Search results for: information centric network

Authors: Lucie Jirotková, Daniel Macek, Andrea Palazzo, Veronika Malinová

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Currently, the implementation of 3D models in the construction industry is gaining popularity. Countries around the world are developing their own modelling standards and implement the use of 3D models into their individual permitting processes. Another theme that needs to be addressed are public building spaces and their subsequent maintenance, where the usage of BIM methodology is directly offered. The significant benefit of the implementation of Building Information Management is the information transfer. The 3D model contains not only the spatial representation of the item shapes but also various parameters that are assigned to the individual elements, which are easily traceable, mainly because they are all stored in one place in the BIM model. However, it is important to keep the data in the models up to date to achieve useability of the model throughout the life cycle of the building. It is now becoming standard practice to use BIM models in the construction of buildings, however, the building environment is very often neglected. Especially in large-scale development projects, the public space of buildings is often forwarded to municipalities, which obtains the ownership and are in charge of its maintenance. A 3D model of the building surroundings would include both the above-ground visible elements of the development as well as the underground parts, such as the technological facilities of water features, electricity lines for public lighting, etc. The paper shows the possibilities of a model in the field of information for the handover of premises, the following maintenance and decision making. The attributes and spatial representation of the individual elements make the model a reliable foundation for the creation of "Smart Cities". The paper analyses the current use of the BIM methodology and presents the state-of-the-art possibilities of development.

Keywords: BIM model, urban space, BIM methodology, facility management

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Authors: Domingos Viegas, Miguel Almeida, Carmen Rocha, Ilda Novo, Yolanda Luna

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Forest fires along the more than 1200km of the Spanish-Portuguese border are more and more frequent, currently achieving around 2000 fire events per year. Some of these events develop to large international wildfire requiring concerted operations based on shared information between the two countries. The fire event of Valencia de Alcantara (2003) causing several fatalities and more than 13000ha burnt, is a reference example of these international events. Currently, Portugal and Spain have a specific cross-border cooperation protocol on wildfires response for a strip of about 30km (15 km for each side). It is recognized by public authorities the successfulness of this collaboration however it is also assumed that this cooperation should include more functionalities such as the development of a common risk information system for transboundary fire events. Since Portuguese and Spanish authorities use different approaches to determine the fire risk indexes inputs and different methodologies to assess the fire risk, sometimes the conjoint firefighting operations are jeopardized since the information is not harmonized and the understanding of the situation by the civil protection agents from both countries is not unique. Thus, a methodology aiming the harmonization of the fire risk calculation and perception by Portuguese and Spanish Civil protection authorities is hereby presented. The final results are presented as well. The fire risk index used in this work is the Canadian Fire Weather Index (FWI), which is based on meteorological data. The FWI is limited on its application as it does not take into account other important factors with great effect on the fire appearance and development. The combination of these factors is very complex since, besides the meteorology, it addresses several parameters of different topics, namely: sociology, topography, vegetation and soil cover. Therefore, the meaning of FWI values is different from region to region, according the specific characteristics of each region. In this work, a methodology for FWI calibration based on the number of fire occurrences and on the burnt area in the transboundary regions of Portugal and Spain, in order to assess the fire risk based on calibrated FWI values, is proposed. As previously mentioned, the cooperative firefighting operations require a common perception of the information shared. Therefore, a common classification of the fire risk for the fire events occurred in the transboundary strip is proposed with the objective of harmonizing this type of information. This work is integrated in the ECHO project SpitFire - Spanish-Portuguese Meteorological Information System for Transboundary Operations in Forest Fires, which aims the development of a web platform for the sharing of information and supporting decision tools to be used in international fire events involving Portugal and Spain.

Keywords: data harmonization, FWI, international collaboration, transboundary wildfires

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Authors: Maryam Kheirollahpour, Mahmoud Danaee, Amir Faisal Merican, Asma Ahmad Shariff

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Background: The presence of nonlinearity among the risk factors of eating behavior causes a bias in the prediction models. The accuracy of estimation of eating behaviors risk factors in the primary prevention of obesity has been established. Objective: The aim of this study was to explore the potential of a hybrid model of structural equation modeling (SEM) and Artificial Neural Networks (ANN) to predict eating behaviors. Methods: The Partial Least Square-SEM (PLS-SEM) and a hybrid model (SEM-Artificial Neural Networks (SEM-ANN)) were applied to evaluate the factors affecting eating behavior patterns among university students. 340 university students participated in this study. The PLS-SEM analysis was used to check the effect of emotional eating scale (EES), body shape concern (BSC), and body appreciation scale (BAS) on different categories of eating behavior patterns (EBP). Then, the hybrid model was conducted using multilayer perceptron (MLP) with feedforward network topology. Moreover, Levenberg-Marquardt, which is a supervised learning model, was applied as a learning method for MLP training. The Tangent/sigmoid function was used for the input layer while the linear function applied for the output layer. The coefficient of determination (R²) and mean square error (MSE) was calculated. Results: It was proved that the hybrid model was superior to PLS-SEM methods. Using hybrid model, the optimal network happened at MPLP 3-17-8, while the R² of the model was increased by 27%, while, the MSE was decreased by 9.6%. Moreover, it was found that which one of these factors have significantly affected on healthy and unhealthy eating behavior patterns. The p-value was reported to be less than 0.01 for most of the paths. Conclusion/Importance: Thus, a hybrid approach could be suggested as a significant methodological contribution from a statistical standpoint, and it can be implemented as software to be able to predict models with the highest accuracy.

