Search results for: graph drawing

Authors: Venus Pagare, Amit Kharat, Dhaval K. Thakkar, Tushar J. Palekar

Abstract:

Introduction: Chronic low back pain (CLBP) is a major public health problem and is the leading musculoskeletal cause of disability. Altered neuromuscular control of core muscles, particulary transverses abdominis (TrA) is thought to be a contributing factor for the development of CLBP. Therefore, various exercises targeting the TrA are commonly incorporated into the rehabilitation. Objectives: To investigate the effects of 3 different core exercises on activation capacity of TrA muscle in individuals with CLBP as compared with healthy controls. Methodology: Thickness of TrA muscle was measured by ultrasound imaging in 30 patients with CLBP and 30 healthy controls. Measurements were taken during 3 different TrA activation exercises i.e Abdominal drawing in maneuver (ADIM), Abdominal drawing in with straight leg raise (ADSLR) and breathe hold at maximum expiration (ME). Thickness of the muscle at rest (at the end of normal tidal expiration) was taken as a baseline measure. Results: There was a significant difference between the healthy subjects and patients with low back pain with regard to the thickness of TrA at rest and thickness during contraction. ADIM produced a significant increase in the thickness of TrA compared to ADSLR and ME (p<0.001). Also, increase in thickness of TrA was more in the control group than patients with low back pain. Conclusion: CLBP patients exhibited atrophy of TrA muscle with delayed activation. Also, of the various core exercises, ADIM can be an effective method for activation of TrA.

Keywords: LBP, CLBP, ADSLR, ADIM

Procedia PDF Downloads 282

Authors: Michele Gattullo, Vito M. Manghisi, Alessandro Evangelista, Enricoandrea Laviola

Abstract:

In this work, we explored the use of Augmented Reality (AR) to support students in laboratory lectures in Distance Learning (DL), designing an application that proved to be ready for use next semester. AR could help students in the understanding of complex concepts as well as increase their motivation in the learning process. However, despite many prototypes in the literature, it is still less used in schools and universities. This is mainly due to the perceived limited advantages to the investment costs, especially regarding changes needed in the teaching modalities. However, with the spread of epidemiological emergency due to SARS-CoV-2, schools and universities were forced to a very rapid redefinition of consolidated processes towards forms of Distance Learning. Despite its many advantages, it suffers from the impossibility to carry out practical activities that are of crucial importance in STEM ("Science, Technology, Engineering e Math") didactics. In this context, AR perceived advantages increased a lot since teachers are more prepared for new teaching modalities, exploiting AR that allows students to carry on practical activities on their own instead of being physically present in laboratories. In this work, we designed an AR application for the support of engineering students in the understanding of assembly drawings of complex machines. Traditionally, this skill is acquired in the first years of the bachelor's degree in industrial engineering, through laboratory activities where the teacher shows the corresponding components (e.g., bearings, screws, shafts) in a real machine and their representation in the assembly drawing. This research aims to explore the effectiveness of AR to allow students to acquire this skill on their own without physically being in the laboratory. In a preliminary phase, we interviewed students to understand the main issues in the learning of this subject. This survey revealed that students had difficulty identifying machine components in an assembly drawing, matching between the 2D representation of a component and its real shape, and understanding the functionality of a component within the machine. We developed a mobile application using Unity3D, aiming to solve the mentioned issues. We designed the application in collaboration with the course professors. Natural feature tracking was used to associate the 2D printed assembly drawing with the corresponding 3D virtual model. The application can be displayed on students’ tablets or smartphones. Users could interact with selecting a component from a part list on the device. Then, 3D representations of components appear on the printed drawing, coupled with 3D virtual labels for their location and identification. Users could also interact with watching a 3D animation to learn how components are assembled. Students evaluated the application through a questionnaire based on the System Usability Scale (SUS). The survey was provided to 15 students selected among those we participated in the preliminary interview. The mean SUS score was 83 (SD 12.9) over a maximum of 100, allowing teachers to use the AR application in their courses. Another important finding is that almost all the students revealed that this application would provide significant power for comprehension on their own.

