Search results for: algorithm development

Authors: Gatoto Placide, Michel Roddy Lollchund, Gace Athanase Dalson

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This paper first presents a review of the current situation of energy access rate in Burundi, which is relatively low compared to other countries. The paper aims to identify the key gaps in improving the electrical energy access in Burundi and proposes a solution to overcome these gaps. It is shown that the electrical power grid is old and concentrated in north-west and in Bujumbura city while other regions lack access to national grids. Next to that, the link between electricity access and sustainable development in Burundi is clarified. Further, some solutions are suggested to solve energy access problems such as the electricity transmission lines extension and renovation, diversification of energy sources.

Keywords: Burundi, energy access, hydropower, sustainable development

Procedia PDF Downloads 184

Authors: Rhoda N. Kayongo

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As behavior analysts in education continue to debate on how higher institutions can continue to benefit from their social and academic related programs, higher education is facing challenges in the area of character development. This is manifested in the percentages of college completion rates, teen pregnancies, drug abuse, sexual abuse, suicide, plagiarism, lack of academic integrity, and violence among their students. Attending college is a perceived opportunity to positively influence the actions and behaviors of the next generation of society; thus colleges and universities have to provide opportunities to develop students’ values and behaviors. Prior studies were mainly conducted in private institutions and more so in developed countries. However, with the complexity of the nature of student body currently due to the changing world, a multidimensional approach combining multiple factors that enhance character development outcomes is needed to suit the changing trends. The main purpose of this study was to identify opportunities in colleges and develop a model for predicting character development outcomes. A survey questionnaire composed of 7 scales including in-classroom interaction, out-of-classroom interaction, school climate, personal lifestyle, home environment, and peer influence as independent variables and character development outcomes as the dependent variable was administered to a total of five hundred and one students of 3rd and 4th year level in selected public colleges and universities in the Philippines and Rwanda. Using structural equation modelling, a predictive model explained 57% of the variance in character development outcomes. Findings from the results of the analysis showed that in-classroom interactions have a substantial direct influence on character development outcomes of the students (r = .75, p < .05). In addition, out-of-classroom interaction, school climate, and home environment contributed to students’ character development outcomes but in an indirect way. The study concluded that in the classroom are many opportunities for teachers to teach, model and integrate character development among their students. Thus, suggestions are made to public colleges and universities to deliberately boost and implement experiences that cultivate character within the classroom. These may contribute tremendously to the students' character development outcomes and hence render effective models of behaviour analysis in higher education.

Keywords: character development, tertiary institutions, predictive model, behavior analysis

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Authors: Hiba Alkhalaf

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Historic cities and places of cultural significance is continuously under the pressure of economic development and social change that threaten its natural and cultural environment. The challenge here is to find a balance between preserving the cultural character while ensuring the socio-economic gains and continuity of its uniqueness. That is by sustaining the use, character, meaning and social interaction associated with the place, in other words the sense of place. The main argument here is what we attempt to conserve is the cultural physical and non-physical dimensions of the historic city. It is based on the proposition that what give the historic city its character is its strong sense of place- whether it is historic or current. When properly identified, its various dimensions (use, meaning and form) would help determine what to sustain and what not by making the development meaningfully related to the uniqueness of the historic place. Accordingly, those socio-economic features within the context of a changing historic environment needed to be clarified. This paper, thus, explores the various perspectives of the role of sense of place within the historic city and its connection to cultural heritage. It also reviews urban conservation practice as it is currently understood in the context of historic city development. It concludes that sense of place lies in complex interrelated relationships between various users of the place and the physical, economic, cultural, political, and environmental contexts in which they interact. This calls for the need to sustain the sense of place as part of the overall urban development and conservation strategies.

Keywords: cultural heritage, historic urban areas, urban development, sense of place

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Authors: Xiaoqing Wang, Junfeng Wang, Xiaolan Zhu

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Android operating system has been recognized by most application developers because of its good open-source and compatibility, which enriches the categories of applications greatly. However, it has become the target of malware attackers due to the lack of strict security supervision mechanisms, which leads to the rapid growth of malware, thus bringing serious safety hazards to users. Therefore, it is critical to detect Android malware effectively. Generally, the permissions declared in the AndroidManifest.xml can reflect the function and behavior of the application to a large extent. Since current Android system has not any restrictions to the number of permissions that an application can request, developers tend to apply more than actually needed permissions in order to ensure the successful running of the application, which results in the abuse of permissions. However, some traditional detection methods only consider the requested permissions and ignore whether it is actually used, which leads to incorrect identification of some malwares. Therefore, a machine learning detection method based on the actually used permissions combination and API calls was put forward in this paper. Meanwhile, several experiments are conducted to evaluate our methodology. The result shows that it can detect unknown malware effectively with higher true positive rate and accuracy while maintaining a low false positive rate. Consequently, the AdaboostM1 (J48) classification algorithm based on information gain feature selection algorithm has the best detection result, which can achieve an accuracy of 99.8%, a true positive rate of 99.6% and a lowest false positive rate of 0.

