Search results for: case citation network

Authors: V. Samulionis, J. Banys, A. Sánchez-Ferrer

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Inorganic nanoparticles are used for fabrication of various composites based on polymer materials because they exhibit a good homogeneity and solubility of the composite material. Multifunctional materials based on composites of a polymer containing inorganic nanotubes are expected to have a great impact on industrial applications in the future. An emerging family of such composites are polyurea elastomers with inorganic MoS2 nanotubes or MoSI nanowires. Polyurea elastomers are a new kind of materials with higher performance than polyurethanes. The improvement of mechanical, chemical and thermal properties is due to the presence of hydrogen bonds between the urea motives which can be erased at high temperature softening the elastomeric network. Such materials are the combination of amorphous polymers above glass transition and crosslinkers which keep the chains into a single macromolecule. Polyurea exhibits a phase separated structure with rigid urea domains (hard domains) embedded in a matrix of flexible polymer chains (soft domains). The elastic properties of polyurea can be tuned over a broad range by varying the molecular weight of the components, the relative amount of hard and soft domains, and concentration of nanoparticles. Ultrasonic methods as non-destructive techniques can be used for elastomer composites characterization. In this manner, we have studied the temperature dependencies of the longitudinal ultrasonic velocity and ultrasonic attenuation of these new polyurea elastomers and composites with inorganic nanoparticles. It was shown that in these polyurea elastomers large ultrasonic attenuation peak and corresponding velocity dispersion exists at 10 MHz frequency below room temperature and this behaviour is related to glass transition Tg of the soft segments in the polymer matrix. The relaxation parameters and Tg depend on the segmental molecular weight of the polymer chains between crosslinking points, the nature of the crosslinkers in the network and content of MoS2 nanotubes or MoSI nanowires. The increase of ultrasonic velocity in composites modified by nanoparticles has been observed, showing the reinforcement of the elastomer. In semicrystalline polyurea elastomer matrices, above glass transition, the first order phase transition from quasi-crystalline to the amorphous state has been observed. In this case, the sharp ultrasonic velocity and attenuation anomalies were observed near the transition temperature TC. Ultrasonic attenuation maximum related to glass transition was reduced in quasicrystalline polyureas indicating less influence of soft domains below TC. The first order phase transition in semicrystalline polyurea elastomer samples has large temperature hysteresis (> 10 K). The impact of inorganic MoS2 nanotubes resulted in the decrease of the first order phase transition temperature in semicrystalline composites.

Keywords: inorganic nanotubes, polyurea elastomer composites, ultrasonic velocity, ultrasonic attenuation

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Authors: Martabolette Stecher

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Introductory: How is knowledge and ability to act on employable opportunities constructed among students and graduates at higher educations? This question have been drawn much attention by researchers, governments and universities in Denmark, since there has been an increases in the rate of unemployment among graduates from higher education. The fact that more than ten thousand graduates from higher education without the opportunity to get a job in these years has a tremendous impact upon the social economy in Denmark. Every time a student graduate from higher education and become unemployed, it is possible to trace upon the person´s chances to get a job many years ahead. This means that the tremendous rate of graduate unemployment implies a decrease in employment and lost prosperity in Denmark within a billion Danish Kroner scale. Basic methodologies: The present study investigates the construction of knowledge and ability to act upon employable opportunities among students and graduates at higher educations in Denmark in a literature review as well as a preliminary study of students from Aarhus University. 15 students from the candidate of drama have been engaging in an introductory program at the beginning of their candidate study, which included three workshops focusing upon the more personal matters of their studies and life. They have reflected upon this process during the intervention and afterwards in a semi-structured interview. Concurrently a thorough literature review has delivered key concepts for the exploration of the research question. Major findings of the study: It is difficult to find one definition of what employability encompasses, hence the overall picture of how to incorporate the concept is difficult. The present theory of employability has been focusing upon the competencies, which students and graduates are going to develop in order to become employable. In recent years there has been an emphasis upon the mechanism which supports graduates to trust themselves and to develop their self-efficacy in terms of getting a sustainable job. However, there has been little or no focus in the literature upon the idea of how students and graduates from higher education construct knowledge about and ability to act upon employable opportunities involving network of actors both material and immaterial network and meaningful relations for students and graduates in developing their enterprising behavior to achieve employment. The Act-network-theory combined with theory of entrepreneurship education suggests an alternative strategy to focus upon when explaining sustainable ways of creating employability among graduates. The preliminary study also supports this theory suggesting that it is difficult to emphasize a single or several factors of importance rather highlighting the effect of a multitude network. Concluding statement: This study is the first step of a ph.d.-study investigating this problem in Denmark and the USA in the period 2015 – 2019.

