Search results for: network of tourism actors

Authors: Apidet Booranawong, Wiklom Teerapabkajorndet

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An enhanced ad-hoc on-demand distance vector routing (E-AODV) protocol for control system applications in wireless sensor and actuator networks (WSANs) is proposed. Our routing algorithm is designed by considering both wireless network communication and the control system aspects. Control system error and network delay are the main selection criteria in our routing protocol. The control and communication performance is evaluated on multi-hop IEEE 802.15.4 networks for building-temperature control systems. The Gilbert-Elliott error model is employed to simulate packet loss in wireless networks. The simulation results demonstrate that the E-AODV routing approach can significantly improve the communication performance better than an original AODV routing under various packet loss rates. However, the control performance result by our approach is not much improved compared with the AODV routing solution.

Keywords: WSANs, building temperature control, AODV routing protocol, control system error, settling time, delay, delivery ratio

Procedia PDF Downloads 339

Authors: Ying Su, Morgan C. Wang

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Long-term time series forecasting is an important research area for automated machine learning (AutoML). Currently, forecasting based on either machine learning or statistical learning is usually built by experts, and it requires significant manual effort, from model construction, feature engineering, and hyper-parameter tuning to the construction of the time series model. Automation is not possible since there are too many human interventions. To overcome these limitations, this article proposed to use recurrent neural networks (RNN) through the memory state of RNN to perform long-term time series prediction. We have shown that this proposed approach is better than the traditional Autoregressive Integrated Moving Average (ARIMA). In addition, we also found it is better than other network systems, including Fully Connected Neural Networks (FNN), Convolutional Neural Networks (CNN), and Nonpooling Convolutional Neural Networks (NPCNN).

Keywords: automated machines learning, autoregressive integrated moving average, neural networks, time series analysis

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Authors: Jessica Terese Mueller, Christoph Breitsprecher, Mike Oliver Mosko

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Due to an unusually high number of asylum seekers entering Germany over the course of the past few years, the need for community interpreters has increased dramatically, in order to make the communication between asylum seekers and various actors in social and governmental agencies possible. In the field of social work in particular, there are community interpreters who possess a wide spectrum of qualifications spanning from state-certified professional interpreters with graduate degrees to lay or ad-hoc interpreters with little to no formal training. To the best of our knowledge, Germany has no official national quality standards for the training of community interpreters at present, which would serve to professionalise this field as well as to assure a certain degree of quality in the training programmes offered. Given the current demand for trained community interpreters, there is a growing number of training programmes geared toward qualifying community interpreters who work with asylum seekers in Germany. These training programmes range from short one-day workshops to graduate programmes with specialisations in Community Interpreting. As part of a larger project to develop quality standards for the qualification of community interpreters working with asylum seekers in the field of social work, a needs assessment was performed in the city-state of Hamburg and the state of North Rhine Westphalia in the form of focus groups and individual interviews with relevant actors in the field in order to determine the content and practical knowledge needed for community interpreters from the perspectives of those who work in and rely on this field. More specifically, social workers, volunteers, certified language and cultural mediators, paid and volunteer community interpreters and asylum seekers were invited to take part in focus groups in both locations, and asylum seekers, training providers, researchers, linguists and other national and international experts were individually interviewed. The responses collected in these focus groups and interviews have been analysed using Mayring’s concept of content analysis. In general, the responses indicate a high degree of overlap related to certain categories as well as some categories which seemed to be of particular importance to certain groups individually, while showing little to no relevance for other groups. For example, the topics of accuracy and transparency of the interpretations, as well as professionalism and ethical concerns were touched on in some form in most groups. Some group-specific topics which are the focus of experts were topics related to interpreting techniques and more concretely described theoretical and practical knowledge which should be covered in training programmes. Social workers and volunteers generally concentrated on issues regarding the role of the community interpreters and the importance of setting and clarifying professional boundaries. From the perspective of service receivers, asylum seekers tended to focus on the importance of having access to interpreters who are from their home region or country and who speak the same regiolect, dialect or variety as they do in order to prevent misunderstandings or misinterpretations which might negatively affect their asylum status. These results indicate a certain degree of consensus with trainings offered internationally for community interpreters.

Keywords: asylum seekers, community interpreting, needs assessment, quality standards, training

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Authors: Emmanuel Mugiraneza

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Rwanda uses defence diplomacy to pursue international collective security through different mechanisms. This paper shows that with an intent of promoting international collective security, Rwanda has constituted its defense diplomacy policy in three standpoints. First, Rwanda has formed strategic cooperation alliances with state actors, regional and international Organizations that enables her to participate in and promote international collective peace, security and cooperation. Secondary, Rwanda uses defence diplomacy to foster cooperation in to pre-empt, minimize and neutralize potential triggers that would lead to the outbreak of international conflict. Thirdly, Rwanda implements defence diplomacy policy strategy through internationally recognized operational and tactical standards while dispelling hostilities, assisting the friendly nation’s forces and or building and maintaining public confidence and trust in the areas where Rwanda Defence Force deploys for peacekeeping missions in Sudan, South Sudan, Central African Republic and Mozambique for a counterterrorism mission.

