Search results for: hybrid hierarchical clustering

Authors: Nadia Samantha Zuñiga-Peña, Norberto Hernández-Romero, Omar Aguilar-Mejia, Salatiel García-Nava

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Using unmanned aerial vehicles (UAVs) for load transport has gained significant importance in various sectors due to their ability to improve efficiency, reduce costs, and access hard-to-reach areas. Although UAVs offer numerous advantages for load transport, several complications and challenges must be addressed to exploit their potential fully. Complexity relays on UAVs are underactuated, non-linear systems with a high degree of coupling between their variables and are subject to forces with uncertainty. One of the biggest challenges is modeling and controlling the system formed by UAVs carrying a load. In order to solve the controller problem, in this work, a hybridization of Neural Network and Hunger Games Search (HGS) metaheuristic algorithm is developed and implemented to find the parameters of the Super Twisting Sliding Mode Controller for the 8 degrees of freedom model of UAV with payload. The optimized controller successfully tracks the UAV through the three-dimensional desired path, demonstrating the effectiveness of the proposed solution. A comparison of performance shows the superiority of the neural network HGS (NNHGS) over the HGS algorithm, minimizing the tracking error by 57.5 %.

Keywords: neural networks, hunger games search, super twisting sliding mode controller, UAVs.

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Authors: Amare Worku, Harikrishnan Muralidharan

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The research for more environmentally friendly sources of energy is a result of growing environmental awareness. In this aspect, wind energy is a very good option and there are two different wind turbines, horizontal axis wind turbine (HAWT) and vertical axis turbine (VAWT). For locations outside of integrated grid networks, vertical axis wind turbines (VAWT) present a feasible solution. However, those turbines have several drawbacks related to various setups, VAWT has a very low efficiency when compared with HAWT, but they work under different conditions and installation areas. This paper reviewed numerous measurements taken to improve the efficiency of VAWT configurations, either directly or indirectly related to the performance efficiency of the turbine. Additionally, the comparison and advantages of HAWT and VAWT turbines and also the findings of the design methodologies used for the VAWT design have been reviewed together with efficiency enhancement revision. Most of the newly modified designs are based on the turbine blade structure modification but need other studies on behalf other than electromechanical modification. Some of the techniques, like continuous variation of pitch angle control and swept area control, are not the most effective since VAWT is Omni-directional, and so wind direction is not a problem like HAWT. Hybrid system technology has become one of the most important and efficient methods to enhance the efficiency of VAWT. Besides hybridization, the contra-rotating method is also good if the installation area is big enough in an urban area.

Keywords: wind turbine, horizontal axis wind turbine, vertical axis wind turbine, hybridization

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Authors: Masoud Shahmanzari

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The aim of this paper is to present a Variable Neighborhood Search (VNS) with Tabu Search (TS) conditions for the Roaming Salesman Problem (RSP). The RSP is a special case of the well-known traveling salesman problem (TSP) where a set of cities with time-dependent rewards and a set of campaign days are given. Each city can be visited on any day and a subset of cities can be visited multiple times. The goal is to determine an optimal campaign schedule consist of daily open/closed tours that visit some cities and maximizes the total net benefit while respecting daily maximum tour duration constraints and the necessity to return campaign base frequently. This problem arises in several real-life applications and particularly in election logistics where depots are not fixed. We formulate the problem as a mixed integer linear programming (MILP), in which we capture as many real-world aspects of the RSP as possible. We also present a hybrid metaheuristic algorithm based on a VNS with TS conditions. The initial feasible solution is constructed via a new matheuristc approach based on the decomposition of the original problem. Next, this solution is improved in terms of the collected rewards using the proposed local search procedure. We consider a set of 81 cities in Turkey and a campaign of 30 days as our largest instance. Computational results on real-world instances show that the developed algorithm could find near-optimal solutions effectively.

Keywords: optimization, routing, election logistics, heuristics

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Authors: Nadine Yehya, Chantal Maatouk

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Low energy buildings have been developed to achieve global climate commitments in reducing energy consumption. They comprise energy efficient buildings, zero energy buildings, positive buildings and passive house buildings. The reduced energy demands in Low Energy buildings call for advanced building energy modeling that focuses on studying active building systems such as heating, cooling and ventilation, improvement of systems performances, and development of control systems. Modeling and building simulation have expanded to cover different modeling approach i.e.: detailed physical model, dynamic empirical models, and hybrid approaches, which are adopted by various simulation tools. This paper uses DesignBuilder with EnergyPlus simulation engine in order to; First, study the impact of efficiency measures on building energy behavior by comparing Low energy residential model to a conventional one in Beirut-Lebanon. Second, choose the appropriate energy systems for the studied case characterized by an important cooling demand. Third, study dynamic modeling of Variable Refrigerant Flow (VRF) system in EnergyPlus that is chosen due to its advantages over other systems and its availability in the Lebanese market. Finally, simulation of different energy systems models with different modeling approaches is necessary to confront the different modeling approaches and to investigate the interaction between energy systems and building envelope that affects the total energy consumption of Low Energy buildings.