Keywords: augmented reality, distance learning, STEM didactics, technology in education

Procedia PDF Downloads 103

Authors: Evridiki Papachristou, Nikolaos Bilalis

Abstract:

Imagine an apparel industry where fashion design does not begin with a paper-and-pen drawing which is then translated into pattern and later to a 3D model where the designer tries out different fabrics, colours and contrasts. Instead, imagine a fashion designer in the future who produces that initial fashion drawing in a three-dimensional space and won’t leave that environment until the product is done, communicating his/her ideas with the entire development team in true to life 3D. Three-dimensional (3D) technology - while well established in many other industrial sectors like automotive, aerospace, architecture and industrial design, has only just started to open up a whole range of new opportunities for apparel designers. The paper will discuss the process of 3D simulation technology enhanced by high quality visualization of data and its capability to ensure a massive competitiveness in the market. Secondly, it will underline the most frequent problems & challenges that occur in the process chain when various partners in the production of textiles and apparel are working together. Finally, it will offer a perspective of how the Virtual Prototyping Technology will make the global textile and apparel industry change to a level where designs will be visualized on a computer and various scenarios modeled without even having to produce a physical prototype. This state-of-the-art 3D technology has been described as transformative and“disruptive”comparing to the process of the way apparel companies develop their fashion products today. It provides the benefit of virtual sampling not only for quick testing of design ideas, but also reducing process steps and having more visibility.A so called“digital asset” that can be used for other purposes such as merchandising or marketing.

Keywords: 3D visualization, apparel, virtual prototyping, prototyping technology

Procedia PDF Downloads 546

Authors: Meng-Jou Chien, Jheng-Cheng Chen, Chang-Hsiung Tsai

Abstract:

Let maxζG(m) denote the maximum number of edges in a subgraph of graph G induced by m nodes. The n-dimensional augmented cube, denoted as AQn, a variation of the hypercube, possesses some properties superior to those of the hypercube. We study the cases when G is the augmented cube AQn.

Keywords: interconnection network, augmented cube, induced subgraph, bisection width

Procedia PDF Downloads 368

Authors: C. M. Nur Syazwani, M. K. Ahmad Imran, Rizal E. M. Nasir

Abstract:

The study on BWB UV begins in UiTM since 2005 and three designs have been studied and published. The latest designs are Baseline-III and inspired by birds that have features and aerodynamics behaviour of cruising birds without flapping capability. The aircraft featuring planform and configuration are similar to the bird. Baseline-III has major flaws particularly in its low lift-to-drag ratio, stability and issues regarding limited controllability. New design known as Baseline-IV replaces straight, swept wing to delta wing and have a broader tail compares to the Baseline-III’s. The objective of the study is to investigate aerodynamics of Baseline-IV bird-inspired BWB aircraft. This will be achieved by theoretical calculation and wind tunnel experiments. The result shows that both theoretical and wind tunnel experiments of Baseline-IV graph of CL and CD versus alpha are quite similar to each other in term of pattern of graph slopes and values. Baseline-IV has higher lift coefficient values at wide range of angle of attack compares to Baseline-III. Baseline-IV also has higher maximum lift coefficient, higher maximum lift-to-drag and lower parasite drag. It has stable pitch moment versus lift slope but negative moment at zero lift for zero angle-of-attack tail setting. At high angle of attack, Baseline-IV does not have stability reversal as shown in Baseline-III. Baseline-IV is proven to have improvements over Baseline-III in terms of lift, lift-to-drag ratio and pitch moment stability at high angle-of-attack.