Keywords: android, API Calls, machine learning, permissions combination

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Authors: Mosaad Hamouda, Kamal Khalaf, Zaker Mousa

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National projects are considered Egypt's future vision in investing its various resources and the best way to bring about a developmental renaissance that constitutes a quantum leap because of its developmental impact on the planning regions, which it achieves in attracting and localizing investments to achieve urban development, and what this has a noticeable impact on dividing those regions in order to achieve a developmental balance or at least reduce the severity of the disparities between them, by measuring the impact of these projects, which appear in the per capita share of the various developmental variables, and also analyzing global and local experiences so that a balanced division of the country’s regions can be reached, and the research finds a set of planning foundations that are compatible with the settlement of these national projects in the future.

Keywords: national projects, regional development, division of regions, development disparities

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Authors: Seungwoo Kim, Yeongcheol Cho

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In this paper, a holonomic mobile robot is designed in omnidirectional wheels and an adaptive fuzzy controller is presented for its precise trajectories. A kind of adaptive controller based on fuzzy multi-layered algorithm is used to solve the big parametric uncertainty of motor-controlled dynamic system of 3-wheels omnidirectional mobile robot. The system parameters such as a tracking force are so time-varying due to the kinematic structure of omnidirectional wheels. The fuzzy adaptive control method is able to solve the problems of classical adaptive controller and conventional fuzzy adaptive controllers. The basic idea of new adaptive control scheme is that an adaptive controller can be constructed with parallel combination of robust controllers. This new adaptive controller uses a fuzzy multi-layered architecture which has several independent fuzzy controllers in parallel, each with different robust stability area. Out of several independent fuzzy controllers, the most suited one is selected by a system identifier which observes variations in the controlled system parameter. This paper proposes a design procedure which can be carried out mathematically and systematically from the model of a controlled system. Finally, the good performance of a holonomic mobile robot is confirmed through live tests of the tracking control task.

Keywords: fuzzy adaptive control, fuzzy multi-layered controller, holonomic mobile robot, omnidirectional wheels, robustness and stability.

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Authors: C. B. Le, V. N. Pham

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In modern data analysis, multi-source data appears more and more in real applications. Multi-source data clustering has emerged as a important issue in the data mining and machine learning community. Different data sources provide information about different data. Therefore, multi-source data linking is essential to improve clustering performance. However, in practice multi-source data is often heterogeneous, uncertain, and large. This issue is considered a major challenge from multi-source data. Ensemble is a versatile machine learning model in which learning techniques can work in parallel, with big data. Clustering ensemble has been shown to outperform any standard clustering algorithm in terms of accuracy and robustness. However, most of the traditional clustering ensemble approaches are based on single-objective function and single-source data. This paper proposes a new clustering ensemble method for multi-source data analysis. The fuzzy optimized multi-objective clustering ensemble method is called FOMOCE. Firstly, a clustering ensemble mathematical model based on the structure of multi-objective clustering function, multi-source data, and dark knowledge is introduced. Then, rules for extracting dark knowledge from the input data, clustering algorithms, and base clusterings are designed and applied. Finally, a clustering ensemble algorithm is proposed for multi-source data analysis. The experiments were performed on the standard sample data set. The experimental results demonstrate the superior performance of the FOMOCE method compared to the existing clustering ensemble methods and multi-source clustering methods.

Keywords: clustering ensemble, multi-source, multi-objective, fuzzy clustering

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Authors: Saad M. Darwish, Mohamed A. El-Iskandarani, Guitar M. Shawkat

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Nowadays, the amount of available multimedia data is continuously on the rise. The need to find a required image for an ordinary user is a challenging task. Content based image retrieval (CBIR) computes relevance based on the visual similarity of low-level image features such as color, textures, etc. However, there is a gap between low-level visual features and semantic meanings required by applications. The typical method of bridging the semantic gap is through the automatic image annotation (AIA) that extracts semantic features using machine learning techniques. In this paper, a multi-label image annotation system guided by Firefly and Bayesian method is proposed. Firstly, images are segmented using the maximum variance intra cluster and Firefly algorithm, which is a swarm-based approach with high convergence speed, less computation rate and search for the optimal multiple threshold. Feature extraction techniques based on color features and region properties are applied to obtain the representative features. After that, the images are annotated using translation model based on the Net Bayes system, which is efficient for multi-label learning with high precision and less complexity. Experiments are performed using Corel Database. The results show that the proposed system is better than traditional ones for automatic image annotation and retrieval.

Keywords: feature extraction, feature selection, image annotation, classification

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Authors: Fekri Shawtari

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The banking sector plays a very crucial role in the economic development of the country. As a financial intermediary, it has assigned a great role in the economic growth and stability. This paper aims to examine the empirically the relationship between banking industry and economic growth in state of Qatar. We adopt the VAR vector error correction model (VECM) along with Granger causality to address the issue over the long-run and short-run between the banking sector and economic growth. It is expected that the results will give policy directions to the policymakers to make strategies that are conducive toward boosting development to achieve the targeted economic growth in current situation.