Keywords: employablity, graduates, action, opportunities

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Authors: Taus Muganda

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This research explores the intricate relationship between e-procurement adoption and effective service delivery in the Uganda Coffee Industry, focusing on the processes involved, key actors, and the impact of digital transformation. The study is guided by three prominent theories, Actor-Network Theory, Resource-Based View Theory, and Institutional Theory to comprehensively explore the dynamics of e-procurement in the context of the coffee sector. The primary aim of this project is to examine the e-procurement adoption process and its role in enhancing service delivery within the Uganda Coffee Industry. The research questions guiding this inquiry are: firstly, whether e-procurement adoption and implementation contribute to achieving quality service delivery; and secondly, how e-procurement adoption can be effectively realized within the Uganda Coffee Industry. To address these questions, the study has laid out specific objectives. Firstly, it seeks to investigate the impact of e-procurement on effective service delivery, analysing how the integration of digital processes influences the overall quality of services provided in the coffee industry. Secondly, it aims to critically analyse the measures required to achieve effective delivery outcomes through the adoption and implementation of e-procurement, assessing the strategies that can maximize the benefits of digital transformation. Furthermore, the research endeavours to identify and examine the key actor’s instrumental in achieving effective service delivery within the Uganda Coffee Industry. By utilizing Actor-Network Theory, the study will elucidate the network of relationships and collaborations among actors involved in the e-procurement process. The research contributes to addressing a critical gap in the sector. Despite coffee being the leading export crop in Uganda, constituting 16% of total exports, there is a recognized need for digital transformation, specifically in the realm of e-procurement, to enhance the productivity of producers and contribute to the economic growth of the country. The study aims to provide insights into transforming the Uganda Coffee Industry by focusing on improving the e-procurement services delivered to actors in the coffee sector. The three forms of e-procurement investigated in this research—E-Sourcing, E-Payment, and E-Invoicing—serve as focal points in understanding the multifaceted dimensions of digital integration within the Uganda Coffee Industry. This research endeavours to offer practical recommendations for policymakers, industry stakeholders, and the UCDA to strategically leverage e-procurement for the benefit of the entire coffee value chain.

Keywords: e-procurement, effective service delivery, actors, actor-network theory, resource-based view theory, institutional theory, e-invocing, e-payment, e-sourcing

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Authors: Swarnali Chakma, Akihiko Hokugo

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Research on three case studies reviewed here explains many aspects and complications of evacuation behavior during an emergency period. The scenario and phenomenon of the disaster were different, but the similarities are that after receiving the warning peoples does not take it seriously. Many individuals evacuated after taking some kind of action, for example; return to home, searching for family members, prepared valuable things etc. Based on a review of the literature, the data identified a number of factors that help explain evacuation behavior during the disaster. In the case of Japan, cultural inhibitors impact people’s behavior; for example, following the traffic rules, some people lost their time to skip because of the slow-moving car makes overcrowded traffic and some of them were washed away by the tsunami. In terms of Bangladeshi culture, women did not want to evacuate without men because staying men and women who do not know each other under the same roof together is not regular practice or comfortable. From these three case studies, it is observed that early warning plays an important role in cyclones, typhoons and earthquakes. A high level of trust from residents in the warning system is important to real evacuation. It is necessary to raise awareness of disaster and provide information on the vulnerability to cyclones, typhoons and earthquakes hazards at community levels. The local level may help decision makers and other stakeholders to make a better decision regarding an effective disaster management.

Keywords: disaster management, emergency period, evacuation, shelter, typhoon

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Authors: Bowen Ding, Yihao Kuang

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In recent years, with the development of large-scale pre-trained lan-guage models, building vector representations of text through deep neural network models has become a standard practice for natural language processing tasks. From the performance on downstream tasks, we can know that the text representation constructed by these models contains linguistic information, but its encoding mode and extent are unclear. In this work, a structural probe is proposed to detect whether the vector representation produced by a deep neural network is embedded with a syntax tree. The probe is trained with the deep metric learning method, so that the distance between word vectors in the metric space it defines encodes the distance of words on the syntax tree, and the norm of word vectors encodes the depth of words on the syntax tree. The experiment results on ELMo and BERT show that the syntax tree is encoded in their parameters and the word representations they produce.

Keywords: deep metric learning, syntax tree probing, natural language processing, word representations

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Authors: Zhou Mo, Dennis Chow

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In the dynamic positioning system (DPS) for vessels, the reliable information transmission between each note basically relies on the wireless protocols. From the perspective of cluster-based routing protocols for wireless sensor networks, the data fusion technology based on the sleep scheduling mechanism and remaining energy in network layer is proposed, which applies the sleep scheduling mechanism to the routing protocols, considering the remaining energy of node and location information when selecting cluster-head. The problem of uneven distribution of nodes in each cluster is solved by the Equilibrium. At the same time, Classified Forwarding Mechanism as well as Redelivery Policy strategy is adopted to avoid congestion in the transmission of huge amount of data, reduce the delay in data delivery and enhance the real-time response. In this paper, a simulation test is conducted to improve the routing protocols, which turn out to reduce the energy consumption of nodes and increase the efficiency of data delivery.

Keywords: DPS for vessel, wireless sensor network, data fusion, routing protocols

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Authors: Abdullah Almalky, Colin Evers

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Gifted individuals in rural areas may lack access and opportunities compared with urban students. This case study research provides research-based evidence to identify the professional needs of principals running rural schools with gifted education (GE) programs. The data were obtained from diverse cases (high-performing [HP] and low-performing [LP] schools) by conducting interviews with principals and teachers, conducting focus groups with gifted students, and analyzing policy documents. The findings reveal a lack of knowledge among principals in relation to GE. However, HP schools were more concerned with the needs of gifted students compared with LP schools. In addition, principals of HP schools were mostly instructional leaders, whereas LP schools were mostly led by building managers. Therefore, the study recommends a revision of GE policy in Saudi Arabia and urges ministries of education and universities to consider including GE in principals’ and teachers’ preparation programs to better serve gifted students in schools.

