Search results for: structural approach

Authors: Mateen A Khan, Taj Mohammad, Md. Imtaiyaz Hassan

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Alzheimer’s disease is characterized by the accumulation of the processing products of the amyloid beta peptide cleaved by amyloid precursor protein (APP). Iron increases the synthesis of amyloid beta peptides, which is why iron is present in Alzheimer's disease patients' amyloid plaques. Iron misregulation in the brain is linked to the overexpression of APP protein, which is directly related to amyloid-β aggregation in Alzheimer’s disease. The APP 5'-UTR region encodes a functional iron-responsive element (IRE) stem-loop that represents a potential target for modulating amyloid production. Targeted regulation of APP gene expression through the modulation of 5’-UTR sequence function represents a novel approach for the potential treatment of AD because altering APP translation can be used to improve both the protective brain iron balance and provide anti-amyloid efficacy. The molecular docking analysis of APP IRE RNA with eukaryotic translation initiation factors yields several models exhibiting substantial binding affinity. The finding revealed that the interaction involved a set of functionally active residues within the binding sites of eIF4F. Notably, APP IRE RNA and eIF4F interaction were stabilized by multiple hydrogen bonds with residues of APP IRE RNA and eIF4F. It was evident that APP IRE RNA exhibited a structural complementarity that tightly fit within binding pockets of eIF4F. The simulation studies further revealed the stability of the complexes formed between RNA and eIF4F, which is crucial for assessing the strength of these interactions and subsequent roles in the pathophysiology of Alzheimer’s disease. In addition, MD simulations would capture conformational changes in the IRE RNA and protein molecules during their interactions, illustrating the mechanism of interaction, conformational change, and unbinding events and how it may affect aggregation propensity and subsequent therapeutic implications. Our binding studies correlated well with the translation efficiency of APP mRNA. Overall, the outcome of this study suggests that the genomic modification and/or inhibiting the expression of amyloid protein by targeting APP IRE RNA can be a viable strategy to identify potential therapeutic targets for AD and subsequently be exploited for developing novel therapeutic approaches.

Keywords: Alzheimer's disease, Protein-RNA interaction analysis, molecular docking simulations, conformational dynamics, binding stability, binding kinetics, protein synthesis.

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Authors: Tsegahun Manyazewal, Francesco Marinucci, Getachew Belay, Abraham Tesfaye, Gonfa Ayana, Amaha Kebede, Tsegahun Manyazewal, Francesco Marinucci, Getachew Belay, Abraham Tesfaye, Gonfa Ayana, Amaha Kebede, Yewondwossen Tadesse, Susan Lehman, Zelalem Temesgen

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In-service health trainings in Sub-Saharan Africa are mostly content-centered with higher disconnection with the real practice in the facility. This study intended to evaluate in-service training approach aimed to strengthen health care human resources. A combined web-based and face-to-face training was designed and piloted in Ethiopia with the diagnosis of tuberculosis. During the first part, which lasted 43 days, trainees accessed web-based material and read without leaving their work; while the second part comprised a one-day hands-on evaluation. Trainee’s competency was measured using multiple-choice questions, written-assignments, exercises and hands-on evaluation. Of 108 participants invited, 81 (75%) attended the course and 71 (88%) of them successfully completed. Of those completed, 73 (90%) scored a grade from A to C. The approach was effective to transfer knowledge and turn it into practical skills. In-service health training should transform from a passive one-time-event to a continuous behavioral change of participants and improvements on their actual work.

Keywords: Ethiopia, health care, Mycobacterium tuberculosis, training

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Authors: Mohd Zamri Che Wanik

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This paper presents the management of the Fault Ride Through event within a Solar Farm during a grid fault. The modeling and simulation of a photovoltaic (PV) with battery energy storage connected to the power network will be described. The modeling approach and the study analysis performed are described. The model and operation scenarios are simulated using a digital simulator for different scenarios. The dynamic response of the system when subjected to sudden self-clearance temporary fault is presented. The capability of the PV system and battery storage riding through the power system fault and, at the same time, supporting the local grid by injecting fault current is demonstrated. For each case, the different control methods to achieve the objective of supporting the grid according to grid code requirements are presented and explained. The inverter modeling approach is presented and described.

