Search results for: decentralized data management
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30731

Search results for: decentralized data management

26981 The Impact of Market Orientation on the Adoption of E-Marketing and Value Co-Creation

Authors: Shu-Hui Chuang, Shao-Chun Chiu, Shu-Hsin Chuang

Abstract:

While the marketing management literature is regarding the direct benefits of market orientation (MO) on firm value, the impact of such MO-based value co-creation remains largely an unexplored area of research. Thus, the primary objective of this study is to provide some new perspectives in examining how MO can enhance value co-creation for customers and sellers. In particular, drawing from the relational view of the firm and IT literature, we propose that the chain of MO-based co-creation of value and how adopt e-marketing systems between partners can facilitate this chain. Using data on use of the e-marketing system, we empirically validate that the sellers’ integrated MO is critical in increasing the e-marketing adoption, which in turn helps to creation co-creation value for both parties.

Keywords: market orientation, value co-creation, e-marketing system, relational view of the firm

Procedia PDF Downloads 518
26980 Implementation of Complete Management Practices in Managing the Cocoa Pod Borer

Authors: B. Saripah, A. Alias

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Cocoa Theobroma cacao (Linnaeus) (Malvales: Sterculiaceae) is subjected to be infested by various numbers of insect pests, and Conopomorpha cramerella Snellen (Lepidoptera: Gracillariidae) is the most serious pest of cocoa in Malaysia. The pest was indigenous to the South East Asia. Several control measures have been implemented and the chemicals have been a major approach if not unilateral, in the management of CPB. Despite extensive use of insecticides, CPB continues to cause an unacceptable level of damage; thus, the combination of several control approaches should be sought. The study was commenced for 12 months at three blocks; Block 18C with complete management practices which include insecticide application, pruning, fertilization and frequent harvesting, Block 17C was treated with frequent harvesting at intervals of 7-8 days, and Block 19C was served as control block. The results showed that the mean numbers of CPB eggs were recorded higher in Block 17C compared with Block 18C in all sampling occasions. Block 18C shows the lowest mean number of CPB eggs in both sampling plots, outside and core plots and it was found significantly different (p ≤ 0. 05) compared to the other blocks. The mean number of CPB eggs was fluctuated throughout sampling occasions, the lowest mean number of eggs was recorded in January (17C) and November (18C), while the highest was recorded in April (17C) and December 2012 (18C). Frequent spraying with insecticides at the adjacent block (18C) helps in reducing CPB eggs in the control block (Block 19C), although there was no spraying was implemented Block 19C. In summary, the combination of complete management practices at Block 18C seems to have some effect on the CPB population at Blocks 17 and 19C because all blocks are adjacent to each other.

Keywords: cocoa, theobroma cacao, cocoa pod borer, conopomorpha cramerella

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26979 Social Work Practice to Labour Welfare: A Proposed Model of Field Work Practicum and Role of Social Worker in India

Authors: Naeem Ahmed

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Social work is a professional activity based on the approach of “helping people to help themselves” (Stroup). Social work education and practice both are based on humanitarian philosophy in which social workers try to increase the happiness of the society and to reduce the problems of society. Labour welfare is a specialised field of social work which especially focuses on welfare of organised and unorganised labour. In India labour is facing numerous problems in both organised and unorganised sectors because of ignorance, illiteracy, high rate of unemployment etc. In most of the Indian social work institutions we have this specialization with different names like Human Resource Management or Industrial Relation and Personnel Management or Industrial Relations and Labour Welfare or Industrial Social Work etc. Field work practice is integrated part of social work education curriculum in all specialised field. In India we have different field work practice models being followed in different institutions. The main objective of this paper is to prepare a universal field work practicum model in the field of labour welfare. This paper is exploratory in nature, researcher used personal experience and secondary data (model of field work practice in different institutions like Aligarh Muslim University, Pondicherry University, Central University of Karnataka, University of Lucknow, MJP Rohilkhand University Bareilly etc.) Researcher found that there is an immediate need to upgrade the curriculum or field work practice in this particular field, as more than 40 percent of total population engaged in either unorganised or organised sector (NSSO 2011-12) and they are not aware about their rights. In this way a social worker can play an important role in existing labour welfare facilities by making them aware.

Keywords: field work, labour welfare, organised labour, social work practice, unorganised labour

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26978 A Controlled Natural Language Assisted Approach for the Design and Automated Processing of Service Level Agreements

Authors: Christopher Schwarz, Katrin Riegler, Erwin Zinser

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The management of outsourcing relationships between IT service providers and their customers proofs to be a critical issue that has to be stipulated by means of Service Level Agreements (SLAs). Since service requirements differ from customer to customer, SLA content and language structures vary largely, standardized SLA templates may not be used and an automated processing of SLA content is not possible. Hence, SLA management is usually a time-consuming and inefficient manual process. For overcoming these challenges, this paper presents an innovative and ITIL V3-conform approach for automated SLA design and management using controlled natural language in enterprise collaboration portals. The proposed novel concept is based on a self-developed controlled natural language that follows a subject-predicate-object approach to specify well-defined SLA content structures that act as templates for customized contracts and support automated SLA processing. The derived results eventually enable IT service providers to automate several SLA request, approval and negotiation processes by means of workflows and business rules within an enterprise collaboration portal. The illustrated prototypical realization gives evidence of the practical relevance in service-oriented scenarios as well as the high flexibility and adaptability of the presented model. Thus, the prototype enables the automated creation of well defined, customized SLA documents, providing a knowledge representation that is both human understandable and machine processable.

