Search results for: cost performance

Authors: Ali R. Alshawawreh, Francisco Liébana-Cabanillas, Francisco J. Blanco-Encomienda

Abstract:

Collaboration between marketing and business intelligence (BI) is crucial in today's ever-evolving business landscape. These two domains play pivotal roles in molding customers' experiential knowledge. Marketing insights offer valuable information regarding customer needs, preferences, and behaviors, thus refining marketing strategies and enhancing overall customer experiences. Conversely, BI facilitates data-driven decision-making, leading to heightened operational efficiency, product quality, and customer satisfaction. The analysis of customer data through BI unveils patterns and trends, informing product development, marketing campaigns, and customer service initiatives aimed at enriching experiences and knowledge. Customer experiential knowledge (CEK) encompasses customers' implicit comprehension of consumption experiences influenced by diverse factors, including social and cultural influences. This study primarily focuses on telecommunications companies in Jordan, scrutinizing how experiential customer knowledge mediates the relationship between marketing intelligence, business intelligence, and innovation in product and service offerings. Drawing on theoretical frameworks such as the resource-based view (RBV) and service-dominant logic (SDL), the research aims to comprehend how organizations utilize their resources, particularly knowledge, to foster innovation. Employing a quantitative research approach, the study collected and analyzed primary data to explore hypotheses. The chosen method was justified for its efficacy in handling large sample sizes. Structural equation modeling (SEM) facilitated by Smart PLS software evaluated the relationships between the constructs, followed by mediation analysis to assess the indirect associations in the model. The study findings offer insights into the intricate dynamics of organizational innovation, uncovering the interconnected relationships between business intelligence, customer experiential knowledge-based innovation (CEK-DI), marketing intelligence (MI), and product and service innovation (PSI), underscoring the pivotal role of advanced intelligence capabilities in developing innovative practices rooted in a profound understanding of customer experiences. Organizations equipped with cutting-edge BI tools are better positioned to devise strategies informed by precise insights into customer needs and behaviors. Furthermore, the positive impact of BI on PSI reaffirms the significance of data-driven decision-making in shaping the innovation landscape. Companies leveraging BI demonstrate adeptness in identifying market opportunities guiding the development of novel products and services. The substantial impact of CEK-DI on PSI highlights the crucial role of customer experiences in driving organizational innovation. Firms actively integrating customer insights into their innovation processes are more likely to create offerings aligned with customer expectations, fostering higher levels of product and service innovation. Additionally, the positive and significant effect of MI on CEK-DI underscores the critical role of market insights in shaping innovative strategies. While the relationship between MI and PSI is positive, a slightly weaker significance level indicates a nuanced association, suggesting that while MI contributes to innovation, other factors may also influence the innovation landscape, warranting further exploration. In conclusion, the study underscores the essential role of intelligence capabilities, particularly artificial intelligence, in driving innovation, emphasizing the necessity for organizations to leverage market and customer intelligence for effective and competitive innovation practices. Collaborative efforts between marketing and business intelligence serve as pivotal drivers of innovation, influencing experiential customer knowledge and shaping organizational strategies and practices, ultimately enhancing overall customer experiences and organizational performance.

Keywords: marketing intelligence, business intelligence, product, customer experiential knowledge-driven innovation

Procedia PDF Downloads 43

Authors: Arthur Müller

Abstract:

The study treats human dimensions of hunting by conducting statistical data analysis and providing decision-making support by examples of good prefectural governance and successful wildlife management, crucial to reduce pest species and sustain a stable hunter population in the future. Therefore it analyzes recent revision of wildlife legislation, reveals differences in administrative management structures, as well as socio-demographic characteristics of hunters in correlation with harvest trends of sika deer and wild boar in 47 prefectures in Japan between 1990 and 2013. In a wider context, Japan’s decentralized license hunting system might take the potential future role of a regional pioneer in East Asia. Consequently, the study contributes to similar issues in premature hunting systems of South Korea and Taiwan. Firstly, a quantitative comparison of seven mainland regions was conducted in Hokkaido, Tohoku, Kanto, Chubu, Kinki, Chugoku, and Kyushu. Example prefectures were chosen by a cluster analysis. Shifts, differences, mean values and exponential growth rates between trap and gun hunters, age classes and common occupation types of hunters were statistically exterminated. While western Japan is characterized by high numbers of aged trap-hunters, occupied in agricultural- and forestry, the north-eastern prefectures show higher relative numbers of younger gun-hunters occupied in the field of production and process workers. With the exception of Okinawa island, most hunters in all prefectures are 60 years and older. Hence, unemployed and retired hunters are the fastest growing occupation group. Despite to drastic decrease in hunter population in absolute numbers, Hunting Recruitment Index indicated that all age classes tend to continue their hunting activity over a longer period, above ten years from 2004 to 2013 than during the former decade. Associated with a rapid population increase and distribution of sika deer and wild boar since 1978, a number of harvest from hunting and culling also have been rapidly increasing. Both wild boar hunting and culling is particularly high in western Japan, while sika hunting and culling proofs most successful in Hokkaido, central and western Japan. Since the Wildlife Protection and Proper Hunting Act in 1999 distinct prefectural hunting management authorities with different power, sets apply management approaches under the principles of subsidiarity and guidelines of the Ministry of Environment. Additionally, the Act on Special Measures for Prevention of Damage Related to Agriculture, Forestry, and Fisheries Caused by Wildlife from 2008 supports local hunters in damage prevention measures through subsidies by the Ministry of Agriculture and Forestry, which caused a rise of trap hunting, especially in western Japan. Secondly, prefectural staff in charge of wildlife management in seven regions was contacted. In summary, Hokkaido serves as a role model for dynamic, integrative, adaptive “feedback” management of Ezo sika deer, as well as a diverse network between management organizations, while Hyogo takes active measures to trap-hunt wild boars effectively. Both prefectures take the leadership in institutional performance and capacity. Northern prefectures in Tohoku, Chubu and Kanto region, firstly confronted with the emergence of wild boars and rising sika deer numbers, demand new institution and capacity building, as well as organizational learning.

Keywords: hunting and culling harvest trends, hunter socio-demographics, regional comparison, wildlife management approach

Procedia PDF Downloads 255

Authors: Kyriaki Hatziagapiou, Eleni Kakouri, Konstantinos Bethanis, Alexandra Nikola, Eleni Koniari, Charalabos Kanakis, Elias Christoforides, George Lambrou, Petros Tarantilis

Abstract:

Medulloblastoma is a highly invasive tumour, as it tends to disseminate throughout the central nervous system early in its course. Despite the high 5-year-survival rate, a significant number of patients demonstrate serious long- or short-term sequelae (e.g., myelosuppression, endocrine dysfunction, cardiotoxicity, neurological deficits and cognitive impairment) and higher mortality rates, unrelated to the initial malignancy itself but rather to the aggressive treatment. A strong rationale exists for the use of Crocus sativus L (saffron) and its bioactive constituents (crocin, crocetin, safranal) as pharmaceutical agents, as they exert significant health-promoting properties. Crocins are water soluble carotenoids. Unlike other carotenoids, crocins are highly water-soluble compounds, with relatively low toxicity as they are not stored in adipose and liver tissues. Crocins have attracted wide attention as promising anti-cancer agents, due to their antioxidant, anti-inflammatory, and immunomodulatory effects, interference with transduction pathways implicated in tumorigenesis, angiogenesis, and metastasis (disruption of mitotic spindle assembly, inhibition of DNA topoisomerases, cell-cycle arrest, apoptosis or cell differentiation) and sensitization of cancer cells to radiotherapy and chemotherapy. The current research aimed to study the potential cytotoxic effect of crocins on TE671 medulloblastoma cell line, which may be useful in the optimization of existing and development of new therapeutic strategies. Crocins were extracted from stigmas of saffron in ultrasonic bath, using petroleum-ether, diethylether and methanol 70%v/v as solvents and the final extract was lyophilized. Identification of crocins according to high-performance liquid chromatography (HPLC) analysis was determined comparing the UV-vis spectra and the retention time (tR) of the peaks with literature data. For the biological assays crocin was diluted to nuclease and protease free water. TE671 cells were incubated with a range of concentrations of crocins (16, 8, 4, 2, 1, 0.5 and 0.25 mg/ml) for 24, 48, 72 and 96 hours. Analysis of cell viability after incubation with crocins was performed with Alamar Blue viability assay. The active ingredient of Alamar Blue, resazurin, is a blue, nontoxic, cell permeable compound virtually nonfluorescent. Upon entering cells, resazurin is reduced to a pink and fluorescent molecule, resorufin. Viable cells continuously convert resazurin to resorufin, generating a quantitative measure of viability. The colour of resorufin was quantified by measuring the absorbance of the solution at 600 nm with a spectrophotometer. HPLC analysis indicated that the most abundant crocins in our extract were trans-crocin-4 and trans-crocin-3. Crocins exerted significant cytotoxicity in a dose and time-dependent manner (p < 0.005 for exposed cells to any concentration at 48, 72 and 96 hours versus cells not exposed); as their concentration and time of exposure increased, the reduction of resazurin to resofurin decreased, indicating reduction in cell viability. IC50 values for each time point were calculated ~3.738, 1.725, 0.878 and 0.7566 mg/ml at 24, 48, 72 and 96 hours, respectively. The results of our study could afford the basis of research regarding the use of natural carotenoids as anticancer agents and the shift to targeted therapy with higher efficacy and limited toxicity. Acknowledgements: The research was funded by Fellowships of Excellence for Postgraduate Studies IKY-Siemens Programme.