Keywords: faut ride through, solar farm, grid code, power network

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Authors: William Creighton, Jan Smitheram

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Queer discourse has been tied to a middle-class, urban-centric, white approach to the discussion of queerness. In doing so, the multilayeredness of queer existence has been washed away in favour of palatable queer occupation. This paper uses design to explore a queer anti-urbanist approach to facilitate a more egalitarian architectural occupancy. Scott Herring’s work on queer anti-urbanism is key to this approach. Herring redeploys anti-urbanism from its historical understanding of open hostility, rejection and desire to destroy the city towards a mode of queer critique that counters normative ideals of homonormative metronormative gay lifestyles. He questions how queer identity has been closed down into a more diminutive frame where those who do not fit within this frame are subjected to persecution or silenced through their absence. We extend these ideas through design to ask how a queer anti-urbanist approach facilitates a more egalitarian architectural occupancy. Following a “design as research” methodology, the design outputs allow a vehicle to ask how we might live, otherwise, in architectural space. A design as research methodologically is a process of questioning, designing and reflecting – in a non-linear, iterative approach – establishes itself through three projects, each increasing in scale and complexity. Each of the three scales tackled a different body relationship. The project began exploring the relations between body to body, body to known others, and body to unknown others. Moving through increasing scales was not to privilege the objective, the public and the large scale; instead, ‘intra-scaling’ acts as a tool to re-think how scale reproduces normative ideas of the identity of space. There was a queering of scale. Through this approach, the results were an installation that brings two people together to co-author space where the installation distorts the sensory experience and forces a more intimate and interconnected experience challenging our socialized proxemics: knees might touch. To queer the home, the installation was used as a drawing device, a tool to study and challenge spatial perception, drawing convention, and as a way to process practical information about the site and existing house – the device became a tool to embrace the spontaneous. The final design proposal operates as a multi-scalar boundary-crossing through “private” and “public” to support kinship through communal labour, queer relationality and mooring. The resulting design works to set adrift bodies in a sea of sensations through a mix of pleasure programmes. To conclude, through three design proposals, this design research creates a relationship between queer anti-urbanism and design. It asserts that queering the design process and outcome allows a more inclusive way to consider place, space and belonging. The projects lend to a queer relationality and interdependence by making spaces that support the unsettled, out-of-place, but is it queer enough?

Keywords: queer, queer anti-urbanism, design as research, design

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Authors: María Araya Léon, Ainoa Abella, Aura Murillo, Ricardo Guasch, Laura Clèries

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Objectives: This article aims to examine scientific theory framed within the term hospitals of the future from a multidisciplinary and cross-sectional perspective. To understand the connection that the various cross-sectional areas we studied have with architectural spaces and to determine the future outlook of the works examined and how they can be classified into the categories of need/solution, evolution/revolution, collective/individual, and preventive/corrective. Background: The changes currently taking place within the context of healthcare demonstrate how important these projects are and the need for companies to face future changes. Method: A systematic review has been carried out focused on what will the hospitals of the future be like in relation to the elements that form part of their use, design, and architectural space experience, using the WOS database from 2016 to 2019. Results: The large number of works about sensoring & big data and the scarce amount related to the area of materials is worth highlighting. Furthermore, no growth concerning future issues is envisaged over time. Regarding classifications, the articles we reviewed address evolutionary and collective solutions more, and in terms of preventive and corrective solutions, they were found at a similar level. Conclusions: Although our research focused on the future of hospitals, there is little evidence representing this approach. We also detected that, given the relevance of the research on how the built environment influences human health and well-being, these studies should be promoted within the context of healthcare.

Keywords: hospitals, future, architectural space, disruptive approach

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Authors: Edward K. Boahen, Brunel E. Bouya-Moko, Changda Wang

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The major threat to online social network (OSN) users is account compromisation. Spammers now spread malicious messages by exploiting the trust relationship established between account owners and their friends. The challenge in detecting a compromised account by service providers is validating the trusted relationship established between the account owners, their friends, and the spammers. Another challenge is the increase in required human interaction with the feature selection. Research available on supervised learning (machine learning) has limitations with the feature selection and accounts that cannot be profiled, like application programming interface (API). Therefore, this paper discusses the various behaviours of the OSN users and the current approaches in detecting a compromised OSN account, emphasizing its limitations and challenges. We propose a deep learning approach that addresses and resolve the constraints faced by the previous schemes. We detailed our proposed optimized nonsymmetric deep auto-encoder (OPT_NDAE) for unsupervised feature learning, which reduces the required human interaction levels in the selection and extraction of features. We evaluated our proposed classifier using the NSL-KDD and KDDCUP'99 datasets in a graphical user interface enabled Weka application. The results obtained indicate that our proposed approach outperformed most of the traditional schemes in OSN compromised account detection with an accuracy rate of 99.86%.

