Search results for: supportive approach

Authors: Vinicius G. Goecks, Gregory M. Gremillion, William D. Nothwang

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Modern approaches to train intelligent agents rely on prolonged training sessions, high amounts of input data, and multiple interactions with the environment. This restricts the application of these learning algorithms in robotics and real-world applications, in which there is low tolerance to inadequate actions, interactions are expensive, and real-time processing and action are required. This paper addresses this issue introducing CyberSteer, a novel approach to efficiently design intrinsic reward functions based on human intention to guide deep reinforcement learning agents with no environment-dependent rewards. CyberSteer uses non-expert human operators for initial demonstration of a given task or desired behavior. The trajectories collected are used to train a behavior cloning deep neural network that asynchronously runs in the background and suggests actions to the deep reinforcement learning module. An intrinsic reward is computed based on the similarity between actions suggested and taken by the deep reinforcement learning algorithm commanding the agent. This intrinsic reward can also be reshaped through additional human demonstration or critique. This approach removes the need for environment-dependent or hand-engineered rewards while still being able to safely shape the behavior of autonomous robotic agents, in this case, based on human intention. CyberSteer is tested in a high-fidelity unmanned aerial vehicle simulation environment, the Microsoft AirSim. The simulated aerial robot performs collision avoidance through a clustered forest environment using forward-looking depth sensing and roll, pitch, and yaw references angle commands to the flight controller. This approach shows that the behavior of robotic systems can be shaped in a reduced amount of time when guided by a non-expert human, who is only aware of the high-level goals of the task. Decreasing the amount of training time required and increasing safety during training maneuvers will allow for faster deployment of intelligent robotic agents in dynamic real-world applications.

Keywords: human-robot interaction, intelligent robots, robot learning, semisupervised learning, unmanned aerial vehicles

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Authors: Dawood Al Chanti, Alice Caplier

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Sparse representations of signals have received a great deal of attention in recent years. In this paper, the interest of using sparse representation as a mean for performing sparse discriminative analysis between spontaneous facial expressions is demonstrated. An automatic facial expressions recognition system is presented. It uses a KSVD-SVM approach which is made of three main stages: A pre-processing and feature extraction stage, which solves the problem of shared subspace distribution based on the random projection theory, to obtain low dimensional discriminative and reconstructive features; A dictionary learning and sparse coding stage, which uses the KSVD model to learn discriminative under or over dictionaries for sparse coding; Finally a classification stage, which uses a SVM classifier for facial expressions recognition. Our main concern is to be able to recognize non-basic affective states and non-acted expressions. Extensive experiments on the JAFFE static acted facial expressions database but also on the DynEmo dynamic spontaneous facial expressions database exhibit very good recognition rates.

Keywords: dictionary learning, random projection, pose and spontaneous facial expression, sparse representation

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Authors: Mustafa Eruyar, Ersoy Pehlivan, Fatih Kafalı, Fatih Gundogan

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All megacities are not only under the pressure of common urbanization and growth problems but also dealing with different challenges according to their specific circumstances. However, the majority of cities focuses mainly on popular smart city projects, which are usually driven by strong private sector, regardless of their characteristics, each city needs to develop customized projects within a tailor-made smart city roadmap to be able to solve its own challenges. Smart city manifest, helps citizens to feel the action better than good reading smart city vision statements, which consists of five elements; namely purpose, values, mission, vision, and strategy. This study designs a methodology for smart city roadmap based on a top-down approach, breaking down of smart city manifest to feasible projects for a systematic smart city transformation. This methodology was implemented in Istanbul smart city transformation program which includes smart city literature review, current state analysis, roadmap, and architecture projects, respectively. Istanbul smart city roadmap project followed an extensive literature review of certain leading smart cities around the world and benchmarking of the city’s current state using well known smart city indices. In the project, needs of citizens and service providers of the city were identified via stakeholder, persona and social media analysis. The project aimed to develop smart city projects targeting fulfilling related needs by implementing a gap analysis between current state and foreseen plans. As a result, in 11 smart city domains and enablers; 24 strategic objectives, 50 programs, and 101 projects were developed with the support of 183 smart city stakeholder entities and based on 125 citizen persona profiles and last one-year social media analysis. In conclusion, the followed methodology helps cities to identify and prioritize their needs and plan for long-term sustainable development, despite limited resources.

Keywords: needs-based, manifest, roadmap, smart city, top-down approach

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Authors: Xhevrie Mamaqi

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Organization capacity learning is a process referring to the sum total of individual and collective learning through training programs, experience and experimentation, among others. Today, in-business ongoing training is one of the most important strategies for human capital development and it is crucial to sustain and improve workers’ knowledge and skills. Many organizations, firms and business are adopting a strategy of continuous learning, encouraging employees to learn new skills continually to be innovative and to try new processes and work in order to achieve a competitive advantage and superior business results. This paper uses the Resource Based View and Capacities (RBV) approach to construct a hypothetical relationships model between training and business results. The test of the model is applied on transversal data. A sample of 266 business of Spanish sector service has been selected. A Structural Equation Model (SEM) is used to estimate the relationship between ongoing training, represented by two latent dimension denominated Human and Social Capital resources and economic business results. The coefficients estimated have shown the efficient of some training aspects explaining the variation in business results.