Keywords: economic growth, banking sector, Qatar, vector error correction model, VECM

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Authors: Shagufta Jahangir, Nadeemullah, Yaqoob, Raisa Jahangir

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The Persian language word ‘Purdah’ and in Arabic ‘Hajab’ is used for veil. Veil has been used by women for being escaped from men. In one way or the other veil has been continuously used in ancient as well as modern civilizations by women. Developed nations have blamed the use of veil an obstacle in the process of development. Therefore, modern nations have struggled to get rid of the use of veil. They argue that it is a sign of slavery for women and it is an obstacle in the path of development. The modern secular Muslims considered veil as the biggest obstacle for social and economic development. It makes a woman helpless, as being zanjir in her feet. It has become an obstacle in the process of development for women. It is also considered as a tool for segregation among men and women. The so called Muslims of the modern era are trying to introduce changes in religion by imitation the modern nations of the world. In particular ways for Muslim woman use of veil in Islam is must. It is a right provided her by religion. It provides her strength. In the Holy Quran word ‘Hajab’ is used 5 times. Islam is against domination and forceful practice of veil, as a part of teaching of Islam it is being adopted by women as a protection. This article aims at: (1) historical background of veil (2) Its existence in civilizations, (3) Meaning and interpretation of veil in Islamic context, (4) Economic impact of it on women (5) Discussion on its practice in Islamic (eastern) and other (European) circles and conclusions followed by concerted bibliography.

Keywords: veil, economic development, civilizations, obstacle, secular Muslims, segregation

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Authors: Yassine Mohammed Benyoucef, Razin Andery Dionisovich

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Biomimicry is an old approach, but in the scientific conceptualization is new, as an approach of innovation based on the emulation of Nature, in recent years, this approach brings many potential theories and innovations in the architecture field. Indeed, these innovations have changed our view towards other Natural organisms also to the design processes in architecture, now the use of the biomimicry approach allows the application of a great sustainable development. The Sahara area is heading towards a sustainable policy with the desire to develop this rich context in terms of architecture, because of the rapid evolution of the architectural and urban concepts and the technology acceleration in one side, and under the pressure of the architectural crisis and the accelerated urbanization in the Saharan cities on the other side, the imperatives of sustainable development, ecology, climate adaptation, energy needs, are strongly imposed. Besides that, the new architectural and urban projects in the Saharan cities are not reliable in terms of energy efficiency and design and relationship with the environment. This article discusses the using of biomimetic strategy in the sustainable development of Saharan architecture. The aim of the article is to present a synthesis of biomimicry approach and propose the biomimicry as a solution for the development of Saharan architecture which can use this approach as a sustainable and innovation strategy. The biomimicry is the solution for effective strategies of development and can have a great potential point to meet the current challenges of designing efficient for forms or structures, energy efficiency, and climate issues. Moreover, the Sahara can be a favorable soil for great changes, the use of this approach is the key for the most optimal strategies and sustainable development of the Saharan architecture.

Keywords: biomimicry, Sahara, architecture, nature, innovation, technology

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Authors: Thomas Kipkurgat, Silahs Chemwaina

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Communication and ICT is a crucial component in realization of vision 2030, radio has played a key role in dissemination of information to mass audience. Since time immemorial, mass media has played a vital role in passing information on agricultural development issues both locally and internationally. This paper aimed at assessing the role of community radio stations in enhancing agricultural development in Kenya. The paper sought to identify the main contributions of KASS FM radio in the agricultural development especially in rural areas, the study also aimed to establish the appropriate adjustments in editorial policies of KASS FM radio in helping to promote agricultural development related programmes in rural areas. Despite some weaknesses in radio programming and the mode of interaction with the rural people, the findings of this study showed that the rural communities are better off today than in the old days when FM radios were non-existent. KASS FM has come up with different developmental programmes that have positively contributed to changing the rural people’s ways of life. These programmes include farming, health, marital values, environment, cultural issues, human rights, democracy, religious teachings, peace and reconciliation. Such programmes feature experts, professionals and opinion leaders who address numerous topics of interest to the community. The local people participate in the production of these programmes through letters to the editor, and phone-ins, among others. Programmes such as political talk shows, which feature in KASS FM, has become one of the most important ways of community participation. The interpretation and conclusions are based on the empirical data analysis and the theories of development advanced by international development communication scholars, as presented in the paper. The study ends with some recommendations on how KASS FM can best serve the interests of the poor people in rural areas, and helps improve their lives.

