Search results for: inquiry- based instruction

Authors: Franziska Mais, Till Gramberg

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The paper presents the development of a sustainable business model for a platform-based application tailored for sawing companies in small and medium-sized enterprises (SMEs). The focus is on the integration of sustainability principles into the design of the business model to ensure a technologically advanced, legally sound, and economically efficient solution. Easy2IoT is a research project that aims to enable companies in the prefabrication sheet metal and sheet metal processing industry to enter the Industrial Internet of Things (IIoT) with a low-threshold and cost-effective approach. The methodological approach of Easy2IoT includes an in-depth requirements analysis and customer interviews with stakeholders along the value chain. Based on these insights, actions, requirements, and potential solutions for smart services are derived. The structuring of the business ecosystem within the application plays a central role, whereby the roles of the partners, the management of the IT infrastructure and services, as well as the design of a sustainable operator model are considered. The business model is developed using the value proposition canvas, whereby a detailed analysis of the requirements for the business model is carried out, taking sustainability into account. This includes coordination with the business model patterns, according to Gassmann, and integration into a business model canvas for the Easy2IoT product. Potential obstacles and problems are identified and evaluated in order to formulate a comprehensive and sustainable business model. In addition, sustainable payment models and distribution channels are developed. In summary, the article offers a well-founded insight into the systematic development of a sustainable business model for platform-based applications in SME sawmills, with a particular focus on the synergy of ecological responsibility and economic efficiency.

Keywords: business model, sustainable business model, IIoT, IIoT-platform, industrie 4.0, big data

Procedia PDF Downloads 82

Authors: N. Cihan KayaçEtin, Stijn Verdoodt, Alexis Versele

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The construction industry is accounted for one-third of all waste generated in the European Union (EU) countries. The Circular Economy Action Plan of the EU aims to tackle this issue and aspires to enhance the sustainability of the construction industry by adopting more circular principles and bio-based material use. The Interreg Circular Bio-Based Construction Industry (CBCI) project was conceived to research how this adoption can be facilitated. For this purpose, an approach is developed that integrates technical, legal and social aspects and provides business models for circular designing and building with bio-based materials. In the scope of the project, the research outputs are to be displayed in a real-life setting by constructing a demo terraced single-family house, the living lab (LL) located in Ghent (Belgium). The realization of the LL is conducted in a step-wise approach that includes iterative processes for design, description, criteria definition and multi-criteria assessment of building components. The essence of the research lies within the exploratory approach to the state-of-art building envelope and technical systems options for achieving an optimum combination for a circular and bio-based construction. For this purpose, nine preliminary designs (PD) for building envelope are generated, which consist of three basic construction methods: masonry, lightweight steel construction and wood framing construction supplemented with bio-based construction methods like cross-laminated timber (CLT) and massive wood framing. A comparative analysis on the PDs was conducted by utilizing several complementary tools to assess the circularity. This paper focuses on the life cycle assessment (LCA) approach for evaluating the environmental impact of the LL Ghent. The adoption of an LCA methodology was considered critical for providing a comprehensive set of environmental indicators. The PDs were developed at the component level, in particular for the (i) inclined roof, (ii-iii) front and side façade, (iv) internal walls and (v-vi) floors. The assessment was conducted on two levels; component and building level. The options for each component were compared at the first iteration and then, the PDs as an assembly of components were further analyzed. The LCA was based on a functional unit of one square meter of each component and CEN indicators were utilized for impact assessment for a reference study period of 60 years. A total of 54 building components that are composed of 31 distinct materials were evaluated in the study. The results indicate that wood framing construction supplemented with bio-based construction methods performs environmentally better than the masonry or steel-construction options. An analysis on the correlation between the total weight of components and environmental impact was also conducted. It was seen that masonry structures display a high environmental impact and weight, steel structures display low weight but relatively high environmental impact and wooden framing construction display low weight and environmental impact. The study provided valuable outputs in two levels: (i) several improvement options at component level with substitution of materials with critical weight and/or impact per unit, (ii) feedback on environmental performance for the decision-making process during the design phase of a circular single family house.

Keywords: circular and bio-based materials, comparative analysis, life cycle assessment (LCA), living lab

Procedia PDF Downloads 183

Authors: Afaneen Anwer, Samara M. Kamil

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Load Forecast required prediction accuracy based on optimal operation and maintenance. A good accuracy is the basis of economic dispatch, unit commitment, and system reliability. A good load forecasting system fulfilled fast speed, automatic bad data detection, and ability to access the system automatically to get the needed data. In this paper, the formulation of the load forecasting is discussed and the solution is obtained by using artificial neural network method. A MATLAB environment has been used to solve the load forecasting schedule of Iraqi super grid network considering the daily load for three years. The obtained results showed a good accuracy in predicting the forecasted load.

