Search results for: regional features

Authors: T. Pastraporn, J. Panida, P. Gasamapong, N. Jintana

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The study of inclusive educational environment of exceptional and normal children at the regional centre for special education aimed to establish guidelines for creating an environment for inclusive education. Buildings utilization of thirty-five elementary schools providing inclusive educational program in Bangkok were analyzed to study the following aspects: 1) The environment of exceptional and normal students’ inclusive classes at the regional centre for special education 2) The patterns of the environment suited to the exceptional and normal students’ inclusive classes 3) Environmental management policies for the inclusive classes of exceptional and normal students. Information was gathered from surveys, observations, questionnaires, document analysis, interviews, and non-experimental research. The findings showed that the usable spaces in school buildings were designated to enhance the three kinds of social learning experience: 1) Support class control 2) Help developing students’ personality consisting of physical, verbal and emotional expressions that are socially accepted 3) Recognition and learning, which are needed for the increasing of learning experience, were caused by having an interaction with the environment. Thus, the school buildings’ space designation positively affected the environmental management of exceptional and normal students’ inclusive classes.

Keywords: learning environment, inclusive education, school buildings, exceptional and normal children

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Authors: Faruk Ortes, Derya Karabulut, Yunus Ziya Arslan

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Myoelectric features gathering from musculature environment are considered on a preferential basis to perceive muscle activation and control human arm prostheses according to recent experimental researches. EMG (electromyography) signal based human arm prostheses have shown a promising performance in terms of providing basic functional requirements of motions for the amputated people in recent years. However, these assistive devices for neurorehabilitation still have important limitations in enabling amputated people to perform rather sophisticated or functional movements. Surface electromyogram (EMG) is used as the control signal to command such devices. This kind of control consists of activating a motion in prosthetic arm using muscle activation for the same particular motion. Extraction of clear and certain neural information from EMG signals plays a major role especially in fine control of hand prosthesis movements. Many signal processing methods have been utilized for feature extraction from EMG signals. The specific objective of this study was to compare widely used time domain features of EMG signal including integrated EMG(IEMG), root mean square (RMS) and waveform length(WL) for prediction of externally applied forces to human hands. Obtained features were classified using artificial neural networks (ANN) to predict the forces. EMG signals supplied to process were recorded during only type of muscle contraction which is isometric and isotonic one. Experiments were performed by three healthy subjects who are right-handed and in a range of 25-35 year-old aging. EMG signals were collected from muscles of the proximal part of the upper body consisting of: biceps brachii, triceps brachii, pectorialis major and trapezius. The force prediction results obtained from the ANN were statistically analyzed and merits and pitfalls of the extracted features were discussed with detail. The obtained results are anticipated to contribute classification process of EMG signal and motion control of powered human arm prosthetics control.

Keywords: assistive devices for neurorehabilitation, electromyography, feature extraction, force estimation, human arm prosthesis

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Authors: A. N. Paithane, D. S. Bormane, S. D. Shirbahadurkar

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It has been seen that emotion recognition is an important research topic in the field of Human and computer interface. A novel technique for Feature Extraction (FE) has been presented here, further a new method has been used for human emotion recognition which is based on HHT method. This method is feasible for analyzing the nonlinear and non-stationary signals. Each signal has been decomposed into the IMF using the EMD. These functions are used to extract the features using fission and fusion process. The decomposition technique which we adopt is a new technique for adaptively decomposing signals. In this perspective, we have reported here potential usefulness of EMD based techniques.We evaluated the algorithm on Augsburg University Database; the manually annotated database.

Keywords: intrinsic mode function (IMF), Hilbert-Huang transform (HHT), empirical mode decomposition (EMD), emotion detection, electrocardiogram (ECG)

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Authors: Takele Nemomsa, Girma Mamo, Tesfaye Balemi

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Climate change refers to a change in the state of the climate that can be identified (e.g. using statistical tests) by changes in the mean and/or variance of its properties and that persists for an extended period, typically decades or longer. In Ethiopia; Maize production in relation to climate change at regional and sub- regional scales have not been studied in detail. Thus, this study was aimed to analyse the impact of climate change on maize yield in Ambo Districts, Central Ethiopia. To this effect, weather data, soil data and maize experimental data for Arganne hybrid were used. APSIM software was used to investigate the response of maize (Zea mays) yield to different agronomic management practices using current and future (2020s–2080s) climate data. The climate change projections data which were downscaled using SDSM were used as input of climate data for the impact analysis. Compared to agronomic practices the impact of climate change on Arganne in Central Ethiopia is minute. However, within 2020s-2080s in Ambo area; the yield of Arganne hybrid is projected to reduce by 1.06% to 2.02%, and in 2050s it is projected to reduce by 1.56 While in 2080s; it is projected to increase by 1.03% to 2.07%. Thus, to adapt to the changing climate; farmers should consider increasing plant density and fertilizer rate per hectare.

