Search results for: integration features

Authors: Liqiang Duan, Ma Jingkai, Lv Zhipeng, Haifan Cai

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The integrated solar combined cycle (ISCC) system has a series of advantages such as increasing the system power generation, reducing the cost of solar power generation, less pollutant and CO₂ emission. In this paper, the parabolic trough collectors with direct steam generation (DSG) technology are considered to replace the heat load of heating surfaces in heat regenerator steam generation (HRSG) of a conventional natural gas combined cycle (NGCC) system containing a PG9351FA gas turbine and a triple pressure HRSG with reheat. The detailed model of the NGCC system is built in ASPEN PLUS software and the parabolic trough collectors with DSG technology is modeled in EBSILON software. ISCC-DSG systems with the replacement of single, two, three and four heating surfaces are studied in this paper. Results show that: (1) the ISCC-DSG systems with the replacement heat load of HPB, HPB+LPE, HPE2+HPB+HPS, HPE1+HPE2+ HPB+HPS are the best integration schemes when single, two, three and four stages of heating surfaces are partly replaced by the parabolic trough solar energy collectors with DSG technology. (2) Both the changes of feed water flow and the heat load of the heating surfaces in ISCC-DSG systems with the replacement of multi-stage heating surfaces are smaller than those in ISCC-DSG systems with the replacement of single heating surface. (3) ISCC-DSG systems with the replacement of HPB+LPE heating surfaces can increase the solar power output significantly. (4) The ISCC-DSG systems with the replacement of HPB heating surfaces has the highest solar-thermal-to-electricity efficiency (47.45%) and the solar radiation energy-to-electricity efficiency (30.37%), as well as the highest exergy efficiency of solar field (33.61%).

Keywords: HRSG, integration scheme, parabolic trough collectors with DSG technology, solar power generation

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Authors: Shahrokh Barati, Reza Ramezani

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Due to the countries growing attention to the renewable energy producing, the demand for energy from renewable energy has gone up among the renewable energy sources; wind energy is the fastest growth in recent years. In this regard, in order to increase the availability of wind turbines, using of Fault Detection and Isolation (FDI) system is necessary. Wind turbines include of various faults such as sensors fault, actuator faults, network connection fault, mechanical faults and faults in the generator subsystem. Although, sensors and actuators have a large number of faults in wind turbine but have discussed fewer in the literature. Therefore, in this work, we focus our attention to design a sensor and actuator fault detection and isolation algorithm and Fault-tolerant control systems (FTCS) for Wind Turbine. The aim of this research is to propose a comprehensive fault detection and isolation system for sensors and actuators of wind turbine based on data-driven approaches. To achieve this goal, the features of measurable signals in real wind turbine extract in any condition. The next step is the feature selection among the extract in any condition. The next step is the feature selection among the extracted features. Features are selected that led to maximum separation networks that implemented in parallel and results of classifiers fused together. In order to maximize the reliability of decision on fault, the property of fault repeatability is used.

Keywords: FDI, wind turbines, sensors and actuators faults, renewable energy

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Authors: Spoorthi Sripad

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Rapid advancements in LiDAR (Light Detection and Ranging) technology, coupled with the synergy of remote sensing, have revolutionized Earth observation methodologies. This paper delves into the transformative impact of integrated LiDAR and remote sensing systems. Focusing on miniaturization, cost reduction, and improved resolution, the study explores the evolving landscape of terrestrial and aquatic environmental monitoring. The integration of multi-wavelength and dual-mode LiDAR systems, alongside collaborative efforts with other remote sensing technologies, presents a comprehensive approach. The paper highlights the pivotal role of LiDAR in environmental assessment, urban planning, and infrastructure development. As the amalgamation of LiDAR and remote sensing reshapes Earth observation, this research anticipates a paradigm shift in our understanding of dynamic planetary processes.

Keywords: LiDAR, remote sensing, earth observation, advancements, integration, environmental monitoring, multi-wavelength, dual-mode, technology, urban planning, infrastructure, resolution, miniaturization

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Authors: Maassoumeh Bemani Naeini

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Studies on interlanguage have long been engaged in describing the phenomenon of variation in SLA. Pursuing the same goal and particularly addressing the role of linguistic features, this study describes the use of Persian morphology in the interlanguage of two adult English-speaking learners of Persian L2. Taking the general approach of a combination of contrastive analysis, error analysis and interlanguage analysis, this study focuses on the identification and prediction of some possible instances of transfer from English L1 to Persian L2 across six elicitation tasks aiming to investigate whether any of contextual features may variably influence the learners’ order of morpheme accuracy in the areas of copula, possessives, articles, demonstratives, plural form, personal pronouns, and genitive cases.  Results describe the existence of task variation in the interlanguage system of Persian L2 learners.

