Search results for: legal judgment prediction

Authors: Mikel Niño, Roberto V. Zicari, Todor Ivanov, Kim Hee, Naveed Mushtaq, Marten Rosselli, Concha Sánchez-Ocaña, Karsten Tolle, José Miguel Blanco, Arantza Illarramendi, Jörg Besier, Harry Underwood

Abstract:

One of the application fields for data analysis techniques and technologies gaining momentum is the area of social good or “common good”, covering cases related to humanitarian crises, global health care, or ecology and environmental issues, among others. The promotion of data-driven projects in this field aims at increasing the efficacy and efficiency of social initiatives, improving the way these actions help humanity in general and people in need in particular. This application field, however, poses its own barriers and challenges when developing data-driven projects, lagging behind in comparison with other scenarios. These challenges derive from aspects such as the scope and scale of the social issue to solve, cultural and political barriers, the skills of main stakeholders and the technological resources available, the motivation to be engaged in such projects, or the ethical and legal issues related to sensitive data. This paper analyzes the application of data projects in the field of social good, reviewing its current state and noteworthy initiatives, and presenting a framework covering the key aspects to analyze in such projects. The goal is to provide guidelines to understand the main challenges and opportunities for this type of data project, as well as identifying the main differential issues compared to “classical” data projects in general. A case study is presented on the initial steps and stakeholder analysis of a data project for the inclusion of refugees in the city of Frankfurt, Germany, in order to empirically confront the framework with a real example.

Keywords: data-driven projects, humanitarian operations, personal and sensitive data, social good, stakeholders analysis

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Authors: Natsuda Rattamanee

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Like other countries, Thailand continually experiences strong protests against dam and reservoir proposals, especially large-scale projects. The protestors are constantly worried about the potential significant adverse impacts of the projects on the environment and society. Although project proponents are required by laws to assess the environmental and social impacts of the dam proposals by making environmental impact assessment (EIA) reports and finding mitigation measures before implementing the plans, the outcomes of the assessments often do not lessen the affected people and public’s concerns about the potential negative effects of the projects. One of the main reasons is that Thailand does not have a proper and efficient law to regulate project proponents when determining the scope of environmental impact assessments. Scoping is the crucial second stage of the preparation of an EIA report. The appropriate scope of assessments will allow EIA studies to focus only on the significant effects of the proposed project on particular resources, areas, and communities. It will offer crucial and sufficient information to the decision-makers and the public. The decision to implement the dam and reservoir projects considered based on the assessments with a proper scoping will eventually be more widely accepted by the public and reduce community opposition. The research work seeks to identify flaws in the current requirements of scoping steps under Thai laws and regulations and proposes recommendations to improve the legal scheme. The paper explores the well-established United States laws and relevant rules regulating how lead agencies determine the scope of their environmental impact assessments and some guidelines concerning scoping published by dominant institutions. Policymakers and legislature will find the results of studies helpful in improving the scoping-step requirements of EIA for dam and reservoir projects and reducing the level of anti-dam protests in Thailand.

Keywords: dam and reservoir, EIA, environmental impact assessment, law, scoping, Thailand

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Authors: Seember Susan Aondoakura

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This paper examines the international legal framework established to address the challenges women and girls experience in situations of violent conflict. The United Nations (UN) women, peace, and security agenda (hereafter WPS agenda, the Agenda) aspire to make wars safer for women. It recognizes women's agency in armed conflict and their victimization and formulates measures for their protection. The Agenda also acknowledges women's participation in conflict transformation and post-conflict reconstruction. It also calls for the involvement of women in conflict transformation, encourages the protection of women from sex and gender-based violence (SGBV), and provides relief and recovery from conflict-related SGBV. Using Third World Critical Feminist Theory, this paper argues that the WPS agenda overly focus on the protection of women from SGBV occurring in the less developed and conflict-ridden states in the global south, obscures the complicity of western states and economies to the problem, and silences the privileges that such states derive from war economies that continue to fuel conflict. This protectionist approach of the UN also obliterates other equally pressing problems in need of attention, like the high rates of economic degradation in conflict-ravaged societies of the global south. Prioritising protection also 'others' the problem, obliterating any sense of interconnections across geographical locations and situating women in the less developed economies of the global south as the victims and their men as the perpetrators. Prioritising protection ultimately situates western societies as saviours of Third World women with no recourse to their role in engendering and sustaining war. The paper demonstrates that this saviour mentality obliterates chances of any meaningful coalition between the local and the international in framing and addressing the issue, as solutions are formulated from a specific lens—the white hegemonic lens.

Keywords: conflict, protection, security, SGBV

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Authors: Carlos Gonzales, Zaida Quiroz, Marcos Prates

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Several spatial variables collected at the same location that share a common spatial distribution can be modeled simultaneously through a multivariate geostatistical model that takes into account the correlation between these variables and the spatial autocorrelation. The main goal of this model is to perform spatial prediction of these variables in the region of study. Here we focus on a geostatistical multivariate formulation that relies on sharing common spatial random effect terms. In particular, the first response variable can be modeled by a mean that incorporates a shared random spatial effect, while the other response variables depend on this shared spatial term, in addition to specific random spatial effects. Each spatial random effect is defined through a Gaussian process with a valid covariance function, but in order to improve the computational efficiency when the data are large, each Gaussian process is approximated to a Gaussian random Markov field (GRMF), specifically to the block nearest neighbor Gaussian process (Block-NNGP). This approach involves dividing the spatial domain into several dependent blocks under certain constraints, where the cross blocks allow capturing the spatial dependence on a large scale, while each individual block captures the spatial dependence on a smaller scale. The multivariate geostatistical model belongs to the class of Latent Gaussian Models; thus, to achieve fast Bayesian inference, it is used the integrated nested Laplace approximation (INLA) method. The good performance of the proposed model is shown through simulations and applications for massive data.

Keywords: Block-NNGP, geostatistics, gaussian process, GRMF, INLA, multivariate models.