Keywords: gifted, Saudi Arabia, leadership, policy, rural education, case study, interview

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Authors: Hamdi Amroun, Yacine Benziani, Mehdi Ammi

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In this paper, we want to determine whether the accurate prediction of nicotine concentration can be obtained by using a network of smart objects and an e-cigarette. The approach consists of, first, the recognition of factors influencing smoking cessation such as physical activity recognition and participant’s behaviors (using both smartphone and smartwatch), then the prediction of the configuration of the e-cigarette (in terms of nicotine concentration, power, and resistance of e-cigarette). The study uses a network of commonly connected objects; a smartwatch, a smartphone, and an e-cigarette transported by the participants during an uncontrolled experiment. The data obtained from sensors carried in the three devices were trained by a Long short-term memory algorithm (LSTM). Results show that our LSTM-based model allows predicting the configuration of the e-cigarette in terms of nicotine concentration, power, and resistance with a root mean square error percentage of 12.9%, 9.15%, and 11.84%, respectively. This study can help to better control consumption of nicotine and offer an intelligent configuration of the e-cigarette to users.

Keywords: Iot, activity recognition, automatic classification, unconstrained environment

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Authors: Keigo Ide, Toru Maruyama, Michihiro Ito, Hiroyuki Fujimura, Yoshikatu Nakano, Shoichiro Suda, Sachiyo Aburatani, Haruko Takeyama

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Understanding environmental system is one of the important tasks. In recent years, conservation of coral environments has been focused for biodiversity issues. The damage of coral reef under environmental impacts has been observed worldwide. However, the casual relationship between damage of coral and environmental impacts has not been clearly understood. On the other hand, structure/diversity of marine bacterial community may be relatively robust under the certain strength of environmental impact. To evaluate the coral environment conditions, it is necessary to investigate relationship between marine bacterial composition in coral reef and environmental factors. In this study, the Time Scale Network Analysis was developed and applied to analyze the marine environmental data for investigating the relationship among coral, bacterial community compositions and environmental factors. Seawater samples were collected fifteen times from November 2014 to May 2016 at two locations, Ishikawabaru and South of Sesoko in Sesoko Island, Okinawa. The physicochemical factors such as temperature, photosynthetic active radiation, dissolved oxygen, turbidity, pH, salinity, chlorophyll, dissolved organic matter and depth were measured at the coral reef area. Metagenome and metatranscriptome in seawater of coral reef were analyzed as the biological factors. Metagenome data was used to clarify marine bacterial community composition. In addition, functional gene composition was estimated from metatranscriptome. For speculating the relationships between physicochemical and biological factors, cross-correlation analysis was applied to time scale data. Even though cross-correlation coefficients usually include the time precedence information, it also included indirect interactions between the variables. To elucidate the direct regulations between both factors, partial correlation coefficients were combined with cross correlation. This analysis was performed against all parameters such as the bacterial composition, the functional gene composition and the physicochemical factors. As the results, time scale network analysis revealed the direct regulation of seawater temperature by photosynthetic active radiation. In addition, concentration of dissolved oxygen regulated the value of chlorophyll. Some reasonable regulatory relationships between environmental factors indicate some part of mechanisms in coral reef area.

Keywords: coral environment, marine microbiology, network analysis, omics data analysis

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Authors: Shadi Fathi, Moura Mehravar, Mujib Rahman

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The railwaytransportation network in the UK is over 100 years old and is known as one of the oldest mass transit systems in the world. This aged track network requires frequent closure for maintenance. One of the main reasons for closure is inadequate drainage due to the leakage in the buried drainage pipes. The leaking water can cause localised subgrade weakness, which subsequently can lead to major ground/substructure failure.Different condition assessment methods are available to assess the railway substructure. However, the existing condition assessment methods are not able to detect any local ground weakness/damageand provide details of the damage (e.g. size and location). To tackle this issue, a hybrid back-analysis technique based on artificial neural network (ANN) and genetic algorithm (GA) has been developed to predict the substructurelayers’ moduli and identify any soil weaknesses. At first, afinite element (FE) model of a railway track section under Falling Weight Deflection (FWD) testing was developed and validated against field trial. Then a drainage pipe and various scenarios of the local defect/ soil weakness around the buried pipe with various geometriesand physical properties were modelled. The impact of the soil local weaknesson the track surface deflection wasalso studied. The FE simulations results were used to generate a database for ANN training, and then a GA wasemployed as an optimisation tool to optimise and back-calculate layers’ moduli and soil weakness moduli (ANN’s input). The hybrid ANN-GA back-analysis technique is a computationally efficient method with no dependency on seed modulus values. The modelcan estimate substructures’ layer moduli and the presence of any localised foundation weakness.

