Search results for: autonomous

Authors: Filip Franciszek Karuga, Szymon Turkiewicz, Marta Ditmer, Marcin Sochal, Piotr Białasiewicz, Agata Gabryelska

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Circadian rhythm, an internal coordinator of physiological processes is composed of a set of semi-autonomous clocks. Clocks are regulated through the expression of circadian clock genes which form feedback loops, creating an oscillator. The primary loop consists of activators: CLOCK, BMAL1 and repressors: CRY, PER. CLOCK can be substituted by the Neuronal PAS Domain Protein 2 (NPAS2). Orphan nuclear receptor (REV-ERB-α) is a component of the secondary major loop, modulating the expression of BMAL1. Circadian clocks might be disrupted by the obstructive sleep apnea (OSA), which has also been associated with type II diabetes mellitus (DM2). Interestingly, studies suggest that dysregulation of NPAS2 and REV-ERB-α might contribute to the pathophysiology of DM2 as well. The goal of our study was to examine the role of NPAS2 and REV-ERB-α in DM2 in OSA patients. After examination of the clinical data, all participants underwent polysomnography (PSG) to assess their apnea-hypopnea index (AHI). Based on the acquired data participants were assigned to one of 3 groups: OSA (AHI>30, no DM2; n=17 for NPAS2 and 34 for REV-ERB-α), DM2 (AHI>30 + DM2; n=7 for NPAS2 and 15 for REV-ERB-α) and control group (AHI<5, no DM2; n=16 for NPAS2 and 31 for REV-ERB-α). ELISA immunoassay was performed to assess the serum protein level of REV-ERB-α and NPAS2. The only statistically significant difference between groups was observed in NPAS2 protein level (p=0.037). Post-hoc analysis showed significant differences between the OSA and the control group (p=0.017). AHI and NPAS2 level was significantly correlated (r=-0.478, p=0.002) in all groups. A significant correlation was observed between the REV-ERB-α level and sleep efficiency (r=0.617, p=0.005) as well as sleep maintenance efficiency (r=0.645, p=0.003) in the OSA group. We conclude, that NPAS2 is associated with OSA severity and might contribute to metabolic sequelae of this disease. REV-ERB-α on the other hand can influence sleep continuity and efficiency.

Keywords: OSA, diabetes mellitus, endocrinology, chronobiology

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Authors: Alessandro Preziosi, Antonio Prioletti, Luca Castangia

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Deformable part models achieve high precision in pedestrian recognition, but all publicly available implementations are too slow for real-time applications. We implemented a deformable part model algorithm fast enough for real-time use by exploiting information about the camera position and orientation. This implementation is both faster and more precise than alternative DPM implementations. These results are obtained by computing convolutions in the frequency domain and using lookup tables to speed up feature computation. This approach is almost an order of magnitude faster than the reference DPM implementation, with no loss in precision. Knowing the position of the camera with respect to horizon it is also possible prune many hypotheses based on their size and location. The range of acceptable sizes and positions is set by looking at the statistical distribution of bounding boxes in labelled images. With this approach it is not needed to compute the entire feature pyramid: for example higher resolution features are only needed near the horizon. This results in an increase in mean average precision of 5% and an increase in speed by a factor of two. Furthermore, to reduce misdetections involving small pedestrians near the horizon, input images are supersampled near the horizon. Supersampling the image at 1.5 times the original scale, results in an increase in precision of about 4%. The implementation was tested against the public KITTI dataset, obtaining an 8% improvement in mean average precision over the best performing DPM-based method. By allowing for a small loss in precision computational time can be easily brought down to our target of 100ms per image, reaching a solution that is faster and still more precise than all publicly available DPM implementations.

Keywords: autonomous vehicles, deformable part model, dpm, pedestrian detection, real time

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Authors: Aline F. C. Pereira

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In recent years, modern slavery has increasingly gathered attention in scholarly discussions and policy debates. Whereas the mainstream studies focus on forced labour and trafficking, little attention is paid to other forms of exploitation, such as degrading conditions of work –criminalised in Brazil as an autonomous type of slavery since 2003. This paper aims to bridge this gap. It adopts a mixed method that comprises both qualitative and quantitative analysis, to investigate the adjudication of 164 cases of degrading conditions of work by Brazilian labour courts. The research discloses an ungrounded reluctance to apply the domestic legal framework, as in most of the cases degrading conditions of work are not recognised as contemporary slavery, despite the law. In some cases, not even situations described as subhuman and degrading of human dignity were framed as slavery. The analysis also suggests that, as in chattel times, lack of freedom and subjection remain relevant in the legal characterisation of slave labour. The examination has further unraveled a phenomenon absent in previous studies: normalisation of precarity. By depicting precarity as natural and inevitable in rural areas, labour courts ensure conformity to the status quo and reduce the likelihood of resistance by victims. Moreover, compensations afforded to urban workers are higher than granted to rural employees, which seems to place human beings in hierarchical categories -a trace of colonialism. In sum, the findings challenge the worldwide spread assumption that Brazil addresses slavery efficiently. Conversely, the Brazilian Labour Judiciary seems to remain subservient to a colonial perspective of slavery, legitimising, and sanctioning abusive practices.

Keywords: adjudication, contemporary slavery, degrading conditions of work, normalisation of precarity

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Authors: Tanzeela Anbreen, Ammara Maqsood

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Reading into writing is one of university students' most required academic skills. The current study explored postgraduate university students’ writing quality using a corpus-based approach. Twelve postgraduate students’ literature review essays were chosen for the corpus-based analysis. These essays were chosen because students had to incorporate multiple reading sources in these essays, which was a new writing exercise for them. The students were provided feedback at least two times which comprised of the written comments by the tutor highlighting the areas of improvement and also by using the ‘track changes’ function. This exercise was repeated two times, and students submitted two drafts. This investigation included only the finally submitted work of the students. A corpus-based approach was adopted to analyse the essays because it promotes autonomous discovery and personalised learning. The aim of this analysis was to understand the existing level of students’ writing before the start of their postgraduate thesis. Text Inspector was used to analyse the quality of essays. With the help of the Text Inspector tool, the vocabulary used in the essays was compared to the English Vocabulary Profile (EVP), which describes what learners know and can do at each Common European Framework of Reference (CEFR) level. Writing quality was also measured for the Flesch reading ease score, which is a standard to describe the ease of understanding the writing content. The results reflected that students found writing essays using multiple sources challenging. In most essays, the vocabulary level achieved was between B1-B2 of the CEFL level. The study recommends that students need extensive training in developing academic writing skills, particularly in writing the literature review type assignment, which requires multiple sources citations.