Keywords: APSIM, downscaling, response, SDSM

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Authors: McKenzie S. Braley, Lesley Jessiman

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If language reveals internal psychological processing, then it is also likely that language use in autobiographical memory transcripts may be used as a window into attachment style and related personality features. The current study, therefore, examined the possible associations between attachment style, negative affectivity, social inhibition, and linguistic features extracted from autobiographical memory transcripts. Young adult participants (n = 61) filled out attachment and personality questionnaires, and orally reported a relationship-related memory. Memories were audio-recorded and later transcribed verbatim. Using a computerized linguistic extraction tool, positive affect words, negative affect words, and cognition words were extracted. Spearman’s rank correlation coefficients revealed that attachment anxiety was negatively correlated with cognition words (r2 = -0.26, p = 0.047) and that negative affectivity was negatively correlated with positive affect words (r2 = -0.32, p = 0.012). The findings suggest that attachment style and personality are associated with speech styles indicative of both emotionality and depth of processing. Because attachment styles, negative affectivity, and social inhibition are associated with poor mental health outcomes, analyses of key linguistics features in autobiographical memory narratives may provide reliable screening tools for mental wellbeing.

Keywords: attachment style, autobiographical memory, language, negative affectivity, social inhibition

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Authors: Ruma Rano, Firoza Sultana, Bishal Bhuyan, Nurul Alam Mazumder

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Fly ash collected from Cachar Paper Mill, Assam, India has been thoroughly characterized in respect of its physico-chemical, morphological and mineralogical features were concerned by using density, LOI, FTIR, XRD, SEM-EDS etc. The results reveal that there is a striking difference in the features and properties of the coarser and finer fractions .The high carbon ash consists of large unburnt carbon (chars), irregular carbonaceous particles in the coarser fraction, which appear to be porous and may be used as domestic fuel. The percentage of char albeit the carbon content decreases with decrease in size of particles. The various fractions essentially contain quartz and mullite as the main mineral phases. For suggesting the potential utilization channels, number of experiments were performed correlating the total characteristic features. Water holding capacities of different size classified fractions were determined, the coarser fractions have unexpectedly higher water holding capacities than the finer ones. An attempt has been made to correlate the results obtained with potential use in agriculture. Another potential application of coarser particles is used as adsorbent for effluents containing waste organic materials. Thus thorough characterization leads to not only a definite direction about the uses of the value added components but also gives useful information regarding the prevailing combustion process.

Keywords: chars, porous, water holding capacity, combustion process

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Authors: Ji Min China

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The 20th century was the century of globalization. Developed transportation and the progress of information media made the earth into a global village. The differences between regions is increasingly reduced, "cultural convergence" phenomenon intensified, regional specialties and traditional culture has been eroded. In the field of architecture, while experienced orderly rational modernism baptism, it is increasingly recognized that set the expense of cultural differences and forced to follow the universal international-style building has been outdated. At the same time, in the 21st century environmental issues has been paid more and more attention, and the concept of sustainable development and sustainable building have been proposed.This makes the domestic and foreign architects began to explore the possibilities of building and reflect local cultural characteristics of the new vernacular architecture as a viable diversified architectural tendencies by domestic and foreign architects’ favor. The author will use the production and creative process of the new vernacular architecture at home and abroad as the background, and select some outstanding examples of the analysis and discussion, then reinterpret the "new vernacular architecture" in China now. This paper will pay more attention to how to master the true meaning of the here and now "new vernacular" as well as its multiple dimensions of sustainability in the future. It also determines the paper will be a two-way aspect and multi-dimensional understanding and mining of the "new vernacular".

