Index-based Approach Research Articles

Public institutions\u2019 capacities regarding climate change adaptation and risk management support in agriculture: the case of Punjab Province, Pakistan

Public institutions could play an important role in building agricultural resilience to climate change by providing information and technology support to farmers. This study takes the case of Pakistan to investigate the perspective and capacities of public institutions as well as to identify gaps in current institutional arrangements in dealing and managing climate change in the agriculture sector. For this purpose, 53 office bearers from thirteen public institutions in Punjab province of Pakistan were interviewed using a semi-structured questionnaire to collect data on climate knowledge, training, coordination, and resource availability. The study uses an index-based approach to calculate Institutional Capacity Indices (ICI) based on selected seven indicators. The results of the index analysis show that institutions have the least financial capacity, followed by lacking physical and human resources. Whereas results show high index value for perception and knowledge, indicating a good understanding of climate change at the institutional level. The overall ICI index value indicates a medium level capacity of institutions in dealing with climate change. Moreover, the study shows that gaps in management, non-availability of financial and physical resources, and lack of training are the key bottlenecks for limited adaptation support from public institutions. This study highlights the importance of reducing gaps so that institutions could play their role in building the resilience of the agriculture sector to climate change.

Measuring education sector resilience in the face of flood disasters in Pakistan: an index-based approach.

School resilience is characterized as risk management techniques to build a safe environment for students. Recognizing the need of building disaster resilience for the education sector, this study is aimed at assessing flood disaster resilience of elementary schools in four extremely vulnerable districts of Khyber Pakhtunkhwa province of Pakistan. This paper established the assessment tool by incorporating climate resilience indices and 16 tasks of the Hyogo Framework for action designed for the education sector. It discusses four dimensions: physical conditions of elementary schools, human resources, institutional issues, and external relationships, each with three parameters and five variables. The data were obtained for 60 variables from 20 randomly selected elementary schools. Indicators of resilience were identified, and an index-based approach was used to get the composite values of the four dimensions of resilience. Correlations between the dimensions, components, and indicators were also checked in the current study. Results show that schools in Nowshera, followed by Charsadda, Peshawar, and Dera Ismail Khan, are the most resilient to flood disasters. For all 12 parameters under 4 dimensions, the relative resilience of study districts is the same. The findings further indicated that there is a strong correlation between the pairs of human resources and institutional issues as well as institutional issues and external relationships that can also enhance human resources and external relationships. Furthermore, institutional issues are also correlated with external relationships and human resources, which indicate that there is a triangular relationship among human resources, institutional issues, and external relationships. The findings would encourage policymakers and practitioners to develop an effective plan to improve the resilience of schools using the overall resilience situation. In short, education sector disaster resilience can be achieved by integrated planning and implementation approach. In this respect, disaster managers, public and private education sectors, school staff, students, and parents need to establish synergies to devise a comprehensive plan of action to enhance disaster education.

Soil Salinity Research and Mapping using Remote Sensing GIS

The research study evaluated the soil salinity by using special scientific tools like Remote Sensing and GIS technology, so that proper measurements could be taken for the sustainable agriculture and water management. A study to evaluate an irrigation system in the dry and semi-dry zone of straight Salyan, The study is made on the basis of salinity to evaluate the system. The primary data use for the study was the satellite images. This study employed an index-based approach of using Geographic Information System with field data. The satellite images of four different years was used to examine the effective area. Several combinations of the ratio of signals received in different spectral bands were used for development of this index. Near Infrared and Thermal IR spectral bands proved to be most effective as this combination helped easy detection of salt affected area. The results were confirmed by field research and laboratory analysis. The research will not only RS base for this field measurement also required for verification and correction. Several combinations of the ratio of signals received in different spectral bands were used for development of this index.

A multi-stage multi-criteria hierarchical decision-making approach for sustainable supplier selection

Sustainable supplier selection is known as a crucial objective in supply chains due to its impact on profitability, adorability, flexibility, and agility of the system. This study proposes a new multi-stage hierarchical fuzzy index-based approach with which decision-makers are empowered to select the most sustainable supplier based on sustainability triple bottom line criteria. Besides, a new fuzzy extension for the best-worst method is proposed considering trapezoidal fuzzy membership functions that can cover uncertainty under imprecise environments. This study makes a contribution to the literature of sustainable supply chains in the sense that it facilitates the computational complexity of previous decision-making approaches by collecting the most relevant criteria and a straightforward fuzzy process. Besides, the graded mean integration representation method has been adopted for prioritizing the supplier based on their performance of sustainable development, which enhances the accuracy of selection compared with previous ranking methods. The proposed study can be utilized as a benchmark for sustainability evaluations between suppliers. A real-world case study is resolved to illustrate the superiority and broad application of the proposed model.