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Authors: Andrew R. Beatty

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The exploitation of Australia’s vast mineral wealth is regulated by a matrix of planning, environment and heritage legislation, and despite the desire for a ‘balance’ between economic, environmental and heritage values, Aboriginal objects and places are often detrimentally impacted by mining approvals. The Australian experience is not novel. There are other cases of clashes between the rights of traditional landowners and businesses seeking to exploit mineral or other resources on or beneath those lands, including in the United States, Canada, and Brazil. How one reconciles the rights of traditional owners with those of resource companies is an ongoing legal problem of general interest. In Australia, planning and environmental approvals for resource projects are ordinarily issued by State or Territory governments. Federal legislation such as the Aboriginal and Torres Strait Islander Heritage Protection Act 1984 (Cth) is intended to act as a safety net when State or Territory legislation is incapable of protecting Indigenous objects or places in the context of approvals for resource projects. This paper will analyse the context and effectiveness of legislation enacted to protect Indigenous heritage in the planning process. In particular, the paper will analyse how the statutory objects of such legislation need to be weighed against the statutory objects of competing legislation designed to facilitate and control resource exploitation. Using a current claim in the Federal Court of Australia for the protection of a culturally significant landscape as a case study, this paper will examine the challenges faced in ascribing value to cultural heritage within the wider context of environmental and planning laws. Our findings will reveal that there is an inherent difficulty in defining and weighing competing economic, environmental and heritage considerations. An alternative framework will be proposed to guide regulators towards making decisions that result in better protection of Indigenous heritage in the context of resource management.

Keywords: environmental law, heritage law, indigenous rights, mining

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Authors: Samy A. Khalil, U. Ali Rahoma

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The measurements of solar radiation, satellite data has been routinely utilize to estimate solar energy. However, the temporal coverage of satellite data has some limits. The reanalysis, also known as "retrospective analysis" of the atmosphere's parameters, is produce by fusing the output of NWP (Numerical Weather Prediction) models with observation data from a variety of sources, including ground, and satellite, ship, and aircraft observation. The result is a comprehensive record of the parameters affecting weather and climate. The effectiveness of reanalysis datasets (ERA-5) for North Africa was evaluate against high-quality surfaces measured using statistical analysis. Estimating the distribution of global solar radiation (GSR) over five chosen areas in North Africa through ten-years during the period time from 2011 to 2020. To investigate seasonal change in dataset performance, a seasonal statistical analysis was conduct, which showed a considerable difference in mistakes throughout the year. By altering the temporal resolution of the data used for comparison, the performance of the dataset is alter. Better performance is indicate by the data's monthly mean values, but data accuracy is degraded. Solar resource assessment and power estimation are discuses using the ERA-5 solar radiation data. The average values of mean bias error (MBE), root mean square error (RMSE) and mean absolute error (MAE) of the reanalysis data of solar radiation vary from 0.079 to 0.222, 0.055 to 0.178, and 0.0145 to 0.198 respectively during the period time in the present research. The correlation coefficient (R2) varies from 0.93 to 99% during the period time in the present research. This research's objective is to provide a reliable representation of the world's solar radiation to aid in the use of solar energy in all sectors.

Keywords: solar energy, ERA-5 analysis data, global solar radiation, North Africa

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Authors: Jennifer Nutton, Gayle Ployer, Ky Scott, Jenny Morgan

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Working in a circle within higher education creates a decolonial space of mutual respect, responsibility, and reciprocity that facilitates collaborative learning and deep connections among learners and instructors. This approach is beyond simply facilitating a group in a circle but opens the door to creating a sacred space connecting each member to the land, to the Indigenous peoples who have taken care of the lands since time immemorial, to one another, and to one’s own positionality. These deep connections not only center human knowledges and relationships but also acknowledges responsibilities to land. Working in a circle as a relational pedagogical praxis also disrupts institutional power dynamics by creating a space of collaborative learning and deep connections in the classroom. Inherent within circle work is to facilitate connections not just academically but emotionally, physically, culturally, and spiritually. Recent literature supports the use of online talking circles, finding that it can offer a more relational and experiential learning environment, which is often absent in the virtual world and has been made more evident and necessary since the pandemic. These deeper experiences of learning and connection, rooted in both knowledge and the land, can then be shared with openness and vulnerability with one another, facilitating growth and change. This process of beginning with the land is critical to ensure we have the grounding to obstruct the ongoing realities of colonialism. The authors, who identify as both Indigenous and non-Indigenous, as both educators and learners, reflect on their teaching and learning experiences in circle. They share a relational pedagogical praxis framework that has been successful in educating future social workers, environmental activists, and leaders in social and human services, health, legal and political fields.

Keywords: circle work, relational pedagogies, decolonization, distance education

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Authors: Brindha Senthil Kumar, Payel Chakraborty, Senthil Kumar Nachimuthu, Arindam Maitra, Prem Nath

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Gastric cancer is predominantly caused by demographic and diet factors as compared to other cancer types. The aim of the study is to predict Early Gastric Cancer (ECG) from diet and lifestyle factors using supervised machine learning algorithms. For this study, 160 healthy individual and 80 cases were selected who had been followed for 3 years (2016-2019), at Civil Hospital, Aizawl, Mizoram. A dataset containing 11 features that are core risk factors for the gastric cancer were extracted. Supervised machine algorithms: Logistic Regression, Naive Bayes, Support Vector Machine (SVM), Multilayer perceptron, and Random Forest were used to analyze the dataset using Python Jupyter Notebook Version 3. The obtained classified results had been evaluated using metrics parameters: minimum_false_positives, brier_score, accuracy, precision, recall, F1_score, and Receiver Operating Characteristics (ROC) curve. Data analysis results showed Naive Bayes - 88, 0.11; Random Forest - 83, 0.16; SVM - 77, 0.22; Logistic Regression - 75, 0.25 and Multilayer perceptron - 72, 0.27 with respect to accuracy and brier_score in percent. Naive Bayes algorithm out performs with very low false positive rates as well as brier_score and good accuracy. Naive Bayes algorithm classification results in predicting ECG showed very satisfactory results using only diet cum lifestyle factors which will be very helpful for the physicians to educate the patients and public, thereby mortality of gastric cancer can be reduced/avoided with this knowledge mining work.

