580 research outputs found
An Estimate of Forest Biomass in Ayer Hitam Forest Reserve
From an inventory conducted in Ayer Hitam Forest (AHFR), the average dbh ranged from 20.6 to 26.0 cm while
the basal area ranged from 9.16 to 21.57 m2/ha. Modified biomass regression equation was used in the biomass
estimation. The biomass density for trees of 10 cm dbh and above in all the compartments in AHFR ranged from
83.69 to 232.39 t/ha. The total biomass in the 1248 ha of AHFR is estimated at 223,568 t. Variations in
biomass density among the compartments indicate the different stages of recovery or different stages of succession.
Biomass information was used to estimate other parameters such as carbon content and energy content. The
estimated carbon content is 111,784 t while the energy content is 3.74 x 1012 kJ. The estimated annual carbon
accumulation ranges from 0.30 to 0.50 t/ha/yr while the energy fixed ranges from 1.00 x 107 to 1.67 x 107 kJ/
ha/yr. Forest also plays an important role in carbon cycle and energy production. Biomass is the organic matter
fixed by the tree and is the source of all other productivity of the forest
An approach to improving the power management system in electronic devices
Thesis (S.M. in System Design and Management)--Massachusetts Institute of Technology, Engineering Systems Division, 2010.Page 100 blank. Cataloged from PDF version of thesis.Includes bibliographical references (p. 98-99).The current power management technology baseline does not address the increasing gap between system charge performance and functionality needs in a smartphone. This gap can eventually inhibit further increases in functionality and develop a balancing loop effect that reduces smartphone growth rates. Longer smartphone operation duration between recharging is currently being addressed with the introduction of low power circuit chips, low power displays and power management software. This thesis explores options that improve overall power management by looking at the power source and recharging methods. This thesis also explores technology transitions and management strategies that address the different multi-mode interactions between technology transitions.by Jui Min Lim.S.M.in System Design and Managemen
Achieving competitive advantage through supply chain agility under uncertainty:A novel multi-criteria decision-making structure
Sustainable supply chain management in stakeholders:supporting from sustainable supply and process management in the healthcare industry in Vietnam
© 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group. Prior studies presented the sustainable supply chain management practices, but an approach from stakeholders is still untapped. The interaction between forward and reverse flows also needs to be involved in investment recovery. Sustainable supply chain management is an increasing concern in the environmental, social and economic performance. This study uses fuzzy Delphi method to validate a set of criteria and uses exploratory factor analysis to confirm the aspects. This study applies stakeholder theory in combination with fuzzy set theory and decision-making trial and evaluation method to explore the interrelationships among attributes. The results show that sustainable supply management and process management are the major cause aspects. Investment recovery has not been noticed in the healthcare industry, reflected in the weak interaction. The top five criteria are supplier assessment, environmental management systems, green certification of supplier, supplier collaboration and health and safety certifications. This study provides theoretical and managerial implications
Toward Sustainability:Using Big Data to Explore Decisive Supply Chain Risk Factors Under Uncertainty
Rapid market changes aimed at sustainability have led to supply chain risks and uncertainties in the Taiwanese light-emitting diode industry. These risks and uncertainties can be captured by social media, quantitative and qualitative data (referred to herein as big data), but the industry has been unable to manage this information boom to respond to customer needs. These various types of data have their own characteristics that affect decision making about developing firm capabilities. This study aggregates the various data to undertake an extensive investigation of supply chain risks and uncertainties. Specifically, this study proposes using the fuzzy and grey Delphi methods to identify a set of reliable attributes and, based on these attributes, transforming big data to a manageable scale to consider their impacts. Subsequently, both the fuzzy and grey Decision Making Trial and Evaluation Laboratories applied to determine the causal relationships for supply chain risks and uncertainties. The results reveal that capacity and operations have greater influence than other supply chain attributes and that risks stemming from triggering events are difficult to diagnose and control. The implications, conclusions and findings are addressed
Horizontal and vertical emissions of carbon dioxide and methane from a tropical peat soil cultivated with pineapple (Ananas comosus L) Merr.)
