Search results for: MITM bootstrap vulnerability

Authors: Mouad Zouina, Benaceur Outtaj

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The proposed work falls within the context of improving data security for m-commerce systems. In this context we have placed under the light some flaws encountered in HTTPS the most used m-commerce protocol, particularly the man in the middle attack, shortly MITM. The man in the middle attack is an active listening attack. The idea of this attack is to target the handshake phase of the HTTPS protocol which is the transition from a non-secure connection to a secure connection in our case HTTP to HTTPS. This paper proposes a solution to fix those flaws based on the upgrade of HSTS standard handshake sequence using the DNSSEC standard.

Keywords: m-commerce, HTTPS, HSTS, DNSSEC, MITM bootstrap vulnerability

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Authors: Hannah F. Opayinka, Adedayo A. Adepoju

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This study is an extension of a prior study on the modification of the existing m-out-of-n (moon) bootstrap method for heavy-tailed distributions in which modified m-out-of-n (mmoon) was proposed as an alternative method to the existing moon technique. In this study, both moon and mmoon techniques were applied to two real income datasets which followed Lognormal and Pareto distributions respectively with finite variances. The performances of these two techniques were compared using Standard Error (SE) and Root Mean Square Error (RMSE). The findings showed that mmoon outperformed moon bootstrap in terms of smaller SEs and RMSEs for all the sample sizes considered in the two datasets.

Keywords: Bootstrap, income data, lognormal distribution, Pareto distribution

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Authors: Brahim Boukabcha, Amar Rebbouh

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The bootstrap method based on the idea of exploiting all the information provided by the initial sample, allows us to study the properties of estimators. In this article we will present a theoretical study on the different methods of bootstrapping and using the technique of re-sampling in statistics inference to calculate the standard error of means of an estimator and determining a confidence interval for an estimated parameter. We apply these methods tested in the regression models and Pareto model, giving the best approximations.

Keywords: bootstrap, error standard, bias, jackknife, mean, median, variance, confidence interval, regression models

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Authors: Edlira Donefski, Tina Donefski, Lorenc Ekonomi

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Edgeworth Approximation, Bootstrap, and Monte Carlo Simulations have considerable impacts on achieving certain results related to different problems taken into study. In our paper, we have treated a financial case related to the effect that has the components of a cash-flow of one of the most successful businesses in the world, as the financial activity, operational activity, and investment activity to the cash and cash equivalents at the end of the three-months period. To have a better view of this case, we have created a vector autoregression model, and after that, we have generated the impulse responses in the terms of asymptotic analysis (Edgeworth Approximation), Monte Carlo Simulations, and residual bootstrap based on the standard errors of every series created. The generated results consisted of the common tendencies for the three methods applied that consequently verified the advantage of the three methods in the optimization of the model that contains many variants.

Keywords: autoregression, bootstrap, edgeworth expansion, Monte Carlo method

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Authors: Anjli Pathak, Harshit Sosan Lakra, Smriti Mishra

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The increasing urbanization affects the external environment in which people exist and imposes livelihood vulnerability to shocks and stresses. Although research on the linkages between urbanization and vulnerability has been increasing, only a few studies have examined the caste/ethnicity in livelihood vulnerability. In this study, we explore how physical capital influences vulnerability among indigenous people in the context of livelihood. The study identifies the dimensions and indicators of physical capital that influence the profile of household vulnerability in the livelihood-building process. The result identified five dimensions and 19 indicators of livelihood vulnerability. The study also visualizes the inter-relationship between physical capital and other livelihood capital in formulating the livelihood vulnerability framework.

Keywords: urbanization, livelihood vulnerability, indigenous people, physical capital

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Authors: O. Ikpotokin

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In any production process, every product is aimed to attain a certain standard, but the presence of assignable cause of variability affects our process, thereby leading to low quality of product. The ability to identify and remove this type of variability reduces its overall effect, thereby improving the quality of the product. In case of a univariate control chart signal, it is easy to detect the problem and give a solution since it is related to a single quality characteristic. However, the problems involved in the use of multivariate control chart are the violation of multivariate normal assumption and the difficulty in identifying the quality characteristic(s) that resulted in the out of control signals. The purpose of this paper is to examine the use of non-parametric control chart (the bootstrap approach) for obtaining control limit to overcome the problem of multivariate distributional assumption and the p-value method for detecting out of control signals. Results from a performance study show that the proposed bootstrap method enables the setting of control limit that can enhance the detection of out of control signals when compared, while the p-value method also enhanced in identifying out of control variables.