Keywords: computer security, network security, online social network, account compromisation

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Authors: Nico Fuchs, Fabian Wüllhorst, Laura Maier, Dirk Müller

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The decarbonization of building stocks necessitates the modernization of existing buildings. Key measures for this include reducing energy demands through insulation of the building envelope, replacing heat generators, and installing solar systems. Given limited financial resources, it is impractical to modernize all buildings in a portfolio simultaneously; instead, prioritization of buildings and modernization measures for a given planning horizon is essential. Optimization models for modernization pathways can assist portfolio managers in this prioritization. However, modeling and solving these large-scale optimization problems, often represented as mixed-integer problems (MIP), necessitates simplifying the operation of building energy systems particularly with respect to system dynamics and transient behavior. This raises the question of which level of simplification remains sufficient to accurately account for realistic costs and emissions of building energy systems, ensuring a fair comparison of different modernization measures. This study addresses this issue by comparing a two-stage simulation-based optimization approach with a single-stage mathematical optimization in a mixed-integer linear programming (MILP) formulation. The simulation-based approach serves as a benchmark for realistic energy system operation but requires a restriction of the solution space to discrete choices of modernization measures, such as the sizing of heating systems. After calculating the operation of different energy systems in terms of the resulting final energy demands in simulation models on a first stage, the results serve as input for a second stage MILP optimization, where the design of each building in the portfolio is optimized. In contrast to the simulation-based approach, the MILP-based approach can capture a broader variety of modernization measures due to the efficiency of MILP solvers but necessitates simplifying the building energy system operation. Both approaches are employed to determine the cost-optimal design and dimensioning of several buildings in a portfolio to meet climate targets within limited yearly budgets, resulting in a modernization pathway for the entire portfolio. The comparison reveals that the MILP formulation successfully captures design decisions of building energy systems, such as the selection of heating systems and the modernization of building envelopes. However, the results regarding the optimal dimensioning of heating technologies differ from the results of the two-stage simulation-based approach, as the MILP model tends to overestimate operational efficiency, highlighting the limitations of the MILP approach.

Keywords: building energy system optimization, model accuracy in optimization, modernization pathways, building stock decarbonization

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Authors: Nicholas Fletcher, Zachary Houston, Yongmei Zhao, Christopher Howard, Kristofer Thurecht

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One promising approach to enhance nanomedicine therapeutic efficacy is to include a targeting agent, such as an antibody, to increase accumulation at the tumor site. However, the application of such targeted nanomedicines remains limited, in part due to difficulties involved with biomolecule conjugation to synthetic nanomaterials. One approach recently developed to overcome this has been to engineer bispecific antibodies (BsAbs) with dual specificity, whereby one portion binds to methoxy polyethyleneglycol (mPEG) epitopes present on synthetic nanomedicines, while the other binds to molecular disease markers of interest. In this way, noncovalent complexes of nanomedicine core, comprising a hyperbranched polymer (HBP) of primarily mPEG, decorated with targeting ligands are able to be produced by simple mixing. Further work in this area has now demonstrated such complexes targeting the breast cancer marker epidermal growth factor receptor (EGFR) to show enhanced binding to tumor cells both in vitro and in vivo. Indeed the enhanced accumulation at the tumor site resulted in improved therapeutic outcomes compared to untargeted nanomedicines and free chemotherapeutics. The current work on these BsAb-HBP conjugates focuses on further probing antibody-nanomaterial interactions and demonstrating broad applicability to a range of cancer types. Herein are reported BsAb-HBP materials targeted towards prostate-specific membrane antigen (PSMA) and study of their behavior in vivo using ⁸⁹Zr positron emission tomography (PET) in a dual-tumor prostate cancer xenograft model. In this model mice bearing both PSMA+ and PSMA- tumors allow for PET imaging to discriminate between nonspecific and targeted uptake in tumors, and better quantify the increased accumulation following BsAb conjugation. Also examined is the potential for formation of these targeted complexes in situ following injection of individual components? The aim of this approach being to avoid undesirable clearance of proteinaceous complexes upon injection limiting available therapeutic. Ultimately these results demonstrate BsAb functionalized nanomaterials as a powerful and versatile approach for producing targeted nanomedicines for a variety of cancers.

Keywords: bioengineering, cancer, nanomedicine, polymer chemistry

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Authors: I. Bouhaf Kharkhachi, A. Attaf

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Tin sulfide thin films on glass substrate were prepared by spray ultrasonic technique, at different experimental conditions. The influence of deposition time (2, 4, 6, 8 and 10 min) on different properties of thin films, such us, (XRD) and (UV) spectroscopy visible spectrum was investigated. X-ray diffraction showing that thin films crystallized in SnS, SnS2, and Sn2S3 phases. The results of (UV) spectroscopy visible spectrum show that films deposited at 4 min are large transmittance 60% in the visible region.

Keywords: SnS, thin films, ultrasonic spray, X-ray diffraction, UV spectroscopy visible

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Authors: Kapila Warnakulasuriya, Walimuni Janaka Mendis

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In this study, an artificial intelligence-based approach is developed to diagnose abnormal tissues in human or animal bodies by analyzing magnetic resonance signals. As opposed to the conventional method of generating an image from the magnetic resonance signals, which are then evaluated by a radiologist for the diagnosis of abnormalities, in the discussed approach, the magnetic resonance signals are analyzed by an artificial intelligence algorithm without having to generate or analyze an image. The AI-based program compares magnetic resonance signals with millions of possible magnetic resonance waveforms which can be generated from various types of normal tissues. Waveforms generated by abnormal tissues are then identified, and images of the abnormal tissues are generated with the possible location of them in the body for further diagnostic tests.