Keywords: hybrid model, structural equation modeling, artificial neural networks, eating behavior patterns

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Authors: Eric Mensah, Carlos Mensah

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The road maintenance backlogs created as a result of deferred maintenance especially in developing countries has caused considerable deterioration of many road assets. This is usually due to difficulties encountered in selecting and prioritising maintainable roads based on objective criteria rather than some political or other less important criteria. In order to ensure judicious use of limited resources for road maintenance, five factors were identified as the most important criteria for road management within the study area. This was based on the judgements of 40 experts. The results were further used to develop weightings using the Multi-Criteria Decision Process (MCDP) to analyse and select road alternatives according to maintenance goal. Using Geographical Information Systems (GIS), maintainable roads were grouped using the Jenk’s natural breaks to allow for further prioritised in order of importance for display on a dashboard of maps, charts, and tables. This reduces the problems of subjective maintenance and road selections, thereby reducing wastage of resources and easing the maintenance process through an object organised spatial decision support system.

Keywords: decision support, geographical information systems, multi-criteria decision process, weighted sum

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Authors: Clement C. Aladi, Zhaoxia Yi

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This study investigates factors influencing the implementation of flexible curricula in e-learning in Information Systems (IS) higher education. Drawing from curriculum theorists and contemporary literature, and using the Technology, Pedagogy, and Content Knowledge (TPACK) framework, it explores teacher-related challenges and their impact on curriculum flexibility implementation. By using the PLS-SEM, the study uncovers these factors and hopes to contribute to enhancing curriculum flexibility in delivering online and blended learning in IS higher education.

Keywords: flexible curriculum, online learning, e-learning, technology

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Authors: Lanchi Xie, Zhihui Li, Zhigang Li, Guiqiang Wang, Lei Xu, Yuwen Yan

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Image-based facial features can be classified into category recognition features and individual recognition features. Current automated face recognition systems extract a specific feature vector of different dimensions from a facial image according to their pre-trained neural network. However, to improve the efficiency of parameter calculation, an algorithm generally reduces the image details by pooling. The operation will overlook the details concerned much by forensic experts. In our experiment, we adopted a variety of face recognition algorithms based on deep learning, compared a large number of naturally collected face images with the known data of the same person's frontal ID photos. Downscaling and manual handling were performed on the testing images. The results supported that the facial recognition algorithms based on deep learning detected structural and morphological information and rarely focused on specific markers such as stains and moles. Overall performance, distribution of genuine scores and impostor scores, and likelihood ratios were tested to evaluate the accuracy of biometric systems and forensic experts. Experiments showed that the biometric systems were skilled in distinguishing category features, and forensic experts were better at discovering the individual features of human faces. In the proposed approach, a fusion was performed at the score level. At the specified false accept rate, the framework achieved a lower false reject rate. This paper contributes to improving the interpretability of the objective method of facial comparison and provides a novel method for human-machine collaboration in this field.

Keywords: likelihood ratio, automated facial recognition, facial comparison, biometrics

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Authors: Nurunnahar Akter, Elena Kulinskaya, Nicholas Steel, Ilyas Bakbergenuly