Keywords: bootstrap control limit, p-value method, out-of-control signals, p-value, quality characteristics

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Authors: P. S. Jagadeesh Kumar, Mingmin Pan, Xianpei Li, Yanmin Yuan, Tracy Lin Huan

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Researchers are doing enchanting research into the inherited features of Alzheimer’s disease and probable consistent therapies. In Alzheimer’s, memories are extinct in reverse order; memories formed lately are more transitory than those from formerly. Reminiscence therapy includes the conversation of past actions, trials and knowledges with another individual or set of people, frequently with the help of perceptible reminders such as photos, household and other acquainted matters from the past, music and collection of tapes. In this manuscript, the competence of reminiscence therapy for Alzheimer’s disease is measured using logistic regression based linear bootstrap aggregating. Logistic regression is used to envisage the experiential features of the patient’s memory through various therapies. Linear bootstrap aggregating shows better stability and accuracy of reminiscence therapy used in statistical classification and regression of memories related to validation therapy, supportive psychotherapy, sensory integration and simulated presence therapy.

Keywords: Alzheimer’s disease, linear bootstrap aggregating, logistic regression, reminiscence therapy

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Authors: S. Phanyaem

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This paper presents the confidence intervals for the effect size base on bootstrap resampling method. The meta-analytic confidence interval for effect size is proposed that are easy to compute. A Monte Carlo simulation study was conducted to compare the performance of the proposed confidence intervals with the existing confidence intervals. The best confidence interval method will have a coverage probability close to 0.95. Simulation results have shown that our proposed confidence intervals perform well in terms of coverage probability and expected length.

Keywords: effect size, confidence interval, bootstrap method, resampling

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Authors: Saman Javadi, Mehdi Hashemy, Mohahammad Mahmoodi

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Vulnerability maps are employed as an important solution in order to handle entrance of pollution into the aquifers. The common way to provide vulnerability map is DRASTIC. Meanwhile, application of the method is not easy to apply for any aquifer due to choosing appropriate constant values of weights and ranks. In this study, a new approach using k-means clustering is applied to make vulnerability maps. Four features of depth to groundwater, hydraulic conductivity, recharge value and vadose zone were considered at the same time as features of clustering. Five regions are recognized out of the case study represent zones with different level of vulnerability. The finding results show that clustering provides a realistic vulnerability map so that, Pearson’s correlation coefficients between nitrate concentrations and clustering vulnerability is obtained 61%.

Keywords: clustering, data mining, groundwater, vulnerability assessment

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Authors: Neha Gupta

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Landslide vulnerability is considered as the crucial parameter for the assessment of landslide risk. The term vulnerability defined as the damage or degree of elements at risk of different dimensions, i.e., physical, social, economic, and environmental dimensions. Himalaya region is very prone to multi-hazard such as floods, forest fires, earthquakes, and landslides. With the increases in fatalities rates, loss of infrastructure, and economy due to landslide in the Himalaya region, leads to the assessment of vulnerability. In this study, a methodology to measure the combination of vulnerability dimension, i.e., social vulnerability, physical vulnerability, and environmental vulnerability in one framework. A combined result of these vulnerabilities has rarely been carried out. But no such approach was applied in the Indian Scenario. The methodology was applied in an area of east Sikkim Himalaya, India. The physical vulnerability comprises of building footprint layer extracted from remote sensing data and Google Earth imaginary. The social vulnerability was assessed by using population density based on land use. The land use map was derived from a high-resolution satellite image, and for environment vulnerability assessment NDVI, forest, agriculture land, distance from the river were assessed from remote sensing and DEM. The classes of social vulnerability, physical vulnerability, and environment vulnerability were normalized at the scale of 0 (no loss) to 1 (loss) to get the homogenous dataset. Then the Multi-Criteria Analysis (MCA) was used to assign individual weights to each dimension and then integrate it into one frame. The final vulnerability was further classified into four classes from very low to very high.