Keywords: magnetic resonance, artificial intelligence, magnetic waveform analysis, abnormal tissues

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Authors: De Castro-Pardo M., Cabello J. M., Martin J. M., Ruiz F.

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In this paper, we propose a new Water Sustainability Indicator based on a Multi-Reference methodology that permits modeling compensation between the analysed criteria and provides a participative approach. The proposed indicator provides results based on 19 variables grouped into 5 dimensions: availability, access, resilience, good governance and economic capacity. The indicator was applied to assess water sustainability in 27 European countries. The results showed that Finland, the Netherlands, Sweden and the United Kingdom obtained the best global results in terms of weak water (compensatory) sustainability. In terms of strong water (non-compensatory) sustainability, no country gained acceptable results in terms of strong sustainability. Climate change and the state of freshwater resources were detected as especially vulnerable in all the analysed countries. The results identified some eastern European countries with low GDP and good performance of availability and cost of water, with bad results in terms of governance and water productivity. These results could jeopardize water sustainability in the event of a potential economic development if these limitations are not addressed. In a context of economic and political instability due to the current armed conflict in nearby countries such as Ukraine, it is especially important to pay attention to these countries, whose good governance indicators could worsen even more. The proposed indicator allowed to the identification of warning signs and could contribute to the improvement in decision-making processes. Moreover, it could improve the monitoring of international water policies.

Keywords: water sustainability, composite indicators, compensatory approach, sustainability European policies

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Authors: Noury Bakrim

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Formalization is indeed a foundational Mathematical Linguistics as demonstrated by the pioneering works. While dialoguing with this frame, we nonetheless propone, in our approach of language as a real object, a mathematical linguistics/biosemiotics defined as a dialectical synthesis between induction and computational deduction. Therefore, relying on the parametric interaction of cycles, rules, and features giving way to a sub-hypothetic biological point of view, we first hypothesize a factorial equation as an explanatory principle within Category Mathematics of the Ergobrain: our computation proposal of Universal Grammar rules per cycle or a scalar determination (multiplying right/left columns of the determinant matrix and right/left columns of the logarithmic matrix) of the transformable matrix for rule addition/deletion and cycles within representational mapping/cycle heredity basing on the factorial example, being the logarithmic exponent or power of rule deletion/addition. It enables us to propone an extension of minimalist merge/label notions to a Language Merge (as a computing principle) within cycle recursion relying on combinatorial mapping of rules hierarchies on external Entax of the Event Sequence. Therefore, to define combinatorial maps as language merge of features and combinatorial hierarchical restrictions (governing, commanding, and other rules), we secondly hypothesize from our results feature/hierarchy exponentiation on graph representation deriving from Gromov's Symbolic Dynamics where combinatorial vertices from Fe are set to combinatorial vertices of Hie and edges from Fe to Hie such as for all combinatorial group, there are restriction maps representing different derivational levels that are subgraphs: the intersection on I defines pullbacks and deletion rules (under restriction maps) then under disjunction edges H such that for the combinatorial map P belonging to Hie exponentiation by intersection there are pullbacks and projections that are equal to restriction maps RM₁ and RM₂. The model will draw on experimental biomathematics as well as structural frames with focus on Amazigh and English (cases from phonology/micro-semantics, Syntax) shift from Structure to event (especially Amazigh formant principle resolving its morphological heterogeneity).

Keywords: rule/cycle addition/deletion, bio-mathematical methodology, general merge calculation, feature exponentiation, combinatorial maps, event sequence

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Authors: Syed W. Hasan, Zhiqun Tian

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Wet spinning provides a facile and economic route to fabricate graphene nanofibers (GFs) on mass scale. Nevertheless, the pristine GFs exhibit significantly low electrical and mechanical properties owing to stacked graphene sheets and weak inter-atomic bonding. In this report, we present highly conductive Ag-decorated-GFs (Ag/GFs). The SEM micrographs show Ag nanoparticles (NPs) (dia ~10 nm) are homogeneously distributed throughout the cross-section of the fiber. The Ag NPs provide a conductive network for the electrons flow raising the conductivity to 1.8(10^4) S/m which is 4 times higher than the pristine GFs. Our results surpass the conductivities of graphene fibers doped with CNTs, Nanocarbon, fullerene, and Cu. The chemical and structural attributes of Ag/GFs are further elucidated through XPS, AFM and Raman spectroscopy.