Keywords: English L1, Interlanguage Analysis, Persian L2, SLA variation

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Authors: P. Shrivastava, A. Shukla, K. Verma, S. Rungta

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Parkinson's disease is a chronic neurological disorder that directly affects human gait. It leads to slowness of movement, causes muscle rigidity and tremors. Gait serve as a primary outcome measure for studies aiming at early recognition of disease. Using gait techniques, this paper implements efficient binary bat algorithm for an early detection of Parkinson's disease by selecting optimal features required for classification of affected patients from others. The data of 166 people, both fit and affected is collected and optimal feature selection is done using PSO and Bat algorithm. The reduced dataset is then classified using neural network. The experiments indicate that binary bat algorithm outperforms traditional PSO and genetic algorithm and gives a fairly good recognition rate even with the reduced dataset.

Keywords: parkinson, gait, feature selection, bat algorithm

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Authors: Lemac Tin

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This paper deals with the lyrical subject of the confessional poetry which is the main part of her stylistic strucuture. We concluded two types of this subject in the classical confessional poetic discourse; reflexive and authentic subject. We offer the model of their genesis, textual features and appeareance realisations. Genesis is related to the theories of deriving poetry from emotion and magic and their similar position in the primitive lyrics and lyrics of the ancient civilizations. Textual features are related to the emotive and semiotic analysis of each type. Appearance realisations of these two types are I-subject, We-subject, transvocal and objectified subject. We check this approaches on some of the poems from World literature.

Keywords: confessional poetry, confessional lyrical subject, magic, emotion, emotive analysis, semiotic analysis

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Authors: Idil Kanter Otcu

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Nowadays, due to the growing problems of energy supply and the drastic reduction of natural non-renewable resources, the development of new applications in the energy sector and steps towards greater efficiency in energy consumption are required. Since buildings account for a large share of energy consumption, increasing the structural density of buildings causes an increase in energy consumption. This increase in energy consumption means that energy efficiency approaches to building design and the integration of new systems using emerging technologies become necessary in order to curb this consumption. As new systems for productive usage of generated energy are developed, buildings that require less energy to operate, with rational use of resources, need to be developed. One solution for reducing the energy requirements of buildings is through landscape planning, design and application. Requirements such as heating, cooling and lighting can be met with lower energy consumption through planting design, which can help to achieve more efficient and rational use of resources. Within this context, rather than a planting design which considers only the ecological and aesthetic features of plants, these considerations should also extend to spatial organization whereby the relationship between the site and open spaces in the context of climatic elements and planting designs are taken into account. In this way, the planting design can serve an additional purpose. In this study, a landscape design which takes into consideration location, local climate morphology and solar angle will be illustrated on a sample building project.

Keywords: energy efficiency, landscape design, plant design, xeriscape landscape

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Authors: S. Kherchaoui, A. Houacine

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This paper presents a facial expression recognition system. It performs identification and classification of the seven basic expressions; happy, surprise, fear, disgust, sadness, anger, and neutral states. It consists of three main parts. The first one is the detection of a face and the corresponding facial features to extract the most expressive portion of the face, followed by a normalization of the region of interest. Then calculus of curvelet coefficients is performed with dimensionality reduction through principal component analysis. The resulting coefficients are combined with two ratios; mouth ratio and face edge ratio to constitute the whole feature vector. The third step is the classification of the emotional state using the SVM method in the feature space.

Keywords: facial expression identification, curvelet coefficient, support vector machine (SVM), recognition system

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Authors: Widhi Hanantyo Suryadinata

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Efforts undertaken by Indonesia and China to shift the strategies and security of renewable energy on a global stage involve approaches through policy construction related to rare minerals processing or value-adding in Indonesia and manufacturing policies through the New Energy Vehicles (NEVs) policy in China. Both policies encompass several practical regulations and policies that can be utilized for the implementation of Indonesia and China's grand efforts and ideas. Policy development in Indonesia and China can be analyzed using a comparative analysis method, as well as employing a pyramid illustration to identify policy construction phases based on the real conditions of the domestic market and implemented policies. This approach also helps to identify the potential integration of policies needed to enhance the policy development phase of a country within the pyramid. It also emphasizes the significance of integration policy to redefine renewable energy strategy and security on the global stage.