Keywords: blended wing-body, bird-inspired blended wing-body, aerodynamic, stability

Procedia PDF Downloads 479

Authors: Ho-Won Jung, Donghun Lee, Hyung-Jin Kim

Abstract:

Predictive analytics (data analysis) uses a subset of measurements (the features, predictor, or independent variable) to predict another measurement (the outcome, target, or dependent variable) on a single person or unit. It applies empirical methods in statistics, operations research, and machine learning to predict the future, or otherwise unknown events or outcome on a single or person or unit, based on patterns in data. Most analyses of metabolic syndrome are not predictive analytics but statistical explanatory studies that build a proposed model (theory building) and then validate metabolic syndrome predictors hypothesized (theory testing). A proposed theoretical model forms with causal hypotheses that specify how and why certain empirical phenomena occur. Predictive analytics and explanatory modeling have their own territories in analysis. However, predictive analytics can perform vital roles in explanatory studies, i.e., scientific activities such as theory building, theory testing, and relevance assessment. In the context, this study is to demonstrate how to use our predictive analytics to support theory building (i.e., hypothesis generation). For the purpose, this study utilized a big data predictive analytics platform TM based on a co-occurrence graph. The co-occurrence graph is depicted with nodes (e.g., items in a basket) and arcs (direct connections between two nodes), where items in a basket are fully connected. A cluster is a collection of fully connected items, where the specific group of items has co-occurred in several rows in a data set. Clusters can be ranked using importance metrics, such as node size (number of items), frequency, surprise (observed frequency vs. expected), among others. The size of a graph can be represented by the numbers of nodes and arcs. Since the size of a co-occurrence graph does not depend directly on the number of observations (transactions), huge amounts of transactions can be represented and processed efficiently. For a demonstration, a total of 13,254 metabolic syndrome training data is plugged into the analytics platform to generate rules (potential hypotheses). Each observation includes 31 predictors, for example, associated with sociodemographic, habits, and activities. Some are intentionally included to get predictive analytics insights on variable selection such as cancer examination, house type, and vaccination. The platform automatically generates plausible hypotheses (rules) without statistical modeling. Then the rules are validated with an external testing dataset including 4,090 observations. Results as a kind of inductive reasoning show potential hypotheses extracted as a set of association rules. Most statistical models generate just one estimated equation. On the other hand, a set of rules (many estimated equations from a statistical perspective) in this study may imply heterogeneity in a population (i.e., different subpopulations with unique features are aggregated). Next step of theory development, i.e., theory testing, statistically tests whether a proposed theoretical model is a plausible explanation of a phenomenon interested in. If hypotheses generated are tested statistically with several thousand observations, most of the variables will become significant as the p-values approach zero. Thus, theory validation needs statistical methods utilizing a part of observations such as bootstrap resampling with an appropriate sample size.

Keywords: explanatory modeling, metabolic syndrome, predictive analytics, theory building

Procedia PDF Downloads 243

Authors: Wenjun Hou, Marek Perkowski

Abstract:

The Traveling Salesman problem is famous in computing and graph theory. In short, it asks for the Hamiltonian cycle of the least total weight in a given graph with N nodes. All variations on this problem, such as those with K-bounded-degree nodes, are classified as NP-complete in classical computing. Although several papers propose theoretical high-level designs of quantum algorithms for the Traveling Salesman Problem, no quantum circuit implementation of these algorithms has been created up to our best knowledge. In contrast to previous papers, the goal of this paper is not to optimize some abstract complexity measures based on the number of oracle iterations, but to be able to evaluate the real circuit and time costs of the quantum computer. Using the emerging quantum programming language Q# developed by Microsoft, which runs quantum circuits in a quantum computer simulation, an implementation of the bounded-degree problem and its respective quantum circuit were created. To apply Grover’s algorithm to this problem, a quantum oracle was designed, evaluating the cost of a particular set of edges in the graph as well as its validity as a Hamiltonian cycle. Repeating the Grover algorithm with an oracle that finds successively lower cost each time allows to transform the decision problem to an optimization problem, finding the minimum cost of Hamiltonian cycles. N log₂ K qubits are put into an equiprobablistic superposition by applying the Hadamard gate on each qubit. Within these N log₂ K qubits, the method uses an encoding in which every node is mapped to a set of its encoded edges. The oracle consists of several blocks of circuits: a custom-written edge weight adder, node index calculator, uniqueness checker, and comparator, which were all created using only quantum Toffoli gates, including its special forms, which are Feynman and Pauli X. The oracle begins by using the edge encodings specified by the qubits to calculate each node that this path visits and adding up the edge weights along the way. Next, the oracle uses the calculated nodes from the previous step and check that all the nodes are unique. Finally, the oracle checks that the calculated cost is less than the previously-calculated cost. By performing the oracle an optimal number of times, a correct answer can be generated with very high probability. The oracle of the Grover Algorithm is modified using the recalculated minimum cost value, and this procedure is repeated until the cost cannot be further reduced. This algorithm and circuit design have been verified, using several datasets, to generate correct outputs.