Keywords: automated processing, controlled natural language, knowledge representation, information technology outsourcing, service level management

Procedia PDF Downloads 427
26977 Design of Incident Information System in IoT Virtualization Platform

Authors: Amon Olimov, Umarov Jamshid, Dae-Ho Kim, Chol-U Lee, Ryum-Duck Oh

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This paper proposes IoT virtualization platform based incident information system. IoT information based environment is the platform that was developed for the purpose of collecting a variety of data by managing regionally scattered IoT devices easily and conveniently in addition to analyzing data collected from roads. Moreover, this paper configured the platform for the purpose of providing incident information based on sensed data. It also provides the same input/output interface as UNIX and Linux by means of matching IoT devices with the directory of file system and also the files. In addition, it has a variety of approaches as to the devices. Thus, it can be applied to not only incident information but also other platforms. This paper proposes the incident information system that identifies and provides various data in real time as to urgent matters on roads based on the existing USN/M2M and IoT visualization platform.

Keywords: incident information system, IoT, virtualization platform, USN, M2M

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26976 The Impact of Socio-Economic and Type of Religion on the Behavior of Obedience among Arab-Israeli Teenagers

Authors: Sadhana Ghnayem

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This article examines the relationship between several socio-economic and background variables of Arab-Israeli families and their effect on the conflict management style of forcing, where teenage children are expected to obey their parents without questioning. The article explores the inter-generational gap and the desire of Arab-Israeli parents to force their teenage children to obey without questioning. The independent variables include: the sex of the parent, religion (Christian or Muslim), income of the parent, years of education of the parent, and the sex of the teenage child. We use the dependent variable of “Obedience Without Questioning” that is reported twice: by each of the parents as well as by the children. We circulated a questionnaire and collected data from a sample of 180 parents and their adolescent child living in the Galilee area during 2018. In this questionnaire we asked each of the parent and his/her teenage child about whether the latter is expected to follow the instructions of the former without questioning. The outcome of this article indicates, first, that Christian-Arab families are less authoritarian than Muslims families in demanding sheer obedience from their children. Second, female parents indicate more than male parents that their teenage child indeed obeys without questioning. Third, there is a negative correlation between the variable “Income” and “Obedience without Questioning.” Yet, the regression coefficient of this variable is close zero. Fourth, there is a positive correlation between years of education and obedience reported by the children. In other words, more educated parents are more likely to demand obedience from their children.  Finally, after running the regression, the study also found that the impact of the variables of religion as well as the sex of the child on the dependent variable of obedience is also significant at above 95 and 90%, respectively.

Keywords: conflict, religion, conflict management style, obedience

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26975 Social Network Analysis as a Research and Pedagogy Tool in Problem-Focused Undergraduate Social Innovation Courses

Authors: Sean McCarthy, Patrice M. Ludwig, Will Watson

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This exploratory case study explores the deployment of Social Network Analysis (SNA) in mapping community assets in an interdisciplinary, undergraduate, team-taught course focused on income insecure populations in a rural area in the US. Specifically, it analyzes how students were taught to collect data on community assets and to visualize the connections between those assets using Kumu, an SNA data visualization tool. Further, the case study shows how social network data was also collected about student teams via their written communications in Slack, an enterprise messaging tool, which enabled instructors to manage and guide student research activity throughout the semester. The discussion presents how SNA methods can simultaneously inform both community-based research and social innovation pedagogy through the use of data visualization and collaboration-focused communication technologies.

Keywords: social innovation, social network analysis, pedagogy, problem-based learning, data visualization, information communication technologies

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26974 Evaluation of Clinical Decision Support System in Electronic Medical Record System: A Case of Malawi National Art Electronic Medical Record System

Authors: Pachawo Bisani, Goodall Nyirenda

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The Malawi National Antiretroviral Therapy (NART) Electronic Medical Record (EMR) system was designed and developed with guidance from the Ministry of Health through the Department of HIV and AIDS (DHA) with the aim of supporting the management of HIV patient data and reporting in high prevalence ART clinics. As of 2021, the system has been scaled up to over 206 facilities across the country. The system is integrated with the clinical decision support system (CDSS) to assist healthcare providers in making a decision about an individual patient at a particular point in time. Despite NART EMR undergoing several evaluations and assessments, little has been done to evaluate the clinical decision support system in the NART EMR system. Hence, the study aimed to evaluate the use of CDSS in the NART EMR system in Malawi. The study adopted a mixed-method approach, and data was collected through interviews, observations, and questionnaires. The study has revealed that the CDSS tools were integrated into the ART clinic workflow, making it easy for the user to use it. The study has also revealed challenges in system reliability and information accuracy. Despite the challenges, the study further revealed that the system is effective and efficient, and overall, users are satisfied with the system. The study recommends that the implementers focus more on the logic behind the clinical decision-support intervention in order to address some of the concerns and enhance the accuracy of the information supplied. The study further suggests consulting the system's actual users throughout implementation.