Keywords: crocetin, crocin, medulloblastoma, saffron

Procedia PDF Downloads 192

Authors: Ghidey Ghebreyohanes, Eltahir Awad Gasim Khalil, Zemenfes Tsighe, Faiza Ali

Abstract:

Background: reproductive health (RH) is a state of physical, mental and social well-being in all matters relating to the reproductive system at all stages of life. In East Africa including Eritrea, adolescents comprise more than a quarter of the population. The region holds the highest rates of sexually transmitted diseases, HIV, unwanted pregnancy and unsafe abortion with its complications. Young girls carry the highest burden of reproductive health problems due to their risk taking behavior, lack of knowledge, peer pressure, physiologic immaturity and low socioeconomic status. Design: this was a Community-based, randomized, case-controlled and pre-test-post-test intervention study. Setting: Zoba Debub was randomly selected out of the six zobas in Eritrea. The four high schools out of the 26 in Zoba Debub were randomly selected as study target schools. Over three quarter of the people live on farming. The target population was female students attending grade nine with majority of these girls live in the distant villages and walk to school. The study participants were randomly selected (n=165) from each school. Furthermore, the 1 intervention and 3 controls for the study arms were assigned randomly. Objectives: this study aimed to assess the effectiveness of peer reproductive health education in improving knowledge, attitude, and health service use of high school adolescent girls in Eritrea Methods: the protocol was reviewed and approved by the Scientific and Ethics Committees of Faculty of Nursing Sciences, University of Khartoum. Data was collected using pre-designed and pretested questionnaire emphasizing on reproductive health knowledge, attitude and practice. Sample size was calculated using proportion formula (α 0.01; power of 95%). Measures used were scores and proportions. Descriptive and inferential statistics, t-test and chi square at (α .01), 99% confidence interval were used to compare changes of pre and post-intervention scores using SPSS soft ware. Seventeen students were selected for peer educators by the school principals and other teachers based on inclusion criteria that include: good academic performance and acceptable behavior. One peer educator educated one group composed of 8-10 students for two months. One faculty member was selected to supervise peer educators. The principal investigator conducted the training of trainers and provided supervision and discussion to peer educators every two weeks until the end of intervention. Results: following informed consent, 627 students [164 in intervention and 463 in the control group] with a ratio of 1 to 3, were enrolled in the study. The mean age for the total study population was 15.4±1.0 years. The intervention group mean age was 15.3±1.0 year; while the control group had a mean age of 15.4±1.0. The mean ages for the study arms were similar (p= 0.4). The majority (96 %) of the study participants are from Tigrigna ethnic group. Reproductive knowledge scores which was calculated out of a total 61 grade points: intervention group (pretest 6.7 %, post-test 33.6 %; p= 0.0001); control group (pretest 7.3 %, posttest 7.3 %, p= 0.92). Proportion difference in attitude calculated out of 100%: intervention group (pretest 42.3 % post test 54.7% p= 0.001); controls group (pretest 45%, post test 44.8 p= 0.7). Proportion difference in Practice calculated out of 100 %: intervention group (pretest 15.4%, post test 80.4 % p= 0.0001); control group (pretest 16.8%, posttest 16.9 % p= 0.8). Mothers were quoted as major (> 90 %) source of reproductive health information. All focus group discussants and most of survey participants agreed on the urgent need of reproductive health information and services for adolescent girls. Conclusion: reproductive health knowledge and use of facilities is poor among adolescent girls in sub-urban Eretria. School-based peer reproductive health education is effective and is the best strategy to improve reproductive health knowledge and attitudes.