Keywords: Early Gastric cancer, Machine Learning, Diet, Lifestyle Characteristics

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Authors: Joonas Pääkkönen

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In sports, individuals and teams are typically interested in final rankings. Final results, such as times or distances, dictate these rankings, also known as places. Places can be further associated with ordered random variables, commonly referred to as order statistics. In this work, we introduce a simple, yet accurate order statistical ordinal regression function that predicts relay race places with changeover-times. We call this function the Fenton-Wilkinson Order Statistics model. This model is built on the following educated assumption: individual leg-times follow log-normal distributions. Moreover, our key idea is to utilize Fenton-Wilkinson approximations of changeover-times alongside an estimator for the total number of teams as in the notorious German tank problem. This original place regression function is sigmoidal and thus correctly predicts the existence of a small number of elite teams that significantly outperform the rest of the teams. Our model also describes how place increases linearly with changeover-time at the inflection point of the log-normal distribution function. With real-world data from Jukola 2019, a massive orienteering relay race, the model is shown to be highly accurate even when the size of the training set is only 5% of the whole data set. Numerical results also show that our model exhibits smaller place prediction root-mean-square-errors than linear regression, mord regression and Gaussian process regression.

Keywords: Fenton-Wilkinson approximation, German tank problem, log-normal distribution, order statistics, ordinal regression, orienteering, sports analytics, sports modeling

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Authors: Takuro Kida, Yuichi Kida

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In this paper, it is shown a base of the new trend of algorithm mathematically that treats a historical reason of continuous discrimination in the world as well as its solution by introducing new concepts of parallel world that includes an invisible set of errors as its companion. With respect to a matrix operator-filter bank that the matrix operator-analysis-filter bank H and the matrix operator-sampling-filter bank S are given, firstly, we introduce the detail algorithm to derive the optimum matrix operator-synthesis-filter bank Z that minimizes all the worst-case measures of the matrix operator-error-signals E(ω) = F(ω) − Y(ω) between the matrix operator-input-signals F(ω) and the matrix operator-output-signals Y(ω) of the matrix operator-filter bank at the same time. Further, feedback is introduced to the above approximation theory, and it is indicated that introducing conversations with feedback do not superior automatically to the accumulation of existing knowledge of signal prediction. Secondly, the concept of category in the field of mathematics is applied to the above optimum signal approximation and is indicated that the category-based approximation theory is applied to the set-theoretic consideration of the recognition of humans. Based on this discussion, it is shown naturally why the narrow perception that tends to create isolation shows an apparent advantage in the short term and, often, why such narrow thinking becomes intimate with discriminatory action in a human group. Throughout these considerations, it is presented that, in order to abolish easy and intimate discriminatory behavior, it is important to create a parallel world of conception where we share the set of invisible error signals, including the words and the consciousness of both worlds.

Keywords: matrix filterbank, optimum signal approximation, category theory, simultaneous minimization

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Authors: Kevin Moustapha

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Psychopathy is perceived today as being «the most important concept in the criminal justice system» and as «the most important legal notion of the early 21 th century». The explosion of research related to psychopathy seems to perfectly illustrate this trend. Traditionally, many studies tend to focus on links between insanity defense and psychopathy. That is why our purpose in this article is to analyze psychopathic disorders in the scope of judges sentencing in Canada. Indeed, in every Canadian case related to dangerous offenders, judges must balance between fairness and protection of the individuals rights of the accused and protection of society from dangerous predators who may commit future acts of physical or sexual violence. Increasingly, psychopathic disorders are taking an important part in judge sentencing, especially in Canada. This phenomenon can be illustrated by the high proportion of psychopath offenders incarcerated in North American prisons. Many decisions in Canadians courtrooms seem to point out that psychopathy is often used as a strong argument by the judges to preserve public safety. The fact that psychopathy is often associated with violence, recklessness and recidivism, it could explain why many judges consider psychopathic disorders as an aggravating factor. Generally, the judge reasoning is based on article 753 of Canadian Criminal Code related to dangerous offenders, which is used for individuals who show a pattern of repetitive and persistent aggressive behaviour. However, with cognitive neurosciences, the psychopath’s situation in courtrooms would probably change. Cerebral imaging and news data provided by the neurosciences show that emotional and volitional functions in psychopath’s brains are impaired. Understanding these new issues could enable some judges to recognize psychopathic disorders as a mitigating factor. Two important questions ought to be raised in this article: can exploring psychopaths ‘brains really change the judge sentencing in Canadian courtrooms? If yes, can judges consider psychopathy more as a mitigating factor than an aggravating factor?

Keywords: criminal law, judges sentencing, neurosciences, psychopathy

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Authors: Tosin Deborah Akanbi

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The Building Information Modeling Execution Plan (BEP) is a document that manifests the specifications for the adoption and execution of building information modeling in the construction sector in an organized manner so as to attain the listed goals. In this regard, the study examined the barriers to the adoption of building information modeling, evaluated the effect of building information modeling adoption characteristics on the key elements of a building information modeling execution plan and developed a strategic framework for a BEP in the Lagos State construction industry. Data were gathered through a questionnaire survey with 332 construction professionals in the study area. Three online structured interviews were conducted to support and validate the findings of the quantitative analysis. The results showed the significant relationships and connections between the variables in the framework: BIM usage and model quality control (aBIMskill -> dMQ, Beta = 0.121, T statistics = 1.829), BIM adoption characteristics and information exchange (bBIM_CH -> dIE, Beta = 0.128, T statistics = 1.727), BIM adoption characteristics and process design (bBIM_CH -> dPD, Beta = 0.170, T statistics = 2.754), BIM adoption characteristics and roles and responsibilities (bBIM_CH -> dRR, Beta = 0.131, T statistics = 2.181), interest BIM barriers and BIM adoption characteristics (cBBIM_INT -> bBIM_CH, Beta = 0.137, T statistics = 2.309), legal BIM barriers and BIM adoption characteristics (cBBIM_LEG -> bBIM_CH, Beta = 0.168, T statistics = 2.818), professional BIM barriers and BIM adoption characteristics (cBBIM_PRO -> bBIM_CH, Beta = 0.152, T statistics = 2.645). The results also revealed that seven final themes were generated, namely: model structure and process design, BIM information exchange and collaboration procedures, project goals and deliverables, project model quality control, roles and responsibilities, reflect Lagos state construction industry and validity of the BEP framework. Thus, there is a need for the policy makers to direct interventions to promote, encourage and support the understanding and adoption of BIM by emphasizing the various benefits of using the technology in the Lagos state construction industry.