Keywords: defence diplomacy, collective security, Rwanda, Peacekeeping

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Authors: Abdorreza Rabiee, Shahla Mohammad Hoseini Mirzaei

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The advantages of distributed generations (DGs) based on renewable energy sources (RESs) leads to high penetration level of DGs in distribution network. With incorporation of DGs in distribution systems, the system reliability and security, as well as voltage profile, is improved. However, the protection of such systems is still challenging. In this paper, at first, the related papers are reviewed and then a practical scheme is proposed for coordination of OCRs in distribution system with DGs. The coordination problem is formulated as a nonlinear programming (NLP) optimization problem with the object function of minimizing total operating time of OCRs. The proposed method is studied based on a simple test system. The optimization problem is solved by General Algebraic Modeling System (GAMS) to calculate the optimal time dial setting (TDS) and also pickup current setting of OCRs. The results show the effectiveness of the proposed method and its applicability.

Keywords: distributed generation, DG, distribution network, over current relay, OCR, protection coordination, pickup current, time dial setting, TDS

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Authors: Rick Evans

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Despite over 40 years of research into why women choose not to enroll or leave undergraduate engineering programs, along with the subsequent and serious efforts to attract more women, women receiving bachelor's degrees in engineering in the US have remained disappointingly low. We know that even despite their struggles to become more welcoming and inclusive, engineering programs remain gendered, raced and classed. However, our research team has found that women who participate and indeed thrive in undergraduate engineering project teams do so in numbers that far exceed their participation in undergraduate programs. We believe part of the answer lies in the ways that project teams facilitate experiential learning, specifically providing opportunities for members to play, practice and perform. We employ a multi-case study method and assume a feminist, activist and interpretive perspective. We seek to generate concrete and context-dependent knowledge in order to explore potentially new variables and hypotheses. Our focus is to learn from those select women who are thriving. For this oral or e-poster presentation, we will focus on the results of the second of our semi-structured interviews – the learning journey interview. During this interview, we ask participants to tell us the story/ies of their participation in project teams. Our results suggest these women find joy in their experience of developing and applying engineering expertise. They experience this joy and develop their expertise in the highly patterned progression of play, practice and performance. Play is a purposeful activity in which someone enters an imaginary world, a world not yet real to them. However, this imaginary world is still very much connected to the real world, in this case, a particular kind of engineering, in that the ways of engaging are already established, codified and rule-governed. As such, these women are novices motivated to join a community of actors. Practice, better understood as practices, a count noun, is an embodied, materially interconnected collection of actions organized around the shared understandings of that community of actors. Those shared understandings reveal a social order – a particular field of engineering. No longer novices, these women begin to develop and display their emergent identities as engineers. Perform is activity meant either to demonstrate competence and/or to enable, even teach play and practice to others. As performers, these women participants become models for others. They direct play and practice, contextualizing both within a field of engineering and the specific aims of the project team community. By playing, practicing and performing engineering, women claim their identities as engineers and, equally important, have those identities acknowledged by team members. If we hope to transform our gendered, raced, classed institutions, we need to learn more about women who thrive within those institutions. We need to learn more about their processes of becoming and belonging as engineers. Our research presentation begins with a description of project teams and our multi-case study method. We then offer detailed descriptions of play, practice, and performance using the voices of women in project teams.

Keywords: engineering education, gender, identity, project teams

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Authors: Liuhui Zhu, Peng Zeng

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With the rapid development in China, the urbanization has entered the transformation and promotion stage, and its direction of development has shifted to overall regional synergy. China has a large number of towns and villages, with comparative small scale and scattered distribution, which always support and provide resources to cities leading to urban-rural opposition, so it is difficult to achieve common development in a single town or village. In this context, the regional development should focus more on towns and villages to form a synergetic system, joining the regional association with cities. Thus, the paper raises the question about how to effectively organize towns and villages system to regulate the resource allocation and improve the comprehensive value of the regional area. To answer the question, it is necessary to find a suitable research unit and analysis of its present situation of towns and villages system for optimal development. By combing relevant researches and theoretical models, the county is the most basic administrative unit in China, which can directly guide and regulate the development of towns and villages, so the paper takes county as the research unit. Following the theoretical concept of ‘three structures and one network’, the paper concludes the research framework to analyse the present situation of towns and villages system, including scale structure, functional structure, spatial structure, and organization network. The analytical methods refer to the fractal theory and gravity model, using statistics and spatial data. The scale structure analyzes rank-size dimensions and uses the principal component method to calculate the comprehensive scale of towns and villages. The functional structure analyzes the functional types and industrial development of towns and villages. The spatial structure analyzes the aggregation dimension, network dimension, and correlation dimension of spatial elements to represent the overall spatial relationships. In terms of organization network, from the perspective of entity and ono-entity, the paper analyzes the transportation network and gravitational network. Based on the present situation analysis, the optimization strategies are proposed in order to achieve a synergetic relationship between towns and villages in the county area. The paper uses Suning county in the Beijing-Tianjin-Hebei region as a case study to apply the research framework and methods and then proposes the optimization orientations. The analysis results indicate that: (1) The Suning county is lack of medium-scale towns to transfer effect from towns to villages. (2) The distribution of gravitational centers is uneven, and the effect of gravity is limited only for nearby towns and villages. The gravitational network is not complete, leading to economic activities scattered and isolated. (3) The overall development of towns and villages system is immature, staying at ‘single heart and multi-core’ stage, and some specific optimization strategies are proposed. This study provides a regional view for the development of towns and villages and concludes the research framework and methods of towns and villages system for forming an effective synergetic relationship between them, contributing to organize resources and stimulate endogenous motivation, and form counter magnets to join the urban-rural integration.