Keywords: global renewable energy security, global energy security, policy development, comparative analysis, shifting of global energy security, Indonesia, China

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Authors: Khadra Ahmed, Khaled Kheireldin

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In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.

Keywords: planktons, diversity indices, water quality index, water ways

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Authors: Jessica Ding

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The field of global health is currently advocating for a resurgence in the use of traditional medicines to improve people-centered care. Healthcare policies are rapidly changing in response; in China, the increasing presence of TCM in the same spaces as biomedicine has led to a new term: integrative medicine. However, the existence of TCM as a part of integrative medicine creates a pressing paradoxical tension where TCM is both seen as a marginalized system within ‘modern’ hospitals and as a modality worth integrating. Additionally, the impact of such shifts has not been fully explored: the World Health Organization for one focuses only on three angles —practices, products, and practitioners— with regards to traditional medicines. Through ten weeks of fieldwork conducted at an urban hospital in Shanghai, China, this research expands the perspective of existing strategies by looking at integrative care through a fourth lens: patients and families. The understanding of self-care, health-seeking behavior, and non-professional caregiving structures are critical to grasping the significance of traditional medicine for people-centered care. Indeed, those individual and informal health care expectations align with the very spaces and needs that traditional medicine has filled before such ideas of integration. It specifically looks at this issue via three processes that operationalize experiences of care: (1) how aspects of TCM are valued within integrative medicine, (2) how negotiations of care occur between patients and doctors, and (3) how 'good quality' caregiving presents in integrative clinical spaces. This research hopes to lend insight into how culturally embedded traditions, bureaucratic and institutional rationalities, and social patterns of health-seeking behavior influence care to shape illness experiences at the intersection of two medical modalities. This analysis of patients’ clinical and illness experiences serves to enrich the narratives of integrative medical care’s ability to provide patient-centered care to determine how international policies are realized at the individual level. This anthropological study of the integration of Traditional Chinese medicine in local contexts can reveal the extent to which global strategies, as promoted by the WHO and the Chinese government actually align with the expectations and perspectives of patients receiving care. Ultimately, this ethnographic analysis of a local Chinese context hopes to inform global policies regarding the future use and integration of traditional medicines.

Keywords: emergent systems, global health, integrative medicine, traditional Chinese medicine, TCM

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Authors: M. A. Ben Messaoud, A. Bouzid, N. Ellouze

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Speech Segmentation is the measure of the change point detection for partitioning an input speech signal into regions each of which accords to only one speaker. In this paper, we apply two features based on multi-scale product (MP) of the clean speech, namely the spectral centroid of MP, and the zero crossings rate of MP. We focus on multi-scale product analysis as an important tool for segmentation extraction. The multi-scale product is based on making the product of the speech wavelet transform coefficients at three successive dyadic scales. We have evaluated our method on the Keele database. Experimental results show the effectiveness of our method presenting a good performance. It shows that the two simple features can find word boundaries, and extracted the segments of the clean speech.

Keywords: multiscale product, spectral centroid, speech segmentation, zero crossings rate

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Authors: Temitope O. Tokosi

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Healthcare is a human right. The sensitivity of health issues has necessitated the introduction of Enterprise Content Management (ECM) at district hospitals in the Western Cape Province of South Africa. The objective is understanding clinicians’ perception of ECM at their workplace. It is a descriptive case study design of constructivist paradigm. It employed a phenomenological data analysis method using a pattern matching deductive based analytical procedure. Purposive and s4nowball sampling techniques were applied in selecting participants. Clinicians expressed concerns and frustrations using ECM such as, non-integration with other hospital systems. Inadequate access points to ECM. Incorrect labelling of notes and bar-coding causes more time wasted in finding information. System features and/or functions (such as search and edit) are not possible. Hospital management and clinicians are not constantly interacting and discussing. Information turnaround time is unacceptably lengthy. Resolving these problems would involve a positive working relationship between hospital management and clinicians. In addition, prioritising the problems faced by clinicians in relation to relevance can ensure problem-solving in order to meet clinicians’ expectations and hospitals’ objective. Clinicians’ perception should invoke attention from hospital management with regards technology use. The study’s results can be generalised across clinician groupings exposed to ECM at various district hospitals because of professional and hospital homogeneity.