Keywords: building information modelling execution plan, BIM adoption characteristics, BEP framework, construction industry

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Authors: Bi-Huei Tsai

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This work explores the inter-region investment behaviors of integrated circuit (IC) design industry from Taiwan to China using the amount of foreign direct investment (FDI). According to the mutual dependence among different IC design industrial locations, Lotka-Volterra model is utilized to explore the FDI interactions between South and East China. Effects of inter-regional collaborations on FDI flows into China are considered. Evolutions of FDIs into South China for IC design industry significantly inspire the subsequent FDIs into East China, while FDIs into East China for Taiwan’s IC design industry significantly hinder the subsequent FDIs into South China. The supply chain along IC industry includes IC design, manufacturing, packing and testing enterprises. I C manufacturing, packaging and testing industries depend on IC design industry to gain advanced business benefits. The FDI amount from Taiwan’s IC design industry into East China is the greatest among the four regions: North, East, Mid-West and South China. The FDI amount from Taiwan’s IC design industry into South China is the second largest. If IC design houses buy more equipment and bring more capitals in South China, those in East China will have pressure to undertake more FDIs into East China to maintain the leading position advantages of the supply chain in East China. On the other hand, as the FDIs in East China rise, the FDIs in South China will successively decline since capitals have concentrated in East China. Prediction of Lotka-Volterra model in FDI trends is accurate because the industrial interactions between the two regions are included. Finally, this work confirms that the FDI flows cannot reach a stable equilibrium point, so the FDI inflows into East and South China will expand in the future.

Keywords: Lotka-Volterra model, foreign direct investment, competitive, Equilibrium analysis

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Authors: Theresa Ukamaka Nwagha, Angela Ogechukwu Ugwu, Martins Nweke

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Background and Objectives: Blood transfusion is an effective and proven treatment for some severe complications of sickle cell disease. Recurrent transfusions have put patients with sickle cell disease at risk of developing antibodies against the various antigens they were exposed to. This study aims to investigate the frequency of red blood cell alloimmunization in patients with sickle disease in Africa. Materials and Methods: This is a systematic review of peer-reviewed literature published in English. The review was conducted consistent with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. Data sources for the review include MEDLINE, PubMed, CINAHL, and Academic Search Complete. Included in this review are articles that reported the frequency/prevalence of red blood cell alloimmunization in sickle cell disease patients in Africa. Eligible studies were subjected to independent full-text screening and data extraction. Risk of bias assessment was conducted with the aid of the mixed method appraisal tool. We employed a random-effects model of meta-analysis to estimate the pooled prevalence. We computed Cochrane’s Q statistics and I2 and prediction interval to quantify heterogeneity in effect size. Results: The prevalence estimates range from 2.6% to 29%. Pooled prevalence was estimated to be 10.4% (CI 7.7.–13.8); PI = 3.0 – 34.0%), with significant heterogeneity (I2 = 84.62; PI = 2.0-32.0%) and publication bias (Egger’s t-test = 1.744, p = 0.0965). Conclusion: The frequency of red cell alloantibody varies considerably in Africa. The alloantibodies appeared frequent in this order: the Rhesus, Kell, Lewis, Duffy, MNS, and Lutheran

Keywords: frequency, red blood cell, alloimmunization, sickle cell disease, Africa

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Authors: Iva Trako, Maris Micaela Sviatschi, Guadalupe Kavanaugh

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Domestic violence is a major concern in developing countries, with important social, economic and health consequences. However, institutions do not usually address the problems facing women or ethnic and religious minorities. For example, the police do very little to stop domestic violence in rural areas of developing countries. This paper exploits the introduction of women’s justice centers (WJCs) in Peru to provide causal estimates on the effects of improving access to justice for women and children. These centers offer a new integrated public service model for women by including medical, psychological and legal support in cases of violence against women. Our empirical approach uses a difference in difference estimation exploiting variation over time and space in the opening of WJC together with province-by-year fixed effects. Exploiting administrative data from health providers and district attorney offices, we find that after the opening of these centers, there are important improvements on women's welfare: a large reduction in femicides and female hospitalizations for assault. Moreover, using geo-coded household surveys we find evidence that the existence of these services reduces domestic violence, improves women's health, increases women's threat points and, therefore, lead to household decisions that are more aligned with their interests. Using administrative data on the universe of schools, we find large gains on human capital for their children: affected children are more likely to enroll, attend school and have better grades in national exams, instead of working for the family. In sum, the evidence in this paper shows that providing access to justice for women can be a powerful tool to reduce domestic violence and increase education of children, suggesting a positive inter-generational benefit.