Keywords: finite element (FE) model, drainage defect, falling weight deflectometer (FWD), hybrid ANN-GA

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Authors: Mustafa Alhamdi

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Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

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Authors: Zachary Pan

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Our general mission is to solve the problem of classifying images into different body part types and deciding if each of them is healthy or not. However, for now, we will determine healthiness for only one-sixth of the body parts, specifically the chest. We will detect pneumonia in X-ray scans of those chest images. With this type of AI, doctors can use it as a second opinion when they are taking CT or X-ray scans of their patients. Another ad-vantage of using this machine learning classifier is that it has no human weaknesses like fatigue. The overall ap-proach to this problem is to split the problem into two parts: first, classify the image, then determine if it is healthy. In order to classify the image into a specific body part class, the body parts dataset must be split into test and training sets. We can then use many models, like neural networks or logistic regression models, and fit them using the training set. Now, using the test set, we can obtain a realistic accuracy the models will have on images in the real world since these testing images have never been seen by the models before. In order to increase this testing accuracy, we can also apply many complex algorithms to the models, like multiplicative weight update. For the second part of the problem, to determine if the body part is healthy, we can have another dataset consisting of healthy and non-healthy images of the specific body part and once again split that into the test and training sets. We then use another neural network to train on those training set images and use the testing set to figure out its accuracy. We will do this process only for the chest images. A major conclusion reached is that convolutional neural networks are the most reliable and accurate at image classification. In classifying the images, the logistic regression model, the neural network, neural networks with multiplicative weight update, neural networks with the black box algorithm, and the convolutional neural network achieved 96.83 percent accuracy, 97.33 percent accuracy, 97.83 percent accuracy, 96.67 percent accuracy, and 98.83 percent accuracy, respectively. On the other hand, the overall accuracy of the model that de-termines if the images are healthy or not is around 78.37 percent accuracy.

Keywords: body part, healthcare, machine learning, neural networks

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Authors: Monjur E-Khoda Tarafdar

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Institutional autonomy and academic freedom corresponding to accountability are seen as a core concept of university governance. Universities are crucial factors in search of truth for knowledge production and dissemination. Academic leaders are the pivots to progressively influence the university governance. Therefore, in a continuum of debate about autonomy and accountability in the aspect of perception, academic leadership has been studied. Having longstanding acquaintance in the field the researcher has been instrumental to gain lived experiences of the informants in this qualitative study. Case studies are useful to gain an understanding of the complexities of a particular site to preserve a sense of wholeness of the site being investigated. Thus, multiple case study approach has been employed with a sample size of seventy-one. Such large size of informants was interviewed in order to capture a wider range of views that exist in Bangladesh. This qualitative multiple case study has engaged in-depth interviewing method of academic leaders and policy makers of three case universities. Open-ended semi-structured questionnaires are used to have a comprehensive understanding of how the perception of autonomy and accountability of academic leaders has impacted university governance in the context of Bangladesh. The paper has interpreted the voices of the informants and distinguished both the transformational and transactional style of academic leaderships in local university settings against the globally changed higher education demography. The study finds contextual dissimilarity in the perspectives of autonomy and accountability of academic leadership towards university governance. Unaccountability results in losing autonomous power and collapsing academic excellence. Since accountability grows competitiveness and competence, the paper also focuses on how academic leaders abuse the premise of academic loyalty to universities.

Keywords: academic loyalty, accountability, autonomy, leadership, perception, university governance

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Authors: Aaidha Hammad

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The age a child to be exposed to a second language is a controversial issue in communities such as the Maldives where English is taught as a second language. It has been observed that different stakeholders have different viewpoints towards the issue. Some believe that the earlier children are exposed to a second language, the better they learn, while others disagree with the notion. Hence, this case study investigates whether children learn a second language better when they are exposed at an earlier age or not. The spoken and written data collected confirm that earlier exposure helps in mastering the sound pattern and speaking fluency with more native-like accent, while a later age is better for learning more abstract and concrete aspects such as grammar and syntactic rules.

Keywords: age, fluency, second language acquisition, development of language skills

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Authors: Haiping Zhu

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The purpose of this work-in-progress paper is to explore how the Chinese philosophic-religious tradition of Taoism impacts on the consumption behaviour of contemporary Chinese consumers. Although much cultural research has been conducted on Chinese consumption behaviours, most studies have approached the subject from Western perspectives. Examination of the limited literature indicates a gap in the knowledge of the relationship of traditional Chinese Taoism philosophy and Chinese consumption behaviour. To bridge this gap, this study examines Chinese consumption behaviour at a Taoist-related Chinese religious festival - the DuanWu festival - in order to seek some understanding of how the Taoism philosophic-religious tradition influences Chinese consumption behaviour from the point of view of the individuals involved. It focuses attention on their expression of Taoism cultural values, purchasing experience and subsequent consumption behaviours. This study undertook multiple methods for Taoist case study data collection: accompanied shopping with Taoists before DuanWu Festival; participant observations during DuanWu Festival; and in-depth interviews in order to explore Taoists consumption behaviours at the end of the Festival. Specifically, the finding from the Taoist case study corroborates and details the influence of the Taoism doctrine: man–nature orientation, Fenshui, ecological effect, and ecological knowledge, on their attitudes toward green purchasing behaviour. Findings from this Taoist case study - one of a series of three Chinese philosophic religious tradition case studies - contribute to the deeper understanding of contemporary Chinese consumers from a non-Western viewpoint and offer initial insights for global marketers to differentiate consumer needs and develop effective marketing strategies.