Keywords: physical model, variable refrigerant flow heat pump, dynamic modeling, EnergyPlus, the modeling approach

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Authors: Pedram Saadati, Zahra Nazari

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In the last decade, the role and importance of knowledge-based technological businesses in the insurance industry has greatly increased, and due to the weakness of previous studies in Iran, the current research deals with the design of the InsurTech empowerment model. In order to obtain the conceptual model of the research, a hybrid framework has been used. The statistical population of the research in the qualitative part were experts, and in the quantitative part, the InsurTech activists. The tools of data collection in the qualitative part were in-depth and semi-structured interviews and structured self-interaction matrix, and in the quantitative part, a researcher-made questionnaire. In the qualitative part, 55 indicators, 20 components and 8 concepts (dimensions) were obtained by the content analysis method, then the relationships of the concepts with each other and the levels of the components were investigated. In the quantitative part, the information was analyzed using the descriptive analytical method in the way of path analysis and confirmatory factor analysis. The proposed model consists of eight dimensions of supporter capability, supervisor of insurance innovation ecosystem, managerial, financial, technological, marketing, opportunity identification, innovative InsurTech capabilities. The results of statistical tests in identifying the relationships of the concepts with each other have been examined in detail and suggestions have been presented in the conclusion section.

Keywords: insurTech, knowledge-base, empowerment model, factor analysis, insurance

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Authors: Adam Gorine, Faten Spondon

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Python is considered the most popular programming language and offers its own ecosystem for archiving and maintaining open-source software packages. This system is called the python package index (PyPI), the repository of this programming language. Unfortunately, one-third of these software packages have vulnerabilities that allow attackers to execute code automatically when a vulnerable or malicious package is installed. This paper contributes to large-scale empirical studies investigating security issues in the python ecosystem by evaluating package vulnerabilities. These provide a series of implications that can help the security of software ecosystems by improving the process of discovering, fixing, and managing package vulnerabilities. The vulnerable dataset is generated using the NVD, the national vulnerability database, and the Snyk vulnerability dataset. In addition, we evaluated 807 vulnerability reports in the NVD and 3900 publicly known security vulnerabilities in Python Package Manager (pip) from the Snyk database from 2002 to 2022. As a result, many Python vulnerabilities appear in high severity, followed by medium severity. The most problematic areas have been improper input validation and denial of service attacks. A hybrid scanning tool that combines the three scanners bandit, snyk and dlint, which provide a clear report of the code vulnerability, is also described.

Keywords: Python vulnerabilities, bandit, Snyk, Dlint, Python package index, ecosystem, static analysis, malicious attacks

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Authors: Lucas Viani, Benedetta Mennucci, Soo Young Park, Johannes Gierschner

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Organic semiconductors have attracted the attention of the scientific community in the past decades due to their unique physicochemical properties, allowing new designs and alternative device fabrication methods. Until today, organic electronic devices are largely based on conjugated polymers mainly due to their easy processability. In the recent years, due to moderate ET and CT efficiencies and the ill-defined nature of polymeric systems the focus has been shifting to small conjugated molecules with well-defined chemical structure, easier control of intermolecular packing, and enhanced CT and ET properties. It has led to the synthesis of new small molecules, followed by the growth of their crystalline structure and ultimately by the device preparation. This workflow is commonly followed without a clear knowledge of the ET and CT properties related mainly to the macroscopic systems, which may lead to financial and time losses, since not all materials will deliver the properties and efficiencies demanded by the current standards. In this work, we present a theoretical workflow designed to predict the key properties of ET of these new materials prior synthesis, thus speeding up the discovery of new promising materials. It is based on quantum mechanical, hybrid, and classical methodologies, starting from a single molecule structure, finishing with the prediction of its packing structure, and prediction of properties of interest such as static and averaged excitonic couplings, and exciton diffusion length.

Keywords: organic semiconductor, organic crystals, energy transport, excitonic couplings

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Authors: Niklas Panten, Eberhard Abele

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This paper presents a novel approach for real-time and near-optimal control of industrial smart grids by deep reinforcement learning (DRL). To achieve highly energy-efficient factory systems, the energetic linkage of machines, technical building equipment and the building itself is desirable. However, the increased complexity of the interacting sub-systems, multiple time-variant target values and stochastic influences by the production environment, weather and energy markets make it difficult to efficiently control the energy production, storage and consumption in the hybrid industrial smart grids. The studied deep reinforcement learning approach allows to explore the solution space for proper control policies which minimize a cost function. The deep neural network of the DRL agent is based on a multilayer perceptron (MLP), Long Short-Term Memory (LSTM) and convolutional layers. The agent is trained within multiple Modelica-based factory simulation environments by the Advantage Actor Critic algorithm (A2C). The DRL controller is evaluated by means of the simulation and then compared to a conventional, rule-based approach. Finally, the results indicate that the DRL approach is able to improve the control performance and significantly reduce energy respectively operating costs of industrial smart grids.

Keywords: industrial smart grids, energy efficiency, deep reinforcement learning, optimal control

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Authors: C. A. Anser Pasha

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In this paper, a new Vehicular Speed Detection Camera System that is applicable as an alternative to traditional radars with the same accuracy or even better is presented. The real-time measurement and analysis of various traffic parameters such as speed and number of vehicles are increasingly required in traffic control and management. Image processing techniques are now considered as an attractive and flexible method for automatic analysis and data collections in traffic engineering. Various algorithms based on image processing techniques have been applied to detect multiple vehicles and track them. The SDCS processes can be divided into three successive phases; the first phase is Objects detection phase, which uses a hybrid algorithm based on combining an adaptive background subtraction technique with a three-frame differencing algorithm which ratifies the major drawback of using only adaptive background subtraction. The second phase is Objects tracking, which consists of three successive operations - object segmentation, object labeling, and object center extraction. Objects tracking operation takes into consideration the different possible scenarios of the moving object like simple tracking, the object has left the scene, the object has entered the scene, object crossed by another object, and object leaves and another one enters the scene. The third phase is speed calculation phase, which is calculated from the number of frames consumed by the object to pass by the scene.