Keywords: access to justice, domestic violence, education, household bargaining

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Authors: Muhammed Ashiq Villanthenkodath, Shreya Pal

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Purpose: This study scrutinizes the impact of economic globalization on ecological footprint while endogenizing economic growth and energy consumption from 1990 to 2018 in India. Design/methodology/approach: The standard unit root test has been employed for time series analysis to unveil the integration order. Then, the cointegration was confirmed using autoregressive distributed lag (ARDL) analysis. Further, the study executed the dynamic ARDL simulation model to estimate long-run and short-run results along with simulation and robotic prediction. Findings: The cointegration analysis confirms the existence of a long-run association among variables. Further, economic globalization reduces the ecological footprint in the long run. Similarly, energy consumption decreases the ecological footprint. In contrast, economic growth spurs the ecological footprint in India. Originality/value: This study contributes to the literature in many ways. First, unlike studies that employ CO2 emissions and globalization nexus, this study employs ecological footprint for measuring environmental quality; since it is the broader measure of environmental quality, it can offer a wide range of climate change mitigation policies for India. Second, the study executes a multivariate framework with updated series from 1990 to 2018 in India to explore the link between EF, economic globalization, energy consumption, and economic growth. Third, the dynamic autoregressive distributed lag (ARDL) model has been used to explore the short and long-run association between the series. Finally, to our limited knowledge, this is the first study that uses economic globalization in the EF function of India amid facing a trade-off between sustainable economic growth and the environment in the era of globalization.

Keywords: economic globalization, ecological footprint, India, dynamic ARDL simulation model

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Authors: Zhongmin Wang, Wudong Fan, Hengshan Zhang, Yimin Zhou

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In data-driven prognostic methods, the prediction accuracy of the estimation for remaining useful life of bearings mainly depends on the performance of health indicators, which are usually fused some statistical features extracted from vibrating signals. However, the existing health indicators have the following two drawbacks: (1) The differnet ranges of the statistical features have the different contributions to construct the health indicators, the expert knowledge is required to extract the features. (2) When convolutional neural networks are utilized to tackle time-frequency features of signals, the time-series of signals are not considered. To overcome these drawbacks, in this study, the method combining convolutional neural network with gated recurrent unit is proposed to extract the time-frequency image features. The extracted features are utilized to construct health indicator and predict remaining useful life of bearings. First, original signals are converted into time-frequency images by using continuous wavelet transform so as to form the original feature sets. Second, with convolutional and pooling layers of convolutional neural networks, the most sensitive features of time-frequency images are selected from the original feature sets. Finally, these selected features are fed into the gated recurrent unit to construct the health indicator. The results state that the proposed method shows the enhance performance than the related studies which have used the same bearing dataset provided by PRONOSTIA.

Keywords: continuous wavelet transform, convolution neural net-work, gated recurrent unit, health indicators, remaining useful life

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Authors: Tugba Bayoglu

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Aerodynamic parameter estimation is very crucial in missile design phase, since accurate high fidelity aerodynamic model is required for designing high performance and robust control system, developing high fidelity flight simulations and verification of computational and wind tunnel test results. However, in literature, there is not enough missile aerodynamic parameter identification study for three main reasons: (1) most air to air missiles cannot fly with constant speed, (2) missile flight test number and flight duration are much less than that of fixed wing aircraft, (3) variation of the missile aerodynamic parameters with respect to Mach number is higher than that of fixed wing aircraft. In addition to these challenges, identification of aerodynamic parameters for high wind angles by using classical estimation techniques brings another difficulty in the estimation process. The reason for this, most of the estimation techniques require employing polynomials or splines to model the behavior of the aerodynamics. However, for the missiles with a large variation of aerodynamic parameters with respect to flight variables, the order of the proposed model increases, which brings computational burden and complexity. Therefore, in this study, it is aimed to solve nonlinear aerodynamic parameter identification problem for a supersonic air to air missile by using Artificial Neural Networks. The method proposed will be tested by using simulated data which will be generated with a six degree of freedom missile model, involving a nonlinear aerodynamic database. The data will be corrupted by adding noise to the measurement model. Then, by using the flight variables and measurements, the parameters will be estimated. Finally, the prediction accuracy will be investigated.

Keywords: air to air missile, artificial neural networks, open loop simulation, parameter identification

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Authors: Mohammed Saleh Rezk, Reza Kashani

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Auxiliary damping has gained popularity in recent years, especially in structures such as mid- and high-rise buildings. Distributed damping systems (typically viscous and viscoelastic) or reactive damping systems (such as tuned mass dampers) are the two types of damping choices for such structures. Distributed VE dampers are normally configured as braces or damping panels, which are engaged through relatively small movements between the structural members when the structure sways under wind or earthquake loading. In addition to being used as stand-alone dampers in distributed damping applications, VE dampers can also be incorporated into the suspension element of tuned mass dampers (TMDs). In this study, analytical and numerical tools for modeling and design of multilayer viscoelastic damping devices to be used in dampening the vibration of large structures are developed. Considering the limitations of analytical models for the synthesis and analysis of realistic, large, multilayer VE dampers, the emphasis of the study has been on numerical modeling using the finite element method. To verify the finite element models, a two-layer VE damper using ½ inch synthetic viscoelastic urethane polymer was built, tested, and the measured parameters were compared with the numerically predicted ones. The numerical model prediction and experimentally evaluated damping and stiffness of the test VE damper were in very good agreement. The effectiveness of VE dampers in adding auxiliary damping to larger structures is numerically demonstrated by chevron bracing one such damper numerically into the model of a massive frame subject to an abrupt lateral load. A comparison of the responses of the frame to the aforementioned load, without and with the VE damper, clearly shows the efficacy of the damper in lowering the extent of frame vibration.

Keywords: viscoelastic, damper, distributed damping, tuned mass damper

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Authors: David Lloyd, David Owen, Martin Jardine

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Introduction: European weight regulations with respect to food products require a full understanding of regulation guidelines to assure regulatory compliance. It is suggested that the complexity of regulation leads to practices which result to over filling of food packages by food processors. Purpose: To establish current practices by food processors and the financial, sustainable and societal impacts on the food supply chain of ineffective food production practices. Methods: An analysis of food packing controls with 10 companies of varying food categories and quantitative based research of a further 15 food processes on the confidence in weight control analysis of finished food packs within their organisation. Results: A process floor analysis of manufacturing operations focussing on 10 products found over fill of packages ranging from 4.8% to 20.2%. Standard deviation figures for all products showed a potential for reducing average weight of the pack whilst still retain the legal status of the product. In 20% of cases, an automatic weight analysis machine was in situ however weight packs were still significantly overweight. Collateral impacts noted included the effect of overfill on raw material purchase and added food miles often on a global basis with one raw material alone creating 10,000 extra food miles due to the poor weight control of the processing unit. A case study of a meat and bakery product will be discussed with the impact of poor controls resulting from complex legislation. The case studies will highlight extra energy costs in production and the impact of the extra weight on fuel usage. If successful a risk assessment model used primarily on food safety but adapted to identify waste /sustainability risks will be discussed within the presentation.

