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We have developed in this paper a morphological disambiguation hybrid system for the Arabic language that identifies the stem, lemma and root of a given sentence words. Following an out-of-context analysis performed by the morphological analyser Alkhalil Morpho Sys, the system first identifies all the potential tags of each word of the sentence. Then, a disambiguation phase is carried out to choose for each word the right solution among those obtained during the first phase. This problem has been solved by equating the disambiguation issue with a surface optimization problem of spline functions. Tests have shown the interest of this approach and the superiority of its performances compared to those of the state of the art.

Purpose – This study aims to determine the roles of technology trough digital democracy in younger generation’s political education.

Design/Methodology/Approach – The language is analyzed using the theory of generative morphology which is developed by Morris Hale, Aronoff, Scalise, and Dardjowidjojo. The basic theory is the word formation through affixation process.

Findings – It is found that Devayan belongs to agglitunative-type language. Therefore, this language forms its words using prefixes, infixes, and suffixes by managing the process of morphemes compounding in order to get actual and potential words. Potential word formation is classified as language units that do not exist in reality.

Research Limitations/Implications – This research limits the scope of attention only on the morphological process.

Originality/Value – The findings can be used as references for those concerns in the revitalization of this minority language in the effort of composing a dictionary of Devayan.

Surveillance is the emerging concept in the current technology, as it plays a vital role in monitoring keen activities at the nooks and corner of the world. Among which moving object identifying and tracking by means of computer vision techniques is the major part in surveillance. If we consider moving object detection in video analysis is the initial step among the various computer applications. The main drawbacks of the existing object tracking method is a time-consuming approach if the video contains a high volume of information. There arise certain issues in choosing the optimum tracking technique for this huge volume of data. Further, the situation becomes worse when the tracked object varies orientation over time and also it is difficult to predict multiple objects at the same time. In order to overcome these issues here, we have intended to propose an effective method for object detection and movement tracking. In this paper, we proposed robust video object detection and tracking technique. The proposed technique is divided into three phases namely detection phase, tracking phase and evaluation phase in which detection phase contains Foreground segmentation and Noise reduction. Mixture of Adaptive Gaussian (MoAG) model is proposed to achieve the efficient foreground segmentation. In addition to it the fuzzy morphological filter model is implemented for removing the noise present in the foreground segmented frames. Moving object tracking is achieved by the blob detection which comes under tracking phase. Finally, the evaluation phase has feature extraction and classification. Texture based and quality based features are extracted from the processed frames which is given for classification. For classification we are using J48 ie, decision tree based classifier. The performance of the proposed technique is analyzed with existing techniques k-NN and MLP in terms of precision, recall, f-measure and ROC.

The purpose of this paper is to enlarge the body of knowledge on research through design (RtD) methods that can be employed by landscape architects and others working on (but not limited to) sustainable energy transition.

A specific approach to RtD – qualitative landscape structure analysis (QLSA) – is introduced and illustrated by means of diagrams and photographs. Two case studies showcase the application of QLSA for research on solar parks in the Netherlands and research on wind turbines in the Alpine foothills in Southern Germany.

The case studies show how RtD can help to define design principles for large solar parks and arrangement of wind turbines in particular landscape types in the Netherlands and Germany, respectively. In doing so, RtD can help to expand the breadth of spatial research beyond well-established methods such as multi-criteria decision analysis and environmental impact assessment.

The paper provides insights into contemporary RtD in two countries and affirms the importance of such research with regard to landscape transformations while starting to define a research niche for landscape architects and other environmental designers working on the topic of sustainable energy transition.

Effective rail surface defects detection method is the basic guarantee to manufacture high-quality rail. However, the existed visual inspection methods have disadvantages such as poor ability to locate the rail surface region and high sensitivity to uneven reflection. This study aims to propose a bionic rail surface defect detection method to obtain the high detection accuracy of rail surface defects under uneven reflection environments.

Through this bionic rail surface defect detection algorithm, the positioning and correction of the rail surface region can be computed from maximum run-length smearing (MRLS) and background difference. A saliency image can be generated to simulate the human visual system through some features including local grayscale, local contrast and edge corner effect. Finally, the meanshift algorithm and adaptive threshold are developed to cluster and segment the saliency image.

On the constructed rail defect data set, the bionic rail surface defect detection algorithm shows good recognition ability on the surface defects of the rail. Pixel- and defect-level index in the experimental results demonstrate that the detection algorithm is better than three advanced rail defect detection algorithms and five saliency models.

The bionic rail surface defect detection algorithm in the production process is proposed. Particularly, a method based on MRLS is introduced to extract the rail surface region and a multifeature saliency fusion model is presented to identify rail surface defects.

