Search results for: healthcare data security

Authors: Hoyeon Park, Yunhwan Keon, Kyoung-Jae Kim

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Location Based Social Network services (LBSNs) is a new term that combines location based service and social network service (SNS). Unlike traditional SNS, LBSNs emphasizes empirical elements in the user's actual physical location. Point-of-Interest (POI) is the most important factor to implement LBSNs recommendation system. POI information is the most popular spot in the area. In this study, we would like to recommend POI to users in a specific area through recommendation system using collaborative filtering. The process is as follows: first, we will use different data sets based on Seoul and New York to find interesting results on human behavior. Secondly, based on the location-based activity information obtained from the personalized LBSNs, we have devised a new rating that defines the user's preference for the area. Finally, we have developed an automated rating algorithm from massive raw data using distributed systems to reduce advertising costs of LBSNs.

Keywords: location-based social network services, point-of-interest, recommender systems, business analytics

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Authors: Elizabeth M. Seabrook, Nikki S. Rickard

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Examining time-dependent measures of emotion such as variability, instability, and inertia, provide critical and complementary insights into mental health status. Observing changes in the pattern of emotional expression over time could act as a tool to identify meaningful shifts between psychological well- and ill-being. From a practical standpoint, however, examining emotion dynamics day-to-day is likely to be burdensome and invasive. Utilizing social media data as a facet of lived experience can provide real-world, temporally specific access to emotional expression. Emotional language on social media may provide accurate and sensitive insights into individual and community mental health and well-being, particularly with focus placed on the within-person dynamics of online emotion expression. The objective of the current study was to examine the dynamics of emotional expression on the social network platform Facebook for active users and their relationship with psychological well- and ill-being. It was expected that greater positive and negative emotion variability, instability, and inertia would be associated with poorer psychological well-being and greater depression symptoms. Data were collected using a smartphone app, MoodPrism, which delivered demographic questionnaires, psychological inventories assessing depression symptoms and psychological well-being, and collected the Status Updates of consenting participants. MoodPrism also delivered an experience sampling methodology where participants completed items assessing positive affect, negative affect, and arousal, daily for a 30-day period. The number of positive and negative words in posts was extracted and automatically collated by MoodPrism. The relative proportion of positive and negative words from the total words written in posts was then calculated. Preliminary analyses have been conducted with the data of 9 participants. While these analyses are underpowered due to sample size, they have revealed trends that greater variability in the emotion valence expressed in posts is positively associated with greater depression symptoms (r(9) = .56, p = .12), as is greater instability in emotion valence (r(9) = .58, p = .099). Full data analysis utilizing time-series techniques to explore the Facebook data set will be presented at the conference. Identifying the features of emotion dynamics (variability, instability, inertia) that are relevant to mental health in social media emotional expression is a fundamental step in creating automated screening tools for mental health that are temporally sensitive, unobtrusive, and accurate. The current findings show how monitoring basic social network characteristics over time can provide greater depth in predicting risk and changes in depression and positive well-being.

Keywords: emotion, experience sampling methods, mental health, social media

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Authors: Abera Kotu, Girma Tesema, Mitiku Tadesse

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This study investigated ACE supported instruction and pre-service mathematics teachers’ mental construction in solving equations and inequalities. A mixed approach with concurrent parallel design was employed. It was conducted on two intact groups of regular first-year pre-service mathematics teachers at Fiche College of Teachers’ Education in which one group was assigned as an intervention group and the other group as a comparison group using the lottery method. There were 33 participants in the intervention and 32 participants in the comparison. Six pre-service mathematics teachers were selected for interview using purposive sampling based on pre-test results. An instruction supported with ACE cycle was given to the intervention group for two weeks duration of time. Written tasks, interviews, and observations were used to collect data. Data collected from written tasks were analyzed quantitatively using independent samples t-test and effect size. Data collected from interviews and observations were analyzed narratively. The findings of the study uncovered that ACE-supported instruction has a moderate effect on Pre-service Mathematics Teachers’ levels of conceptualizations of action, process, object, ad schema. Moreover, the ACE supported group out scored and performed better than the usual traditional method supported groups across the levels of conceptualization. The majority of pre-service mathematics teachers’ levels of conceptualizations were at action and process levels and their levels of conceptualization were linked with genetic decomposition more at action and object levels than object and schema. The use of ACE supported instruction is recommended to improve pre-service mathematics teachers’ mental construction.

Keywords: ACE teaching cycle, APOS theory, mental construction, genetic composition

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Authors: A. A. Akharayi, B. E. Anjola

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The economic development of a country depends greatly on internally built revenue. Small and Medium-scale Enterprise (SMEs) contributes to the economic buoyancy as it provides employment for the teeming population, encourages job creation by youths who believes in themselves and also by others who have gathered finance enough to invest in growable investment. SMEs is faced with several challenges. The study investigates the role and challenges of SMEs Somolu Local Government Area. Simple random sampling techniques were used to select entrepreneurs (SMEs owners and managers). One hundred and fifty (150) registered SMEs were selected across the LGA data collection with the use of well-structured questionnaire. The data collected were analysed using Statistical Package for Social Science (SPSS) version 21. The result of the analysis indicated that marketing, finance, social facilities and indiscriminate taxes among other high level of fund available significantly (p <0 .05) increase firm capacity while marketing showed a significant (p < 0.05) relationship with profit level.