Keywords: load forecasting, neural network, back-propagation algorithm, Iraqi power system

Procedia PDF Downloads 583

Authors: Bernd Kiefer, Abraham Gebru Tesfay, Dietrich Klakow

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The motivation of our work is to detect different terrain types traversed by a robot based on acoustic data from the robot-terrain interaction. Different acoustic features and classifiers were investigated, such as Mel-frequency cepstral coefficient and Gamma-tone frequency cepstral coefficient for the feature extraction, and Gaussian mixture model and Feed forward neural network for the classification. We analyze the system’s performance by comparing our proposed techniques with some other features surveyed from distinct related works. We achieve precision and recall values between 87% and 100% per class, and an average accuracy at 95.2%. We also study the effect of varying audio chunk size in the application phase of the models and find only a mild impact on performance.

Keywords: acoustic features, autonomous robots, feature extraction, terrain classification

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Authors: Mohd Adib Abd Muin

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Social entrepreneurship has become a new phenomenon in a country in order to reduce social problems and eradicate poverty communities. However, the study based on Islamic social entrepreneurship from the social entrepreneurial activity is still new especially in the Islamic perspective. In addition, this research found that is lacking of model on social entrepreneurship that focus on Islamic perspective. Therefore, the objective of this paper is to identify the issues and research gap based on Islamic perspective from existing models and to develop a concept of Islamic social entrepreneurship according to Islamic perspective and Maqasid Shari’ah. The research method used in this study is literature review and comparative analysis from 11 existing models of social entrepreneurship. The research finding shows that 11 existing models on social entrepreneurship has been analyzed and it shows that the existing models on social entrepreneurship do not emphasize on Islamic perspective.

Keywords: component, social entrepreneurship, Islamic perspective, research gap

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Authors: Connie Edang, Siti Arpah Noordin, Shamila Mohamed Shuhidan

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For the past few decades, there are growing numbers of knowledge based industries in Malaysia. As competitive edge has become so important nowadays, the consideration of research and development (R&D) should be put at the highest priority. Alike other industries, HEIs are also contributors to the nation’s development and wealth. Hence, to become a hub for creating a knowledge-based society, HEIs not only responsible for producing skillful human capital, but also to get involved in R&D. With the importance of R&D in today’s modern economy and the rise of Science and Technology, it gives opportunities for researchers to explore this sector as to place Malaysia as a provider in some key strategic industries, including medical and health sciences field. Academic researchers/medical researchers possess unique tacit and skills based in accordance with their experience and professional expert areas. In completing a collaborative research work, there must be platforms to enable the conversion of their knowledge hence beneficial towards creation of new knowledge. The objectives of this study are to: i) explore the knowledge creation activities of medical researchers in the Malaysian Higher Education Institution (HEI); ii) explore the driving forces for knowledge creation activities among the researchers; and iii) explore the interpretation of medical researchers on the establishment of ‘ba’ in the creation of knowledge. Based on the SECI model was introduced by Nonaka and Takeuchi and the Japanese concept of ‘ba’, a qualitative study whereby semi structured interview was used as to gather the informants’ viewpoints and insights based on their experience capitalizing ‘ba’ to support their knowledge creation activities. A single the study was conducted at one of the HEIs located in Sabah. From this study, both face to face and the ICT-assisted tools are found to be significant to support interaction of their knowledge. ICT seems to ease their interaction with other research collaborator. However, this study revealed that interaction conducted in physical settings is still be best preferred by the medical researchers especially situations of whereby their knowledge is hard to be externalized. Moreover, it revealed that motivational factors play important roles as for driving forces affecting their knowledge creation activities. Other than that, the medical researchers addressed that the mix interaction bring forth value in terms of facilitating knowledge creation. Therefore this study would benefit the institution to highly optimize the utilization of good platform so that knowledge can be transferred and be made used by others in appropriate ways.