Keywords: business results, human and social capital resources, training, RBV theory, SEM

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Authors: Akbar Farahani, Afsaneh Hassani, Peyman M. Farkhondeh

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Human Resource Management as one of the core processes of the project-based companies, despite its key role in the success and competitive advantage, is relatively unknown. In the project-based companies, due to the accelerated movement of knowledge in the work activities and the temporary nature of the project, the need to develop mechanisms for achieving optimal management of this issues is very challenging. Approach to human resource management in these companies evolves with goals, strategies, and operational processes. Therefore, the need for appropriate tools to facilitate implementation of the optimized human resource management in the project is more than before,Which currently with the development of information technology and modern communication, appropriate to address the optimal approach for dynamic management of human resources in the project have been provided.This is done by using the referral system implemented in Mahab GCE that provides 1: the ability to use humans in projects without geographic limitation and 2:information on the activities and outcomes of referrals.Furthermore, by using this system, recording the lessons learned after any particular activity on projects,accessing quantitative information, procedures, documentation of learned practices that have been stored in the data base as well as using them in future projects is provided.

Keywords: human resource management, project base company, ERP, referrals system

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Authors: Doris Lacej, Eni Bushi

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Cleaning and disinfection procedures are essential for maintaining the cleanliness status of the pharmaceutical manufacturing environment particularly of the cleanrooms and sterile unit area. The Good Manufacturing Practice (GMP) Annex 1 recommendation highly requires the implementation of the standard and validated cleaning and disinfection protocols. However, environmental monitoring has shown that even a validated cleaning method with certified agents may result in the presence of atypical microorganisms’ colony that exceeds GMP limits for a specific cleanroom area. In response to this issue, this case study aims to arrive at the root cause of the microbial contamination observed in the sterile production environment in Profarma pharmaceutical industry in Albania through applying a problem-solving practical approach that ensures the appropriate sterility grade. The guidelines and literature emphasize the importance of several factors in the prevention of possible microbial contamination occurring in cleanrooms, grade A and C. These factors are integrated into a practical framework, to identify the root cause of the presence of Aspergillus Niger colony in the sterile production environment in Profarma pharmaceutical industry in Albania. In addition, the application of a semi-automatic disinfecting system such as H2O2 FOG into sterile grade A and grade C cleanrooms has been an effective solution in eliminating the atypical colony of Aspergillus Niger. Selecting the appropriate detergents and disinfectants at the right concentration, frequency, and combination; the presence of updated and standardized guidelines for cleaning and disinfection as well as continuous training of operators on these practices in accordance with the updated GMP guidelines are some of the identified factors that influence the success of achieving sterility grade. However, to ensure environmental sustainability it is important to be prepared for identifying the source of contamination and making the appropriate decision. The proposed case-based practical approach may help pharmaceutical companies to achieve sterile production and cleanliness environmental sustainability in challenging situations. Apart from the integration of valid agents and standardized cleaning and disinfection protocols according to GMP Annex 1, pharmaceutical companies must be careful and investigate the source and all the steps that can influence the results of an abnormal situation. Subsequently apart from identifying the root cause it is important to solve the problem with a successful alternative approach.

Keywords: cleanrooms, disinfectants, environmental monitoring, GMP Annex 1

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Authors: Phuc D. Nguyen, Kristy L. Hansen, Branko Zajamsek

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The existence of special characteristics of wind farm noise such as amplitude modulation (AM) contributes significantly to annoyance, which could ultimately result in sleep disturbance and other adverse health effects for residents living near wind farms. In order to detect and quantify this phenomenon, several methods have been developed which can be separated into three types: time-domain, frequency-domain and hybrid methods. However, due to a lack of systematic validation of these methods, it is still difficult to select the best method for identifying AM. Furthermore, previous comparisons between AM methods have been predominantly qualitative or based on synthesised signals, which are not representative of the actual noise. In this study, a comparison between methods for detecting and quantifying AM has been carried out. The results are based on analysis of real noise data which were measured at a wind farm in South Australia. In order to evaluate the performance of these methods in terms of detecting AM, an approach has been developed to select the most successful method of AM detection. This approach uses a receiver operating characteristic (ROC) curve which is based on detection of AM in audio files by experts.

Keywords: amplitude modulation, wind farm noise, ROC curve

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Authors: Smriti, Ajeet Kumar

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We present a variant of the Irving-Kirkwood procedure to obtain the microscopic expressions of the cross-section averaged continuum fields such as internal force and moment in one-dimensional nanostructures in the non-equilibrium setting. In one-dimensional continuum theories for slender bodies, we deal with quantities such as mass, linear momentum, angular momentum, and strain energy densities, all defined per unit length. These quantities are obtained by integrating the corresponding pointwise (per unit volume) quantities over the cross-section of the slender body. However, no well-defined cross-section exists for these nanostructures at finite temperature. We thus define the cross-section of a nanorod to be an infinite plane which is fixed in space even when time progresses and defines the above continuum quantities by integrating the pointwise microscopic quantities over this infinite plane. The method yields explicit expressions of both the potential and kinetic parts of the above quantities. We further specialize in these expressions for helically repeating one-dimensional nanostructures in order to use them in molecular dynamics study of extension, torsion, and bending of such nanostructures. As, the Irving-Kirkwood procedure does not yield expressions of stiffnesses, we resort to a thermodynamic equilibrium approach to obtain the expressions of axial force, twisting moment, bending moment, and the associated stiffnesses by taking the first and second derivatives of the Helmholtz free energy with respect to conjugate strain measures. The equilibrium approach yields expressions independent of kinetic terms. We then establish the equivalence of the expressions obtained using the two approaches. The derived expressions are used to understand the extension, torsion, and bending of single-walled carbon nanotubes at non-zero temperatures.

