Search results for: k-means clustering based feature weighting

Authors: Naim Suleyman Ting, Yakup Sahin, Ismail Aksoy

Abstract:

This paper presents a zero voltage transition-zero current transition (ZVT-ZCT)-PWM DC-DC boost converter with direct power transfer. In this converter, the main switch turns on with ZVT and turns off with ZCT. The auxiliary switch turns on and off with zero current switching (ZCS). The main diode turns on with ZVS and turns off with ZCS. Besides, the additional current or voltage stress does not occur on the main device. The converter has features as simple structure, fast dynamic response and easy control. Also, the proposed converter has direct power transfer feature as well as excellent soft switching techniques. In this study, the operating principle of the converter is presented and its operation is verified for 1 kW and 100 kHz model.

Keywords: direct power transfer, boost converter, zero-voltage transition, zero-current transition

Procedia PDF Downloads 797

Authors: Magdalena Wilk-Kozubek, Magdalena Rowińska, Krzysztof Rola, Joanna Cybińska

Abstract:

Leuco dye-based thermochromic systems are classified as intelligent materials because they exhibit thermally induced color changes. Thanks to this feature, they are mainly used as temperature sensors in many industrial sectors. For example, placing a thermochromic material on a chemical reactor may warn about exceeding the maximum permitted temperature for a chemical process. Usually two components, a color former and a developer are needed to produce a system with irreversible color change. The color former is an electron donating (proton accepting) compound such as fluoran leuco dye. The developer is an electron accepting (proton donating) compound such as organic carboxylic acid. When the developer melts, the color former - developer complex is created and the termochromic system becomes colored. Typically, the melting point of the applied developer determines the temperature at which the color change occurs. When the lactone ring of the color former is closed, then the dye is in its colorless state. The ring opening, induced by the addition of a proton, causes the dye to turn into its colored state. Since the color former and the developer are often solid, they can be incorporated into polymer films to facilitate their practical use in industry. The objective of this research was to fabricate a leuco dye-based termochromic system that will irreversibly change color after reaching the temperature of 100°C. For this purpose, benzofluoran leuco dye (as color former) and phenoxyacetic acid (as developer with a melting point of 100°C) were introduced into the polymer films during the drop casting process. The film preparation process was optimized in order to obtain thin films with appropriate properties such as transparency, flexibility and homogeneity. Among the optimized factors were the concentration of benzofluoran leuco dye and phenoxyacetic acid, the type, average molecular weight and concentration of the polymer, and the type and concentration of the surfactant. The selected films, containing benzofluoran leuco dye and phenoxyacetic acid, were combined by mild heat treatment. Structural characterization of single and combined films was carried out by FTIR spectroscopy, morphological analysis was performed by optical microscopy and SEM, phase transitions were examined by DSC, color changes were investigated by digital photography and UV-Vis spectroscopy, while emission changes were studied by photoluminescence spectroscopy. The resulting thermochromic system is colorless at room temperature, but after reaching 100°C the developer melts and it turns irreversibly pink. Therefore, it could be used as an additional sensor to warn against boiling of water in power plants using water cooling. Currently used electronic temperature indicators are prone to faults and unwanted third-party actions. The sensor constructed in this work is transparent, thanks to which it can be unnoticed by an outsider and constitute a reliable reference for the person responsible for the apparatus.

Keywords: color developer, leuco dye, thin film, thermochromism

Procedia PDF Downloads 81

Authors: Somayeh Zeinali

Abstract:

A component is generally defined as a piece of executable software with a published interface. Component-based software engineering (CBSE) has become recognized as a new sub-discipline of software engineering. In the component-based software development, components cannot be completely secure and thus easily become vulnerable. Some researchers have investigated this issue and proposed approaches to detect component intrusions or protect distributed components. Software security also refers to the process of creating software that is considered secure.The terms “dependability”, “trustworthiness”, and “survivability” are used interchangeably to describe the properties of software security.

Keywords: component-based software development, component-based software engineering , software security attributes, dependability, component

Procedia PDF Downloads 537

Authors: Thanh-Phong Dao, Shyh-Chour Huang

Abstract:

This study presents a quasi-zero stiffness (QZS) vibration isolator using flexure-based spring mechanisms which afford both negative and positive stiffness elements, which enable self-adjustment. The QZS property of the isolator is achieved at the equilibrium position. A nonlinear mathematical model is then developed, based on the pre-compression of the flexure-based spring mechanisms. The dynamics are further analyzed using the Harmonic Balance method. The vibration attention efficiency is illustrated using displacement transmissibility, which is then compared with the corresponding linear isolator. The effects of parameters on performance are also investigated by numerical solutions. The flexure-based spring mechanisms are subsequently designed using the concept of compliant mechanisms, with evaluation by ANSYS software, and simulations of the QZS isolator.

Keywords: vibration isolator, quasi-zero stiffness, flexure-based spring mechanisms, compliant mechanism

Procedia PDF Downloads 439

Authors: Mohamed Mounir Tellache, Hiroyuki Kambara, Yasuharu Koike, Makoto Miyakoshi, Natsue Yoshimura

Abstract:

This study explores the practicality of using electroencephalographic (EEG) independent components to predict eight-direction finger movements in pseudo-real-time. Six healthy participants with individual-head MRI images performed finger movements in eight directions with two different arm configurations. The analysis was performed in two stages. The first stage consisted of using independent component analysis (ICA) to separate the signals representing brain activity from non-brain activity signals and to obtain the unmixing matrix. The resulting independent components (ICs) were checked, and those reflecting brain-activity were selected. Finally, the time series of the selected ICs were used to predict eight finger-movement directions using Sparse Logistic Regression (SLR). The second stage consisted of using the previously obtained unmixing matrix, the selected ICs, and the model obtained by applying SLR to classify a different EEG dataset. This method was applied to two different settings, namely the single-participant level and the group-level. For the single-participant level, the EEG dataset used in the first stage and the EEG dataset used in the second stage originated from the same participant. For the group-level, the EEG datasets used in the first stage were constructed by temporally concatenating each combination without repetition of the EEG datasets of five participants out of six, whereas the EEG dataset used in the second stage originated from the remaining participants. The average test classification results across datasets (mean ± S.D.) were 38.62 ± 8.36% for the single-participant, which was significantly higher than the chance level (12.50 ± 0.01%), and 27.26 ± 4.39% for the group-level which was also significantly higher than the chance level (12.49% ± 0.01%). The classification accuracy within [–45°, 45°] of the true direction is 70.03 ± 8.14% for single-participant and 62.63 ± 6.07% for group-level which may be promising for some real-life applications. Clustering and contribution analyses further revealed the brain regions involved in finger movement and the temporal aspect of their contribution to the classification. These results showed the possibility of using the ICA-based method in combination with other methods to build a real-time system to control prostheses.

Keywords: brain-computer interface, electroencephalography, finger motion decoding, independent component analysis, pseudo real-time motion decoding

Procedia PDF Downloads 123

Authors: Piyanut Sujit

Abstract:

The purposes of this study were to: 1) create knowledge and develop web based instruction on the puppet show, 2) evaluate the effectiveness of the web based instruction on the puppet show by using the criteria of 80/80, and 3) compare and analyze the achievement of the students before and after learning with web based instruction on the puppet show. The population of this study included 53 students in the Program of Library and Information Sciences who registered in the subject of Reading and Reading Promotion in semester 1/2011, Suansunandha Rajabhat University. The research instruments consisted of web based instruction on the puppet show, specialist evaluation form, achievement test, and tests during the lesson. The research statistics included arithmetic mean, variable means, standard deviation, and t-test in SPSS for Windows. The results revealed that the effectiveness of the developed web based instruction was 84.67/80.47 which was higher than the set criteria at 80/80. The student achievement before and after learning showed statistically significant difference at 0.05 as in the hypothesis.

Keywords: puppet, puppet show, web based instruction, library and information sciences

Procedia PDF Downloads 351

Authors: A. Dinelka Panagoda, Bathiya Bandara, Chamod Wijetunga, Chathura Malinda, Lakmal Rupasinghe, Chethana Liyanapathirana

Abstract:

This research takes us forward with the concepts of Federated Learning and Software-Defined Networking (SDN) to introduce an efficient malware detection technique and provide a mitigation mechanism to give birth to a resilient and automated healthcare sector network system by also adding the feature of extended privacy preservation. Due to the daily transformation of new malware attacks on hospital Integrated Clinical Environment (ICEs), the healthcare industry is at an undefinable peak of never knowing its continuity direction. The state of blindness by the array of indispensable opportunities that new medical device inventions and their connected coordination offer daily, a factor that should be focused driven is not yet entirely understood by most healthcare operators and patients. This solution has the involvement of four clients in the form of hospital networks to build up the federated learning experimentation architectural structure with different geographical participation to reach the most reasonable accuracy rate with privacy preservation. While the logistic regression with cross-entropy conveys the detection, SDN comes in handy in the second half of the research to stack up the initial development phases of the system with malware mitigation based on policy implementation. The overall evaluation sums up with a system that proves the accuracy with the added privacy. It is no longer needed to continue with traditional centralized systems that offer almost everything but not privacy.

Keywords: software-defined network, federated learning, privacy, integrated clinical environment, decentralized learning, malware detection, malware mitigation

Procedia PDF Downloads 155

Authors: Asghar Zamani, Mostafa Falahmorad

Abstract:

Virtualization is established to combine and use the unique capabilities of employees to increase productivity and agility to provide services regardless of location. Adapting to fast and continuous change and getting maximum access to human resources are reasons why virtualization is happening. The distance problem is solved by information. Flexibility is the most important feature of virtualization, and information will be the main focus of virtualized companies. In this research, we used the Covid-19 opportunity window to assess the productivity of the companies that had been going through more virtualized management before the Covid-19 in comparison with those that just started planning on developing infrastructures on virtual management after the crises of pandemic occurred. The research process includes financial (profitability and customer satisfaction) and behavioral (organizational culture and reluctance to change) metrics assessment. In addition to financial and CRM KPIs, a questionnaire is devised to assess how manager and employees’ attitude has been changing towards the migration to virtualization. The sample companies and questions are selected by asking from experts in the IT industry of Iran. In this article, the conclusion is that companies open to virtualization based on accurate strategic planning or willing to pay to train their employees for virtualization before the pandemic are more agile in adapting to change and moving forward in recession. The prospective companies in this research, not only could compensate for the short period loss from the first shock of the Covid-19, but they could also foresee new needs of their customer sooner than other competitors, resulting in the need to employ new staff for executing the emerging demands. Findings were aligned with the literature review. Results can be a wake-up call for business owners especially in developing countries to be more resilient toward modern management styles instead of continuing with traditional ones.