Keywords: quantum computing, quantum circuit optimization, quantum algorithms, hybrid quantum algorithms, quantum programming, Grover’s algorithm, traveling salesman problem, bounded-degree TSP, minimal cost, Q# language

Procedia PDF Downloads 144

Authors: Ejikeme Johnson Kanu

Abstract:

This research explores the environmental justice of host communities in south-eastern Nigeria whose source of livelihood has been destroyed due to oil exploitation. Environmental justice scholarship in the area often adopts Western liberal ideology from a more macro level synthesis (Niger Delta). This study therefore explored the sufficiency or otherwise of the adoption of Western liberal ideology in the framing of environmental justice (EJ) in the area which neglects the impact of colonialism and cultural domination. Mixed archival research supplemented by secondary analysis guided this study. Drawing from data analysis, the paper first argues that micro-level studies are required to either validate or invalidate the studies done at the macro-level (Niger Delta) which has often been used to generalise around environmental injustice done within the host communities even though the communities (South-eastern) differ significantly from (South-south) in terms of language, culture, socio-political and economic formation which indicate that the drivers of EJ may differ among them. Secondly, the paper argues that EJ framing from the Western worldview adopted in the study area is insufficient to understand environmental injustice suffered in the study area and there is the need for environmental justice framing that will consider the impact of colonialism and nonrecognition of the cultural identities of the host communities which breed environmental justice. The study, therefore, concludes by drawing from decolonial theory to consider how the framing of EJ would move beyond the western liberal EJ to Indigenous environmental justice.

Keywords: environmental justice, culture, decolonial, nonrecognition, indigenous environmental justice

Procedia PDF Downloads 101

Authors: Marcelo Costa Cardoso, Luciano Pessanha Moreira

Abstract:

In this work, the plastic behaviour of cold-rolled zinc coated dual-phase steel sheets DP600 and DP800 grades is firstly investigated with the help of uniaxial, hydraulic bulge and Forming Limit Curve (FLC) tests. The uniaxial tensile tests were performed in three angular orientations with respect to the rolling direction to evaluate the strain-hardening and plastic anisotropy. True stress-strain curves at large strains were determined from hydraulic bulge testing and fitted to a work-hardening equation. The limit strains are defined at both localized necking and fracture conditions according to Nakajima’s hemispherical punch procedure. Also, an elasto-plastic localization model is proposed in order to predict strain and stress based forming limit curves. The investigated dual-phase sheets showed a good formability in the biaxial stretching and drawing FLC regions. For both DP600 and DP800 sheets, the corresponding numerical predictions overestimated and underestimated the experimental limit strains in the biaxial stretching and drawing FLC regions, respectively. This can be attributed to the restricted failure necking condition adopted in the numerical model, which is not suitable to describe the tensile and shear fracture mechanisms in advanced high strength steels under equibiaxial and biaxial stretching conditions.

Keywords: advanced high strength steels, forming limit curve, numerical modelling, sheet metal forming

Procedia PDF Downloads 344

Authors: Thanusha D. Abeywickrama, Inoka C. Perera, Genji Kurisu

Abstract:

Tuberculosis, considered being as the ninth leading cause of death worldwide, cause from a single infectious agent M. tuberculosis and the drug resistance nature of this bacterium is a continuing threat to the world. Therefore TB preventing treatment is expanding, where this study designed to analyze the regulatory mechanism of GntR transcriptional regulator gene Rv0792c, which lie between several genes codes for some hypothetical proteins, a monooxygenase and an oxidoreductase. The gene encoding Rv0792c was cloned into pET28a and expressed protein was purified to near homogeneity by Nickel affinity chromatography. It was previously reported that the protein binds within the intergenic region (BS region) between Rv0792c gene and monooxygenase (Rv0793). This resulted in binding of three protein molecules with the BS region suggesting tight control of monooxygenase as well as its own gene. Since monooxygenase plays a key role in metabolism, this gene may have a global regulatory role. The natural ligand for this regulator is still under investigation. In relation to the Rv0792 protein structure, a Circular Dichroism (CD) spectrum was carried out to determine its secondary structure elements. Percentage-wise, 17.4% Helix, 21.8% Antiparallel, 5.1% Parallel, 12.3% turn and 43.5% other were revealed from CD spectrum data under room temperature. Differential Scanning Calorimetry (DSC) was conducted to assess the thermal stability of Rv0792, which the melting temperature of protein is 57.2 ± 0.6 °C. The graph of heat capacity (Cp) versus temperature for the best fit was obtained for non-two-state model, which concludes the folding of Rv0792 protein occurs through stable intermediates. Peak area (∆HCal ) and Peak shape (∆HVant ) was calculated from the graph and ∆HCal / ∆HVant was close to 0.5, suggesting dimeric nature of the protein.

Keywords: CD spectrum, DSC analysis, GntR transcriptional regulator, protein structure

Procedia PDF Downloads 197

Authors: M. Nekri, A. Khelladi

Abstract:

The world wide web network is a network with a complex topology, the main properties of which are the distribution of degrees in power law, A low clustering coefficient and a weak average distance. Modeling the web as a graph allows locating the information in little time and consequently offering a help in the construction of the research engine. Here, we present a model based on the already existing probabilistic graphs with all the aforesaid characteristics. This work will consist in studying the web in order to know its structuring thus it will enable us to modelize it more easily and propose a possible algorithm for its exploration.

Keywords: clustering coefficient, preferential attachment, small world, web community

Procedia PDF Downloads 235

Authors: Jeff Chak-Fu Wong, Tony Chun Yin Yip

Abstract:

The transition from secondary school to university seems exciting for many first-year students but can be more challenging than expected. Enabling instructors to know students’ learning habits and styles enhances their understanding of the students’ learning backgrounds, allows teachers to provide better support for their students, and has therefore high potential to improve teaching quality and learning, especially in any mathematics-related courses. The aim of this research is to collect students’ data using online surveys, to analyze students’ factors using learning analytics and educational data mining and to discover the characteristics of the students at risk of falling behind in their studies based on students’ previous academic backgrounds and collected data. In this paper, we use correlation-based distance methods and mutual information for measuring student factor relationships. We then develop a factor network using the Minimum Spanning Tree method and consider further study for analyzing the topological properties of these networks using social network analysis tools. Under the framework of mutual information, two graph-based feature filtering methods, i.e., unsupervised and supervised infinite feature selection algorithms, are used to analyze the results for students’ data to rank and select the appropriate subsets of features and yield effective results in identifying the factors affecting students at risk of failing. This discovered knowledge may help students as well as instructors enhance educational quality by finding out possible under-performers at the beginning of the first semester and applying more special attention to them in order to help in their learning process and improve their learning outcomes.

Keywords: students' academic performance, correlation-based distance method, social network analysis, feature selection, graph-based feature filtering method

Procedia PDF Downloads 92

Authors: Babak Bahri, Fatemeh Yassaee Meybodi, Changiz Eslahchi

Abstract:

In the pursuit of effective cancer therapies, the exploration of combinatorial drug regimens is crucial to leverage synergistic interactions between drugs, thereby improving treatment efficacy and overcoming drug resistance. However, identifying synergistic drug pairs poses challenges due to the vast combinatorial space and limitations of experimental approaches. This study introduces ClusterSyn, a machine learning (ML)-powered framework for classifying anti-cancer drug synergy scores. ClusterSyn employs a two-step approach involving drug clustering and synergy score prediction using a fully connected deep neural network. For each cell line in the training dataset, a drug graph is constructed, with nodes representing drugs and edge weights denoting synergy scores between drug pairs. Drugs are clustered using the Markov clustering (MCL) algorithm, and vectors representing the similarity of drug pairs to each cluster are input into the deep neural network for synergy score prediction (synergy or antagonism). Clustering results demonstrate effective grouping of drugs based on synergy scores, aligning similar synergy profiles. Subsequently, neural network predictions and synergy scores of the two drugs on others within their clusters are used to predict the synergy score of the considered drug pair. This approach facilitates comparative analysis with clustering and regression-based methods, revealing the superior performance of ClusterSyn over state-of-the-art methods like DeepSynergy and DeepDDS on diverse datasets such as Oniel and Almanac. The results highlight the remarkable potential of ClusterSyn as a versatile tool for predicting anti-cancer drug synergy scores.

Keywords: drug synergy, clustering, prediction, machine learning., deep learning

Procedia PDF Downloads 39

Authors: Bhavneet Bharti, Prahbhjot Malhi, Vandana Thakur

Abstract:

Introduction: Children of the urban migrant laborers have great difficulty in accessing government programs which are otherwise routinely available in rural settings. These include programs for child care, nutrition, health and education. There are major communicative fault-lines preventing advocacy for these marginalized children. The overarching aim of this study was to investigate the role of an innovative strategy of children’s drawings in supporting communication between children, social workers, pediatricians and other child advocates to fulfil their fundamental child rights. Materials and Methods: The data was collected over a period of one-year April 2015 to April 2016 during the routine visits by the members of the Social Pediatrics team including a social worker, pediatricians and an artist to the makeshift colony of migrant laborers. Once a week a drawing session was organized where the children including adolescents were asked to any drawing and provide a narrative thereafter. 5-30 children attended these weekly sessions for one year. All these drawings were then classified into various themes and exhibited on 16th April 2016 in the Govt. College of Art Museum. The forum was used for advocacy of Child Rights of these underprivileged children to Secretary social welfare. Results: Mean (SD) age of children in present observational study was 8.5 (2.5) years, with 60% of the boys. Majority of children demonstrated themes which were local and contextualized to their daily needs, threats and festivals which clearly underscored their fundamental right to basic services and equality of opportunities to achieve their full development Drawings of tap with flowing water, queues of people collecting water from hand pumps reflect the local problem of water availability for these children. Young children talking about fear of rape and murder following their drawings indicate the looming threat of potential abuse and neglect. Besides reality driven drawing, children also echoed supernatural beliefs, dangers and festivities in their drawings. Anyone who watched these children at work with art materials was able to see the intense level of absorption, clearly indicating the enjoyment they received, making it a meaningful activity. Indeed, this self-advocacy through art exhibition led to the successful establishment of mobile Anganwadi (A social safety net programme of the government) in their area of stay. Conclusions: This observational study is an example of how children were able to do self-advocacy to protect their rights. Of particular importance, these drawings address how psychologists and other child advocates can ensure in a child-centered manner that the voice of children is heard and represented in all assessments of their well-being and future care options.

Keywords: child advocacy, children drawings, child rights, marginalized children

Procedia PDF Downloads 152

Authors: Konstantinos Pikos, Dimitrios Kaimaris

Abstract:

Although designing building blocks is a procedure used by many planners around the world, there isn’t an automated tool that will help planners and designers achieve their goals with lesser effort. The difficulty of the subject lies in the repeating process of manually drawing lines, while not only it is mandatory to maintain the desirable offset but to also achieve a lesser impact to the existing building stock. In this paper, using Geographical Information Systems (GIS) and the Python programming language, an automated tool integrated into ArcGIS PRO, is being presented. Despite its simplistic enviroment and the lack of specialized building legislation due to the complex state of the field, a planner who is aware of such technical information can use the tool to draw an initial approach of the final building blocks in an area with pre-existing buildings in an attempt to organize the usually sprawling suburbs of a city or any continuously developing area. The tool uses ESRI’s ArcPy library to handle the spatial data, while interactions with the user is made throught Tkinter. The main process consists of a modification of building edgescoordinates, using NumPy library, in an effort to draw the line of best fit, so the user can get the optimal results per block’s side. Finally, after the tool runs successfully, a table of primary planning information is shown, such as the area of the building block and its coverage rate. Regardless of the primary stage of the tool’s development, it is a solid base where potential planners with programming skills could invest, so they can make the tool adapt to their individual needs. An example of the entire procedure in a test area is provided, highlighting both the strengths and weaknesses of the final results.

