Search results for: information systems success model

Authors: Olakunle Felix Adekunle

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Risk management is recognised as an essential tool to tackle the inevitable uncertainty associated with business and projects at all levels. But it frequently fails to meet expectations, with projects continuing to run late, over budget or under performing, and business is not gaining the expected benefits. The evident disconnect which often occurs between strategic vision and tactical project delivery typically arises from poorly defined project objectives and inadequate attention to the proactive management of risks that could affect those objectives. One of the main failings in the traditional approach to risk management arises from a narrow focus on the downside, restricted to the technical or operational field, addressing tactical threats to processes, performance or people. This shortcoming can be overcome by widening the scope of risk management to encompass both strategic risks and upside opportunities, creating an integrated approach which can bridge the gap between strategy and tactics. Integrated risk management addresses risk across a variety of levels in the organisation, including strategy and tactics, and covering both opportunity and threat. Effective implementation of integrated risk management can produce a number of benefits to the organisation which are not available from the typical limited-scope risk process. This paper explores how to expand risk management to deliver strategic advantage while retaining its use as a tactical tool.

Keywords: risk management, success, organization, strategy, project, tactis, vision

Procedia PDF Downloads 397

Authors: Klára Gajdošíková

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The aim of this study was to examine the quiet eye method and its components using the mobile eye tracking device. Quiet eye training was proven to be beneficial for different sports, including golf. The main idea of this method is to prolong your fixations on a specific place in order to improve your performance. The shot examined in this study is called putt. Its importance is based on its role on a golf course because, many times, it is the last putt that decides whether you win or lose. Quiet eye training helps players be more focused under pressure, control their attention and overall improve their putting success. Six highly skilled golfers with a handicap ranging from - 4 to + 4, aged 23 to 26, participated in a pilot study with the usage of an eye-tracking device. The study took place in an indoor training area at the golf club Hostivař. Crosstabs showed significant differences between individuals' laterality and their gaze into AOI - areas of interest (middle part of the ball, top of the ball, bottom of the ball, back side of the ball). Statistically significant differences were also discovered between the mean fixation duration of participants with AOI on the middle part of the ball and all other AOIs. The results of this study helped us understand the examined phenomena and showed us the next aim in future quiet eye research. Future research should focus on examining a quiet eye on the golf course. Applying a quiet eye and therefore changing the way we concentrate might be beneficial for coaches and players themselves.

Keywords: eye tracking, golf, laterality, quiet eye

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Authors: Omar Farshad Jeelani, Makaire Njie, Viktoriia M. Korzhuk

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Recently, the application of AI-powered algorithms in healthcare continues to flourish. Particularly, access to healthcare information, including patient health history, diagnostic data, and PII (Personally Identifiable Information) is paramount in the delivery of efficient patient outcomes. However, as the exchange of healthcare information between patients and healthcare providers through AI-powered solutions increases, protecting a person’s information and their privacy has become even more important. Arguably, the increased adoption of healthcare AI has resulted in a significant concentration on the security risks and protection measures to the security and privacy of healthcare data, leading to escalated analyses and enforcement. Since these challenges are brought by the use of AI-based healthcare solutions to manage healthcare data, AI-based data protection measures are used to resolve the underlying problems. Consequently, this project proposes AI-powered safeguards and policies/laws to protect the privacy of healthcare data. The project presents the best-in-school techniques used to preserve the data privacy of AI-powered healthcare applications. Popular privacy-protecting methods like Federated learning, cryptographic techniques, differential privacy methods, and hybrid methods are discussed together with potential cyber threats, data security concerns, and prospects. Also, the project discusses some of the relevant data security acts/laws that govern the collection, storage, and processing of healthcare data to guarantee owners’ privacy is preserved. This inquiry discusses various gaps and uncertainties associated with healthcare AI data collection procedures and identifies potential correction/mitigation measures.

Keywords: data privacy, artificial intelligence (AI), healthcare AI, data sharing, healthcare organizations (HCOs)

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Authors: Rajesh Singh, Kailash Kale

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In this paper, the Binomial process type occurrence of software failures is considered and failure intensity has been characterized by one parameter Rayleigh class Software Reliability Growth Model (SRGM). The proposed SRGM is mathematical function of parameters namely; total number of failures i.e. η-0 and scale parameter i.e. η-1. It is assumed that very little or no information is available about both these parameters and then considering non-informative priors for both these parameters, the Bayes estimators for the parameters η-0 and η-1 have been obtained under square error loss function. The proposed Bayes estimators are compared with their corresponding maximum likelihood estimators on the basis of risk efficiencies obtained by Monte Carlo simulation technique. It is concluded that both the proposed Bayes estimators of total number of failures and scale parameter perform well for proper choice of execution time.