Keywords: legislation, overfill, profile, waste

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Authors: Ashirgul Kozhagulova, Ainash Shabdirova, Galym Tokazhanov, Minh Nguyen

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The synthetic rocks have been advantageous over the natural rocks in terms of availability and the consistent studying the impact of a particular parameter. The artificial rocks can be fabricated using variety of techniques such as mixing sand and Portland cement or gypsum, firing the mixture of sand and fine powder of borosilicate glass or by in-situ precipitation of calcite solution. In this study, sodium silicate solution has been used as the cementing agent for the quartz sand. The molded soft cylindrical sandstone samples are placed in the gas-tight pressure vessel, where the hardening of the material takes place as the chemical reaction between carbon dioxide and the silicate solution progresses. The vessel allows uniform disperse of carbon dioxide and control over the ambient gas pressure. Current paper shows how the bonding material is initially distributed in the intergranular space and the surface of the sand particles by the usage of Electron Microscopy and the Energy Dispersive Spectroscopy. During the study, the strength of the cement bond as a function of temperature is observed. The impact of cementing agent dosage on the micro and macro characteristics of the sandstone is investigated. The analysis of the cement bond at micro level helps to trace the changes to particles bonding damage after a potential yielding. Shearing behavior and compressional response have been examined resulting in the estimation of the shearing resistance and cohesion force of the sandstone. These are considered to be main input values to the mathematical prediction models of sand production from weak clastic oil reservoir formations.

Keywords: artificial sanstone, cement bond, microstructure, SEM, triaxial shearing

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Authors: Ashis Mallick, Rajeev Ranjan

Abstract:

The closed form solution for thermal stresses in an annular fin with hyperbolic profile is derived using Adomian decomposition method (ADM). The conductive-convective fin with variable thermal conductivity is considered in the analysis. The nonlinear heat transfer equation is efficiently solved by ADM considering insulated convective boundary conditions at the tip of fin. The constant of integration in the solution is to be estimated using minimum decomposition error method. The solution of temperature field is represented in a polynomial form for convenience to use in thermo-elasticity equation. The non-dimensional thermal stress fields are obtained using the ADM solution of temperature field coupled with the thermo-elasticity solution. The influence of the various thermal parameters in temperature field and stress fields are presented. In order to show the accuracy of the ADM solution, the present results are compared with the results available in literature. The stress fields in fin with hyperbolic profile are compared with those of uniform thickness profile. Result shows that hyperbolic fin profile is better choice for enhancing heat transfer. Moreover, less thermal stresses are developed in hyperbolic profile as compared to rectangular profile. Next, Nelder-Mead based simplex search method is employed for the inverse estimation of unknown non-dimensional thermal parameters in a given stress fields. Owing to the correlated nature of the unknowns, the best combinations of the model parameters which are satisfying the predefined stress field are to be estimated. The stress fields calculated using the inverse parameters give a very good agreement with the stress fields obtained from the forward solution. The estimated parameters are suitable to use for efficient and cost effective fin designing.

Keywords: Adomian decomposition, inverse analysis, hyperbolic fin, variable thermal conductivity

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Authors: Omar Bouledroua, Djamel Zelmati, Zahreddine Hafsi, Milos B. Djukic

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Transporting hydrogen gas through the existing natural gas pipeline network offers an efficient solution for energy storage and conveyance. Hydrogen generated from excess renewable electricity can be conveyed through the API 5L steel-made pipelines that already exist. In recent years, there has been a growing demand for the transportation of hydrogen through existing gas pipelines. Therefore, numerical and experimental tests are required to verify and ensure the mechanical integrity of the API 5L steel pipelines that will be used for pressurized hydrogen transportation. Internal pressure loading is likely to accelerate hydrogen diffusion through the internal pipe wall and consequently accentuate the hydrogen embrittlement of steel pipelines. Furthermore, pre-cracked pipelines are susceptible to quick failure, mainly under a time-dependent cyclic pressure loading that drives fatigue crack propagation. Meanwhile, after several loading cycles, the initial cracks will propagate to a critical size. At this point, the remaining service life of the pipeline can be estimated, and inspection intervals can be determined. This paper focuses on the hydrogen embrittlement of API 5L steel-made pipeline under cyclic pressure loading. Pressurized hydrogen gas is transported through a network of pipelines where demands at consumption nodes vary periodically. The resulting pressure profile over time is considered a cyclic loading on the internal wall of a pre-cracked pipeline made of API 5L steel-grade material. Numerical modeling has allowed the prediction of fatigue crack evolution and estimation of the remaining service life of the pipeline. The developed methodology in this paper is based on the ASME B31.12 standard, which outlines the guidelines for hydrogen pipelines.