Keywords: radar, image processing, detection, tracking, segmentation

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Authors: Andrea Tundis, Carlos García Cordero, Rolf Egert, Alfredo Garro, Max Mühlhäuser

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Resilience is an important system property that relies on the ability of a system to automatically recover from a degraded state so as to continue providing its services. Resilient systems have the means of detecting faults and failures with the added capability of automatically restoring their normal operations. Mastering resilience in the domain of Cyber-Physical Systems is challenging due to the interdependence of hybrid hardware and software components, along with physical limitations, laws, regulations and standards, among others. In order to overcome these challenges, this paper presents a modeling approach, based on the concept of Dynamic Cells, tailored to the management of Smart Grids. Additionally, a heuristic algorithm that works on top of the proposed modeling approach, to find resilient configurations, has been defined and implemented. More specifically, the model supports a flexible representation of Smart Grids and the algorithm is able to manage, at different abstraction levels, the resource consumption of individual grid elements on the presence of failures and faults. Finally, the proposal is evaluated in a test scenario where the effectiveness of such approach, when dealing with complex scenarios where adequate solutions are difficult to find, is shown.

Keywords: cyber-physical systems, energy management, optimization, smart grids, self-healing, resilience, security

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Authors: Ricardo Daziano

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In the analysis and planning of the mobility ecosystem, preferences for ride-hailing over incumbent street-hailing services need better understanding. In this paper, a seminonparametric discrete choice model that allows for flexible preference heterogeneity is fitted with data from a discrete choice experiment among adult commuters in Montreal, Canada (N=760). Participants chose among Uber, Teo (a local electric ride-hailing service that was in operation when data was collected in 2018), and a standard taxi when presented with information about cost, time (on-trip, waiting, walking), powertrain of the car (gasoline/hybrid) for Uber and taxi, and whether the available electric Teo was a Tesla (which was one of the actual features of the Teo fleet). The fitted flexible model offers several behavioral insights. Waiting time for ride-hailing services is associated with a statistically significant but low marginal disutility. For other time components, including on-ride, and street-hailing waiting and walking the estimates of the value of time show an interesting pattern: whereas in a conditional logit on-ride time reductions are valued higher, in the flexible LML specification means of the value of time follow the expected pattern of waiting and walking creating a higher disutility. At the same time, the LML estimates show the presence of important, multimodal unobserved preference heterogeneity.

Keywords: discrete choice, electric taxis, ridehailing, semiparametrics

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Authors: Özlem Ateş Sönmezoğlu, Begüm Terzi, Ahmet Yıldırım, Ramazan Özbey

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The basic criteria which determine durum wheat quality is its suitability for pasta processing that is pasta making quality. Bright yellow color is a desired property in pasta products. Durum wheat pasta making quality is affected by grain pigment content and oxidative enzymes which affect adversely bright yellow color. Of the oxidative enzymes, lipoxygenase LOX is the most effective one on oxidative bleaching of yellow pigments in durum wheat products. Thus, wheat cultivars that are high in yellow pigments but low in LOX enzyme activity should be preferred for the production of pasta with high color quality. The aim of this study was to reduce lipoxygenase activities of the backcross durum wheat lines that were previously improved for their protein quality. For this purpose, two advanced lines with different parents (TMB2 and TMB3) were used recurrent parents. Also, Gediz-75 wheat with low LOX enzyme activity was used as the gene source. In all of the generations, backcrossed plants carrying the targeted gene region (Lpx-B1.1) were selected using SSR markers by marker assisted selection method. As a result, the study will be completed in three years instead of six years required in a classical backcross breeding study, leading to the development of high-quality candidate varieties. This research has been financially supported by TÜBİTAK (Project No: 112T910).

Keywords: durum wheat, lipoxygenase, LOX, Lpx-B1.1, MAS, Triticum durum

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Authors: Shraddha Palikhe, Sunkuk Kim

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The construction industry is the most labor intensive in Nepal. It is obvious that construction is a major sector and any productivity enhancement activity in this sector will have a positive impact in the overall improvement of the national economy. Previous studies have stated that Nepal has poor labor productivity among other south Asian countries. Though considerable research has been done on productivity factors in other countries, no study has addressed labor productivity issues in Nepal. Therefore, the main objective of this study is to identify and hierarchy the influence factors for poor labor productivity. In this study, a questionnaire approach is chosen as a method of the survey from thirty experts involved in the construction industry, such as Architects, Civil Engineers, Project Engineers and Site Engineers. A survey was conducted in Nepal, to identify the major factors impacting construction labor productivity. Analytic Hierarchy Process (AHP) analysis method was used to understand the underlying relationships among the factors, categorized into five groups, namely (1) Labor-management group; (2) Material management group; (3) Human labor group; (4) Technological group and (5) External group and was divided into 33 subfactors. AHP was used to establish the relative importance of the criteria. The AHP makes pairwise comparisons of relative importance between hierarchy elements grouped by labor productivity decision criteria. Respondents were asked to answer based on their experience of construction works. On the basis of the respondent’s response, weight of all the factors were calculated and ranked it. The AHP results were tabulated based on weight and ranking of influence factors. AHP model consists of five main criteria and 33 sub-criteria. Among five main criteria, the scenario assigns a weight of highest influential factor i.e. 26.15% to human labor group followed by 23.01% to technological group, 22.97% to labor management group, 17.61% material management group and 10.25% to external group. While in 33 sub-criteria, the most influential factor for poor productivity in Nepal are lack of monetary incentive (20.53%) for human labor group, unsafe working condition (17.55%) for technological group, lack of leadership (18.43%) for labor management group, unavailability of tools at site (25.03%) for material management group and strikes (35.01%) for external group. The results show that AHP model associated criteria are helpful to predict the current situation of labor productivity. It is essential to consider these influence factors to improve the labor productivity in the construction industry of Nepal.