Keywords: binomial process, non-informative prior, maximum likelihood estimator (MLE), rayleigh class, software reliability growth model (SRGM)

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Authors: Nam Don Kim, Jungho Moon, Tae Yun Chung

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This paper proposes an Internet of Things (IoT) based virtualization platform for providing smart tourism services. The virtualization platform provides a consistent access interface to various types of data by naming IoT devices and legacy information systems as pathnames in a virtual file system. In the other words, the IoT virtualization platform functions as a middleware which uses the metadata for underlying collected data. The proposed platform makes it easy to provide customized tourism information by using tourist locations collected by IoT devices and additionally enables to create new interactive smart tourism services focused on the tourist locations. The proposed platform is very efficient so that the provided tourism services are isolated from changes in raw data and the services can be modified or expanded without changing the underlying data structure.

Keywords: internet of things (IoT), IoT platform, serviceplatform, virtual file system (VSF)

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Authors: S. A. Al-Qallaf, S. A. Al-Mawsawi, A. Haider

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In order to evaluate the performance of a unified power flow controller (UPFC), mathematical models for steady state and dynamic analysis are to be developed. The steady state model is mainly concerned with the incorporation of the UPFC in load flow studies. Several load flow models for UPFC have been introduced in literature, and one of the most reliable models is the decoupled UPFC model. In spite of UPFC decoupled load flow model simplicity, it is more robust compared to other UPFC load flow models and it contains unique capabilities. Some shortcoming such as additional set of nonlinear equations are to be solved separately after the load flow solution is obtained. The aim of this study is to investigate the different control strategies that can be realized in the decoupled load flow model (individual control and combined control), and the impact of the location of the UPFC in the network on its control parameters.

Keywords: UPFC, decoupled model, load flow, control parameters

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Authors: Marko Batic, Nikola Tomasevic, Sanja Vranes

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One of the strongholds in the ubiquitous efforts related to the energy conservation and energy efficiency improvement is represented by the retrofit of high energy consumers in buildings. In general, HVAC systems represent the highest energy consumers in buildings. However they usually suffer from mal-operation and/or malfunction, causing even higher energy consumption than necessary. Various Fault Detection and Diagnosis (FDD) systems can be successfully employed for this purpose, especially when it comes to the application at a single device/unit level. In the case of more complex systems, where multiple devices are operating in the context of the same building, significant energy efficiency improvements can only be achieved through application of comprehensive FDD systems relying on additional higher level knowledge, such as their geographical location, served area, their intra- and inter- system dependencies etc. This paper presents a comprehensive FDD system that relies on the utilization of common knowledge repository that stores all critical information. The discussed system is deployed as a test-bed platform at the two at Fiumicino and Malpensa airports in Italy. This paper aims at presenting advantages of implementation of the knowledge base through the utilization of ontology and offers improved functionalities of such system through examples of typical queries and reasoning that enable derivation of high level energy conservation measures (ECM). Therefore, key SPARQL queries and SWRL rules, based on the two instantiated airport ontologies, are elaborated. The detection of high level irregularities in the operation of airport heating/cooling plants is discussed and estimation of energy savings is reported.

Keywords: airport ontology, knowledge management, ontology modeling, reasoning

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Authors: Esther Chiramal, Kelvin Soh Boon Kai

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Explainable AI is a strong strategy implemented to understand complex black-box model predictions in a human-interpretable language. It provides the evidence required to execute the use of trustworthy and reliable AI systems. On the other hand, however, it also opens the door to locating possible vulnerabilities in an AI model. Traditional adversarial text attack uses word substitution, data augmentation techniques, and gradient-based attacks on powerful pre-trained Bidirectional Encoder Representations from Transformers (BERT) variants to generate adversarial sentences. These attacks are generally white-box in nature and not practical as they can be easily detected by humans e.g., Changing the word from “Poor” to “Rich”. We proposed a simple yet effective Grey-box cum Black-box approach that does not require the knowledge of the model while using a set of surrogate Transformer/BERT models to perform the attack using Explainable AI techniques. As Transformers are the current state-of-the-art models for almost all Natural Language Processing (NLP) tasks, an attack generated from BERT1 is transferable to BERT2. This transferability is made possible due to the attention mechanism in the transformer that allows the model to capture long-range dependencies in a sequence. Using the power of BERT generalisation via attention, we attempt to exploit how transformers learn by attacking a few surrogate transformer variants which are all based on a different architecture. We demonstrate that this approach is highly effective to generate semantically good sentences by changing as little as one word that is not detectable by humans while still fooling other BERT models.