Keywords: ‘ba’, knowledge creation dynamics, Malaysia, higher education institution, medical researchers

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Authors: John Onolame Unuofin, Uchechukuw U. Nwodo, Anthony I. Okoh

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Laccase is constantly gaining status as important biocatalyst in biotechnology. The illimitable potential of its industrial applications and the corresponding aggressive need for phenomenal volumes of extracellularly secreted laccases have called for its interminable production from sources which are able to meet this demand within a relatively short period of time, preferably bacteria. In response to this call, this study was designed to source for laccase-producing bacteria from different environmental matrices. Three sampling environments were chosen such as wastewater treatment plants, University of Fort Hare vicinity and the Hogback woodland, all within the Eastern Cape, South Africa. Samples such as effluents, sediments, leaf litters, degrading wood and rock scrapings were selectively enriched with some model aromatic compounds and were further screened qualitatively and quantitatively on five phenolic substrates ABTS (2,2’-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid), Guaiacol, 1-Naphthol, Potassium Ferric Cyanide and Syringaldazine). Basis for selection was their ability to elicit a colour change on at least three of the above mentioned agar based assay substrates. The choice isolates were further identified based on 16S rRNA molecular identification techniques. 33 isolates were screened out of the 40 representative distinct colonies during the qualitative plate screens, while quantitative screens selected out 11 bacterial isolates. They were, based on molecular identification, desginated as members of the genera Pseudomonas, Stenotrophomonas and Citrobacter of the gammaproteobacteria and Bordetalla and Achromobacter of the betaproteobacteria respectively. We therefore conclude based on our outcomes that we may have isolated efficient laccase-producing bacteria, which might be of beneficial significance in catalysis and biotechnology.

Keywords: beta proteobacteria, catalysis, gammaproteobacteria, laccase

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Authors: Nor Fazlina Iryani Abdul Hamid, Mohamad Khatim Hasan

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Evolution of software quality measurement has been started since McCall introduced his quality model in year 1977. Starting from there, several software quality models and software quality measurement methods had emerged but none of them focused on telecommunication industry. In this paper, the implementation of software quality measurement system for telecommunication industry was compulsory to accommodate the rapid growth of telecommunication industry. The quality value of the telecommunication related software could be calculated using this system by entering the required parameters. The system would calculate the quality value of the measured system based on predefined quality metrics and aggregated by referring to the quality model. It would classify the quality level of the software based on Net Satisfaction Index (NSI). Thus, software quality measurement system was important to both developers and users in order to produce high quality software product for telecommunication industry.

Keywords: software quality, quality measurement, quality model, quality metric, net satisfaction index

Procedia PDF Downloads 592

Authors: Mohammad Hassan Shojaeefard, Abolfazl Khalkhali, Khashayar Ghadirinejad

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In the present study, first, a three-dimensional finite element model of lower legform impactor according to the pedestrian protection regulation EC 78/2009 is carried out. The FE model of lower legform impactor then validated on static and dynamic tests by three main criteria which are bending angle, shear displacement and upper tibia acceleration. At the second step, the validated impactor is employed to evaluate bumper of a B-class automotive based on pedestrian protection criteria defined in EC regulation. Finally, based on some investigations an improved design for the bumper is then represented and compared with the base design. Results show that very good improvement in meeting the pedestrian protection criteria is achieved.

Keywords: pedestrian protection, legform impactor, automotive bumper, finite element method

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Authors: S. Botman, D. Borchevkin, V. Petrov, E. Bogdanov, M. Patrushev, N. Shusharina

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In this paper, we report the development of the device for diagnostics of cardiovascular system state and associated automated workstation for large-scale medical measurement data collection and analysis. It was shown that optimal design for the monitoring device is wristband as it represents engineering trade-off between accuracy and usability. The monitoring device is based on the infrared reflective photoplethysmographic sensor, which allows collecting multiple physiological parameters, such as heart rate and pulsing wave characteristics. Developed device use BLE interface for medical and supplementary data transmission to the coupled mobile phone, which process it and send it to the doctor's automated workstation. Results of this experimental model approbation confirmed the applicability of the proposed approach.

Keywords: cardiovascular diseases, health monitoring systems, photoplethysmography, pulse wave, remote diagnostics

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Authors: Gurmeet Kaur

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Agile software development methods are being recognized as popular, and efficient approach to the development of software system that has a short delivery period with high quality also that meets customer requirements with zero defect. In agile software development, quality means quality of code where in the quality is maintained through the use of methods or approaches like refactoring, test driven development, behavior driven development, acceptance test driven development, and demand driven development. Software quality is measured in term of metrics such as the number of defects during development of software. Usage of above mentioned methods or approaches, reduces the possibilities of defects in developed software, and hence improve quality. This paper focuses on study of agile based quality methods or approaches for software development that ensures improved quality of software as well as reduced cost, and customer satisfaction.