Keywords: towns and villages system, organization structure, county area, fractal theory, gravity model

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Authors: Wullapa Wongsinlatam

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Back propagation algorithm (BP) is a widely used technique in artificial neural network and has been used as a tool for solving the time series problems, such as decreasing training time, maximizing the ability to fall into local minima, and optimizing sensitivity of the initial weights and bias. This paper proposes an improvement of a BP technique which is called IM-COH algorithm (IM-COH). By combining IM-COH algorithm with cuckoo search algorithm (CS), the result is cuckoo search improved control output hidden layer algorithm (CS-IM-COH). This new algorithm has a better ability in optimizing sensitivity of the initial weights and bias than the original BP algorithm. In this research, the algorithm of CS-IM-COH is compared with the original BP, the IM-COH, and the original BP with CS (CS-BP). Furthermore, the selected benchmarks, four time series samples, are shown in this research for illustration. The research shows that the CS-IM-COH algorithm give the best forecasting results compared with the selected samples.

Keywords: artificial neural networks, back propagation algorithm, time series, local minima problem, metaheuristic optimization

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Authors: Shuyi Xie

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As the vital city in south China since the ancient time, Guangzhou has been losing its leading role among the rising neighboring cities, especially, Hong Kong and Shenzhen, since the late 1980s, with the overloaded infrastructure and deteriorating urban environment in its old inner city. Fortunately, with the new expansion of its administrative area in 2000, the local municipality considered it as a great opportunity to solve a series of alarming urban problems. Thus, for the first time, strategic planning was introduced to China for providing more convincing and scientific basis towards better urban future. Differed from traditional Chinese planning practices, which rigidly and dogmatically focused on future blueprints, the strategic planning of Guangzhou proceeded from analyzing practical challenges and opportunities towards establishing reasonable developing objectives and proposing corresponding strategies. Moreover, it was pioneering that the municipality invited five planning institutions for proposals, among which, the paper focuses on the one proposed by China Academy of Urban Planning & Design from its theoretical basis to problems’ defining and analyzing the process, as well as planning results. Since it was closer to the following municipal decisions and had a more far-reaching influence for other Chinese cities' following practices. In particular, it demonstrated an innovative exploration on the role played by urban developing rate on deciding urban growth patterns (‘Spillover-reverberation’ or ‘Leapfrog’). That ultimately established an unprecedented paradigm on deciding an appropriate urban spatial structure in future, including its specific location, function and scale. Besides the proposal itself, this article highlights the role of interactions, among actors, as well as proposals, subsequent discussions, summaries and municipal decisions, especially the establishment of the rolling dynamic evaluation system for periodical reviews on implementation situations, as the first attempt in China. Undoubtedly, strategic planning of Guangzhou has brought out considerable benefits, especially opening the strategic mind for plentiful Chinese cities in the following years through establishing a flexible and dynamic planning mechanism highlighted the interactions among multiple actors with innovative and effective tools, methodologies and perspectives on regional, objective-approach and comparative analysis. However, compared with some developed countries, the strategic planning in China just started and has been greatly relied on empirical studies rather than scientific analysis. Moreover, it still faced a bit of controversy, for instance, the certain gap among institutional proposals, final municipal decisions and implemented results, due to the lacking legal constraint. Also, how to improve the public involvement in China with an absolute up-down administrative system is another urgent task. In future, despite of irresistible and irretrievable weakness, some experiences and lessons from previous international practices, with the combination of specific Chinese situations and domestic practices, would enable to promote the further advance on strategic planning in China.

Keywords: evaluation system, global perspective, Guangzhou, interactions, strategic planning, urban growth patterns

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Authors: M.Rüştü Karaman, İsmail İşeri, Kadir Saltalı, A.Reşit Brohi, Ayhan Horuz, Mümin Dizman

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Considerable relations has recently been given to the environmental hazardous caused by agricultural chemicals such as excess fertilizers. In this study, a neural network approach was investigated in the prediction of potential nitrate pollution across different land-use patterns by using a feedforward multilayered computer model of artificial neural network (ANN) with proper training. Periodical concentrations of some anions, especially nitrate (NO3-), and cations were also detected in drainage waters collected from the drain pipes placed in irrigated tomato field, unirrigated wheat field, fallow and pasture lands. The soil samples were collected from the irrigated tomato field and unirrigated wheat field on a grid system with 20 m x 20 m intervals. Site specific nitrate concentrations in the soil samples were measured for ANN based simulation of nitrate leaching potential from the land profiles. In the application of ANN model, a multi layered feedforward was evaluated, and data sets regarding with training, validation and testing containing the measured soil nitrate values were estimated based on spatial variability. As a result of the testing values, while the optimal structures of 2-15-1 was obtained (R2= 0.96, P < 0.01) for unirrigated field, the optimal structures of 2-10-1 was obtained (R2= 0.96, P < 0.01) for irrigated field. The results showed that the ANN model could be successfully used in prediction of the potential leaching levels of nitrate, based on different land use patterns. However, for the most suitable results, the model should be calibrated by training according to different NN structures depending on site specific soil parameters and varied agricultural managements.