Keywords: literature review essays, postgraduate students, corpus-based analysis, vocabulary proficiency

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Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini

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This paper presents a Guidance and Control (G&C) strategy to address spacecraft maneuvering problem for future Rendezvous and Docking (RVD) missions. The proposed strategy allows safe and propellant efficient trajectories for space servicing missions including tasks such as approaching, inspecting and capturing. This work provides the validation test results of the G&C laws using a Hardware-In-the-Loop (HIL) setup with two robotic mockups representing the chaser and the target spacecraft. Through this paper, the challenges of the relative motion control in space are first summarized, and in particular, the constraints imposed by the mission, spacecraft and, onboard processing capabilities. Second, the proposed algorithm is introduced by presenting the formulation of constrained Model Predictive Control (MPC) to optimize the fuel consumption and explicitly handle the physical and geometric constraints in the system, e.g. thruster or Line-Of-Sight (LOS) constraints. Additionally, the coupling between translational motion and rotational motion is addressed via dual quaternion based kinematic description and accordingly explained. The resulting convex optimization problem allows real-time implementation capability based on a detailed discussion on the computational time requirements and the obtained results with respect to the onboard computer and future trends of space processors capabilities. Finally, the performance of the algorithm is presented in the scope of a potential future mission and of the available equipment. The results also cover a comparison between the proposed algorithms with Linear–quadratic regulator (LQR) based control law to highlight the clear advantages of the MPC formulation.

Keywords: autonomous vehicles, embedded optimization, real-time experiment, rendezvous and docking, space robotics

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Authors: Houda Zouar, Hanane Sarnou

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In the 21st, century the concept of learners' autonomy is crucial. The concept of self-regulated learning has come forward as a result of enabling learners to direct their learning with autonomy towards academic goals achievement. Academic self-regulation is defined as the process by which learners systematically plan, monitor and asses their learning to achieve their academic established goals. In the field of English as a foreign language, teachers emphasise the role of learners’ autonomy to foster the process of English language learning. Consequently, academic self-regulation is considered as a vehicle to enhance autonomy among English language learners. However, not all learners can be equally self-regulators if not well assisted, mainly those novice pupils of basic education. For this matter, understanding the role of teachers in fostering academic self- regulation must be among the preliminary objectives in searching and developing this area. The present research work targets the role of the Algerian middle school teachers in enhancing academic self-regulation and teaching pupils how to learn, besides their role as models in the trajectory of teaching their pupils to become self-regulators. Despite the considerable endeavours in the field of educational setting on Self-Regulated Learning, the literature of the Algerian context indicates confined endeavours to undertake and divulge this notion. To go deeper into this study, a mixed method approach was employed to confirm our hypothesis. For data collection, teachers were observed and addressed by a questionnaire on their role in enhancing academic self- regulation among their pupils. The result of the research indicates that the attempts of middle school Algerian teachers are implicit and limited. This study emphasises the need to prepare English language teachers with the necessary skills to promote autonomous and self-regulator English learners.

Keywords: Algeria, English as a foreign language, middle school, self-regulation, Teachers' role

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Authors: Nurulhuda A. Manaf, Nor Najihah Zainal Abidin, Nur Amalina Jamaludin

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Coordinating service interactions are a vital part of developing distributed applications that are built up as networks of autonomous participants, e.g., software components, web services, online resources, involve a collaboration between a diverse number of participant services on different providers. The complexity in coordinating service interactions reflects how important the techniques and approaches require for designing and coordinating the interaction between participant services to ensure the overall goal of a collaboration between participant services is achieved. The objective of this research is to develop capability of steering a complex service interaction towards a desired outcome. Therefore, an efficient technique for modelling, generating, and verifying the coordination of service interactions is developed. The developed model describes service interactions using service choreographies approach and focusing on a declarative approach, advocating an Object Management Group (OMG) standard, Semantics of Business Vocabulary and Rules (SBVR). This model, namely, SBVR model for service choreographies focuses on a declarative deontic rule expressing both obligation and prohibition, which can be more useful in working with coordinating service interactions. The generated SBVR model is then be formulated and be transformed into Alloy model using Alloy Analyzer for verifying the generated SBVR model. The transformation of SBVR into Alloy allows to automatically generate the corresponding coordination of service interactions (service choreography), hence producing an immediate instance of execution that satisfies the constraints of the specification and verifies whether a specific request can be realised in the given choreography in the generated choreography.

Keywords: service choreography, service coordination, behavioural modelling, complex interactions, declarative specification, verification, model transformation, semantics of business vocabulary and rules, SBVR

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Authors: Recep Yücel, Cihat Kartal, Mustafa Kara

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On the basis of strategic management, it is believed in the necessity of a number of innovations in the postmodern management approach in the management of universities in our country. In this sense, some of these requirements are the integration of public and private universities, international integration, R & D status and increasing young population will create a dynamic structure. According to the postmodern management approach, universities, in our country despite being governed by the classical approach autonomous universities; academically are thought solid, to be non-hierarchical and creative. In fact, studies that require a multidisciplinary academic environment, universities and there is a close cooperation between formal and non-formal sub-units. Moreover, terms of postmodern management approaches, the requirements specified in the direction of solving the problem of an increasing number of universities in our country is considered to be more difficult. Therefore, considering the psychological impact on the academic personnel the university organizational structure, the study are trying to aim to propose an appropriate model of university organization. In this context, the study sought to answer the question how to have an impact innovation and international integration on the academic achievement of the classical organizational structure. Finally, in the study, due to the adoption of the classical organizational structure of the university, integration is considered to be difficult, academic cooperation between universities at the international level and maintaining it. In addition, it was understood that block the efforts of this organization structure, academic motivation, development and innovation. In this study under these purposes; on the basis of the existing organization and management structure of the universities in the Marmara Region in Turkey, a study was conducted with qualitative research methods. The data have been analyzed using content analysis and assessment was based on the results obtained.