Keywords: new vernacular architecture, regional culture, multi dimension, sustainable

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Authors: Farnoosh Faal

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The excessive reliance on private cars has led to a range of problems, such as traffic congestion, air pollution, and carbon emissions, which have significant impacts on public health and the environment. Public open spaces have the potential to promote sustainable transportation and reduce dependence on cars by providing alternative mobility options, including walking, cycling, and public transit. This paper examines the existing research on the relationship between public open spaces and sustainable transportation. It discusses the key design principles and planning strategies that can enhance the accessibility and safety of public open spaces, particularly for pedestrians and cyclists. The paper also explores the role of public open spaces in promoting active mobility and reducing car use in urban and suburban contexts. Finally, the paper highlights the policy and institutional barriers that hinder the integration of public open spaces with sustainable transportation systems and suggests some potential solutions to overcome these barriers. Overall, the paper argues that public open spaces have immense potential to facilitate sustainable transportation and reduce car dependence, and therefore, it is important to prioritize the development and maintenance of public open spaces as a key component of sustainable urban and regional planning.

Keywords: public open space, sustainable transportation, active mobility, car dependence, urban and regional planning, traffic congestion

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Authors: Ida Zubaidah

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With the advancement of information and communication technologies, in many cases, geographical distance is no longer considered as a main barrier in distance education. Geographical distance, even from a continent to another, between students and their instructor or students and their campus can be connected by the Internet, telephone or any other means of communication technology. Managing distance learning in an archipelagic country like Indonesia, however, has some different stories. Comprising more than 17,000 islands and 6.000 of them inhabited, Indonesia is considered as one of the most archipelagic countries in the world. In some areas or islands that have adequate public transportation and communication facilities the courses can be delivered quite well. In other areas that geographically very remote and dispersed islander, Universitas Terbuka, an open university in Indonesia, has to have very different strategies in overcoming the specific and even emergency situations in learning delivery. This ongoing research paper aims to share experiences of how Universitas Terbuka makes serious and unique efforts in overcoming the barriers and obstacles in providing educational service in part of difficult areas, especially in eastern areas of Indonesia. The data collection methods are observation of sample areas and in-depth interview with the head of regional offices of Universitas Terbuka in eastern Indonesia, staff, and tutors. Conducting educational deliveries in in difficult areas with no regular and adequate transportation has made the regional office have specific strategies in making the learning process run as smooth as possible. Sending a tutor to an area to meet some students and conducting a series of tutorial, which are supposed to be weekly, in several days is one of the strategies. Recruiting local people to manage the students in the area is another strategy. The absence of regular transportation from island to island, high tides, hurricanes, are among the obstacles faced by the regional offices in doing their job. Non geographical barriers such as unavailability of qualified tutor, inadequate tutor payment, are problems as well. The learning process, however, has to be done in any way, otherwise the distance education mission to reach unreachable cannot be achieved.

Keywords: distance education, Terbuka University, difficult area, geographical barrier, learning services

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Authors: Andi Triswoyo

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The establishment of ASEAN Community 2015 was proposed to integrate concretely, in terms of regional cooperation. All of the members of the ASEAN itself compete to prepare themselves in the actual place. Regarding to the Bali Concord III, subsequently ASEAN Community was categorized by three elements, such as (1) ASEAN Political-security Community (APC), (2) ASEAN Economic Community (AEC), and (3) ASEAN Socio-cultural Community (ASC). Preparing on three components above, civil society organizations must be prioritized as the main body, which ensure grassroots society itself obtain maximum benefits or advantage of these declarations. NU, as the representative of mass-based organizations, was choose, due to the highly influences toward Moslem rural-traditionalist, which has the largest followers in Indonesia. This paper was aimed to explain the contribution of NU in developing and empowering society. Furthermore, it will use historical perspective, by looking for related data, which contain basic- knowledge and explanatory facts in literary desk. It would elaborate in NU’s urgency for promoting civil societies roles in ASEAN Community. In the ends, this paper was proposed to measure to what extend NU’s roles in promoting the Civil Society in Indonesia and its potential capability to get involved at the upcoming regional communities. Hopefully, the attempt to strengthen Civil Society Organizations (CSOs), like NU can push faster in creating good governance and democracy, toward social configurations amongst state, market and civil society.