Keywords: clinician, electronic content management, hospital, perception, technology

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Authors: Nicolay Worren, Christopher A. Brown

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Axiomatic design (AD) has mainly been applied to support the design of physical products and software solutions. However, it was intended as a general design approach that would also be applicable to the design of social systems, including organizations (i.e., organization design). In this article, we consider how AD may be successfully transferred to the field of organizational design. On the one hand, it provides a much-needed pragmatic approach that can help leaders clarify the link between the purpose and structure of their organizations, identify ineffective organizational structures, and increase the chance of achieving strategic goals. On the other hand, there are four conceptual challenges that may create uncertainty and resistance among scholars and practitioners educated in the social sciences: 1) The exclusive focus in AD on negative interdependencies ('coupling'); 2) No obvious way of representing the need for integration across design parameters (DPs); 3) A lack of principles for handling control processes that seem to require 'deliberate coupling' of FRs; and 4) A lack of principles for handling situations where conflicting FRs (i.e., coupling) might require integration rather than separation. We discuss alternative options for handling these challenges so that scholars and practitioners can make use of AD for organization design.

Keywords: axiomatic design, organization design, social systems, concept definitions

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Authors: Claire Xu, Welton Wang, Manasvi Pinnaka, Anqi Pan, Michael Han

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Hospitalizations account for one-third of the total health care spending in the US. Early risk detection and intervention can reduce this high cost and increase the satisfaction of both patients and physicians. Due to the lack of awareness of the potential arising risks in home environment, the opportunities for patients to seek early actions of clinical visits are dramatically reduced. This research aims to offer a highly personalized remote patients monitoring and risk assessment AI framework to identify the potentially preventable hospitalization for both acute as well as chronic diseases. A hybrid-AI framework is trained with data from clinical setting, patients surveys, as well as online databases. 20+ risk factors are analyzed ranging from activities, biometric info, demographic info, socio-economic info, hospitalization history, medication info, lifestyle info, etc. The AI model yields high performance of 87% accuracy and 88 sensitivity with 20+ features. This hybrid-AI framework is proven to be effective in identifying the potentially preventable hospitalization. Further, the high indicative features are identified by the models which guide us to a healthy lifestyle and early intervention suggestions.

Keywords: hospitalization prevention, machine learning, remote patient monitoring, risk prediction

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Authors: Shilpi Tripathi

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India has adopted the policy of economic reforms (Globalization, Liberalization, and Privatization) in 1991 which has reduced the trade barriers and investment restrictions and further increased the economy’s international trade, foreign direct investment (FDI) inflows and Gross Domestic Product (GDP) growth. The paper empirically studies the relationship between India’s international trades, GDP, FDI and environment during 1978-2012. The first part of the paper focuses on the background and trends of FDI, GDP, trade, and environment (CO2). The second part focuses on the literature regarding the relationship among all the variables. The last part of paper, we examine the results of empirical analysis like co integration and Granger causality between foreign trade, FDI inflows, GDP and CO2 since 1978. The findings of the paper revealed that there is only one uni- directional causality exists between GDP and trade. The direction of causality reveals that international trade is one of the major contributors to the economic growth (GDP). While, there is no causality found between GDP and FDI, FDI, and CO2 and International trade and CO2. The paper concludes with the policy recommendations that will ensure environmental friendly trade, investment and growth in India for future.

Keywords: international trade, foreign direct investment, GDP, CO2, co-integration, granger causality test

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Authors: A. J. S. P. Nileema, S. Kulatunga , S. H. Palihawadana