Keywords: challenge, development, economic, small and medium scale enterprise

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Authors: Luisa Müting, Wisnu Harto Adiwijoyo

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Agroforestry systems transform the agricultural landscapes in the Sahel region of Africa, providing food and farming products consumed for subsistence or sold for income. In the incrementally dry climate of the Sahel region, the spreading of agroforestry practices is integral for policymaker efforts to counteract land degradation and provide soil restoration in the region. Several measures on agroforestry practices have been implemented in the region by governmental and non-governmental institutions in recent years. However, despite the efforts, past research shows that awareness of how policies and interventions are being consumed and perceived by the public remains low. Therefore, interpreting public policy dilemmas by analyzing the public perception regarding agroforestry concepts and practices is necessary. Public perceptions and discourses can be an essential driver or constraint for the adoption of agroforestry practices in the region. Thus, understanding the public discourse behavior of crucial stakeholders could assist policymakers in developing inclusive and contextual policies that are relevant to the context of agroforestry adoption in Sahel region. To answer how information about agroforestry spreads and is perceived by the public. As internet usage increased drastically over the past decade, reaching a share of 33 percent of the population being connected to the internet, this research is based on online conversation data. Social media data from Facebook are gathered daily between April 2021 and April 2022 in Djibouti, Senegal, Mali, and Nigeria based on their share of active internet users compared to other countries in the Sahel region. A systematic methodology was applied to the extracted social media using discourse network analysis (DNA). This study then clustered the data by the types of agroforestry practices, sentiments, and country. Additionally, this research extracted the text data from online news media during the same period to pinpoint events related to the topic of agroforestry. The preliminary result indicates that tree management, crops, and livestock integration, diversifying species and genetic resources, and focusing on interactions and productivity across the agricultural system; are the most notable keywords in agroforestry-related conversations within the four countries in the Sahel region. Additionally, approximately 84 percent of the discussions were still dominated by big actors, such as NGO or government actors. Furthermore, as a subject of communication within agroforestry discourse, the Great Green Wall initiative generates almost 60 percent positive sentiment within the captured social media data, effectively having a more significant outreach than general agroforestry topics. This study provides an understanding for scholars and policymakers with a springboard for further research or policy design on agroforestry in the four countries of the Sahel region with systematically uncaptured novel data from the internet.

Keywords: sahel, djibouti, senegal, mali, nigeria, social networks analysis, public discourse analysis, sentiment analysis, content analysis, social media, online news, agroforestry, land restoration

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Authors: Jonathan K. Hill

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The transportation networks throughout Africa remain the only transportation infrastructure system in the world that is attacked by terrorists at a high frequency, so the international community can learn from each attack. The targeting of transportation should be recognized as a direct attack against a civilian population, so the international community should work to better understand the types of attacks utilized, the types of improvised explosive device designs adapted to transportation targets, and the ways the various modes of transportation have been attacked throughout the continent. Some countries have seen grenade attacks that have resulted in only injuries, while some countries have experienced large vehicle bombings that have resulted in hundreds of injuries and numerous deaths. With insurgencies, explosive devices have been small, complex, and generally target an enemy of the insurgency. With terrorist bombings, the explosive devices have been large, brazen, and targeted at civilian populations. And, these civilian populations are easily targeted within the transportation system. The presentation provided by Assess Africa LLC is titled ‘Evolution of Bombings Against Transportation Infrastructure’ and covers improvised explosive device characteristics, how improvised explosive devices have been adapted to transportation targets in Africa, analyses recent incidents, and provides some advice for effective protective measures. A main component of the improvised explosive device characteristics portion of the presentation focuses on the link between explosive device components, the intelligence network, and the bomb-builder’s network. By understanding the components, how the use of various components can be linked to a terrorist group’s capabilities, and how the bomb-builder acquires materials, the analysis of improvised explosive device attacks takes on a new direction – one that focuses on defeating the network instead of merely reviewing incidents of the past.

Keywords: Africa, bombings, critical infrastructure protection, transportation security

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Authors: Fariea Bakul, Chhanda Karmaker

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The present study was designed to investigate the effects of parental bonding on adult’s cognitive emotion regulation and also to investigate gender differences in parental bonding and cognitive emotion regulation. Data were collected by using convenience sampling technique from 100 adult students (50 males and 50 females) of different universities of Dhaka city, ages between 20 to 25 years, using Bengali version of Parental Bonding Inventory and Bengali version of Cognitive Emotion Regulation Questionnaire. The obtained data were analyzed by using multiple regression analysis and independent samples t-test. The results revealed that fathers care (β =0.317, p < 0.05) was only significantly positively associated with adult’s cognitive emotion regulation. Adjusted R² indicated that the model explained 30% of the variance in adult’s adaptive cognitive emotion regulation. No significant association was found between parental bonding and less adaptive cognitive emotion regulations. Results from independent samples t-test also revealed that there was no significant gender difference in both parental bonding and cognitive emotion regulations.

Keywords: cognitive emotion regulation, parental bonding, parental care, parental over-protection

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Authors: Humraaz Kaja, Kofi Mensah, Frasia Oosthuizen

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Background and Aim: Vilazodone was approved in 2011 as an antidepressant to treat the major depressive disorder. As a relatively new drug, it is not clear if all adverse effects have been identified. The aim of this study was to review the adverse effects reported to the WHO Programme for International Drug Monitoring (PIDM) in order to add to the knowledge about the safety profile and adverse effects caused by vilazodone. Method: Data on adverse effects reported for vilazodone was obtained from the database VigiAccess managed by PIDM. Data was extracted from VigiAccess using Excel® and analyzed using descriptive statistics. The data collected was compared to the patient information leaflet (PIL) of Viibryd® and the FDA documents to determine adverse drug reactions reported post-marketing. Results: A total of 9708 adverse events had been recorded on VigiAccess, of which 6054 were not recorded on the PIL and the FDA approval document. Most of the reports were received from the Americas and were for adult women aged 45-64 years (24%, n=1059). The highest number of adverse events reported were for psychiatric events (19%; n=1889), followed by gastro-intestinal effects (18%; n=1839). Specific psychiatric disorders recorded included anxiety (316), depression (208), hallucination (168) and agitation (142). The systematic review confirmed several psychiatric adverse effects associated with the use of vilazodone. The findings of this study suggested that these common psychiatric adverse effects associated with the use of vilazodone were not known during the time of FDA approval of the drug and is not currently recorded in the patient information leaflet (PIL). Conclusions: In summary, this study found several adverse drug reactions not recorded in documents emanating from clinical trials pre-marketing. This highlights the importance of continued post-marketing surveillance of a drug, as well as the need for further studies on the psychiatric adverse events associated with vilazodone in order to improve the safety profile.