Keywords: landslide, multi-criteria analysis, MCA, physical vulnerability, social vulnerability

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Authors: Karima Kimouche

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In this paper, we consider the asymptotic problems in spectral analysis of stationary causal random fields. We impose conditions only involving (conditional) moments, which are easily verifiable for a variety of nonlinear random fields. Limiting distributions of periodograms and smoothed periodogram spectral density estimates are obtained and applications to the spectral domain bootstrap are given.

Keywords: spatial nonlinear processes, spectral estimators, GMC condition, bootstrap method

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Authors: Lanja F. Rauf, Salahalddin S. Ali, Nadhir Al-Ansari

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Evolving groundwater vulnerability from DRASTIC to modified DRASTIC methods helps choose the most accurate areas that are most delicate toward pollution. This study aims to modify DRASTIC with land use and water quality index for groundwater vulnerability assessment in the Halabja-Khurmal sub-basin, NE/Iraq. The Halabja- Khurmal sub-basin groundwater vulnerability index is calculated from nine hydrogeological parameters by the overlay weighting method. As a result, 1.3 % of the total area has a very high vulnerability value and 46.1 % with high vulnerability. The regions with high groundwater vulnerability have a high water table and groundwater recharge. Nitrate concentration was used to validate the result, and the Pearson correlation and recession analysis between the modified DRASTIC index and nitrate concentration depicted a strong relation with 0.76 and 0.7, respectively.

Keywords: groundwater vulnerability, modified DRASTIC, land-use, nitrate pollution, water quality index

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Authors: Abdullah M. Algarni, Yashwant K. Malaiya

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Some of the key aspects of vulnerability-discovery, dissemination, and disclosure-have received some attention recently. However, the role of interaction among the vulnerability discoverers and vulnerability acquirers has not yet been adequately addressed. Our study suggests that a major percentage of discoverers, a majority in some cases, are unaffiliated with the software developers and thus are free to disseminate the vulnerabilities they discover in any way they like. As a result, multiple vulnerability markets have emerged. In some of these markets, the exchange is regulated, but in others, there is little or no regulation. In recent vulnerability discovery literature, the vulnerability discoverers have remained anonymous individuals. Although there has been an attempt to model the level of their efforts, information regarding their identities, modes of operation, and what they are doing with the discovered vulnerabilities has not been explored. Reports of buying and selling of the vulnerabilities are now appearing in the press; however, the existence of such markets requires validation, and the natures of the markets need to be analysed. To address this need, we have attempted to collect detailed information. We have identified the most prolific vulnerability discoverers throughout the past decade and examined their motivation and methods. A large percentage of these discoverers are located in Eastern and Western Europe and in the Far East. We have contacted several of them in order to collect first-hand information regarding their techniques, motivations, and involvement in the vulnerability markets. We examine why many of the discoverers appear to retire after a highly successful vulnerability-finding career. The paper identifies the actual vulnerability markets, rather than the hypothetical ideal markets that are often examined. The emergence of worldwide government agencies as vulnerability buyers has significant implications. We discuss potential factors that can impact the risk to society and the need for detailed exploration.

Keywords: risk management, software security, vulnerability discoverers, vulnerability markets

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Authors: Edlira Donefski, Lorenc Ekonomi, Tina Donefski

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Edgeworth approximation is one of the most important statistical methods that has a considered contribution in the reduction of the sum of standard deviation of the independent variables’ coefficients in a Quantile Regression Model. This model estimates the conditional median or other quantiles. In this paper, we have applied approximating statistical methods in an economical problem. We have created and generated a quantile regression model to see how the profit gained is connected with the realized sales of the cosmetic products in a real data, taken from a local business. The Linear Regression of the generated profit and the realized sales was not free of autocorrelation and heteroscedasticity, so this is the reason that we have used this model instead of Linear Regression. Our aim is to analyze in more details the relation between the variables taken into study: the profit and the finalized sales and how to minimize the standard errors of the independent variable involved in this study, the level of realized sales. The statistical methods that we have applied in our work are Edgeworth Approximation for Independent and Identical distributed (IID) cases, Bootstrap version of the Model and the Edgeworth approximation for Bootstrap Quantile Regression Model. The graphics and the results that we have presented here identify the best approximating model of our study.