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Computer aided detection (CAD) system was developed for the diagnosis of pulmonary tuberculosis using digital chest X-rays with MATLAB image processing techniques using a statistical approach. The study comprised of 200 digital chest radiographs collected from the National Hospital for Respiratory Diseases - Welisara, Sri Lanka. Pre-processing was done to remove identification details. Lung fields were segmented and then divided into four quadrants; right upper quadrant, left upper quadrant, right lower quadrant, and left lower quadrant using the image processing techniques in MATLAB. Contrast, correlation, homogeneity, energy, entropy, and maximum probability texture features were extracted using the gray level co-occurrence matrix method. Descriptive statistics and normal distribution analysis were performed using SPSS. Depending on the radiologists’ interpretation, chest radiographs were classified manually into PTB - positive (PTBP) and PTB - negative (PTBN) classes. Features with standard normal distribution were analyzed using an independent sample T-test for PTBP and PTBN chest radiographs. Among the six features tested, contrast, correlation, energy, entropy, and maximum probability features showed a statistically significant difference between the two classes at 95% confidence interval; therefore, could be used in the classification of chest radiograph for PTB diagnosis. With the resulting value ranges of the five texture features with normal distribution, a classification algorithm was then defined to recognize and classify the quadrant images; if the texture feature values of the quadrant image being tested falls within the defined region, it will be identified as a PTBP – abnormal quadrant and will be labeled as ‘Abnormal’ in red color with its border being highlighted in red color whereas if the texture feature values of the quadrant image being tested falls outside of the defined value range, it will be identified as PTBN–normal and labeled as ‘Normal’ in blue color but there will be no changes to the image outline. The developed classification algorithm has shown a high sensitivity of 92% which makes it an efficient CAD system and with a modest specificity of 70%.

Keywords: chest radiographs, computer aided detection, image processing, pulmonary tuberculosis

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Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi

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Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.

Keywords: breast cancer, diagnosis, machine learning, biomarker classification, neural network

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Authors: Angelica S. Valeriani, Lorenzo Biasiolo

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In recent years, the scale of the impact of climate change and its related side effects has become ever more massive and devastating. Sustainable Development Goals (SDGs), promoted by United Nations, aim to front issues related to climate change, among others. In particular, the project CROWD4SDG focuses on a bunch of SDGs since it promotes environmental activities and climate-related issues. In this context, we developed a prototype of an application, under advanced development considering web design, that focuses on SDG 13 (SDG on climate action) by providing users with useful instruments to face environmental crises and climate-related disasters. Our prototype is thought and structured for both web and mobile development. The main goal of the application, POLI4SDG, is to help users to get through emergency services. To this extent, an organized overview and classification prove to be very effective and helpful to people in need. A careful analysis of data related to environmental crises prompted us to integrate the user contribution, i.e., exploiting a core principle of Citizen Science, into the realization of a public catalog, available for consulting and organized according to typology and specific features. In addition, gender equality and opportunity features are considered in the prototype in order to allow women, often the most vulnerable category, to have direct support. The overall description of the application functionalities is detailed. Moreover, the implementation features and properties of the prototype are discussed.

Keywords: crowdsourcing, social media, SDG, climate change, natural disasters, gender equality

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Authors: Marcus Lee

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The energy sector is the largest contributor of greenhouse gas emissions in Malaysia, which induces climate change. The climate change problem is therefore an energy sector problem. Tackling climate change issues successfully is contingent on actions taken in the energy sector. The researcher propounds that ‘Climate Policy Integration’ (CPI) into energy policy is a viable and insufficiently developed strategy in Malaysia that promotes the synergies between climate change and energy objectives, in order to achieve the targets found in both climate change and energy policies. In exploring this hypothesis, this paper presentation will focus on two particular aspects. Firstly, the meaning of CPI as an approach and as a concept will be explored. As an approach, CPI into energy policy means the integration of climate change objectives into the energy policy area. Its subject matter focuses on establishing the functional interrelations between climate change and energy objectives, by promoting their synergies and minimising their contradictions. However, its conceptual underpinnings are less than straightforward. Drawing from the ‘principle of integration’ found in international treaties and declarations such as the Stockholm Declaration 1972, the Rio Declaration 1992 and the United Nations Framework on Climate Change 1992 (‘UNFCCC’), this paper presentation will explore the contradictions in international standards on how the sustainable development tenets of environmental sustainability, social development and economic development are to be balanced and its relevance to CPI. Further, the researcher will consider whether authority may be derived from international treaties and declarations in order to argue for the prioritisation of environmental sustainability over the other sustainable development tenets through CPI. Secondly, this paper presentation will also explore the degree to which CPI into energy policy has been achieved and pursued in Malaysia. In particular, the strength of the conceptual framework with regard to CPI in Malaysian governance will be considered by assessing Malaysia’s National Policy on Climate Change (2009) (‘NPCC 2009’). The development (or the lack of) of CPI as an approach since the publication of the NPCC 2009 will also be assessed based on official government documents and policies that may have a climate change and/or energy agenda. Malaysia’s National Renewable Energy Policy and Action Plan (2010), draft National Energy Efficiency Action Plan (2014), Intended Nationally Determined Contributions (2015) in relation to the Paris Agreement, 11th Malaysia Plan (2015) and Biennial Update Report to the UNFCCC (2015) will be discussed. These documents will be assessed for the presence of CPI based on the language/drafting of the documents as well as the degree of subject matter regarding CPI expressed in the documents. Based on the analysis, the researcher will propose solutions on how to improve Malaysia’s climate change and energy governance. The theory of reflexive governance will be applied to CPI. The concluding remarks will be about whether CPI reflects reflexive governance by demonstrating how the governance process can be the object of shaping outcomes.