Keywords: adverse drug reactions, pharmacovigilance, post-marketing surveillance, vilazodone

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Authors: S. M. Kulkarni, D. S. Bormane, S. L. Nalbalwar

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The rapid development in the technology have dramatic impact on the medical health care field. Medical data base obtained with latest machines like CT Machine, MRI scanner requires large amount of memory storage and also it requires large bandwidth for transmission of data in telemedicine applications. Thus, there is need for video compression. As the database of medical images contain number of frames (slices), hence while coding of these images there is need of motion estimation. Motion estimation finds out movement of objects in an image sequence and gets motion vectors which represents estimated motion of object in the frame. In order to reduce temporal redundancy between successive frames of video sequence, motion compensation is preformed. In this paper three step search (TSS) block matching algorithm is implemented on different types of video sequences. It is shown that three step search algorithm produces better quality performance and less computational time compared with exhaustive full search algorithm.

Keywords: block matching, exhaustive search motion estimation, three step search, video compression

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Authors: Aslina Asnawi, A. Amidah Amrawaty, Nirwana

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This article examines the relationship of local culture on the ability to access finance on beef cattle farmer. The local culture in this study associated with the values held by the farmer community so far and affect the character of farmers both in his personal life and his relationship with the surrounding environment. The data was collected by using interview and questionnaire instrument. Data were analyzed using descriptive analysis and correlation analysis. The result show that local culture identified in this study include: honesty, cleverness, decency, firmness, hard work, and shame. It’s important result that local culture has been associated with the ability to access financing for beef cattle farmers. The higher values are adopted and maintained by farmers will increase their ability to obtain loans from both informal and formal institutions. Strengthening the local culture is important because it affects the character of farmers who became one of the considerations for lenders other than collateral, capacity and capital is precisely the financing constraints for them.

Keywords: access funding, beef cattle farmers, character, local culture

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Authors: Meghry Nazarian, Ibrahim Duyar

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Effective management of a diverse workforce in the United Arab Emirates (UAE) presents peculiar importance as two-thirds of residents are expatriates who have diverse ethnic and cultural backgrounds. Like any other organization in the country, UAE schools have become upmost diverse settings in the world. The purpose of this study was to examine whether principals’ cultural intelligence has direct and indirect (moderating) influences on teachers’ perceived diversity climate. A quantitative causal-comparative research design was employed to analyze the data. Participants included random samples of principals and teachers working in the private and charter schools in the Emirate of Abu Dhabi. The data-gathering online questionnaires included previously developed and validated scales as the measures of study variables. More specifically, the multidimensional short-form measure of Cultural Intelligence (CQ) and the diversity climate scale were used to measure the study variables. Multivariate statistics, including the analysis of multivariate analysis of variance (MANCOVA) and structural equation modeling (SEM), were employed to examine the relationships between the study variables. The preliminary analyses of data showed that principals and teachers have differing views of diversity management and climate in schools. Findings also showed that principals’ cultural intelligence has both direct and moderating influences on teachers’ perceived diversity climate. The study findings are expected to inform policymakers and practicing educational leaders in addressing diversity management in a country where the majority of the residents are the minority who have diverse ethnic and cultural backgrounds.

Keywords: diversity management, united arab emirates, school principals’ cultural intelligence (CQ), teachers’ perceived diversity climate

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Authors: Pius Babuna

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Sustainable water use is important for the existence of the human race. Water resources carrying capacity (WRCC) measures the sustainability of water use; however, the calculation and optimization of WRCC remain challenging. This study used a mathematical model (the Logistics Growth of Water Resources -LGWR) and a linear objective function to model water sustainability. We tested the validity of the models using data from Ghana. Total freshwater resources, water withdrawal, and population data were used in MATLAB. The results show that the WRCC remains sustainable until the year 2132 ±18, when half of the total annual water resources will be used. The optimized water treatment cost suggests that Ghana currently wastes GHȼ 1115.782± 50 cedis (~$182.21± 50) per water treatment plant per month or ~ 0.67 million gallons of water in an avoidable loss. Adopting an optimized water treatment scheme and a watershed management approach will help sustain the WRCC.

Keywords: water resources carrying capacity, smart water management, optimization, sustainable water use, water withdrawal

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Authors: Berhanu Keno Terfa

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Flash floods are among the most dangerous natural disasters that pose a significant threat to human existence. They occur frequently and can cause extensive damage to homes, infrastructure, and ecosystems while also claiming lives. Although flash floods can happen anywhere in the world, their impact is particularly severe in developing countries due to limited financial resources, inadequate drainage systems, substandard housing options, lack of early warning systems, and insufficient preparedness. To address these challenges, a comprehensive study has been undertaken to analyze and map flood inundation using Geographic Information System (GIS) techniques by considering various factors that contribute to flash flood resilience and developing effective mitigation strategies. Key factors considered in the analysis include slope, drainage density, elevation, Curve Number, rainfall patterns, land-use/cover classes, and soil data. These variables were computed using ArcGIS software platforms, and data from the Sentinel-2 satellite image (with a 10-meter resolution) were utilized for land-use/cover classification. Additionally, slope, elevation, and drainage density data were generated from the 12.5-meter resolution of the ALOS Palsar DEM, while other relevant data were obtained from the Ethiopian Meteorological Institute. By integrating and regularizing the collected data through GIS and employing the analytic hierarchy process (AHP) technique, the study successfully delineated flash flood hazard zones (FFHs) and generated a suitable land map for urban agriculture. The FFH model identified four levels of risk in Bishoftu City: very high (2106.4 ha), high (10464.4 ha), moderate (1444.44 ha), and low (0.52 ha), accounting for 15.02%, 74.7%, 10.1%, and 0.004% of the total area, respectively. The results underscore the vulnerability of many residential areas in Bishoftu City, particularly the central areas that have been previously developed. Accurate spatial representation of flood-prone areas and potential agricultural zones is crucial for designing effective flood mitigation and agricultural production plans. The findings of this study emphasize the importance of flood risk mapping in raising public awareness, demonstrating vulnerability, strengthening financial resilience, protecting the environment, and informing policy decisions. Given the susceptibility of Bishoftu City to flash floods, it is recommended that the municipality prioritize urban agriculture adaptation, proper settlement planning, and drainage network design.