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Although Hormone Replacement Therapy (HRT) is an effective treatment in ameliorating menopausal symptoms, it has mixed effects on different health outcomes, increasing, for instance, the risk of breast cancer. Because of this, many symptomatic women are left untreated. Untreated menopausal symptoms may result in other health issues, which eventually put an extra burden and costs to the health care system. All-cause mortality analysis may explain the net benefits and risks of the HRT therapy. However, it received far less attention in HRT studies. This study investigated the impact of HRT on all-cause mortality using electronically recorded primary care data from The Health Improvement Network (THIN) that broadly represents the female population in the United Kingdom (UK). The study entry date for this study was the record of the first HRT prescription from 1984, and patients were followed up until death or transfer to another GP practice or study end date, which was January 2017. 112,354 HRT users (cases) were matched with 245,320 non-users by age at HRT initiation and general practice (GP). The hazards of all-cause mortality associated with HRT were estimated by a parametric Weibull-Cox model adjusting for a wide range of important medical, lifestyle, and socio-demographic factors. The multilevel multiple imputation techniques were used to deal with missing data. This study found that during 32 years of follow-up, combined HRT reduced the hazard ratio (HR) of all-cause mortality by 9% (HR: 0.91; 95% Confidence Interval, 0.88-0.94) in women of age between 46 to 65 at first treatment compared to the non-users of the same age. Age-specific mortality analyses found that combined HRT decreased mortality by 13% (HR: 0.87; 95% CI, 0.82-0.92), 12% (HR: 0.88; 95% CI, 0.82-0.93), and 8% (HR: 0.92; 95% CI, 0.85-0.98), in 51 to 55, 56 to 60, and 61 to 65 age group at first treatment, respectively. There was no association between estrogen-only HRT and women’s all-cause mortality. The findings from this study may help to inform the choices of women at menopause and to further educate the clinicians and resource planners.

Keywords: hormone replacement therapy, multiple imputations, primary care data, the health improvement network (THIN)

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Authors: Chechen Liao, Sheng Yi Lin

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With the popularity of smartphone usage and the flourish of social networks, many people began to use the 'check-in' functions to share their location information and days of live and self-disclosure. In order to increase exposure and awareness, some stores provide discounts and other benefits to attract consumers to 'check-in' in their stores. The purpose of this study was to investigate whether personality traits, intrinsic motivations, extrinsic motivations, and privacy concerns would affect self-disclosure of location for consumers. Research data were collected from 407 individuals that have used Facebook check-in in Taiwan. This study used SmartPLS 2.0 structural equation modeling to validate the model. The results show that information sharing, information storage, enjoyment, self-presentation, get a feedback, economic reward, and keep up with trends had significant positive effects on self-disclosure. While extroversion and openness to use have significant positive effects on self-disclosure, conscientiousness and privacy concerns have significant negative effects on self-disclosure. The results of the study provide academic and practical implications for the future growth of location-based self-disclosure.

Keywords: check-in, extrinsic motivation, intrinsic motivation, personality trait, self-disclosure

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Authors: Boris Ershov

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Depression is the most common mood disorder experienced by patients who have sustained a traumatic brain injury (TBI) and is associated with poorer cognitive functional outcomes. However, in some cases, similar cognitive impairments can also be observed in depression. There is not enough information about the features of the cognitive deficit in patients with TBI in relation to patients with depression. TBI patients without depressive symptoms (TBInD, n25), TBI patients with depressive symptoms (TBID, n31), and 28 patients with bipolar II disorder (BP) were included in the study. There were no significant differences in participants in respect to age, handedness and educational level. The patients clinical status was determined by using Montgomery–Asberg Depression Rating Scale (MADRS). All participants completed a cognitive battery (The Brief Assessment of Cognition in Affective Disorders (BAC-A)). Additionally, the Rey–Osterrieth Complex Figure (ROCF) was used to assess visuospatial construction abilities and visual memory, as well as planning and organizational skills. Compared to BP, TBInD and TBID showed a significant impairments in visuomotor abilities, verbal and visual memory. There were no significant differences between BP and TBID groups in working memory, speed of information processing, problem solving. Interference effect (cognitive inhibition) was significantly greater in TBInD and TBID compared to BP. Memory bias towards mood-related information in BP and TBID was greater in comparison with TBInD. These results suggest that depressive symptoms are associated with impairments some executive functions in combination at decrease of speed of information processing.

Keywords: bipolar II disorder, depression, neurocognitive deficits, traumatic brain injury

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Authors: Pallavi Mane, Nikita Mankar, Shraddha Mazire, Rasika Pashankar

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Content sharing sites are very useful in sharing information and images. However, with the increasing demand of content sharing sites privacy and security concern have also increased. There is need to develop a tool for controlling user access to their shared content. Therefore, we are developing an Adaptive Privacy Policy Prediction (A3P) system which is helpful for users to create privacy settings for their images. We propose the two-level framework which assigns the best available privacy policy for the users images according to users available histories on the site.