Keywords: arcPy, GIS, python, building blocks

Procedia PDF Downloads 153

Authors: Bikis Muhammed, Sehra Sedigh Sarvestani, Ali R. Hurson, Lasanthi Gamage

Abstract:

Vehicular traffic events have overly complex spatial correlations and temporal interdependencies and are also influenced by environmental events such as weather conditions. To capture these spatial and temporal interdependencies and make more realistic vehicular traffic predictions, graph neural networks (GNN) based traffic prediction models have been extensively utilized due to their capability of capturing non-Euclidean spatial correlation very effectively. However, most of the already existing GNN-based traffic prediction models have some limitations during learning complex and dynamic spatial and temporal patterns due to the following missing factors. First, most GNN-based traffic prediction models have used static distance or sometimes haversine distance mechanisms between spatially separated traffic observations to estimate spatial correlation. Secondly, most GNN-based traffic prediction models have not incorporated environmental events that have a major impact on the normal traffic states. Finally, most of the GNN-based models did not use an attention mechanism to focus on only important traffic observations. The objective of this paper is to study and make real-time vehicular traffic predictions while incorporating the effect of weather conditions. To fill the previously mentioned gaps, our prediction model uses a real-time driving distance between sensors to build a distance matrix or spatial adjacency matrix and capture spatial correlation. In addition, our prediction model considers the effect of six types of weather conditions and has an attention mechanism in both spatial and temporal data aggregation. Our prediction model efficiently captures the spatial and temporal correlation between traffic events, and it relies on the graph attention network (GAT) and Bidirectional bidirectional long short-term memory (Bi-LSTM) plus attention layers and is called GAT-BILSTMA.

Keywords: deep learning, real time prediction, GAT, Bi-LSTM, attention

Procedia PDF Downloads 44

Authors: Han-Yu Cheng

Abstract:

This study aims to explore the impact of AI-generated illustration works on the aesthetic symbol consumption of consumers in Taiwan. The advancement of artificial intelligence drawing has lowered the barriers to entry, enabling more individuals to easily enter the field of illustration. Using Japanese anime style as an example, with the development of Generative Artificial Intelligence (Generative AI), an increasing number of illustration works are being generated by machines, sparking discussions about aesthetics and art consumption. Through surveys and the analysis of consumer perspectives, this research investigates how this influences consumers' aesthetic experiences and the resulting changes in the traditional art market and among creators. The study reveals that among consumers in Taiwan, particularly those interested in Japanese anime style, there is a pronounced interest and curiosity surrounding the emergence of Generative AI. This curiosity is particularly notable among individuals interested in this style but lacking the technical skills required for creating such artworks. These works, rooted in elements of Japanese anime style, find ready acceptance among enthusiasts of this style due to their stylistic alignment. Consequently, they have garnered a substantial following. Furthermore, with the reduction in entry barriers, more individuals interested in this style but lacking traditional drawing skills have been able to participate in producing such works. Against the backdrop of ongoing debates about artistic value since the advent of artificial intelligence (AI), Generative AI-generated illustration works, while not entirely displacing traditional art, to a certain extent, fulfill the aesthetic demands of this consumer group, providing a similar or analogous aesthetic consumption experience. Additionally, this research underscores the advantages and limitations of Generative AI-generated illustration works within this consumption environment.

Keywords: generative AI, anime aesthetics, Japanese anime illustration, art consumption

Procedia PDF Downloads 44

Authors: Souad Slimani, Sylvain Gravier, Simon Schmidt

Abstract:

Recently, several vertex identifying notions were introduced (identifying coloring, lid-coloring,...); these notions were inspired by identifying codes. All of them, as well as original identifying code, is based on separating two vertices according to some conditions on their closed neighborhood. Therefore, twins can not be identified. So most of known results focus on twin-free graph. Here, we show how twins can modify optimal value of vertex-identifying parameters for identifying coloring and locally identifying coloring.