Keywords: Ag nanoparticles, Conductive fibers, Graphene, Wet spinning

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Authors: Faiza Mahi, Fatima Debbat, Mohamed Fayçal Khelfi

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This paper proposes a control approach using Fuzzy Lo system. More precisely, the study focuses on the improvement of users service in terms of analysis and control of a transportation system their waiting times in the exchange platforms of passengers. Many studies have been developed in the literature for such problematic, and many control tools are proposed. In this paper we focus on the use of fuzzy logic technique to control the system during its evolution in order to minimize the arrival gap of connected transportation means at the exchange points of passengers. An example of illustration is worked out and the obtained results are reported. an important area of research is the modeling and simulation ordering system. We describe an approach to analysis using Fuzzy Logic. The hybrid simulator developed in toolbox Matlab consists calculation of waiting time transportation mode.

Keywords: Fuzzy logic, Hybrid system, Waiting Time, Transportation system, Control

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Authors: Brian W. Mandikiana

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Homestead food production has the potential to alleviate hunger, improve health and nutrition for children and adults. This article examines the relationship between self-reported hunger and homestead food production using the ordered probit model. A sample of households participating in homestead food production was drawn from the first wave of the South African National Income Dynamics Survey, a nationally representative cross-section. The sample selection problem was corrected using an ordered probit model with sample selection approach. The findings show that homestead food production exerts a positive and significant impact on children and adults’ ability to cope with hunger and malnutrition. Yet, on the contrary, potential gains of homestead food production are threatened by shocks such as crop failure.

Keywords: agriculture, hunger, nutrition, sample selection

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Authors: Artur Matuck, Guilherme F. Nobre

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Machines can be either tool, media, or social agents. Advances in technology have been delivering machines capable of autonomous expression, both through communication and art. This paper deals with models (theoretical approach) and experiments (applied approach) related to artificial agents. On one hand it traces how social sciences' scholars have worked with topics such as text automatization, man-machine writing cooperation, and communication. On the other hand it covers how computer sciences' scholars have built communicative and artistic machines, including the programming of creativity. The aim is to present a brief survey on artificially intelligent communicators and artificially creative writers, and provide the basis to understand the meta-authorship and also to new and further man-machine co-authorship.

Keywords: artificial communication, artificial creativity, artificial writers, meta-authorship, robotic art

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Authors: Mariayee Doraisamy, Suhaimi bin Ibrahim, Mohd Naz’ri Mahrin

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There are several methods to monitor software projects and the objective for monitoring is to ensure that the software projects are developed and delivered successfully. A performance measurement is a method that is closely associated with monitoring and it can be scrutinized by looking at two important attributes which are efficiency and effectiveness both of which are factors that are important for the success of a software project. Consequently, a successful steering is achieved by monitoring and controlling a software project via the performance measurement criteria and metrics. Hence, this paper is aimed at identifying the performance measurement criteria and the metrics for monitoring the performance of a software project by using the Goal Question Metrics (GQM) approach. The GQM approach is utilized to ensure that the identified metrics are reliable and useful. These identified metrics are useful guidelines for project managers to monitor the performance of their software projects.

Keywords: component, software project performance, goal question metrics, performance measurement criteria, metrics

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Authors: Kolade Olawande Owoeye, George Weir

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Terrorism and extremism activities on the internet are becoming the most significant threats to national security because of their potential dangers. In response to this challenge, law enforcement and security authorities are actively implementing comprehensive measures by countering the use of the internet for terrorism. To achieve the measures, there is need for intelligence gathering via the internet. This includes real-time monitoring of potential websites that are used for recruitment and information dissemination among other operations by extremist groups. However, with billions of active webpages, real-time monitoring of all webpages become almost impossible. To narrow down the search domain, there is a need for efficient webpage classification techniques. This research proposed a new approach tagged: SentiPosit-based method. SentiPosit-based method combines features of the Posit-based method and the Sentistrenght-based method for classification of terrorism and extremism webpages. The experiment was carried out on 7500 webpages obtained through TENE-webcrawler by International Cyber Crime Research Centre (ICCRC). The webpages were manually grouped into three classes which include the ‘pro-extremist’, ‘anti-extremist’ and ‘neutral’ with 2500 webpages in each category. A supervised learning algorithm is then applied on the classified dataset in order to build the model. Results obtained was compared with existing classification method using the prediction accuracy and runtime. It was observed that our proposed hybrid approach produced a better classification accuracy compared to existing approaches within a reasonable runtime.

Keywords: sentiposit, classification, extremism, terrorism

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Authors: Fadoua Ouamani, Narjès Bellamine Ben Saoud, Henda Hajjami Ben Ghézala

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In the last few years and over the last decades, there was a growing interest in the development of Computer Supported Collaborative Learning (CSCL) environments. However, the existing systems ignore the variety of learners and their socio-cultural differences, especially in the case of distant and networked learning. In fact, within such collaborative learning environments, learners from different socio-cultural backgrounds may interact together. These learners evolve within various cultures and social contexts and acquire different socio-cultural values and behaviors. Thus, they should be assisted while communicating and collaborating especially in an intercultural group. Besides, the communication and collaboration tools provided to each learner must depend on and be adapted to her/his socio-cultural profile. The main goal of this paper is to present the proposed socio-cultural adaptation approach based on and guided by ontologies to adapt CSCL environments to the socio-cultural profiles of its users (learners or others).