Keywords: university, strategic management, postmodern management approaches, multidisciplinary studies

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Authors: Sylvester Akpah, Selasi Vondee

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Unmanned Aerial Vehicles (UAV) as they are also known, drones have attracted increasing attention in recent years due to their ubiquitous nature and boundless applications in the areas of communication, surveying, aerial photography, weather forecasting, medical delivery, surveillance amongst others. Operated remotely in real-time or pre-programmed, drones can fly autonomously or on pre-defined routes. The application of these aerial vehicles has successfully penetrated the world due to technological evolution, thus a lot more businesses are utilizing their capabilities. Unfortunately, while drones are replete with the benefits stated supra, they are riddled with some problems, mainly attributed to the complexities in learning how to master drone flights, collision avoidance and enterprise security. Additional challenges, such as the analysis of flight data recorded by sensors attached to the drone may take time and require expert help to analyse and understand. This paper presents an autonomous drone control system using a chatbot. The system allows for easy control of drones using conversations with the aid of Natural Language Processing, thus to reduce the workload needed to set up, deploy, control, and monitor drone flight missions. The results obtained at the end of the study revealed that the drone connected to the chatbot was able to initiate flight missions with just text and voice commands, enable conversation and give real-time feedback from data and requests made to the chatbot. The results further revealed that the system was able to process natural language and produced human-like conversational abilities using Artificial Intelligence (Natural Language Understanding). It is recommended that radio signal adapters be used instead of wireless connections thus to increase the range of communication with the aerial vehicle.

Keywords: artificial ntelligence, chatbot, natural language processing, unmanned aerial vehicle

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Authors: Dilliram Paudyal

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The history of taxation in Nepal dates back to antiquity. However, the modern tax system gained its momentum after the establishment of democracy in 1951, which initially focused only land tax and tariff on foreign trade. In the due time, several taxes were introduced, such as direct taxes, indirect taxes, and non-taxes. However, the tax structure in Nepal is heavily dominated by indirect taxes that contribute more than 60 % of the total revenue. The government has been mobilizing revenues through a series of tax reforms during the Tenth Five-year Plan (2002 – 2007) and successive Three-year Interim Development Plans by introducing several tax measures. However, these reforms are regressive in nature, which does not lead the overall economy towards short-run stability as well as in the long run development. Based on the literature review and discussion among government officials and few taxpayers individually and groups, this paper aims to major issues and challenges that hinder the tax reform effective in Nepal. Additionally, this paper identifies potential way and process of tax reform in Nepal. The results of the study indicate that transparency in a major problem in Nepalese tax system in Nepal, where serious structural constraints with administrative and procedural complexities envisaged in the Income Tax Act and taxpayers are often unaware of the specific size of tax which is to comply them. Some other issues include high tax rate, limited tax base, leakages in tax collection, rigid and complex Income Tax Act, inefficient and corrupt tax administration, limited potentialities of direct taxes and negative responsiveness of land tax with higher administrative costs. In the context, modality of tax structure and mobilize additional resources is to be rectified on a greater quantum by establishing an effective, dynamic and highly power driven Autonomous Revenue Board.

Keywords: corrupt, development, inefficient, taxation

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Authors: Namugenyi Ephrance Eunice, Julianne Sansa Otim, Marco Zennaro, Stephen D. Wolthusen

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The Internet of Things (IoT) is a network of connected data processing devices, mechanical and digital machinery, items, animals, or people that may send data across a network without requiring human-to-human or human-to-computer interaction. Each component has sensors that can pick up on specific phenomena, as well as processing software and other technologies that can link to and communicate with other systems and/or devices over the Internet or other communication networks and exchange data with them. IoT is increasingly being used in fields other than consumer electronics, such as public safety, emergency response, industrial automation, autonomous vehicles, the Internet of Medical Things (IoMT), and general environmental monitoring. Consumer-based IoT applications, like smart home gadgets and wearables, are also becoming more prevalent. This paper presents the main IoT deployment areas for environmental monitoring in developing regions and the backhaul options suitable for them. A detailed review of each of the list of papers selected for the study is included in section III of this document. The study includes an overview of existing IoT deployments, the underlying communication architectures, protocols, and technologies that support them. This overview shows that Low Power Wireless Area Networks (LPWANs), as summarized in Table 1, are very well suited for monitoring environment architectures designed for remote locations. LoRa technology, particularly the LoRaWAN protocol, has an advantage over other technologies due to its low power consumption, adaptability, and suitable communication range. The prevailing challenges of the different architectures are discussed and summarized in Table 3 of the IV section, where the main problem is the obstruction of communication paths by buildings, trees, hills, etc.