Keywords: virtual management, virtual organization, competitive advantage, KPI, profit

Procedia PDF Downloads 69

Authors: Pablo Oteiza, Ricardo Alvarez, Mehrdad Pirnia, Fuat Can

Abstract:

To effectively combat climate change, many countries around the world have committed to a decarbonisation of their electricity, along with promoting a large-scale integration of renewable energy sources (RES). While this trend represents a unique opportunity to effectively combat climate change, achieving a sound and cost-efficient energy transition towards low-carbon power systems poses significant challenges for the multi-year Transmission Network Expansion Planning (TNEP) problem. The objective of the multi-year TNEP is to determine the necessary network infrastructure to supply the projected demand in a cost-efficient way, considering the evolution of the new generation mix, including the integration of RES. The rapid integration of large-scale RES increases the variability and uncertainty in the power system operation, which in turn increases short-term flexibility requirements. To meet these requirements, flexible generating technologies such as energy storage systems must be considered within the TNEP as well, along with proper models for capturing the operational challenges of future power systems. As a consequence, TNEP formulations are becoming more complex and difficult to solve, especially for its application in realistic-sized power system models. To meet these challenges, there is an increasing need for developing efficient algorithms capable of solving the TNEP problem with reasonable computational time and resources. In this regard, a promising research area is the use of artificial intelligence (AI) techniques for solving large-scale mixed-integer optimization problems, such as the TNEP. In particular, the use of AI along with mathematical optimization strategies based on decomposition has shown great potential. In this context, this paper presents an efficient algorithm for solving the multi-year TNEP problem. The algorithm combines AI techniques with Column Generation, a traditional decomposition-based mathematical optimization method. One of the challenges of using Column Generation for solving the TNEP problem is that the subproblems are of mixed-integer nature, and therefore solving them requires significant amounts of time and resources. Hence, in this proposal we solve a linearly relaxed version of the subproblems, and trained a binary classifier that determines the value of the binary variables, based on the results obtained from the linearized version. A key feature of the proposal is that we integrate the binary classifier into the optimization algorithm in such a way that the optimality of the solution can be guaranteed. The results of a study case based on the HRP 38-bus test system shows that the binary classifier has an accuracy above 97% for estimating the value of the binary variables. Since the linearly relaxed version of the subproblems can be solved with significantly less time than the integer programming counterpart, the integration of the binary classifier into the Column Generation algorithm allowed us to reduce the computational time required for solving the problem by 50%. The final version of this paper will contain a detailed description of the proposed algorithm, the AI-based binary classifier technique and its integration into the CG algorithm. To demonstrate the capabilities of the proposal, we evaluate the algorithm in case studies with different scenarios, as well as in other power system models.

Keywords: integer optimization, machine learning, mathematical decomposition, transmission planning

Procedia PDF Downloads 68

Authors: Ameen Alahdal

Abstract:

This paper investigates copular constructions in Raimi Yemeni Arabic (RYA). The aim of the paper is actually twofold. First it explores the types of copular constructions in Raimi Yemeni Arabic, a variety of Arabic that has not attracted a lot of attention. In this connection, the paper shows that RYA manifests ‘bare’, verbal and pronominal/PRON copular constructions, just like other varieties of Arabic and indeed other Semitic languages like Hebrew. The sentences below from RYA represent the three constructions, respectively. (1) a. nada Hilwah Nada pretty.3sf ‘Nada is pretty’ b. kan al-banat hina was the-girls here ‘The girls were here c. ali hu-l mudiir Ali he-the manager ‘Ali is the manager’ Interestingly, in addition to these common types of copular constructions, RYA seems to exhibit dual copula sentences, a construction that features both a pronominal copula and a verbal copula. Such a construction is attested neither in Standard Arabic nor in other modern varieties of Arabic such as Lebanese, Moroccan, Egyptian, Jordanian. Remarkably, dual copular sentences do not appear even in other dialects of Yemeni Arabic such as Sanaani, Adeni and Tehami. (2) is an example. (2) maha kan-ih mudarrisah maha was-she teacher.3sf ‘Maha was a teacehr’ Second, the paper considers the cartography of subject positions in copular constructions proposed by Shlonsky and Rizzi (2018). Different copular constructions seem to involve different subject positions (which might eventually correlate with different interpretations – not our concern in this paper). Here, it is argued that in a bare copular sentence, as in (1a), RYA might exploit two criterial subject positions (in Rizzi’s sense), in addition to the canonical Spec,TP position. Under mainstream minimalist assumption, a copular sentence is analyzed as a PredP. Thus, in addition to the PredP-related thematic subject position, a criterial subject position is posited outside of PredP. (3) below represents the cartography of subject positions in a bare copular construction. (3) [……..DP subj PredP DP Pred DP/AP/PP ] In PRON sentences, as exemplified in (1c), another two subject positions are postulated high in the clause, particularly above PolP. (4) illustrates the hierarchy of the subject positions in a PRON copular construction. The subject resides in Spec,SUBJ2P. (4) …DP SUBJ2 …DP SUBJ1 … Pol … DP subj PredP Another related phenomenon in RYA which sets it apart from other languages like Hebrew is that of negative bare copular construction. This construction involves a PRON, which is not found in its affirmative counterpart. PRON, however, is hosted neither by SUBJ20 nor by SUBJ10. Rather, PRON occurs below Neg0 (Pol0 in the hierarchy). This situation raises interesting issues for the hierarchy of subjects in copular constructions as well as to the syntax of the left periphery in general. With regard to what causes the subject to move, there are different potential triggers. For instance, movement of the subject at the base, i.e., out of PredP is triggered by a labeling failure. Other movements of the subject can be driven by a formal feature like EPP, or a criterial feature like [subj].