Keywords: CSCL, socio-cultural profile, adaptation, ontology

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Authors: Mohammad Reza Oftadeh

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The purpose of the article is to describe project objective structure (POS) concept that was developed on research activities and experiences about project management, Balanced Scorecard (BSC) and European Foundation Quality Management Excellence Model (EFQM Excellence Model). Furthermore, this paper tries to define a balanced, systematic, and integrated measurement approach to meet project objectives and project strategic goals based on a process-oriented model. In this paper, POS is suggested in order to measure project performance in the project life cycle. After using the POS model, the project manager can ensure in order to achieve the project objectives on the project charter. This concept can help project managers to implement integrated and balanced monitoring and control project work.

Keywords: project objectives, project performance management, PMBOK, key performance indicators, integration management

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Authors: Abdelaziz Hussien

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This article reports investigations of a study into the effectiveness of a traits cooperative learning (TCL) on teacher candidates’ writing achievement, composition, and attitudes towards traits of writing approach and small group learning. Mixed methodologies were used with the participants in a repeated measures quasi-experimental design. Forty-two class teacher candidates, enrolled in the Bahrain Teachers College, completed the pre and post author-developed measures. The results suggest that TCL has a positive effect on the participants’ writing achievement, composition, and attitudes towards traits of writing approach, but not on the attitudes towards small group learning. Further implications to teacher education are presented.

Keywords: trait-based language education, cooperative learning, writing achievement, writing composition, traits of writing, teacher education

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Authors: Sai Maniveer Adapa, Sai Guptha Perla, Adithya Reddy P.

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Thyroid nodules can often be diagnosed with ultrasound imaging, although differentiating between benign and malignant nodules can be challenging for medical professionals. This work suggests a novel approach to increase the precision of thyroid nodule identification by combining machine learning and deep learning. The new approach first extracts information from the ultrasound pictures using a deep learning method known as a convolutional autoencoder. A support vector machine, a type of machine learning model, is then trained using these features. With an accuracy of 92.52%, the support vector machine can differentiate between benign and malignant nodules. This innovative technique may decrease the need for pointless biopsies and increase the accuracy of thyroid nodule detection.

Keywords: thyroid tumor diagnosis, ultrasound images, deep learning, machine learning, convolutional auto-encoder, support vector machine

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Authors: Karen Odendaal

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Accounting transactions are becoming more complex, and more extensive accounting guidance is provided on a continuous basis. It is widely perceived that conceptual teaching of accounting contributes to lifelong learning. Such a conceptual teaching approach also contributes to effective accounting problem-solving. This framework-based approach is rooted in educational psychologies such as constructivism and Ausubel’s subsumption theory. This study aimed at investigating the ability of students to solve complex accounting problems by using only concepts underlying the Conceptual Framework. An assignment was administered to pre-graduate students at a South African university and this study made use of an interpretative research design which implemented multiple research instruments to investigate the ability of students to solve complex accounting problems using only concepts underlying the Conceptual Framework. Student perceptions were analysed and were aided by a related reflective questionnaire. The importance of the study indicates the necessity of Accounting educators to enhance a conceptual understanding among students as a mechanism for problem-solving of accounting issues. The results indicate that the ability of students to solve accounting problems effectively using only the Conceptual Framework depends on the complexity of the scenario and the students’ familiarity with the problem. The study promotes a balanced and more conceptual (rather than only technical) preference to the problem-solving of complex accounting problems. The study indubitably promotes considerable emphasis on the importance of the Conceptual Framework in accounting education and the promotion of life-long learning in the subject field.

Keywords: accounting education, conceptual teaching, constructivism, framework-based, problem-solving

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Authors: Maryam Memarian, Mahmood Naghizadeh

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Deconstruction is an approach that is entirely incompatible with the traditional prevalent architecture. Considering the fact that this approach attempts to put architecture in sharp contrast with its opposite events and transpires with attending to the neglected and missing aspects of architecture and deconstructing its stable structures. It also recklessly proceeds beyond the existing frameworks and intends to create a different and more efficient prospect for space. The aim of deconstruction architecture is to satisfy both the prospective and retrospective visions as well as takes into account all tastes of the present in order to transcend time. Likewise, it ventures to fragment the facts and symbols of the past and extract new concepts from within their heart, which coincide with today’s circumstances. Since this approach is an attempt to surpass the limits of the prevalent architecture, it can be employed to design places in which creative events occur and imagination and ambition flourish. Thought-provoking artistic events can grow and mature in such places and be represented in the best way possible to all people. The concept of event proposed in the plan grows out of the interaction between space and creation. In addition to triggering surprise and high impressions, it is also considered as a bold journey into the suspended realms of the traditional conflicts in architecture such as architecture-landscape, interior-exterior, center-margin, product-process, and stability-instability. In this project, at first, through interpretive-historical research method and examining the inputs and data collection, recognition and organizing takes place. After evaluating the obtained data using deductive reasoning, the data is eventually interpreted. Given the fact that the research topic is in its infancy and there is not a similar case in Iran with limited number of corresponding instances across the world, the selected topic helps to shed lights on the unrevealed and neglected parts in architecture. Similarly, criticizing, investigating and comparing specific and highly prized cases in other countries with the project under study can serve as an introduction into this architecture style.