Keywords: online information services, prediction, security and protection, web based services

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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: Narayani Sepaha

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In earlier days, the sufferer was burdened to prove the offence as well as to put the offender to punishment. The adversary system of legal procedure was characterized simply by two parties: the prosecution and the defence. With the onset of this system, firstly the judge started acting as a neutral arbitrator, and secondly, the state inadvertently started assuming the lead role and thereby relegated the victims to the position of oblivion. In this process, with the increasing role of police forces and the government, the victims got systematically excluded from the key stages of the case proceedings and were reduced to the stature of a prosecution witness. This paper tries to emphasise the increasing control over the various stages of the trial, by other stakeholders, leading to the marginalization of victims in the trial process. This monopolization has signalled the onset of an era of gross neglect of victims in the whole criminal justice system. This consciousness led some reformists to raise their concerns over the issue, during the early part of the 20th century. They started supporting the efforts which advocated giving prominence to the participation of victims in the trial process. This paved the way for the evolution of the science of victimology. Markedly the innovativeness to work out facts, seek opinions and statements of the victims and reassure that their voice is also heard has ensured the revival of their rightful roles in the justice delivery system. Many countries, like the US, have set an example by acknowledging the advantages of participation of victims in trials like in the proceedings of the Ariel Castro Kidnappings of Cleveland, Ohio and enacting laws for protecting their rights within the framework of the legal system to ensure speedy and righteous delivery of justice in some of the most complicated cases. An attempt has been made to flag that the accused have several rights in contrast to the near absence of separate laws for victims of crime, in India. It is sad to note that, even in the initial process of registering a crime the victims are subjected to the mercy of the officers in charge and thus begins the silent suffering of these victims, which continues throughout the process of their trial. The paper further contends, that the degree of victim participation in trials and its impact on the outcomes, can be debated and evaluated, but its potential to alter their position and make them regain their lost status cannot be ignored. Victim participation in trial proceedings will help the court in perceiving the facts of the case in a better manner and in arriving at a balanced view of the case. This will not only serve to protect the overall interest of the victims but will act to reinforce the faith in the criminal justice delivery system. It is pertinent to mention that there is an urgent need to review the accused centric prosecution system and introduce appropriate amendments so that the marginalization of victims comes to an end.

Keywords: victim participation, criminal justice, India, trial, marginalised

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Authors: Saikat Majumdar, D. C. Kalita

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The Agriculture sector plays an important role in the rural economy of India. It is the backbone of our Indian economy and is the dominant sector in terms of employment and livelihood. Agriculture still contributes significantly to export earnings and is an important source of raw materials as well as of demand for many industrial products particularly fertilizers, pesticides, agricultural implements and a variety of consumer goods, etc. The performance of the agricultural sector influences the growth of Indian economy. According to the 2011 Agricultural Census of India, an estimated 61.5 percentage of rural populations are dependent on agriculture. Proper Agricultural infrastructure has the potential to transform the existing traditional agriculture into a most modern, commercial and dynamic farming system in India through its diffusion of technology. The rate of adoption of modern technology reflects the progress of development in agricultural sector. The adoption of any improved agricultural technology is also dependent on the development of road infrastructure or road network. The present study was consisting of 300 sample farmers out which 150 samples was taken from the developed area and rest 150 samples was taken from underdeveloped area. The samples farmers under develop and underdeveloped areas were collected by using Multistage Random Sampling procedure. In the first stage, North 24 Parganas District have been selected purposively. Then from the district, one developed and one underdeveloped block was selected randomly. In the third phase, 10 villages have been selected randomly from each block. Finally, from each village 15 sample farmers was selected randomly. The extents of adoption of technology in different areas were calculated through various parameters. These are percentage area under High Yielding Variety Cereals, percentage area under High Yielding Variety pulses, area under hybrids vegetables, irrigated area, mechanically operated area, amount spent on fertilizer and pesticides, etc. in both developed and underdeveloped areas of North 24 Parganas District, West Bengal. The percentage area under High Yielding Variety Cereals in the developed and underdeveloped areas was 34.86 and 22.59. 42.07 percentages and 31.46 percentages for High Yielding Variety pulses respectively. In the case the area under irrigation it was 57.66 and 35.71 percent while for the mechanically operated area it was 10.60 and 3.13 percent respectively in developed and underdeveloped areas of North 24 Parganas district, West Bengal. It clearly showed that the extent of adoption of technology was significantly higher in the developed area over underdeveloped area. Better road network system helps the farmers in increasing his farm income, farm assets, cropping intensity, marketed surplus and the rate of adoption of new technology. With this background, an attempt is made in this paper to study the impact of Agricultural Infrastructure on the adoption of modern technology in agriculture in North 24 Parganas District, West Bengal.

Keywords: agricultural infrastructure, adoption of technology, farm income, road network

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Authors: Mohamed Zaidour

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In this summary, we are going to look in brief at the bridges and their building and construction on most roads and we have followed a simple method to explain each field clearly because the geographical and climatic diversity of an area leads to different methods and types of roads and installation engineering in other areas In mountain areas we need to build retaining walls in areas of rain. It needs to construct ferries to discharge water from roads in areas of temporary or permanent rivers. There is a need to build bridges and construct road installations in the process of collecting the necessary information, such as soil type. This information needs it, engineer, when designing the constructor and in this section, we will identify the types and methods of calculation bridge columns rules phrases the walls are chock.