Keywords: clinical decision support system, electronic medical record system, usability, antiretroviral therapy

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26973 Mangroves in the Douala Area, Cameroon: The Challenges of Open Access Resources for Forest Governance

Authors: Bissonnette Jean-François, Dossa Fabrice

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The project focuses on analyzing the spatial and temporal evolution of mangrove forest ecosystems near the city of Douala, Cameroon, in response to increasing human and environmental pressures. The selected study area, located in the Wouri River estuary, has a unique combination of economic importance, and ecological prominence. The study included valuable insights by conducting semi-structured interviews with resource operators and local officials. The thorough analysis of socio-economic data, farmer surveys, and satellite-derived information was carried out utilizing quantitative approaches in Excel and SPSS. Simultaneously, qualitative data was subjected to rigorous classification and correlation with other sources. The use of ArcGIS and CorelDraw facilitated the visual representation of the gradual changes seen in various land cover classifications. The research reveals complex processes that characterize mangrove ecosystems on Manoka and Cape Cameroon Islands. The lack of regulations in urbanization and the continuous growth of infrastructure have led to a significant increase in land conversion, causing negative impacts on natural landscapes and forests. The repeated instances of flooding and coastal erosion have further shaped landscape alterations, fostering the proliferation of water and mudflat areas. The unregulated use of mangrove resources is a significant factor in the degradation of these ecosystems. Activities including the use of wood for smoking and fishing, together with the coastal pollution resulting from the absence of waste collection, have had a significant influence. In addition, forest operators contribute to the degradation of vegetation, hence exacerbating the harmful impact of invasive species on the ecosystem. Strategic interventions are necessary to guarantee the sustainable management of these ecosystems. The proposals include advocating for sustainable wood exploitation techniques, using appropriate techniques, along with regeneration, and enforcing rules to prevent wood overexploitation. By implementing these measures, the ecological balance can be preserved, safeguarding the long-term viability of these precious ecosystems. On a conceptual level, this paper uses the framework developed by Elinor Ostrom and her colleagues to investigate the consequences of open access resources, where local actors have not been able to enforce measures to prevent overexploitation of mangrove wood resources. Governmental authorities have demonstrated limited capacity to enforce sustainable management of wood resources and have not been able to establish effective relationships with local fishing communities and with communities involved in the purchase of wood. As a result, wood resources in the mangrove areas remain largely accessible, while authorities do not monitor wood volumes extracted nor methods of exploitation. There have only been limited and punctual attempts at forest restoration with no significant consequence on mangrove forests dynamics.

Keywords: Mangroves, forest management, governance, open access resources, Cameroon

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26972 Mobile Learning: Toward Better Understanding of Compression Techniques

Authors: Farouk Lawan Gambo

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Data compression shrinks files into fewer bits then their original presentation. It has more advantage on internet because the smaller a file, the faster it can be transferred but learning most of the concepts in data compression are abstract in nature therefore making them difficult to digest by some students (Engineers in particular). To determine the best approach toward learning data compression technique, this paper first study the learning preference of engineering students who tend to have strong active, sensing, visual and sequential learning preferences, the paper also study the advantage that mobility of learning have experienced; Learning at the point of interest, efficiency, connection, and many more. A survey is carried out with some reasonable number of students, through random sampling to see whether considering the learning preference and advantages in mobility of learning will give a promising improvement over the traditional way of learning. Evidence from data analysis using Ms-Excel as a point of concern for error-free findings shows that there is significance different in the students after using learning content provided on smart phone, also the result of the findings presented in, bar charts and pie charts interpret that mobile learning has to be promising feature of learning.

Keywords: data analysis, compression techniques, learning content, traditional learning approach

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26971 Water Body Detection and Estimation from Landsat Satellite Images Using Deep Learning

Authors: M. Devaki, K. B. Jayanthi

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The identification of water bodies from satellite images has recently received a great deal of attention. Different methods have been developed to distinguish water bodies from various satellite images that vary in terms of time and space. Urban water identification issues body manifests in numerous applications with a great deal of certainty. There has been a sharp rise in the usage of satellite images to map natural resources, including urban water bodies and forests, during the past several years. This is because water and forest resources depend on each other so heavily that ongoing monitoring of both is essential to their sustainable management. The relevant elements from satellite pictures have been chosen using a variety of techniques, including machine learning. Then, a convolution neural network (CNN) architecture is created that can identify a superpixel as either one of two classes, one that includes water or doesn't from input data in a complex metropolitan scene. The deep learning technique, CNN, has advanced tremendously in a variety of visual-related tasks. CNN can improve classification performance by reducing the spectral-spatial regularities of the input data and extracting deep features hierarchically from raw pictures. Calculate the water body using the satellite image's resolution. Experimental results demonstrate that the suggested method outperformed conventional approaches in terms of water extraction accuracy from remote-sensing images, with an average overall accuracy of 97%.