Keywords: remote sensing, flush flood hazards, Bishoftu, GIS.

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Authors: Rajish Shil, Mohammad Ali Houri, Mohammad Milad Ismail, Fatimah Al Kaabi

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The clinical presentation of Primary hyperparathyroidism can vary from simple asymptomatic hypercalcemia to severe life-threatening hypercalcemic crisis with multi-organ dysfunction, which can be due to parathyroid adenoma or sometimes with malignant cancer. This cascade of clinical presentation can lead to a diagnostic and therapeutic challenge for treating the disease. We are presenting a case of severe hypercalcemic crisis due to parathyroid adenoma with an emphasis on early management, diagnosis, and interventions to prevent any lifelong complications and any permanent organ dysfunction. A 30 years old female with a history of primary Infertility, admitted to Al Ain Hospital critical care unit with Acute Severe Necrotizing Pancreatitis. She initially had a 1-month history of abdominal pain on and off, for which she was treated conservatively with no much improvement, and later on, she developed life-threatening severe pancreatitis, which required her to be admitted to the critical care unit. She was transferred from a private healthcare facility, where she was found to have a very high level of calcium up to 15mmol/L. She received systemic Zoledronic Acid, which lowered her calcium level transiently and later was increased again. She went on to develop multiple end-organ damages along with multiple electrolytes disturbances. She was found to have high levels of Parathyroid hormone, which was correlated with a parathyroid mass on the neck via radiological imaging. After a long course of medical treatment to lower the calcium to a near-normal level, parathyroidectomy was done, which showed parathyroid adenoma on histology. She developed hungry bone syndrome after the surgery and pancreatic pseudocyst after resolving of pancreatitis. She required aggressive treatment with Intravenous calcium for her hypocalcemia as she received zoledronic acid at the beginning of the disease. Later on, she was discharged on long term calcium and other electrolytes supplements. In patients presenting with hypercalcemia, it is prudent to investigate and start treatment early to prevent complications and end-organ damage from hypercalcemia and also to treat the primary cause of the hypercalcemia, with conscious follow up to prevent hypocalcemic complications after treatment. It is important to follow up patients with parathyroid adenomas for a long period in order to detect any recurrence of the tumor or to make sure if the primary tumor is either benign or malignant.

Keywords: hypercalcemia, pancreatitis, hypocalcemia, hyperparathyroidism

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Authors: Alejandra Torres-Landa López

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Introduction: Can architecture students be creative in spaces conformed by an educational infrastructure build with paradigms of the past?, this question and others related are answered in this paper as it presents the PhD research: An anthropic conflict in Mexican Higher Education Institutes, problems and challenges of the educational infrastructure in teaching and learning History of Architecture. This research was finished in 2013 and is one of the first studies conducted nationwide in Mexico that analysis the educational infrastructure impact in learning architecture; its objective was to identify which elements of the educational infrastructure of Mexican Higher Education Institutes where architects are formed, hinder or contribute to the teaching and learning of History of Architecture; how and why it happens. The methodology: A mixed methodology was used combining quantitative and qualitative analysis. Different resources and strategies for data collection were used, such as questionnaires for students and teachers, interviews to architecture research experts, direct observations in Architecture classes, among others; the data collected was analyses using SPSS and MAXQDA. The veracity of the quantitative data was supported by the Cronbach’s Alpha Coefficient, obtaining a 0.86, figure that gives the data enough support. All the above enabled to certify the anthropic conflict in which Mexican Universities are. Major findings of the study: Although some of findings were probably not unknown, they haven’t been systematized and analyzed with the depth to which it’s done in this research. So, it can be said, that the educational infrastructure of most of the Higher Education Institutes studied, is a barrier to the educational process, some of the reasons are: the little morphological variation of space, the inadequate control of lighting, noise, temperature, equipment and furniture, the poor or none accessibility for disable people; as well as the absence, obsolescence and / or insufficiency of information technologies are some of the issues that generate an anthropic conflict understanding it as the trouble that teachers and students have to relate between them, in order to achieve significant learning). It is clear that most of the educational infrastructure of Mexican Higher Education Institutes is anchored to paradigms of the past; it seems that they respond to the previous era of industrialization. The results confirm that the educational infrastructure of Mexican Higher Education Institutes where architects are formed, is perceived as a "closed container" of people and data; infrastructure that becomes a barrier to teaching and learning process. Conclusion: The research results show it's time to change the paradigm in which we conceive the educational infrastructure, it’s time to stop seen it just only as classrooms, workshops, laboratories and libraries, as it must be seen from a constructive, urban, architectural and human point of view, taking into account their different dimensions: physical, technological, documental, social, among others; so the educational infrastructure can become a set of elements that organize and create spaces where ideas and thoughts can be shared; to be a social catalyst where people can interact between each other and with the space itself.

Keywords: educational infrastructure, impact of space in learning architecture outcomes, learning environments, teaching architecture, learning architecture

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Authors: O. Benturki, A. Benturki

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Activated carbon was prepared from Jujube seeds by chemical activation with potassium hydroxide (KOH), followed by pyrolysis at 800°C. Batch studies were conducted for kinetic, thermodynamic and equilibrium studies on the adsorption of phenol (P) and 2-4 dichlorophenol (2-4 DCP) from aqueous solution, than the adsorption capacities followed the order of 2-4 dichlorophenol > phenol. The operating variables studied were initial phenols concentration, contact time, temperature and solution pH. Results show that the pH value of 7 is favorable for the adsorption of phenols. The sorption data have been analyzed using Langmuir and Freundlich isotherms. The isotherm data followed Langmuir Model. The adsorption processes conformed to the pseudo-second-order rate kinetics. Thermodynamic parameters such as enthalpy, entropy and Gibb’s free energy changes were also calculated and it was found that the sorption of phenols by Jujuba seeds activated carbon was a spontaneous process The maximum adsorption efficiency of phenol and 2-4 dichlorophenol was 142.85 mg.g−1 and 250 mg.g−1, respectively.