Keywords: thermoelasticity, molecular dynamics, one dimensional nanostructures, nanotube buckling

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Authors: Mahsaossadat Pourrahmati Khelejan

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The purpose of this research was to identify and prioritize the sustainable development of sports venues using new and degradable energies with using the AHP Hierarchical Analysis approach. The research method is a descriptive strategy with regard to the direction of implementation and is a hierarchical research with a practical purpose. In this study, 30 experts (physical education faculty members, geography professors, accredited sports venues managers, and renewable energy engineers) were selected using purposeful sampling method as the research population. The research tool was a researcher-made questionnaire on the factors affecting the sustainable development of sports venues by using new technologies and degradable energy. Finally, the research questionnaire was designed with four components and 21 items. All steps were performed by using Expert Choice software. The importance of indicators that influence the sustainable development of sports venues is highlighted by the use of clean and degradable energy, for example: 1. Economic factor, weighing 0.420 2. Environmental index, weighing 0. 320 3. Physical index, weighing 0.148 4. Social index, weighing 0.122.

Keywords: Sports Venues, Sustainable Development, Degradable Energies, Prioritize

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Authors: Firas A. Al Laban, Mohamed Chabi, Sammani Danwawu Abdullahi

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There are a real needs to integrate types of Open Educational Resources (OER) with an intelligent system to extract information and knowledge in the semantic searching level. Those needs raised because most of current learning standard adopted web based learning and the e-learning systems does not always serve all educational goals. Semantic Web systems provide educators, students, and researchers with intelligent queries based on a semantic knowledge management learning system. An ontology-based learning system is an advanced system, where ontology plays the core of the semantic web in a smart learning environment. The objective of this paper is to discuss the potentials of ontologies and mapping different kinds of ontologies; heterogeneous or homogenous to manage and control different types of Open Educational Resources. The important contribution of this research is to approach a methodology uses logical rules and conceptual relations to map between ontologies of different educational resources. We expect from this methodology to establish for an intelligent educational system supporting student tutoring, self and lifelong learning system.

Keywords: knowledge management systems, ontologies, semantic web, open educational resources

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Authors: Cavidan Yakupoglu, Kurt Rohloff

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In this study, we aim to provide a novel parameter selection model for the BFVrns scheme, which is one of the prominent FHE schemes. Parameter selection in lattice-based FHE schemes is a practical challenges for experts or non-experts. Towards a solution to this problem, we introduce a hybrid principles-based approach that combines theoretical with experimental analyses. To begin, we use regression analysis to examine the parameters on the performance and security. The fact that the FHE parameters induce different behaviors on performance, security and Ciphertext Expansion Factor (CEF) that makes the process of parameter selection more challenging. To address this issue, We use a multi-objective optimization algorithm to select the optimum parameter set for performance, CEF and security at the same time. As a result of this optimization, we get an improved parameter set for better performance at a given security level by ensuring correctness and security against lattice attacks by providing at least 128-bit security. Our result enables average ~ 5x smaller CEF and mostly better performance in comparison to the parameter sets given in [1]. This approach can be considered a semiautomated parameter selection. These studies are conducted using the PALISADE homomorphic encryption library, which is a well-known HE library. The abstract goes here.

Keywords: lattice cryptography, fully homomorphic encryption, parameter selection, LWE, RLWE

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Authors: Durga Toshniwal, Lokesh Agrawal

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As the web continues to play an increasing role in information exchange, and conducting daily activities, computer users have become the target of miscreants which infects hosts with malware or adware for financial gains. Unfortunately, even a single visit to compromised web site enables the attacker to detect vulnerabilities in the user’s applications and force the downloading of multitude of malware binaries. We provide an approach to effectively scan the so-called drive-by downloads on the Internet. Drive-by downloads are result of URLs that attempt to exploit their visitors and cause malware to be installed and run automatically. To scan the web for malicious pages, the first step is to use a crawler to collect URLs that live on the Internet, and then to apply fast prefiltering techniques to reduce the amount of pages that are needed to be examined by precise, but slower, analysis tools (such as honey clients or antivirus programs). Although the technique is effective, it requires a substantial amount of resources. A main reason is that the crawler encounters many pages on the web that are legitimate and needs to be filtered. In this paper, to characterize the nature of this rising threat, we present implementation of a web crawler on Python, an approach to search the web more efficiently for pages that are likely to be malicious, filtering benign pages and passing remaining pages to antivirus program for detection of malwares. Our approaches starts from an initial seed of known, malicious web pages. Using these seeds, our system generates search engines queries to identify other malicious pages that are similar to the ones in the initial seed. By doing so, it leverages the crawling infrastructure of search engines to retrieve URLs that are much more likely to be malicious than a random page on the web. The results shows that this guided approach is able to identify malicious web pages more efficiently when compared to random crawling-based approaches.