Keywords: Yemeni Arabic, copular constructions, cartography of subjects, labeling, criterial positions

Procedia PDF Downloads 83

Authors: Wei Wang, Yilun Xu

Abstract:

With the development of knowledge economy era, deepening the mechanism of cooperation and adhering to sharing and win-win cooperation has become new direction of urban development nowadays. In recent years, innovative collaborations between cities are becoming more and more frequent, whose influence on urban network space has aroused many scholars' attention. Taking 46 cities in China as the research object, the paper builds the connectivity of innovative network between cities and the linkages of urban external innovation using patent cooperation data among cities, and explores urban network space in China by the application of GIS, which is a beneficial exploration to the study of social network space in China in the era of information network. The result shows that the urban innovative network space and geographical entity space exist differences, and the linkages of external innovation are not entirely related to the city innovative capacity and the level of economy development. However, urban innovative network space and geographical entity space are similar in hierarchical clustering. They have both formed Beijing-Tianjin-Hebei, Yangtze River Delta, Pearl River Delta three metropolitan areas and Beijing-Shenzhen-Shanghai-Hangzhou four core cities, which lead the development of innovative network space in China.

Keywords: innovative collaboration, urban network space, the connectivity of innovative network, the linkages of external innovation

Procedia PDF Downloads 159

Authors: Abeer Toheed Quadri, Maria Abubakar, Mehreen Sirshar

Abstract:

Component Based Software Development (CBSD) is a new trend in software development. Selection of quality components is not enough to ensure software quality in Component Based Software System (CBSS). A software product is considered to be a quality product if it satisfies its customer’s needs and has minimum defects. Authors’ survey different research papers and analyzes various techniques which ensure software quality in component based software development. This paper includes an investigation about how to improve the quality of a component based software system without effecting quality attributes. The reported information is identified from literature survey. The developments of component based systems are rising as they reduce the development time, effort and cost by means of reuse. After analysis, it has been explored that in order to achieve the quality in a CBSS we need to have the components that are certified through software measure because the predictability of software quality attributes of system depend on the quality attributes of the constituent components, integration process and the framework used.

Keywords: CBSD (component based software development), CBSS (component based software system), quality components, SQA (software quality assurance)

Procedia PDF Downloads 387

Authors: Soheila Sadeghi

Abstract:

Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: cost prediction, machine learning, project management, random forest, neural networks

Procedia PDF Downloads 13

Authors: M. Bodner, M. Scampicchio

Abstract:

Fourier Transform Infrared (FT-IR) spectroscopy coupled with chemometrics was used to distinguish between butter samples and non-butter samples. Further, quantification of the content of margarine in adulterated butter samples was investigated. Fingerprinting region (1400-800 cm^–1) was used to develop unsupervised pattern recognition (Principal Component Analysis, PCA), supervised modeling (Soft Independent Modelling by Class Analogy, SIMCA), classification (Partial Least Squares Discriminant Analysis, PLS-DA) and regression (Partial Least Squares Regression, PLS-R) models. PCA of the fingerprinting region shows a clustering of the two sample types. All samples were classified in their rightful class by SIMCA approach; however, nine adulterated samples (between 1% and 30% w/w of margarine) were classified as belonging both at the butter class and at the non-butter one. In the two-class PLS-DA model’s (R² = 0.73, RMSEP, Root Mean Square Error of Prediction = 0.26% w/w) sensitivity was 71.4% and Positive Predictive Value (PPV) 100%. Its threshold was calculated at 7% w/w of margarine in adulterated butter samples. Finally, PLS-R model (R² = 0.84, RMSEP = 16.54%) was developed. PLS-DA was a suitable classification tool and PLS-R a proper quantification approach. Results demonstrate that FT-IR spectroscopy combined with PLS-R can be used as a rapid, simple and safe method to identify pure butter samples from adulterated ones and to determine the grade of adulteration of margarine in butter samples.

Keywords: adulterated butter, margarine, PCA, PLS-DA, PLS-R, SIMCA

Procedia PDF Downloads 127

Authors: Thomas Soro, Tim Stott, Brendan O'Rourke

Abstract:

The construction of artistic reputation has been examined within sociology, philosophy, and economics but, baring a few noteworthy exceptions its discursive aspect has been largely ignored. This is particularly surprising given that contemporary artworks primarily rely on discourse to construct their ontological status. This paper contributes a discourse analytical perspective to the broad body of literature on artistic reputation by providing an understanding of how it is discursively constructed within the institutional context of online contemporary art magazines. This paper uses corpora compiled from the websites of e-flux and ARTnews, two leading online contemporary art magazines, to examine how these organisations discursively construct the reputation of artists. By constructing word-sketches of the term 'Artist', the paper identified the most significant modifiers attributed to artists and the most significant verbs which have 'artist' as an object or subject. The most significant results were analysed through concordances and demonstrated a somewhat surprising lack of evaluative representation. To examine this feature more closely, the paper then analysed three announcement texts from e-flux’s site and three review texts from ARTnews' site, comparing the use of modifiers and verbs in the representation of artists, artworks, and institutions. The results of this analysis support the corpus findings, suggesting that artists are rarely represented in evaluative terms. Based on the relatively high frequency of evaluation in the representation of artworks and institutions, these results suggest that there may be discursive norms at work in the field of online contemporary art magazines which regulate the use of verbs and modifiers in the evaluation of artists.

Keywords: contemporary art, corpus linguistics, critical discourse analysis, symbolic capital

Procedia PDF Downloads 142

Authors: Ben Clapperton, Daniel Stahl, Kimberley Goldsmith, Trudie Chalder

Abstract:

Chronic fatigue syndrome (CFS) is a condition characterised by chronic disabling fatigue and other symptoms that currently can't be explained by any underlying medical condition. Although clinical trials support the effectiveness of cognitive behaviour therapy (CBT), the success rate for individual patients is modest. Patients vary in their response and little is known which factors predict or moderate treatment outcomes. The aim of the project is to develop a prediction model from baseline characteristics of patients, such as demographics, clinical and psychological variables, which may predict likely treatment outcome and provide guidance for clinical decision making and help clinicians to recommend the best treatment. The project is aimed at identifying subgroups of patients with similar baseline characteristics that are predictive of treatment effects using modern cluster analyses and data mining machine learning algorithms. The characteristics of these groups will then be used to inform the types of individuals who benefit from a specific treatment. In addition, results will provide a better understanding of for whom the treatment works. The suitability of different clustering methods to identify subgroups and their response to different treatments of CFS patients is compared.