Keywords: bridges, buildings, concrete, constructions, roads

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Authors: Pakinee Aimmanee, Phoom Chokratsamesiri

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Search engine has become an essential tool nowadays for people to search for their needed information on the internet. In this work, we evaluate the performance of the search engine from three factors: the keyword frequency, the number of inbound links, and the difficulty of the keyword. The evaluations are based on the ranking position and the number of days that Google has seen or detect the webpage. We find that the keyword frequency and the difficulty of the keyword do not affect the Google ranking where the number of inbound links gives remarkable improvement of the ranking position. The optimal number of inbound links found in the experiment is 10.

Keywords: SEO, information retrieval, web search, knowledge technologies

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Authors: H. K. V. Narayan

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This study was conducted at Tata Memorial Hospital (TMH), Mumbai, India. The study was to evaluate the impact of adapting Smart Card (SC) for clinical and business transactions in order to reduce Lead times and to enforce business rules of the hospital. The objective for implementing the Smart Card was to improve the patient perception of quality in terms of structures process and outcomes and also to improve the productivity of the Institution. The Smart Card was implemented in phases from 2011 and integrated with the Hospital Information System (HIS/EMR). The implementation was a learning curve for all the stake holders as software obviated the need to use hardcopies of transactions. The acceptability to the stake holders was challenge in change management. The study assessed the impact 3 years into the implementation and the observed trends have suggested that it has decreased the lead times for services and increased the no of transactions and thereby the productivity. Patients who used to complain of multiple queues and cumbersome transactions now compliment the administration for effective use of Information and Communication Technology.

Keywords: smart card, high availability of health care information, reduction in potential medical errors due to elimination of transcription errors, reduction in no of queues, increased transactions, augmentation of revenue

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Authors: Chao-Ton Su, Li-Fei Chen

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The parameter design is crucial to improving the uniformity of a product or process. In the product design stage, parameter design aims to determine the optimal settings for the parameters of each element in the system, thereby minimizing the functional deviations of the product. In the process design stage, parameter design aims to determine the operating settings of the manufacturing processes so that non-uniformity in manufacturing processes can be minimized. The parameter design, trying to minimize the influence of noise on the manufacturing system, plays an important role in the high-tech companies. Taiwan has many well-known high-tech companies, which show key roles in the global economy. Quality remains the most important factor that enables these companies to sustain their competitive advantage. In Taiwan however, many high-tech companies face various quality problems. A common challenge is related to root causes and defect patterns. In the R&D stage, root causes are often unknown, and defect patterns are difficult to classify. Additionally, data collection is not easy. Even when high-volume data can be collected, data interpretation is difficult. To overcome these challenges, high-tech companies in Taiwan use more advanced quality improvement tools. In addition to traditional statistical methods and quality tools, the new trend is the application of powerful tools, such as neural network, fuzzy theory, data mining, industrial engineering, operations research, and innovation skills. In this study, several examples of optimizing the parameter settings for the manufacturing process in Taiwan’s tech companies will be presented to illustrate proposed approach’s effectiveness. Finally, a discussion of using traditional experimental design versus the proposed approach for process optimization will be made.

Keywords: quality engineering, parameter design, neural network, genetic algorithm, experimental design

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Authors: Hossein Bazmara, Kaamran Raahemifar, Mostafa Sefidgar, Madjid Soltani

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Angiogenesis is formation of new blood vessels from existing vessels. Due to flow of blood in vessels, during angiogenesis, blood flow plays an important role in regulating the angiogenesis process. Multiple mathematical models of angiogenesis have been proposed to simulate the formation of the complicated network of capillaries around a tumor. In this work, a multi-scale model of angiogenesis is developed to show the effect of blood flow on capillaries and network formation. This model spans multiple temporal and spatial scales, i.e. intracellular (molecular), cellular, and extracellular (tissue) scales. In intracellular or molecular scale, the signaling cascade of endothelial cells is obtained. Two main stages in development of a vessel are considered. In the first stage, single sprouts are extended toward the tumor. In this stage, the main regulator of endothelial cells behavior is the signals from extracellular matrix. After anastomosis and formation of closed loops, blood flow starts in the capillaries. In this stage, blood flow induced signals regulate endothelial cells behaviors. In cellular scale, growth and migration of endothelial cells is modeled with a discrete lattice Monte Carlo method called cellular Pott's model (CPM). In extracellular (tissue) scale, diffusion of tumor angiogenic factors in the extracellular matrix, formation of closed loops (anastomosis), and shear stress induced by blood flow is considered. The model is able to simulate the formation of a closed loop and its extension. The results are validated against experimental data. The results show that, without blood flow, the capillaries are not able to maintain their integrity.