Keywords: agriculture, development, communication, KASS FM, radio, rural areas, Kenya

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Authors: Yang Chen, Lili Fu

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Promoting urban regeneration in existing areas has been elevated to a national strategy in China. In this context, because of the multidimensional sustainable effect through the intensive use of land, mixed-use development has become an important objective for high-quality urban regeneration in the inner city. However, in the long period of time since China's reform and opening up, the "unbalanced phenomenon" of mixed-use development in China's inner cities has been very serious. On the one hand, the excessive focus on certain individual spaces has led to an increase in the level of mixed-use development in some areas, substantially ahead of others, resulting in a growing gap between different parts of the inner city; On the other hand, the excessive focus on a one-dimensional element of the spatial organization of mixed-use development, such as the enhancement of functional mix or spatial capacity, has led to a lagging phenomenon or neglect in the construction of other dimensional elements, such as pedestrian permeability, green environmental quality, social inclusion, etc. This phenomenon is particularly evident in the central area of the inner city, and it clearly runs counter to the need for sustainable development in China's new era. Therefore, a rational qualitative and quantitative analysis of the "unbalanced phenomenon" will help to identify the problem and provide a basis for the formulation of relevant optimization plans in the future. This paper builds a dynamic evaluation method of mixed-use development based on a meta-dimensional model and then uses spatial evolution analysis and spatial consistency analysis with ArcGIS software to reveal the "unbalanced phenomenon " in over the past 40 years of the central city area in Nanjing, a China’s typical city facing regeneration. This study result finds that, compared to the increase in functional mix and capacity, the dimensions of residential space mix, public service facility mix, pedestrian permeability, and greenness in Nanjing's city central area showed different degrees of lagging improvement, and the unbalanced development problems in each part of the city center are different, so the governance and planning plan for future mixed-use development needs to fully address these problems. The research methodology of this paper provides a tool for comprehensive dynamic identification of mixed-use development level’s change, and the results deepen the knowledge of the evolution of mixed-use development patterns in China’s inner cities and provide a reference basis for future regeneration practices.

Keywords: mixed-use development, unbalanced phenomenon, the meta-dimensional model, over the past 40 years of Nanjing, China

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Authors: Rakesh Mishra, Mukunda Upadhyay, Rajni Singh

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This paper attempts to link remittances sent by internal as well as international out-migrants and its domestic preferences of usage in three different dimension of Household level development in India and its states. Investment of remittances in these sectors reveals for mixed choices of preferential among the states from where people have out-migrated. The multivariate analysis implies that among all three indicators of human development, health (Investment in Food and Health) is the one that attracts the major investment followed by capital formation and least on Education. Usage of the remittances has been found to be varying across all the states in India as far as usage in health, capital formation and education are concerned. Orissa, Nagaland, Madhya Pradesh, Jharkhand, Gujarat, D & H Haweli are some of the states and union territory that contributes highest of its international remittances on health, while most of the usage of the internal remittances has second or third preferences of investment on the health except for Uttar Pradesh, D & H Haweli, Arunachal Pradesh and A & N Is. This paper tries to access usage of international remittances as well as internal remittances on the flow of remittances at the micro level and its implications across three basic determinants of Human Development that is Health, Capital formation and Education coupled with the preferences of usage in presence of Several Socio economic and Demographic variable.

Keywords: multivariate analysis, household development, remittances, internal and international migration

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Authors: Jose Funes, Jeff Sauer, Laixiang Sun

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This research examines determinants of multifamily housing development and spillovers in the District of Columbia. A range of socioeconomic factors related to income distribution, productivity, and land use policies are thought to influence the development in contemporary U.S. multifamily housing markets. The analysis leverages data from the American Community Survey to construct panel datasets spanning from 2010 to 2019. Using spatial regression, we identify several socioeconomic measures and land use policies both positively and negatively associated with new housing supply. We contextualize housing estimates related to race in relation to uneven development in the contemporary D.C. housing supply.

Keywords: neighborhood effect, sorting, spatial spillovers, multifamily housing

Procedia PDF Downloads 99

Authors: Sardorbek Numonov, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Dongeun Choi, Byung-Woo Hong

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The detection of curvilinear structures often plays an important role in the analysis of images. In particular, it is considered as a crucial step for the diagnosis of chronic respiratory diseases to localize the fissures in chest CT imagery where the lung is divided into five lobes by the fissures that are characterized by linear features in appearance. However, the characteristic linear features for the fissures are often shown to be subtle due to the high intensity variability, pathological deformation or image noise involved in the imaging procedure, which leads to the uncertainty in the quantification of anatomical or functional properties of the lung. Thus, it is desired to enhance the linear features present in the chest CT images so that the distinctiveness in the delineation of the lobe is improved. We propose a recursive diffusion process that prefers coherent features based on the analysis of structure tensor in an anisotropic manner. The local image features associated with certain scales and directions can be characterized by the eigenanalysis of the structure tensor that is often regularized via isotropic diffusion filters. However, the isotropic diffusion filters involved in the computation of the structure tensor generally blur geometrically significant structure of the features leading to the degradation of the characteristic power in the feature space. Thus, it is required to take into consideration of local structure of the feature in scale and direction when computing the structure tensor. We apply an anisotropic diffusion in consideration of scale and direction of the features in the computation of the structure tensor that subsequently provides the geometrical structure of the features by its eigenanalysis that determines the shape of the anisotropic diffusion kernel. The recursive application of the anisotropic diffusion with the kernel the shape of which is derived from the structure tensor leading to the anisotropic scale-space where the geometrical features are preserved via the eigenanalysis of the structure tensor computed from the diffused image. The recursive interaction between the anisotropic diffusion based on the geometry-driven kernels and the computation of the structure tensor that determines the shape of the diffusion kernels yields a scale-space where geometrical properties of the image structure are effectively characterized. We apply our recursive anisotropic diffusion algorithm to the detection of curvilinear structure in the chest CT imagery where the fissures present curvilinear features and define the boundary of lobes. It is shown that our algorithm yields precise detection of the fissures while overcoming the subtlety in defining the characteristic linear features. The quantitative evaluation demonstrates the robustness and effectiveness of the proposed algorithm for the detection of fissures in the chest CT in terms of the false positive and the true positive measures. The receiver operating characteristic curves indicate the potential of our algorithm as a segmentation tool in the clinical environment. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: anisotropic diffusion, chest CT imagery, chronic respiratory disease, curvilinear structure, fissure detection, structure tensor