Keywords: hydrogen embrittlement, pipelines, transient flow, cyclic pressure, fatigue crack growth

Procedia PDF Downloads 92

Authors: Mauro Iannazzone, Carmine D'Agostino

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Off-shore wind turbines are currently considered as a reliable source of renewable energy Worldwide and especially in the UK. Most of the operational off-shore wind turbines located in shallow waters (i.e. < 30 m) are supported on monopiles. Monopiles are open-ended steel tubes with diameter ranging between 4 to 6 m. It is expected that future off-shore wind farms will be located in water depths as high as 70 m. Therefore, alternative foundation arrangements are needed. Foundations for off-shore structures normally consist of open-ended piles driven into the soil by means of impact hammers. During pile installation, the soil inside the pile may be mobilized by the increasing shear strength such as to prevent more soil from entering the pile. This phenomenon is known as soil plugging, and represents an important issue as it may change significantly the driving resistance of open-ended piles. In fact, if the plugging formation is unexpected, the installation may require more powerful and more expensive hammers. Engineers need to estimate whether the driven pile will be installed in a plugged or unplugged mode. As a consequence, a prediction of the degree of soil plugging is required in order to correctly predict the drivability of the pile. This work presents a brief review of the state-of-the-art of pile driving and approaches used to predict formation of soil plugs. In addition, a novel analytical approach is proposed, which is based on the vertical equilibrium of a plugged pile. Differently from previous studies, this research takes into account the enhancement of the stress within the soil plug. Finally, the work presents and discusses a series of experimental tests, which are carried out on small-scale models piles to validate the analytical solution.

Keywords: off-shore wind turbines, pile installation, soil plugging, wind energy

Procedia PDF Downloads 313

Authors: Pranab Kumar Goswami, Elena Gurung

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Small and medium enterprises (SME) are considered as the driving force for the economic growth of a developing country like India. Most of the SMEs are located in residential/non-industrial areas to avoid legal obligations of occupational safety and health (OSH) provisions. This study was conducted in Delhiwith a view to analyze the accidents that occurredduringthe year 2019 & 2020. The objective of the study was to find out the accident prone SMEs in Delhi and major causes of such accidents. Methods: Survey and comprehensive data analysis methods, followed by applying simple statistical techniques, were used for this study. The accident reports for the study period collected from the labour department and police stations were analyzed for the study. The injured workers were interviewed to ascertain safety compliances, training and awareness programs, etc. The study was completed in March2021. Results: It was found that most of the accidents took place in SMEs located in residential/non- industrial areas in Delhi. The accident-prone machines were found to be power presses (42%) and injection moulding machines (37%). Predominantly unsafe machinery or unsafe working conditions and lack of training of worker were observed to be the major causes of accidents in such industries. Conclusions: It was concluded from the study that unsafe machinery/equipment and lack of proper training to the workers were two main reasons for increase in accidents.It was also concluded that the industries located in industrial areas were better placed in terms of workplace compliances. The managements who were running their operations from residential/non-industrial areaswere found to be less aware on health and safety issues. Lack of enforcement by government agencies in such areas has escalated this problem. Adequate training to workers, managing safe & healthy workplace, and sustained enforcement can reduce accidents in such industries.

Keywords: SME, accident prevention, cause of accident, unorganised

Procedia PDF Downloads 102

Authors: Levente Kovács, Fruzsina Luca Kézér, Ottó Szenci

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Prediction of the onset of calving and recognizing difficulties at calving has great importance in decreasing neonatal losses and reducing the risk of health problems in the early postpartum period. In this study, changes of rumination time, reticuloruminal pH and temperature were investigated in eutocic (EUT, n = 10) and dystocic (DYS, n = 8) dairy cows around parturition. Rumination time was continuously recorded using an acoustic biotelemetry system, whereas reticuloruminal pH and temperature were recorded using an indwelling and wireless data transmitting system. The recording period lasted from 3 d before calving until 7 days in milk. For the comparison of rumination time and reticuloruminal characteristics between groups, time to return to baseline (the time interval required to return to baseline from the delivery of the calf) and area under the curve (AUC, both for prepartum and postpartum periods) were calculated for each parameter. Rumination time decreased from baseline 28 h before calving both for EUT and DYS cows (P = 0.023 and P = 0.017, respectively). After 20 h before calving, it decreased onwards to reach 32.4 ± 2.3 and 13.2 ± 2.0 min/4 h between 8 and 4 h before delivery in EUT and DYS cows, respectively, and then it decreased below 10 and 5 min during the last 4 h before calving (P = 0.003 and P = 0.008, respectively). Until 12 h after delivery rumination time reached 42.6 ± 2.7 and 51.0 ± 3.1 min/4 h in DYS and EUT dams, respectively, however, AUC and time to return to baseline suggested lower rumination activity in DYS cows than in EUT dams for the 168-h postpartum observational period (P = 0.012 and P = 0.002, respectively). Reticuloruminal pH decreased from baseline 56 h before calving both for EUT and DYS cows (P = 0.012 and P = 0.016, respectively), but did not differ between groups before delivery. In DYS cows, reticuloruminal temperature decreased from baseline 32 h before calving by 0.23 ± 0.02 °C (P = 0.012), whereas in EUT cows such a decrease was found only 20 h before delivery (0.48 ± 0.05 °C, P < 0.01). AUC of reticuloruminal temperature calculated for the prepartum period was greater in EUT cows than in DYS cows (P = 0.042). During the first 4 h after calving, it decreased from 39.7 ± 0.1 to 39.00 ± 0.1 °C and from 39.8 ± 0.1 to 38.8 ± 0.1 °C in EUT and DYS cows, respectively (P < 0.01 for both groups) and reached baseline levels after 35.4 ± 3.4 and 37.8 ± 4.2 h after calving in EUT and DYS cows, respectively. Based on our results, continuous monitoring of changes in rumination time and reticuloruminal temperature seems to be promising in the early detection of cows with a higher risk of dystocia. Depressed postpartum rumination time of DYS cows highlights the importance of the monitoring of cows experiencing difficulties at calving.