Dichotomous impacts on social and environmental sustainability: competitiveness and development levels matter

PurposeWhereas in developed countries, sustainability primarily focuses on environmental topics, in developing countries the issues of poverty, development and equity are equally, if not more, important. The purpose of this paper is to apply measures of social and environmental sustainability to assess sustainable development for the period 2005–2015 across a sample of 94 countries for which relevant data are available. Countries include two groups: developed and developing countries.Design/methodology/approachUsing the index-based approach introduced by the World Economic Forum in its Global Competitiveness Project, a range of indicators are collected for estimating trends in both social and environmental sustainability. For the panel of data identified, a dynamic panel data estimator method is applied to the data set constructed. This paper presents the empirical results identifying key competitiveness factors related to social and environmental sustainability (separately and combining both aspects in a comprehensive sustainability framework).FindingsThis study explores how sustainable competitiveness offers a comprehensive assessment of the inter-related dynamics of the social, the environmental and economic building blocks of sustainable development simultaneously. Performance impacts are found to differ substantially across two groups of countries depending on their development level. This highlights the challenges in shaping and achieving sustainable development goals.Originality/valueTo the best of the authors’ knowledge, this research is novel in examining the intersections between economic competitiveness and environmental and social sustainability addressing an identified research gap. In addition, the paper investigates the most important competitiveness pillars focusing on both strengths and weaknesses in sustainable competitiveness across developed and developing countries.

The relevance of city size to the vulnerability of surrounding rural areas: An empirical study of flooding in Pakistan

Research on the dynamics of vulnerability has to-date either focused on a regional or national scale or assessed the influence of city size on the vulnerability of the city itself. Little attention has been paid to how city size influences the vulnerability of surrounding rural areas—this has been investigated in this study. A conceptual framework—City Size and Rural Vulnerability (SCARV)—is proposed and operationalised in the context of Pakistan. A household survey was conducted to collect 325 samples from the flood-affected rural population surrounding three different sized cities in Punjab Province, Pakistan. Indicators of vulnerability were identified and an index-based approach was used to get the composite values of the three components of vulnerability—namely, exposure, susceptibility and capacity. The composite values were then classified to identify the level of vulnerability of each household. Statistical tests were performed to investigate the differences in vulnerability between the study areas. The results indicate that rural populations surrounding smaller cities are less exposed but more vulnerable compared to rural communities surrounding larger cities. This is largely because rural populations adjoining large cities have better capacities to deal with flood hazards. This points to a need to focus on increasing the coping capacity of small and medium-sized cities and their rural surroundings. Moreover, the research highlights the importance of rural-urban linkages in the hazard vulnerability discourse. These results can help disaster managers, regional and rural development planners, and practitioners to develop relevant flood risk reduction strategies which considers spatial and regional development aspects of hazard vulnerability.

Innovation in the maritime sector: aligning strategy with outcomes

ABSTRACT Innovation is identified as one of the main avenues to maintain competitiveness and its importance is well established in business studies. Along maritime logistics chains, innovation is being increasingly recognized as a determinant of success. However, beyond the naval architecture literature, little attention has been given to the role that innovation plays in maritime business. Notwithstanding the increasing number of innovation efforts that can be traced in the industry, little is known of the processes and mechanisms that make innovation successful, with the result that initiatives are often uncoordinated, unfocused, poorly managed, and do not deliver the expected results. In order to improve innovation processes, better insight is needed into what motivates innovation along maritime supply chains, in particular for ocean carriers, (inland) terminal operators, port managers, and hinterland transport operators. To this end, the paper proposes an index-based approach using data collected for 59 innovation cases to capture the degree of alignment between innovation strategy and outcomes in various maritime logistics business sectors. Substantial misalignment exists between company strategies and innovation success, and efforts should be made to improve the strategic processes that lead to collaborative innovation in maritime supply chains.