Keywords: reproductive health, adolescent girls, eretria, health education

Procedia PDF Downloads 337

Authors: Mohamed Sameer Mughal, Andrew D. Ross, Damian J. Fearon

Abstract:

Background: The fast-paced changing landscape of UK Higher Education Institution (HEIs) is poised by changes and challenges affecting Middle Managers (MM) in their job roles. MM contribute to the success of HEIs by balancing the equilibrium and pass organization strategies from senior staff towards operationalization directives to junior staff. However, this study showcased from the data analyzed during the semi structured interviews; MM job role is becoming more complex due to changes and challenges creating colossal pressures and workloads in day-to-day working. Current development programmes provisions by Human Resources (HR) departments in such HEIs are not feasible, applicable, and matching the true essence and requirements of MM who suggest that programmes offered by HR are too generic to suit their precise needs and require tailor made espousal to work effectively in their pertinent job roles. Methodologies: This study aims to capture demands of MM Development Needs (DN) by means of a conceptual model as conclusive part of the research that is divided into 2 phases. Phase 1 initiated by carrying out 2 pilot interviews with a retired Emeritus status professor and HR programmes development coordinator. Key themes from the pilot and literature review subsidized into formulation of 22 set of questions (Kvale and Brinkmann) in form of interviewing questionnaire during qualitative data collection. Data strategy and collection consisted of purposeful sampling of 12 semi structured interviews (n=12) lasting approximately an hour for all participants. The MM interviewed were at faculty and departmental levels which included; deans (n=2), head of departments (n=4), subject leaders (n=2), and lastly programme leaders (n=4). Participants recruitment was carried out via emails and snowballing technique. The interviews data was transcribed (verbatim) and managed using Computer Assisted Qualitative Data Analysis using Nvivo ver.11 software. Data was meticulously analyzed using Miles and Huberman inductive approach of positivistic style grounded theory, whereby key themes and categories emerged from the rich data collected. The data was precisely coded and classified into case studies (Robert Yin); with a main case study, sub cases (4 classes of MM) and embedded cases (12 individual MMs). Major Findings: An interim conceptual model emerged from analyzing the data with main concepts that included; key performance indicators (KPI’s), HEI effectiveness and outlook, practices, processes and procedures, support mechanisms, student events, rules, regulations and policies, career progression, reporting/accountability, changes and challenges, and lastly skills and attributes. Conclusion: Dynamic elements affecting MM includes; increase in government pressures, student numbers, irrelevant development programmes, bureaucratic structures, transparency and accountability, organization policies, skills sets… can only be confronted by employing structured development programmes originated by HR that are not provided generically. Future Work: Stage 2 (Quantitative method) of the study plans to validate the interim conceptual model externally through fully completed online survey questionnaire (Bram Oppenheim) from external HEIs (n=150). The total sample targeted is 1500 MM. Author contribution focuses on enhancing management theory and narrow the gap between by HR and MM development programme provision.

Keywords: development needs (DN), higher education institutions (HEIs), human resources (HR), middle managers (MM)

Procedia PDF Downloads 214

Authors: Ali Kazemi

Abstract:

Those within the volatile and interconnected international economic markets, appropriately predicting market trends, hold substantial fees for traders and financial establishments. Traditional device mastering strategies have made full-size strides in forecasting marketplace movements; however, monetary data's complicated and networked nature calls for extra sophisticated processes. This observation offers a groundbreaking method for monetary marketplace prediction that leverages the synergistic capability of Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. Our suggested algorithm is meticulously designed to forecast the traits of inventory market indices and cryptocurrency costs, utilizing a comprehensive dataset spanning from January 1, 2015, to December 31, 2023. This era, marked by sizable volatility and transformation in financial markets, affords a solid basis for schooling and checking out our predictive version. Our algorithm integrates diverse facts to construct a dynamic economic graph that correctly reflects market intricacies. We meticulously collect opening, closing, and high and low costs daily for key inventory marketplace indices (e.g., S&P 500, NASDAQ) and widespread cryptocurrencies (e.g., Bitcoin, Ethereum), ensuring a holistic view of marketplace traits. Daily trading volumes are also incorporated to seize marketplace pastime and liquidity, providing critical insights into the market's shopping for and selling dynamics. Furthermore, recognizing the profound influence of the monetary surroundings on financial markets, we integrate critical macroeconomic signs with hobby fees, inflation rates, GDP increase, and unemployment costs into our model. Our GCN algorithm is adept at learning the relational patterns amongst specific financial devices represented as nodes in a comprehensive market graph. Edges in this graph encapsulate the relationships based totally on co-movement styles and sentiment correlations, enabling our version to grasp the complicated community of influences governing marketplace moves. Complementing this, our LSTM algorithm is trained on sequences of the spatial-temporal illustration discovered through the GCN, enriched with historic fee and extent records. This lets the LSTM seize and expect temporal marketplace developments accurately. Inside the complete assessment of our GCN-LSTM algorithm across the inventory marketplace and cryptocurrency datasets, the version confirmed advanced predictive accuracy and profitability compared to conventional and opportunity machine learning to know benchmarks. Specifically, the model performed a Mean Absolute Error (MAE) of 0.85%, indicating high precision in predicting day-by-day charge movements. The RMSE was recorded at 1.2%, underscoring the model's effectiveness in minimizing tremendous prediction mistakes, which is vital in volatile markets. Furthermore, when assessing the model's predictive performance on directional market movements, it achieved an accuracy rate of 78%, significantly outperforming the benchmark models, averaging an accuracy of 65%. This high degree of accuracy is instrumental for techniques that predict the course of price moves. This study showcases the efficacy of mixing graph-based totally and sequential deep learning knowledge in economic marketplace prediction and highlights the fee of a comprehensive, records-pushed evaluation framework. Our findings promise to revolutionize investment techniques and hazard management practices, offering investors and economic analysts a powerful device to navigate the complexities of cutting-edge economic markets.

Keywords: financial market prediction, graph convolutional networks (GCNs), long short-term memory (LSTM), cryptocurrency forecasting

Procedia PDF Downloads 30

Authors: Claire Harrison, Raajit K. Rampal, Vikas Gupta, Srdan Verstovsek, Moshe Talpaz, Jean-Jacques Kiladjian, Ruben Mesa, Andrew Kuykendall, Alessandro Vannucchi, Francesca Palandri, Sebastian Grosicki, Timothy Devos, Eric Jourdan, Marielle J. Wondergem, Haifa Kathrin Al-Ali, Veronika Buxhofer-Ausch, Alberto Alvarez-Larrán, Sanjay Akhani, Rafael Muñoz-Carerras, Yury Sheykin, Gozde Colak, Morgan Harris, John Mascarenhas

Abstract:

Myelofibrosis (MF) is characterized by bone marrow fibrosis, anemia, splenomegaly and constitutional symptoms. Progressive bone marrow fibrosis results from aberrant megakaryopoeisis and expression of proinflammatory cytokines, both of which are heavily influenced by bromodomain and extraterminal domain (BET)-mediated gene regulation and lead to myeloproliferation and cytopenias. Pelabresib (CPI-0610) is an oral small-molecule investigational inhibitor of BET protein bromodomains currently being developed for the treatment of patients with MF. It is designed to downregulate BET target genes and modify nuclear factor kappa B (NF-κB) signaling. MANIFEST-2 was initiated based on data from Arm 3 of the ongoing Phase 2 MANIFEST study (NCT02158858), which is evaluating the combination of pelabresib and ruxolitinib in Janus kinase inhibitor (JAKi) treatment-naïve patients with MF. Primary endpoint analyses showed splenic and symptom responses in 68% and 56% of 84 enrolled patients, respectively. MANIFEST-2 (NCT04603495) is a global, Phase 3, randomized, double-blind, active-control study of pelabresib and ruxolitinib versus placebo and ruxolitinib in JAKi treatment-naïve patients with primary MF, post-polycythemia vera MF or post-essential thrombocythemia MF. The aim of this study is to evaluate the efficacy and safety of pelabresib in combination with ruxolitinib. Here we report updates from a recent protocol amendment. The MANIFEST-2 study schema is shown in Figure 1. Key eligibility criteria include a Dynamic International Prognostic Scoring System (DIPSS) score of Intermediate-1 or higher, platelet count ≥100 × 10^9/L, spleen volume ≥450 cc by computerized tomography or magnetic resonance imaging, ≥2 symptoms with an average score ≥3 or a Total Symptom Score (TSS) of ≥10 using the Myelofibrosis Symptom Assessment Form v4.0, peripheral blast count <5% and Eastern Cooperative Oncology Group performance status ≤2. Patient randomization will be stratified by DIPSS risk category (Intermediate-1 vs Intermediate-2 vs High), platelet count (>200 × 10^9/L vs 100–200 × 10^9/L) and spleen volume (≥1800 cm^3 vs <1800 cm^3). Double-blind treatment (pelabresib or matching placebo) will be administered once daily for 14 consecutive days, followed by a 7 day break, which is considered one cycle of treatment. Ruxolitinib will be administered twice daily for all 21 days of the cycle. The primary endpoint is SVR35 response (≥35% reduction in spleen volume from baseline) at Week 24, and the key secondary endpoint is TSS50 response (≥50% reduction in TSS from baseline) at Week 24. Other secondary endpoints include safety, pharmacokinetics, changes in bone marrow fibrosis, duration of SVR35 response, duration of TSS50 response, progression-free survival, overall survival, conversion from transfusion dependence to independence and rate of red blood cell transfusion for the first 24 weeks. Study recruitment is ongoing; 400 patients (200 per arm) from North America, Europe, Asia and Australia will be enrolled. The study opened for enrollment in November 2020. MANIFEST-2 was initiated based on data from the ongoing Phase 2 MANIFEST study with the aim of assessing the efficacy and safety of pelabresib and ruxolitinib in JAKi treatment-naïve patients with MF. MANIFEST-2 is currently open for enrollment.