Keywords: anti-architecture, creativity, deconstruction, event

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Authors: Serag El Hegazi

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The development of an assessment methodological framework for local and institutional sustainability is a key factor for future development plans and visions. This paper develops an approach to local and institutional sustainability assessment (ALISA). The ALISA methodology is a methodological framework that assists in the clarification, formulation, preparation, selection, and ranking of key indicators to facilitate the assessment of the level of sustainability at the local and institutional levels in North African and Middle Eastern cities. According to the literature review, this paper formulates a methodological framework, ALISA, which is a combination of the UNCSD (2001) Theme Indicators Framework and the issue-based Framework illustrated by McLaren (1996). The methodological framework has been implemented to formulate, select, and prioritise key indicators that most directly reflect the issues of a case study at the local community and institutional level. Yet, in the meantime, there is a lack of clear indicators and frameworks that can be developed to apply successfully at the local and institutional levels in the MENA Region, particularly in the cities of Benghazi and Amman. This is an essential issue for sustainability development estimation. Therefore, a conceptual framework was developed to be tested as a methodology to collect and classify data. The Approach to Local and Institutional Sustainability Assessment (ALISA) is a methodological framework that was developed to apply to certain cities in the MENA region. The main goal is to develop the ALISA framework to formulate, choose, and prioritize sustainability key indicators, which then can assist in guiding an assessment progress to improve decisions and policymakers towards the development of sustainable cities at the local and institutional level in the city of Benghazi. The conceptual, methodological framework, which supports this research with joint documentary and analysed data in two case studies, including focus-group discussions, semi-structured interviews, and questionnaires, reflects the approach required to develop a combined framework that assists the development of sustainability indicators. To achieve this progress and reach the aim of this paper, which is developing a practical approach for sustainability indicators framework that could be used as a tool to develop local and institutional sustainability indicators, appropriate stages must be applied to propose a set of local and institutional sustainability indicators as follows: Step one: issues clarifications, Step two: objectives formation/analysing of issues and boundaries, Step three: indicators preparation, First list of proposed indictors, Step four: indicator selection, Step five: indicator rating/ranking.

Keywords: sustainability indicators, approach to local and institutional level, ALISA, policymakers

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Authors: Wan You Ning

Abstract:

Addressing the rising prevalence of mental health issues among youths, the Multi-dimensional Approach to Resilience and Support in Advanced School-based Mental Health Service Delivery (MARS-ASMHSD) framework proposes the implementation of advanced mental health services in low-resource areas to further instil mental health resilience among students in a school-based setting. Recognizing the unsustainability of direct service delivery due to rapidly growing demands and costs, the MARS-ASMHSD framework endorses the deinstitutionalization of mental healthcare and explores a tiered, multi-dimensional approach in mental healthcare provision, establishing advanced school-based mental health service delivery. The framework is developed based on sustainable and credible evidence-based practices and modifications of existing mental health service deliveries in Asia, including Singapore, Thailand, Malaysia, Japan, and Taiwan. Dissemination of the framework model for implementation will enable a more progressive and advanced school-based mental health service delivery in low-resource areas. Through the evaluation of the mental health landscape and the role of stakeholders in the respective countries, the paper concludes with a multi-dimensional framework model for implementation in low-resource areas. A mixed-method independent research study is conducted to facilitate the framework's development.

Keywords: mental health, youths, school-based services, framework development

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Authors: Alex Ellery

Abstract:

Geoengineering approaches to climate change mitigation are unpopular and regarded with suspicion. Of these, space-based approaches are regarded as unworkable and enormously costly. Here, a space-based approach is presented that is modest in cost, fully controllable and reversible, and acts as a natural spur to the development of solar power satellites over the longer term as a clean source of energy. The low-cost approach exploits self-replication technology which it is proposed may be enabled by 3D printing technology. Self-replication of 3D printing platforms will enable mass production of simple spacecraft units. Key elements being developed are 3D-printable electric motors and 3D-printable vacuum tube-based electronics. The power of such technologies will open up enormous possibilities at low cost including space-based geoengineering.