Keywords: water body, Deep learning, satellite images, convolution neural network

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26970 A Comparative Evaluation of Stone Spout Management Systems in Heritage and Non-heritage Areas of the Kathmandu Valley, Nepal

Authors: Mira Tripathi, Ken Hughey, Hamish G. Rennie

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Management of water resources is a major challenge throughout the world and in many long-established societies people still use traditional water harvesting and management techniques. Despite often being seen as efficient and cost effective, traditional methods are in decline or have been abandoned in many countries. Nevertheless, traditional approaches continue to be useful in some countries such as Nepal. The extent to which such traditional measures, in this case via stone spouts, may survive modernization, while fulfilling socio-cultural, tourism, and other needs is the focus of the research. The research develops an understanding of the socio-cultural, tourism and other values of stone spouts for the people of urban and peri-urban heritage and non-heritage areas of the Kathmandu Valley to help ongoing sustainable management of remaining spouts. Three research questions are addressed: the impacts of changes in social and cultural norms and values; development activities; and, the incremental and ongoing loss of traditional stone spout infrastructure. A meta-theory framework has been developed which synthesizes Institutional, Attachment, Central Place and Common Property theories, which form analytical lenses for the mixed-method research approach. From the exploration of the meta-theory approach, it was found that no spouts are in pristine condition but those in non-heritage areas are in better condition than those in heritage areas. “Utility value” is the main driver that still motivates people to conserve spouts.

Keywords: stone spouts, social and cultural norms and values, meta-theory, Kathmandu Valley

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26969 Sponsorship Strategy, Its Visibility, and Return: A Case Study on Brazilian Olympic Games

Authors: Elizabeth F. Rodrigues, Julia da R. Mattos, Naira Q. Leitão, Roberta T. da Cunha

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The business strategy of many companies has two factors in common: the search for the competitive edge and its long term maintenance. The thing that differentiates the companies’ performance in their abilities to set the right strategy, which depends on their capacity to analyze and apply all sort of management support tools. In this context, the sponsorship of events stands out as an important way to increase brand awareness, especially when it is a worldwide event, such as Rio 2016 Olympic and Paralympic Games. This paper will present the case of a car maker company, which chose to invest on sponsorship as a way to reach its goals and grow in the brazilian market.

Keywords: strategy, sponsorship, events, management

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26968 Human Immunodeficiency Virus (HIV) Test Predictive Modeling and Identify Determinants of HIV Testing for People with Age above Fourteen Years in Ethiopia Using Data Mining Techniques: EDHS 2011

Authors: S. Abera, T. Gidey, W. Terefe

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Introduction: Testing for HIV is the key entry point to HIV prevention, treatment, and care and support services. Hence, predictive data mining techniques can greatly benefit to analyze and discover new patterns from huge datasets like that of EDHS 2011 data. Objectives: The objective of this study is to build a predictive modeling for HIV testing and identify determinants of HIV testing for adults with age above fourteen years using data mining techniques. Methods: Cross-Industry Standard Process for Data Mining (CRISP-DM) was used to predict the model for HIV testing and explore association rules between HIV testing and the selected attributes among adult Ethiopians. Decision tree, Naïve-Bayes, logistic regression and artificial neural networks of data mining techniques were used to build the predictive models. Results: The target dataset contained 30,625 study participants; of which 16, 515 (53.9%) were women. Nearly two-fifth; 17,719 (58%), have never been tested for HIV while the rest 12,906 (42%) had been tested. Ethiopians with higher wealth index, higher educational level, belonging 20 to 29 years old, having no stigmatizing attitude towards HIV positive person, urban residents, having HIV related knowledge, information about family planning on mass media and knowing a place where to get testing for HIV showed an increased patterns with respect to HIV testing. Conclusion and Recommendation: Public health interventions should consider the identified determinants to promote people to get testing for HIV.

Keywords: data mining, HIV, testing, ethiopia

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26967 The Impact of Brand Hate and Love: A Thematic Analysis of Online Emotions in Response to Disney’s Corporate Activism

Authors: Roxana D. Maiorescu-Murphy

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Companies have recently embraced political activism as an alleged responsibility toward the communities they operate in. As a result of its recency, there is little understanding of the impact of corporate activism on consumers. In addition, embracing corporate activism engenders polarizing opinions, potentially leading to a crisis of morality shown in past literature to flourish in online settings. The present study contributes to the literature on communication management, which currently lacks research on stakeholder perceptions toward corporate activism in general and from the perspective of the stakeholders’ emotions of brand hate versus a love that they display before a specific corporate act of activism. For this purpose, the study analyzed online reactions on Twitter following Disney’s stance against Florida’s House Bill 1577 enacted in April 2022. Dubbed the “Don’t Say Gay Bill” by the left wing and the “Parental Rights Bill” by the conservative movement, the legislation triggered polarizing opinions in society and among Disney’s stakeholders, as the company announce it was taking action against it. Given the scarcity of research on corporate political activism and crises of morality, the current study enacted the case study methodology. Consequently, it answered to the research questions of how online stakeholders responded to Disney’s stance as well as why they formed such an opinion. The data were collected from Twitter over a seven-day period of analysis, namely from March 28- April 3, 2022. The period of analysis started on the day Disney announced its stance (March 28, 2022) until the reactions to its announcement petered out significantly (April 3, 2022). The final sample of analysis consisted of N=1,344 and represented Twitter comments in response to the company’s political announcement. The data were analyzed using the grounded theory methodology, which implied multiple exposures to the text and the undertaking of an inductive-deductive approach that led to the emergence of several recurrent themes. The findings revealed that the stakeholders’ prior emotions toward the company (brand hate versus brand love) did not play a greater role in their (dis)agreement with the latter’s activism than the users’ political stances. Specifically, whether they despised or hated Disney prior to this incident was less significant than their personal political stances. Above all, users were more inclined to transition from brand love to brand hate and vice versa based on the political side they viewed Disney to fall under.