Keywords: climate policy integration, mainstreaming, policy coherence, Malaysian energy governance

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Authors: Eyosiyas Aga

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The development of information communication technology has transformed the paper-based mapping and land registration processes to a computerized and networked system. The computerization and networking of real property information system play a vital role in good governance and sustainable development of emerging countries through cost effective, easy and accessible service delivery for the customer. The efficient, transparent and sustainable real property system is becoming the basic infrastructure for the urban development thus improve the data management system and service delivery in the organizations. In Ethiopia, the real property administration is paper based as a result, it confronted problems of data management, illegal transactions, corruptions, and poor service delivery. In order to solve this problem and to facilitate real property market, the implementation of web-based real property updating system is crucial. A web-based real property updating is one of the automation (computerizations) methods to facilitate data sharing, reduce time and cost of the service delivery in real property administration system. In additions, it is useful for the integration of data onto different information systems and organizations. This system is designed by combining open source software which supported by open Geo-spatial consortium. The web-based system is mainly designed by using open source software with the help of open Geo-spatial Consortium. The Open Geo-spatial Consortium standards such as the Web Feature Service and Web Map Services are the most widely used standards to support and improves web-based real property updating. These features allow the integration of data from different sources, and it can be used to maintain consistency of data throughout transactions. The PostgreSQL and Geoserver are used to manage and connect a real property data to the flex viewer and user interface. The system is designed for both internal updating system (municipality); which is mainly updating of spatial and textual information, and the external system (customer) which focus on providing and interacting with the customer. This research assessed the potential of open source web applications and adopted this technology for real property updating system in Ethiopia through simple, cost effective and secured way. The system is designed by combining and customizing open source software to enhance the efficiency of the system in cost effective way. The existing workflow for real property updating is analyzed to identify the bottlenecks, and the new workflow is designed for the system. The requirement is identified through questionnaire and literature review, and the system is prototype for the study area. The research mainly aimed to integrate human resource with technology in designing of the system to reduce data inconsistency and security problems. In additions, the research reflects on the current situation of real property administration and contributions of effective data management system for efficient, transparent and sustainable urban development in Ethiopia.

Keywords: cadaster, real property, sustainable, transparency, web feature service, web map service

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Authors: Chamindi Dilkushi Senaratne

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Borrowing is the morphological, syntactic and (usually) phonological integration of lexical items from one language into the structure of another language. Borrowings show complete linguistic integration and due to the frequency of use become fossilized in the recipient language differentiating them from switches and mixes. Code mixes are different to borrowings. Code mixing takes place when speakers use lexical items in casual conversation to serve a variety of functions. This study presents an analysis of lexical items used in English newspapers in Sri Lanka in 2017 which reveal characteristics of borrowing or code mixes. Both phenomena arise due to language contact. The study will also use data from social media websites that comment on newspaper articles available on the web. The study reiterates that borrowings are distinguishable from code mixes and that they are two different phenomena that occur in language contact situations. The study also shows how existing morphological processes are used to create new vocabulary in language use. The study sheds light into how existing morphological processes are used by the bilingual to be creative, innovative and convey a bilingual identity.

Keywords: borrowing, code mixing, morphological processes

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Authors: Rik van Leeuwen, Ger Koole

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Within hospitality, marketing departments use segmentation to create tailored strategies to ensure personalized marketing. This study provides a data-driven approach by segmenting guest profiles via hierarchical clustering based on an extensive set of features. The industry requires understandable outcomes that contribute to adaptability for marketing departments to make data-driven decisions and ultimately driving profit. A marketing department specified a business question that guides the unsupervised machine learning algorithm. Features of guests change over time; therefore, there is a probability that guests transition from one segment to another. The purpose of the study is to provide steps in the process from raw data to actionable insights, which serve as a guideline for how hospitality companies can adopt an algorithmic approach.