Keywords: communication technologies, environmental monitoring, Internet of Things, IoT deployment challenges

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Authors: Methembe Mdlalose

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This paper synthesizes the findings of a study that utilized a purposive sampling methodology laced within a grounded theory analytical framework with LED managers, mayors, and traditional leaders representing six municipalities of uThukela District of KwaZulu-Natal, South Africa. The paper critiques the two institution’s micro-relations within local governance and their overall impact on the general development discourse of rural areas. The study is located in the province of KwaZulu-Natal, a part of South Africa that experiences extremely low levels of development in rural areas and suffers from high rates of inequality, poverty, and unemployment. The paper unpacks the role of two significant stakeholders in the local sphere. Considered as the two dominant stakeholders at the local level, questions of compatibility between traditional leaders and municipal councillors often surge, as the two institutions (who represent two autonomous entities) that operate within the same operational boarders. The discussion around community development lies very deeply on accountability, which assures citizens that fruitless spending is curbed and good governance is maintained. If development is to be assured, it is vital to monitor accountability within government spheres and its departments. It is further essential to monitor the relations within local government. The findings of this research confirmed how relationships between traditional leaders and councillors can and have contributed to economic development or its stagnation thereof in rural areas. In addition, the findings revealed that there is an extensive need for the two stakeholders to work collectively, as this is a vital move in planning for development. Furthermore, the better accountability of local government and a better understanding of how clear policy and its implementation is may be a valuable asset in the discourse of community economic development in rural areas.

Keywords: economic development, traditional leadership, democratically elected councillors, local governance

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Authors: Paula Paulino, Alzira Matias, Ana Margarida Veiga Simão

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Self-regulated learning (SRL) directs students in analyzing proposed tasks, setting goals and designing plans to achieve those goals. The literature has suggested a metacognitive strategy for goal attainment known as Mental Contrasting with Implementation Intentions (MCII). This strategy involves Mental Contrasting (MC), in which a significant goal and an obstacle are identified, and Implementation Intentions (II), in which an "if... then…" plan is conceived and operationalized to overcome that obstacle. The present study proposes to assess the MCII process and whether it promotes students’ commitment towards learning goals during school tasks in sciences subjects. In this investigation, we intended to study the MCII strategy in a systemic context of the classroom. Fifty-six students from middle school and secondary education attending a public school in Lisbon (Portugal) participated in the study. The MCII strategy was explicitly taught in a procedure that included metacognitive modeling, guided practice and autonomous practice of strategy. A mental contrast between a goal they wanted to achieve and a possible obstacle to achieving that desire was instructed, and then the formulation of plans in order to overcome the obstacle identified previously. The preliminary results suggest that the MCII metacognitive strategy, applied to the school context, leads to more sophisticated reflections, the promotion of learning goals and the elaboration of more complex and specific self-regulated plans. Further, students achieve better results on school tests and worksheets after strategy practice. This study presents important implications since the MCII has been related to improved outcomes and increased attendance. Additionally, MCII seems to be an innovative process that captures students’ efforts to learn and enhances self-efficacy beliefs during learning tasks.

Keywords: implementation intentions, learning goals, mental contrasting, metacognitive strategy, self-regulated learning

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Authors: Xiang Zhang, Daohong Yang, Ziyuan Wu, Lei Li, Wanting Zhou

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Visual Simultaneous Localization and Mapping (VSLAM) uses cameras to collect information in unknown environments to realize simultaneous localization and environment map construction, which has a wide range of applications in autonomous driving, virtual reality and other related fields. At present, the related research achievements about VSLAM can maintain high accuracy in static environment. But in dynamic environment, due to the presence of moving objects in the scene, the movement of these objects will reduce the stability of VSLAM system, resulting in inaccurate localization and mapping, or even failure. In this paper, a robust VSLAM method was proposed to effectively deal with the problem in dynamic environment. We proposed a dynamic region removal scheme based on semantic segmentation neural networks and geometric constraints. Firstly, semantic extraction neural network is used to extract prior active motion region, prior static region and prior passive motion region in the environment. Then, the light weight frame tracking module initializes the transform pose between the previous frame and the current frame on the prior static region. A motion consistency detection module based on multi-view geometry and scene flow is used to divide the environment into static region and dynamic region. Thus, the dynamic object region was successfully eliminated. Finally, only the static region is used for tracking thread. Our research is based on the ORBSLAM3 system, which is one of the most effective VSLAM systems available. We evaluated our method on the TUM RGB-D benchmark and the results demonstrate that the proposed VSLAM method improves the accuracy of the original ORBSLAM3 by 70%˜98.5% under high dynamic environment.

Keywords: dynamic scene, dynamic visual SLAM, semantic segmentation, scene flow, VSLAM

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Authors: Giulia Sarego, Lorenzo Olivieri, Andrea Valmorbida, Carlo Bettanini, Giacomo Colombatti, Marco Pertile, Enrico C. Lorenzini

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International guidelines recommend removing any artificial body in Low Earth Orbit (LEO) within 25 years from mission completion. Among disposal strategies, electrodynamic tethers appear to be a promising option for LEO, thanks to the limited storage mass and the minimum interface requirements to the host spacecraft. In particular, recent technological advances make it feasible to deorbit large objects with tether lengths of a few kilometers or less. To further investigate such an innovative passive system, the European Union is currently funding the project E.T.PACK – Electrodynamic Tether Technology for Passive Consumable-less Deorbit Kit in the framework of the H2020 Future Emerging Technologies (FET) Open program. The project focuses on the design of an end of life disposal kit for LEO satellites. This kit aims to deploy a taped tether that can be activated at the spacecraft end of life to perform autonomous deorbit within the international guidelines. In this paper, the orbital performance of the E.T.PACK deorbiting kit is compared to other disposal methods. Besides, the orbital decay prediction is parametrized as a function of spacecraft mass and tether system performance. Different values of length, width, and thickness of the tether will be evaluated for various scenarios (i.e., different initial orbital parameters). The results will be compared to other end-of-life disposal methods with similar allocated resources. The analysis of the more innovative system’s performance with the tape coated with a thermionic material, which has a low work-function (LWT), for which no active component for the cathode is required, will also be briefly discussed. The results show that the electrodynamic tether option can be a competitive and performant solution for satellite disposal compared to other deorbit technologies.