Keywords: corporate political advocacy, crisis management, brand hate, brand love

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26966 Predicting the Impact of Scope Changes on Project Cost and Schedule Using Machine Learning Techniques

Authors: Soheila Sadeghi

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In the dynamic landscape of project management, scope changes are an inevitable reality that can significantly impact project performance. These changes, whether initiated by stakeholders, external factors, or internal project dynamics, can lead to cost overruns and schedule delays. Accurately predicting the consequences of these changes is crucial for effective project control and informed decision-making. This study aims to develop predictive models to estimate the impact of scope changes on project cost and schedule using machine learning techniques. The research utilizes a comprehensive dataset containing detailed information on project tasks, including the Work Breakdown Structure (WBS), task type, productivity rate, estimated cost, actual cost, duration, task dependencies, scope change magnitude, and scope change timing. Multiple machine learning models are developed and evaluated to predict the impact of scope changes on project cost and schedule. These models include Linear Regression, Decision Tree, Ridge Regression, Random Forest, Gradient Boosting, and XGBoost. The dataset is split into training and testing sets, and the models are trained using the preprocessed data. Cross-validation techniques are employed to assess the robustness and generalization ability of the models. The performance of the models is evaluated using metrics such as Mean Squared Error (MSE) and R-squared. Residual plots are generated to assess the goodness of fit and identify any patterns or outliers. Hyperparameter tuning is performed to optimize the XGBoost model and improve its predictive accuracy. The feature importance analysis reveals the relative significance of different project attributes in predicting the impact on cost and schedule. Key factors such as productivity rate, scope change magnitude, task dependencies, estimated cost, actual cost, duration, and specific WBS elements are identified as influential predictors. The study highlights the importance of considering both cost and schedule implications when managing scope changes. The developed predictive models provide project managers with a data-driven tool to proactively assess the potential impact of scope changes on project cost and schedule. By leveraging these insights, project managers can make informed decisions, optimize resource allocation, and develop effective mitigation strategies. The findings of this research contribute to improved project planning, risk management, and overall project success.

Keywords: cost impact, machine learning, predictive modeling, schedule impact, scope changes

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26965 Campaigns of Youth Empowerment and Unemployment In Development Discourses: In the Case of Ethiopia

Authors: Fentie, Belay, Mulat

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In today’s high decrement figure of the global economy, nations are facing many economic, social and political challenges; universally, there is high distress of food and other survival insecurity. Further, as a result of conflict, natural disasters, and leadership influences, youths are existentially less empowered and unemployed, especially in developing countries. With this situation to handle well challenges, it’s important to search, investigate and deliberate about youth, unemployment, empowerment and possible management fashions, as youths have the potential to carry and fight such battles. The method adopted is a qualitative analysis of secondary data sources in youth empowerment, unemployment and development as an inclusive framework. Youth unemployment is a major development headache for most African countries. In Ethiopia, following weak youth empowerment, youth unemployment has increased from time to time, and quality education and organization linkage matter as an important constraint. As a management challenge, although accessibility of quality education for Ethiopian youths is an important constraint, the country's youths are fortified deceptively and harassed in a vicious political challenge in their struggle to fetch social and economic changes in the country. Further, thousands of youths are inactivated, criminalized and lost their lives and this makes youths hopeless anger in their lives and pushes them further to be exposed for addictions, prostitution, violence, and illegitimate migrations. This youth challenge wasn’t only destined for African countries; rather, indeed, it was a global burden and headed as a global agenda. As a resolution, the construction of a healthy education system can create independent youths who acquire success and accelerate development. Developing countries should ensue development in the cultivation of empowerment tools through long and short-term education, implementing policy in action, diminishing wide-ranging gaps of (religion, ethnicity & region), and take high youth population as an opportunity and empower them. Further managing and empowering youths to be involved in decision-making, giving political weight and building a network of organizations to easily access job opportunities are important suggestions to save youths in work, for both increasing their income and the country's food security balance.

Keywords: development, Ethiopia, management, unemployment, youth empowerment

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26964 Assessing Flood Risk and Mapping Inundation Zones in the Kelantan River Basin: A Hydrodynamic Modeling Approach

Authors: Fatemehsadat Mortazavizadeh, Amin Dehghani, Majid Mirzaei, Nurulhuda Binti Mohammad Ramli, Adnan Dehghani

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Flood is Malaysia's most common and serious natural disaster. Kelantan River Basin is a tropical basin that experiences a rainy season during North-East Monsoon from November to March. It is also one of the hardest hit areas in Peninsular Malaysia during the heavy monsoon rainfall. Considering the consequences of the flood events, it is essential to develop the flood inundation map as part of the mitigation approach. In this study, the delineation of flood inundation zone in the area of Kelantan River basin using a hydrodynamic model is done by HEC-RAS, QGIS and ArcMap. The streamflow data has been generated with the weather generator based on the observation data. Then, the data is statistically analyzed with the Extreme Value (EV1) method for 2-, 5-, 25-, 50- and 100-year return periods. The minimum depth, maximum depth, mean depth, and the standard deviation of all the scenarios, including the OBS, are observed and analyzed. Based on the results, generally, the value of the data increases with the return period for all the scenarios. However, there are certain scenarios that have different results, which not all the data obtained are increasing with the return period. Besides, OBS data resulted in the middle range within Scenario 1 to Scenario 40.