Keywords: reticuloruminal pH, reticuloruminal temperature, rumination time, dairy cows, dystocia

Procedia PDF Downloads 316

Authors: N. D. Iswarya, M. A. Maluk Mohamed, N. Vijaya

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Grid is infrastructure that allows the deployment of distributed data in large size from multiple locations to reach a common goal. Scheduling data intensive applications becomes challenging as the size of data sets are very huge in size. Only two solutions exist in order to tackle this challenging issue. First, computation which requires huge data sets to be processed can be transferred to the data site. Second, the required data sets can be transferred to the computation site. In the former scenario, the computation cannot be transferred since the servers are storage/data servers with little or no computational capability. Hence, the second scenario can be considered for further exploration. During scheduling, transferring huge data sets from one site to another site requires more network bandwidth. In order to mitigate this issue, this work focuses on incorporating cognitive science in scheduling. Cognitive Science is the study of human brain and its related activities. Current researches are mainly focused on to incorporate cognitive science in various computational modeling techniques. In this work, the problem solving approach of human brain is studied and incorporated during the data intensive scheduling in grid environments. Here, a cognitive engine is designed and deployed in various grid sites. The intelligent agents present in CE will help in analyzing the request and creating the knowledge base. Depending upon the link capacity, decision will be taken whether to transfer data sets or to partition the data sets. Prediction of next request is made by the agents to serve the requesting site with data sets in advance. This will reduce the data availability time and data transfer time. Replica catalog and Meta data catalog created by the agents assist in decision making process.

Keywords: data grid, grid workflow scheduling, cognitive artificial intelligence

Procedia PDF Downloads 395

Authors: Victor Toom

Abstract:

Albeit it is never possible to anticipate the full range of difficulties after a catastrophe, efforts to identify victims of mass casualty events have become institutionalized and standardized with the aim of effectively and efficiently addressing the many challenges and contingencies. Such ‘disaster victim identification’ (DVI) practices are dependent on the forensic sciences, are subject of national legislation, and are reliant on technical and organizational protocols to mitigate the many complexities in the wake of catastrophe. Apart from such technological, legal and bureaucratic elements constituting a DVI operation, victims’ families and their emotions are also part and parcel of any effort to identify casualties of mass human fatality incidents. Take for example the fact that forensic experts require (antemortem) information from the group of relatives to make identification possible. An identified body or body part is also repatriated to kin. Relatives are thus main stakeholders in DVI operations. Much has been achieved in years past regarding facilitating victims’ families’ issues and their emotions. Yet, how families are dealt with by experts and authorities is still considered a difficult topic. Due to sensitivities and required emphatic interaction with families on the one hand, and the rationalized DVI efforts, on the other hand, there is still scope for improving communication, providing information and meaningful inclusion of relatives in the DVI effort. This paper aims to bridge the standardized world of DVI efforts and families’ experienced realities and makes suggestions to further improve DVI efforts through inclusion of victims’ families. Based on qualitative interviews, the paper narrates involvement and experiences of inter alia DVI practitioners, victims’ families, advocates and clergy in the wake of the 1995 Srebrenica genocide which killed approximately 8,000 men, and the 9/11 in New York City with 2,750 victims. The paper shows that there are several models of including victims’ families into a DVI operation, and it argues for a model of where victims’ families become a partner in DVI operations.

Keywords: disaster victim identification (DVI), victims’ families, social science (qualitative), 9/11 attacks, Srebrenica genocide

Procedia PDF Downloads 232

Authors: Didier Auroux, Vladimir Groza

Abstract:

This work is part of STEEP Marie-Curie ITN project, and it focuses on the identification of unknown parameters of the proposed generic Abrasive WaterJet Milling (AWJM) PDE model, that appears as an ill-posed inverse problem. The necessity of studying this problem comes from the industrial milling applications where the possibility to predict and model the final surface with high accuracy is one of the primary tasks in the absence of any knowledge of the model parameters that should be used. In this framework, we propose the identification of model parameters by minimizing a cost function, measuring the difference between experimental and numerical solutions. The adjoint approach based on corresponding Lagrangian gives the opportunity to find out the unknowns of the AWJM model and their optimal values that could be used to reproduce the required trench profile. Due to the complexity of the nonlinear problem and a large number of model parameters, we use an automatic differentiation software tool (TAPENADE) for the adjoint computations. By adding noise to the artificial data, we show that in fact the parameter identification problem is highly unstable and strictly depends on input measurements. Regularization terms could be effectively used to deal with the presence of data noise and to improve the identification correctness. Based on this approach we present results in 2D and 3D of the identification of the model parameters and of the surface prediction both with self-generated data and measurements obtained from the real production. Considering different types of model and measurement errors allows us to obtain acceptable results for manufacturing and to expect the proper identification of unknowns. This approach also gives us the ability to distribute the research on more complex cases and consider different types of model and measurement errors as well as 3D time-dependent model with variations of the jet feed speed.

Keywords: Abrasive Waterjet Milling, inverse problem, model parameters identification, regularization

Procedia PDF Downloads 317

Authors: Farida Ibrahim

Abstract:

Right to information is the public's right to know through having access to public information held by state bodies. Recognized as a cornerstone in transparent, participatory and open democracies, the right to information is increasingly perceived today as an emerging human right on the international level. While this right is conceptualized in a range of different contexts, the paper focuses on its conceptualization as a force for socio-economic change for disadvantaged groups. The paper's goal is study the instrumental capacity of this right in empowering the public to access state-held information pertinent to their socio-economic rights. In this regard, the paper views the right to information as an inclusionary tool that is capable of spurring inclusion for individuals excluded from the ambits of both: public participation and social justice. For exploring this, the paper examines the advocacy role played by civil society groups in furthering this instrumental capacity. In particular, the paper presents a focused account on the Egyptian case. While Egypt has recently adopted its constitutional provision on access to information, doubts arise on Egyptian citizens' genuine ability to access information held by state bodies. The politico-economic environment, long term culture of bureaucratic secrecy, and legal framework do not provide promising outcomes on access to public information. Within the particular context of the Egyptian case, this paper questions the extent to which civil society in Egypt is capable of instrumentally employing the political opportunity offered by the constitutional entitlement to information access for pressuring public authorities to disclose information. Through four lawsuits brought by civil society groups in Egypt, the paper argues that the right to information has instrumentally provided civil society actors with new domains of mobilization for furthering the realization of social and economic rights, and ultimately, for renegotiating a new social order lining the relationship between the Egyptian state and its citizens marginalized by socio-economic imbalances.

Keywords: civil society, Egypt, right to information, socio-economic rights

Procedia PDF Downloads 282