Keywords: deorbiting performance, H2020, spacecraft disposal, space electrodynamic tethers

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Authors: Anna Strakowska, Marian Zaborski

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This abstract focuses an overview of the methods used to create self-healing silicone composites. It has been shown how incorporating of polyhedral oligomeric silsesquioxanes (POSS) molecules with acid and basic groups to silicone rubber affects the barrier properties, mechanical properties in room and reduced temperature or the influence on relaxation rates of the methylvinylsilicone rubber vulcanizates. Moreover, the presence of silsesquioxanes, their content and the way of composites preparing affect the amount of ionic bonds, as indicated by dynamic - mechanical thermal analysis (DMTA) as well as measurements of equilibrium swelling in toluene. The aim of this work was to study the influence of concentration and different functional groups types selected silsesquioxanes compounds on self-healing effect of silicone rubber and obtain elastomers with good barrier and mechanical properties. Composites based on the methylvinylsilicone rubber with fumed silica as the fillers were manufactured and studied. To obtain self-healing effect various silsesquioxanes with amino and acid groups were used. Every tested sample demonstrated the ability to the self-treatment. The most significant effect was observed for system containing amic-acid isobytyl POSS/ aminopropylisobutyl POSS. Composite with this silsesquioxanes was exhibited the best improvement of gas permeability after heal. Moreover, the addition of POSS with acid and basic groups clearly affects the mechanical properties of the vulcanizates. The most significant effect was observed for the composite material consisting of amic-acid isobytyl POSS / aminoethylaminopropylisobutyl POSS, which tensile strength was even greater than the reference vulcanizate with fumed silica. The development of autonomous self-healing materials could have an enormous influence on all industry branches from motorization to power industry. Self-repairing materials would have a massive impact on lengthening product lifetimes, increasing safety, and lowering product costs by reducing maintenance requirements.

Keywords: barrier properties, mechanical properties, POSS, self-healing composites

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Authors: Noor Abdelhamid

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Almost half of Cairo’s growing population is housed in self-built, self-governed informal settlements serving as an alternative in the absence of government-provided public housing. These settlements emerged as the spatial expression of informal practices or activities operating outside regulated, formal frameworks. A comprehensive narrative of political events, administrative decisions, and urban policies set the stage for the growth of informal expression in Egypt. The purpose of this qualitative inquiry is to portray informal self-governance practiced by residents in the Cairo region. This research argues that informal spatial practices offer an alternative urban framework for bottom-up development in the absence of government provisions. In the context of this study, informal self-governance is defined as the residents’ autonomous control and use of public urban space in informal settlements. The case study for this research is Ard al-Liwa, a semi-formal settlement representing the majority of informal settlement typologies in Egypt, which consist of the formal occupation of land through an uncontrolled land subdivision, zoning, and construction. An inductive methodological approach is adopted to first study informal practices as singular activities and then as components of a larger environment. The collected set of empirical data consists of audiovisual material and observations obtained during regular site visits and interviews with residents native to the settlement. Methods of analysis are synthesized to identify themes in the data: the static and dynamic use of sidewalks, the urban traces of informal building allocation and construction, the de facto right to urban space, and the resultant spatial patterns. The paper concludes by positioning the research in the context of the current architectural practice, questioning the role, and responsibility, of designers in these self-governed urban regions.

Keywords: Egypt, informal settlements, self-governance, urban framework

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Authors: Afroditi Zamanidou, Dionysios Giannakopoulos, Konstantinos Manolitsis

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A notable amount of electrical energy demand in many countries worldwide is used to cover public energy demand for road, square and other public spaces’ lighting. Renewable energy can contribute in a significant way to the electrical energy demand coverage for public lighting. This paper focuses on the sizing and design of a hybrid energy system (HES) exploiting the solar-wind energy potential to meet the electrical energy needs of lighting roads, squares and other public spaces. Moreover, the proposed HES provides coverage of the electrical energy demand for a Wi-Fi hotspot and a charging hotspot for the end-users. Alongside the sizing of the energy production system of the proposed HES, in order to ensure a reliable supply without interruptions, a storage system is added and sized. Multiple scenarios of energy consumption are assumed and applied in order to optimize the sizing of the energy production system and the energy storage system. A database with meteorological prediction data for 51 areas in Greece is developed in order to assess the possible deployment of the proposed HES. Since there are detailed meteorological prediction data for all 51 areas under investigation, the use of these data is evaluated, comparing them to real meteorological data. The meteorological prediction data are exploited to form three hourly production profiles for each area for every month of the year; minimum, average and maximum energy production. The energy production profiles are combined with the energy consumption scenarios and the sizing results of the energy production system and the energy storage system are extracted and presented for every area. Finally, the economic performance of the proposed HES in terms of Levelized cost of energy is estimated by calculating and assessing construction, operation and maintenance costs.

Keywords: energy production system sizing, Greece’s deployment potential, meteorological prediction data, wind-solar hybrid energy system, levelized cost of energy

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Authors: Mark Andrew

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Geopolitical tensions are at a thirty-year high, and the pace of technological innovation is driving asymmetry in force capabilities between nation states and between non-state actors. Technology futures are a vital component of defence capability growth, and investments in technology futures need to be informed by accurate and reliable forecasts of the options for ‘systems of systems’ innovation, development, and deployment. This paper describes a method for forecasting technology futures developed through an analysis of four key systems’ development stages, namely: technology domain categorisation, scanning results examining novel systems’ signals and signs, potential system-of systems’ implications in warfare theatres, and political ramifications in terms of funding and development priorities. The method has been applied to several technology domains, including physical systems (e.g., nano weapons, loitering munitions, inflight charging, and hypersonic missiles), biological systems (e.g., molecular virus weaponry, genetic engineering, brain-computer interfaces, and trans-human augmentation), and information systems (e.g., sensor technologies supporting situation awareness, cyber-driven social attacks, and goal-specification challenges to proliferation and alliance testing). Although the current application of the method has been team-centred using paper-based rapid prototyping and iteration, the application of autonomous language models (such as GPT-3) is anticipated as a next-stage operating platform. The importance of forecasting accuracy and reliability is considered a vital element in guiding technology development to afford stronger contingencies as ideological changes are forecast to expand threats to ecology and earth systems, possibly eclipsing the traditional vulnerabilities of nation states. The early results from the method will be subjected to ground truthing using longitudinal investigation.