Keywords: web crawler, malwares, seeds, drive-by-downloads, security

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Authors: Julien Romieux, Fabio Verdicchio

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Wireless Sensor Networks (WSNs), which sense environmental data with battery-powered nodes, require multi-hop communication. This power-demanding task adds an extra workload that is unfairly distributed across the network. As a result, nodes run out of battery at different times: this requires an impractical individual node maintenance scheme. Therefore we investigate a new Cooperative Sensing approach that extends the WSN operational life and allows a more practical network maintenance scheme (where all nodes deplete their batteries almost at the same time). We propose a novel cooperative algorithm that derives a piecewise representation of the sensed signal while controlling approximation accuracy. Simulations show that our algorithm increases WSN operational life and spreads communication workload evenly. Results convey a counterintuitive conclusion: distributing workload fairly amongst nodes may not decrease the network power consumption and yet extend the WSN operational life. This is achieved as our cooperative approach decreases the workload of the most burdened cluster in the network.

Keywords: cooperative signal processing, signal representation and approximation, power management, wireless sensor networks

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Authors: Sana Fatima, Paul Sadler, Jon Cooper, David Mendel, Ayesha Jameel

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Background: Neurodiversity refers to intrinsic differences between human minds and encompasses dyspraxia, dyslexia, attention deficit hyperactivity disorder, dyscalculia, autism spectrum disorder, and Tourette syndrome. There is increasing recognition of neurodiversity in relation to disability/diversity in medical education and the associated impact on training, career progression, and personal and professional wellbeing. In addition, documented and anecdotal evidence suggests that medical educators and training providers in all four nations (UK) are increasingly concerned about understanding neurodiversity and identifying and providing support for neurodivergent trainees. Summary of Work: A national Neurodiversity Task and Finish group were established to survey Health Education England local office Professional Support teams about insights into infrastructure, training for educators, triggers for assessment, resources, and intervention protocols. This group drew from educational leadership, professional and personal neurodiverse expertise, occupational medicine, employer human resource, and trainees. An online, exploratory survey was conducted to gather insights from supervisors and trainers across England using the Professional Support Units' platform. Summary of Results: This survey highlighted marked heterogeneity in the identification, assessment, and approaches to support and management of neurodivergent trainees and highlighted a 'deficit' approach to neurodiversity. It also demonstrated a paucity of educational and protocol resources for educators and supervisors in supporting neurodivergent trainees. Discussions and Conclusions: In phase one, we focused on faculty development. An educational repository for all supervising trainees using a thematic approach was formalised. This was guided by our survey findings specific for neurodiversity and took a triple 'A' approach: awareness, assessment, and action. This is further supported by video material incorporating stories in training as well as mobile workshops for trainers for more immersive learning. The subtle theme from both the survey and Task and finish group suggested a move away from deficit-focused methods toward a positive holistic, interdisciplinary approach within a biopsychosocial framework. Contributions: 1. Faculty Knowledge and basic understanding of neurodiversity are key to supporting trainees with known or underlying Neurodiverse conditions. This is further complicated by challenges around non-disclosure, varied presentations, stigma, and intersectionality. 2. There is national (and international) inconsistency in the approach to how trainees are managed once a neurodiverse condition is suspected or diagnosed. 3. A carefully constituted and focussed Task and Finish group can rapidly identify national inconsistencies in neurodiversity and implement rapid educational interventions. 4. Nuanced findings from surveys and discussion can reframe the approach to neurodiversity; from a medical model to a more comprehensive, asset-based, biopsychosocial model of support, fostering a cultural shift, accepting 'diversity' in all its manifestations, visible and hidden.

Keywords: neurodiversity, professional support, human considerations, workplace wellbeing

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Authors: Thota Sai Prakash, B. Yaswanth, Jhade Bhuvaneswar, Marreddy Divakar Reddy, Shyam Ji Gupta

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Across the globe, there are a lot of chronic diseases, and heart disease stands out as one of the most perilous. Sadly, many lives are lost to this condition, even though early intervention could prevent such tragedies. However, identifying heart disease in its initial stages is not easy. To address this challenge, we propose an automated system aimed at predicting the presence of heart disease using advanced techniques. By doing so, we hope to empower individuals with the knowledge needed to take proactive measures against this potentially fatal illness. Our approach towards this problem involves meticulous data preprocessing and the development of predictive models utilizing classification algorithms such as Support Vector Machines (SVM), Decision Tree, and Random Forest. We assess the efficiency of every model based on metrics like accuracy, ensuring that we select the most reliable option. Additionally, we conduct thorough data analysis to reveal the importance of different attributes. Among the models considered, Random Forest emerges as the standout performer with an accuracy rate of 96.04% in our study.

Keywords: support vector machines, decision tree, random forest

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Authors: Sireesha Tamada, Debraj Bhattacharjee, Pranab K. Dan, Prabha Bhola

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The most important component in an automotive transmission system is the gearbox which controls the speed of the vehicle. In an automatic transmission, the right positioning of actuators ensures efficient transmission mechanism embodiment, wherein the challenge lies in formulating the number of actuators associated with modelling a gearbox. Data with respect to actuation and gear shifting sequence has been retrieved from the available literature, including patent documents, and has been used in this proposed heuristics based methodology for modelling actuation sequence in a gear box. This paper presents a methodological approach in designing a gearbox for the purpose of obtaining an optimal shifting sequence. The computational model considers factors namely, the number of stages and gear teeth as input parameters since these two are the determinants of the gear ratios in an epicyclic gear train. The proposed transmission schematic or stick diagram aids in developing the gearbox layout design. The number of iterations and development time required to design a gearbox layout is reduced by using this approach.