Improvements in multi-metric index development using a whole-index approach

Abstract Multi-metric indices (MMIs) are the most common tool used to assess ecological integrity. Traditionally, only the metrics with the highest correlation to disturbance are incorporated. The rationale being that combining the metrics with the strongest individual relationships to disturbance should yield an MMI with the strongest possible relationship to disturbance. An alternative to this traditional metric-based method was proposed, which we term the index-based approach. Under this method, thousands of MMIs are generated through the random selection of candidate metrics and then a model competition framework is adopted to select the best performing MMI. An index-based approach may prove more sensitive to disturbance because even metrics weakly related to disturbance on their own may nonetheless contribute unique and valuable information to the whole MMI. Our goal was to compare the traditional metric-based method with the novel index-based approach to MMI development and validation to ascertain which generates a superior MMI for vegetation-based biomonitoring in prairie pothole wetlands. We sampled vegetation from 72 marshes from across prairie Alberta between 2014 and 2015. These ranged from temporarily- to permanently-ponded marsh classes and spanned a gradient in anthropogenic disturbance. Vegetation surveys yielded 732 initial metrics associated with abundance, richness and traits, 88 of which were reasonably sensitive to disturbance (p

Assessing Socioeconomic Vulnerability after a Hurricane: A Combined Use of an Index-Based approach and Principal Components Analysis

Small Island Developing States (SIDS) are vulnerable to sea-level rise and hydro-meteorological hazards. In addition to the efforts to reduce the hazards, a holistic strategy that also addresses the vulnerability and exposure of residents and their assets is essential to mitigate the impacts of such hazards. Evaluating the socioeconomic vulnerability of SIDS can serve the purpose of identification of the root drivers of risk. In this paper, we present a methodology to assess and map socioeconomic vulnerability at a neighbourhood scale using an index-based approach and principal component analysis (PCA). The index-based vulnerability assessment approach has a modular and hierarchical structure with three components: susceptibility, lack of coping capacities and lack of adaptation, which are further composed of factors and variables. To compute the index, we use census data in combination with data coming from a survey we performed in the aftermath of Irma. PCA is used to screen the variables, to identify the most important variables that drive vulnerability and to cluster neighbourhoods based on the common factors. The methods are applied to the case study of Sint Maarten in the context of the disaster caused by Hurricane Irma in 2017. Applying the combined analysis of index-based approach with PCA allows us to identify the critical neighbourhoods on the island and to identify the main variables or drivers of vulnerability. Results show that the lack of coping capacities is the most influential component of vulnerability in Sint Maarten. From this component, the “immediate action” and the “economic coverage” are the most critical factors. Such analysis also enables decision-makers to focus their (often limited) resources more efficiently and have a more significant impact concerning disaster risk reduction.

Autocorrect on Drugs e-Dictionary Search Module Using Levenshtein Distance Algorithm

The Dictionary of Medicine in the form of a physical book has many drawbacks, one of them is its thickness makes it impractical to be carried. This becomes a motivation to develop drug dictionary applications in the form of a Drugs e-Dictionary. One of the developed Drugs e-Dictionary uses A-Z index-based approach to discover any drug terms. This approach is less effective and less efficient timewise. Therefore, it is necessary to add a search function that has an autocorrect feature to aid the user. The purpose of this study is to build a search module that has an autocorrect feature on Drugs e-Dictionary using the Levenshtein Distance algorithm. The methodology or the stages of this research divided into the construction of a search module on Drugs e-Dictionary, implementation of the Levenshtein Distance algorithm, and autocorrect validation test. The results of the algorithm implementation show that the search module with the autocorrect feature can detect typing errors in the inputted terms by producing the closest drug term output in the database, then automatically provide suggestions for improvement and display the results of the improved drug terms to the user. it reaches 90% accuracy of inputted query, with 90% precision and 90% recall.

Assessment of environmental and social sustainability performance of the freight transportation industry: An index-based approach