Keywords: BERT, explainable AI, Grey-box text attack, transformer

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Authors: Anastasia Rita Widiarti, Agus Harjoko, Marsono, Sri Hartati

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This paper presents the results of a study to test whether the Javanese character manuscript image preprocessing model that have been more widely applied, can also be applied to segment of the Batak characters manuscripts. The treatment process begins by converting the input image into a binary image. After the binary image is cleaned of noise, then the segmentation lines using projection profile is conducted. If unclear histogram projection is found, then the smoothing process before production indexes line segments is conducted. For each line image which has been produced, then the segmentation scripts in the line is applied, with regard of the connectivity between pixels which making up the letters that there is no characters are truncated. From the results of manuscript preprocessing system prototype testing, it is obtained the information about the system truth percentage value on pieces of Pustaka Batak Podani Ma AjiMamisinon manuscript ranged from 65% to 87.68% with a confidence level of 95%. The value indicates the truth percentage shown the initial processing model in Javanese characters manuscript image can be applied also to the image of the Batak characters manuscript.

Keywords: connected component, preprocessing, manuscript image, projection profiles

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Authors: Baladitya Swaika, Rahul Khatry

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Computer Adaptive Tests (CATs) is one of the most efficient ways for testing the cognitive abilities of students. CATs are based on Item Response Theory (IRT) which is based on item selection and ability estimation using statistical methods of maximum information selection/selection from posterior and maximum-likelihood (ML)/maximum a posteriori (MAP) estimators respectively. This study aims at combining both classical and Bayesian approaches to IRT to create a dataset which is then fed to a neural network which automates the process of ability estimation and then comparing it to traditional CAT models designed using IRT. This study uses python as the base coding language, pymc for statistical modelling of the IRT and scikit-learn for neural network implementations. On creation of the model and on comparison, it is found that the Neural Network based model performs 7-10% worse than the IRT model for score estimations. Although performing poorly, compared to the IRT model, the neural network model can be beneficially used in back-ends for reducing time complexity as the IRT model would have to re-calculate the ability every-time it gets a request whereas the prediction from a neural network could be done in a single step for an existing trained Regressor. This study also proposes a new kind of framework whereby the neural network model could be used to incorporate feature sets, other than the normal IRT feature set and use a neural network’s capacity of learning unknown functions to give rise to better CAT models. Categorical features like test type, etc. could be learnt and incorporated in IRT functions with the help of techniques like logistic regression and can be used to learn functions and expressed as models which may not be trivial to be expressed via equations. This kind of a framework, when implemented would be highly advantageous in psychometrics and cognitive assessments. This study gives a brief overview as to how neural networks can be used in adaptive testing, not only by reducing time-complexity but also by being able to incorporate newer and better datasets which would eventually lead to higher quality testing.

Keywords: computer adaptive tests, item response theory, machine learning, neural networks

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Authors: N. David, H. O. Gao

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Air pollution is a serious environmental threat on a global scale and can cause harm to human health, morbidity and premature mortality. Reliable monitoring and control systems are therefore necessary to develop coping skills against the hazards associated with this phenomenon. However, existing environmental monitoring means often do not provide a sufficient response due to practical and technical limitations. Commercial microwave links that form the infrastructure for transmitting data between cell phone towers can be harnessed to map rain at high tempo-spatial resolution. Rainfall causes a decrease in the signal strength received by these wireless communication links allowing it to be used as a built-in sensor network to map the phenomenon. In this study, we point to the potential that lies in this system to indirectly monitor areas where air pollution is reduced. The relationship between pollutant wash-off and rainfall provides an opportunity to acquire important spatial information about air quality using existing cell-phone tower signals. Since the density of microwave communication networks is high relative to any dedicated sensor arrays, it could be possible to rely on this available observation tool for studying precipitation scavenging on air pollutants, for model needs and more.

Keywords: air pollution, commercial microwave links, rainfall, washout

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Authors: Patik Joslin Kenfack, Polyakov Vladimir Mikhailovich

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Machine Learning (ML) systems are trained using human generated data that could be biased by implicitly containing racist, sexist, or discriminating data. ML models learn those biases or even amplify them. Recent research in work on has begun to consider issues of fairness. The concept of fairness is extended to recommendation. A recommender system will be considered fair if it doesn’t under rank items of protected group (gender, race, demographic...). Several metrics for evaluating fairness concerns in recommendation systems have been proposed, which take pairs of items as ‘instances’ in fairness evaluation. It doesn’t take in account the fact that the fairness should be evaluated across a list of items. The paper explores a probabilistic approach that generalize pairwise metric by using a list k (listwise) of items as ‘instances’ in fairness evaluation, parametrized by k. We also explore new regularization method based on this metric to improve fairness ranking during model training.