Keywords: automatic transmission, gear-shifting, multi-stage planetary gearbox, rank ordered clustering

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Authors: Claudia Koby, Merav Boaz, Meirav Zaiger Kober

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Krembo Wings is an all-inclusive youth movement which brings children and youth with any disability together with their able-bodied peers (counselors) for weekly fun and educational social activities. Krembo Wings utilizes a socio-educational framework to create and lead social change through members with and without disabilities. All the work that Krembo Wings engages in stems from its central goal of promoting inclusion and integration using social and psychological theories to develop its unique model and approach. The key to Krembo Wings' approach in promoting inclusion is active participation – each member, with and without disabilities, is enabled to participate to their fullest capacity in the youth movement and its activities. In order for this to be achieved, all activities are adjustable and are modified to fit the abilities of each member. Additionally, youth counselors – most of whom are members without disabilities – go through extensive training in order to act as 'intermediaries' for their partner with disabilities, enabling and facilitating their partner's participation in a way that allows them to be as independent and active as possible. The relationship is one of friendship and not of caretaking. There is always a nurse on-hand to tend to any caretaking needs. Two essential elements of Krembo Wings' model is the broadening of concepts – shifting and changing the understanding of certain concepts such as what it means to be 'independent' or 'able' – and the development of a unique language – creating a language which both reflects and shapes reality. These elements of Krembo Wings' model foster the development of the values of acceptance and appreciation of those who are 'different'. It instills in members and counselors a new way of perceiving the world, one in which inclusion and integration are achievable and natural. Krembo Wings is certain that implementation of this model will promote the participation and inclusion of individuals with disabilities in society while promoting diversity. This model can serve as a platform which can be replicated and adjusted to suit any environment.

Keywords: innovative model for inclusion, socio-educational movement, youth leadership, youth with and without disabilities

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Authors: Samar M. Alqhtani, Suhuai Luo, Brian Regan

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Data fusion technology can be the best way to extract useful information from multiple sources of data. It has been widely applied in various applications. This paper presents a data fusion approach in multimedia data for event detection in twitter by using Dempster-Shafer evidence theory. The methodology applies a mining algorithm to detect the event. There are two types of data in the fusion. The first is features extracted from text by using the bag-ofwords method which is calculated using the term frequency-inverse document frequency (TF-IDF). The second is the visual features extracted by applying scale-invariant feature transform (SIFT). The Dempster - Shafer theory of evidence is applied in order to fuse the information from these two sources. Our experiments have indicated that comparing to the approaches using individual data source, the proposed data fusion approach can increase the prediction accuracy for event detection. The experimental result showed that the proposed method achieved a high accuracy of 0.97, comparing with 0.93 with texts only, and 0.86 with images only.

Keywords: data fusion, Dempster-Shafer theory, data mining, event detection

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Authors: Jean Marie Tshimula, Atsushi Togashi

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We develop a data-science approach for providing an interactive visualization and predictive models to find insights into the projects' historical data in order for stakeholders understand some unseen opportunities in the African market that might escape them behind the online project portfolio of the African Development Bank. This machine learning-based web application identifies the market trend of the fastest growing economies across the continent as well skyrocketing sectors which have a significant impact on the future of business in Africa. Owing to this, the approach is tailored to predict where the investment needs are the most required. Moreover, we create a corpus that includes the descriptions of over more than 1,200 projects that approximately cover 14 sectors designed for some of 53 African countries. Then, we sift out this large amount of semi-structured data for extracting tiny details susceptible to contain some directions to follow. In the light of the foregoing, we have applied the combination of Latent Dirichlet Allocation and Random Forests at the level of the analysis module of our methodology to highlight the most relevant topics that investors may focus on for investing in Africa.

Keywords: machine learning, topic modeling, natural language processing, big data

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Authors: Amor Jnifene, Cedric Cocaud

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One of the most constraining problems facing the development of autonomous vehicles is the limitations of current technologies. Guidance and navigation controllers need to be faster and more robust. Communication data links need to be more reliable and secure. For an Unmanned Aerial Vehicles (UAV) to be useful, and fully autonomous, one important feature that needs to be an integral part of the navigation system is autonomous trajectory planning. The work discussed in this paper presents a method for on-line trajectory planning for UAV’s. This method takes into account various constraints of different types including specific vectors of approach close to target points, multiple objectives, and other constraints related to speed, altitude, and obstacle avoidance. The trajectory produced by the proposed method ensures a smooth transition between different segments, satisfies the minimum curvature imposed by the dynamics of the UAV, and finds the optimum velocity based on available atmospheric conditions. Given a set of objective points and waypoints a skeleton of the trajectory is constructed first by linking all waypoints with straight segments based on the order in which they are encountered in the path. Secondly, vectors of approach (VoA) are assigned to objective waypoints and their preceding transitional waypoint if any. Thirdly, the straight segments are replaced by 3D curvilinear trajectories taking into account the aircraft dynamics. In summary, this work presents a method for on-line 3D trajectory generation (TG) of Unmanned Aerial Vehicles (UAVs). The method takes as inputs a series of waypoints and an optional vector of approach for each of the waypoints. Using a dynamic model based on the performance equations of fixed wing aircrafts, the TG computes a set of 3D parametric curves establishing a course between every pair of waypoints, and assembling these sets of curves to construct a complete trajectory. The algorithm ensures geometric continuity at each connection point between two sets of curves. The geometry of the trajectory is optimized according to the dynamic characteristics of the aircraft such that the result translates into a series of dynamically feasible maneuvers. In summary, this work presents a method for on-line 3D trajectory generation (TG) of Unmanned Aerial Vehicles (UAVs). The method takes as inputs a series of waypoints and an optional vector of approach for each of the waypoints. Using a dynamic model based on the performance equations of fixed wing aircraft, the TG computes a set of 3D parametric curves establishing a course between every pair of waypoints, and assembling these sets of curves to construct a complete trajectory. The algorithm ensures geometric continuity at each connection point between two sets of curves. The geometry of the trajectory is optimized according to the dynamic characteristics of the aircraft such that the result translates into a series of dynamically feasible maneuvers.