This article sets out to show how principles and questions about method that underlie a way of interpreting the discipline of conservation and restoration can find results in research and studies, aiming at achieving even conscious reuse process. The occasion is the very recent research performed on the former Church of Saints Gerolamo and Francesco Saverio in Genoa, Italy, the Jesuit church annexed to the 17th-century College of the order. It is a small Baroque jewel in the heart of the ancient city, former University Library and actually abandoned, forgotten for years, inaccessible and awaiting a new use.

The two-year work carried out on the monumental building was conducted according to a study and research methodology developed and refined over the years within the activities of the School of Specialisation in Architectural Heritage and Landscape of the University of Genoa. It is a multidisciplinary and rigorous approach, which aims to train high-level professionals, up-to-date and aware of the multiple problems that interventions on existing buildings, especially of a monumental nature, involve.

The biennal study has been carried out within the activities of the Post-Graduate Programme in Architectural Heritage and Landscape of the University of Genoa. The work methodology faces the challenges of the contemporary complexity, raised by the progressive broadening of the concept of cultural “heritage” and by the problems of its conservation, its active safeguard and its reuse: safety in respect of seismic risk, fire and hydro geological instability, universal accessibility – cognitive, physical and alternative – resource efficiency, comfort and savings in energy consumption, sustainability, communication and involvement of local communities and stakeholders.

The goals of the work were the following: understanding of the architectural heritage, through the correlated study of its geometries, elements and construction materials, surfaces, structures, spaces and functions; understanding of the transformations that the building has undergone over time, relating the results of historical reconstructions from indirect sources and those of direct archaeological analysis; assessment of the state of conservation of the building recognising phenomena of deterioration, damage, faults and deficits that affect materials, construction elements, systems and structures; identification of the causes and extent of damage, faults and deficits, assessing the vulnerability and level of exposure of the asset to the aggression of environmental factors and related risks; evaluation of the compatibility between the characteristics of the available spaces, the primary needs of conservation, the instance of regeneration and possible new uses; the definition of criteria and guidelines for establishing the planning of conservation, restoration and redevelopment interventions.

Worldwide, natural hazards are affecting urban cultural heritage and World Heritage Sites, exacerbating other environmental and human-induced threats deriving from deterioration, uncontrolled urbanization and unsustainable tourism. This paper aims to develop a disaster risk analysis in Italian historic centers because they are complex large-scale systems that are cultural and economic resources for the country, as well as fragile areas.

A heritage-oriented qualitative methodology for risk assessment is proposed based upon the formalization of risk as a function of hazard, vulnerability and exposure, taking into account the values of cultural heritage assets.

This work provides a contribution to the body of knowledge in the Italian context of disaster risk mitigation on World Heritage Sites, opening for further research on the monitoring and maintenance of the tangible heritage assets. The application to the site of San Gimignano proves the effectiveness of the methodology for proposing preventive measures and actions that ensure the preservation of cultural values and a safer built environment.

The application of a value-based simplified approach to risk analysis is a novelty for historic centers that are listed as World Heritage Sites.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.

The purpose of this paper is to study the organizational processes in co-creation with multiple stakeholders within the scope of innovation networks. It consists of analyzing the necessary adaptation of organizational processes and to structure a proposal of an integrated process.

This paper is a review article, an analysis of relevant articles in the areas of co-creation with multiple stakeholders, innovation networks, dynamic capabilities and organizational aspects linked to network organization which reflect on the main differences by relating them to the relevant literature.

Identification of related processes: Innovation development, knowledge integration/sharing, Co-evolution, Value Co-creation, Value Capture, Stakeholders capabilities, and elements of an integrated process in an innovation network.

Proposition of an integrated co-creation process with multiple stakeholders in an innovation network based on dynamic capabilities with the elements of literature and an analysis of the model variables. This process makes it possible, before reconfiguring the network itself, to create and to define the Project in an integrated manner. They also promote an evolution in the commitment, in the relationship and in the sharing of knowledge among the stakeholders and in the anticipation and evaluation by the stakeholders.

This paper purposed a multi-facet sentiment analysis system.

Hence, This paper uses multidomain resources to build a sentiment analysis system. The manual lexicon based features that are extracted from the resources are fed into a machine learning classifier to compare their performance afterward. The manual lexicon is replaced with a custom BOW to deal with its time consuming construction. To help the system run faster and make the model interpretable, this will be performed by employing different existing and custom approaches such as term occurrence, information gain, principal component analysis, semantic clustering, and POS tagging filters.

The proposed system featured by lexicon extraction automation and characteristics size optimization proved its efficiency when applied to multidomain and benchmark datasets by reaching 93.59% accuracy which makes it competitive to the state-of-the-art systems.

The construction of a custom BOW. Optimizing features based on existing and custom feature selection and clustering approaches.