Access to information and the role of environmental assessment registries for public participation

International practice shows an increasing use of web-based Environmental Assessment (EA) registries or project websites to provide public access to information. In support of statutory public participation, registries inform when to participate and provide relevant documents and the continued availability of information. However, what constitutes good practice in this field? This article proposes a framework for assessing good practice in providing access to information via registries. Based on performance indicators for an ‘ideal’ registry, the framework allows evaluation in the review categories: framework conditions, notice of projects, provision of documents, accessibility of information and ongoing information regarding the status of the environmental assessment. An explorative case study analysis applies the framework and presents results on the performance of international practice examples

Business intelligence framework using ant colony optimization for feature selection in higher education institution

Recently, business intelligence (BI) has become an important tool for effective decision-making. BI is a mathematical framework to gain information and knowledge through the process of extracting, transforming, managing, and analyzing data. The demand for accurate knowledge in higher education sector needs a correct technique to extract the exact information for decision-making. However, current BI frameworks and systems lack the ability to transform data into information, and these caused users not to able to fully utilize the BI outcome. This research developed a BI framework for the higher education that is able to explore, analyse and visualize the relevant data into information for use by the top management. This framework identifies the best set of attributes and evaluates the performance of the model with the help of 27 input features. In this case study, the framework used Ant Colony Optimization (ACO) technique mainly to identify the best set of attributes, and the performance was validated using Support Vector Machine (SVM). The framework consists of four layers which are data source, data integration, analytic, and access. Each layer contributes to decision making in terms of processing data, selection of significant features and data visualization. In this study, 46,658 input data were processed for identification of Graduate on Time (GOT) decision in the context of higher education referred as Masters and Doctor of Philosophy (PhD) postgraduates who completed their study within a specified period. The performance evaluation of the data achieved accuracies of 86.44% for PhD and 96.2% for Master’s. Based on the findings, the results showed that the BI dashboard as an output from the framework is capable of providing a good decision-making tool for education management

Disability issues, trends and recommendations for the World Bank

This paper is intended to provide the World Bank with the information, and insights necessary for policy formulation, and strategic planning in the area of disability. After describing the two major contemporary disability definitions, and comparing their suitability for disability policy, and planning, the paper presents a descriptive analysis of the evolution, and current status of disability policy, and practice. Based on this information, a political and economic case is made in favor of investing public, and private resources, including World Bank resources, in policies and strategies designed to increase access for people with disabilities to social, and economic opportunities. The essential elements of such policies, and strategies are then described, and incorporated into a strategic framework for possible use by the World Bank in its ongoing effort to develop appropriate, and cost-effective approaches to disability.Health Monitoring&Evaluation,Social Protections&Assistance,Social Cohesion,Gender and Law,Work&Working Conditions

Nagro, S. and Campion, R. (2015) Research and Development of Methodology, Tools, Techniques and Methods to Analyze and Design Interface, Media, Pedagogy for Educational Topics to be Delivered via Mobile Technology, ICMBE 2015, 17th International Conference on Medical and Biomedical Engineering, Istanbul, July 18-19.

Mobile devices are becoming ever more widely available, with growing functionality, and they are increasingly used as enabling technology to give students access to educational material anytime and anywhere. However, the design of educational material's user interfaces for mobile devices is beset by many unresolved research problems such as those arising from constraints associated with mobile devices or from issues linked to effective learning. The proposed research aims to produce: (i) a method framework for the design and evaluation of educational material’s interfaces to be delivered on mobile devices, in multimedia form based on Human Computer Interaction strategies; and (ii) a software tool implemented as a fast-track alternative to use the method framework in full. The investigation will combine qualitative and quantitative methods, including interviews and questionnaires for data collection and three case studies for validating the method framework. The method framework is a framework to enable an educational designer to effectively and efficiently create educational multimedia interfaces to be used on mobile devices by following a particular methodology that contains practical and usable tools and techniques. It is a method framework that accepts any educational material in its final lesson plan and deals with this plan as a static element, it will not suggest any changes in any information given in the lesson plan but it will help the instructor to design his final lesson plan in a multimedia format to be presented in mobile devices