Keywords: trajectory planning, unmanned autonomous air vehicle, vector of approach, waypoints

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Authors: Virakti Dhaval Shah

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Advances in technology and the changes in lifestyle and work expectations amid the COVID-19 pandemic are requiring changes to vocational assessment, provision of vocational training, and identification of job matches for individuals with intellectual disability. Vocational assessment involves the assessment of interests, skills, abilities, and strengths/weaknesses, as well as a detailed understanding of healthcare, familial, social, community, workplace-related and policy-level protective and risk factors impacting the individual. In India, vocational assessment procedures such as interviews play a major role in vocational placement today. Unfortunately, many of the most widely used vocational assessment instruments in India were developed in the 1970s to 2000s and have not been revised since. Hence, there is a dire need to update existing tools and prepare a structured approach for vocational service providers to meet the unique employment needs of individuals with intellectual disabilities. To address this need, this project designed a multi-domain assessment toolkit for a structured approach to vocational assessment, training, and job placement for individuals with intellectual disabilities in India. Methods included conducting an empirical review of the available tools currently in use in India for the vocational assessment of persons with intellectual disabilities. Domains addressed in the instrument review were organized into a structured system, and additional items related to contemporary technology, pandemic-related experiences of persons with disabilities, and changes in lifestyle and work expectations due to the pandemic were added. Items assessing behaviors, provision of vocational training, and identification of job matches for individuals with intellectual disabilities were developed. The proposed tool has the potential to benefit organizations working with and preparing individuals with intellectual disabilities to find successful employment by undertaking a structured approach to vocational assessment, rehabilitation, training, and placement. It can be particularly useful for guiding new professionals doing vocational rehabilitation in India.

Keywords: intellectual disability, rehabilitation, vocational assessment, vocational rehabilitation

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Authors: Alba Francesca Canta

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The present is one of those times when what normally seems to constitute a reason for living vanishes, particularly in times of crisis, during which certainties of all times crumble, and critical issues emerge, especially in already problematic areas such as the role of women and children. This paper aims to explore the issue of gender and highlight the importance of education for people’s development and well-being. The study is part of the broader framework of the capability approach, a multidimensional approach based on the need to consider a person’s wealth by virtue of their opportunity and freedom to live a ‘life of worth. The results of empirical research conducted in 2020 will be presented, the main objective of which was to measure, through qualitative (project techniques, focus groups, interviews with key informants) and quantitative (questionnaire) methods, the level of empowerment of women in two Italian territories and the consequent well-being of their children. By means of the relationship study, the present research results show that a higher level of women’s empowerment corresponds to a higher level of children’s well-being in a positive virtuous process. The opportunity structure and education are the main driving guide both to women’s empowerment and children’s well-being, emphasizing the importance of education to gender culture as a key factor for the development of the whole society. Among all the traumatic events that broke the harmony of the world and caused an abrupt turn in all areas of society, the crisis of democracy and education are some of the harshest. Nevertheless, education continues to be a fundamental pillar of Global Development Agendas, and above all, democratic education is the main factor in the development of a generative society, capable of forming people who know how to live in society. In this context, recovering democratic and inclusive education can be the key to a breakthrough. In the capability approach Sen, and other Scholars, point out education from two different perspectives: a. education as a fundamental right capable of influencing other real fields of people’s life (i.e., being educated to prevent illness, to vote, etc.) and b. spread communitarian education, tolerance, inclusive, democratic, and respectful, capable of forming human beings. This kind of educational system can directly lead to a general process of gender education that presupposes respect for essential principles: equality, uniqueness, and the participation of all in the processes of defining a democratic society. Many practices of women and children’s exclusions essentially derive from social factors (norms, values, quality of institutions, relations of power, educational and cultural practices) that can build strong barriers. Respect for these principles and education for gender culture could foster the renewal of society and the acquisition of fundamental skills for a generative and inclusive society, such as critical skills, cosmopolitan skills, and narrative imagination.

Keywords: capability approach, children’s well-being, education, women’s empowerment

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Authors: Federico Valenzuela-Beltran, Sonia E. Ruiz, Alfredo Reyes-Salazar, Juan Bojorquez

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A reliability-based methodology which uses structural demand hazard curves to consider the increment of the ductility demands of structures with tilting is proposed. The approach considers the effect of two orthogonal components of the ground motions as well as the influence of soil-structure interaction. The approach involves the calculation of ductility demand hazard curves for symmetric systems and, alternatively, for systems with different degrees of asymmetry. To get this objective, demand hazard curves corresponding to different global ductility demands of the systems are calculated. Next, Uniform Exceedance Rate Spectra (UERS) are developed for a specific mean annual rate of exceedance value. Ratios between UERS corresponding to asymmetric and to symmetric systems located in soft soil of the valley of Mexico are obtained. Results indicate that the ductility demands corresponding to tilted structures may be several times higher than those corresponding to symmetric structures, depending on several factors such as tilting angle and vibration period of structure and soil.