Keywords: Fairness, Recommender System, Ranking, Listwise Approach

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Authors: Kriddikorn Kaewwongsri, Nikom Suvonvorn

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In the deep south of Thailand, checkpoints for people verification are necessary for the security management of risk zones, such as official buildings in the conflict area. In this paper, we propose an automatic checkpoint system that verifies persons using information from ID cards and facial features. The methods for a person’s information abstraction and verification are introduced based on useful information such as ID number and name, extracted from official cards, and facial images from videos. The proposed system shows promising results and has a real impact on the local society.

Keywords: face comparison, card recognition, OCR, checkpoint system, authentication

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Authors: Haitham A. Hussein, Rozi Abdullah, Issa Saket, Md. Azlin

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The gravitational effect has been extensively applied to separate oil from water in water and wastewater treatment systems. The maximum oil globules removal efficiency is improved by obtaining the best flow uniformity in separator tanks. This study used 2D computational fluid dynamics (CFD) to investigate the effect of different inlet baffle positions inside the separator tank. Laboratory experiment has been conducted, and the measured velocity fields which were by Nortek Acoustic Doppler Velocimeter (ADV) are used to verify the CFD model. Computational investigation results indicated that the construction of an inlet baffle in a suitable location provides the minimum recirculation zone volume, creates the best flow uniformity, and dissipates kinetic energy in the oil and water separator tank. Useful formulas were predicted to design the oil and water separator tanks geometry based on an experimental model.

Keywords: oil/water separator tanks, inlet baffles, CFD, VOF

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Authors: Michael Hast

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Within their first year, infants can differentiate between objects based on their weight. By at least 5 years children hold consistent weight-related misconceptions about the physical world, such as that heavy things fall faster than lighter ones because of their weight. Such misconceptions are seen as a challenge for science education since they are often highly resistant to change through instruction. Understanding the time point of emergence of such ideas could, therefore, be crucial for early science pedagogy. The paper thus discusses two studies that jointly address the issue by examining young children’s search behaviour in hidden displacement tasks under consideration of relative object weight. In both studies, they were tested with a heavy or a light ball, and they either had information about one of the balls only or both. In Study 1, 88 toddlers aged 2 to 3½ years watched a ball being dropped into a curved tube and were then allowed to search for the ball in three locations – one straight beneath the tube entrance, one where the curved tube lead to, and one that corresponded to neither of the previous outcomes. Success and failure at the task were not impacted by weight of the balls alone in any particular way. However, from around 3 years onwards, relative lightness, gained through having tactile experience of both balls beforehand, enhanced search success. Conversely, relative heaviness increased search errors such that children increasingly searched in the location immediately beneath the tube entry – known as the gravity bias. In Study 2, 60 toddlers aged 2, 2½ and 3 years watched a ball roll down a ramp and behind a screen with four doors, with a barrier placed along the ramp after one of four doors. Toddlers were allowed to open the doors to find the ball. While search accuracy generally increased with age, relative weight did not play a role in 2-year-olds’ search behaviour. Relative lightness improved 2½-year-olds’ searches. At 3 years, both relative lightness and relative heaviness had a significant impact, with the former improving search accuracy and the latter reducing it. Taken together, both studies suggest that between 2 and 3 years of age, relative object weight is increasingly taken into consideration in navigating naïve physical concepts. In particular, it appears to contribute to the early emergence of misconceptions relating to object weight. This insight from developmental psychology research may have consequences for early science education and related pedagogy towards early conceptual change.

Keywords: conceptual development, early science education, intuitive physics, misconceptions, object weight

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Authors: Yasser F. Hassan

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The reduction or removal of noise in a color image is an essential part of image processing, whether the final information is used for human perception or for an automatic inspection and analysis. This paper describes the modeling system based on the rough neural network model to adaptive cellular automata for various image processing tasks and noise remover. In this paper, we consider the problem of object processing in colored image using rough neural networks to help deriving the rules which will be used in cellular automata for noise image. The proposed method is compared with some classical and recent methods. The results demonstrate that the new model is capable of being trained to perform many different tasks, and that the quality of these results is comparable or better than established specialized algorithms.

Keywords: rough sets, rough neural networks, cellular automata, image processing

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Authors: Ahmad. A. Kardan, Amir Narimani, Foozhan Ataiefard

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Recommender Systems have been developed to provide contents and services compatible to users based on their behaviors and interests. Due to information overload in online discussion forums and users diverse interests, recommending relative topics and threads is considered to be helpful for improving the ease of forum usage. In order to lead learners to find relevant information in educational forums, recommendations are even more needed. We present a hybrid thread recommender system for MOOC forums by applying social network analysis and association rule mining techniques. Initial results indicate that the proposed recommender system performs comparatively well with regard to limited available data from users' previous posts in the forum.