Keywords: bootstrap, edgeworth approximation, IID, quantile

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Authors: Wenqing Fan, Yixuan Cheng, Wei Huang

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The diversity and complexity of modern IT systems make it almost impossible for internal teams to find vulnerabilities in all software before the software is officially released. The emergence of threat intelligence and vulnerability reporting policy has greatly reduced the burden on software vendors and organizations to find vulnerabilities. However, to prove the existence of the reported vulnerability, it is necessary but difficult for security incident response team to build a deliberated vulnerable environment from the vulnerability report with limited and incomplete information. This paper presents a structured, standardized, machine-oriented vulnerability intelligence format, that can be used to automate the orchestration of Deliberated Vulnerable Environment (DVE). This paper highlights the important role of software configuration and proof of vulnerable specifications in vulnerability intelligence, and proposes a triad model, which is called DIR (Dependency Configuration, Installation Configuration, Runtime Configuration), to define software configuration. Finally, this paper has also implemented a prototype system to demonstrate that the orchestration of DVE can be automated with the intelligence.

Keywords: DIR triad model, DVE, vulnerability intelligence, vulnerability recurrence

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Authors: Cuong V Nguyen, Ralph Horne, John Fien, France Cheong

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Social vulnerability to climate change is increasingly being acknowledged, and proposals to measure and manage it are emerging. Building upon this work, this paper proposes an approach to social vulnerability assessment using a new mechanism to aggregate and account for causal relationships among components of a Social Vulnerability Index (SVI). To operationalize this index, the authors propose a means to develop an appropriate primary dataset, through application of a specifically-designed household survey questionnaire. The data collection and analysis, including calibration and calculation of the SVI is demonstrated through application in case study city in central coastal Vietnam. The calculation of SVI at the fine-grained local neighbourhood scale provides high resolution in vulnerability assessment, and also obviates the need for secondary data, which may be unavailable or problematic, particularly at the local scale in developing countries. The SVI household survey is underpinned by the results of a Delphi survey, an in-depth interview and focus group discussions with local environmental professionals and community members. The research reveals inherent limitations of existing SVIs but also indicates the potential for their use in assessing social vulnerability and making decisions associated with responding to climate change at the local scale.

Keywords: climate change, local scale, social vulnerability, social vulnerability index

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Authors: Hafida Bouarfa, Mohamed Abed

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The main object of our work is the development and the validation of a system indicated Fuzzy Vulnerability. Fuzzy Vulnerability uses a fuzzy representation in order to tolerate the imprecision during the description of construction. At the the second phase, we evaluated the similarity between the vulnerability of a new construction and those of the whole of the historical cases. This similarity is evaluated on two levels: 1) individual similarity: bases on the fuzzy techniques of aggregation; 2) Global similarity: uses the increasing monotonous linguistic quantifiers (RIM) to combine the various individual similarities between two constructions. The third phase of the process of Fuzzy Vulnerability consists in using vulnerabilities of historical constructions narrowly similar to current construction to deduce its estimate vulnerability. We validated our system by using 50 cases. We evaluated the performances of Fuzzy Vulnerability on the basis of two basic criteria, the precision of the estimates and the tolerance of the imprecision along the process of estimation. The comparison was done with estimates made by tiresome and long models. The results are satisfactory.

Keywords: case based reasoning, fuzzy logic, fuzzy case based reasoning, seismic vulnerability

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Authors: G. Sridevi, Amalendu Jyotishi, Sushanta Mahapatra, G. Jagadeesh, Satyasiba Bedamatta

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Climate change is a main challenge for agriculture, food security and rural livelihoods for millions of people in India. Agriculture is the sector most vulnerable to climate change due to its high dependence on climate and weather conditions. Among India’s population of more than one billion people, about 68% are directly or indirectly involved in the agricultural sector. This sector is particularly vulnerable to present-day climate variability. In this contest this paper examines the Socio-economic and climate analytical study of the vulnerability index in Indian states of Andhra Pradesh and Karnataka. Using secondary data; it examines the vulnerability through five different sub-indicator of socio-demographic, agriculture, occupational, common property resource (CPR), and climate in respective states among different districts. Data used in this paper has taken from different sources, like census in India 2011, Directorate of Economics and Statistics of respective states governments. Rainfall data was collected from the India Meteorological Department (IMD). In order to capture the vulnerability from two different states the composite vulnerability index (CVI) was developed and used. This indicates the vulnerability situation of different districts under two states. The study finds that Adilabad district in Andhra Pradesh and Chamarajanagar in Karnataka had highest level of vulnerability while Hyderabad and Bangalore in respective states have least level of vulnerability.