Keywords: angiogenesis, endothelial cells, multi-scale model, cellular Pott's model, signaling cascade

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Authors: Suchitra Chnadrashekhar

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Earlier looked as a support function in an organization information technology has now become a critical utility to manage their daily operations. Organizations are processing huge amount of data which was unimaginable few decades before. This has opened the opportunity for IT sector to help industries across domains to handle the data in the most intelligent manner. Presence of IT has been a leverage for the Oil & Gas industry to store, manage and process the data in most efficient way possible thus deriving the economic value in their day-to-day operations. Proper synchronization between Operational data system and Information Technology system is the need of the hour. Predictive analytics supports oil and gas companies by addressing the challenge of critical equipment performance, life cycle, integrity, security, and increase their utilization. Predictive analytics go beyond early warning by providing insights into the roots of problems. To reach their full potential, oil and gas companies need to take a holistic or systems approach towards asset optimization and thus have the functional information at all levels of the organization in order to make the right decisions. This paper discusses how the use of predictive analysis in oil and gas industry is redefining the dynamics of this sector. Also, the paper will be supported by real time data and evaluation of the data for a given oil production asset on an application tool, SAS. The reason for using SAS as an application for our analysis is that SAS provides an analytics-based framework to improve uptimes, performance and availability of crucial assets while reducing the amount of unscheduled maintenance, thus minimizing maintenance-related costs and operation disruptions. With state-of-the-art analytics and reporting, we can predict maintenance problems before they happen and determine root causes in order to update processes for future prevention.

Keywords: hydrocarbon, information technology, SAS, predictive analytics

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Authors: Aditya Verma

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E-voting using blockchain provides us with a distributed system where data is present on each node present in the network and is reliable and secure too due to its immutability property. This work compares various blockchain consensus algorithms used for e-voting applications in the past, based on performance and node scalability, and chooses the optimal one and improves on one such previous implementation by proposing solutions for the loopholes of the optimally working blockchain consensus algorithm, in our chosen application, e-voting.

Keywords: blockchain, parallel bft, consensus algorithms, performance

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Authors: Chun-Min Lin, Yuh-Jen Wu, Ching-Ting Chung

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The formulation of tourism policies requires objective academic research and evidence as support, especially research from local academia. Taiwan is a small island, and its economic growth relies heavily on tourism revenue. Taiwanese government has been devoting to the promotion of the tourism industry over the past few decades. Scientific research outcomes by Taiwanese scholars may and will help lay the foundations for drafting future tourism policy by the government. In this study, a total of 120 full journal articles published between 2008 and 2016 from the Journal of Tourism and Leisure Studies (JTSL) were examined to explore the scientific research trend of tourism study in Taiwan. JTSL is one of the most important Taiwanese journals in the tourism discipline which focuses on tourism-related issues and uses traditional Chinese as the study language. The method of co-word analysis from bibliometrics approaches was employed for semantic analysis in this study. When analyzing Chinese words and phrases, word segmentation analysis is a crucial step. It must be carried out initially and precisely in order to obtain meaningful word or word chunks for further frequency calculation. A word segmentation system basing on N-gram algorithm was developed in this study to conduct semantic analysis, and 100 groups of meaningful phrases with the highest recurrent rates were located. Subsequently, co-word analysis was employed for semantic classification. The results showed that the themes of tourism research in Taiwan in recent years cover the scope of tourism education, environmental protection, hotel management, information technology, and senior tourism. The results can give insight on the related issues and serve as a reference for tourism-related policy making and follow-up research.

Keywords: bibliometrics, co-word analysis, word segmentation, tourism research, policy

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Authors: Joseph Gear, Yue Xu, Ernest Foo, Praveen Gauravaran, Zahra Jadidi, Leonie Simpson

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Deep learning methods have been seeing an increasing application to the long-standing security research goal of automatic vulnerability detection for source code. Attention, however, must still be paid to the task of producing vector representations for source code (code embeddings) as input for these deep learning models. Graphical representations of code, most predominantly Abstract Syntax Trees and Code Property Graphs, have received some use in this task of late; however, for very large graphs representing very large code snip- pets, learning becomes prohibitively computationally expensive. This expense may be reduced by intelligently pruning this input to only vulnerability-relevant information; however, little research in this area has been performed. Additionally, most existing work comprehends code based solely on the structure of the graph at the expense of the information contained by the node in the graph. This paper proposes Semantic-enhanced Code Embedding for Vulnerability Discovery (SCEVD), a deep learning model which uses semantic-based feature selection for its vulnerability classification model. It uses information from the nodes as well as the structure of the code graph in order to select features which are most indicative of the presence or absence of vulnerabilities. This model is implemented and experimentally tested using the SARD Juliet vulnerability test suite to determine its efficacy. It is able to improve on existing code graph feature selection methods, as demonstrated by its improved ability to discover vulnerabilities.