Keywords: construction, hierarchical analysis, influence factors, labor productivity

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Authors: Lorena Caires Moreira, Marcos Kauffman

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This paper outlines the results of experimental research on deploying an emerging augmented reality (AR) system for real-time task assistance of highly customized and high-risk manual operations. The focus is on operators’ training capabilities and the aim is to test if such technologies can support achieving higher levels of knowledge retention and accuracy of task execution to improve health and safety (H and S) levels. The proposed solution is tested and validated using a real-world case study of electric vehicles’ battery module assembly. The experimental results revealed that the proposed AR method improved the training practices by increasing the knowledge retention levels from 40% to 84% and improved the accuracy of task execution from 20% to 71%, compared to the traditional paper-based method. The results of this research can be used as a demonstration of how emerging technologies are advancing the choice of manual, hybrid, or fully automated processes by promoting the connected worker (Industry 5.0) and supporting manufacturing in becoming more resilient in times of constant market changes.

Keywords: augmented reality, extended reality, connected worker, XR-assisted operator, manual assembly, industry 5.0, smart training, battery assembly

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Authors: Ander Pomposo

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Purpose: The aim of this study was to investigate the impact that dialogue has on the relationship between shared leadership and innovative behavior and the importance of dialogue in innovation. This study wants to contribute to the literature by providing theorists and researchers a better understanding of how to move forward in the studies of moderator variables in the relationship between shared leadership and team outcomes such as innovation. Methodology: A systematic review of the literature, originally adopted from the medical sciences but also used in management and leadership studies, was conducted to synthesize research in a systematic, transparent and reproducible manner. A final sample of 48 empirical studies was scientifically synthesized. Findings: Shared leadership gives a better solution to team management challenges and goes beyond the classical, hierarchical, or vertical leadership models based on the individual leader approach. One of the outcomes that emerge from shared leadership is team innovative behavior. To intensify the relationship between shared leadership and team innovative behavior, and understand when is more effective, the moderating effects of other variables in this relationship should be examined. This synthesis of the empirical studies revealed that dialogue is a moderator variable that has an impact on the relationship between shared leadership and team innovative behavior when leadership is understood as a relational process. Dialogue is an activity between at least two speech partners trying to fulfill a collective goal and is a way of living open to people and ideas through interaction. Dialogue is productive when team members engage relationally with one another. When this happens, participants are more likely to take responsibility for the tasks they are involved and for the relationships they have with others. In this relational engagement, participants are likely to establish high-quality connections with a high degree of generativity. This study suggests that organizations should facilitate the dialogue of team members in shared leadership which has a positive impact on innovation and offers a more adaptive framework for the leadership that is needed in teams working in complex work tasks. These results uncover the necessity of more research on the role that dialogue plays in contributing to important organizational outcomes such as innovation. Case studies describing both best practices and obstacles of dialogue in team innovative behavior are necessary to gain a more detailed insight into the field. It will be interesting to see how all these fields of research evolve and are implemented in dialogue practices in the organizations that use team-based structures to deal with uncertainty, fast-changing environments, globalization and increasingly complex work.

Keywords: dialogue, innovation, leadership, shared leadership, team innovative behavior

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Authors: Prapin Nuchpiam

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The importance of social innovation has become increasingly significant as the process of developing effective solutions to social problems and being a force of change for people’s better quality of life. In order to promote social innovation, active collaboration between government, business organizations, and the civil society sector is needed. A proper legal framework also plays an important role in building the social innovation ecosystem. Currently, there is no specific law designed for social innovation or a so-called “social innovation law”. One of the legal frameworks for social innovation is the development of hybrid legal forms for social enterprises such as the UK’s Community Interest Company (CIC), the US’s Low-Profit Limited Liability Company (L3C) and the US’s Benefit Corporation (B-Corp), among others. This is because social enterprise is recognized as an organizational form of social innovation with its aim for social benefit goals and the achievement of financial sustainability. Nonetheless, there has been a debate over the differences and similarities between social innovation and social enterprise. Thus, social enterprise law might not fit well with social innovation, resulting in a search for a legal framework specially designed for social innovation. This paper aims to study the interrelationship between social innovation, social enterprise, and the role of law to see whether we need a specific law for social innovation. If so, what should such a legal framework look like? The paper will provide a critical analysis of innovative legal forms for social enterprise as a type of social innovation law. A proper legal framework for social innovation could help promote the sector, which could result in finding new solutions to social problems. It will also bring about a greater common understanding of the exciting development of legal scholarship in this way, which will, in turn, serve as a productive basis or direction for further research on this increasingly important topic.