Keywords: hierarchical cluster analysis, hospitality, market segmentation

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Authors: Jonix Owino, Heather Fuller

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Refugees flee from their home countries due to civil unrest, war, persecution and migrate to Western countries such as the United States in search of a safe haven. Transitioning into a new society and culture can be challenging, thereby affecting refugee’s quality of life and well-being in the host communities. Moreover, as individuals age, they experience physical, cognitive and socioemotional changes that may impact their quality of life. However, little is known about the predictors of quality of life among aging refugees. It is not clear how quality of life varies by age, that is, between midlife refugees in comparison to their older counterparts. In addition to age, other sociodemographic factors such as gender, socioeconomic status, or country of origin are likely to have differential associations to quality of life, yet research on such variations among older refugees is sparse. Thus the present study seeks to explore factors associated with quality of life by asking the following research questions: 1) Do sociodemographic factors (such as age and gender) predict quality of life among older refugees, 2) Is there an association between social integration and quality of life, and 3) Is there an association between migratory related experiences (such as post migratory adjustments) and quality of life. The present study recruited 90 refugees (primarily originating from Bhutan, Somalia, Burundi, and Sudan) aged 50 or older living in the US. The participants completed a structured questionnaire which assessed factors such as participant’s sociodemographic attributes (e.g., age, gender, length of residence in the US, country of origin, employment, level of education, and marital status), and validated measures of social integration, post-migration living difficulties, and quality of life. Preliminary results suggest sociodemographic variability in quality of life among these refugees. Further analyses will be conducted using hierarchical regression analyses to address the following hypotheses: first, it is hypothesized that quality of life will vary by age and gender such that younger refugees and men will report higher quality of life. Second, it is expected that refugees with greater levels of social integration will also report better quality of life. Finally, post-migration factors such as language barriers and family stress are hypothesized to predict poorer quality of life. Further results will be analyzed, including potential moderating effects of age and gender, and resulting findings will be interpreted and discussed. The findings from this study have potential implications for communities on how they can better support older refugees as well as develop social programs that can effectively cater to their well-being. Conclusions will be drawn and discussed in light of policies related to both aging and refugee migration within the context of the US.

Keywords: aging out of place, migration, older refugees, quality of life, social integration

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Authors: Syed Atif Hassan, Luv Mehta, Syed Asif Hassan

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Hit song science is a field of investigation wherein machine learning techniques are applied to music tracks in order to extract such features from audio signals which can capture information that could explain the popularity of respective tracks. Record companies invest huge amounts of money into recruiting fresh talents and churning out new music each year. Gaining insight into the basis of why a song becomes popular will result in tremendous benefits for the music industry. This paper aims to extract basic musical and more advanced, acoustic features from songs while also taking into account external factors that play a role in making a particular song popular. We use a dataset derived from popular Spotify playlists divided by genre. We use ten genres (blues, classical, country, disco, hip-hop, jazz, metal, pop, reggae, rock), chosen on the basis of clear to ambiguous delineation in the typical sound of their genres. We feed these features into three different classifiers, namely, SVM with RBF kernel, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model at the end. Predicting song popularity is particularly important for the music industry as it would allow record companies to produce better content for the masses resulting in a more competitive market.

Keywords: classifier, machine learning, music tracks, popularity, prediction

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Authors: Yohanes Kristianto

Abstract:

The objective of this paper is to compose a sustainable supply chain that integrates product, process and networks design. An integrated life cycle assessment and techno-economic optimization is proposed that might deliver more economically feasible operations, minimizes environmental impacts and maximizes social contributions. Closed loop economy of the supply chain is achieved by reusing waste to be raw material of final products. Societal benefit is given by the supply chain by absorbing waste as source of raw material and opening new work opportunities. A case study of ethanol supply chain from rice straws is considered. The modeling results show that optimization within the scope of LCA is capable of minimizing both CO₂ emissions and energy and utility consumptions and thus enhancing raw materials utilization. Furthermore, the supply chain is capable of contributing to local economy through jobs creation. While the model is quite comprehensive, the future research recommendation on energy integration and global sustainability is proposed.