Keywords: activated carbon, adsorption, isotherms, Jujuba seeds, phenols, langmuir

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Authors: Hyun-Woo Cho

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Continuous monitoring of industrial plants is one of necessary tasks when it comes to ensuring high-quality final products. In terms of monitoring and diagnosis, it is quite critical and important to detect some incipient abnormal events of manufacturing processes in order to improve safety and reliability of operations involved and to reduce related losses. In this work a new multivariate statistical online diagnostic method is presented using a case study. For building some reference models an empirical discriminant model is constructed based on various past operation runs. When a fault is detected on-line, an on-line diagnostic module is initiated. Finally, the status of the current operating conditions is compared with the reference model to make a diagnostic decision. The performance of the presented framework is evaluated using a dataset from complex industrial processes. It has been shown that the proposed diagnostic method outperforms other techniques especially in terms of incipient detection of any faults occurred.

Keywords: data mining, empirical model, on-line diagnostics, process fault, process monitoring

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Authors: Lucas Bublitz, Michael Herdrich

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By achieving the first commercialization approval in San Francisco the Autonomous Driving (AD) industry proves the technology maturity of the SAE L4 AD systems and the corresponding software and hardware stack. This milestone reflects the upcoming phase in the industry, where the focus is now about scaling and supervising larger autonomous vehicle (AV) fleets in different operation areas. This requires an operation framework, which organizes and assigns responsibilities to the relevant AV technology and operation stakeholders from the AV system provider, the Remote Intervention Operator, the MaaS provider and regulatory & approval authority. This holistic operation framework consists of technological, processual, and organizational activities to ensure safe operation for fully automated vehicles. Regarding the supervision of large autonomous vehicle fleets, a major focus is on the continuous field monitoring. The field monitoring approach must reflect the safety and security criticality of incidents in the field during driving operation. This includes an automatic containment approach, with the overall goal to avoid safety critical incidents and reduce downtime by a malfunction of the AD software stack. An End-to-end (E2E) field monitoring approach detects critical faults in the field, uses a knowledge-based approach for evaluating the safety criticality and supports the automatic containment of these E/E faults. Applying such an approach will ensure the scalability of AV fleets, which is determined by the handling of incidents in the field and the continuous regulatory compliance of the technology after enhancing the Operational Design Domain (ODD) or the function scope by Functions on Demand (FoD) over the entire digital product lifecycle.

Keywords: field monitoring, incident management, multicompliance management for AI in AD, root cause analysis, database approach

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Authors: Yi-Lin Chen, Sheng-Jou Hung, Tsunglin Liu

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Adaptive immune system recognizes a wide range of antigens via expressing a large number of structurally distinct T cell and B cell receptor genes. The distinct receptor genes arise from complex rearrangements called V(D)J recombination, and constitute the immune repertoire. A common method of profiling immune repertoire is via amplifying recombined receptor genes using multiple primers and high-throughput sequencing. This multiplex-PCR approach is efficient; however, the resulting repertoire can be distorted because of primer bias. To eliminate primer bias, 5’ RACE is an alternative amplification approach. However, the application of RACE approach is limited by its low efficiency (i.e., the majority of data are non-regular receptor sequences, e.g., containing intronic segments) and lack of the convenient tool for analysis. We propose a computational tool that can correctly identify non-regular receptor sequences in RACE data via aligning receptor sequences against the whole gene instead of only the exon regions as done in all other tools. Using our tool, the remaining regular data allow for an accurate profiling of immune repertoire. In addition, a RACE approach is improved to yield a higher fraction of regular T-cell receptor sequences. Finally, we quantify the degree of primer bias of a multiplex-PCR approach via comparing it to the RACE approach. The results reveal significant differences in frequency of VJ combination by the two approaches. Together, we provide a new experimental and computation pipeline for an unbiased profiling of immune repertoire. As immune repertoire profiling has many applications, e.g., tracing bacterial and viral infection, detection of T cell lymphoma and minimal residual disease, monitoring cancer immunotherapy, etc., our work should benefit scientists who are interested in the applications.

Keywords: immune repertoire, T-cell receptor, 5' RACE, high-throughput sequencing, sequence alignment

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Authors: Bara' Al-Mistarehi

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Documentation and assessment of conservation state of an archaeological structure is a significant procedure in any management plan. However, it has always been a challenge to apply this with a low coast and safe methodology. It is also a time-demanding procedure. Therefore, a low cost, efficient methodology for documenting the state of a structure is needed. In the scope of this research, this paper will employ digital photogrammetry and laser scanner to one of highly significant structures in Germany, The Old Castle (German: Altes Schloss). The site is well known for its unique features. However, the castle suffers from serious deterioration threats because of the environmental conditions and the absence of continuous monitoring, maintenance and repair plans. Digital photogrammetry is a generally accepted technique for the collection of 3D representations of the environment. For this reason, this image-based technique has been extensively used to produce high quality 3D models of heritage sites and historical buildings for documentation and presentation purposes. Additionally, terrestrial laser scanners are used, which directly measure 3D surface coordinates based on the run-time of reflected light pulses. These systems feature high data acquisition rates, good accuracy and high spatial data density. Despite the potential of each single approach, in this research work maximum benefit is to be expected by a combination of data from both digital cameras and terrestrial laser scanners. Within the paper, the usage, application and advantages of the technique will be investigated in terms of building high realistic 3D textured model for some parts of the old castle. The model will be used as diagnosing tool of the conservation state of the castle and monitoring mean for future changes.