Keywords: consumer behaviour, culture values, green purchase behaviour, Taoism

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Authors: Yasmin Nanabhay

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The paper scrutinizes the literature on accountability and non-accountability, and then presents an analysis of a South African case which demonstrated consequences of a lack of accountability. Ethical conduct displayed by members of the public sector is integral to creating a sustainable democratic government, which upholds the constitutional tenets of accountability, transparency and professional ethicality. Furthermore, a true constitutional democracy emphasises and advocates the notion of service leadership that nurtures public participation and engages with citizens in a positive manner. Ethical conduct and accountability in the public sector earns public trust; hence these are key principles in good governance. Yet, in the years since the advent of democracy in South Africa, the government has been plagued by rampant corruption and mal-administration by public officials and politicians in leadership positions. The control measures passed by government in an attempt to ensure ethicality and accountability within the public sector include codes of ethics, rules of conduct and the enactment of legislation. These are intended to shape the mindset of members of the public sector, with the ultimate aim of an efficient, effective, ethical, responsive and accountable public service. The purpose of the paper is to analyse control systems and accountability within the public sector and to present reasons for non-accountability by means of a selected case study. The selected case study is the corruption trial of Jackie Selebi, who served as National Commissioner of the South African Police Service but was dismissed from the post. The reasons for non-accountability in the public sector as well as recommendations based on the findings to enhance accountability will be undertaken. The case study demonstrates the experience and impact of corruption and/or mal-administration, as a result of a lack of accountability, which has contributed to the increasing loss of confidence in political leadership in the country as elsewhere in the world. The literature is applied to the erstwhile National Commissioner of the South African Police Service and President of Interpol, as a case study of non-accountability.

Keywords: corruption, internal control, maladministration, non-compliance, oversight mechanisms, public accountability, public sector

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Authors: Han Xue, Zhang Lanyue

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In order to seek more effective feature extraction technology, feature extraction method based on MFCC combined with vector hydrophone is exposed in the paper. The sound pressure signal and particle velocity signal of two kinds of ships are extracted by using MFCC and its evolution form, and the extracted features are fused by using fisher-ratio and correlated distance criterion. The features are then identified by BP neural network. The results showed that MFCC, First-Order Differential MFCC and Second-Order Differential MFCC features can be used as effective features for recognition of underwater targets, and the fusion feature can improve the recognition rate. Moreover, the results also showed that the recognition rate of the particle velocity signal is higher than that of the sound pressure signal, and it reflects the superiority of vector signal processing.

Keywords: vector information, MFCC, differential MFCC, fusion feature, BP neural network

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Authors: Kouzi Katia

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This paper proposes a Direct Torque Control (DTC) algorithm of dual Stator Induction Motor (DSIM) drive using two approach intelligent techniques: Artificial Neural Network (ANN) approach replaces the switching table selector block of conventional DTC and Mamdani Fuzzy Logic controller (FLC) is used for stator resistance estimation. The fuzzy estimation method is based on an online stator resistance correction through the variations of stator current estimation error and its variation. The fuzzy logic controller gives the future stator resistance increment at the output. The main advantage of suggested algorithm control is to reduce the hardware complexity of conventional selectors, to avoid the drive instability that may occur in certain situation and ensure the tracking of the actual of the stator resistance. The effectiveness of the technique and the improvement of the whole system performance are proved by results.

Keywords: artificial neural network, direct torque control, dual stator induction motor, fuzzy logic estimator, switching table

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Authors: Zsolt János Viharos, Krisztián Balázs Kis, Imre Paniti, Gábor Belső, Péter Németh, János Farkas

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The paper presents the results and industrial applications in the production setup period estimation based on industrial data inherited from the field of polymer cutting. The literature of polymer cutting is very limited considering the number of publications. The first polymer cutting machine is known since the second half of the 20th century; however, the production of polymer parts with this kind of technology is still a challenging research topic. The products of the applying industrial partner must met high technical requirements, as they are used in medical, measurement instrumentation and painting industry branches. Typically, 20% of these parts are new work, which means every five years almost the entire product portfolio is replaced in their low series manufacturing environment. Consequently, it requires a flexible production system, where the estimation of the frequent setup periods' lengths is one of the key success factors. In the investigation, several (input) parameters have been studied and grouped to create an adequate training information set for an artificial neural network as a base for the estimation of the individual setup periods. In the first group, product information is collected such as the product name and number of items. The second group contains material data like material type and colour. In the third group, surface quality and tolerance information are collected including the finest surface and tightest (or narrowest) tolerance. The fourth group contains the setup data like machine type and work shift. One source of these parameters is the Manufacturing Execution System (MES) but some data were also collected from Computer Aided Design (CAD) drawings. The number of the applied tools is one of the key factors on which the industrial partners’ estimations were based previously. The artificial neural network model was trained on several thousands of real industrial data. The mean estimation accuracy of the setup periods' lengths was improved by 30%, and in the same time the deviation of the prognosis was also improved by 50%. Furthermore, an investigation on the mentioned parameter groups considering the manufacturing order was also researched. The paper also highlights the manufacturing introduction experiences and further improvements of the proposed methods, both on the shop floor and on the quotation preparation fields. Every week more than 100 real industrial setup events are given and the related data are collected.