Keywords: ATDD, BDD, DDD, TDD

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Authors: Asma Alzahrani, Elizabeth Stojanovski

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This study investigated factors that influence mathematics achievement based on a sample of ninth-grade students (N  =  21,444) from the High School Longitudinal Study of 2009 (HSLS09). Key aspects studied included efficacy in mathematics, interest and enjoyment of mathematics, identity with mathematics and future utility beliefs and how these influence mathematics achievement. The predictability of mathematics achievement based on these factors was assessed using correlation coefficients and multiple linear regression. Spearman rank correlations and multiple regression analyses indicated positive and statistically significant relationships between the explanatory variables: mathematics efficacy, identity with mathematics, interest in and future utility beliefs with the response variable, achievement in mathematics.

Keywords: Mathematics achievement, math efficacy, mathematics interest, factors influence

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Authors: I. Nižetić Kosović, T. Jagušt

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Lately, with the increasing number of location-based applications, demand for highly accurate and reliable indoor localization became urgent. This is a challenging problem, due to the measurement variance which is the consequence of various factors like obstacles, equipment properties and environmental changes in complex nature of indoor environments. In this paper we propose low-cost custom-setup infrastructure solution and localization algorithm based on the Weighted Centroid Localization (WCL) method. Localization accuracy is increased by several enhancements: calibration of RSSI values gained from wireless nodes, repetitive measurements of RSSI to exclude deviating values from the position estimation, and by considering orientation of the device according to the wireless nodes. We conducted several experiments to evaluate the proposed algorithm. High accuracy of ~1m was achieved.

Keywords: indoor environment, received signal strength indicator, weighted centroid localization, wireless localization

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Authors: Cedric Leong, Parth Desai, Parth Patel

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The purpose of this project was to develop a neural network based on qualitative team data to predict alliance scores to determine winners of matches in the FIRST Robotics Competition (FRC). The game for the competition changes every year with different objectives and game objects, however the idea was to create a prediction system which can be reused year by year using some of the statistics that are constant through different games, making our system adaptable to future games as well. Aerial Assist is the FRC game for 2014, and is played in alliances of 3 teams going against one another, namely the Red and Blue alliances. This application takes any 6 teams paired into 2 alliances of 3 teams and generates the prediction for the final score between them.

Keywords: artifical neural network, prediction system, qualitative team data, FIRST Robotics Competition (FRC)

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Authors: Beata Jackowska-Zduniak

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We formulate and analyze a mathematical model describing dynamics of cancer growth under the influence of radiation therapy. The effect of this type of therapy is considered as an additional equation of discussed model. Numerical simulations show that delay, which is added to ordinary differential equations and represent time needed for transformation from one type of cells to the other one, affects the behavior of the system. The validation and verification of proposed model is based on medical data. Analytical results are illustrated by numerical examples of the model dynamics. The model is able to reconstruct dynamics of treatment of cancer and may be used to determine the most effective treatment regimen based on the study of the behavior of individual treatment protocols.

Keywords: mathematical modeling, numerical simulation, ordinary differential equations, radiation therapy

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Authors: Ashfaque Hossain Khan, Brian Thomson, Ratan Debnath, Abhishek Motayed, Mulpuri V. Rao

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Though the efforts had been made, the problem of cross-sensitivity for a single metal oxide-based sensor can’t be fully eliminated. In this work, a sensor array has been designed and fabricated comprising of platinum (Pt), copper (Cu), and silver (Ag) decorated TiO2 and ZnO functionalized GaN nanowires using industry-standard top-down fabrication approach. The metal/metal-oxide combinations within the array have been determined from prior molecular simulation study using first principle calculations based on density functional theory (DFT). The gas responses were obtained for both single and mixture of NO2, SO2, ethanol, and H2 in the presence of H2O and O2 gases under UV light at room temperature. Each gas leaves a unique response footprint across the array sensors by which precise discrimination of cross-sensitive gases has been achieved. An unsupervised principal component analysis (PCA) technique has been implemented on the array response. Results indicate that each gas forms a distinct cluster in the score plot for all the target gases and their mixtures, indicating a clear separation among them. In addition, the developed array device consumes very low power because of ultra-violet (UV) assisted sensing as compared to commercially available metal-oxide sensors. The nanowire sensor array, in combination with PCA, is a potential approach for precise real-time gas monitoring applications.