Keywords: Digital photogrammetry, Terrestrial laser scanners, 3D textured model, archaeological structure

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Authors: Somaye Ghafarpour, Kamran Yazdanbakhsh, Mohamad Reza Zarbakhsh, Simin Hosseinian, Samira Ghafarpour

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Unsatisfactory sleep quality is one of the most common complications of pregnancy, which can predispose mothers to postpartum depression, requiring implementing effective psychological interventions to prevent and modify behaviors accentuating sleep problems. This study was a randomized clinical controlled trial with a pre-test/post-test design aiming to investigate the effectiveness of sleep behavioral interventions during the third trimester of pregnancy on sleep quality and postpartum depression. A total of 50 pregnant mothers in the 26-30 weeks of pregnancy suffering from sleep problems (based on the score obtained from the Pittsburgh Sleep Questionnaire) were randomized into two groups (control and intervention, n= 25 per group). The data were collected using interviews, the Pittsburgh Sleep Quality Index (PSQI), and the Edinburgh Postnatal Depression Scale (EPDS) were used. The participants in the intervention group received eight 60-minute sessions of combinational training for behavioral therapy techniques. At the end of the intervention and four weeks after delivery, sleep quality and postpartum depression were evaluated. Considering that the Kolmogorov Smirnov test confirmed the normal distribution of the data, the independent t-test and analysis of covariance were used to analyze the data, showing that the behavioral interventions were effective on the overall sleep quality after delivery (p=0.001); however, no statistically significant effects were observed on postpartum depression, the sub-scales of sleep disorders, and daily functioning (p>0.05). Considering the potential effectiveness of behavioral interventions in improving sleep quality and alleviating insomnia symptoms, it is recommended to implement such measures as an effective intervention to prevent or treat these problems during prenatal and postnatal periods.

Keywords: behavioral interventions, sleep quality, postpartum depression, pregnancy, delivery

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Authors: Danlei Yang, Luofeng Huang

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The integration of digital twin technology with renewable energy systems offers an innovative approach to predicting and optimising performance throughout the entire lifecycle. A digital twin is a continuously updated virtual replica of a real-world entity, synchronised with data from its physical counterpart and environment. Many digital twin companies today claim to have mature digital twin products, but their focus is primarily on equipment visualisation. However, the core of a digital twin should be its model, which can mirror, shadow, and thread with the real-world entity, which is still underdeveloped. For a floating solar energy system, a digital twin model can be defined in three aspects: (a) the physical floating solar energy system along with environmental factors such as solar irradiance and wave dynamics, (b) a digital model powered by artificial intelligence (AI) algorithms, and (c) the integration of real system data with the AI-driven model and a user interface. The experimental setup for the floating solar energy system, is designed to replicate real-ocean conditions of floating solar installations within a controlled laboratory environment. The system consists of a water tank that simulates an aquatic surface, where a floating catamaran structure supports a solar panel. The solar simulator is set up in three positions: one directly above and two inclined at a 45° angle in front and behind the solar panel. This arrangement allows the simulation of different sun angles, such as sunrise, midday, and sunset. The solar simulator is positioned 400 mm away from the solar panel to maintain consistent solar irradiance on its surface. Stability for the floating structure is achieved through ropes attached to anchors at the bottom of the tank, which simulates the mooring systems used in real-world floating solar applications. The floating solar energy system's sensor setup includes various devices to monitor environmental and operational parameters. An irradiance sensor measures solar irradiance on the photovoltaic (PV) panel. Temperature sensors monitor ambient air and water temperatures, as well as the PV panel temperature. Wave gauges measure wave height, while load cells capture mooring force. Inclinometers and ultrasonic sensors record heave and pitch amplitudes of the floating system’s motions. An electric load measures the voltage and current output from the solar panel. All sensors collect data simultaneously. Artificial neural network (ANN) algorithms are central to developing the digital model, which processes historical and real-time data, identifies patterns, and predicts the system’s performance in real time. The data collected from various sensors are partly used to train the digital model, with the remaining data reserved for validation and testing. The digital twin model combines the experimental setup with the ANN model, enabling monitoring, analysis, and prediction of the floating solar energy system's operation. The digital model mirrors the functionality of the physical setup, running in sync with the experiment to provide real-time insights and predictions. It provides useful industrial benefits, such as informing maintenance plans as well as design and control strategies for optimal energy efficiency. In long term, this digital twin will help improve overall solar energy yield whilst minimising the operational costs and risks.

Keywords: digital twin, floating solar energy system, experiment setup, artificial intelligence

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Authors: Ivo Zution Goncalves, Christopher M. U. Neale, Hiran Medeiros, Everardo Mantovani, Natalia Souza

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Multispectral and thermal infrared imagery from satellite sensors coupled with climate and soil datasets were used to estimate evapotranspiration and biomass in center pivots planted to maize in Brazil during the 2016 season. The hybrid remote sensing based model named Spatial EvapoTranspiration Modelling Interface (SETMI) was applied using multispectral and thermal infrared imagery from the Landsat Thematic Mapper instrument. Field data collected by the IRRIGER center pivot management company included daily weather information such as maximum and minimum temperature, precipitation, relative humidity for estimating reference evapotranspiration. In addition, soil water content data were obtained every 0.20 m in the soil profile down to 0.60 m depth throughout the season. Early season soil samples were used to obtain water-holding capacity, wilting point, saturated hydraulic conductivity, initial volumetric soil water content, layer thickness, and saturated volumetric water content. Crop canopy development parameters and irrigation application depths were also inputs of the model. The modeling approach is based on the reflectance-based crop coefficient approach contained within the SETMI hybrid ET model using relationships developed in Nebraska. The model was applied to several fields located in Minas Gerais State in Brazil with approximate latitude: -16.630434 and longitude: -47.192876. The model provides estimates of real crop evapotranspiration (ET), crop irrigation requirements and all soil water balance outputs, including biomass estimation using multi-temporal satellite image inputs. An interpolation scheme based on the growing degree-day concept was used to model the periods between satellite inputs, filling the gaps between image dates and obtaining daily data. Actual and accumulated ET, accumulated cold temperature and water stress and crop water requirements estimated by the model were compared with data measured at the experimental fields. Results indicate that the SETMI modeling approach using data assimilation, showed reliable daily ET and crop water requirements for maize, interpolated between remote sensing observations, confirming the applicability of the SETMI model using new relationships developed in Nebraska for estimating mainly ET and water requirements in Brazil under tropical conditions.