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Authors: L. Yu, W. K. Li, S. K. Ong, A. Y. C. Nee

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In this paper, a scalable augmented reality framework for handheld devices is presented. The presented framework is enabled by using a server-client data communication structure, in which the search for tracking targets among a database of images is performed on the server-side while pixel-wise 3D tracking is performed on the client-side, which, in this case, is a handheld mobile device. Image search on the server-side adopts a residual-enhanced image descriptors representation that gives the framework a scalability property. The tracking algorithm on the client-side is based on a gravity-aligned feature descriptor which takes the advantage of a sensor-equipped mobile device and an optimized intensity-based image alignment approach that ensures the accuracy of 3D tracking. Automatic content streaming is achieved by using a key-frame selection algorithm, client working phase monitoring and standardized rules for content communication between the server and client. The recognition accuracy test performed on a standard dataset shows that the method adopted in the presented framework outperforms the Bag-of-Words (BoW) method that has been used in some of the previous systems. Experimental test conducted on a set of video sequences indicated the real-time performance of the tracking system with a frame rate at 15-30 frames per second. The presented framework is exposed to be functional in practical situations with a demonstration application on a campus walk-around.

Keywords: augmented reality framework, server-client model, vision-based tracking, image search

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Authors: L. Diogo, A. Legrand, J. Nguyen-Cao, J. Rogeau, S. Bornhofen

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Lenia is a system of cellular automata with continuous states, space and time, which surprises not only with the emergence of interesting life-like structures but also with its beauty. This paper reports ongoing research on a GPU implementation of Lenia using CUDA C++ and OpenGL Interoperability. We demonstrate how CUDA as a low-level GPU programming paradigm allows optimizing performance and memory usage of the Lenia algorithm. A comparative analysis through experimental runs with existing implementations shows that the CUDA implementation outperforms the others by one order of magnitude or more. Cellular automata hold significant interest due to their ability to model complex phenomena in systems with simple rules and structures. They allow exploring emergent behavior such as self-organization and adaptation, and find applications in various fields, including computer science, physics, biology, and sociology. Unlike classic cellular automata which rely on discrete cells and values, Lenia generalizes the concept of cellular automata to continuous space, time and states, thus providing additional fluidity and richness in emerging phenomena. In the current literature, there are many implementations of Lenia utilizing various programming languages and visualization libraries. However, each implementation also presents certain drawbacks, which serve as motivation for further research and development. In particular, speed is a critical factor when studying Lenia, for several reasons. Rapid simulation allows researchers to observe the emergence of patterns and behaviors in more configurations, on bigger grids and over longer periods without annoying waiting times. Thereby, they enable the exploration and discovery of new species within the Lenia ecosystem more efficiently. Moreover, faster simulations are beneficial when we include additional time-consuming algorithms such as computer vision or machine learning to evolve and optimize specific Lenia configurations. We developed a Lenia implementation for GPU using the C++ and CUDA programming languages, and CUDA/OpenGL Interoperability for immediate rendering. The goal of our experiment is to benchmark this implementation compared to the existing ones in terms of speed, memory usage, configurability and scalability. In our comparison we focus on the most important Lenia implementations, selected for their prominence, accessibility and widespread use in the scientific community. The implementations include MATLAB, JavaScript, ShaderToy GLSL, Jupyter, Rust and R. The list is not exhaustive but provides a broad view of the principal current approaches and their respective strengths and weaknesses. Our comparison primarily considers computational performance and memory efficiency, as these factors are critical for large-scale simulations, but we also investigate the ease of use and configurability. The experimental runs conducted so far demonstrate that the CUDA C++ implementation outperforms the other implementations by one order of magnitude or more. The benefits of using the GPU become apparent especially with larger grids and convolution kernels. However, our research is still ongoing. We are currently exploring the impact of several software design choices and optimization techniques, such as convolution with Fast Fourier Transforms (FFT), various GPU memory management scenarios, and the trade-off between speed and accuracy using single versus double precision floating point arithmetic. The results will give valuable insights into the practice of parallel programming of the Lenia algorithm, and all conclusions will be thoroughly presented in the conference paper. The final version of our CUDA C++ implementation will be published on github and made freely accessible to the Alife community for further development.