Keywords: cross-sensitivity, gas sensor, principle component analysis (PCA), sensor array

Procedia PDF Downloads 107

Authors: Nur Aziza Luxfiati

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Clustering is partitioning data sets into sub-sets or groups in such a way that elements certain properties have shared property settings with a high level of similarity within one group and a low level of similarity between groups. . The K-Means algorithm is one of thealgorithmsclustering as a grouping tool that is most widely used in scientific and industrial applications because the basic idea of the kalgorithm is-means very simple. In this research, applying the technique of clustering using the k-means algorithm as a method of solving the problem of national development imbalances between regions in Central Java Province based on macroeconomic indicators. The data sample used is secondary data obtained from the Central Java Provincial Statistics Agency regarding macroeconomic indicator data which is part of the publication of the 2019 National Socio-Economic Survey (Susenas) data. score and determine the number of clusters (k) using the elbow method. After the clustering process is carried out, the validation is tested using themethodsBetween-Class Variation (BCV) and Within-Class Variation (WCV). The results showed that detection outlier using z-score normalization showed no outliers. In addition, the results of the clustering test obtained a ratio value that was not high, namely 0.011%. There are two district/city clusters in Central Java Province which have economic similarities based on the variables used, namely the first cluster with a high economic level consisting of 13 districts/cities and theclustersecondwith a low economic level consisting of 22 districts/cities. And in the cluster second, namely, between low economies, the authors grouped districts/cities based on similarities to macroeconomic indicators such as 20 districts of Gross Regional Domestic Product, with a Poverty Depth Index of 19 districts, with 5 districts in Human Development, and as many as Open Unemployment Rate. 10 districts.

Keywords: clustering, K-Means algorithm, macroeconomic indicators, inequality, national development

Procedia PDF Downloads 158

Authors: Rima Alfaraj, Abeer Alarawi, Murtadha AlTammar

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The global energy landscape heavily relies on the oil and gas industry, which faces the critical challenge of reducing its carbon footprint. To address this issue, the integration of advanced materials like aerogels has emerged as a promising solution to enhance sustainability and environmental performance within the industry. This study thoroughly examines the application of aerogel-based technologies in the oil and gas sector, focusing particularly on their role in carbon capture and storage (CCS) initiatives. Aerogels, known for their exceptional properties, such as high surface area, low density, and customizable pore structure, have garnered attention for their potential in various CCS strategies. The review delves into various fabrication techniques utilized in producing aerogel materials, including sol-gel, supercritical drying, and freeze-drying methods, to assess their suitability for specific industry applications. Beyond fabrication, the practicality of aerogel materials in critical areas such as flow assurance, enhanced oil recovery, and thermal insulation is explored. The analysis spans a wide range of applications, from potential use in pipelines and equipment to subsea installations, offering valuable insights into the real-world implementation of aerogels in the oil and gas sector. The paper also investigates the adsorption and storage capabilities of aerogel-based sorbents, showcasing their effectiveness in capturing and storing carbon dioxide (CO₂) molecules. Optimization of pore size distribution and surface chemistry is examined to enhance the affinity and selectivity of aerogels towards CO₂, thereby improving the efficiency and capacity of CCS systems. Additionally, the study explores the potential of aerogel-based membranes for separating and purifying CO₂ from oil and gas streams, emphasizing their role in the carbon capture and utilization (CCU) value chain in the industry. Emerging trends and future perspectives in integrating aerogel-based technologies within the oil and gas sector are also discussed, including the development of hybrid aerogel composites and advanced functional components to further enhance material performance and versatility. By synthesizing the latest advancements and future directions in aerogel used for CCS applications in the oil and gas industry, this review offers a comprehensive understanding of how these innovative materials can aid in transitioning towards a more sustainable and environmentally conscious energy landscape. The insights provided can assist in strategic decision-making, drive technology development, and foster collaborations among academia, industry, and policymakers to promote the widespread adoption of aerogel-based solutions in the oil and gas sector.

Keywords: CCS, porous, carbon capture, oil and gas, sustainability

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Authors: Hassen Hamouda, Mohamed Ouwais Kabaou, Med Salim Bouhlel

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The growth of wireless technology made opportunistic scheduling a widespread theme in recent research. Providing high system throughput without reducing fairness allocation is becoming a very challenging task. A suitable policy for resource allocation among users is of crucial importance. This study focuses on scheduling multiple streaming flows on the downlink of a WiMAX system based on orthogonal frequency division multiple access (OFDMA). In this paper, we take the first step in formulating and analyzing this problem scrupulously. As a result, we proposed a new scheduling scheme based on Round Robin (RR) Algorithm. Because of its non-opportunistic process, RR does not take in account radio conditions and consequently it affect both system throughput and multi-users diversity. Our contribution called MORRA (Modified Round Robin Opportunistic Algorithm) consists to propose a solution to this issue. MORRA not only exploits the concept of opportunistic scheduler but also takes into account other parameters in the allocation process. The first parameter is called courtesy coefficient (CC) and the second is called Buffer Occupancy (BO). Performance evaluation shows that this well-balanced scheme outperforms both RR and MaxSNR schedulers and demonstrate that choosing between system throughput and fairness is not required.