Keywords: ASEAN community, Nahdlatul Ulama, civil society organizations(CSO), civil society

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Authors: Jeanne-Mari Retief

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As of November 2016, three African states have withdrawn from the International Criminal Court (ICC) and more are expected to follow. The alleged abuse of universal jurisdiction and targeting of African states by the ICC motivated the withdrawals. These historical exits raise many questions, especially in regard to the adequate investigation and prosecution of international crimes in a continent with a history of impunity. Even though African courts exist and one more is proposed, many issues remain i.e. adequate access to the courts, the extent of the courts’ jurisdiction, and proposed methods of effectively dealing with international crimes in Africa. This paper seeks to address the practical effects of the withdrawal from the ICC and the problems posed through utilizing regional courts. It will specifically look at the practical challenges existing courts face, the lack of access to the latter, issues concerning the proposed African Court for Justice and Human Rights, and the shocking promotion of impunity in Africa. These all have severe implications for African citizens and victims of the most heinous crimes. The mantra of African solutions to African problems places an important duty on states to ensure the actual provision of these solutions, which can only be achieved through a critical analysis of the questions above.

Keywords: ACJHR, Africa, impunity, justice, Malabo protocol

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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: M. Elham Ghabouli

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Intermediate cities which also called medium size cities have an important role in the process of globalization. It is argued that, in some cases this type of cities may be depopulated or in otherwise may be transformed as the periphery of metropolitans so that the personal identity of the city and its local cultural heritage could suffer from its neighbor metropolitan. Over the last decades, the role of tourism in development process and the cultural heritage is increased. The effect of tourism in socio-economic growth makes motivation for study on tourism development in regional and urban planning process. Tourism potentially has a specific role in promoting sustainable development especially by its economic and socio-cultural effects. The positive role of tourism in local development and in cultural heritage should be empowered by urban and regional planning. Damavand is an intermediate city located in Tehran province, Iran. Considering its local specific characteristic like social structure, antiquities and natural monuments made a suitable case study for studying on urban tourism planning method. Focusing on recognition of historical and cultural heritage of Damavand, this paper tried to peruse cultural-historical heritage protecting issue through “base plan methodology” which is introduced as a first step of urban planning for intermediate cities.

Keywords: urban planning, tourism, cultural heritage, intermediate cities

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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: 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: Ana Pego

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Environmental technologies were developed for decades. Clean technologies emerged a few years ago. In these perspectives, the use of cleantech technologies has become very important due the fact of new era of environmental feats. As such, the market itself has become more competitive, more collaborative towards a better use of clean technologies. This paper shows the importance of clean technologies in offshore energy sector in Portuguese market, its localization and its impact on economy. Clean technologies are directly related with renewable cluster and concomitant with economic and social resource optimization criteria, geographic aspects, climate change and soil features. Cleantech is related with regional development, socio-technical transitions in organisations. There are an economical and social combinations which allow specialisation of regions in activities, higher employment, reduce of energy costs, local knowledge spillover and, business collaboration and competitiveness. The methodology used will be quantitative (IO matrix for Portugal 2013) and qualitative (questionnaires to stakeholders). The mix of both methodologies will confirm whether the use of technologies will allow a positive impact on economic and social variables used on this model. It is expected a positive impact on Portuguese economy both in investment and employment taking in account the localization of offshore renewable activities. This means that the importance of offshore renewable investment in Portugal has a few points which should be pointed out: the increase of specialised employment, localization of specific activities in territory, and increase of value added in certain regions. The conclusion will allow researchers and organisation to compare the Portuguese model to other European regions in order to a better use of natural and human resources.

Keywords: cleantech, economic impact, localisation, territory dynamics

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Authors: Se-Hwa Park, En-Kyung Han, Jae-Young Lim, Hye-Jung Ahn