Keywords: forecasting, technology futures, uncertainty, complexity

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Authors: Kyoungwoon Kim, Cuong Huynh, Cam Nguyen

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Exploding demands for more data, faster data transmission speed, less interference, more users, more wireless devices, and better reliable service-far exceeding those provided in the current mobile communications networks in the RF spectrum below 6 GHz-has led the wireless communication industry to focus on higher, previously unallocated spectrums. High frequencies in RF spectrum near (around 28 GHz) or within the millimeter-wave regime is the logical solution to meet these demands. This high-frequency RF spectrum is of increasingly important for wireless communications due to its large available bandwidths that facilitate various applications requiring large-data high-speed transmissions, reaching up to multi-gigabit per second, of vast information. It also resolves the traffic congestion problems of signals from many wireless devices operating in the current RF spectrum (below 6 GHz), hence handling more traffic. Consequently, the wireless communication industries are moving towards 5G (fifth generation) for next-generation communications such as mobile phones, autonomous vehicles, virtual reality, and the Internet of Things (IoT). The U.S. Federal Communications Commission (FCC) proved on 14th July 2016 three frequency bands for 5G around 28, 37 and 39 GHz. We present some silicon-based RFIC power amplifiers (PA) for possible implementation for 5G wireless communications around 28, 37 and 39 GHz. The 16.5-28 GHz PA exhibits measured gain of more than 34.5 dB and very flat output power of 19.4±1.2 dBm across 16.5-28 GHz. The 25.5/37-GHz PA exhibits gain of 21.4 and 17 dB, and maximum output power of 16 and 13 dBm at 25.5 and 37 GHz, respectively, in the single-band mode. In the dual-band mode, the maximum output power is 13 and 9.5 dBm at 25.5 and 37 GHz, respectively. The 10-19/23-29/33-40 GHz PA has maximum output powers of 15, 13.3, and 13.8 dBm at 15, 25, and 35 GHz, respectively, in the single-band mode. When this PA is operated in dual-band mode, it has maximum output powers of 11.4/8.2 dBm at 15/25 GHz, 13.3/3 dBm at 15/35 GHz, and 8.7/6.7 dBm at 25/35 GHz. In the tri-band mode, it exhibits 8.8/5.4/3.8 dBm maximum output power at 15/25/35 GHz. Acknowledgement: This paper was made possible by NPRP grant # 6-241-2-102 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors

Keywords: Microwaves, Millimeter waves, Power Amplifier, Wireless communications

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Authors: B. Karabuluter, O. Karaduman

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Traffic management and traffic planning are important issues, especially in big cities. Due to the increase of personal vehicles and the physical constraints of urban roads, the problem of transportation especially in crowded cities over time is revealed. This situation reduces the living standards, and it can put human life at risk because the vehicles such as ambulance, fire department are prevented from reaching their targets. Even if the city planners take these problems into account, emergency planning and traffic management are needed to avoid cases such as traffic congestion, intersections, traffic jams caused by traffic accidents or roadworks. In this study, in smart traffic management issues, proposed solutions using intelligent vehicles acting in cooperation with urban roads are examined. Traffic management is becoming more difficult due to factors such as fatigue, carelessness, sleeplessness, social behavior patterns, and lack of education. However, autonomous vehicles, which remove the problems caused by human weaknesses by providing driving control, are increasing the success of practicing the algorithms developed in city traffic management. Such intelligent vehicles have become an important solution in urban life by using 'swarm intelligence' algorithms and cooperative driving methods to provide traffic flow, prevent traffic accidents, and increase living standards. In this study, studies conducted in this area have been dealt with in terms of traffic jam, intersections, regulation of traffic flow, signaling, prevention of traffic accidents, cooperation and communication techniques of vehicles, fleet management, transportation of emergency vehicles. From these concepts, some taxonomies were made out of the way. This work helps to develop new solutions and algorithms for cities where intelligent vehicles that can perform cooperative driving can take place, and at the same time emphasize the trend in this area.

Keywords: intelligent traffic management, cooperative driving, smart driving, urban road, swarm intelligence, connected vehicles

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Authors: Gary Pattemore, Michael Edgar, Andrew Job, Marina Auad, Kathryn Job

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As critical commodities become more scarce, significant time and resources have been used to better understand complicated ore bodies and extract their full potential. These challenging ore bodies provide several pain points for geologists and engineers to overcome, poor handling of these issues flows downs stream to the processing plant affecting throughput rates and recovery. Many open cut mines utilise blast hole drilling to extract additional information to feed back into the modelling process. This method requires samples to be collected during or after blast hole drilling. Samples are then sent for assay with turnaround times varying from 1 to 12 days. This method is time consuming, costly, requires human exposure on the bench and collects elemental data only. To address this challenge, research has been undertaken to utilise hyperspectral imaging across a broad spectrum to scan samples, collars or take down hole measurements for minerals and moisture content and grade abundances. Automation of this process using unmanned vehicles and on-board processing reduces human in pit exposure to ensure ongoing safety. On-board processing allows data to be integrated into modelling workflows with immediacy. The preliminary results demonstrate numerous direct and indirect benefits from this new technology, including rapid and accurate grade estimates, moisture content and mineralogy. These benefits allow for faster geo modelling updates, better informed mine scheduling and improved downstream blending and processing practices. The paper presents recommendations for implementation of the technology in open cut mining environments.