Keywords: basal crop coefficient, irrigation, remote sensing, SETMI

Procedia PDF Downloads 146

Authors: Ximena Castillo, Jaime Pizarro

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This research describes the development of a very cheap mesoporous silica material similar to hexagonal mesoporous silica (HMS) and using a silicate extract as precursor. This precursor is obtained from cheap fly ash by an easy calcination process at 850 °C and a green extraction with water. The obtained mesoporous fly ash material had a surface area of 282 m2 g-1 and a pore size of 5.7 nm. It was functionalized with ethylene diamino moieties via the well-known SAMMS method, followed by a DRIFT analysis that clearly showed the successful functionalization. An excellent adsorbent was obtained for the adsorption of sulfate anions by the solid’s modification with copper forming a copper-ethylenediamine complex. The adsorption of sulfates was studied in a batch system ( experimental conditions: pH=8.0; 5 min). The kinetics data were adjusted according to a pseudo-second order model with a high coefficient of linear regression at different initial concentrations. The adsorption isotherm that best fitted the experimental data was the Freundlich model. The maximum sulfate adsorption capacity of this very cheap fly ash based adsorbent was 146.1 mg g-1, 3 times greater than the values reported in literature and commercial adsorbent materials.

Keywords: fly ash, mesoporous materials, SAMMS, sulfate

Procedia PDF Downloads 183

Authors: Rauha Salam

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In Pakistan, over the past decade, the notion of what counts as a true ‘masculine and feminine’ behaviour has become more complicated with the inspection of social media. Given its strong religious and socio-cultural norms, patriarchal values are entrenched in the local and cultural traditions of the Pakistani society and regulate the social value of gender. However, the increasing use of internet among Pakistani men and women, especially in the form of social media uses by the youth, is increasingly becoming disruptive and challenging to the strict modes of behavioural monitoring and control both at familial and state level. Facebook, being the prime social media communication platform in Pakistan, provide its users a relatively ‘safe’ place to embrace how they want to be perceived by their audience. Moreover, the availability of an array of semiotic resources (e.g. the videos, audios, visuals and gifs) on Facebook makes it possible for the users to create a virtual identity that allows them to describe themselves in detail. By making use of Multimodal Discourse Analysis, I aimed to investigate how men and women in Pakistan construct their gendered identities multimodally (visually and linguistically) through their Facebook posts and how these semiotic modes are interconnected to communicate specific meanings. In case of the female data, the analysis showed an ambivalence as females were found to be conforming to the existing socio-cultural norms of the society and they were also employing social media platforms to deviate from traditional gendered patterns and to voice their opinions simultaneously. Similarly, the male data highlighted the reproduction of the prevalent cultural models of masculinity. However, there were instances in the data that showed a digression from the standard norms and there is a (re)negotiation of the traditional patriarchal representations.

Keywords: Facebook, Gendered Identities, Multimodal Discourse Analysis, Pakistan

Procedia PDF Downloads 121

Authors: Dongping Fang, Lian Duan, Xiaojing Yuan, Mike Xu, Allyn Klunder, Kevin Tan, Suiting Cao, Yeqing Ji

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Accurate prediction of a medical condition with straight clinical evidence is a long-sought topic in the medical management and health insurance field. Although great progress has been made with machine learning algorithms, the medical community is still, to a certain degree, suspicious about the model's accuracy and interpretability. This paper presents an innovative hierarchical attention deep learning model to achieve good prediction and clear interpretability that can be easily understood by medical professionals. This deep learning model uses a hierarchical attention structure that matches naturally with the medical history data structure and reflects the member’s encounter (date of service) sequence. The model attention structure consists of 3 levels: (1) attention on the medical code types (diagnosis codes, procedure codes, lab test results, and prescription drugs), (2) attention on the sequential medical encounters within a type, (3) attention on the medical codes within an encounter and type. This model is applied to predict the occurrence of stage 3 chronic kidney disease (CKD3), using three years’ medical history of Medicare Advantage (MA) members from a top health insurance company. The model takes members’ medical events, both claims and electronic medical record (EMR) data, as input, makes a prediction of CKD3 and calculates the contribution from individual events to the predicted outcome. The model outcome can be easily explained with the clinical evidence identified by the model algorithm. Here are examples: Member A had 36 medical encounters in the past three years: multiple office visits, lab tests and medications. The model predicts member A has a high risk of CKD3 with the following well-contributed clinical events - multiple high ‘Creatinine in Serum or Plasma’ tests and multiple low kidneys functioning ‘Glomerular filtration rate’ tests. Among the abnormal lab tests, more recent results contributed more to the prediction. The model also indicates regular office visits, no abnormal findings of medical examinations, and taking proper medications decreased the CKD3 risk. Member B had 104 medical encounters in the past 3 years and was predicted to have a low risk of CKD3, because the model didn’t identify diagnoses, procedures, or medications related to kidney disease, and many lab test results, including ‘Glomerular filtration rate’ were within the normal range. The model accurately predicts members A and B and provides interpretable clinical evidence that is validated by clinicians. Without extra effort, the interpretation is generated directly from the model and presented together with the occurrence date. Our model uses the medical data in its most raw format without any further data aggregation, transformation, or mapping. This greatly simplifies the data preparation process, mitigates the chance for error and eliminates post-modeling work needed for traditional model explanation. To our knowledge, this is the first paper on an interpretable deep-learning model using a 3-level attention structure, sourcing both EMR and claim data, including all 4 types of medical data, on the entire Medicare population of a big insurance company, and more importantly, directly generating model interpretation to support user decision. In the future, we plan to enrich the model input by adding patients’ demographics and information from free-texted physician notes.

