mudunkotuwa

Abstract:

A paradigm shift in container inventory management (CIM) is a long-awaited industry need. Virtual container yard (VCY) is a concept developed in 2013 and its primary objective is to minimize shipping transport cost through implementing container exchange between carriers. Shipping lines always try to maintain lower container idle time and provide higher customer satisfaction. However, it is disappointing to note that carriers turn a blind eye to the escalating cost resulted from the present inefficient CIM mechanism. The cost of empty container management is simply transferred to the importers and exporters as freight adjustments. It also creates an environmental hazard. Therefore, it has now become a problem for the society. Therefore, a paradigm shift may be required as the present CIM system is not working for common interests of human beings as it should be.

Keywords: collaboation, inventory, shipping, virtual container yard

Procedia PDF Downloads 245

Authors: A. Samer Ezeldin, Sarah A. Fotouh

Abstract:

Optimization of resources is very important in all fields, as in construction management. Project managers have to face problems regarding management of cost, time and available resources of single projects and more problems arise when managing multiple projects. Most of the studies focused on optimization of resources for a single project, but, this paper will discuss the design and modeling of multiple resources optimization for multiple projects using Genetic Algorithm. Most of the companies in construction industry optimize the resources for single projects only, but with the presence of several mega projects in several developing countries running at the same time, there is a need for a model to enhance the efficiency of available resources and decreases the fluctuation as much as possible. The proposed model calculates the cost of each resource, tries to minimize the cost of extra resources as much as possible and generates the schedule of each project within a selected program.

Keywords: construction management, genetic algorithm, multiple projects, multiple resources, optimization

Procedia PDF Downloads 435

Authors: Mazyar Yosofi, Olivier Kerbrat, Pascal Mognol

Abstract:

Life cycle assessment of additive manufacturing processes has evolved significantly since these past years. A lot of existing studies mainly focused on energy consumption. Nowadays, new methodologies of life cycle inventory acquisition came through the literature and help manufacturers to take into account all the input and output flows during the manufacturing step of the life cycle of products. Indeed, the environmental analysis of the phenomena that occur during the manufacturing step of additive manufacturing processes is going to be well known. Now it becomes possible to count and measure accurately all the inventory data during the manufacturing step. Optimization of the environmental performances of processes can now be considered. Environmental performance improvement can be made by varying process parameters. However, a lot of these parameters (such as manufacturing speed, the power of the energy source, quantity of support materials) affect directly the mechanical properties, surface finish and the dimensional accuracy of a functional part. This study aims to improve the environmental performance of an additive manufacturing process without deterioration of the part quality. For that purpose, the authors have developed a generic method that has been applied on multiple parts made by additive manufacturing processes. First, a complete analysis of the process parameters is made in order to identify which parameters affect only the environmental performances of the process. Then, multiple parts are manufactured by varying the identified parameters. The aim of the second step is to find the optimum value of the parameters that decrease significantly the environmental impact of the process and keep the part quality as desired. Finally, a comparison between the part made by initials parameters and changed parameters is made. In this study, the major finding claims by authors is to reduce the environmental impact of an additive manufacturing process while respecting the three quality criterion of parts, mechanical properties, dimensional accuracy and surface roughness. Now that additive manufacturing processes can be seen as mature from a technical point of view, environmental improvement of these processes can be considered while respecting the part properties. The first part of this study presents the methodology applied to multiple academic parts. Then, the validity of the methodology is demonstrated on functional parts.

Keywords: additive manufacturing, environmental impact, environmental improvement, mechanical properties

Procedia PDF Downloads 271

Authors: Prakash Kumar Nayak, Avinash Kumar, Uma Dash, Kalpana Rayaguru

Abstract:

Soybean oil is one of the most widely consumed cooking oils, worldwide. Deep-fat frying of foods at higher temperatures adds unique flavour, golden brown colour and crispy texture to foods. But it brings in various changes like hydrolysis, oxidation, hydrogenation and thermal alteration to oil. The presence of Peroxide value (PV) is one of the most important factors affecting the quality of the deep-fat fried oil. Using bentonite as an adsorbent, the PV can be reduced, thereby improving the quality of the soybean oil. In this study, operating parameters like heating time of oil (10, 15, 20, 25 & 30 h), contact time ( 5, 10, 15, 20, 25 h) and concentration of adsorbent (0.25, 0.5, 0.75, 1.0 and 1.25 g/ 100 ml of oil) have been optimized by response surface methodology (RSM) considering percentage reduction of PV as a response. Adsorption data were analysed by fitting with Langmuir and Freundlich isotherm model. The results show that the Langmuir model shows the best fit compared to the Freundlich model. The adsorption process was also found to follow a pseudo-second-order kinetic model.

Keywords: bentonite, Langmuir isotherm, peroxide value, RSM, soybean oil

Procedia PDF Downloads 357

Authors: Thorsten Herrmann, Alexander Laukemann, Hansgeorg Binz, Daniel Roth

Abstract:

For the analysis of already identified and existing problems, the pertinent literature provides a comprehensive collection of approaches as well as methods in order to analyze the problems in detail. But coming up with problems, which are assets worth pursuing further, is often challenging. However, the importance of well-formulated problem ideas and their influence of subsequent creative processes are incontestable and proven. In order to meet the covered challenges, the Institute for Engineering Design and Industrial Design (IKTD) developed the Emoji Method. This paper presents the Emoji Method, which support designers to generate problem ideas in a structured way. Considering research findings from knowledge management and innovation management, research into emojis and emoticons reveal insights by means of identifying and formulating problem ideas within the early design phase. The simple application and the huge supporting potential of the Emoji Method within the early design phase are only few of the many successful results of the conducted evaluation. The Emoji Method encourages designers to identify problem ideas and describe them in a structured way in order to start focused with generating solution ideas for the revealed problem ideas.

Keywords: emojis, problem ideas, innovation management, knowledge management

Procedia PDF Downloads 134