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Purpose: The objective of this study is to provide basic data for understanding the substance of inpatient life with CRPS (Complex Regional Pain Syndrome) and developing efficient and effective nursing intervention. Methods: From September 2018 to November, we have interviewed 10 CRPS patients about inpatient experiences. To understand the implication of inpatient life experiences with CRPS and intrinsic structure, we have used the question: 'How about the inpatient experiences with CRPS'. For data analysis, the method suggested by Colaizzi was applied as a phenomenological method. Results: According to the analysis, the study participants' inpatient life process was structured in six categories: (a) breakthrough pain experience (b) the limitation of pain treatment, (c) worsen factors of pain during inpatient period, (d) treat method for pain, (e) positive experience for inpatient period, (f) requirements for medical team, family and people in hospital room. Conclusion: Inpatient with CRPS have experienced the breakthrough pain. They had expected immediate treatment for breakthrough pain, but they experienced severe pain because immediate treatment was not implemented. Pain-worsening factors which patients with CRPS are as follows: personal factors from negative emotions such as insomnia, stress, sensitive character, pain part touch or vibration stimulus on the bed, physical factors from high threshold or rapid speed during fast transfer, conflict with other people, climate factors such as humidity or low temperature, noise, smell, lack of space because of many visitors. Patients actively manage the pain committing into another tasks or diversion. And also, patients passively manage the pain, just suppress, give-up. They think positively about rehabilitation treatment. And they require the understanding and sympathy for other people, and emotional support, immediate intervention for medical team. Based on the results of this study, we suppose the guideline of systematic breakthrough pain management for the relaxation of sudden pain, using notice of informing caution for touch or vibration. And we need to develop non-medicine pain management nursing intervention.

Keywords: breakthrough pain, CRPS, complex regional pain syndrome, inpatient life experiences, phenomenological method

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Authors: Jan Muhammad, Saad Malik, Fadia W. Al-Azawi, Ali Imran

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In the era of climate variability, rising temperatures are the most significant aspect. In this study PRECIS model data and observed data are used for assessing the temperature change scenarios of Sindh province during the first half of present century. Observed data from various meteorological stations of Sindh are the primary source for temperature change detection. The current scenario (1961–1990) and the future one (2010-2050) are acted by the PRECIS Regional Climate Model at a spatial resolution of 25 * 25 km. Regional Climate Model (RCM) can yield reasonably suitable projections to be used for climate-scenario. The main objective of the study is to map the simulated temperature as obtained from climate model-PRECIS and their comparison with observed temperatures. The analysis is done on all the districts of Sindh in order to have a more precise picture of temperature change scenarios. According to results the temperature is likely to increases by 1.5 - 2.1°C by 2050, compared to the baseline temperature of 1961-1990. The model assesses more accurate values in northern districts of Sindh as compared to the coastal belt of Sindh. All the district of the Sindh province exhibit an increasing trend in the mean temperature scenarios and each decade seems to be warmer than the previous one. An understanding of the change in temperatures is very vital for various sectors such as weather forecasting, water, agriculture, and health, etc.

Keywords: PRECIS Model, real observed data, Arc GIS, interpolation techniques

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Authors: Olumide A. Fafore, Khondlo Mtshali

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The beginning of the 21st century saw the emergence of new and global threats to national and transnational security in West Africa and the Asia Pacific regions as a result of the spread of jihadist terrorism across borders, a manifestation of the rise of radical Islam. Extremist and armed Islamic movements influenced by Salafism, the Jihad in Afghanistan and the Muslim Brotherhood are prevalent in Northern Nigeria, Niger, Cameroon, Mali, Chad, Pakistan, Afghanistan, and India. Carrying out attacks across borders, including assassinations, murders, armed robberies, and kidnapping, assisted by open and porous borders and large flow of illegal immigrants across borders. This paper examines the effect of Radical Islam on Transnational security through a review of past literature and the social and security consequences on the people of the regions. Our findings indicate that the activities of armed Islamic movements such as Boko Haram, Ansaru and Al-Qaeda are having a negative impact on the economy, development, and security of the states and people of West Africa and the Asia Pacific. It stresses the importance of regional, transnational and international cooperation, as these threats to national and transnational security can no longer be solved in a national or regional framework.

Keywords: Islamic movements, jihadist terrorism, radical Islam, transnational security

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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: 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: 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: Tanmay Bisen, Aastha Shayla

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This study introduces an advanced approach to tree canopy detection in urban environments and a regional analysis of Northern and Central Kolkata that delves into the intricate relationship between urban development and environmental conservation. Leveraging high-resolution drone imagery from diverse urban green spaces in Kolkata, we fine-tuned the deep forest model to enhance its precision and accuracy. Our results, characterized by an impressive Intersection over Union (IoU) score of 0.90 and a mean average precision (mAP) of 0.87, underscore the model's robustness in detecting and classifying tree crowns amidst the complexities of aerial imagery. This research not only emphasizes the importance of model customization for specific datasets but also highlights the potential of drone-based remote sensing in urban forestry studies. The study investigates the spatial distribution, density, and environmental impact of trees in Northern and Central Kolkata. The findings underscore the significance of urban green spaces in met-ropolitan cities, emphasizing the need for sustainable urban planning that integrates green infrastructure for ecological balance and human well-being.