Keywords: OFDMA, opportunistic scheduling, fairness hierarchy, courtesy coefficient, buffer occupancy

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Authors: Caihong Sun, Xizi Zhang

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Rating prediction is an important problem for recommender systems. The task is to predict the rating for an item that a user would give. Most of the existing algorithms for the task ignore the effect of negative ratings rated by users on items, but the negative ratings have a significant impact on users’ purchasing decisions in practice. In this paper, we present a rating prediction algorithm based on factorization machines that consider the effect of negative ratings inspired by Loss Aversion theory. The aim of this paper is to develop a concave and a convex negative disgust function to evaluate the negative ratings respectively. Experiments are conducted on MovieLens dataset. The experimental results demonstrate the effectiveness of the proposed methods by comparing with other four the state-of-the-art approaches. The negative ratings showed much importance in the accuracy of ratings predictions.

Keywords: factorization machines, feature engineering, negative ratings, recommendation systems

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Authors: Kristin Lewis, Howard Steele, Anne Murphy, Miriam Steele, Karen Bonuck, Paul Meissner

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The present study examines data collected during the randomized control trial (RCT) of the Group Attachment-Based Intervention (GABI©), a trauma-informed, attachment-based intervention aimed at promoting healthy parent-child relationships that support child development. Families received treatment at Treatment Center and were randomly assigned to either the GABI condition or the treatment as usual condition, a parenting class called Systematic Training for Effective Parenting (STEP). Significant improvements in the parent-child relationship have been reported for families participating in GABI, but not in the STEP control group relying on Coding Interactive Behavior (CIB) as applied to 5-minute video-films of mothers and their toddlers in a free play context. This report considers five additional attachment-relevant 'clinical codes' that were also applied to the 5-minute free play sessions. Seventy-two parent-child dyads (38 in GABI and 34 in STEP) were compared to one another at intake and end-of-treatment, on these five-point dimensions: two-parent codes—the dissociation and ignoring; two child codes—simultaneous display of contradictory behavior and fear; and one parent-child code, i.e., role reversal. Overall, scores were low for these clinical codes; thus, a binary measure was computed contrasting no evidence with some evidence of each clinical code. Crosstab analyses indicate that child fear at end-of-treatment was significantly lower among children who participated in GABI (7% or 3 children) as compared to those whose mothers participated in STEP (29% or 10 children) Chi Sq= 6.57 (1), p < .01. Discussion focuses on the potential for GABI to reduce childhood fearfulness and so enhance the child's health.

Keywords: coding interactive behavior, clinical codes, group attachment based intervention, GABI, attachment, fear

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Authors: Olaf Visker, Arnout De Vries, Lambert Schomaker

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Predictive policing refers to the usage of analytical techniques to identify potential criminal activity. It has been widely implemented by various police departments. Being a relatively new area of research, there are, to the author’s knowledge, no absolute tried, and true methods and they still exhibit a variety of potential problems. One of those problems is closely related to the lack of understanding of how acting on these prediction influence crime itself. The goal of law enforcement is ultimately crime reduction. As such, a policy needs to be established that best facilitates this goal. This research aims to find such a policy by using adversarial agent-based modeling in combination with modern reinforcement learning techniques. It is presented here that a baseline model for both law enforcement and criminal agents and compare their performance to their respective reinforcement models. The experiments show that our smart law enforcement model is capable of reducing crime by making more deliberate choices regarding the locations of potential criminal activity. Furthermore, it is shown that the smart criminal model presents behavior consistent with popular crime theories and outperforms the baseline model in terms of crimes committed and time to capture. It does, however, still suffer from the difficulties of capturing long term rewards and learning how to handle multiple opposing goals.

Keywords: adversarial, agent based modelling, predictive policing, reinforcement learning

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Authors: Ejaz Ahmed, Huang Yong

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The operation of aero engines has a critical importance in the vicinity of lean blowout (LBO) limits. Lefebvre’s model of LBO based on empirical correlation has been extended to flame volume concept by the authors. The flame volume takes into account the effects of geometric configuration, the complex spatial interaction of mixing, turbulence, heat transfer and combustion processes inside the gas turbine combustion chamber. For these reasons, flame volume based LBO predictions are more accurate. Although LBO prediction accuracy has improved, it poses a challenge associated with Vf estimation in real gas turbine combustors. This work extends the approach of flame volume prediction previously based on fuel iterative approximation with cold flow simulations to reactive flow simulations. Flame volume for 11 combustor configurations has been simulated and validated against experimental data. To make prediction methodology robust as required in the preliminary design stage, reactive flow simulations were carried out with the combination of probability density function (PDF) and discrete phase model (DPM) in FLUENT 15.0. The criterion for flame identification was defined. Two important parameters i.e. critical injection diameter (Dp,crit) and critical temperature (Tcrit) were identified, and their influence on reactive flow simulation was studied for Vf estimation. Obtained results exhibit ±15% error in Vf estimation with experimental data.