The orchestration of Machine Learning frameworks with datastreams and GPU acceleration in Kafka-ML: A deep-learning performance comparative

Machine Learning (ML) applications need large volumes of data to train their modelsso that they can make high-quality predictions. Given digital revolution enablers suchas the Internet of Things (IoT) and the Industry 4.0, this information is generated inlarge quantities in terms of continuous data streams and not in terms of staticdatasets as it is the case with most AI (Artificial Intelligence) frameworks. Kafka-ML isa novel open-source framework that allows the complete management of ML/AIpipelines through data streams. In this article, we present new features for the Kafka-ML framework, such as the support for the well-known ML/AI framework PyTorch,as well as for GPU acceleration at different points along the pipeline. This pipelinewill be described by taking a real Industry 4.0 use case in the Petrochemical Industry.Finally, a comprehensive evaluation with state-of-the-art deep learning models willbe carried out to demonstrate the feasibility of the platform.Funding for open access charge: Universidad de Málaga / CBUA Consejería de Economía, Innovación, Ciencia y Empleo, Junta de Andalucía; European Commission; Ministerio de Ciencia, Innovación y Universidades. This work is funded by the Spanish projects RT2018-099777-B-100 (‘rFOG: Improving Latency and Reliability of Offloaded Computation to theFOG for Critical Services’), PY20_00788 (‘IntegraDos: Providing Real-Time Services for the Internet of Things through Cloud Sensor Integration’),TSI-063000-2021-116 (‘Digital vertical twins for B5G/6G networks’), TED2021-130167B-C33 (‘GEDIER: Application of Digital Twins to moresustainable irrigated farms’), and CPP2021-009032(‘ZeroVision: Enabling Zero impact wastewater treatment through Computer Vision and Fed-erated AI’); and the European project LIFEWATCH-2019-11-UMA-01-BD (‘EnBiC2-Lab - Environmental and Biodiversity Climate Change Lab’).This project has received funding from the European Union's Horizon Europe research and innovation proframme under the Marie Skłodowska-Curie grant agreement No 101086218. Funding for open access charge: Universidad de Málaga / CBUA

Information security threat assessment using social engineering in the organizational context: literature review

Trabalho apresentado em WorldCist'22 - 10th World Conference on Information Systems and Technologies, 12-14 abril 2022, Budva, MontenegroDue to the value and diversity of data that organizations use and pro duce in their activity, it is extremely important to protect this asset. Security flaws can arise due to several factors and whenever it is difficult to access the desired information because of technological barriers. In this case, attacks are redirected to the exploitation of human beings vulnerabilities through various techniques. The objective of this work focuses on literature review, studying the underlying theme of Social Engineering, as it uses human trust, convincing someone of something fake, using various interactions and different vectors to gain access to private information. Design Science Research will support the research work due to the possibility of construction, evaluation, and subsequent validation of the artefact. The contribution of a framework proposal for preventing social engi neering attacks in organizations and providing the best recommendations, guid ing, and supporting the stakeholders in the selection and definition of controls that guarantee the security of organizational information and avoid possible at tacks by Social Engineering. It is expected that the practical effects of the future work will result in a reduction in the number of attacks using Social Engineering, greater individual and collective preparation to deal with this problem and, over time, the incentive to the continued expansion of the adoption of these artefacts at the organizational level.N/

Exploring the Relationship Between Civil Legal Assistance and the Outcomes of Domestic and Intimate Partner Violence Victims: A Literature Review

While there are a variety of services available to victims of Domestic and Intimate Partner Violence, the civil legal needs of victims often go unmet. In addition to this, these is a relatively small body of research from which programs that provide civil legal aid can discover best practices and use evidence-based approaches. This article aims to begin addressing these issues by examining available literature and program evaluations, connecting program factors to client outcomes. The two main conclusions found from the evaluation are that full representation provides the most benefits and that the type of law being practiced (i.e. protective order, custody, etc.) has little to no effect on outcomes. While these findings begin to provide vague direction concerning best practices for DV and IPV civil legal assistance services, another important finding to note is that there is a general lack of information concerning this topic. In response to this, I provide rudimentary recommendations for an open access case tracking framework that programs could utilize to improve data availability