Keywords: life cycle assessment, techno-economic optimization, sustainable supply chains, closed loop economy

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Authors: Rabi Mouhcine, Amrouch Mustapha, Mahani Zouhir, Mammass Driss

Abstract:

In this paper, we present a system for offline recognition cursive Arabic handwritten text based on Hidden Markov Models (HMMs). The system is analytical without explicit segmentation used embedded training to perform and enhance the character models. Extraction features preceded by baseline estimation are statistical and geometric to integrate both the peculiarities of the text and the pixel distribution characteristics in the word image. These features are modelled using hidden Markov models and trained by embedded training. The experiments on images of the benchmark IFN/ENIT database show that the proposed system improves recognition.

Keywords: recognition, handwriting, Arabic text, HMMs, embedded training

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Authors: Wei Li, Tuo Yang

Abstract:

In order to satisfy the real-time and accurate requirements of cigarette smoke detection in complex scenes, a cigarette smoke detection technology based on the combination of deep learning and color features was proposed. Firstly, based on the color features of cigarette smoke, the suspicious cigarette smoke area in the image is extracted. Secondly, combined with the efficiency of cigarette smoke detection and the problem of network overfitting, a network model for cigarette smoke detection was designed according to YOLOV3 algorithm to reduce the false detection rate. The experimental results show that the method is feasible and effective, and the accuracy of cigarette smoke detection is up to 99.13%, which satisfies the requirements of real-time cigarette smoke detection in complex scenes.

Keywords: deep learning, computer vision, cigarette smoke detection, YOLOV3, color feature extraction

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Authors: Gheorghe Braniste

Abstract:

It is a matter of common knowledge the fact that the International Olympic Movement is characterized by dynamism and adaptability to the challenges of modern society. A significant proof of this is the establishment of the IOC Refugee Olympic Team in 2016, at the Olympic Games in Rio de Janeiro, a practice continued in Tokyo in 2020 and with a great chance to be successfully repeated in subsequent editions: Paris 2024 and Dakar 2026. This phenomenon is all the more welcome as, after the global refugee crisis of 2015, when the whole world has seen millions of people in the world displaced, we are now experiencing the negative effects of the war that started in February 2022 in Ukraine; which caused the exodus of the population to neighboring countries. Therefore, the international Olympic community must decide how to integrate Ukrainian athletes with refugee status into the Olympic system. Until the establishment of an internationally agreed policy, Romania and the Republic of Moldova, as countries directly involved in this process, must find urgent solutions to allow athletes to continue their Olympic careers. This article proposes a description of the strategies adopted both at the national level and at the level of sports clubs and an analysis of their impact on the performance of athletes.

Keywords: olympic movement, olympic games, refugees, performance, integration

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Authors: Harveen Kaur Tatla, Parisa Niknejad, Rajender Gupta, Bipro Ranjan Dhar, Mohd. Adana Khan

Abstract:

Sewage sludge management presents a pressing challenge in the realm of wastewater treatment, calling for sustainable and efficient solutions. This study explores the integration of Hydrothermal Liquefaction (HTL) and Anaerobic Digestion (AD) as a promising approach to address the complexities associated with sewage sludge treatment. The integration of these two processes offers a complementary and synergistic framework, allowing for the mitigation of inherent limitations, thereby enhancing overall efficiency, product quality, and the comprehensive utilization of sewage sludge. In this research, we investigate the optimal sequencing of HTL and AD within the treatment framework, aiming to discern which sequence, whether HTL followed by AD or AD followed by HTL, yields superior results. We explore a range of HTL working temperatures, including 250°C, 300°C, and 350°C, coupled with residence times of 30 and 60 minutes. To evaluate the effectiveness of each sequence, a battery of tests is conducted on the resultant products, encompassing Total Ammonia Nitrogen (TAN), Chemical Oxygen Demand (COD), and Volatile Fatty Acids (VFA). Additionally, elemental analysis is employed to determine which sequence maximizes energy recovery. Our findings illuminate the intricate dynamics of HTL and AD integration for sewage sludge management, shedding light on the temperature-residence time interplay and its impact on treatment efficiency. This study not only contributes to the optimization of sewage sludge treatment but also underscores the potential of integrated processes in sustainable waste management strategies. The insights gleaned from this research hold promise for advancing the field of wastewater treatment and resource recovery, addressing critical environmental and energy challenges.

Keywords: Anaerobic Digestion (AD), aqueous phase, energy recovery, Hydrothermal Liquefaction (HTL), sewage sludge management, sustainability.

Procedia PDF Downloads 55