Keywords: social innovation, social enterprise, legal framework, regulation

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Authors: Noury Bakrim

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From the point of view of language morphodynamics, interpretative Readability of the text-result (the stasis) is not the external hermeneutics of its various potential reading events but the paradigmatic, semantic immanence of its dynamics. In other words, interpretative Readability articulates the potential tension between projection (intentionality of the discursive event) and the result (Readability within the syntagmatic stasis). We then consider that translation represents much more a metalinguistic conversion of neurocognitive bilingual sub-routines and modular relations than a semantic equivalence. Furthermore, the actualizing Readability (the process of rewriting a target text within a target language/genre) builds upon the descriptive level between the generative syntax/semantic from and its paradigmatic potential translatability. Translation corpora reveal the evidence of a certain focusing on the positivist stasis of the source text at the expense of its interpretative Readability. For instance, Fluchere's brilliant translation of Miller's Tropic of cancer into French realizes unconsciously an inversion of the hierarchical relations between Life Thought and Fable: From Life Thought (fable) into Fable (Life Thought). We could regard the translation of Bernard Kreiss basing on Canetti's work die englischen Jahre (les annees anglaises) as another inversion of the historical scale from individual history into Hegelian history. In order to describe and test both translation process and result, we focus on the pedagogical practice which enables various principles grounding in interpretative/actualizing Readability. Henceforth, establishing the analytical uttering dynamics of the source text could be widened by other practices. The reversibility test (target - source text) or the comparison with a second translation in a third language (tertium comparationis A/B and A/C) point out the evidence of an impossible event. Therefore, it doesn't imply an uttering idealistic/absolute source but the irreducible/non-reproducible intentionality of its production event within the experience of world/discourse. The aim of this paper is to conceptualize translation as the tension between interpretative and actualizing Readability in a new approach grounding in morphodynamics of language and Translatability (mainly into French) within literary and non-literary texts articulating theoretical and described pedagogical corpora.

Keywords: readability, translation as deverbalization, translation as conversion, Tertium Comparationis, uttering actualization, translation pedagogy

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Authors: Kottaridi Klimentia, Demopoulos Vasilis, Sidiropoulos Anastasios, Ihara Diego, Nikolaidis Vasileios, Antonopoulos Dimitrios

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Aflatoxins are highly poisonous and carcinogenic compounds produced by species of the genus Aspergillus spp. that can infect a variety of agricultural foods, including dried figs. Biological and environmental factors, such as population, pathogenicity, and aflatoxinogenic capacity of the strains, topography, soil, and climate parameters of the fig orchards, are believed to have a strong effect on aflatoxin levels. Existing methods for aflatoxin detection and measurement, such as high performance liquid chromatography (HPLC), and enzyme-linked immunosorbent assay (ELISA), can provide accurate results, but the procedures are usually time-consuming, sample-destructive, and expensive. Predicting aflatoxin levels prior to crop harvest is useful for minimizing the health and financial impact of a contaminated crop. Consequently, there is interest in developing a tool that predicts aflatoxin levels based on topography and soil analysis data of fig orchards. This paper describes the development of a risk assessment tool for the contamination of aflatoxin on dried figs, based on the location and altitude of the fig orchards, the population of the fungus Aspergillus spp. in the soil, and soil parameters such as pH, saturation percentage (SP), electrical conductivity (EC), organic matter, particle size analysis (sand, silt, clay), the concentration of the exchangeable cations (Ca, Mg, K, Na), extractable P, and trace of elements (B, Fe, Mn, Zn and Cu), by employing machine learning methods. In particular, our proposed method integrates three machine learning techniques, i.e., dimensionality reduction on the original dataset (principal component analysis), metric learning (Mahalanobis metric for clustering), and k-nearest neighbors learning algorithm (KNN), into an enhanced model, with mean performance equal to 85% by terms of the Pearson correlation coefficient (PCC) between observed and predicted values.

Keywords: aflatoxins, Aspergillus spp., dried figs, k-nearest neighbors, machine learning, prediction

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Authors: Ghada Badr, Manar Hosny, Nuha Bintayyash, Eman Albilali, Souad Larabi Marie-Sainte

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The median problem is significantly applied to derive the most reasonable rearrangement phylogenetic tree for many species. More specifically, the problem is concerned with finding a permutation that minimizes the sum of distances between itself and a set of three signed permutations. Genomes with equal number of genes but different order can be represented as permutations. In this paper, an algorithm, namely BeamGA median, is proposed that combines a heuristic search approach (local beam) as an initialization step to generate a number of solutions, and then a Genetic Algorithm (GA) is applied in order to refine the solutions, aiming to achieve a better median with the smallest possible reversal distance from the three original permutations. In this approach, any genome rearrangement distance can be applied. In this paper, we use the reversal distance. To the best of our knowledge, the proposed approach was not applied before for solving the median problem. Our approach considers true biological evolution scenario by applying the concept of common intervals during the GA optimization process. This allows us to imitate a true biological behavior and enhance genetic approach time convergence. We were able to handle permutations with a large number of genes, within an acceptable time performance and with same or better accuracy as compared to existing algorithms.