Keywords: artificial intelligence, ANN, drainage water, nitrate pollution

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Authors: Sina Saadati

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Multiprocessors Systems-On-Chips (MPSOCs) are used widely on modern computers to execute sophisticated software and applications. These systems include different processors for distinct aims. Most of the proposed task schedulers attempt to improve energy consumption. In some schedulers, the processor's temperature is considered to increase the system's reliability and performance. In this research, we have proposed a new method for thermal-aware task scheduling which is based on an artificial neural network (ANN). This method enables us to consider a variety of factors in the scheduling process. Some factors like ambient temperature, season (which is important for some embedded systems), speed of the processor, computing type of tasks and have a complex relationship with the final temperature of the system. This Issue can be solved using a machine learning algorithm. Another point is that our solution makes the system intelligent So that It can be adaptive. We have also shown that the computational complexity of the proposed method is cheap. As a consequence, It is also suitable for battery-powered systems.

Keywords: task scheduling, MOSOC, artificial neural network, machine learning, architecture of computers, artificial intelligence

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Authors: Redouane Tlemsani, Redouane, Belkacem Kouninef, Abdelkader Benyettou

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In this paper, our system is a Markovien system which we can see it like a Dynamic Bayesian Networks. One of the major interests of these systems resides in the complete training of the models (topology and parameters) starting from training data. The Bayesian Networks are representing models of dubious knowledge on complex phenomena. They are a union between the theory of probability and the graph theory in order to give effective tools to represent a joined probability distribution on a set of random variables. The representation of knowledge bases on description, by graphs, relations of causality existing between the variables defining the field of study. The theory of Dynamic Bayesian Networks is a generalization of the Bayesians networks to the dynamic processes. Our objective amounts finding the better structure which represents the relationships (dependencies) between the variables of a dynamic bayesian network. In applications in pattern recognition, one will carry out the fixing of the structure which obliges us to admit some strong assumptions (for example independence between some variables).

Keywords: Arabic on line character recognition, dynamic Bayesian network, pattern recognition, networks

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Authors: Azza Mohsin Al-Hashami, Reginald Victor

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Treatment of wastewater involves physical, chemical, and biological processes to remove the pollutants from wastewater. This study evaluates of the effectiveness of sewage treatment plants (STP) in Samail, Oman. Samail STP has tertiary treatment using conventional activated sludge with surface aeration. The collection of wastewater is through a network with a total length of about 60 km and also by tankers for the areas outside the network. Treated wastewater from this STP is used for the irrigation of vegetation in the STP premises and as a backwash for sand filters. Some treated water is supplied to the Samail municipality, which uses it for the landscaping, road construction, and 'the Million Date Palms' project. In this study, homogenous samples were taken from eight different treatment stages along the treatment continuum for one year, at a frequency of once a month, to evaluate the physical, chemical, and biological parameters. All samples were analyzed using the standard methods for the examination of water and wastewater. The spatial variations in water quality along the continuum are discussed. Despite these variations, the treated wastewater from Samail STP was of good quality, and most of the parameters are within class A category in Oman Standards for wastewater reuse and discharge.

Keywords: wastewater, STP, treatment, processes

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Authors: T. Vandeyar

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The purpose of this study is to explore how Government policy on ICT influences teaching and learning in South African schools. An instrumental case study using backward mapping principles as a strategy of inquiry was used. Utilizing a social constructivist lens and guided by a theoretical framework of a sociocultural approach to policy analysis, this exploratory qualitative research study set out to investigate how teachers appropriate government policy on ICT in South African schools. Three major findings emanated from this study. First, although teachers were ignorant of the national e-education policy their professionalism and agency were key in formulating and implementing an e-education policy in practice. Second, teachers repositioned themselves not as recipients or reactors of the e-education policy but as social and cultural actors of policy appropriation and formulation. Third, the lack of systemic support to teachers catalyzed improved school and teacher collaborations, teachers became drivers of ICT integration through collaboration, innovation, institutional practice and institutional leadership.

Keywords: ICT, teachers as change agents, practice as policy, teacher's beliefs, teacher's attitudes

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Authors: Andreas Aagaard Nohr

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International Relations is an academic discipline which is rarely in direct contact with its field. However, there has in recent years been a growing interest in the different agents within and beyond the state and their associated practices; yet some of the research tools with which to study them are not widely used. This paper introduces video-observation as a method for the study of IR and argues that it offers a unique way of studying the complexity of the everyday context of actors. The paper is divided into two main parts: First, the philosophical and methodological underpinnings of the kind of data that video-observation produces are discussed; primarily through a discussion of the phenomenology of Husserl, Heidegger, and Merleau-Ponty. Second, taking simulation of a WTO negotiation round as an example, the paper discusses how the data created can be analysed: in particular with regard to the structure of events, the temporal and spatial organization of activities, rhythm and periodicity, and the concrete role of artefacts and documents. The paper concludes with a discussion of the ontological, epistemological, and practical challenges and limitations that ought to be considered if video-observation is chosen as a method within the field of IR.