Keywords: grade control, hyperspectral scanning, artificial intelligence, autonomous mining, machine learning

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Authors: Youcef Serhane, Abdelkrim Bouzaza, Dominique Wolbert, Aymen Amin Assadi

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Throughout history, the use of chemical weapons is not exclusive to combats between army corps; some of these weapons are also found in very targeted intelligence operations (political assassinations), organized crime, and terrorist organizations. To improve the speed of action, important technological devices have been developed in recent years, in particular in the field of protection and decontamination techniques to better protect and neutralize a chemical threat. In order to assess certain protective, decontaminating technologies or to improve medical countermeasures, tests must be conducted. In view of the great toxicity of toxic chemical agents from (real) wars, simulants can be used, chosen according to the desired application. Here, we present an investigation about using a photocatalytic filtering reactor (PFR) for highly contaminated environments containing diethyl sulfide (DES). This target pollutant is used as a simulant of CWA, namely of Yperite (Mustard Gas). The influence of the inlet concentration (until high concentrations of DES (1200 ppmv, i.e., 5 g/m³ of air) has been studied. Also, the conversion rate was monitored under different relative humidity and different flow rates (respiratory flow - standards: ISO / DIS 8996 and NF EN 14387 + A1). In order to understand the efficacity of pollutant neutralization by PFR, a kinetic model based on the Langmuir–Hinshelwood (L–H) approach and taking into account the mass transfer step was developed. This allows us to determine the adsorption and kinetic degradation constants with no influence of mass transfer. The obtained results confirm that this small configuration of reactor presents an extremely promising way for the use of photocatalysis for treatment to deal with highly contaminated environments containing real chemical warfare agents. Also, they can give birth to an individual protection device (an autonomous cartridge for a gas mask).

Keywords: photocatalysis, photocatalytic filtering reactor, diethylsulfide, chemical warfare agents

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Authors: Thiago Spilborghs Bueno Meyer, Plinio Thomaz Aquino Junior

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Through speech, which privileges the functional and interactive nature of the text, it is possible to ascertain the spatiotemporal circumstances, the conditions of production and reception of the discourse, the explicit purposes such as informing, explaining, convincing, etc. These conditions allow bringing the interaction between humans closer to the human-robot interaction, making it natural and sensitive to information. However, it is not enough to understand what is said; it is necessary to recognize emotions for the desired interaction. The validity of the use of neural networks for feature selection and emotion recognition was verified. For this purpose, it is proposed the use of neural networks and comparison of models, such as recurrent neural networks and deep neural networks, in order to carry out the classification of emotions through speech signals to verify the quality of recognition. It is expected to enable the implementation of robots in a domestic environment, such as the HERA robot from the RoboFEI@Home team, which focuses on autonomous service robots for the domestic environment. Tests were performed using only the Mel-Frequency Cepstral Coefficients, as well as tests with several characteristics of Delta-MFCC, spectral contrast, and the Mel spectrogram. To carry out the training, validation and testing of the neural networks, the eNTERFACE’05 database was used, which has 42 speakers from 14 different nationalities speaking the English language. The data from the chosen database are videos that, for use in neural networks, were converted into audios. It was found as a result, a classification of 51,969% of correct answers when using the deep neural network, when the use of the recurrent neural network was verified, with the classification with accuracy equal to 44.09%. The results are more accurate when only the Mel-Frequency Cepstral Coefficients are used for the classification, using the classifier with the deep neural network, and in only one case, it is possible to observe a greater accuracy by the recurrent neural network, which occurs in the use of various features and setting 73 for batch size and 100 training epochs.

Keywords: emotion recognition, speech, deep learning, human-robot interaction, neural networks

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Authors: Maad Kamal Al-Anni

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This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Keywords: Intrusion Detection System (IDS), Mobile Adhoc Networks (MANET), Back Propagation Algorithm (BPA), Neural Networks (NN)

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Authors: Strahinja Kovacevic, Milica Karadzic Banjac, Jasmina Vitas, Stefan Vukmanovic, Radomir Malbasa, Lidija Jevric, Sanja Podunavac-Kuzmanovic

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The present study deals with chemometric regression analysis of quality parameters and the radical scavenging ability of kombucha fermented kefir-like products obtained with winter savory (WS), peppermint (P), stinging nettle (SN) and wild thyme tea (WT) kombucha inoculums. Each analyzed sample was described by milk fat content (MF, %), total unsaturated fatty acids content (TUFA, %), monounsaturated fatty acids content (MUFA, %), polyunsaturated fatty acids content (PUFA, %), the ability of free radicals scavenging (RSA Dₚₚₕ, % and RSA.ₒₕ, %) and pH values measured after each hour from the start until the end of fermentation. The aim of the conducted regression analysis was to establish chemometric models which can predict the radical scavenging ability (RSA Dₚₚₕ, % and RSA.ₒₕ, %) of the samples by correlating it with the MF, TUFA, MUFA, PUFA and the pH value at the beginning, in the middle and at the end of fermentation process which lasted between 11 and 17 hours, until pH value of 4.5 was reached. The analysis was carried out applying univariate linear (ULR) and multiple linear regression (MLR) methods on the raw data and the data standardized by the min-max normalization method. The obtained models were characterized by very limited prediction power (poor cross-validation parameters) and weak statistical characteristics. Based on the conducted analysis it can be concluded that the resulting radical scavenging ability cannot be precisely predicted only on the basis of MF, TUFA, MUFA, PUFA content, and pH values, however, other quality parameters should be considered and included in the further modeling. This study is based upon work from project: Kombucha beverages production using alternative substrates from the territory of the Autonomous Province of Vojvodina, 142-451-2400/2019-03, supported by Provincial Secretariat for Higher Education and Scientific Research of AP Vojvodina.