The freight transportation activities having an impact on the freight logistics process. The environmental and social sustainability-related processes are poorly managed compared to the economic process. The quality of environmental and social sustainability (EnSoS) practices ought to be enhanced by measuring current sustainability practices, and at the same time, obstacles to sustainability have to be identified. Some of the previous work try to develop a sustainability framework, but less attention is paid to develop the EnSoS assessment framework for the freight transport industry. To bridge this research gap, this study develops an EnSoS framework based on an integrated multi-criteria decision-making (MCDM) method, i.e., fuzzy best-worst method (FBWM) and fuzzy logic approach. The proposed framework evaluates the current sustainability performance with an index and highlights the obstacles to the sustainable freight transportation system. The proposed framework presents two sustainability enablers, nine dimensions, and sixty-three sustainability attributes, including ten new attributes. The FBWM method is used to compute the fuzzy importance weight of attributes, whereas the fuzzy logic is used to assess the performance of each attribute. The proposed framework is validated with the case of the Indian freight industry. The fuzzy transportation EnSoS index (FTEnSoSI) is computed as (3.511, 6.366, 8.418), and close to ‘very environmental and social sustainable (VESS)’ label. The fuzzy performance importance index (FPII) is computed to assess the performance of each attribute. Based on FPII value, thirty attributes are identified as obstacles to transport sustainability. The result analysis presented proposed policy measures for improving EnSoS obstacles.

Weight-Based K-Truss Community Search via Edge Attachment

Community search is the task of discovering dense subgraph that satisfy a set of given query parameters. Most community search algorithms consider link structure while ignoring link weight. A recent study proposed the idea of discovering weighted communities which focuses on both link structure and link weight using an online search approach and index-based approach. In this paper two online algorithms are proposed to scale-up the existing online approach efficiency. Performance evaluation of the proposed algorithms against the existing online approach over different datasets shows a great improvement in terms of search and query evaluation time.

Assessment of Livelihood Vulnerability to Rainfall Variability among Crop Farming Households in Kitui South Sub-County, Kenya

Rainfall variability has negatively impacted rain-fed crop farming in arid and semi-arid lands increasing households’ vulnerability. This study sought to establish the extent to which rain-fed crop farming households in Kitui South sub-County in semi-arid Southeastern Kenya are vulnerable to rainfall variability. The study used index-based approach where Livelihood Vulnerability Index (LVI) for each of the randomly sampled 311 households was calculated using the IPCC framework. Rainfall data for six rainfall seasons for the period 2016-2018 was used to calculate index for exposure while questionnaires were administered to the household heads to establish sensitivity and adaptive capacity indices. Responses from the selected sub-components were assigned index values ranging between zero and one. LVI levels were scored between -1 and +1. The study established that indices for exposure, sensitivity and adaptive capacity were 0.71, 0.09 and 0.19 respectively and that 97.4% of the households in the study area were vulnerable to rainfall variability. The study concludes that households in the study area have different livelihood vulnerability levels to rainfall variability due to differences in their sensitivity and adaptive capacity. The study recommends use of households’ LVI levels in determining appropriate intervention measures to effects of vulnerability to rainfall variability among different farming households in order to avoid generalization.

Lower-limb muscle function is influenced by changing mechanical demands in cycling.

Although cycling is a seemingly simple, reciprocal task, muscles must adapt their function to satisfy changes in mechanical demands induced by higher crank torques and faster pedalling cadences. We examined whether muscle function was sensitive to these changes in mechanical demands across a wide range of pedalling conditions. We collected experimental data of cycling where crank torque and pedalling cadence were independently varied from 13 to 44 N m and 60 to 140 rpm. These data were used in conjunction with musculoskeletal simulations and a recently developed functional index-based approach to characterise the role of human lower-limb muscles. We found that in muscles that generate most of the mechanical power and work during cycling, greater crank torque induced shifts towards greater muscle activation, greater positive muscle-tendon unit (MTU) work and a more motor-like function, particularly in the limb extensors. Conversely, with faster pedalling cadence, the same muscles exhibited a phase advance in muscle activity prior to crank top dead centre, which led to greater negative MTU power and work and shifted the muscles to contract with more spring-like behaviour. Our results illustrate the capacity for muscles to adapt their function to satisfy the mechanical demands of the task, even during highly constrained reciprocal tasks such as cycling. Understanding how muscles shift their contractile performance under varied mechanical and environmental demands may inform decisions on how to optimise pedalling performance and to design targeted cycling rehabilitation therapies for muscle-specific injuries or deficits.