Keywords: video-observation, phenomenology, international relations

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Authors: Elham Serkani, Hossein Gharaee Garakani, Naser Mohammadzadeh, Elaheh Vaezpour

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Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.

Keywords: decision tree, feature selection, intrusion detection system, support vector machine

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Authors: Bhavini Pandya

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This paper considers Hη: T2 → T2 the Perturbed Cerbelli-Giona map. That is a family of 2-dimensional nonlinear area-preserving transformations on the torus T2=[0,1]×[0,1]= ℝ2/ ℤ2. A single parameter η varies between 0 and 1, taking the transformation from a hyperbolic toral automorphism to the “Cerbelli-Giona” map, a system known to exhibit multifractal properties. Here we study the multifractal properties of the family of maps. We apply a box-counting method by defining a grid of boxes Bi(δ), where i is the index and δ is the size of the boxes, to quantify the distribution of stable and unstable manifolds of the map. When the parameter is in the range 0.51< η <0.58 and 0.68< η <1 the map is ergodic; i.e., the unstable and stable manifolds eventually cover the whole torus, although not in a uniform distribution. For accurate numerical results we require correspondingly accurate construction of the stable and unstable manifolds. Here we use the piecewise linearity of the map to achieve this, by computing the endpoints of line segments which define the global stable and unstable manifolds. This allows the generalized fractal dimension Dq, and spectrum of dimensions f(α), to be computed with accuracy. Finally, the intersection of the unstable and stable manifold of the map will be investigated, and compared with the distribution of periodic points of the system.

Keywords: feed forward, gradient descent, neural network, integral equation

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Authors: Muteb Alotaibi, Graham Clarke, Nick Malleson

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The Hajj religious festival at Mina in Saudi Arabia has always presented the opportunity for injuries or deaths. For example, in 1990, a stampede killed 1426 pilgrims, whilst in 1997, 343 people were killed and 1500 injured due to a fire fuelled by high winds sweeping through the tent city in Mina.Many more minor incidents have occurred since then. It is predicted that 5 million pilgrims will soon perform the ritual at Mina (which is, in effect, a temporary city built each year in the desert), which might lead in the future to severe congestion and accidents unless the research is conducted on actions that contribute positively to improving the management of the crowd and facilitating the flow of pilgrims safely and securely. To help prevent further disasters, it is important to first plan better, more accessible locations for emergency services across Mina to ensure a good service for pilgrims. In this paper, we first use a Location Allocation Model (LAM) within a network GIS to examine the optimal locations for key services in the temporary city of Mina. This has been undertaken in relation to the location and movement of the pilgrims during the six day religious festival. The results of various what-if scenarios have been compared against the current location of services. A major argument is that planners should be flexible and locate facilities at different locations throughout the day and night. The use of location-allocation models in this type of comparative static mode has rarely been operationalised in the literature. Second, we model pilgrim movements and behaviours along with the most crowded parts of the network. This has been modelled using an agent-based model. This model allows planners to understand the key bottlenecks in the network and at what usage levels the paths become critically congested. Thus the paper has important implications and recommendations for future disaster planning strategies. This will enable planners to see at what stage in the movements of pilgrims problems occur in terms of potential crushes and trampling incidents. The main application of this research was only customised for pedestrians as the concentration only for pedestrians who move to Jamarat via foot. Further, the network in the middle of Mina was only dedicated for pedestrians for safety, so no Buses, trains and private cars were allowed in this area to prevent the congestion within this network. Initially, this research focus on Mina city as ‘temporary city’ and also about service provision in temporary cities, which is not highlighted in literature so far. Further, it is the first study which use the dynamic demand to optimise the services in the case of day and night time. Moreover, it is the first study which link the location allocation model for optimising services with ABM to find out whether or not the service location is located in the proper location in which it’s not affecting on crowd movement in mainstream flow where some pilgrims need to have health services.

Keywords: ABM, crowd management, hajj, temporary city

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Authors: Lenka Matulova

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Geopolymers are alumosilicate materials that have long been studied. Despite this fact, little is known about the long-term stability of geopolymer mechanical and structural properties, so crucial for their successful industrial application. To improve understanding, we investigated the effect of four different types of environments on the mechanical and structural properties of a metakaolin-based geopolymer (MK GP). The MK GP samples were stored in laboratory conditions (control samples), in water at 20 °C, in water at 80 °C, and outside exposed to the weather. Compressive and tensile strengths were measured after 28, 56, 90, and 360 days. In parallel, structural properties were analyzed using XRD, SEM, and mercury intrusion porosimetry. Whereas the mechanical properties of the samples in laboratory conditions and in 20 °C water were stable, the mechanical properties of the outdoor samples and the samples 80 °C water decreased noticeably after 360 days. Structural analyses were focused on changes in sample microstructure (developing microcrack network, porosity) and identifying zeolites, the presence of which would indicate detrimental processes in the structure that can change it from amorphous to crystalline. No zeolites were found during the 360-day period in MK GP samples, but the reduction in mechanical properties coincided with a developing network of microcracks and changes in pore size distribution.