Keywords: association rule mining, hybrid recommender system, massive open online courses, MOOCs, social network analysis

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Authors: Golshid Gilani, Albert De La Fuente, Ana Blanco

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Sustainability assessment of new and existing buildings has generated a growing interest due to the evident environmental, social and economic impacts during their construction and service life. Façades, as one of the most important exterior elements of a building, may contribute to the building sustainability by reducing the amount of energy consumption and providing thermal comfort for the inhabitants, thus minimizing the environmental impact on both the building and on the environment. Various methods have been used for the sustainability assessment of buildings due to the importance of this issue. However, most of the existing methods mainly concentrate on environmental and economic aspects, disregarding the third pillar of sustainability, which is the social aspect. Besides, there is a little focus on comprehensive sustainability assessment of facades, as an important element of a building. This confirms the need of developing methods for assessing the sustainable performance of building façades as an important step in achieving building sustainability. In this respect, this paper aims at presenting a model for assessing the global sustainability of façade systems. for that purpose, the Integrated Value Model for Sustainable Assessment (MIVES), a Multi-Criteria Decision Making model that integrates the main sustainability requirements (economic, environmental and social) and includes the concept of value functions, used as an assessment tool.

Keywords: façade, MCDM, MIVES, sustainability

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Authors: İsmail Seçer, Taştan Seçer

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In this study, the effect of the group counseling on the victimhood perceptions of the primary school 7th and 8th grade students who are determined to be the subject of peer victimization and their dealing way with it was analyzed. The research model is Solomon Four Group Experimental Model. In this model, there are four groups that were determined with random sampling. Two of the groups have been used as experimental group and the other two have been used as control group. Solomon model is defined as real experimental model. In real experimental models, there are multiple groups consisting of subject which have similar characteristics, and selection of the subjects is done with random sampling. For this purpose, 230 students from Kültür Kurumu Primary School in Erzurum were asked to fill Adolescent Peer Victim Form. 100 students whose victim scores were higher and who were determined to be the subject of bullying were talked face to face and informed about the current study, and they were asked if they were willing to participate or not. As a result of these interviews, 60 students were determined to participate in the experimental study and four group consisting of 15 people were created with simple random sampling method. After the groups had been formed, experimental and control group were determined with casting lots. After determining experimental and control groups, an 11-session group counseling activity which was prepared by the researcher according to the literature was applied. The purpose of applying group counseling is to change the ineffective dealing ways with bullying and their victimhood perceptions. Each session was planned to be 75 minutes and applied as planned. In the control groups, counseling activities in the primary school counseling curricula was applied for 11 weeks. As a result of the study, physical, emotional and verbal victimhood perceptions of the participants in the experimental groups were decreased significantly compared to pre-experimental situations and to those in control group. Besides, it was determined that this change observed in the victimhood perceptions of the experimental group occurred independently from the effect of variables such as gender, age and academic success. The first evidence of the study related to the dealing ways is that the scores of the participants in the experimental group related to the ineffective dealing ways such as despair and avoidance is decreased significantly compared to the pre-experimental situation and to those in control group. The second evidence related to the dealing ways is that the scores of the participants in the experimental group related to effective dealing ways such as seeking for help, consulting social support, resistance and optimism is increased significantly compared to the pre-experimental situation and to those in control group. According to the evidence obtained through the study, it can be said that group counseling is an effective approach to change the victimhood perceptions of the individuals who are the subject of bullying and their dealing strategies with it.

Keywords: bullying, perception of victimization, coping strategies, ancova analysis

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Authors: Ahmed N. Shmroukh, I. M. S. Taha, A. M. Abdel-Ghany, M. Attalla

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Fog systems application for cooling and humidification is still limited, although these systems require less initial cost compared with that of other cooling systems such as pad-and-fan systems. The undesirable relative humidity and air temperature inside the space which have been cooled or humidified are the main reasons for its limited use, which results from the poor control of fog systems. Any accurate control system essentially needs air dry bulb temperature as an input parameter. Therefore, the air dry-bulb temperature in the space needs to be measured accurately. The Scope of the present work is the separation of the fog droplets from the air in a fogged space to measure the air dry bulb temperature accurately. The separation is to be done in a small device inside which the sensor of the temperature measuring instrument is positioned. Vortex separator will be designed and used. Another reference device will be used for measuring the air temperature without separation. A comparative study will be performed to reach at the best device which leads to the most accurate measurement of air dry bulb temperature. The results showed that the proposed devices improved the measured air dry bulb temperature toward the correct direction over that of the free junction. Vortex device was the best. It respectively increased the temperature measured by the free junction in the range from around 2 to around 6°C for different fog on-off duration.