Keywords: artificial life, cellular automaton, GPU optimization, Lenia, comparative analysis.

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Authors: Jack R. McKenzie, Peter A. Appleby, Thomas House, Neil Walton

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Cold-start is a notoriously difficult problem which can occur in recommendation systems, and arises when there is insufficient information to draw inferences for users or items. To address this challenge, a contextual bandit algorithm – the Fast Approximate Bayesian Contextual Cold Start Learning algorithm (FAB-COST) – is proposed, which is designed to provide improved accuracy compared to the traditionally used Laplace approximation in the logistic contextual bandit, while controlling both algorithmic complexity and computational cost. To this end, FAB-COST uses a combination of two moment projection variational methods: Expectation Propagation (EP), which performs well at the cold start, but becomes slow as the amount of data increases; and Assumed Density Filtering (ADF), which has slower growth of computational cost with data size but requires more data to obtain an acceptable level of accuracy. By switching from EP to ADF when the dataset becomes large, it is able to exploit their complementary strengths. The empirical justification for FAB-COST is presented, and systematically compared to other approaches on simulated data. In a benchmark against the Laplace approximation on real data consisting of over 670, 000 impressions from autotrader.co.uk, FAB-COST demonstrates at one point increase of over 16% in user clicks. On the basis of these results, it is argued that FAB-COST is likely to be an attractive approach to cold-start recommendation systems in a variety of contexts.

Keywords: cold-start learning, expectation propagation, multi-armed bandits, Thompson Sampling, variational inference

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Authors: B. R. Raut

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The seismic performance of 20-storey benchmark building with semi-active dampers is investigated under various earthquake ground motions. The Semi-Active Variable Friction Dampers (SAVFD) and Magnetorheological Dampers (MR) are used in this study. A recently proposed predictive control algorithm is employed for SAVFD and a simple mechanical model based on a Bouc–Wen element with clipped optimal control algorithm is employed for MR damper. A parametric study is carried out to ascertain the optimum parameters of the semi-active controllers, which yields the minimum performance indices of controlled benchmark building. The effectiveness of dampers is studied in terms of the reduction in structural responses and performance criteria. To minimize the cost of the dampers, the optimal location of the damper, rather than providing the dampers at all floors, is also investigated. The semi-active dampers installed in benchmark building effectively reduces the earthquake-induced responses. Lesser number of dampers at appropriate locations also provides comparable response of benchmark building, thereby reducing cost of dampers significantly. The effectiveness of two semi-active devices in mitigating seismic responses is cross compared. Among two semi-active devices majority of the performance criteria of MR dampers are lower than SAVFD installed with benchmark building. Thus the performance of the MR dampers is far better than SAVFD in reducing displacement, drift, acceleration and base shear of mid to high-rise building against seismic forces.

Keywords: benchmark building, control strategy, input excitation, MR dampers, peak response, semi-active variable friction dampers

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Authors: Evgeniia Surkova, Manal Assaad, Hleb Makeyeu, Juho Makio

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The main objective of STIMEY (Science, Technology, Innovation, Mathematics, Engineering for the Young) project is the delivery of a hybrid learning environment that combines multi-level components such as social media concepts, robotic artefacts, and radio, among others. It is based on a well-researched pedagogical framework to attract European youths to STEM (science, technology, engineering, and mathematics) education and careers. To develop and integrate these various components, STIMEY is executed in iterative research cycles leading to progressive improvements. Scrum was the development methodology of choice in the project, as studies indicated its benefits as an agile methodology in global software development, especially of e-learning and integrated learning projects. This paper describes the project partners’ experience with the Scrum framework, discussing the challenges faced in its implementation and the mitigation practices employed. The authors conclude with exploring user experience tools and principles for future research, as a novel direction in supporting the Scrum development team.

Keywords: e-learning, global software development, scrum, STEM education

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Authors: Rajaa Filali, Mohamed Bouhdadi

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This paper presents an incremental development of the Dynamic Host Configuration Protocol (DHCP) in Event-B. DHCP is widely used communication protocol, which provides a standard mechanism to obtain configuration parameters. The specification is performed in a stepwise manner and verified through a series of refinements. The Event-B formal method uses the Rodin platform to modeling and verifying some properties of the protocol such as safety, liveness and deadlock freedom. To model and verify the protocol, we use the formal technique Event-B which provides an accessible and rigorous development method. This interaction between modelling and proving reduces the complexity and helps to eliminate misunderstandings, inconsistencies, and specification gaps.