Keywords: chemometrics, regression analysis, kombucha, quality control

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Authors: Zahra Ebrahimi, Abbas Moradan

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This study investigated the effect of applying different layers of activity for different Iranian intermediate EFL learner’s oral proficiency and two of its components (fluency and accura-cy) for the beneficial use of films within speaking classes. For this purpose, thirty Iranian EFL intermediate learners were selected based on availability sampling, they were divided into one experimental group and one control group, each consisting of 15 participants, who were proved to be homogeneous based on the results obtained from IELTS oral proficien-cy test prior to the treatment. Experimental Group received the treatment which was apply-ing different layers of speaking tasks according to learners’ level of fluency and accuracy. Control group received ordinal treatment of speaking classrooms. The materials for this study consisted of 11 English movies for each session, voice-recorder device, and IELTS oral proficiency tests as well as two interviews based on Ur’s oral scale for measuring fluen-cy and accuracy. The treatment was run for 12 sessions in six weeks. At the end of the treatment, all the students both in experimental and control group were given a post-test interview based on Ur’s scale. To compare and contrast the amount of progress of the learners in different groups the results of the pre-test and post-test of speaking were analysed by using T-tests. Moreover, Multivariate analysis of variance was also used to check the hypotheses. Results showed that application of different layers of activity with regard to students’ level, led to a significantly superior performance in experimental group. Thus, this study verified the positive effect of implementation of different layers of activity and tasks to achieve progress in speaking skill. It can also help to create a less stressful at-mosphere of learning in which all the students will be given specific time to speak and lead them to be autonomous learners.

Keywords: differentiated instruction, learners’ style, multiple intelligence, speaking skill, task-based activities

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Authors: Maryam Zahmatkesh

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Middle managers form a significant occupational category in organisations. They undertake a vital role, as they sit between the operational and strategic roles. Traditionally they were acting as diplomat administrators, and were only in power to meet the demands of professionals. Following the introduction of internal market, in line with the principles of New Public Management, middle managers have been considered as change agents. More recently, in the debates of middle managers, there is emphasis on entrepreneurialism and enacting strategic role. It was assumed that granting autonomy to the local organisations and the inception of semi-autonomous hospitals (Foundation Trusts in England and Board of Trustees in Iran) would give managers more autonomy to act proactively and innovatively. This thesis explores the hospital middle managers’ perception of and responses to public management reforms (in particular, hospital autonomy) in England and Iran. In order to meet the aims of the thesis, research was undertaken within the interpretative paradigm, in line with social constructivism. Data were collected from interviews with forty-five middle managers, observational fieldwork and documentary analysis across four teaching university hospitals in England and Iran. The findings show the different ways middle managers’ autonomy is constrained in the two countries. In England, middle managers have financial and human recourses, but their autonomy is constrained by government policy and targets. In Iran, middle managers are less constrained by government policy and targets, but they do not have financial and human resources to exercise autonomy. Unbalanced autonomy causes tension and frustration for middle managers. According to neo-institutional theory, organisations are deeply embedded within social, political, economic and normative settings that exert isomorphic and internal population-level pressures to conform to existing and established modes of operation. Health systems which are seeking to devolve autonomy to middle managers must appreciate the multidimensional nature of the autonomy, as well as the wider environment that organisations are embedded, if they are about to improve the performance of managers and their organisations.

Keywords: autonomy, healthcare organisations, middle managers, new public management

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Authors: K. R. Roopesh Bharatwaj, Avinash Maharana, Favour Tobi Aborisade, Roger Young

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Presently, there are few cases of complete automation of drones and its allied intelligence capabilities. In essence, the potential of the drone has not yet been fully utilized. This paper presents feasible methods to build an intelligent drone with smart capabilities such as self-driving, and obstacle avoidance. It does this through advanced Reinforcement Learning Techniques and performs object detection using latest advanced algorithms, which are capable of processing light weight models with fast training in real time instances. For the scope of this paper, after researching on the various algorithms and comparing them, we finally implemented the Deep-Q-Networks (DQN) algorithm in the AirSim Simulator. In future works, we plan to implement further advanced self-driving and object detection algorithms, we also plan to implement voice-based speech recognition for the entire drone operation which would provide an option of speech communication between users (People) and the drone in the time of unavoidable circumstances. Thus, making drones an interactive intelligent Robotic Voice Enabled Service Assistant. This proposed drone has a wide scope of usability and is applicable in scenarios such as Disaster management, Air Transport of essentials, Agriculture, Manufacturing, Monitoring people movements in public area, and Defense. Also discussed, is the entire drone communication based on the satellite broadband Internet technology for faster computation and seamless communication service for uninterrupted network during disasters and remote location operations. This paper will explain the feasible algorithms required to go about achieving this goal and is more of a reference paper for future researchers going down this path.

Keywords: convolution neural network, natural language processing, obstacle avoidance, satellite broadband technology, self-driving

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Authors: Jovana Petrovic, Biljana Pajin, Ivana Loncarevic, Aleksandar Fistes, Antun Jozinivic, Durdica Ackar, Drago Subaric

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Recovery of food wastes and their conversion to economically viable products will play a vital role for the management strategies in the years to come. Apple pomace may be considered as wastes, but they contain considerable amounts of high value reusable materials. Apple pomace, the by-product of apple juice and cider production, is a good source of fibre, particularly insoluble one. The remaining apple pulp contains 12% dry residue, which is half dietary fibre. Another remarkable aspect is its richness in polyphenols, components with antioxidant activity. Apple pomace could be an interesting alternative source for fibre and polyphenols in extruded corn meals. The extruded corn meals with the addition of finely ground apple pomace were prepared (the ratio of corn meal: apple pomace was 85:15 and 70:30). Characterization of the extrudates in terms of determining the chemical composition and colour was performed. The color of samples was measured by MINOLTA Chroma Meter CR-400 (Minolta Co., Ltd., Osaka, Japan) using D 65 lighting, a 2º standard observer angle and an 8-mm aperture in the measuring head. The following CIELab color coordinates were determined: L* – lightness, a* – redness to greenness and b* – yellowness to blueness. Protein content decreased significantly from 7.91% to 5.19% with increase in pomace from 0% to 30%, while total fibre content increase from 3.39% to 16.62%. The apple pomace addition produced extrudates with a significantly lower L* value and significantly higher a* value. This study has been fully supported by the Provincial Secretariat for High Education and Scientific Research of the Government of Autonomous Province of Vojvodina, Republic of Serbia, project 142-451-2483/2017 and the Ministry of Science and Technological Development of the Republic of Serbia (Project no. 31014).

Keywords: apple pomace, chemical composition, colour, extruded corn snack products, food waste recovery

Procedia PDF Downloads 199