Keywords: artificial neural network, low series manufacturing, polymer cutting, setup period estimation

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Authors: Justin Reverdi, Sixin Zhang, Saïd Aoues, Fabrice Gamboa, Serge Gratton, Thomas Pellegrini

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In vapor cycle systems, the mass flow sensor plays a key role for different monitoring and control purposes. However, physical sensors can be inaccurate, heavy, cumbersome, expensive, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor, based on other standard sensors, is a good alternative. This paper has two main objectives. Firstly, a data-driven model using a convolutional neural network is proposed to estimate the mass flow of the compressor. We show that it significantly outperforms the standard polynomial regression model (thermodynamic maps) in terms of the standard MSE metric and engineer performance metrics. Secondly, a semi-automatic segmentation method is proposed to compute the engineer performance metrics for real datasets, as the standard MSE metric may pose risks in analyzing the dynamic behavior of vapor cycle systems.

Keywords: deep learning, convolutional neural network, vapor cycle system, virtual sensor

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Authors: Satoshi Furukawa, Satomu Morita, Katsuji Nishi, Masahito Hitosugi

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A 75-year-old woman took thyroidectomy forty years previously. Enlarged masses were seen at autopsy just above and below the left clavicle. We proved the diagnosis of papillary thyroid cancer (PTC) and lung metastasis by histological examinations. The prognosis of PTC is excellent; the 10-year survival rate ranges between 85 and 99%. Lung metastases may be found in 10% of the patients with PTC. We report an unusual case of recurrence of PTC with metastasis to the lung.

Keywords: papillary thyroid cancer, lung metastasis, autopsy, histopathological findings

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Authors: Marta Bas-Szymaszek

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This research examines the intricate relationship between language practices and beliefs within international environmental non-governmental organizations (ENGOs), with a particular focus on the Climate Action Network Europe (CAN Europe). While acknowledging that ENGOs often employ multilingual staff, this study aims to analyze the dual role of English within this sector. While English facilitates practical communication among individuals from diverse backgrounds, it also perpetuates inequalities and marginalization within CAN Europe. Instances of linguistic dominance impede participation and representation, reinforcing language hierarchies. Furthermore, the symbolic power of English risks overshadowing the multilingual skills of NGO employees. Through fourteen in-depth interviews, focus group discussions, and observations, this research uncovers the lived experiences of individuals navigating Europe’s largest environmental NGO network. By analyzing CAN Europe’s implicit language policy and the hegemony of English, this study illuminates the challenges within multilingual settings. The organization advocates for the implementation of more inclusive language policies and practices, with the objective of recognizing and embracing linguistic diversity within international environmental NGOs.

Keywords: language policy, English, NGOs, linguistic inclusion, multilingualism

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Authors: Sumaya Ismail, Aijaz Ahmad Reshi

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The advances in sensor and embedded technologies have led to rapid developments in Wireless Sensor Networks (WSNs). Presently researchers focus on the integration of WSNs to the Internet for their pervasive availability to access these network resources as the interoperable subsystems. The recent computing technologies like cloud computing has made resource sharing as a converged infrastructure with required service interfaces for the shared resources over the Internet. This paper presents application architecture for wireless Sensor and Actuator Networks (WSANS) following web of things, which allows easy integration of each node to the Internet in order to provide them with web accessibility. The architecture enables the sensors and actuator nodes accessed and controlled using cloud interface on WWW. The application architecture was implemented using existing web and its emerging technologies. In particular, the Representational State Transfer protocol (REST) was extended for the specific requirements of the application. The Cloud computing environment has been used as a development platform for the application to assess the possibility of integrating the WSAN nodes to Cloud services. The mushroom farm environment monitoring and control using WSANs has been taken as a research use case.

Keywords: WSAN, REST, web of things, ZigBee, cloud interface, PaaS, sensor gateway

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Authors: Georg Brunnthaller, Sandra Stein, Wilfried Sihn

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Logistics service providers are facing increasing volatility concerning future transport demand. Short-term planning horizons and planning uncertainties lead to reduced capacity utilisation and increasing empty mileage. To overcome these challenges, a model is proposed to continuously pre-plan future transport capacity in order to redesign and adjust the intermodal fleet accordingly. It is expected that the model will enable logistics service providers to organise more economically and ecologically sustainable transport chains in a more flexible way. To further describe such planning aspects, this paper gives a structured literature review on transport planning problems. The focus is on strategic and tactical planning levels, comprising relevant fleet-sizing-, network-design- and choice-of-carriers-problems. Models and their developed solution techniques are presented and the literature review is concluded with an outlook to our future research objectives

Keywords: choice of transport mode, fleet-sizing, freight transport planning, multimodal, review, service network design

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Authors: Daewook Kim, Gilwon Yoon