Peat soils have been developed for large scale plantations such as oil palm due to their positive contribution to Malaysia’s economic growth in agriculture sector. However, these developments contribute to the emissions of greenhouse gases (GHGs) mainly carbon (CO2) and methane (CH4). To date, there were limited information of GHGs emissions from pineapple cultivation and also inadequate data on horizontally and vertically soil GHGs emissions in peat soil profile. Thus, this study was carried out to determine carbon CO2 and CH4 emissions horizontally and vertically from a drained tropical peat soils from a drained tropical peat soils cultivated with pineapple (Ananas comosus (L.) Merr. Horizontal and vertical movements of CO2 and CH4 were measured from a drained tropical peatland with Ananas comosus (L.) Merr. Tropical peat soils cultivated with Ananas comosus (L.) Merr. contributed to 79.7 % of CO2, and 0.2 % of CH4 based on the yearly basis regardless of the differences in diurnal transportation; horizontal and vertical emission. Soil CO2 and CH4 were emitted the most through horizontal transportation with 70.84 % CO2, and 0.19 % CH4 compared to 8.85 % CO2, and 0.02 % CH4 in vertical transportation. The emission of CO2 was influenced by depth of water table and temperature. It is generally believed that lowering of peats water table leads to emission of higher CO2 emission because this process leads to exposure of peat soils to oxidation. Seasonal variation in CH4 flux was higher in the wet seasons due to rainfall; this might have increased the water table of the peat soil. The results suggest that CO2 and CH4 emissions occur both horizontally and vertically regardless of season. Therefore in order not to underestimate CO2 and CH4 emissions from peat soil, it is important to measure the emissions of this greenhouse gas which has been implicated in environmental pollution horizontally and vertically
Assessing a hierarchical sustainable solid waste management structure with qualitative information:policy and regulations drive social impacts and stakeholder participation
This study contributes to building a valid hierarchical sustainable solid waste management (SSWM) attribute set with qualitative information, which is a complicated and ambiguous problem with uncertainties. Few studies have provided qualitative information and have addressed the interrelationships and interdependencies among the hierarchical SSWM attributes. SSWM has recently become a difficult problem to solve due to urbanization, inequality, and economic growth. This study aims to propose an SSWM attribute set and identify a causal model through linguistic preferences by using a fuzzy decision-making trial and evaluation laboratory approach to simultaneously handle the uncertainty and the interrelationships. The analytic network process is used to develop the hierarchical structure to weigh the aspects and criteria. Qualitative information is transformed into crisp and comparable values to examine the causal relationships between attributes and confirm the consistency between the theoretical structure and industry phenomena. The results indicate that policy and regulations, stakeholder participation, and social impacts play essential roles in these causal interrelationships. Political leadership in SSWM is required to drive stakeholder participation and achieve social impacts. Population growth and migration, institutional settings, waste recycling and energy recovery, households, and private contractors are the main aspects involved in improving SSWM in Vietnam
A Hybrid Approach to Explore the Risk Dependency Structure among Agribusiness Firms
Although the risk management of agricultural firms is important, studies on the extreme risk dependence among agribusiness firms are minimal due to the diversity and complexity of the risks faced by agricultural firms. In this study, we developed a hybrid approach to analyse and uncover the potential risk dependence among agricultural firms. We examined thirty-two agricultural companies to study their dependence structure for risk losses. Three primary findings emerged. First, risk dependence is strong with an average value of 0.96. Second, the dependence structure is hierarchical and includes two network communities. Third, some key agricultural firms were identified in the dependence structure. These key firms are critical for the transmission of negative impacts across agricultural firms. Correspondingly, we suggest measures and strategies (such as improving the level of technological innovation and joint risk resistance capability) to reduce the impact of risk dependence
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