Keywords: flood inundation, kelantan river basin, hydrodynamic model, extreme value analysis

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26963 Application of Hyperspectral Remote Sensing in Sambhar Salt Lake, A Ramsar Site of Rajasthan, India

Authors: Rajashree Naik, Laxmi Kant Sharma

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Sambhar lake is the largest inland Salt Lake of India, declared as a Ramsar site on 23 March 1990. Due to high salinity and alkalinity condition its biodiversity richness is contributed by haloalkaliphilic flora and fauna along with the diverse land cover including waterbody, wetland, salt crust, saline soil, vegetation, scrub land and barren land which welcome large number of flamingos and other migratory birds for winter harboring. But with the gradual increase in the irrational salt extraction activities, the ecological diversity is at stake. There is an urgent need to assess the ecosystem. Advanced technology like remote sensing and GIS has enabled to look into the past, compare with the present for the future planning and management of the natural resources in a judicious way. This paper is a research work intended to present a vegetation in typical inland lake environment of Sambhar wetland using satellite data of NASA’s EO-1 Hyperion sensor launched in November 2000. With the spectral range of 0.4 to 2.5 micrometer at approximately 10nm spectral resolution with 242 bands 30m spatial resolution and 705km orbit was used to produce a vegetation map for a portion of the wetland. The vegetation map was tested for classification accuracy with a pre-existing detailed GIS wetland vegetation database. Though the accuracy varied greatly for different classes the algal communities were successfully identified which are the major sources of food for flamingo. The results from this study have practical implications for uses of spaceborne hyperspectral image data that are now becoming available. Practical limitations of using these satellite data for wetland vegetation mapping include inadequate spatial resolution, complexity of image processing procedures, and lack of stereo viewing.

Keywords: Algal community, NASA’s EO-1 Hyperion, salt-tolerant species, wetland vegetation mapping

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26962 Incident Management System: An Essential Tool for Oil Spill Response

Authors: Ali Heyder Alatas, D. Xin, L. Nai Ming

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An oil spill emergency can vary in size and complexity, subject to factors such as volume and characteristics of spilled oil, incident location, impacted sensitivities and resources required. A major incident typically involves numerous stakeholders; these include the responsible party, response organisations, government authorities across multiple jurisdictions, local communities, and a spectrum of technical experts. An incident management team will encounter numerous challenges. Factors such as limited access to location, adverse weather, poor communication, and lack of pre-identified resources can impede a response; delays caused by an inefficient response can exacerbate impacts caused to the wider environment, socio-economic and cultural resources. It is essential that all parties work based on defined roles, responsibilities and authority, and ensure the availability of sufficient resources. To promote steadfast coordination and overcome the challenges highlighted, an Incident Management System (IMS) offers an essential tool for oil spill response. It provides clarity in command and control, improves communication and coordination, facilitates the cooperation between stakeholders, and integrates resources committed. Following the preceding discussion, a comprehensive review of existing literature serves to illustrate the application of IMS in oil spill response to overcome common challenges faced in a major-scaled incident. With a primary audience comprising practitioners in mind, this study will discuss key principles of incident management which enables an effective response, along with pitfalls and challenges, particularly, the tension between government and industry; case studies will be used to frame learning and issues consolidated from previous research, and provide the context to link practice with theory. It will also feature the industry approach to incident management which was further crystallized as part of a review by the Joint Industry Project (JIP) established in the wake of the Macondo well control incident. The authors posit that a common IMS which can be adopted across the industry not only enhances response capacity towards a major oil spill incident but is essential to the global preparedness effort.

Keywords: command and control, incident management system, oil spill response, response organisation

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26961 Counterfeit Product Detection Using Block Chain

Authors: Sharanya C. H., Pragathi M., Vathsala R. S., Theja K. V., Yashaswini S.

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Identifying counterfeit products have become increasingly important in the product manufacturing industries in recent decades. This current ongoing product issue of counterfeiting has an impact on company sales and profits. To address the aforementioned issue, a functional blockchain technology was implemented, which effectively prevents the product from being counterfeited. By utilizing the blockchain technology, consumers are no longer required to rely on third parties to determine the authenticity of the product being purchased. Blockchain is a distributed database that stores data records known as blocks and several databases known as chains across various networks. Counterfeit products are identified using a QR code reader, and the product's QR code is linked to the blockchain management system. It compares the unique code obtained from the customer to the stored unique code to determine whether or not the product is original.

Keywords: blockchain, ethereum, QR code

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26960 The Use of Network Tool for Brain Signal Data Analysis: A Case Study with Blind and Sighted Individuals

Authors: Cleiton Pons Ferreira, Diana Francisca Adamatti

Abstract:

Advancements in computers technology have allowed to obtain information for research in biology and neuroscience. In order to transform the data from these surveys, networks have long been used to represent important biological processes, changing the use of this tools from purely illustrative and didactic to more analytic, even including interaction analysis and hypothesis formulation. Many studies have involved this application, but not directly for interpretation of data obtained from brain functions, asking for new perspectives of development in neuroinformatics using existent models of tools already disseminated by the bioinformatics. This study includes an analysis of neurological data through electroencephalogram (EEG) signals, using the Cytoscape, an open source software tool for visualizing complex networks in biological databases. The data were obtained from a comparative case study developed in a research from the University of Rio Grande (FURG), using the EEG signals from a Brain Computer Interface (BCI) with 32 eletrodes prepared in the brain of a blind and a sighted individuals during the execution of an activity that stimulated the spatial ability. This study intends to present results that lead to better ways for use and adapt techniques that support the data treatment of brain signals for elevate the understanding and learning in neuroscience.