Keywords: geopolymer, long-term properties, mechanical properties, metakaolin, structural properties

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Authors: Rabbia Idrees, Ananda Maiti, Saurabh Garg, Muhammad Bilal Amin

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IoT devices are the basic building blocks of IoT network that generate enormous volume of real-time and high-speed data to help organizations and companies to take intelligent decisions. To integrate this enormous data from multisource and transfer it to the appropriate client is the fundamental of IoT development. The handling of this huge quantity of devices along with the huge volume of data is very challenging. The IoT devices are battery-powered and resource-constrained and to provide energy efficient communication, these IoT devices go sleep or online/wakeup periodically and a-periodically depending on the traffic loads to reduce energy consumption. Sometime these devices get disconnected due to device battery depletion. If the node is not available in the network, then the IoT network provides incomplete, missing, and inaccurate data. Moreover, many IoT applications, like vehicle tracking and patient tracking require the IoT devices to be mobile. Due to this mobility, If the distance of the device from the sink node become greater than required, the connection is lost. Due to this disconnection other devices join the network for replacing the broken-down and left devices. This make IoT devices dynamic in nature which brings uncertainty and unreliability in the IoT network and hence produce bad quality of data. Due to this dynamic nature of IoT devices we do not know the actual reason of abnormal data. If data are of poor-quality decisions are likely to be unsound. It is highly important to process data and estimate data quality before bringing it to use in IoT applications. In the past many researchers tried to estimate data quality and provided several Machine Learning (ML), stochastic and statistical methods to perform analysis on stored data in the data processing layer, without focusing the challenges and issues arises from the dynamic nature of IoT devices and how it is impacting data quality. A comprehensive review on determining the impact of dynamic nature of IoT devices on data quality is done in this research and presented a data quality model that can deal with this challenge and produce good quality of data. This research presents the data quality model for the sensors monitoring water quality. DBSCAN clustering and weather sensors are used in this research to make data quality model for the sensors monitoring water quality. An extensive study has been done in this research on finding the relationship between the data of weather sensors and sensors monitoring water quality of the lakes and beaches. The detailed theoretical analysis has been presented in this research mentioning correlation between independent data streams of the two sets of sensors. With the help of the analysis and DBSCAN, a data quality model is prepared. This model encompasses five dimensions of data quality: outliers’ detection and removal, completeness, patterns of missing values and checks the accuracy of the data with the help of cluster’s position. At the end, the statistical analysis has been done on the clusters formed as the result of DBSCAN, and consistency is evaluated through Coefficient of Variation (CoV).

Keywords: clustering, data quality, DBSCAN, and Internet of things (IoT)

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Authors: Donatella R. Fiorino, Marzia Loddo

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The practice of freeing monuments from subsequent additions crosses the entire history of conservation and it is traditionally connected to the aim of valorisation, both for cultural and educational purpose and recently even for touristic exploitation. Defence heritage has been widely interested by these cultural and technical moods from philological restoration to critic innovations. A renovated critical analysis of Italian episodes and in particular the Sardinian case of the area of San Pancrazio in Cagliari, constitute an important lesson about the limits of this practice and the uncertainty in terms of results, towards the definition of a sustainable good practice in the restoration of military architectures.

Keywords: defensive architecture, liberation, Valorisation for tourism, historical restoration

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Authors: Bhuyain Mobarok Hossain

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Image classification and localization research is currently an important strategy in the field of computer vision. The evolution and advancement of deep learning and convolutional neural networks (CNN) have greatly improved the capabilities of object detection and image-based classification. Target detection is important to research in the field of computer vision, especially in video surveillance systems. To solve this problem, we will be applying a convolutional neural network of multiple scales at multiple locations in the image in one sliding window. Most translation networks move away from the bounding box around the area of interest. In contrast to this architecture, we consider the problem to be a classification problem where each pixel of the image is a separate section. Image classification is the method of predicting an individual category or specifying by a shoal of data points. Image classification is a part of the classification problem, including any labels throughout the image. The image can be classified as a day or night shot. Or, likewise, images of cars and motorbikes will be automatically placed in their collection. The deep learning of image classification generally includes convolutional layers; the invention of it is referred to as a convolutional neural network (CNN).