Rapid impact assessment matrix, sustainable analysis and environmental performance index-based approach for selection of wastewater treatment units

Rapid impact assessment matrix, sustainable analysis and environmental performance index-based approach for selection of wastewater treatment units

Rapid impact assessment matrix, sustainable analysis and environmental performance index-based approach for selection of wastewater treatment units

In today's world, engineers and planner are working hard to find the appropriate wastewater treatment technology which is technically feasible, sustainable and along with economical in the long run from available various conventional and advanced treatment technologies. In this study, rapid impact assessment matrix, sustainability analyses and environmental performance index tools used for selection of appropriate the wastewater treatment technology from available activated sludge process, up-flow anaerobic sludge blanket reactor and waste stabilisation pond in India. A questionnaire for the survey consists of physical/chemical, biological/ecological, social/cultural and economical/operational aspects. The survey responses are analysed by rapid impact assessment matrix methods to quantify in terms of an environmental score. Environmental performance index of the options, i.e., activated sludge process, up-flow anaerobic sludge blanket reactor and waste stabilisation pond are 38.775, 94.267 and 27.15, respectively. The analysis results revealed that the up-flow anaerobic sludge blanket reactor is an appropriate and feasible option.

Gender-based approach for assessing risk perception in a multi-hazard environment: A study of high schools of Gilgit, Pakistan

Risk perception is a vital constituent of disaster risk. It is a measure to assess predisposition of individuals to seek disaster preparedness measures. Understanding gendered risk perception in a multi-hazard environment is important for launching proper disaster risk reduction strategies. This study proposes a risk perception assessment methodology, and is operationalized in context of high school students in a multi-hazard area of Gilgit, Pakistan. Risk perception was measured using four components, i.e., fear, attitude, awareness and trust. Indicators were identified using rigorous literature review, and index-based approach was used to calculate overall risk perception. Slovin's sampling method was used to identify sample size of 486 high school students, including 248 boys and 238 girls. Data was collected through structured questionnaires. Chi-square and t-tests were employed to ascertain differences between the two genders. Results have shown poor risk perception of high school students regarding natural hazards. Among the measured risk perception indicators, the fear component received the highest score. The study also observed significant differences in the risk perception indicators. This study highlights that for better understanding of the multifaceted nature of disaster risk, the gender aspect must be incorporated in risk perception assessment.

The mirage water concept and an index-based approach to quantify causes of hydrological changes in semi-arid regions

ABSTRACTIn semi-arid regions, reduced river flows present is a major challenge in water resources management. We present a new standardized contribution of rainfall to runoff index (SCRI) for evaluating changes in rainfall contribution to river flow. We employ the standardized precipitation index (SPI), standardized discharge index (SDI) and SCRI to characterize meteorological drought, hydrological drought and land-use change impacts on river flow, respectively. These indices are applied to the Mond River Basin (Iran), which is regulated by the Salman Farsi and Tangab dams since 2006. A new concept called “mirage water” is proposed that represents the reduced water delivery to downstream areas due to new developments and water withdrawals in headwater tributaries. In particular, mirage water accounts for changes in upstream water consumption between the planning phase and construction/operation life of dams. We recommend that this concept be used for communication with decision-makers and managers to clarify the need for revising dimensions of planned dams.

Susceptibility of Garden Trees and Shrubs to Armillaria Root Rot.

Armillaria root rot (ARR) is a serious disease of woody plants caused by several species of Armillaria. Armillaria isolates from diagnostic samples received in 2017 were identified by genus- and species-specific PCR and compared with isolates from an earlier survey (2004 to 2007). The results were comparable and, therefore, were combined for further analysis. Three species were identified: Armillaria mellea (83%), A. gallica (15%), and A. ostoyae (2%). Their wide host range makes choice of resistant plants in management of the disease difficult. We used the Royal Horticultural Society diagnostic dataset of ARR records from U.K. gardens to compare the susceptibility of different host genera to the disease. The dataset was compared with an earlier experiment at the University of California. An index-based approach was used to separate genera into three categories: 77 low-index (<0.99), 37 medium-index (0.99 to 1.76), and 56 high-index (>1.76) genera were recorded. All three species were associated with both angiosperms and gymnosperms; moreover, A. ostoyae did not show the host preference for gymnosperms that has been reported elsewhere. A. gallica was particularly common on herbaceous perennials and showed a trend to occur on resistant hosts that may be under other stress, supporting its description as an opportunistic pathogen. Four monocotyledons grown as trees or shrubs in U.K. gardens had a very low ARR index according to indices associated with A. mellea and A. ostoyae. Genera in the order Myrtales were almost always low index, while those in the Saxifragales and Fagales were mostly high index. These results provide confidence in the use of host resistance as part of the integrated management of ARR.

An index-based approach to determine partnership in a register-based census

An index-based approach to determine partnership in a register-based census