Keywords: CPI-0610, JAKi treatment-naïve, MANIFEST-2, myelofibrosis, pelabresib

Procedia PDF Downloads 177

Authors: Manavjit Singh Dhindsa, Ursula Das, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

Abstract:

These days, wildland fires, also known as forest fires, are more prevalent than ever. Wildfires have major repercussions that affect ecosystems, communities, and the environment in several ways. Wildfires lead to habitat destruction and biodiversity loss, affecting ecosystems and causing soil erosion. They also contribute to poor air quality by releasing smoke and pollutants that pose health risks, especially for individuals with respiratory conditions. Wildfires can damage infrastructure, disrupt communities, and cause economic losses. The economic impact of firefighting efforts, combined with their direct effects on forestry and agriculture, causes significant financial difficulties for the areas impacted. This research explores different forest fire spread models and presents a comprehensive review of various techniques and methodologies used in the field. A forest fire spread model is a computational or mathematical representation that is used to simulate and predict the behavior of a forest fire. By applying scientific concepts and data from empirical studies, these models attempt to capture the intricate dynamics of how a fire spreads, taking into consideration a variety of factors like weather patterns, topography, fuel types, and environmental conditions. These models assist authorities in understanding and forecasting the potential trajectory and intensity of a wildfire. Emphasizing the need for a comprehensive understanding of wildfire dynamics, this research explores the approaches, assumptions, and findings derived from various models. By using a comparison approach, a critical analysis is provided by identifying patterns, strengths, and weaknesses among these models. The purpose of the survey is to further wildfire research and management techniques. Decision-makers, researchers, and practitioners can benefit from the useful insights that are provided by synthesizing established information. Fire spread models provide insights into potential fire behavior, facilitating authorities to make informed decisions about evacuation activities, allocating resources for fire-fighting efforts, and planning for preventive actions. Wildfire spread models are also useful in post-wildfire mitigation strategies as they help in assessing the fire's severity, determining high-risk regions for post-fire dangers, and forecasting soil erosion trends. The analysis highlights the importance of customized modeling approaches for various circumstances and promotes our understanding of the way forest fires spread. Some of the known models in this field are Rothermel’s wildland fuel model, FARSITE, WRF-SFIRE, FIRETEC, FlamMap, FSPro, cellular automata model, and others. The key characteristics that these models consider include weather (includes factors such as wind speed and direction), topography (includes factors like landscape elevation), and fuel availability (includes factors like types of vegetation) among other factors. The models discussed are physics-based, data-driven, or hybrid models, also utilizing ML techniques like attention-based neural networks to enhance the performance of the model. In order to lessen the destructive effects of forest fires, this initiative aims to promote the development of more precise prediction tools and effective management techniques. The survey expands its scope to address the practical needs of numerous stakeholders. Access to enhanced early warning systems enables decision-makers to take prompt action. Emergency responders benefit from improved resource allocation strategies, strengthening the efficacy of firefighting efforts.