Keywords: code representation, deep learning, source code semantics, vulnerability discovery

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Authors: Sajid Bin Doza

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A town or a city contributes a lot to human mankind. City evolves memory, ambition, frustration and achievement. The city is something that offers life, as the character of the city is. A city is having confined image to the human being. Time place and matter generate this vive, city celebrates with its inhabitant, belongs and to care for each other. Apart from all these; although city and settlements are the contentious and changing phenomenon; the origin of the city in the very delta land started with unique and strategic sequences. Religious belief, topography, availability of resource and connection with commercial hub make the potential of the settlement. Ancient cities of Bengal are not the exception from these phenomenologies. From time immemorial; Bengal is enriched with numerous cities and notorious settlements. These cities and settlements were connected with other inland ports and Bengal became an important trade route, trailed by the Riverine connections. The delta land formation is valued for its geographic situation, consequences of this position; a new story or a new conception could be found in origin of an ancient city. However, the objective of this research is to understand the origin and spirit of the ancient city of Bengal, the research would also try to unfold the authentic and rational meaning of soul of the city, this research addresses the interest to elaborate the soul of the ancient sites of Riverine Delta. As rivers used to have the common character in this very landform; river supported community generated as well. River gives people wealth, sometimes fall us in sorrow. The river provides us commerce and trading. River gives us faith and religion. All these potentials have evolved from the Riverine excel. So the research would approach thoroughly to justify the riverine value as the soul for the ancient cities of Bengal. Cartographic information and illustration would be the preferred language for this research. Preferably, the historic mapping would be the unique folio of this study.

Keywords: memory of the city, riverine network, ancient cities, cartographic mapping, settlement pattern

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Authors: Michael Lousis

Abstract:

This research study is concerned with learner’s errors on Arithmetic and Algebra. The data resulted from a broader international comparative research program called Kassel Project. However, its conceptualisation differed from and contrasted with that of the main program, which was mostly based on socio-demographic data. The way in which the research study was conducted, was not dependent on the researcher’s discretion, but was absolutely dictated by the nature of the problem under investigation. This is because the phenomenon of learners’ mathematical errors is due neither to the intentions of learners nor to institutional processes, rules and norms, nor to the educators’ intentions and goals; but rather to the way certain information is presented to learners and how their cognitive apparatus processes this information. Several approaches for the study of learners’ errors have been developed from the beginning of the 20th century, encompassing different belief systems. These approaches were based on the behaviourist theory, on the Piagetian- constructivist research framework, the perspective that followed the philosophy of science and the information-processing paradigm. The researcher of the present study was forced to disclose the learners’ course of thinking that led them in specific observable actions with the result of showing particular errors in specific problems, rather than analysing scripts with the students’ thoughts presented in a written form. This, in turn, entailed that the choice of methods would have to be appropriate and conducive to seeing and realising the learners’ errors from the perspective of the participants in the investigation. This particular fact determined important decisions to be made concerning the selection of an appropriate framework for analysing the mathematical errors and giving explanations. Thus the rejection of the belief systems concerning behaviourism, the Piagetian-constructivist, and philosophy of science perspectives took place, and the information-processing paradigm in conjunction with the philosophy of mind were adopted as a general account for the elaboration of data. This paper explains why these decisions were appropriate and beneficial for conducting the present study and for the establishment of the ensued thesis. Additionally, the reasons for the adoption of the information-processing paradigm in conjunction with the philosophy of mind give sound and legitimate bases for the development of future studies concerning mathematical error analysis are explained.

Keywords: advantages-disadvantages of theoretical prospects, behavioral prospect, critical evaluation of theoretical prospects, error analysis, information-processing paradigm, opting for the appropriate approach, philosophy of science prospect, Piagetian-constructivist research frameworks, review of research in mathematical errors

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Authors: Muganyizi Jonas Bisheko, G. Rejikumar

Abstract:

Reducing post-harvest losses could be a sustainable solution to enhance the food and income security of smallholder farmers in developing countries. While various research institutions have come up with a number of innovative post-harvest technologies for reducing post-harvest losses, most of them have not been extensively adopted by smallholder farmers. Despite this gap, the synthesized information about the major constraints of post-harvest technology is scarce. This study has been conducted to fill this gap and show the implications of the findings for future post-harvest research. The developed search strategy retrieved 2201 studies. However, after excluding duplicates, title, abstract and full article screening, a total of 41 documents were identified. The major findings are: (i) there is an outstanding deficiency of systematic evidence of the effect of climate change, off-farm income and sources of post-harvest information on the adoption of improved post-harvest technologies; (ii) there is very limited information on adoption constraints pertaining to matters of policy, rules and regulations; (iii) there is very thin literature on behavioral constraints associated with limited adoption of improved post-harvest technologies; (iv) most of the studies focused on post-harvest storage technologies (47%) followed by overall post-harvest management practices (25%), processing technologies (19%) and packaging technologies (3%). Much of the information was found on Cereals (58%), especially maize (44%); (v) geographically, Sub-Saharan Africa accounted for 79% of the reviewed interventions, while South Asia occupied only 21%. The findings of this review are intended to guide various post-harvest technologists and decision-makers in addressing the challenge of huge post-harvest losses.