Keywords: chronic fatigue syndrome, latent class analysis, prediction modelling, self-organizing maps

Procedia PDF Downloads 203

Authors: Housein Deli, Loui Al-Shrouf, Hammoud Al Joumaa, Mohieddine Jelali

Abstract:

When forming metallic materials, fluctuations in material properties, process conditions, and wear lead to deviations in the component geometry. Several hundred features sometimes need to be measured, especially in the case of functional and safety-relevant components. These can only be measured offline due to the large number of features and the accuracy requirements. The risk of producing components outside the tolerances is minimized but not eliminated by the statistical evaluation of process capability and control measurements. The inspection intervals are based on the acceptable risk and are at the expense of productivity but remain reactive and, in some cases, considerably delayed. Due to the considerable progress made in the field of condition monitoring and measurement technology, permanently installed sensor systems in combination with machine learning and artificial intelligence, in particular, offer the potential to independently derive forecasts for component geometry and thus eliminate the risk of defective products - actively and preventively. The reliability of forecasts depends on the quality, completeness, and timeliness of the data. Measuring all geometric characteristics is neither sensible nor technically possible. This paper, therefore, uses the example of car seat rail production to discuss the necessary first step of feature selection and reduction by correlation analysis, as otherwise, it would not be possible to forecast components in real-time and inline. Four different car seat rails with an average of 130 features were selected and measured using a coordinate measuring machine (CMM). The run of such measuring programs alone takes up to 20 minutes. In practice, this results in the risk of faulty production of at least 2000 components that have to be sorted or scrapped if the measurement results are negative. Over a period of 2 months, all measurement data (> 200 measurements/ variant) was collected and evaluated using correlation analysis. As part of this study, the number of characteristics to be measured for all 6 car seat rail variants was reduced by over 80%. Specifically, direct correlations for almost 100 characteristics were proven for an average of 125 characteristics for 4 different products. A further 10 features correlate via indirect relationships so that the number of features required for a prediction could be reduced to less than 20. A correlation factor >0.8 was assumed for all correlations.

Keywords: long-term SHM, condition monitoring, machine learning, correlation analysis, component prediction, wear prediction, regressions analysis

Procedia PDF Downloads 14

Authors: Ana Rita Conde, Pilar Mota, Tânia Botelho, Suzana Caldeira, Isabel Rego, Jessica Pacheco, Osvaldo Silva, Áurea Sousa

Abstract:

Tourism promotes well-being and health to children with ASD and their families. Literature indicates the need to provide tourist activities that integrate the therapeutic component, to promote the development and well-being of children with ASD. The study aims to implement tourist offers in Azores that integrate the therapeutic feature, assess their suitability and impact on the well-being and health of the child and caregivers. Using a mixed methodology, the study integrates families that experience and evaluate the impact of tourism products developed specifically for them.

Keywords: austism spectrum disorder, children, therapeutic tourism activities, well-being, health, inclusive tourism

Procedia PDF Downloads 126

Authors: Jae Seo Lee, Il Keun Kwon

Abstract:

In the last decades, keratin-based on natural extracts has considerably increased interest as a skin tissue regeneration. However, most parts of keratin had a limitation to 3D scaffolds due to low biological affinity and general low mechanical properties. To create a 3D structure, a facile bioink was designed with a photocurable crosslinking stage system using natural polymer-based human keratin. Keratin-based bioink enables the crosslinking more quickly through two types of photo and ion crosslinking for module engineering assembly. Rheological results showed that keratin-based bioink with high concentration possessed superior mechanical rigidity for 3D bioprinting. Different 3D geometrically constructs were successfully fabricated with optimal bioprinting parameters through the 3D printer with X-Y-Z controlled UV laser system. The presented study has offered a distinct advantage for 3D printing of keratin-based hydrogel into 3D complex-shaped biomimetic constructs. Thus, keratin-based bioink opens up new avenues in bioprinting to directly substitute tissue or organs.

Keywords: human keratin, hydrogel, ion-crosslinking, 3D bioprinting

Procedia PDF Downloads 106

Authors: Nilubon Kurubanjerdjit, Nattakarn Iam-On, Ka-Lok Ng

Abstract:

MicroRNAs are small non-coding RNA found in many different species. They play crucial roles in cancer such as biological processes of apoptosis and proliferation. The identification of microRNA-target genes can be an essential first step towards to reveal the role of microRNA in various cancer types. In this paper, we predict miRNA-target genes for lung cancer by integrating prediction scores from miRanda and PITA algorithms used as a feature vector of miRNA-target interaction. Then, machine-learning algorithms were implemented for making a final prediction. The approach developed in this study should be of value for future studies into understanding the role of miRNAs in molecular mechanisms enabling lung cancer formation.

Keywords: microRNA, miRNAs, lung cancer, machine learning, Naïve Bayes, SVM

Procedia PDF Downloads 379

Authors: Seung-Hwan Ju, Yo-Han Choi, Hee-Suk Seo, Tae-Kyung Kim

Abstract:

This study investigates the permissions requested by Android applications, and the possibility of identifying suspicious applications based only on information presented to the user before an application is downloaded. The pattern analysis is based on a smaller data set consisting of confirmed malicious applications. The method is evaluated based on its ability to recognize malicious potential in the analyzed applications. In this study, we develop a system to monitor that mobile application permission at application update. This study is a service-based malware analysis. It will be based on the mobile security study.