Keywords: urban greenery, advanced spatial distribution analysis, drone imagery, deep learning, tree detection

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Authors: Yohannes Haile, Dipo Onipede, Jr., Omar Ashour

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The main thrust of our research is to determine Industry 4.0 readiness of small and mid-size manufacturing companies in our region and assist them to implement Cyber Physical Production System (CPPS) capabilities. Adopting CPPS capabilities will help organizations realize improved quality, order delivery, throughput, new value creation, and reduced idle time of machines and work centers of their manufacturing operations. The key metrics for the assessment include the level of intelligence, internal and external connections, responsiveness to internal and external environmental changes, capabilities for customization of products with reference to cost, level of additive manufacturing, automation, and robotics integration, and capabilities to manufacture hybrid products in the near term, where near term is defined as 0 to 18 months. In our initial evaluation of several manufacturing firms which are profitable and successful in what they do, we found low level of Physical-Digital-Physical (PDP) loop in their manufacturing operations, whereas 100% of the firms included in this research have specialized manufacturing core competencies that have differentiated them from their competitors. The level of automation and robotics integration is low to medium range, where low is defined as less than 30%, and medium is defined as 30 to 70% of manufacturing operation to include automation and robotics. However, there is a significant drive to include these capabilities at the present time. As it pertains to intelligence and connection of manufacturing systems, it is observed to be low with significant variance in tying manufacturing operations management to Enterprise Resource Planning (ERP). Furthermore, it is observed that the integration of additive manufacturing in general, 3D printing, in particular, to be low, but with significant upside of integrating it in their manufacturing operations in the near future. To hasten the readiness of the local and regional manufacturing companies to Industry 4.0 and transitions towards CPPS capabilities, our working group (ADMAR Working Group) in partnership with our university have been engaged with the local and regional manufacturing companies. The goal is to increase awareness, share know-how and capabilities, initiate joint projects, and investigate the possibility of establishing the Center for Cyber Physical Production Systems Innovation (C2P2SI). The center is intended to support the local and regional university-industry research of implementing intelligent factories, enhance new value creation through disruptive innovations, the development of hybrid and data enhanced products, and the creation of digital manufacturing enterprises. All these efforts will enhance local and regional economic development and educate students that have well developed knowledge and applications of cyber physical manufacturing systems and Industry 4.0.

Keywords: automation, cyber-physical production system, digital manufacturing enterprises, disruptive innovation, new value creation, physical-digital-physical loop

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

Abstract:

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: Christopher Meyer, Laima Gerlitz

Abstract:

European ports are facing high political pressure through the implementation of initiatives such as the European Green Deal or IMO's 2030 targets (Fit for 55). However, small and medium-sized ports face even higher challenges compared to bigger ones due to lower capacities in various fields such as investments, infra-structure, Human Resources, and funding opportunities. Small and Medium-Sized Ports (SMPs) roles in economic systems are various depending on their specific functionality in maritime ecosystems. Depending on their different situations, being an actor in multiport gateways, aligned to core ports, regional nodes in peripheries for the hinterland, specialized cluster members, or logistical nodes, different strategic business models may be applied to increase SMPs' competitiveness among other bigger ports. Additionally, SMPs are facing more challenges for future development in terms of digital and green transition of their operations. Thus, it is necessary to evaluate the own strategical position and apply management strategies alongside the regional growth and innovation strategies for diversification or specialisation of own port businesses. The research uses inductive perspectives to set up a transferable framework based on case studies to be analysed. In line with particular research and document analysis, qualitative approaches were considered. The research is based on a deep literature review on SMPs as well as theories on diversification and specialisation. Existing theories from different fields are evaluated on their application for the port sector and these specific maritime actors, paying respect to enabling innovation incorporation to enhance digital and environmental transition with fu-ture perspectives for SMPs. The paper aims to provide a decision-making matrix for the strategic positioning of SMPs in Europe, including opportunities to get access to particular EU funds for future development alongside the Regional In-novation Strategies on Smart Specialisation.

Keywords: strategic planning, sustainability transition, competitiveness portfolio, EU green deal

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Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi

Abstract:

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

Abstract:

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

Procedia PDF Downloads 94