Keywords: image classification, object detection, localization, particle filter

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Authors: Carlos Roberto De Rolt, Julio da Silva Dias, Rafael Tezza, Luca Foschini, Matteo Mura

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The seasonal population fluctuation presents a challenge to touristic cities since the number of inhabitants can double according to the season. The aim of this work is to develop a model that correlates the waste collected with the population of the city and also allow cooperation between the inhabitants and the local government. The model allows public managers to evaluate the impact of the seasonal population fluctuation on waste generation and also to improve planning resource utilization throughout the year. The study uses data from the company that collects the garbage in Florianópolis, a Brazilian city that presents the profile of a city that attracts tourists due to numerous beaches and warm weather. The fluctuations are caused by the number of people that come to the city throughout the year for holidays, summer time vacations or business events. Crowdsensing will be accomplished through smartphones with access to an app for data collection, with voluntary participation of the population. Crowdsensing participants can access information collected in waves for this portal. Crowdsensing represents an innovative and participatory approach which involves the population in gathering information to improve the quality of life. The management of crowdsensing solutions plays an essential role given the complexity to foster collaboration, establish available sensors and collect and process the collected data. Practical implications of this tool described in this paper refer, for example, to the management of seasonal tourism in a large municipality, whose public services are impacted by the floating of the population. Crowdsensing and big data support managers in predicting the arrival, permanence, and movement of people in a given urban area. Also, by linking crowdsourced data to databases from other public service providers - e.g., water, garbage collection, electricity, public transport, telecommunications - it is possible to estimate the floating of the population of an urban area affected by seasonal tourism. This approach supports the municipality in increasing the effectiveness of resource allocation while, at the same time, increasing the quality of the service as perceived by citizens and tourists.

Keywords: big data, dashboards, floating population, smart city, urban management solutions

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Authors: Rozo D. Juan Felipe, Ramírez L. Leonardo Juan, Puerta A. Gabriel Alberto

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The telemedicine services require correct computing resource management to guarantee productivity and efficiency for medical and non-medical staff. The aim of this study was to examine web management strategies to ensure the availability of resources and services in telemedicine so as to provide medical information management with an accessible strategy. In addition, to evaluate the quality-of-service parameters, the followings were measured: delays, throughput, jitter, latency, available bandwidth, percent of access and denial of services based of web management performance map with profiles permissions and database management. Through 24 different test scenarios, the results show 100% in availability of medical information, in relation to access of medical staff to web services, and quality of service (QoS) of 99% because of network delay and performance of computer network. The findings of this study suggest that the proposed strategy of web management is an ideal solution to guarantee the availability, reliability, and accessibility of medical information. Finally, this strategy offers seven user profile used at telemedicine center of Bogota-Colombia keeping QoS parameters suitable to telemedicine services.

Keywords: availability, medical information, QoS, strategy, telemedicine

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Authors: Shibo Wei, Ting Jiang

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Convolutional-recurrent neural networks (CRN) have achieved much success recently in the speech enhancement field. The common processing method is to use the convolution layer to compress the feature space by multiple upsampling and then model the compressed features with the LSTM layer. At last, the enhanced speech is obtained by deconvolution operation to integrate the global information of the speech sequence. However, the feature space compression process may cause the loss of information, so we propose to model the upsampling result of each step with the residual LSTM layer, then join it with the output of the deconvolution layer and input them to the next deconvolution layer, by this way, we want to integrate the global information of speech sequence better. The experimental results show the network model (RES-CRN) we introduce can achieve better performance than LSTM without residual and overlaying LSTM simply in the original CRN in terms of scale-invariant signal-to-distortion ratio (SI-SNR), speech quality (PESQ), and intelligibility (STOI).

Keywords: convolutional-recurrent neural networks, speech enhancement, residual LSTM, SI-SNR

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Authors: Venkat S. Somayajula

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Ground surface temperature history prediction model plays a vital role in determining standards for international nuclear waste management. International standards for borehole based nuclear waste disposal require paleoclimate cycle predictions on scale of a million forward years for the place of waste disposal. This research focuses on developing a paleoclimate cycle prediction model using Bayesian long-short term memory (LSTM) neural architecture operated on accumulated borehole temperature history data. Bayesian models have been previously used for paleoclimate cycle prediction based on Monte-Carlo weight method, but due to limitations pertaining model coupling with certain other prediction networks, Bayesian models in past couldn’t accommodate prediction cycle’s over 1000 years. LSTM has provided frontier to couple developed models with other prediction networks with ease. Paleoclimate cycle developed using this process will be trained on existing borehole data and then will be coupled to surface temperature history prediction networks which give endpoints for backpropagation of LSTM network and optimize the cycle of prediction for larger prediction time scales. Trained LSTM will be tested on past data for validation and then propagated for forward prediction of temperatures at borehole locations. This research will be beneficial for study pertaining to nuclear waste management, anthropological cycle predictions and geophysical features

Keywords: Bayesian long-short term memory neural network, borehole temperature, ground surface temperature history, paleoclimate cycle

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Authors: Xiaoqing Wang, Jianjian Zong, Li Li, Yanxing Zheng, Jinrong Tong, Mao Zhan