Keywords: malware patterns, application permission, application analysis, security

Procedia PDF Downloads 494

Authors: Aleksander Ejsmont, Stefan Wuttke, Joanna Goscianska

Abstract:

Gaining control over particle shape, size and crystallinity is an ongoing challenge for many materials. Especially metalorganic frameworks (MOFs) are recently widely studied. Besides their remarkable porosity and interesting topologies, morphology has proven to be a significant feature. It can affect the further material application. Thus seeking new approaches that enable MOF morphology modulation is important. MOFs are reticular structures, where building blocks are made up of organic linkers and metallic nodes. The most common strategy of ensuring metal source is using salts, which usually exhibit high solubility and hinder morphology control. However, there has been a growing interest in using metal oxides as structure-directing agents towards MOFs due to their very low solubility and shape preservation. Metal oxides can be treated as a metal reservoir during MOF synthesis. Up to now, reports in which receiving MOFs from metal oxides mostly present ZnO conversion to ZIF-8. However, there are other oxides, for instance, Co₃O₄, which often is overlooked due to their structural stability and insolubility in aqueous solutions. Cobalt-based materials are famed for catalytic activity. Therefore the development of their efficient synthesis is worth attention. In the presented work, an optimized Co₃O₄transition to Co-MOFviaa solvothermal approach was proposed. The starting point of the research was the synthesis of Co₃O₄ flower petals and needles under hydrothermal conditions using different cobalt salts (e.g., cobalt(II) chloride and cobalt(II) nitrate), in the presence of urea, and hexadecyltrimethylammonium bromide (CTAB) surfactant as a capping agent. After receiving cobalt hydroxide, the calcination process was performed at various temperatures (300–500 °C). Then cobalt oxides as a source of cobalt cations were subjected to reaction with trimesic acid in solvothermal environment and temperature of 120 °C leading to Co-MOF fabrication. The solution maintained in the system was a mixture of water, dimethylformamide, and ethanol, with the addition of strong acids (HF and HNO₃). To establish how solvents affect metal oxide conversion, several different solvent ratios were also applied. The materials received were characterized with analytical techniques, including X-ray powder diffraction, energy dispersive spectroscopy,low-temperature nitrogen adsorption/desorption, scanning, and transmission electron microscopy. It was confirmed that the synthetic routes have led to the formation of Co₃O₄ and Co-based MOF varied in shape and size of particles. The diffractograms showed receiving crystalline phase for Co₃O₄, and also for Co-MOF. The Co₃O₄ obtained from nitrates and with using low-temperature calcination resulted in smaller particles. The study indicated that cobalt oxide particles of different size influence the efficiency of conversion and morphology of Co-MOF. The highest conversion was achieved using metal oxides with small crystallites.

Keywords: Co-MOF, solvothermal synthesis, morphology control, core-shell

Procedia PDF Downloads 140

Authors: Chalakorn Chitsaart, Suchada Rianmora, Noppawat Vongpiyasatit

Abstract:

In order to reduce the transportation time and cost for direct interface between customer and manufacturer, the image processing technique has been introduced in this research where designing part and defining manufacturing process can be performed quickly. A3D virtual model is directly generated from a series of multi-view images of an object, and it can be modified, analyzed, and improved the structure, or function for the further implementations, such as computer-aided manufacturing (CAM). To estimate and quote the production cost, the user-friendly platform has been developed in this research where the appropriate manufacturing parameters and process detections have been identified and planned by CAM simulation.

Keywords: image processing technique, feature detections, surface registrations, capturing multi-view images, Production costs and Manufacturing processes

Procedia PDF Downloads 234

Authors: Wei Wen Yang, Emily Chia Yu Su

Abstract:

Dengue fever is a mosquito-borne tropical infectious disease caused by the dengue virus. After infection, symptoms usually start from three to fourteen days. Dengue virus may cause a high fever and at least two of the following symptoms, severe headache, severe eye pain, joint pains, muscle or bone pain, vomiting, feature skin rash, and mild bleeding manifestation. In addition, recovery will take at least two to seven days. Dengue fever has rapidly spread in tropical and subtropical areas in recent years. Several phenomena around the world such as global warming, urbanization, and international travel are the main reasons in boosting the spread of dengue. In Taiwan, epidemics occur annually, especially during summer and fall seasons. On the other side, Singapore government also has announced the amounts number of dengue cases spreading in Singapore. As the serious epidemic of dengue fever outbreaks in Taiwan and Singapore, countries around the Asia-Pacific region are becoming high risks of susceptible to the outbreaks and local hub of spreading the virus. To improve public safety and public health issues, firstly, we are going to use Microsoft Excel and SAS EG to do data preprocessing. Secondly, using support vector machines and decision trees builds predict model, and analyzes the infectious cases between Taiwan and Singapore. By comparing different factors causing vector mosquito from model classification and regression, we can find similar spreading patterns where the disease occurred most frequently. The result can provide sufficient information to predict the future dengue infection outbreaks and control the diffusion of dengue fever among countries.