Keywords: deep learning, interpretability, attention, big data, medical conditions

Procedia PDF Downloads 95

Authors: Sarono, Hamim Zaky Hadibasyir, dan Ridho Kurniawan

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Estimation of paddy production is one of the areas that can be examined using the techniques of remote sensing and geographic information systems (GIS) in the field of agriculture. The purpose of this research is to know the amount of the paddy production estimation and how remote sensing and geographic information systems (GIS) are able to perform analysis of paddy production estimation in Tegalallang and Payangan Sub district, Bali Province, Indonesia. The method used is the method of land suitability. This method associates a physical parameters which are to be embodied in the smallest unit of a mapping that represents a mapping unit in a particular field and connecting with its field productivity. Analysis of estimated production using standard land suitability from FAO using matching technique. The parameters used to create the land unit is slope (FAO), climate classification (Oldeman), landform (Prapto Suharsono), and soil type. Land use map consist of paddy and non paddy field information obtained from Geo-eye 1 imagery using visual interpretation technique. Landsat image of the Data used for the interpretation of the landform, the classification of the slopes obtained from high point identification with method of interpolation spline, whereas climate data, soil, use secondary data originating from institutions-related institutions. The results of this research indicate Tegallalang and Payangan Districts in known wetland suitability consists of S1 (very suitable) covering an area of 2884,7 ha with the productivity of 5 tons/ha and S2 (suitable) covering an area of 482,9 ha with the productivity of 3 tons/ha. The sum of paddy production estimation as a results in both districts are 31.744, 3 tons in one year.

Keywords: production estimation, paddy, remote sensing, geography information system, land suitability

Procedia PDF Downloads 347

Authors: Anurag Savarnya

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The reliability of the various parts of electric mining shovel has been assessed through the application of Weibull Model. The study was initiated to find reliability of components of electric mining shovel. The paper aims to optimize the reliability of components and increase the life cycle of component. A multilevel decomposition of the electric mining shovel was done and maintenance records were used to evaluate the failure data and appropriate system characterization was done to model the system in terms of reasonable number of components. The approach used develops a mathematical model to assess the reliability of the electric mining shovel components. The model can be used to predict reliability of components of the hydraulic mining shovel and system performance. Reliability is an inherent attribute to a system. When the life-cycle costs of a system are being analyzed, reliability plays an important role as a major driver of these costs and has considerable influence on system performance. It is an iterative process that begins with specification of reliability goals consistent with cost and performance objectives. The data were collected from an Indian open cast coal mine and the reliability of various components of the electric mining shovel has been assessed by following a Weibull Model.

Keywords: reliability, Weibull model, electric mining shovel

Procedia PDF Downloads 517

Authors: F. O. Danquah, F. Frimpong, E. Owusu Danquah, T. Frimpong, J. Adu, S. K. Amposah, P. Amankwaa-Yeboah, N. E. Amengor

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In the face of global concerns such as population increase, climate change, and limited natural resources, sustainable agriculture practices are critical for ensuring food security and environmental stewardship. The study was conducted in the Forest zones of Ghana during the major and minor seasons of 2023 cropping seasons to evaluate maize yield productivity improvement and profitability of integrating Cajanus cajan (pigeonpea) into a maize production system described as a pigeonpea-maize cropping system. This is towards an integrated soil fertility management (ISFM) with a legume shrub pigeonpea for sustainable maize production while improving smallholder farmers' resilience to climate change. A split-plot design with maize-pigeonpea (Pigeonpea-Maize intercrop – MPP and No pigeonpea/ Sole maize – NPP) and inorganic fertilizer rate (250 kg/ha of 15-15-15 N-P2O5-K2O + 250 kg/ha Sulphate of Ammonia (SoA) – Full rate (FR), 125 kg/ha of 15-15-15 N-P2O5-K2O + 125 kg/ha Sulphate of Ammonia (SoA) – Half rate (HR) and no inorganic fertilizer (NF) as control) was used as the main plot and subplot treatments respectively. The results indicated a significant interaction of the pigeonpea-maize cropping system and inorganic fertilizer rate on the growth and yield of the maize with better and similar maize productivity when HR and FR were used with pigeonpea biomass. Thus, the integration of pigeonpea and its biomass would result in the reduction of recommended fertiliser rate to half. This would improve farmers’ income and profitability for sustainable maize production in the face of climate change.

Keywords: agroforestry tree, climate change, integrated soil fertility management, resource use efficiency

Procedia PDF Downloads 63

Authors: Arzyana Sunkar, Yanto Santosa

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The expansions of independent smallholdings in Indonesia are feared to increase the negative ecological impacts of oil palm plantation on biodiversity. Hence, research is required to identify the conservation importance of independent smallholder oil palm plantations on biodiversity. This paper discussed the role of independent smallholdings in the conservation of biodiversity in oil palm plantations and to compare it with High Conservation Value Forest as a conservation standard of RSPO. The research was conducted from March to April 2016. Data on biodiversity were collected on 16 plantations and 8 private oil palm plantations in the Districts of Kampar, Pelalawan, Kuantan, Singingi and Siak of Riau Province, Indonesia. In addition, data on community environmental perceptions of both smallholder plantation and High Conservation Value (HCV) Forest were also collected. Species that were observed were birds and earthworms. Data on birds were collected using transect method, while identification of earthworm was determine by taking some soil samples and counting the number of individual earthworm found for each worm species. The research used direct interview with oil palm owners and community members, as well as direct observation to examine the environmental conditions of each plantation. In general, field observation and measurement have found that birds species richness was higher in the forested HCV Forest. Nevertheless, if compared to non-forested HCV, bird’s species richness was higher in the independent smallholdings. On the other hand, different results were observed for earthworm, where the density was higher in the independent smallholdings than in the HCV. It can be concluded from this research that managing independent smallholder oil palm plantations and forested HCV forest could enhance biodiversity conservation. The results of this study justified the importance of retaining forested area to safeguard biodiversity in oil palm plantation.

Keywords: biodiversity conservation, high conservation value forest, independent smallholdings, oil palm plantations

Procedia PDF Downloads 229