Keywords: median problem, phylogenetic tree, permutation, genetic algorithm, beam search, genome rearrangement distance

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Authors: Basem Kamal Abasakhiroun Farag

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Fashion, like many other areas of design, has undergone numerous developments over the centuries. The aim of the article is to recognize and evaluate the importance of advanced technologies in fashion design and to examine how they are transforming the role of contemporary fashion designers by transforming the creative process. It also discusses how contemporary culture is involved in such developments and how it influences fashion design in terms of conceptualization and production. The methodology used is based on examining various examples of the use of technology in fashion design and drawing parallels between what was feasible then and what is feasible today. Comparison of case studies, examples of existing fashion designs and experiences with craft methods; We therefore observe patterns that help us predict the direction of future developments in this area. Discussing the technological elements in fashion design helps us understand the driving force behind the trend. The research presented in the article shows that there is a trend towards significantly increasing interest and progress in the field of fashion technology, leading to the emergence of hybrid artisanal methods. In summary, as fashion technologies advance, their role in clothing production is becoming increasingly important, extending far beyond the humble sewing machine.

Keywords: fashion, identity, such, textiles ambient intelligence, proximity sensors, shape memory materials, sound sensing garments, wearable technology bio textiles, fashion trends, nano textiles, new materials, smart textiles, techno textiles fashion design, functional aesthetics, 3D printing.

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Authors: Lorand Ujhazi

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The vast majority of existing canonical studies about migration are focused on examining the general pastoral and legal regulations of the Catholic Church. The weakness of this approach is that it ignores a number of important factors; like the financial, legal and personal circumstances of a particular church or the canonical position of certain organizations which actually look after the immigrants. This paper is a case study, which analyses the current and historical migration related policies and activities of the Catholic Church in Hungary. To achieve this goal the study uses canon law, historical publications, various instructions and communications issued by church superiors, Hungarian and foreign media reports and the relevant Hungarian legislation. The paper first examines how the Hungarian Catholic Church assisted migrants like Armenians fleeing from the Ottoman Empire, Poles escaping during the Second World War, East German and Romanian citizens in the 1980s and refugees from the former Yugoslavia in the 1990s. These events underline the importance of past historical experience in the development of contemporary pastoral and humanitarian policy of the Catholic Church in Hungary. Then the paper turns to the events of the ongoing crisis by describing the unique challenges faced by churches in transit countries like Hungary. Then the research contrasts these findings with the typical responsibilities of churches in countries which are popular destinations for immigrants. The next part of the case study focuses on the changes to the pre-crisis legal and canonical framework which influenced the actions of hierarchical and charity organizations in Hungary. Afterwards, the paper illustrates the dangers of operating in an unclear legal environment, where some charitable activities of the church like a fundraising campaign may be interpreted as a national security risk by state authorities. Then the paper presents the reactions of Hungarian academics to the current migration crisis and finally it offers some proposals how to improve parts of Canon Law which govern immigration. The conclusion of the paper is that during the formulation of the central refugee policy of the Catholic Church decision makers must take into consideration the peculiar circumstances of its particular churches. This approach may prevent disharmony between the existing central regulations, the policy of the Vatican and the operations of the local church organizations.

Keywords: canon law, Catholic Church, civil law, Hungary, immigration, national security

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Authors: M. Talebzadegan, S. Bina , I. Riazi

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The purpose of this paper is to present an active solar energy system to supply heating demands of the teaching staff dormitory of Islamic Azad University of Ramhormoz. The design takes into account the solar radiations and climate data of Ramhormoz town and is based on the daily warm water consumption for health demands of 450 residents of the dormitory, which is equal to 27000 lit of 50 C° water, and building heating requirements with an area of 3500 m² well-protected by heatproof materials. First, heating demands of the building were calculated, then a hybrid system made up of solar and fossil energies was developed and finally, the design was economically evaluated. Since there is only roof space for using 110 flat solar water heaters, the calculations were made to hybridize solar water heating system with heat pumping system in which solar energy contributes 67% of the heat generated. According to calculations, the Net Present Value “N.P.V.” of revenue stream exceeds “N.P.V.” of cash paid off in this project over three years, which makes economically quite promising. The return of investment and payback period of the project is 4 years. Also, the Internal Rate of Return (IRR) of the project was 25%, which exceeds bank rate of interest in Iran and emphasizes the desirability of the project.

Keywords: solar energy, heat demand, renewable, pollution

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Authors: Latif Yanar, Muammer Kaçan

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Decision support systems are getting more important in many fields of science and technology and used effectively especially when the problems to be solved are complicated with many criteria. In this kind of problems one of the main challenges for the decision makers are that sometimes they cannot produce a countable data for evaluating the criteria but the knowledge and sense of experts. In recent years, fuzzy set theory and fuzzy logic based decision models gaining more place in literature. In this study, a decision support model to determine a country to build naval base is proposed and the application of the model is performed, considering Turkish Navy by the evaluations of Turkish Navy officers and academicians of international relations departments of various Universities located in Istanbul. The results achieved from the evaluations made by the experts in our model are calculated by a decision support tool named DESTEC 1.0, which is developed by the authors using C Sharp programming language. The tool gives advices to the decision maker using Analytic Hierarchy Process, Analytic Network Process, Fuzzy Analytic Hierarchy Process and Fuzzy Analytic Network Process all at once. The calculated results for five foreign countries are shown in the conclusion.