Keywords: fog systems, measuring air dry bulb temperature, temperature measurement, vortex separator

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Authors: Sana Ridene, Soumaya Sayeb, Houda Helali, Mohammed Ben Hassen

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Nonwoven structures have a range of applications which include Medical, filtration, geotextile and recently this unconventional fabric is finding a niche in fashion apparel. In this paper, a modified form of Vangheluwe rheological model is used to describe the mechanical behavior of nonwovens fabrics in uniaxial tension. This model is an association in parallel of three Maxwell elements characterized by damping coefficients η1, η2 and η3 and E1, E2, E3 elastic modulus and a nonlinear spring C. The model is verified experimentally with two types of nonwovens (50% viscose /50% Polyester) and (40% viscose/60% Polyester) and a range of three square weights values. Comparative analysis of the theoretical model and the experimental results of tensile test proofs a high correlation between them. The proposed model can fairly well replicate the behavior of nonwoven fabrics during relaxation and sample traction. This allowed us to predict the mechanical behavior in tension and relaxation of fabrics starting only from their technical parameters (composition and weight).

Keywords: mechanical behavior, tensile strength, relaxation, rheological model

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Authors: Ruslan Safarov, Zhanat Shomanova, Yuri Nossenko, Zhandos Mussayev, Ayana Baltabek

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Geochemical maps of distribution of polluting elements V, Cr, Mn, Co, Ni, Cu, Zn, Mo, Cd, Pb on the territory of the Pavlodar city (Kazakhstan), which is an industrial hub were designed. The samples of soil were taken from 100 locations. Elemental analysis has been performed using XRF. The obtained data was used for training of the computational model with gradient boosting algorithm. The optimal parameters of model as well as the loss function were selected. The computational model was used for prediction of polluting elements concentration for 1000 evenly distributed points. Based on predicted data geochemical maps were created. Additionally, the total pollution index Zc was calculated for every from 1000 point. The spatial distribution of the Zc index was visualized using GIS (QGIS). It was calculated that the maximum coverage area of the territory of the Pavlodar city belongs to the moderately hazardous category (89.7%). The visualization of the obtained data allowed us to conclude that the main source of contamination goes from the industrial zones where the strategic metallurgical and refining plants are placed.

Keywords: Pavlodar, geochemical map, gradient boosting, CatBoost, QGIS, spatial distribution, heavy metals

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Authors: Nicolas Delcey, Philippe Baucour, Didier Chamagne, Geneviève Wimmer, Auditeau Gérard, Bausseron Thomas, Bouger Odile, Blanvillain Gérard

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This paper proposes a thermal study of the catenary/pantograph interface for a train in motion. A 2.5D complex model of the pantograph strip has been defined and created by a coupling between a 1D and a 2D model. Experimental and simulation results are presented and with a comparison allow validating the 2.5D model. Some physical phenomena are described and presented with the help of the model such as the stagger motion thermal effect, particular heats and the effect of the material characteristics. Finally it is possible to predict the critical thermal configuration during a train trip.

Keywords: electro-thermal studies, mathematical optimizations, multi-physical approach, numerical model, pantograph strip wear

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Authors: Hanyu Wei

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The last two decades have witnessed a significant number of regeneration practices in historical Chinese cities with the context of rapid urbanisation and economic development. As a response to the possible loss of place identity in the redevelopment process, city makers recognise the potentials of places with cultural significance for maintaining the original landscape. In Chongqing, the prosperities of human settlement history together with the anti-war and post-industrial culture bring this riverside city with its unique urban landscape. Great amounts of historical sites are identified and subjected to conservation planning approaches for urban revitalisation while also maintaining the historic urban landscape. This paper reviews three practices of cultural-led regeneration projects (Hongyadong, Ciqikou, Danzishi) in Chongqing, detailing the urban design and planning principals for the case sites. The paper also presents the conflicting opinions from groups with different interests. By carrying a systematical sustainability evaluation assessment on those projects, the paper critically analyzes the influence of these projects on the broad socio-economic aspects. Although these regeneration cases are thought to achieve the general success in abstaining economic benefits, they are criticised for the over-tourism issues and damages on the authenticity, which further fails to achieve sustainable development.

Keywords: Chongqing, historic urban landscape, sustainable development, urban regeneration

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Authors: Hung Lin-Zin, Lai Mei-Yen

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Prostate cancer is the most commonly diagnosed male cancer in the U.S. The prevalence is around 1 in 8. The etiology of prostate cancer is still unknown, but some predisposing factors, such as age, black race, family history, and obesity, may increase the risk of the disease. In 2020, a total of 7,178 Taiwanese people were nearly diagnosed with prostate cancer, accounting for 5.88% of all cancer cases, and the incidence rate ranked fifth among men. In that year, the total number of deaths from prostate cancer was 1,730, accounting for 3.45% of all cancer deaths, and the death rate ranked 6th among men, accounting for 94.34% of the cases of male reproductive organs. Looking for domestic and foreign literature on the use of OMOP (Observational Medical Outcomes Partnership, hereinafter referred to as OMOP) database analysis, there are currently nearly a hundred literature published related to nursing-related health problems and nursing measures built in the OMOP general data model database of medical institutions are extremely rare. The OMOP common data model construction analysis platform is a system developed by the FDA in 2007, using a common data model (common data model, CDM) to analyze and monitor healthcare data. It is important to build up relevant nursing information from the OMOP- CDM database to assist our daily practice. Therefore, we choose prostate cancer patients who are our popular care objects and use the OMOP- CDM database to explore the common associated health problems. With the assistance of OMOP-CDM database analysis, we can expect early diagnosis and prevention of prostate cancer patients' comorbidities to improve patient care.