Keywords: dengue fever, Taiwan, Singapore, Aedes aegypti

Procedia PDF Downloads 215

Authors: V. Yu. Volgutov, A. I. Orlova, S. A. Khainakov

Abstract:

NaZr2(PO4)3 (NZP) and their structural analogues are characterized by a peculiar behaviors on heating – they have different expansion and contraction along different crystallographic directions due to specific arrangements of crystal structure in these compounds. An important feature of such structures is the ability to incorporate into their structural analogues wide variety of metal cations having different size and oxidation states, with different combinations and concentrations. These cations are located in different crystallographic non-equivalent positions of octahedral tetrahedral crystal framework as well as in inter-framework cavities. Through, due to iso- and hetero-valent isomorphism of the cations (and the anions) in NZP, it becomes possible to tuning the compositions and to obtain the compounds with ‘on a plan’ properties. For the design of compounds with low and ultra-low thermal expansion including those with tailored thermal expansion properties, the following crystallochemical principles it seems are promising: 1) Insertion into crystal M1 position the cations having different sizes and, 2) the variation in the composition of compounds, providing different occupation of crystal M1 position. Following these principles we have designed and synthesized the next NZP-type phosphates series: a) where radii of the cations in the M1 crystal position was varied: Zr1/4Zr2(PO4)3 - Th1/4Zr2(PO4)3 (series I); R1/3Zr2(PO4)3 where R= Nd, Eu, Er (series II), b) where the occupation of M1 crystal position was varied: Zr1/4Zr2(PO4)3-Er1/3Zr2(PO4)3 (series III) and Zr1/4Zr2(PO4)3-Sr1/2Zr2(PO4)3 (series IV). The thermal expansion parameters were determined over the range of 25-800ºC. For each series the minimum axial coefficient of thermal expansion αa = αb, αc and their anisotropy Δα = Iαa - αcI, 10-6 K-1 was found as next: -1.51, 1.07, 2.58 for Th1/4Zr2(PO4)3 (series I); -0.72, 0.10, 0.81 for Nd1/3Zr2(PO4)3 (series II); -2.78, 1.35, 4.12 for Er1/6Zr1/8Zr2(PO4)3 (series III); 2.23, 1.32, 0.91 for Sr1/2Zr2(PO4)3 (series IV). The measured tendencies of the thermal expansion of crystals were in good agreement with predicted ones. For one of the members from the studied phosphates namely Th1/16Zr3/16Zr2(PO4)3 structural refinement have been carried out at 25, 200, 600, and 800°C. The dependencies of the structural parameters with the temperature have been determined.

Keywords: high-temperature crystallography, NaZr2(PO4)3, (NZP) analogs, structural-chemical principles, tuning thermal expansion

Procedia PDF Downloads 216

Authors: Nusrat Zabeen Islam

Abstract:

Partnership between local Non-Government organizations (NGO) and International development organizations has become an important feature in the development sector of Bangladesh. It is an important challenge for International development organizations to work with local NGOs with proper HR practice. Local NGOs have a lack of quality working environment and this affects the employee’s work experiences and overall performance at individual, partnership with International development organizations and organizational level. Many local development organizations due to the size of the organization and scope do not have a human resource (HR) unit. Inadequate Human Resource Policies, skills, leadership and lack of effective strategy is now a common scenario in Non-Government organization sector of Bangladesh. So corruption, nepotism, and fraud, risk of Political Contribution in office /work space, Sexual/ gender based abuse, insecurity take place in work place of development sector. The Complaint Management Mechanism (CMM) in human resource management could be one way to improve human resource competence in these organizations. The responsibility of Complaint Management Unit (CMU) of an International development organization is to make workplace maltreating, discriminating communities free. The information of impact of CMM was collected through case study of an International organization and some of its partner national organizations in Bangladesh who are engaged in different projects/programs. In this mechanism International development organizations collect complaints from beneficiaries/ staffs by complaint management unit and investigate by segregating the type and mood of the complaint and find out solution to improve the situation within a very short period. A complaint management committee is formed jointly with HR and management personnel. Concerned focal point collect complaints and share with CM unit. By conducting investigation, review of findings, reply back to CM unit and implementation of resolution through this mechanism, a successful bridge of communication and feedback can be established within beneficiaries, staffs and upper management. The overall result of Complaint management mechanism application indicates that by applying CMM accountability and transparency of workplace and workforce in development organization can be increased significantly. Evaluations based on outcomes, and measuring indicators such as productivity, satisfaction, retention, gender equity, proper judgment will guide organizations in building a healthy workforce, and will also clearly articulate the return on investment and justify any need for further funding.

Keywords: human resource management in NGOs, challenges in human resource, workplace environment, complaint management mechanism

Procedia PDF Downloads 305

Authors: J. T. Pitale, S. Ghassab, H. Ay, N. Berme

Abstract:

Biomechanics researchers commonly use marker-based optical motion capture (MoCap) systems to extract human body kinematic data. These systems use cameras to detect passive or active markers placed on the subject. The cameras use triangulation methods to form images of the markers, which typically require each marker to be visible by at least two cameras simultaneously. Cameras in a conventional optical MoCap system are mounted at a distance from the subject, typically on walls, ceiling as well as fixed or adjustable frame structures. To accommodate for space constraints and as portable force measurement systems are getting popular, there is a need for smaller and smaller capture volumes. When the efficacy of a MoCap system is investigated, it is important to consider the tradeoff amongst the camera distance from subject, pixel density, and the field of view (FOV). If cameras are mounted relatively close to a subject, the area corresponding to each pixel reduces, thus increasing the image resolution. However, the cross section of the capture volume also decreases, causing reduction of the visible area. Due to this reduction, additional cameras may be required in such applications. On the other hand, mounting cameras relatively far from the subject increases the visible area but reduces the image quality. The goal of this study was to develop a quantitative methodology to investigate marker occlusions and optimize camera placement for a given capture volume and subject postures using three-dimension computer-aided design (CAD) tools. We modeled a 4.9m x 3.7m x 2.4m (LxWxH) MoCap volume and designed a mounting structure for cameras using SOLIDWORKS (Dassault Systems, MA, USA). The FOV was used to generate the capture volume for each camera placed on the structure. A human body model with configurable posture was placed at the center of the capture volume on CAD environment. We studied three postures; initial contact, mid-stance, and early swing. The human body CAD model was adjusted for each posture based on the range of joint angles. Markers were attached to the model to enable a full body capture. The cameras were placed around the capture volume at a maximum distance of 2.7m from the subject. We used the Camera View feature in SOLIDWORKS to generate images of the subject as seen by each camera and the number of markers visible to each camera was tabulated. The approach presented in this study provides a quantitative method to investigate the efficacy and efficiency of a MoCap camera setup. This approach enables optimization of a camera setup through adjusting the position and orientation of cameras on the CAD environment and quantifying marker visibility. It is also possible to compare different camera setup options on the same quantitative basis. The flexibility of the CAD environment enables accurate representation of the capture volume, including any objects that may cause obstructions between the subject and the cameras. With this approach, it is possible to compare different camera placement options to each other, as well as optimize a given camera setup based on quantitative results.