Keywords: DHCP protocol, Event-B, refinement, proof obligation, Rodin

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Authors: Elcin Timur Cakmak, Ayse Oguzlar

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This study presents the results of the tweets sent by Twitter users on social media about the Russia-Ukraine war by bigram and trigram methods. On February 24, 2022, Russian President Vladimir Putin declared a military operation against Ukraine, and all eyes were turned to this war. Many people living in Russia and Ukraine reacted to this war and protested and also expressed their deep concern about this war as they felt the safety of their families and their futures were at stake. Most people, especially those living in Russia and Ukraine, express their views on the war in different ways. The most popular way to do this is through social media. Many people prefer to convey their feelings using Twitter, one of the most frequently used social media tools. Since the beginning of the war, it is seen that there have been thousands of tweets about the war from many countries of the world on Twitter. These tweets accumulated in data sources are extracted using various codes for analysis through Twitter API and analysed by Python programming language. The aim of the study is to find the word sequences in these tweets by the n-gram method, which is known for its widespread use in computational linguistics and natural language processing. The tweet language used in the study is English. The data set consists of the data obtained from Twitter between February 24, 2022, and April 24, 2022. The tweets obtained from Twitter using the #ukraine, #russia, #war, #putin, #zelensky hashtags together were captured as raw data, and the remaining tweets were included in the analysis stage after they were cleaned through the preprocessing stage. In the data analysis part, the sentiments are found to present what people send as a message about the war on Twitter. Regarding this, negative messages make up the majority of all the tweets as a ratio of %63,6. Furthermore, the most frequently used bigram and trigram word groups are found. Regarding the results, the most frequently used word groups are “he, is”, “I, do”, “I, am” for bigrams. Also, the most frequently used word groups are “I, do, not”, “I, am, not”, “I, can, not” for trigrams. In the machine learning phase, the accuracy of classifications is measured by Classification and Regression Trees (CART) and Naïve Bayes (NB) algorithms. The algorithms are used separately for bigrams and trigrams. We gained the highest accuracy and F-measure values by the NB algorithm and the highest precision and recall values by the CART algorithm for bigrams. On the other hand, the highest values for accuracy, precision, and F-measure values are achieved by the CART algorithm, and the highest value for the recall is gained by NB for trigrams.

Keywords: classification algorithms, machine learning, sentiment analysis, Twitter

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Authors: Youmen Chaaban, Abdallah Abu-Tineh

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This article examines the development of a professional development (PD) model for educator growth and learning that is embedded into the school context. The School based Support Program (SBSP), designed for the Qatari context, targets the practices, knowledge, and skills of both school leadership and teachers in an attempt to improve students’ learning outcomes. Key aspects of the model include the development of learning communities among teachers, strong leadership that supports school improvement activities, and the use of research-based PD to improve teacher practices and student achievement. This paper further presents the results of a qualitative study examining the perceptions of nineteen instructional coaches about the strengths of the PD program, the challenges they face in their day-to-day implementation of the program, and their suggestions for the betterment of the program’s implementation and outcomes. Data were collected from the instructional coaches through open-ended surveys followed by focus group interviews. The instructional coaches reported several strengths, which were compatible with the literature on effective PD. However, the challenges they faced were deeply rooted within the structure of the program, in addition to external factors operating at the school and Ministry of Education levels. Thus, a general consensus on the way the program should ultimately develop was reached.

Keywords: situated professional development, school reform, instructional coach, school based support program

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Authors: Uzoma Emmanuel Igboji

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This paper examines the influence of public debts (external and internal) on economic growth and development in Nigeria from (1980-2015). The study uses aggregate GDP as a proxy for economic growth, per capital income as a proxy for standard of living and Government expenditure on health as a proxy for human capital development, while Foreign Direct Investment, Unemployment rate, and Oil revenue were used as control variables. The study made use of ex-post facto research design with the data extracted from the Central Bank of Nigeria (CBN) Statistical Bulletin and the World Bank database. It adopted a multiple regression analysis of the ordinary least square (OLS) method with the help of E-View version 3.0. The results revealed that external debt has a negative and insignificant effect on GDP, per capital income and human capital development. The study concluded that external debts were being channeled to meet the recurrent expenditures of the nation’s economy at the expense of productive investment that could stimulate growth and poverty alleviation. It, however, recommended that government should ensure that the bulk of the total borrowings are mostly sourced from within the domestic economy so that the repayment of the principal and interest will serve as a crowd in-effect rather that crowd out-effect which in turn further accelerates the country’s economic growth and development.

Keywords: economic growth, external debt, internal debt, Nigeria

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Authors: Roman Bieda

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The General Data Protection Regulation (GDPR) will come into force on 25 May 2018 which will create a new legal framework for the protection of personal data in the European Union. Article 20 of GDPR introduces a right to data portability. This right allows for data subjects to receive the personal data which they have provided to a data controller, in a structured, commonly used and machine-readable format, and to transmit this data to another data controller. The right to data portability, by facilitating transferring personal data between IT environments (e.g.: applications), will also facilitate changing the provider of services (e.g. changing a bank or a cloud computing service provider). Therefore, it will contribute to the development of competition and the digital market. The aim of this paper is to discuss the right to data portability and its influence on the development of new digital services.