Keywords: OMOP, nursing diagnosis, health problem, prostate cancer

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Authors: Meng Miao, Jeongwoo Han, Cam Nguyen

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Ultra-wideband (UWB) time-domain impulse communication and radar systems use ultra-short duration pulses in the sub-nanosecond regime, instead of continuous sinusoidal waves, to transmit information. The pulse directly generates a very wide-band instantaneous signal with various duty cycles depending on specific usages. In UWB systems, the total transmitted power is spread over an extremely wide range of frequencies; the power spectral density is extremely low. This effectively results in extremely small interference to other radio signals while maintains excellent immunity to interference from these signals. UWB devices can therefore work within frequencies already allocated for other radio services, thus helping to maximize this dwindling resource. Therefore, impulse UWB technique is attractive for realizing high-data-rate, short-range communications, ground penetrating radar (GPR), and military radar with relatively low emission power levels. UWB antennas are the key element dictating the transmitted and received pulse shape and amplitude in both time and frequency domain. They should have good impulse response with minimal distortion. To facilitate integration with transmitters and receivers employing microwave integrated circuits, UWB antennas enabling direct integration are preferred. We present the development of two UWB antennas operating from 3.1 to 10.6 GHz and 0.3-6 GHz for UWB systems that provide direct integration with microwave integrated circuits. The operation of these antennas is based on the principle of wave propagation on a non-uniform transmission line. Time-domain EM simulation is conducted to optimize the antenna structures to minimize reflections occurring at the open-end transition. Calculated and measured results of these UWB antennas are presented in both frequency and time domains. The antennas have good time-domain responses. They can transmit and receive pulses effectively with minimum distortion, little ringing, and small reflection, clearly demonstrating the signal fidelity of the antennas in reproducing the waveform of UWB signals which is critical for UWB sensors and communication systems. Good performance together with seamless microwave integrated-circuit integration makes these antennas good candidates not only for UWB applications but also for integration with printed-circuit UWB transmitters and receivers.

Keywords: antennas, ultra-wideband, UWB, UWB communication systems, UWB radar systems

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Authors: Raif Parlakkaya, Mustafa Nihat Demirci, Mehmet Nuri Salur

Abstract:

Environmental pollution has detrimental effects on the quality of our life and its scope has reached such an extent that measures are being taken both at the national and international levels to reduce, prevent and mitigate its impact on social, economic and political spheres. Therefore, awareness of environmental problems has been increasing among stakeholders and accordingly among companies. It is seen that corporate reporting is expanding beyond environmental performance. Primary purpose of publishing an environmental report is to provide specific audiences with useful, meaningful information. This paper is intended to analyze the extent and qualification of environmental disclosures of Turkish publicly quoted firms and see how it varies from one sector to another. The data for the study were collected from annual activity reports of companies, listed on the corporate governance index (BIST-XKURY) of Istanbul Stock Exchange. Content analysis was the research methodology used to measure the extent of environmental disclosure. Accordingly, 2015 annual activity reports of companies that carry out business in some particular fields were acquired from Capital Market Board, websites of Public Disclosure Platform and companies’ own websites. These reports were categorized into five main aspects: Environmental policies, environmental management systems, environmental protection and conservation activities, environmental awareness and information on environmental lawsuits. Subsequently, each component was divided into several variables related to what each firm is supposed to disclose about environmental information. In this context, the nature and scope of the information disclosed on each item were assessed according to five different ways (N.I: No Information; G.E.: General Explanations; Q.E.: Qualitative Detailed Explanations; N.E.: Quantitative (numerical) Detailed Explanations; Q.&N.E.: Both Qualitative and Quantitative Explanations).