Keywords: CFD, combustion, gas turbine combustor, lean blowout

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Authors: Expedito J. S. Parente Jr., Italo C. Rios, Joao Paulo C. Marques, Rosana M. A. Saboya, F. Murilo T. Luna, Célio L. Cavalcante Jr.

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Increasing constraints of environmental regulation around the world have led to higher demand for biodegradable products. Vegetable oils present some properties that may favor their use as biolubricants; however, there are others, such as resistance to oxidation and pour point, which affect possible commercial applications. In this study, the physicochemical properties of biolubricants synthesized from different vegetable oils were evaluated and compared with petroleum-based lubricant and pure vegetable oil. Chemical modifications applied to the original vegetable oil improved their oxidative stability and pour point significantly. The addition of commercial antioxidants to the bio-based lubricants was evaluated, yielding values of oxidative stability close to those of mineral basestock oil.

Keywords: biolubricant, vegetable oil, oxidative stability, pour point, antioxidants

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Authors: Norah Almubairik, Wadha Almattar, Amani Alqarni

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Social media applications are increasingly being used in our everyday communications. These applications utilise end-to-end encryption mechanisms, which make them suitable tools for criminals to exchange messages. These messages are preserved in the volatile memory until the device is restarted. Therefore, volatile forensics has become an important branch of digital forensics. In this study, the WormHex tool was developed to inspect the memory dump files of Windows and Mac-based workstations. The tool supports digital investigators to extract valuable data written in Arabic and English through web-based WhatsApp and Twitter applications. The results verify that social media applications write their data into the memory regardless of the operating system running the application, with there being no major differences between Windows and Mac.

Keywords: volatile memory, REGEX, digital forensics, memory acquisition

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Authors: Joao Fialho

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The mathematical modelling of idiopathic scoliosis has been studied throughout the years. The models presented on those papers are based on the orthotic stabilization of the idiopathic scoliosis, which are based on a transversal force being applied to the human spine on a continuous form. When considering the ATT (Antalgic-Trak Technology) device, the existent models cannot be used, as the type of forces applied are no longer transversal nor applied in a continuous manner. In this device, vertical traction is applied. In this study we propose to model the idiopathic scoliosis, using the ATT (Antalgic-Trak Technology) device, and with the parameters obtained from the mathematical modeling, set up a case-by-case individualized therapy plan, for each patient.

Keywords: idiopathic scoliosis, mathematical modelling, human spine, Antalgic-Trak technology

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Authors: Abdullah Işıktaş, Kevser Dincer

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The use of HEPA filters for air conditioning systems in clean rooms tends to increase progressively in pharmaceutical, food stuff industries and in hospitals. There are two standards widely used for HEPA filters; the EN 1822 standards published by the European Union, CEN (European Committee for Standardization) and the US based IEST standard (Institute of Environmental Sciences and Technology. Both standards exhibit some differences in the definitions of efficiency and its measurement methods. While IEST standard defines efficiency at the grit diameter of 0.3 µm, the EN 1822 standard takes MPPS (Most Penetrating Particle Size) as the basis of its definition. That is, the most difficult grit size to catch up. On the other hand, while IEST suggests that photometer and grit counters be used for filter testing, in EN 1822 standard, only the grit (grain) counters are recommended for that purpose. In this study, powder holding capacities of H13 and H14 grade materials under the EN 779 standard are investigated experimentally by using activated carbon. Measurements were taken on an experimental set up based on the TS 932 standard. Filter efficiency was measured by injecting test powder at amounts predetermined in the standards into the filters at certain intervals. The data obtained showed that the powder holding capacities of the activated carbon filter are high enough to yield efficiency of around 90% and that the H13 and H14 filters exhibit high efficiency suitable for the standard used.