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Intrabody communication (IBC) is a new way of transferring data using human body as a medium. Minute current can travel though human body without any harm. IBC can remove electrical wires for human area network. IBC can be also a secure communication network system unlike wireless networks which can be accessed by anyone with bad intentions. One of the IBC systems is based on frequency shift keying modulation where individual data are transmitted to the external devices for the purpose of secure access such as digital door lock. It was found that the quality of IBC data transmission was heavily dependent on ground configurations of electronic circuits. Reliable IBC transmissions were not possible when both of the transmitter and receiver used batteries as circuit power source. Transmission was reliable when power supplies were used as power source for both transmitting and receiving sites because the common ground was established through the grounds of instruments such as power supply and oscilloscope. This was due to transmission dipole size and the ground effects of floor and AC power line. If one site used battery as power source and the other site used the AC power as circuit power source, transmission was possible.

Keywords: frequency shift keying, ground, intrabody, communication, door lock

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Authors: Christen Kutz

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Objective: The aim of this study is to review a case series of 4 high-level Olympic and Division 1 wrestlers who experienced debilitating posterior circulation ischemic strokes during or after a competitive wrestling event and to identify risk factors, etiology and outcomes of stroke in young, healthy elite wrestlers. Background: Stroke occurs in one in 10,000 people under age 64. In young adults, the most common causes of stroke are cardiac embolism, hypercoagulable state, and vasculopathy. One-third of these strokes occur in young, fit individuals. There is little published literature about ischemic strokes that occur in wrestlers. Based on the nature of wrestling, the risk of injury or dissection to neurovascular structures may be a possible theory, but very few case reports exist. Methodology: 4 wrestlers under the age of 44 with a known history of ischemic stroke participated in individual interviews either in person or virtually. Each of the wrestlers provided their demographic information, wrestling background, clinical presentation at the time of stroke, imaging results, identification of potential risk factors, acute treatment and recovery. Results: 3 white male Division 1 wrestlers (2 Lehigh University, 1 Lock Haven University) and 1 black male 2008 Olympian experienced posterior circulation strokes. Case #1 felt a “pop” while wrestling (lateral medullary infarct, possible vertebral artery dissection); Case #2 awoke with severe vertigo, sweating, and vomiting after wrestling the previous day (left cerebellar infarct, (+) protein S deficiency); Case #3 severe vertigo, ataxia, and sensation of impending doom after wrestling earlier that week (left cerebellar infarct, hypoplastic left vertebral artery (+) anti-cardiolipin antibodies). Case #4 severe dizziness, confusion (left cerebellar stroke, vertebral artery dissection, small PFO). Conclusion: 3 wrestlers were started on anti-platelet therapy, risk factors were modified, and returned to their sport. 1 wrestler was placed on anti-coagulation and retired from competition.

Keywords: stroke, wrestling, Olympic, posterior circulation

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Authors: Tan G. K. Y., Chew M. S. J., Sajeev S., Vellasamy A.

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Injuries of the extensor hallucis longus (EHL) tendon are a rare phenomenon, with most occurring due to lacerations or penetrating injuries. Closed traumatic ruptures of the EHL are described as “Mallet injuries of the toe”. These can be classified as bony or soft mallet injuries depending on the presence or absence of a fracture at the insertion site of the EHL tendon in the distal phalanx. We present a case of a 33-year-old woman who presented with a hyperflexion injury to the left big toe with an inability to extend the big toe. Ultrasound showed a complete rupture of the EHL tendon with retraction proximal to the hallucal interphalangeal joint of the big toe. The patient was treated through transarticular pinning and repair using the Arthrex Mini Bio-Suture Tak with a 2-0 fibre wire. Six months postoperatively, the patient had symmetrical EHL power and full range of motion of the toe. The lessons to be drawn from this case report are that isolated hallux mallet injuries are rare and can be easily missed in the absence of penetrating wounds. Patients who have such injuries should be investigated early with the appropriate imaging techniques, such as ultrasound or MRI, and treated surgically.

Keywords: hallux mallet, extensor hallucis longus tendon, extensor hallucis longus

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Authors: Joshua Russell, Omar Zubair, Reuben Ndegwa

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Introduction: Mesenteric ischemia is an uncommon condition that can be challenging to diagnose in the acute setting, with the potential for significant morbidity and mortality. Very rarely has acute acalculous cholecystitis been described in the setting of mesenteric ischemia. Case: This was the case in a 78-year-old male, who initially presented with clinical and radiological evidence of small bowel obstruction, thought likely secondary to malignancy. The patient had a 6-week history of anorexia, worsening lower abdominal pain, and ~30kg of unintentional weight loss over a 12-month period and a CT- scan demonstrated a transition point in the distal ileum. The patient became increasingly hemodynamically unstable and peritonitic, and an emergency laparotomy was performed. Intra-operatively, however, no obvious transition point was identified, and instead, the gallbladder was markedly gangrenous and oedematous, consistent with acalculous cholecystitis. An open total cholecystectomy was subsequently performed. The patient was admitted to the Intensive Care Unit post-operatively and continued to deteriorate over the proceeding 48 hours, with two re-look laparotomies demonstrating progressively worsening bowel ischemia, initially in the distribution of the superior mesenteric artery and then the coeliac trunk. On review, the patient was found to have an aberrant right hepatic artery arising from the superior mesenteric artery. The extent of ischemia was considered non-survivable, and the patient was palliated. Discussion: Multiple theories currently exist for the underlying pathophysiology of acalculous cholecystitis, including biliary stasis, sepsis, and ischemia. This case lends further support to ischemia as the underlying etiology of acalculous cholecystitis. This is particularly the case when considered in the context of the patient’s aberrant right hepatic artery arising from the superior mesenteric artery, which occurs in 11-14% of patients. Conclusion: This case report adds further insight to the debate surrounding the pathophysiology of acalculous cholecystitis. It also presents acalculous cholecystitis as a complication of mesenteric ischemia that should always be considered, especially in the elderly patient and in the context of relatively common anatomical variations. Furthermore, the case brings to attention the importance of maintaining dynamic working diagnoses in the setting of evolving pathophysiology and clinical presentations.