Keywords: decision support system, analytic hierarchy process, fuzzy analytic hierarchy process, analytic network process, fuzzy analytic network process, naval base, country selection, international relations

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Authors: Liu Si, Wang Chunmei, Liu Huangmei

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A prominent component of the semantic versus pragmatic debate, scalar implicature (SI) has been gaining great attention ever since it was proposed by Horn. The constant debate is between the structural and pragmatic approach. The former claims that generation of SI is costless, automatic, and dependent mostly on the structural properties of sentences, whereas the latter advocates both that such generation is largely dependent upon context, and that the process is costly. Many experiments, among which Katsos’s text comprehension experiments are influential, have been designed and conducted in order to verify their views, but the results are not conclusive. Besides, most of the experiments were conducted in English language materials. Katsos conducted one off-line and three on-line text comprehension experiments, in which the previous shortcomings were addressed on a certain extent and the conclusion was in favor of the pragmatic approach. We intend to test the results of Katsos’s experiment in Chinese scalar implicature. Four experiments in both off-line and on-line conditions to examine the generation and response time of SI in Chinese "yixie" (some) and "quanbu (dou)" (all) will be conducted in order to find out whether the structural or the pragmatic approach could be sustained. The study mainly aims to answer the following questions: (1) Can SI be generated in the upper- and lower-bound contexts as Katsos confirmed when Chinese language materials are used in the experiment? (2) Can SI be first generated, then cancelled as default view claimed or can it not be generated in a neutral context when Chinese language materials are used in the experiment? (3) Is SI generation costless or costly in terms of processing resources? (4) In line with the SI generation process, what conclusion can be made about the cognitive processing model of language meaning? Is it a parallel model or a linear model? Or is it a dynamic and hierarchical model? According to previous theoretical debates and experimental conflicts, presumptions could be made that SI, in Chinese language, might be generated in the upper-bound contexts. Besides, the response time might be faster in upper-bound than that found in lower-bound context. SI generation in neutral context might be the slowest. At last, a conclusion would be made that the processing model of SI could not be verified by either absolute structural or pragmatic approaches. It is, rather, a dynamic and complex processing mechanism, in which the interaction of language forms, ad hoc context, mental context, background knowledge, speakers’ interaction, etc. are involved.

Keywords: cognitive linguistics, pragmatics, scalar implicture, experimental study, Chinese language

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Authors: Jesvin Puay-Hwa Yeo, Laavanya Kathiravelu, Sa’Eda Binte Buang

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In the early days, myths and taboos were used by our ancestors to give explanations to the existence of nature and man, as well as to propitiate fortunes and to avoid unluckiness and harm. Myths and taboos are deeply rooted in our cultures and environment, and they form certain characteristics of any society, even in modern societies. With decades of the three main ethnic communities in Singapore – Malay, Indian and Chinese – living together, there has been intermingling and intermixing of traditions and practices. This may mean that what we think is a ‘Malay’ practice is actually one that is a hybrid of the Chinese and Malay. A good example would be the practice of covering all mirrors in a house of mourning. Therefore, the proposed seeks to explore and understand the underlying social influences of Singapore’s oral tradition. As part of a bigger cultural research project: Designing Cultures, the proposed paper focused on using secondary data to contribute to the overall cultural understanding of the integral connections between oral traditions, people and landscapes. The proposed paper will discuss in details the initials findings of the research project, including the two manners that contributed to the intermixing of myths and taboos. The first is the presence of social institutions such as religions, and the second is the presence of cross-cultural minorities such as the Straits Chinese. As well as other observations included the use and influence of Chinese oral traditions such as folklore among the early Chinese immigrants through social institutions.

Keywords: cultural belief, multiracial society, myths, oral tradition

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Authors: Dana El-Mughayyar, Neil Manson, Erin Bigney, Eden Richardson, Dean Tripp, Edward Abraham

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Use of narcotics to treat pain has increased over the past two decades and is a contributing factor to the current public health crisis. Understanding the pre-operative risks of chronic narcotic use may be aided through investigation of psychological measures. The objective of the reported study is to determine predictors of narcotic use two years post-surgery in a thoracolumbar spine surgery population, including an array of psychological factors. A prospective observational study of 191 consecutively enrolled adult patients having undergone thoracolumbar spine surgery is presented. Baseline measures of interest included the Pain Catastrophizing Scale (PCS), Tampa Scale for Kinesiophobia, Multidimensional Scale for Perceived Social Support (MSPSS), Chronic Pain Acceptance Questionnaire (CPAQ-8), Oswestry Disability Index (ODI), Numeric Rating Scales for back and leg pain (NRS-B/L), SF-12’s Mental Component Summary (MCS), narcotic use and demographic variables. The post-operative measure of interest is narcotic use at 2-year follow-up. Narcotic use is collapsed into binary categories of use and no use. Descriptive statistics are run. Chi Square analysis is used for categorical variables and an ANOVA for continuous variables. Significant variables are built into a hierarchical logistic regression to determine predictors of post-operative narcotic use. Significance is set at α < 0.05. Results: A total of 27.23% of the sample were using narcotics two years after surgery. The regression model included ODI, NRS-Leg, time with condition, chief complaint, pre-operative drug use, gender, MCS, PCS subscale helplessness, and CPAQ subscale pain willingness and was significant χ² (13, N=191)= 54.99; p = .000. The model accounted for 39.6% of the variance in narcotic use and correctly predicted in 79.7% of cases. Psychological variables accounted for 9.6% of the variance over and above the other predictors. Conclusions: Managing chronic narcotic usage is central to the patient’s overall health and quality of life. Psychological factors in the preoperative period are significant predictors of narcotic use 2 years post-operatively. The psychological variables are malleable, potentially allowing surgeons to direct their patients to preventative resources prior to surgery.