Keywords: 3D printing, in-situ resource utilization, self-replication technology, space-based geoengineering

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Authors: Wuthichai Wongthatsanekorn, Nuntana Matheekrieangkrai

Abstract:

This research proposes Bee Algorithm (BA) to optimize Ready Mixed Concrete (RMC) truck scheduling problem from single batch plant to multiple construction sites. This problem is considered as an NP-hard constrained combinatorial optimization problem. This paper provides the details of the RMC dispatching process and its related constraints. BA was then developed to minimize total waiting time of RMC trucks while satisfying all constraints. The performance of BA is then evaluated on two benchmark problems (3 and 5construction sites) according to previous researchers. The simulation results of BA are compared in term of efficiency and accuracy with Genetic Algorithm (GA) and all problems show that BA approach outperforms GA in term of efficiency and accuracy to obtain optimal solution. Hence, BA approach could be practically implemented to obtain the best schedule.

Keywords: bee colony optimization, ready mixed concrete problem, ruck scheduling, multiple construction sites

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Authors: Anthony Townley

Abstract:

Contract negotiation is fundamental to commercial law practice. For this study, genre and discourse analytical methodology was used to examine the legal negotiation of a Merger & Acquisition (M&A) deal undertaken by legal and business professionals in English across different jurisdictions in Europe. While some of the most delicate negotiations involved in this process were carried on face-to-face or over the telephone, these were generally progressed more systematically – and on the record – in the form of emails, email attachments, and as comments and amendments recorded in successive ‘marked-up’ versions of the contracts under negotiation. This large corpus of textual data was originally obtained by the author, in 2012, for the purpose of doctoral research. For this study, the analysis is particularly concerned with the use of emails and covering letters to exchange legal advice about the negotiations. These two genres help to stabilize and progress the negotiation process and account for negotiation activities. Swalesian analysis of functional Moves and Steps was able to identify structural similarities and differences between these text types and to identify certain salient discursive features within them. The analytical findings also indicate how particular linguistic strategies are more appropriately and more effectively associated with one legal genre rather than another. The concept of intertextuality is an important dimension of contract negotiation discourse and this study also examined how the discursive relationships between the different texts influence the way that texts are constructed. In terms of materials development, the research findings can contribute to more authentic English for Legal & Business Purposes pedagogies for students and novice lawyers and business professionals. The findings can first be used to design discursive maps that provide learners with a coherent account of the intertextual nature of the contract negotiation process. These discursive maps can then function as a framework in which to present detailed findings about the textual and structural features of the text types by applying the Swalesian genre analysis. Based on this acquired knowledge of the textual nature of contract negotiation, the authentic discourse materials can then be used to provide learners with practical opportunities to role-play negotiation activities and experience professional ways of thinking and using language in preparation for the written discourse challenges they will face in this important area of legal and business practice.

Keywords: English for legal and business purposes, discourse analysis, genre analysis, intertextuality, pedagogical materials

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Authors: Stephanie Chen, Mitja Echim, Christof Büskens

Abstract:

To describe and propagate the behavior of a system mathematical models are formulated. Parameter identification is used to adapt the coefficients of the underlying laws of science. For complex systems this approach can be incomplete and hence imprecise and moreover too slow to be computed efficiently. Therefore, these models might be not applicable for the numerical optimization of real systems, since these techniques require numerous evaluations of the models. Moreover not all quantities necessary for the identification might be available and hence the system must be adapted manually. Therefore, an approach is described that generates models that overcome the before mentioned limitations by not focusing on physical laws, but on measured (sensor) data of real systems. The approach is more general since it generates models for every system detached from the scientific background. Additionally, this approach can be used in a more general sense, since it is able to automatically identify correlations in the data. The method can be classified as a multivariate data regression analysis. In contrast to many other data regression methods this variant is also able to identify correlations of products of variables and not only of single variables. This enables a far more precise and better representation of causal correlations. The basis and the explanation of this method come from an analytical background: the series expansion. Another advantage of this technique is the possibility of real-time adaptation of the generated models during operation. Herewith system changes due to aging, wear or perturbations from the environment can be taken into account, which is indispensable for realistic scenarios. Since these data driven models can be evaluated very efficiently and with high precision, they can be used in mathematical optimization algorithms that minimize a cost function, e.g. time, energy consumption, operational costs or a mixture of them, subject to additional constraints. The proposed method has successfully been tested in several complex applications and with strong industrial requirements. The generated models were able to simulate the given systems with an error in precision less than one percent. Moreover the automatic identification of the correlations was able to discover so far unknown relationships. To summarize the above mentioned approach is able to efficiently compute high precise and real-time-adaptive data-based models in different fields of industry. Combined with an effective mathematical optimization algorithm like WORHP (We Optimize Really Huge Problems) several complex systems can now be represented by a high precision model to be optimized within the user wishes. The proposed methods will be illustrated with different examples.

Keywords: adaptive modeling, automatic identification of correlations, data based modeling, optimization

Procedia PDF Downloads 409