Keywords: vulnerability, agriculture, climate change, global warming

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Authors: Z. A. Ahmad, R. C. Omar, I. Z. Baharuddin, R. Roslan

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Assessments of social vulnerability, carried out holistically, can provide an important guide to the planning process and to decisions on resource allocation at various levels, and can help to raise public awareness of geo-hazard risks. The assessments can help to provide answers for basic questions such as the human vulnerability at the geo-hazard prone or disaster areas causing health damage, economic loss, loss of natural heritage and vulnerability impact of extreme natural hazard event. To overcome these issues, integrated framework for assessing the increasing human vulnerability to environmental changes caused by geo-hazards will be introduced using an indicator from landslide risk map that is related to agent based modeling platform. The indicators represent the underlying factors, which influence a community’s ability to deal with and recover from the damage associated with geo-hazards. Scope of this paper is particularly limited to landslides.

Keywords: social, vulnerability, geo-hazard, methodology, indicators

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Authors: H. Majour, L. Djabri

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Many methods in the groundwater vulnerability have been developed in the world (methods like PRAST, DRIST, APRON/ARAA, PRASTCHIM, GOD). In this study, our choice dealt with two recent complementary methods using category mapping of index with weighting criteria (Point County Systems Model MSCP) namely the standard DRASTIC method and SI (Susceptibility Index). At present, these two methods are the most used for the mapping of the intrinsic vulnerability of groundwater. Two classes of groundwater vulnerability in the Biskra sandy aquifer were identified by the DRASTIC method (average and high) and the SI method (very high and high). Integrated analysis has revealed that the high class is predominant for the DRASTIC method whereas for that of SI the preponderance is for the very high class. Furthermore, we notice that the method SI estimates better the vulnerability for the pollution in nitrates, with a rate of 85 % between the concentrations in nitrates of groundwater and the various established classes of vulnerability, against 75 % for the DRASTIC method. By including the land use parameter, the SI method produced more realistic results.

Keywords: DRASTIC, SI, GIS, Biskra sandy aquifer, Algeria

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Authors: Gubhinder Kundhi, Paul Rilstone

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It is well established that Instrumental Variable (IV) estimators in the presence of weak instruments can be poorly behaved, in particular, be quite biased in finite samples. Finite sample approximations to the distributions of these estimators are obtained using Edgeworth and Saddlepoint expansions. Departures from normality of the distributions of these estimators are analyzed using higher order analytical corrections in these expansions. In a Monte-Carlo experiment, the performance of these expansions is compared to the first order approximation and other methods commonly used in finite samples such as the bootstrap.

Keywords: bootstrap, Instrumental Variable, Edgeworth expansions, Saddlepoint expansions

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Authors: Abida Haddouche, Ahmed Chrif Toubal

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The Neogene basin of the Eastern Mitidja, object of the study area, represents potential water resources and especially groundwater reserves. This water is an important economic; this resource is highly sensitive which need protection and preservation. Unfortunately, these waters are exposed to various forms of pollution, whether from urban, agricultural, industrial or merely accidental. This pollution is a permanent risk of limiting resource. In this context, the work aims to evaluate the intrinsic vulnerability of the aquifer to protect and preserve the quality of this resource. It will focus on the disposal of water and land managers a cartographic document accessible to locate the areas where the water has a high vulnerability. Vulnerability mapping of the Easter Mitidja quaternary aquifer is performed by applying three methods (DRASTIC, DRIST, and GOD). Comparison and validation results show that the DRASTIC method is the most suitable method for aquifer vulnerability of the study area.