Keywords: environmental accounting, disclosure, corporate governance, content analysis

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Authors: Mahdi Allaoua Seklab, Süleyman BaşTürk

Abstract:

In the quest to enhance coastal environmental health, this study introduces a fully autonomous beach cleaning machine, a breakthrough in leveraging green energy and advanced artificial intelligence for ecological preservation. Designed to operate independently, the machine is propelled by a solar-powered system, underscoring a commitment to sustainability and the use of renewable energy in autonomous robotics. The vehicle's autonomous navigation is achieved through a sophisticated integration of LIDAR and a camera system, utilizing an SSD MobileNet V2 object detection model for accurate and real-time trash identification. The SSD framework, renowned for its efficiency in detecting objects in various scenarios, is coupled with the lightweight and precise highly MobileNet V2 architecture, making it particularly suited for the computational constraints of on-board processing in mobile robotics. Training of the SSD MobileNet V2 model was conducted on Google Colab, harnessing cloud-based GPU resources to facilitate a rapid and cost-effective learning process. The model was refined with an extensive dataset of annotated beach debris, optimizing the parameters using the Adam optimizer and a cross-entropy loss function to achieve high-precision trash detection. This capability allows the machine to intelligently categorize and target waste, leading to more effective cleaning operations. This paper details the design and functionality of the beach cleaning machine, emphasizing its autonomous operational capabilities and the novel application of AI in environmental robotics. The results showcase the potential of such technology to fill existing gaps in beach maintenance, offering a scalable and eco-friendly solution to the growing problem of coastal pollution. The deployment of this machine represents a significant advancement in the field, setting a new standard for the integration of autonomous systems in the service of environmental stewardship.

Keywords: autonomous beach cleaning machine, renewable energy systems, coastal management, environmental robotics

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Authors: Satya Pradhan, Venky Nanniyur

Abstract:

As the software industry transitions from a license-based model to a subscription-based Software-as-a-Service (SaaS) model, many software development groups are using a hybrid development model that incorporates Agile and Waterfall methodologies in different parts of the organization. The traditional metrics used for measuring software quality in Waterfall or Agile paradigms do not apply to this new hybrid methodology. In addition, to respond to higher quality demands from customers and to gain a competitive advantage in the market, many companies are starting to prioritize quality as a strategic differentiator. As a result, quality metrics are included in the decision-making activities all the way up to the executive level, including board of director reviews. This paper presents key challenges associated with measuring software quality in organizations using the hybrid development model. We introduce a framework called Prevention-Inspection-Evaluation-Removal (PIER) to provide a comprehensive metric definition for hybrid organizations. The framework includes quality measurements, quality enforcement, and quality decision points at different organizational levels and project milestones. The metrics framework defined in this paper is being used for all Cisco systems products used in customer premises. We present several field metrics for one product portfolio (enterprise networking) to show the effectiveness of the proposed measurement system. As the results show, this metrics framework has significantly improved in-process defect management as well as field quality.

Keywords: quality management system, quality metrics framework, quality metrics, agile, waterfall, hybrid development system

Procedia PDF Downloads 174

Authors: Nadia Noor, Farida Faisal

Abstract:

Horizontal hostility has been identified as a special type of workplace violence and refers to the aggressive behavior inflicted by women towards other women due to gender issues or towards minority group members due to minority issues. Many women, while they want eagerly to succeed and invest invigorated efforts to achieve success, harbor negative feelings for other women to succeed in their career. This phenomenon has been known as Horizontal Violence, Horizontal Hostility, Lateral Violence, Indirect Aggression, or The Tall Poppy Syndrome in Australian culture. Tall Poppy is referred to as a visibly successful individual who attracts envy or hostility due to distinctive characteristics. Therefore, horizontal hostility provides theoretical foundation to examine fierce competition among females than males for their limited access to top level management positions. In Pakistan, gender discrimination persists due to male dominance in the society and women do not enjoy basic equality rights in all aspects of life. They are oppressed at social and organizational level. As Government has been trying to enhance women participation through providing more employment opportunities, provision of peaceful workplace is mandatory that will enable aspiring females to achieve objectives of career success. This research study will help to understand antecedents, dimensions and outcomes of horizontal hostility that hinder career success of competitive females. The present paper is a review paper and various forms of horizontal hostility have been discussed in detail. Different psychological and organizational level drivers of horizontal hostility have been explored through literature. Psychological drivers include oppression, lack of empowerment, learned helplessness and low self-esteem. Organizational level drivers include sticky floor, glass ceiling, toxic work environment and leadership role. Horizontal hostility among working women results in psychological and physical outcomes including stress, low motivation, poor job performance and intention to leave. The study recommends provision of healthy and peaceful work environment that will enable competent women to achieve objectives of career success. In this regard, concrete actions and effective steps are required to promote gender equality at social and organizational level. The need is to ensure the enforcement of legal frameworks by government agencies in order to provide healthy working environment to women by reducing harassment and violence against them. Organizations must eradicate drivers of horizontal hostility and provide women peaceful work environment. In order to develop coping skills, training and mentoring must be provided to them.

Keywords: gender discrimination, glass ceiling, horizontal hostility, oppression

Procedia PDF Downloads 134