Keywords: artificial intelligence, deep learning, forest fire management, fire risk assessment, fire simulation, machine learning, remote sensing, wildfire modeling

Procedia PDF Downloads 62

Authors: Zhi-Zhong Chen, Jun-Hao Lu, Jr., Shih-Ying Chueh

Abstract:

Based on Unified Theory of Acceptance and Use of Technology (UTAUT), the study investigates people’s intention on using smart phones. The study additionally incorporates two new variables: 'self-efficacy' and 'attitude toward using'. Samples are collected by questionnaire survey, in which 240 are valid. After Correlation Analysis, Reliability Test, ANOVA, t-test and Multiple Regression Analysis, the study finds that social impact and self-efficacy have positive effect on use intentions, and the use intentions also have positive effect on use behavior.

Keywords: [1] Ajzen & Fishbein (1975), “Belief, attitude, intention and behavior: An introduction to theory and research”, Reading MA: Addison-Wesley. [2] Bandura (1977) Self-efficacy: toward a unifying theory of behavioural change. Psychological Review , 84, 191–215. [3] Bandura( 1986) A. Bandura, Social foundations of though and action, Prentice-Hall. Englewood Cliffs. [4] Ching-Hui Huang (2005). The effect of Regular Exercise on Elderly Optimism: The Self-efficacy and Theory of Reasoned Action Perspectives.(Master's dissertation, National Taiwan Sport University, 2005).National Digital Library of Theses and Dissertations in Taiwan。 [5] Chun-Mo Wu (2007).The Effects of Perceived Risk and Service Quality on Purchase Intention - an Example of Taipei City Long-Term Care Facilities. (Master's dissertation, Ming Chuan University, 2007).National Digital Library of Theses and Dissertations in Taiwan. [6] Compeau, D.R., and Higgins, C.A., (1995) “Application of social cognitive theory to training for computer skills.”, Information Systems Research, 6(2), pp.118-143. [7] computer-self-efficacy and mediators of the efficacy-performance relationship. International Journal of Human-Computer Studies, 62, 737-758. [8] Davis et al(1989), “User acceptance of computer technology: A comparison of two theoretical models ”, Management Science, 35(8), p.982-1003. [9] Davis et al(1989), “User acceptance of computer technology:A comparison of two theoretical models ”, Management Science, 35(8), p.982-1003. [10] Davis, F.D. (1989). Perceived Usefulness, Perceived Ease of Use and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-340。 [11] Davis. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–340. doi:10.2307/249008 [12] Johnson, R. D. (2005). An empirical investigation of sources of application-specific [13] Mei-yin Hsu (2010).The Study on Attitude and Satisfaction of Electronic Documents System for Administrators of Elementary Schools in Changhua County.(Master's dissertation , Feng Chia University, 2010).National Digital Library of Theses and Dissertations in Taiwan. [14] Ming-Chun Hsieh (2010). Research on Parents’ Attitudes Toward Electronic Toys： The case of Taichung City.(Master's dissertation, Chaoyang University of Technology，2010).National Digital Library of Theses and Dissertations in Taiwan. [15] Moon and Kim（2001）. Extending the TAM for a World-Wide-Web context, Information and Management, v.38 n.4, p.217-230. [16] Shang-Yi Hu (2010).The Impacts of Knowledge Management on Customer Relationship Management – Enterprise Characteristicsand Corporate Governance as a Moderator.(Master's dissertation, Leader University, 2010)。National Digital Library of Theses and Dissertations in Taiwan. [17] Sheng-Yi Hung (2013, September10).Worldwide sale of smartphones to hit one billion IDC：Android dominate the market. ETtoday. Retrieved data form the available protocol:2013/10/3. [18] Thompson, R.L., Higgins, C.A., and Howell, J.M.(1991), “Personal Computing: Toward a Conceptual Model of Utilization”, MIS Quarterly(15:1), pp. 125-143. [19] Venkatesh, V., M.G. Morris, G.B. Davis, and F. D. Davis (2003), “User acceptance of information technology: Toward a unified view, ” MIS Quarterly, 27, No. 3, pp.425-478. [20] Vijayasarathy, L. R. (2004), Predicting Consumer Intentions to Use On-Line Shopping： The Case for an Augmented Technology Acceptance Model, Information and Management, Vol.41, No.6, pp.747-762. [21] Wikipedia - smartphone (http://zh.wikipedia.org/zh-tw/%E6%99%BA%E8%83%BD%E6%89%8B%E6%9C%BA)。 [22] Wu-Minsan (2008).The impacts of self-efficacy, social support on work adjustment with hearing impaired. (Master's dissertation, Southern Taiwan University of Science and Technology, 2008).National Digital Library of Theses and Dissertations in Taiwan. [23] Yu-min Lin (2006). The Influence of Business Employee’s MSN Self-efficacy On Instant Messaging Usage Behavior and Communicaiton Satisfaction.(Master's dissertation, National Taiwan University of Science and Technology, 2006).National Digital Library of Theses and Dissertations in Taiwan.