Keywords: asymmetric yielding, seismic performance, structural reliability, tilted structures

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Authors: Rui Yin, Haojie Wang, Xun Li

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Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then, the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. We also explore contrastive learning as a method for training domain-adapted dense retrievers and show that it leads to strong performance in various retrieval settings. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data.

Keywords: dense retrieval, query generation, contrastive learning, unsupervised training

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Authors: Alireza Alizadeh, Hossein Ghadimi, Oveis Abedinia, Noradin Ghadimi

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A Particle Swarm Optimization with Time Varying Acceleration Coefficients (PSO-TVAC) is proposed to determine optimal economic load dispatch (ELD) problem in this paper. The proposed methodology easily takes care of solving non-convex economic load dispatch problems along with different constraints like transmission losses, dynamic operation constraints and prohibited operating zones. The proposed approach has been implemented on the 3-machines 6-bus, IEEE 5-machines 14-bus, IEEE 6-machines 30-bus systems and 13 thermal units power system. The proposed technique is compared to solve the ELD problem with hybrid approach by using the valve-point effect. The comparison results prove the capability of the proposed method giving significant improvements in the generation cost for the economic load dispatch problem.

Keywords: PSO-TVAC, economic load dispatch, non-convex cost function, prohibited operating zone, transmission losses

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Authors: Mei Lin, Chang Liu

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Argumentative writing is the most prevalent genre in diverse writing tests. How to construct academic arguments is often regarded as a difficult task by most English as a foreign language (EFL) learners. A failure to generate enough ideas and organise them coherently and logically as well as a lack of competence in supporting their arguments with relevant evidence are frequent problems faced by EFL learners when approaching an English argumentative writing task. Overall, these problems are closely related to planning, and planning an argumentative writing at pre-writing stage plays a vital role in a good academic essay. However, how teachers can effectively guide students to generate ideas is rarely discussed in planning English argumentative writing, apart from brainstorming. Brainstorming has been a common practice used by teachers to help students generate ideas. However, some limitations of brainstorming suggest that it can help students generate many ideas, but ideas might not necessarily be coherent and logic, and could sometimes impede production. It calls for a need to explore effective instructional strategies at pre-writing stage of English argumentative writing. This paper will first examine how a Six Thinking Hats approach can be used to provide a dialogic space for EFL learners to experience and collaboratively generate ideas from multiple perspectives at pre-writing stage. Part of the findings of the impact of a twelve-week intervention (from March to July 2021) on students learning to generate ideas through engaging in group discussions of using Six Thinking Hats will then be reported. The research design is based on the sociocultural theory. The findings present evidence from a mixed-methods approach and fifty-nine participants from two first-year undergraduate natural classes in a Chinese university. Analysis of pre- and post- questionnaires suggests that participants had a positive attitude toward the Six Thinking Hats approach. It fosters their understanding of prewriting and argumentative writing, helps them to generate more ideas not only from multiple perspectives but also in a systematic way. A comparison of participants writing plans confirms an improvement in generating counterarguments and rebuttals to support their arguments. Above all, visual and transcripts data of group discussion collected from different weeks throughout the intervention enable teachers and researchers to ‘see’ the hidden process of learning to generate ideas in action.

Keywords: argumentative writing, innovative pedagogy, six thinking hats, dialogic space, prewriting, higher education

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Authors: Ana Carolina Hecht, Noelia Enriz, Mariana Garcia Palacios

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The South American anthropology has been recently focused to research with children in different contexts. In our researches with children from indigenous communities in the lowlands and highlands of South America (Qom and Mbyá), we especially considered social categories that define the different ways of being a boy and a girl. In this way, we built an approach to disrupt monolithic models of childhood. The aim of this paper is to tackle the first stage of life, demarcated from their nominal references and from the upbringing and formative experiences in which children participate. So, we will focus on the network of social relations in the period of childhood, making especial focus on language develops, religion, schooling and games. The crossing of our different thematic interests allows us to consider the complexity of knowledge and skills that come into play during the development of children. Methodologically, this text is based on an ethnographic approach, with frequent visits and periods of cohabitation, for more than a decade with Mbyá and Qom people, who lives within indigenous communities in the provinces of Chaco, Buenos Aires and Misiones, in Argentina. We made participant observation and interviews with children and their families, with the objective to include children's voices in our researches about the whole community.