Keywords: neuroinformatics, bioinformatics, network tools, brain mapping

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26959 A Case Study: Community Forestry in Nepal: Achievements and Challenges

Authors: Bhmika Raiu

Abstract:

The community forestry programme in Nepal officially started in the late 1970s. Since then concerning movement has been evolving to involve local communities in the management and utilization of forests. The policy of the government was originally intended to meet the basic forest products required by the communities through active participation in forest development and management. Later, it was expanded to include the mobilization and empowerment of the members of community forest user groups in the development of their local communities. It was observed that the trend of forest degradation has decreased since the handing over of national forests to local communities, but a number of unintended social anomalies have also cropped up. Such anomalies essentially constitute of the inequity and unfairness in the local and national level and in terms of long-term sustainability of forest resources. This paper provides an overview of various issues of community forestry, especially focusing on the major achievements made in community forestry. It calls for rethinking the community forestry programme in order to face the present day challenges of linking community forestry with livelihood promotion, good governance, and sustainable forest management. It also lays out strategies for reforms in community forestry.

Keywords: community forest, livelihood promotion, challenges, achievements

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26958 Modeling Floodplain Vegetation Response to Groundwater Variability Using ArcSWAT Hydrological Model, Moderate Resolution Imaging Spectroradiometer - Normalised Difference Vegetation Index Data, and Machine Learning

Authors: Newton Muhury, Armando A. Apan, Tek Maraseni

Abstract:

This study modelled the relationships between vegetation response and available water below the soil surface using the Terra’s Moderate Resolution Imaging Spectroradiometer (MODIS) generated Normalised Difference Vegetation Index (NDVI) and soil water content (SWC) data. The Soil & Water Assessment Tool (SWAT) interface known as ArcSWAT was used in ArcGIS for the groundwater analysis. The SWAT model was calibrated and validated in SWAT-CUP software using 10 years (2001-2010) of monthly streamflow data. The average Nash-Sutcliffe Efficiency during the calibration and validation was 0.54 and 0.51, respectively, indicating that the model performances were good. Twenty years (2001-2020) of monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) and soil water content for 43 sub-basins were analysed using the WEKA, machine learning tool with a selection of two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The modelling results show that different types of vegetation response and soil water content vary in the dry and wet season. For example, the model generated high positive relationships (r=0.76, 0.73, and 0.81) between the measured and predicted NDVI values of all vegetation in the study area against the groundwater flow (GW), soil water content (SWC), and the combination of these two variables, respectively, during the dry season. However, these relationships were reduced by 36.8% (r=0.48) and 13.6% (r=0.63) against GW and SWC, respectively, in the wet season. On the other hand, the model predicted a moderate positive relationship (r=0.63) between shrub vegetation type and soil water content during the dry season, which was reduced by 31.7% (r=0.43) during the wet season. Our models also predicted that vegetation in the top location (upper part) of the sub-basin is highly responsive to GW and SWC (r=0.78, and 0.70) during the dry season. The results of this study indicate the study region is suitable for seasonal crop production in dry season. Moreover, the results predicted that the growth of vegetation in the top-point location is highly dependent on groundwater flow in both dry and wet seasons, and any instability or long-term drought can negatively affect these floodplain vegetation communities. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

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26957 Aerodynamic Modeling Using Flight Data at High Angle of Attack

Authors: Rakesh Kumar, A. K. Ghosh

Abstract:

The paper presents the modeling of linear and nonlinear longitudinal aerodynamics using real flight data of Hansa-3 aircraft gathered at low and high angles of attack. The Neural-Gauss-Newton (NGN) method has been applied to model the linear and nonlinear longitudinal dynamics and estimate parameters from flight data. Unsteady aerodynamics due to flow separation at high angles of attack near stall has been included in the aerodynamic model using Kirchhoff’s quasi-steady stall model. NGN method is an algorithm that utilizes Feed Forward Neural Network (FFNN) and Gauss-Newton optimization to estimate the parameters and it does not require any a priori postulation of mathematical model or solving of equations of motion. NGN method was validated on real flight data generated at moderate angles of attack before application to the data at high angles of attack. The estimates obtained from compatible flight data using NGN method were validated by comparing with wind tunnel values and the maximum likelihood estimates. Validation was also carried out by comparing the response of measured motion variables with the response generated by using estimates a different control input. Next, NGN method was applied to real flight data generated by executing a well-designed quasi-steady stall maneuver. The results obtained in terms of stall characteristics and aerodynamic parameters were encouraging and reasonably accurate to establish NGN as a method for modeling nonlinear aerodynamics from real flight data at high angles of attack.