Procedia PDF Downloads 386

Authors: Ali Kadir, S. R. Mishra, M. Shamshuddin, O. Anwar Beg

Abstract:

Motivation- Rotating disk bio-reactors are fundamental to numerous medical/biochemical engineering processes including oxygen transfer, chromatography, purification and swirl-assisted pumping. The modern upsurge in biologically-enhanced engineering devices has embraced new phenomena including bioconvection of micro-organisms (photo-tactic, oxy-tactic, gyrotactic etc). The proven thermal performance superiority of nanofluids i.e. base fluids doped with engineered nanoparticles has also stimulated immense implementation in biomedical designs. Motivated by these emerging applications, we present a numerical thermofluid dynamic simulation of the transport phenomena in bioconvection nanofluid rotating disk bioreactor flow. Methodology- We study analytically and computationally the time-dependent three-dimensional viscous gyrotactic bioconvection in swirling nanofluid flow from a rotating disk configuration. The disk is also deformable i.e. able to extend (stretch) in the radial direction. Stefan blowing is included. The Buongiorno dilute nanofluid model is adopted wherein Brownian motion and thermophoresis are the dominant nanoscale effects. The primitive conservation equations for mass, radial, tangential and axial momentum, heat (energy), nanoparticle concentration and micro-organism density function are formulated in a cylindrical polar coordinate system with appropriate wall and free stream boundary conditions. A mass convective condition is also incorporated at the disk surface. Forced convection is considered i.e. buoyancy forces are neglected. This highly nonlinear, strongly coupled system of unsteady partial differential equations is normalized with the classical Von Karman and other transformations to render the boundary value problem (BVP) into an ordinary differential system which is solved with the efficient Adomian decomposition method (ADM). Validation with earlier Runge-Kutta shooting computations in the literature is also conducted. Extensive computations are presented (with the aid of MATLAB symbolic software) for radial and circumferential velocity components, temperature, nanoparticle concentration, micro-organism density number and gradients of these functions at the disk surface (radial local skin friction, local circumferential skin friction, Local Nusselt number, Local Sherwood number, motile microorganism mass transfer rate). Main Findings- Increasing radial stretching parameter decreases radial velocity and radial skin friction, reduces azimuthal velocity and skin friction, decreases local Nusselt number and motile micro-organism mass wall flux whereas it increases nano-particle local Sherwood number. Disk deceleration accelerates the radial flow, damps the azimuthal flow, decreases temperatures and thermal boundary layer thickness, depletes the nano-particle concentration magnitudes (and associated nano-particle species boundary layer thickness) and furthermore decreases the micro-organism density number and gyrotactic micro-organism species boundary layer thickness. Increasing Stefan blowing accelerates the radial flow and azimuthal (circumferential flow), elevates temperatures of the nanofluid, boosts nano-particle concentration (volume fraction) and gyrotactic micro-organism density number magnitudes whereas suction generates the reverse effects. Increasing suction effect reduces radial skin friction and azimuthal skin friction, local Nusselt number, and motile micro-organism wall mass flux whereas it enhances the nano-particle species local Sherwood number. Conclusions - Important transport characteristics are identified of relevance to real bioreactor nanotechnological systems not discussed in previous works. ADM is shown to achieve very rapid convergence and highly accurate solutions and shows excellent promise in simulating swirling multi-physical nano-bioconvection fluid dynamics problems. Furthermore, it provides an excellent complement to more general commercial computational fluid dynamics simulations.

Keywords: bio-nanofluids, rotating disk bioreactors, Von Karman swirling flow, numerical solutions

Procedia PDF Downloads 132