Keywords: constraints, post-harvest loss, post-harvest technology , smallholder farmer

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Authors: Naima Fatehi

Abstract:

The paper reports on 107 medicinal plants, traditionally used in the South-West of Algeria (Bechar region). The information has been documented by interviewing traditional herbalists, various elderly men and women following different ethnobotanical methods. Ethnobotanical data was arranged alphabetically by botanical name, followed by family name, vernacular name, and part used. The present paper represents significant ethnobotanical information on medical plants used extensively in Bechar region for treating various diseases and provides baseline data for future pharmacological and phytochemical studies.

Keywords: medicinal plants, ethnobotanical survey, South-West Algeria, Bechar region

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Authors: Rosa Hendijani, Amir Ghadimi Herfeh

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Nutrition labels are diet-related health policies. They help individuals improve food-choice decisions and reduce intake of calories and unhealthy food elements, like cholesterol. However, many individuals do not pay attention to nutrition labels or fail to appropriately understand them. According to the literature, thinking and cognitive styles can have significant effects on attention to nutrition labels. According to the author's knowledge, the effect of global/local processing on attention to nutrition labels have not been previously studied. Global/local processing encourages individuals to attend to the whole/specific parts of an object and can have a significant impact on people's visual attention. In this study, this effect was examined with an experimental design using the eye-tracking technique. The research hypothesis was that individuals with local processing would pay more attention to nutrition labels, including nutrition tables and traffic lights. An experiment was designed with two conditions: global and local information processing. Forty participants were randomly assigned to either global or local conditions, and their processing style was manipulated accordingly. Results supported the hypothesis for nutrition tables but not for traffic lights.

Keywords: eye-tracking, nutrition labelling, global/local information processing, individual differences

Procedia PDF Downloads 159

Authors: Daud Muhammad

Abstract:

Introduction: Ankle radiographs are frequently requested in Emergency Departments (ED) for patients presenting with traumatic ankle pain. The Ottawa Ankle Rules (OAR) serve as a clinical guideline to determine the necessity of these radiographs, aiming to reduce unnecessary imaging. This audit was conducted to evaluate the adequacy of clinical information provided in radiograph requests in relation to the OAR. Methods: A retrospective analysis was performed on 50 consecutive ankle radiograph requests under ED clinicians' names for patients aged above 5 years, specifically excluding follow-up radiographs for known fractures. The study assessed whether the provided clinical information met the criteria outlined by the OAR. Results: The audit revealed that none of the 50 radiograph requests contained sufficient information to satisfy the Ottawa Ankle Rules. Furthermore, 10 out of the 50 radiographs (20%) identified fractures. Discussion: The findings indicate a significant lack of adherence to the OAR, suggesting potential overuse of radiography and unnecessary patient exposure to radiation. This non-compliance may also contribute to increased healthcare costs and resource utilization, as well as possible delays in diagnosis and treatment. Recommendations: To address these issues, the following recommendations are proposed: (1) Education and Training: Enhance awareness and training among ED clinicians regarding the OAR. (2) Standardised Request Forms: Implement changes to imaging request forms to mandate relevant information according to the OAR. (3) Scan Vetting: Promote awareness among radiographers to discuss the appropriateness of scan requests with clinicians. (4) Regular re-audits should be conducted to monitor improvements in compliance.

Keywords: Ottawa ankle rules, ankle radiographs, emergency department, traumatic pain

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Authors: Muqaddas Javed, Muhammad Hanif

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The generalized multivariate ratio and regression type estimators for population mean are suggested under multi-phase stratified systematic sampling (MPSSS) using multi auxiliary information. Estimators are developed under the two different situations of availability of auxiliary information. The expressions of bias and mean square error (MSE) are developed. Special cases of suggested estimators are also discussed and simulation study is conducted to observe the performance of estimators.

Keywords: generalized estimators, multi-phase sampling, stratified random sampling, systematic sampling

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Authors: Robert L. Burdett, Bayan Bevrani

Abstract:

Analytical techniques for measuring and planning railway capacity expansion activities have been considered in this article. A preliminary mathematical framework involving track duplication and section sub divisions is proposed for this task. In railways, these features have a great effect on network performance and for this reason they have been considered. Additional motivations have also arisen from the limitations of prior models that have not included them.

Keywords: capacity analysis, capacity expansion, railways, track sub division, track duplication

Procedia PDF Downloads 359