Keywords: data portability, digital market, GDPR, personal data

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Authors: Lim Lie Pin, Lin Hui Wen

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Rural tourism has become popular in Taiwan, the villages based on agriculture including fishery have to follow the trend to develop the local economy and achieve the sustainable development of the rural areas. Through cultural festivals, the tourist could experience the benefit while promoting and stimulating the local development of rural tourism. Cigu is famous for salt history and abundant natural resources, such as lagoon, black-faced spoonbills and other fishery products. Digging clam has become the most special parent-child activities in Tainan and increasing awareness since it was initiated. Therefore, festival organizers and regional destination marketers need to identify visitors’ experiences attributes which lead to opportunities for industry professionals, community involvement to plan and organize regional festivals and their programmes for effective destination branding finding out more potential rural resources encouraging the local industry growth and sustainable development.

Keywords: rural tourism, cultural festival, destination branding, tourist experience, sustainable development

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Authors: Rohit Dey, Sailendra Karra

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This paper aims at solving the problem of multi-target searching in a Global Positioning System (GPS) denied environment using swarm robots with limited sensing and communication abilities. Typically, existing swarm-based search algorithms rely on the presence of a global coordinate system (vis-à-vis, GPS) that is shared by the entire swarm which, in turn, limits its application in a real-world scenario. This can be attributed to the fact that robots in a swarm need to share information among themselves regarding their location and signal from targets to decide their future course of action but this information is only meaningful when they all share the same coordinate frame. The paper addresses this very issue by eliminating any dependency of a search algorithm on the need of a predetermined global coordinate frame by the unification of the relative coordinate of individual robots when within the communication range, therefore, making the system more robust in real scenarios. Our algorithm assumes that all the robots in the swarm are equipped with range and bearing sensors and have limited sensing range and communication abilities. Initially, every robot maintains their relative coordinate frame and follow Levy walk random exploration until they come in range with other robots. When two or more robots are within communication range, they share sensor information and their location w.r.t. their coordinate frames based on which we unify their coordinate frames. Now they can share information about the areas that were already explored, information about the surroundings, and target signal from their location to make decisions about their future movement based on the search algorithm. During the process of exploration, there can be several small groups of robots having their own coordinate systems but eventually, it is expected for all the robots to be under one global coordinate frame where they can communicate information on the exploration area following swarm search techniques. Using the proposed method, swarm-based search algorithms can work in a real-world scenario without GPS and any initial information about the size and shape of the environment. Initial simulation results show that running our modified-Particle Swarm Optimization (PSO) without global information we can still achieve the desired results that are comparable to basic PSO working with GPS. In the full paper, we plan on doing the comparison study between different strategies to unify the coordinate system and to implement them on other bio-inspired algorithms, to work in GPS denied environment.

Keywords: bio-inspired search algorithms, decentralized control, GPS denied environment, swarm robotics, target searching, unifying coordinate systems

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Authors: Maryam Goodarzi, Mahdieh Sheikhi, Mehdi Goodarzi

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This study intends to offer an appropriate strategy development framework for a telecommunication firm (as a case study) which works on Information and Communication Technology (ICT) projects, development of telecommunication networks, and maintenance of local networks, according to its dominant condition. In this approach, first, the objectives were set and the mission was defined. Then, the capability was assessed by SWOT matrix. Using SPACE matrix, the strategy of the company was determined. The strategic direction is set and an appropriate and superior strategy was developed and offered employing QSPM matrix. The theoretical framework or conceptual model of the present study first involves 4 stages of framework development and then from stage 3 (assessing capability) onward, a strategic management model by Fred R. David. In this respect, the tools and methods offered in the framework are appropriate for all kinds of organizations, particularly small firms, and help strategists identify, evaluate, and select strategies.

Keywords: strategy formulation, firm mission, strategic direction, space diagram, quantitative strategic planning matrix, SWOT matrix

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Authors: Mohammad Parvaresh, Mahdi Babaee, Bahareh Arghand, Roushanak Fahimi Hanzaee, Davood Nourmohammadi

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Today, the intelligent network of water and wastewater as one of the key steps in realizing the smart city in the world. Use of pressure relief valves in urban water networks in order to reduce the pressure is necessary in Tehran city. But use these pressure relief valves lead to waste water, more power consumption, and environmental pollution because Tehran Province Water and Wastewater Co. use a quarter of industry 's electricity. In this regard, Tehran Province Water and Wastewater Co. identified solutions to reduce direct and indirect costs in energy use in the process of production, transmission and distribution of water because this company has extensive facilities and high capacity to realize green economy and industry. The aim of this study is to analyze the new project in water and wastewater industry to reach sustainable development.

Keywords: Tehran Province Water and Wastewater Company, water network efficiency, sustainable development, International Environmental Law

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