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With the rapid development of network and communication technology, a great deal of data has been generated in different domains of a network. These data show a trend of increasing scale and more complex structure. Therefore, an effective and flexible cross-domain data-sharing system is needed. The Cross-domain Data Sharing System(CDSS) in a net-centric environment is composed of three sub-systems. The data distribution sub-system provides data exchange service through publish-subscribe technology that supports asynchronism and multi-to-multi communication, which adapts to the needs of the dynamic and large-scale distributed computing environment. The access control sub-system adopts Attribute-Based Access Control(ABAC) technology to uniformly model various data attributes such as subject, object, permission and environment, which effectively monitors the activities of users accessing resources and ensures that legitimate users get effective access control rights within a legal time. The cross-domain access security negotiation subsystem automatically determines the access rights between different security domains in the process of interactive disclosure of digital certificates and access control policies through trust policy management and negotiation algorithms, which provides an effective means for cross-domain trust relationship establishment and access control in a distributed environment. The CDSS’s asynchronous,multi-to-multi and loosely-coupled communication features can adapt well to data exchange and sharing in dynamic, distributed and large-scale network environments. Next, we will give CDSS new features to support the mobile computing environment.

Keywords: data sharing, cross-domain, data exchange, publish-subscribe

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Authors: Jaypalsinh Parmar, Pintu Nakrani, Bhaumik Shah

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Digital Elevation Model (DEM) is elevation data of the virtual grid on the ground. DEM can be used in application in GIS such as hydrological modelling, flood forecasting, morphometrical analysis and surveying etc.. For morphometrical analysis the stream flow network plays a very important role. DEM lacks accuracy and cannot match field data as it should for accurate results of morphometrical analysis. The present study focuses on comparing the Agree method and the conventional Shortest path method for finding out morphometric parameters in the flat region of the Lower Tapi Basin which is located in the western India. For the present study, open source SRTM (Shuttle Radar Topography Mission with 1 arc resolution) and toposheets issued by Survey of India (SOI) were used to determine the morphometric linear aspect such as stream order, number of stream, stream length, bifurcation ratio, mean stream length, mean bifurcation ratio, stream length ratio, length of overland flow, constant of channel maintenance and aerial aspect such as drainage density, stream frequency, drainage texture, form factor, circularity ratio, elongation ratio, shape factor and relief aspect such as relief ratio, gradient ratio and basin relief for 53 catchments of Lower Tapi Basin. Stream network was digitized from the available toposheets. Agree DEM was created by using the SRTM and stream network from the toposheets. The results obtained were used to demonstrate a comparison between the two methods in the flat areas.

Keywords: agree method, morphometric analysis, lower Tapi basin, shortest path method

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Authors: Kherbache Mehdi

Abstract:

Within the framework of the validation of the Master in business administration marketing and sales in INSIM institute international in management Blida, we get the opportunity to do a professional internship in Sonelgaz Enterprise and a thesis. The thesis deals with the integration of social networking in the communication strategy of a company. The problematic is: How communicate with social network can be a solution for companies? The challenges stressed by this thesis were to suggest limits and recommendations to Sonelgaz Enterprise concerning social networks. The whole social networks represent more than a billion people as a potential target for the companies. Thanks to research and a qualitative approach, we have identified tree valid hypothesis. The first hypothesis allows confirming that using social networks cannot be ignored by any company in its communication strategy. However, the second hypothesis demonstrates that it’s necessary to prepare a strategy that integrates social networks in the communication plan of the company. The risk of this strategy is very limited because failure on social networks is not a restraint for the enterprise, social networking is not expensive and, a bad image which could result from it is not as important in the long-term. Furthermore, the return on investment is difficult to evaluate. Finally, the last hypothesis shows that firms establish a new relation between consumers and brands thanks to the proximity allowed by social networks. After the validation of the hypothesis, we suggested some recommendations to Sonelgaz Enterprise regarding the communication through social networks. Firstly, the company must use the interactivity of social network in order to have fruitful exchanges with the community. We also recommended having a strategy to treat negative comments. The company must also suggest delivering resources to the community thanks to a community manager, in order to have a good relation with the community. Furthermore, we advised using social networks to do business intelligence. Sonelgaz Enterprise can have some creative and interactive contents with some amazing applications on Facebook for example. Finally, we recommended to the company to be not intrusive with “fans” or “followers” and to be open to all the platforms: Twitter, Facebook, Linked-In for example.

Keywords: social network, buzz, communication, consumer, return on investment, internet users, web 2.0, Facebook, Twitter, interaction

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Authors: Mark Jason E. Arca, Jay Vee R. Linatoc, Rex Francis N. Lupango, Michael Joe A. Ramirez

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Participation promises an avenue for citizens to take part in governance, but it does not necessarily mean effective participation. The proper integration of participants in the decision-making process should be properly addressed to ensure effectiveness. This study explores the integration of the participants in the decision-making process to reveal the level of participation in the Solid Waste Management audit done by the Citizen Participatory Audit (CPA), a program under the supervision of the Commission on Audit. Specifically, this study will use the experience of participation to identify emerging themes that will help reveal the level of participation through the integrated ladder of participation. The researchers used key informant interviews to gather necessary data from the actors of the program. The findings revealed that the level of participation present in the CPA is at the Placation level, a level below the program’s targeted level of participation. The study also allowed the researchers to reveal facilitating factors in the program that contributed to a better understanding of the practice of participation.

Keywords: citizen participation, culture of participation, ladder of participation, level of participation

Procedia PDF Downloads 411