Keywords: Aquifer of Mitidja, DRASTIC method, geographic information system (GIS), vulnerability mapping

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Authors: K. Shimola, M. Krishnaveni

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This paper examines vulnerability assessment of water resources in a semi-arid basin using the 4-step approach. The vulnerability assessment framework is developed to study the water resources vulnerability which includes the creation of GIS-based vulnerability maps. These maps represent the spatial variability of the vulnerability index. This paper introduces the 4-step approach to assess vulnerability that incorporates a new set of indicators. The approach is demonstrated using a framework composed of a precipitation data for (1975–2010) period, temperature data for (1965–2010) period, hydrological model outputs and the water resources GIS data base. The vulnerability assessment is a function of three components such as exposure, sensitivity and adaptive capacity. The current water resources vulnerability is assessed using GIS based spatio-temporal information. Rainfall Coefficient of Variation, monsoon onset and end date, rainy days, seasonality indices, temperature are selected for the criterion ‘exposure’. Water yield, ground water recharge, evapotranspiration (ET) are selected for the criterion ‘sensitivity’. Type of irrigation and storage structures are selected for the criterion ‘Adaptive capacity’. These indicators were mapped and integrated in GIS environment using overlay analysis. The five sub-basins, namely Arjunanadhi, Kousiganadhi, Sindapalli-Uppodai and Vallampatti Odai, fall under medium vulnerability profile, which indicates that the basin is under moderate stress of water resources. The paper also explores prioritization of sub-basinwise adaptation strategies to climate change based on the vulnerability indices.

Keywords: adaptive capacity, exposure, overlay analysis, sensitivity, vulnerability

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Authors: Sherry Ann Ganase, Sandra Sookram

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In this paper, the vulnerability level to climate change is analysed using a comprehensive index, consisting of five pillars: human, social, natural, physical, and financial. A structural equation model is also applied to determine the indicators and relationships that exist between the observed environmental changes and the quality of life. Using survey data to model the results, a value of 0.382 is derived as the vulnerability level for San Pedro, where values closer to zero indicates lower vulnerability and values closer to one indicates higher vulnerability. The results showed the social pillar to be most vulnerable, with the indicator ‘participation’ ranked the highest in its cohort. Although, the environmental pillar is ranked as least vulnerable, the indicators ‘hazard’ and ‘biodiversity’ obtained scores closer to 0.4, suggesting that changes in the environment are occurring from natural and anthropogenic activities. These changes can negatively influence the quality of life as illustrated in the structural equation modelling. The study concludes by reporting on the need for collective action and participation by households in lowering vulnerability to ensure sustainable development and livelihood.

Keywords: climate change, participation, San Pedro, structural equation model, vulnerability index

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Authors: Ayman Baklizi

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Based on type II censored data, we consider interval estimation of the quantiles of the two-parameter exponential distribution and the difference between the quantiles of two independent two-parameter exponential distributions. We derive asymptotic intervals, Bayesian, as well as intervals based on the generalized pivot variable. We also include some bootstrap intervals in our comparisons. The performance of these intervals is investigated in terms of their coverage probabilities and expected lengths.

Keywords: asymptotic intervals, Bayes intervals, bootstrap, generalized pivot variables, two-parameter exponential distribution, quantiles

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Authors: Syeda Qamarunnisa, Ishrat Jamil, Abid Azhar, Zabta K. Shinwari, Syed Irtifaq Ali

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A phylogenetic analysis of family Solanaceae was conducted using sequence data from the chloroplast intergenic atpB-rbcL spacer. Sequence data was generated from 17 species representing 09 out of 14 genera of Solanaceae from Pakistan. Cladogram was constructed using maximum parsimony method and results indicate that Solanaceae is mainly divided into two subfamilies; Solanoideae and Cestroideae. Four major clades within Solanoideae represent tribes; Physaleae, Capsiceae, Datureae and Solaneae are supported by high bootstrap value and the relationships among them are not corroborating with the previous studies. The findings established that subfamily Cestroideae comprised of three genera; Cestrum, Lycium, and Nicotiana with high bootstrap support. Position of Nicotiana inferred with atpB-rbcL sequence is congruent with traditional classification, which placed the taxa in Cestroideae. In the current study Lycium unexpectedly nested with Nicotiana with 100% bootstrap support and identified as a member of tribe Nicotianeae. Expanded sampling of other genera from Pakistan could be valuable towards improving our understanding of intrafamilial relationships within Solanaceae.