Keywords: narcotics, psychological factors, quality of life, spine surgery

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Authors: Muhammad Arif Khan, Haroon Idrees, Imran Aziz, Sidra Mushtaq

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Social platforms like online discussion and mailing groups are well aligned with academic as well as professional learning spaces. Professional communities are increasingly moving to online forums for sharing and capturing the intellectual abilities. This study investigated dynamics of social connectivity of yahoo mailing groups of Pakistani Library and Information Science (LIS) professionals using Graph Theory technique. Design/Methodology: Social Network Analysis is the increasingly concerned domain for scientists in identifying whether people grow together through online social interaction or, whether they just reflect connectivity. We have conducted a longitudinal study using Network Graph Theory technique to analyze the large data-set of email communication. The data was collected from three yahoo mailing groups using network analysis software over a period of six months i.e. January to June 2016. Findings of the network analysis were reviewed through focus group discussion with LIS experts and selected respondents of the study. Data were analyzed in Microsoft Excel and network diagrams were visualized using NodeXL and ORA-Net Scene package. Findings: Findings demonstrate that professionals and students exhibit intellectual growth the more they get tied within a network by interacting and participating in communication through online forums. The study reports on dynamics of the large network by visualizing the email correspondence among group members in a network consisting vertices (members) and edges (randomized correspondence). The model pair wise relationship between group members was illustrated to show characteristics, reasons, and strength of ties. Connectivity of nodes illustrated the frequency of communication among group members through examining node coupling, diffusion of networks, and node clustering has been demonstrated in-depth. Network analysis was found to be a useful technique in investigating the dynamics of the large network.

Keywords: emailing networks, network graph theory, online social platforms, yahoo mailing groups

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Authors: Drew Fockler

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This research examines how to improve an employee’s experience when transferring between departments within an organization. This research includes a historical review of a Canadian retail organization. Based on this historical review, gaps are identified between current and future visions to show where problems with existing training and development practices need to be resolved to reduce front-line employee turnover within an organization. The strategies within this paper support leaders through the LEAD: Listen, Explore, Act and Develop, Change Management Model. The LEAD Change Management Model supports the change process. This research proposes three possible solutions to improve an employee who is transferring between departments. The best solution to resolve the problem of improving an employee moving between departments experience is creating a Training Manager position within the retail store. A Training Manager position could support both employees and leadership with training and development of staff who are moving between departments. Within this research, an implementation plan using the TransX Model was created. The TransX Model is a hybrid of Leader-Member Exchange Theory and Transformational Leadership Theory to facilitate this organizational change within an organization by creating a common vision. Finally, this research provides the next steps as well as future considerations to enhance the training manager role within an organization.

Keywords: employee transfers, employee engagement, human resources, employee induction, TransX model, lead change management model

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Authors: Nipun Agarwal, David Paul, Fareed Un Din

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Strategy development and implementation is the key to an organization’s success in today’s competitive marketplace. Many organizations develop excellent strategy but are unable to implement this strategy in order to succeed. The difference between strategic goals and its implementation is called strategic error. Strategic error occurs when an organization does not have structures in place to implement their strategy. Strategy implementation happens through projects and having a project management method that provides certainty and agility will help an organization become more competitive in implementing strategy. Numerous project management methods exist in theory and practice. However, projects mainly used the Waterfall method in the past that provides certainty in terms of budget, delivery date and resourcing. It is common practice now to utilise Agile based methods. However, Agile based methods do not provide specific deadlines and budgets. But provide agility in product design and project delivery, which is useful to companies. Both Waterfall and Agile methods in some forms are the opposites of each other. Executive management prefer agility in delivery projects as the competitive landscape changes frequently. However, they also appreciate certainty in the projects being able to quantify budgets, deadlines and resources that is harder for an Agile based method to provide. This paper attempts to develop a hybrid project management method that attempts to merge these Waterfall and Agile methods to provide the positives from both these approaches.

Keywords: strategy, project management, strategy implementation, agile

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Authors: Noureddine Ramdani

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In recent years, extensive attention has been given to the study of conductive nanocomposites due to their unique properties, which are dependent on their size and shape. The potential applications of these materials include electromagnetic interference shielding, energy storage, photovoltaics, and others. These outstanding properties have led to increased interest and research in this field. In this work, a conductive poly benzoxazine nanocomposite, PBZ/Gr-Cu, was synthesized through a compression molding technique to achieve a high-performance material suitable for electromagnetic interference (EMI) shielding applications. The microstructure of the nanocomposites was analyzed using scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR). The thermal stability, electrical conductivity, and EMI shielding properties of the nanocomposites were evaluated using thermogravimetric analysis, a four-point probe, and a VNA analyzer, respectively. The TGA results revealed that the thermal stability and electrical conductivity of the nanocomposites were significantly enhanced by the incorporation of Gr/Cu nanoparticles. The nanocomposites exhibited a low percolation threshold of about 3.5 wt.% and an increase in carrier concentration and mobility of the carriers with increasing hybrid nanofiller content, causing the composites to behave as n-type semiconductors. These nanocomposites also displayed a high dielectric constant and a high dissipation factor in the frequency range of 8-12 GHz, resulting in higher EMI shielding effectiveness (SE) of 25-44 dB. These characteristics make them promising candidates for lightweight EMI shielding materials in aerospace and radar evasion applications.

Keywords: polybenzoxazine matrix, conductive nanocomposites, electrical conductivity, EMI shielding

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