Keywords: parameter estimation, NGN method, linear and nonlinear, aerodynamic modeling

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26956 Big Data’s Mechanistic View of Human Behavior May Displace Traditional Library Missions That Empower Users

Authors: Gabriel Gomez

Abstract:

The very concept of information seeking behavior, and the means by which librarians teach users to gain information, that is information literacy, are at the heart of how libraries deliver information, but big data will forever change human interaction with information and the way such behavior is both studied and taught. Just as importantly, big data will orient the study of behavior towards commercial ends because of a tendency towards instrumentalist views of human behavior, something one might also call a trend towards behaviorism. This oral presentation seeks to explore how the impact of big data on understandings of human behavior might impact a library information science (LIS) view of human behavior and information literacy, and what this might mean for social justice aims and concomitant community action normally at the center of librarianship. The methodology employed here is a non-empirical examination of current understandings of LIS in regards to social justice alongside an examination of the benefits and dangers foreseen with the growth of big data analysis. The rise of big data within the ever-changing information environment encapsulates a shift to a more mechanistic view of human behavior, one that can easily encompass information seeking behavior and information use. As commercial aims displace the important political and ethical aims that are often central to the missions espoused by libraries and the social sciences, the very altruism and power relations found in LIS are at risk. In this oral presentation, an examination of the social justice impulses of librarians regarding power and information demonstrates how such impulses can be challenged by big data, particularly as librarians understand user behavior and promote information literacy. The creeping behaviorist impulse inherent in the emphasis big data places on specific solutions, that is answers to question that ask how, as opposed to larger questions that hint at an understanding of why people learn or use information threaten library information science ideals. Together with the commercial nature of most big data, this existential threat can harm the social justice nature of librarianship.

Keywords: big data, library information science, behaviorism, librarianship

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26955 Data Collection with Bounded-Sized Messages in Wireless Sensor Networks

Authors: Min Kyung An

Abstract:

In this paper, we study the data collection problem in Wireless Sensor Networks (WSNs) adopting the two interference models: The graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR). The main issue of the problem is to compute schedules with the minimum number of timeslots, that is, to compute the minimum latency schedules, such that data from every node can be collected without any collision or interference to a sink node. While existing works studied the problem with unit-sized and unbounded-sized message models, we investigate the problem with the bounded-sized message model, and introduce a constant factor approximation algorithm. To the best known of our knowledge, our result is the first result of the data collection problem with bounded-sized model in both interference models.

Keywords: data collection, collision-free, interference-free, physical interference model, SINR, approximation, bounded-sized message model, wireless sensor networks

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26954 Collective Bargaining Agreement with Its Related Factors and Employees’ Perceived Productivity: The Case of an Academic Institution in Davao City, Philippines

Authors: Amylyn F. Labasano, M. S. Econ

Abstract:

The study predicts the impact of collective bargaining agreement and its related factors on employees’ perceived productivity in terms of union-management relation’s climate, income, fringe benefits, and job satisfaction of the employees. It also determines whether there are significant differences in the employees’ perceived productivity based on the demographic characteristics of the respondents. The results revealed that the relationship climate which exists between the union and the management is found to have significant adverse effect on the average unpaid hours spent by employees working within the college. On the other hand, the total monthly wage earnings of employees have negative effect on the average hours an employee spent in bringing his work home while job satisfaction positively influences the overall productivity level of employees. The result further shows significant differences in the productivity level of employees across civil status and current designation.

Keywords: perceived productivity, collective bargaining agreement, union, union-management relations climate, income, fringe benefits, job satisfaction

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26953 The Twin Terminal of Pedestrian Trajectory Based on City Intelligent Model (CIM) 4.0

Authors: Chen Xi, Lao Xuerui, Li Junjie, Jiang Yike, Wang Hanwei, Zeng Zihao

Abstract:

To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behaviour recognition models, to provide empirical data such as 'pedestrian flow data and human behavioural characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, convolutional neural network

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26952 Unlocking the Potential of Neglected Cereal Resources Waste: Exploring Functional Properties of Algerian Pearl Millet Starch via Wet Milling and Ultrasound Techniques

Authors: Sarra Bouhallel, Sara Legbedj, Rima Messaoud, Sofia Saffarbatti

Abstract:

In the context of global waste management and sustainable resource utilization, millets emerge as a vital yet underutilized cereal resource. Despite their exceptional nutritional profile and resilience to harsh environmental conditions, their potential remains largely untapped. This study aims to contribute to the valorization of seven Algerian pearl millet landraces (Pennisetum glaucum (L.) R. Br) from the southern region by focusing on the characterization of their starches. Utilizing both conventional wet milling, incorporating sodium azide as a microbial growth inhibitor, and a novel green technology—Ultrasound-assisted isolation, we explore avenues for enhancing the functional properties of these starches. Analysis of key functional properties such as swelling power and water solubility index reveals significant enhancements, particularly during heat treatment near the gelatinization temperature [70 - 80 °C]. Furthermore, our investigation into the influence of pre-treatment methods on isolated starches highlights the potential of Ultrasound-assisted isolation in reducing absorbency and water solubility compared to conventional methods. Through rigorous data analysis using SPSS software (Version 23), we ascertain the efficiency of Ultrasound-assisted isolation, underscoring its promising role in the valorization of pearl millet waste. This research not only sheds light on the functional properties of pearl millet starch but also underscores the imperative of sustainable waste management in harnessing the full potential of underutilized cereal resources.

Keywords: isolation, solubility, starch, swelling, ultrasound

Procedia PDF Downloads 56