Keywords: systematics, solanaceae, phylogenetics, intergenic spacer, tribes

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Authors: Sherly M. A., Varsha Vijaykumar, Subhankar Karmakar, Terence Chan, Christian Rau

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This study aims at proposing an indicator-based framework for assessing social vulnerability of any coastal megacity to floods. The final set of indicators of social vulnerability are chosen from a set of feasible and available indicators which are prepared using a Geographic Information System (GIS) framework on a smaller scale considering 1-km grid cell to provide an insight into the spatial variability of vulnerability. The optimal weight for each individual indicator is assigned using data envelopment analysis (DEA) as it avoids subjective weights and improves the confidence on the results obtained. In order to de-correlate and reduce the dimension of multivariate data, principal component analysis (PCA) has been applied. The proposed methodology is demonstrated on twenty four wards of Mumbai under the jurisdiction of Municipal Corporation of Greater Mumbai (MCGM). This framework of vulnerability assessment is not limited to the present study area, and may be applied to other urban damage centers.

Keywords: urban floods, vulnerability, data envelopment analysis, principal component analysis

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Authors: Citra Pertiwi, Muhammad Fikruzzaman Rahawarin

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Government of Indonesia had committed to increasing its national defense the budget up to 1,5 percent of GDP. However, the budget increase does not necessarily allocate efficiently and effectively. Using Data Envelopment Analysis (DEA), the operational units of Indonesian Armed Forces are considered as a proxy to measure those two aspects. The bootstrap technique is being used as well to reduce uncertainty in the estimation. Additionally, technological change is being measured as a nonstationary component. Nearly half of the units are being estimated as fully efficient, with less than a third is considered as effective. Longer and larger sets of data might increase the robustness of the estimation in the future.

Keywords: bootstrap, effectiveness, efficiency, DEA, military, Malmquist, technological change

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Authors: Tewelde Gebresslase Haile, S. P. Singh

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To bridge the existing knowledge gap on public intervention implementations, this study estimates the impact of social protection intervention (SPI) on alleviating social vulnerability. Following a multi-stage sampling, primary information was gathered through a self-administered questionnaire, FGD, and interviews from the target households located at four systematically selected districts of Tigrai, Ethiopia. Factor analysis and Propensity Score Matching are applied to construct Social Vulnerability Index (SVI) and measuring the counterfactual impact of selected intervention. As a multidimensional challenge, social vulnerability is found as an important concept used to guide policy evaluation. Accessibility of basic services of Social Affairs, Agriculture, Health and Education sectors, and Food Security Program are commonly used as SPIs. Finally, this study discovers that the households who had access to SPI have scored 9.65% lower SVI than in the absence of the intervention. Finally, this study suggests the provision of integrated, proactive, productive, and evidence-based SPIs to alleviate social vulnerability.

Keywords: social protection, livelihood assets, social vulnerability, public policy SVI

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Authors: Aniedi A. Udo, Magnus U. Igboekwe, Rasaaq Bello, Francis D. Eyenaka, Michael C. Ohakwere-Eze

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Groundwater vulnerability to pollution was assessed in Akwa Ibom State, Southern Nigeria, with the aim of locating areas with high potentials for resource contamination, especially due to anthropogenic influence. The electrical resistivity method was utilized in the collection of the initial field data. Additional data input, which included depth to static water level, drilled well log data, aquifer recharge data, percentage slope, as well as soil information, were sourced from secondary sources. The initial field data were interpreted both manually and with computer modeling to provide information on the geoelectric properties of the subsurface. Interpreted results together with the secondary data were used to develop the DRASTIC thematic maps. A vulnerability assessment was performed using the DRASTIC model in a GIS environment and areas with high vulnerability which needed immediate attention was clearly mapped out and presented using an aquifer vulnerability map. The model was subjected to validation and the rate of validity was 73% within the area of study.

Keywords: groundwater, vulnerability, DRASTIC model, pollution

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