Keywords: activated carbon filters, HEPA filters, powder holding capacities, air conditioning systems

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Authors: Zeynep Pirselimoglu Batman, Elvan Ender Altay, Murat Zencirkiran

Abstract:

Water and water resources are characteristic areas with their special ecosystems Their natural, cultural and economic value and recreation opportunities are high. Recreational activities differ according to the natural, cultural, socio-economic resource values of the areas. In this sense, water and water edge areas, which are important for their resource values, are also important landscape values for recreational activities. From these landscapes values, creeks and the surrounding areas have become a major source of daily life in the past, as well as a major attraction for people's leisure time. However, their qualities and quantities must be sufficient to enable these areas to be used effectively in a recreational sense and to be able to fulfill their recreational functions. The purpose of the study is to identify the recreational use of the water-based activities and identify effective service areas in dense urbanization zones along the creek and green spaces around them. For this purpose, the study was carried out in the vicinity of Nilufer Creek in Bursa. The study area and its immediate surroundings are in the boundaries of Osmangazi and Nilufer districts. The study was carried out in the green spaces along the creek with an individual interaction of 17.930m. These areas are Hudavendigar Urban Park, Atatürk Urban Forest, Bursa Zoo, Soganlı Botanical Park, Mihrapli Park, Nilufer Valley Park. In the first phase of the study, the efficiency zones of these locations were calculated according to international standards. 3200m of this locations are serving the city population and 800m are serving the district and neighborhood population. These calculations are processed on the digitized map by the AUTOCAD program using the satellite image. The efficiency zone of these green spaces in the city were calculated as 71.04 km². In the second phase of the study, water-based current activities were determined by evaluating the recreational potential of these green spaces, which are located along the Nilufer Creek, where efficiency zones have been identified. It has been determined that water-based activities are used intensively in Hudavendigar Urban Park and interacted with Nilufer Creek. Within the scope of effective zones for the study area, appropriate recreational planning proposals have been developed and water-based activities have been suggested.

Keywords: Bursa, efficiency zone, Nilufer Creek, recreation, water-based activities

Procedia PDF Downloads 161

Authors: Dona Shaini Abhilasha Nanayakkara, Kurugamage Jude Pravinda Gregory Perera

Abstract:

E-commerce platforms have revolutionized the shopping experience, offering convenient ways for consumers to make purchases. To improve interactions with customers and optimize marketing strategies, it is essential for businesses to understand user behavior, preferences, and needs on these platforms. This paper focuses on recommending businesses to customize interactions with users based on their behavioral patterns, leveraging data-driven analysis and machine learning techniques. Businesses can improve engagement and boost the adoption of e-commerce platforms by aligning behavioral patterns with user goals of usability and satisfaction. We propose TheAnalyzer, a clustering-based system designed to enhance business productivity by analyzing user-profiles and improving human-computer interaction. The Analyzer seamlessly integrates with business applications, collecting relevant data points based on users' natural interactions without additional burdens such as questionnaires or surveys. It defines five key user analytics as features for its dataset, which are easily captured through users' interactions with e-commerce platforms. This research presents a study demonstrating the successful distinction of users into specific groups based on the five key analytics considered by TheAnalyzer. With the assistance of domain experts, customized business rules can be attached to each group, enabling The Analyzer to influence business applications and provide an enhanced personalized user experience. The outcomes are evaluated quantitatively and qualitatively, demonstrating that utilizing TheAnalyzer’s capabilities can optimize business outcomes, enhance customer satisfaction, and drive sustainable growth. The findings of this research contribute to the advancement of personalized interactions in e-commerce platforms. By leveraging user behavioral patterns and analyzing both new and existing users, businesses can effectively tailor their interactions to improve customer satisfaction, loyalty and ultimately drive sales.

Keywords: data clustering, data standardization, dimensionality reduction, human computer interaction, user profiling

Procedia PDF Downloads 74

Authors: Zuzana Chaloupková, Zdeňka Marková, Václav Ranc, Radek Zbořil

Abstract:

Prostate cancer is now one of the most serious oncological diseases in men with an incidence higher than that of all other solid tumors combined. Diagnosis of prostate cancer usually involves detection of related genes or detection of marker proteins, such as PSA. One of the new potential markers is PSMA (prostate specific membrane antigen). PSMA is a unique membrane bound glycoprotein, which is considerably overexpressed on prostate cancer as well as neovasculature of most of the solid tumors. Commonly applied methods for a detection of proteins include techniques based on immunochemical approaches, including ELISA and RIA. Magnetically assisted surface enhanced Raman spectroscopy (MA-SERS) can be considered as an interesting alternative to generally accepted approaches. This work describes a utilization of MA-SERS in a detection of PSMA in human blood. This analytical platform is based on magnetic nanocomposites Fe3O4@Ag, functionalized by a low-molecular selector labeled as JB303. The system allows isolating the marker from the complex sample using application of magnetic force. Detection of PSMA is than performed by SERS effect given by a presence of silver nanoparticles. This system allowed us to analyze PSMA in clinical samples with limits of detection lower than 1 ng/mL.

Keywords: diagnosis, cancer, PSMA, MA-SERS, Ag nanoparticles

Procedia PDF Downloads 229