Keywords: motion capture, cameras, biomechanics, gait analysis

Procedia PDF Downloads 296

Authors: R. A. Temah, L. A. Nkengla-Asi

Abstract:

Planning for future disasters sets the stage for a variety of activities that may trigger multiple recurring operations and expose the community to opportunities to minimize risks. Local communities are increasingly embracing the necessity for planning based on local risks, but are also significantly challenged to effectively plan and response to disasters. This research examines basic risk-based disaster planning model and compares it with advanced risk-based planning that introduces the identification and alignment of varieties of local capabilities within and out of the local community that can be pivotal to facilitate the management of local risks and cascading effects prior to a disaster. A critical review shows that the identification and alignment of capabilities can potentially enhance risk-based disaster planning. A tailored holistic approach to risk based disaster planning is pivotal to enhance collective action and a reduction in disaster collective cost.

Keywords: capabilities, disaster planning, hazards, local community, risk-based

Procedia PDF Downloads 183

Authors: H. Aljabiry, L. Bailey, S. Young

Abstract:

Qatar is a desert with an average temperature 37⁰C, reaching over 40⁰C during summer. Precipitation is uncommon and mostly in winter. Qatar depends on desalination for drinking water and on groundwater and recycled water for irrigation. Water consumption and network leakage per capita in Qatar are amongst the highest in the world; re-use of treated wastewater is extremely limited with only 14% of treated wastewater being used for irrigation. This has led to the country disposing of unwanted water from various sources in lagoons situated around the country, causing concern over the possibility of environmental pollution. Accordingly, our hypothesis underpinning this research is that the quality and quantity of water in lagoons is having an impact on the groundwater reservoirs in Qatar. Lagoons (n = 14) and wells (n = 55) were sampled for both summer and winter in 2018 (summer and winter). Water, adjoining soil and plant samples were analysed for multiple elements by Inductively Coupled Plasma Mass Spectrometry. Organic and inorganic carbon were measured (CN analyser) and the major anions were determined by ion chromatography. Salinization in both the lagoon and the wells was seen with good correlations between Cl⁻, Na⁺, Li, SO₄, S, Sr, Ca, Ti (p-value < 0.05). Association of heavy metals was observed of Ni, Cu, Ag, and V, Cr, Mo, Cd which is due to contamination from anthropological activities such as wastewater disposal or spread of contaminated dust. However, looking at each elements none of them exceeds the Qatari regulation. Moreover, gypsum saturation in the system was observed in both the lagoon and wells water samples. Lagoons and the water of the well are found to be of a saline type as well as Ca²⁺, Cl⁻, SO₄²⁻ type evidencing both gypsum dissolution and salinization in the system. Moreover, Maps produced by Inverse distance weighting showed an increasing level of Nitrate in the groundwater in winter, and decrease chloride and sulphate level, indicating recharge effect after winter rain events. While E. coli and faecal bacteria were found in most of the lagoons, biological analysis for wells needs to be conducted to understand the biological contamination from lagoon water infiltration. As a conclusion, while both the lagoon and the well showed the same results, more sampling is needed to understand the impact of the lagoons on the groundwater.

Keywords: groundwater quality, lagoon, treated wastewater, water management, wastewater treatment, wetlands

Procedia PDF Downloads 120

Authors: Dhanuja S. Patil, Sanjay B. Waykar

Abstract:

Event detection is a standout amongst the most key parts for distinctive sorts of area applications of video data framework. Recently, it has picked up an extensive interest of experts and in scholastics from different zones. While detecting video event has been the subject of broad study efforts recently, impressively less existing methodology has considered multi-model data and issues related efficiency. Start of soccer matches different doubtful circumstances rise that can't be effectively judged by the referee committee. A framework that checks objectively image arrangements would prevent not right interpretations because of some errors, or high velocity of the events. Bayesian networks give a structure for dealing with this vulnerability using an essential graphical structure likewise the probability analytics. We propose an efficient structure for analysing and summarization of soccer videos utilizing object-based features. The proposed work utilizes the t-cherry junction tree, an exceptionally recent advancement in probabilistic graphical models, to create a compact representation and great approximation intractable model for client’s relationships in an interpersonal organization. There are various advantages in this approach firstly; the t-cherry gives best approximation by means of junction trees class. Secondly, to construct a t-cherry junction tree can be to a great extent parallelized; and at last inference can be performed utilizing distributed computation. Examination results demonstrates the effectiveness, adequacy, and the strength of the proposed work which is shown over a far reaching information set, comprising more soccer feature, caught at better places.

Keywords: summarization, detection, Bayesian network, t-cherry tree

Procedia PDF Downloads 301