Keywords: chidhood, indigenous people, schooling, upbringing

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Authors: Najeh Lakhoua

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Introduction: Scientific developments and techniques for the systemic approach generate several names to the systemic approach: systems analysis, systems analysis, structural analysis. The main purpose of these reflections is to find a multi-disciplinary approach which organizes knowledge, creates universal language design and controls complex sets. In fact, system analysis is structured sequentially by steps: the observation of the system by various observers in various aspects, the analysis of interactions and regulatory chains, the modeling that takes into account the evolution of the system, the simulation and the real tests in order to obtain the consensus. Thus the system approach allows two types of analysis according to the structure and the function of the system. The purpose of this paper is to present an application of system analysis of Unmanned Aerial Vehicle (UAV) components in order to represent the architecture of this system. Method: There are various analysis methods which are proposed, in the literature, in to carry out actions of global analysis and different points of view as SADT method (Structured Analysis and Design Technique), Petri Network. The methodology adopted in order to contribute to the system analysis of an Unmanned Aerial Vehicle has been proposed in this paper and it is based on the use of SADT. In fact, we present a functional analysis based on the SADT method of UAV components Body, power supply and platform, computing, sensors, actuators, software, loop principles, flight controls and communications). Results: In this part, we present the application of SADT method for the functional analysis of the UAV components. This SADT model will be composed exclusively of actigrams. It starts with the main function ‘To analysis of the UAV components’. Then, this function is broken into sub-functions and this process is developed until the last decomposition level has been reached (levels A1, A2, A3 and A4). Recall that SADT techniques are semi-formal; however, for the same subject, different correct models can be built without having to know with certitude which model is the good or, at least, the best. In fact, this kind of model allows users a sufficient freedom in its construction and so the subjective factor introduces a supplementary dimension for its validation. That is why the validation step on the whole necessitates the confrontation of different points of views. Conclusion: In this paper, we presented an application of system analysis of Unmanned Aerial Vehicle components. In fact, this application of system analysis is based on SADT method (Structured Analysis Design Technique). This functional analysis proved the useful use of SADT method and its ability of describing complex dynamic systems.

Keywords: system analysis, unmanned aerial vehicle, functional analysis, architecture

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Authors: Danny Barash

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Riboswitches are RNA genetic control elements that were originally discovered in bacteria and provide a unique mechanism of gene regulation. They work without the participation of proteins and are believed to represent ancient regulatory systems in the evolutionary timescale. One of the biggest challenges in riboswitch research is that many are found in prokaryotes but only a small percentage of known riboswitches have been found in certain eukaryotic organisms. The few examples of eukaryotic riboswitches were identified using sequence-based bioinformatics search methods that include some slight structural considerations. These pattern-matching methods were the first ones to be applied for the purpose of riboswitch detection and they can also be programmed very efficiently using a data structure called affix arrays, making them suitable for genome-wide searches of riboswitch patterns. However, they are limited by their ability to detect harder to find riboswitches that deviate from the known patterns. Several methods have been developed since then to tackle this problem. The most commonly used by practitioners is Infernal that relies on Hidden Markov Models (HMMs) and Covariance Models (CMs). Profile Hidden Markov Models were also carried out in the pHMM Riboswitch Scanner web application, independently from Infernal. Other computational approaches that have been developed include RMDetect by the use of 3D structural modules and RNAbor that utilizes Boltzmann probability of structural neighbors. We have tried to incorporate more sophisticated secondary structure considerations based on RNA folding prediction using several strategies. The first idea was to utilize window-based methods in conjunction with folding predictions by energy minimization. The moving window approach is heavily geared towards secondary structure consideration relative to sequence that is treated as a constraint. However, the method cannot be used genome-wide due to its high cost because each folding prediction by energy minimization in the moving window is computationally expensive, enabling to scan only at the vicinity of genes of interest. The second idea was to remedy the inefficiency of the previous approach by constructing a pipeline that consists of inverse RNA folding considering RNA secondary structure, followed by a BLAST search that is sequence-based and highly efficient. This approach, which relies on inverse RNA folding in general and our own in-house fragment-based inverse RNA folding program called RNAfbinv in particular, shows capability to find attractive candidates that are missed by Infernal and other standard methods being used for riboswitch detection. We demonstrate attractive candidates found by both the moving-window approach and the inverse RNA folding approach performed together with BLAST. We conclude that structure-based methods like the two strategies outlined above hold considerable promise in detecting riboswitches and other conserved RNAs of functional importance in a variety of organisms.

Keywords: riboswitches, RNA folding prediction, RNA structure, structure-based methods

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Authors: David B. Tsuanyo, Didier Aussel, Yao Azoumah, Pierre Neveu

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An innovative concept called “Flexy-Energy”is developing at 2iE. This concept aims to produce electricity at lower cost by smartly mix different available energies sources in accordance to the load profile of the region. With a higher solar irradiation and due to the fact that Diesel generator are massively used in sub-Saharan rural areas, PV/Diesel hybrid systems could be a good application of this concept and a good solution to electrify this region, provided they are reliable, cost effective and economically attractive to investors. Presentation of the developed approach is the aims of this paper. The PV/Diesel hybrid system designed consists to produce electricity and/or heat from a coupling between Diesel gensets and PV panels without batteries storage, while ensuring the substitution of gasoil by bio-fuels available in the area where the system will be installed. The optimal design of this system is based on his technical performances; the Life Cycle Cost (LCC) and Levelized Cost of Energy are developed and use as economic criteria. The Net Present Value (NPV), the internal rate of return (IRR) and the discounted payback (DPB) are also evaluated according to dual electricity pricing (in sunny and unsunny hours). The PV/Diesel hybrid system obtained is compared to the standalone Diesel gensets. The approach carried out in this paper has been applied to Siby village in Mali (Latitude 12 ° 23'N 8 ° 20'W) with 295 kWh as daily demand. This approach provides optimal physical characteristics (size of the components, number of component) and dynamical characteristics in real time (number of Diesel generator on, their load rate, fuel specific consumptions, and PV penetration rate) of the system. The system obtained is slightly cost effective; but could be improved with optimized tariffing strategies.

Keywords: investments criteria, optimization, PV hybrid, sizing, rural electrification

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