Keywords: acalculous cholecystitis, anatomical variation, general surgery, mesenteric ischemia

Procedia PDF Downloads 191

Authors: Poojan Gharat, Haridas Pal, Sharmistha Dutta Choudhury

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Tuning photophysical properties of guest dyes through host-guest interactions involving macrocyclic hosts are the attractive research areas since past few decades, as these changes can directly be implemented in chemical sensing, molecular recognition, fluorescence imaging and dye laser applications. Excited state intramolecular proton transfer (ESIPT) is an intramolecular prototautomerization process display by some specific dyes. The process is quite amenable to tunability by the presence of different macrocyclic hosts. The present study explores the interesting effect of p-sulfonatocalix[n]arene (SCXn) and cyclodextrin (CD) hosts on the excited-state prototautomeric equilibrium of Chrysazine (CZ), a model antitumour drug. CZ exists exclusively in its normal form (N) in the ground state. However, in the excited state, the excited N* form undergoes ESIPT along with its pre-existing intramolecular hydrogen bonds, giving the excited state prototautomer (T*). Accordingly, CZ shows a single absorption band due to N form, but two emission bands due to N* and T* forms. Facile prototautomerization of CZ is considerably inhibited when the dye gets bound to SCXn hosts. However, in spite of lower binding affinity, the inhibition is more profound with SCX6 host as compared to SCX4 host. For CD-CZ system, while prototautomerization process is hindered by the presence of β-CD, it remains unaffected in the presence of γCD. Reduction in the prototautomerization process of CZ by SCXn and βCD hosts is unusual, because T* form is less dipolar in nature than the N*, hence binding of CZ within relatively hydrophobic hosts cavities should have enhanced the prototautomerization process. At the same time, considering the similar chemical nature of two CD hosts, their effect on prototautomerization process of CZ would have also been similar. The atypical effects on the prototautomerization process of CZ by the studied hosts are suggested to arise due to the partial inclusion or external binding of CZ with the hosts. As a result, there is a strong possibility of intermolecular H-bonding interaction between CZ dye and the functional groups present at the portals of SCXn and βCD hosts. Formation of these intermolecular H-bonds effectively causes the pre-existing intramolecular H-bonding network within CZ molecule to become weak, and this consequently reduces the prototautomerization process for the dye. Our results suggest that rather than the binding affinity between the dye and host, it is the orientation of CZ in the case of SCXn-CZ complexes and the binding stoichiometry in the case of CD-CZ complexes that play the predominant role in influencing the prototautomeric equilibrium of the dye CZ. In the case of SCXn-CZ complexes, the results obtained through experimental findings are well supported by quantum chemical calculations. Similarly for CD-CZ systems, binding stoichiometries obtained through geometry optimization studies on the complexes between CZ and CD hosts correlate nicely with the experimental results. Formation of βCD-CZ complexes with 1:1 stoichiometry while formation of γCD-CZ complexes with 1:1, 1:2 and 2:2 stoichiometries are revealed from geometry optimization studies and these results are in good accordance with the observed effects by the βCD and γCD hosts on the ESIPT process of CZ dye.

Keywords: intermolecular proton transfer, macrocyclic hosts, quantum chemical studies, photophysical studies

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Authors: Zhou Mo, Dennis Chow

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In the dynamic positioning system (DPS) for vessels, the reliable information transmission between each note basically relies on the wireless protocols. From the perspective of cluster-based routing pro-tocols for wireless sensor networks, the data fusion technology based on the sleep scheduling mechanism and remaining energy in network layer is proposed, which applies the sleep scheduling mechanism to the routing protocols, considering the remaining energy of node and location information when selecting cluster-head. The problem of uneven distribution of nodes in each cluster is solved by the Equilibrium. At the same time, Classified Forwarding Mechanism as well as Redelivery Policy strategy is adopted to avoid congestion in the transmission of huge amount of data, reduce the delay in data delivery and enhance the real-time response. In this paper, a simulation test is conducted to improve the routing protocols, which turns out to reduce the energy consumption of nodes and increase the efficiency of data delivery.

Keywords: DPS for vessel, wireless sensor network, data fusion, routing protocols

Procedia PDF Downloads 467