Keywords: identifying coloring, locally identifying coloring, twins, separating

Procedia PDF Downloads 112

Authors: Yuxi Liu, Boris Belousov, Mehrzad Esmaeili Charkhab, Oliver Tessmann

Abstract:

This paper presents a computational solution for designing reconfigurable interlocking structures that are fully assembled with SL Blocks. Formed by S-shaped and L-shaped tetracubes, SL Block is a specific type of interlocking puzzle. Analogous to molecular self-assembly, the aggregation of SL blocks will build a reversible hierarchical and discrete system where a single module can be numerously replicated to compose semi-interlocking components that further align, wrap, and braid around each other to form complex high-order aggregations. These aggregations can be disassembled and reassembled, responding dynamically to design inputs and changes with a unique capacity for reconfiguration. To use these aggregations as architectural structures, we developed computational tools that automate the configuration of SL blocks based on architectural design objectives. There are three critical phases in our work. First, we revisit the hierarchy of the SL block system and devise a top-down-type design strategy. From this, we propose two key questions: 1) How to translate 3D polyominoes into SL block assembly? 2) How to decompose the desired voxelized shapes into a set of 3D polyominoes with interlocking joints? These two questions can be considered the Hamiltonian path problem and the 3D polyomino tiling problem. Then, we derive our solution to each of them based on two methods. The first method is to construct the optimal closed path from an undirected graph built from the voxelized shape and translate the node sequence of the resulting path into the assembly sequence of SL blocks. The second approach describes interlocking relationships of 3D polyominoes as a joint connection graph. Lastly, we formulate the desired shapes and leverage our methods to achieve their reconfiguration within different levels. We show that our computational strategy will facilitate the efficient design of hierarchical interlocking structures with a self-replicating geometric module.

Keywords: computational design, SL-blocks, 3D polyomino puzzle, combinatorial problem

Procedia PDF Downloads 98

Authors: Amirhossein Dodankeh, Hadi Dabiryan, Saeed Hamze

Abstract:

Using fabrics to reinforce composites considerably leads to improved mechanical properties, including resistance to the impact load and the energy absorption of composites. Warp-knitted spacer fabrics (WKSF) are fabrics consisting of two layers of warp-knitted fabric connected by pile yarns. These connections create a space between the layers filled by pile yarns and give the fabric a three-dimensional shape. Today because of the unique properties of spacer fabrics, they are widely used in the transportation, construction, and sports industries. Polyurethane (PU) foams are commonly used as energy absorbers, but WKSF has much better properties in moisture transfer, compressive properties, and lower heat resistance than PU foam. It seems that the use of warp-knitted spacer fabric reinforced PU foam (WKSFRF) can lead to the production and use of composite, which has better properties in terms of energy absorption from the foam, its mold formation is enhanced, and its mechanical properties have been improved. In this paper, the energy absorption efficiency (EAE) of WKSFRF under low-velocity impact is investigated experimentally. The contribution of the effect of each of the structural parameters of the WKSF on the absorption of impact energy has also been investigated. For this purpose, WKSF with different structures such as two different thicknesses, small and large mesh sizes, and position of the meshes facing each other and not facing each other were produced. Then 6 types of composite samples with different structural parameters were fabricated. The physical properties of samples like weight per unit area and fiber volume fraction of composite were measured for 3 samples of any type of composites. Low-velocity impact with an initial energy of 5 J was carried out on 3 samples of any type of composite. The output of the low-velocity impact test is acceleration-time (A-T) graph with a lot deviation point, in order to achieve the appropriate results, these points were removed using the FILTFILT function of MATLAB R2018a. Using Newtonian laws of physics force-displacement (F-D) graph was drawn from an A-T graph. We know that the amount of energy absorbed is equal to the area under the F-D curve. Determination shows the maximum energy absorption is 2.858 J which is related to the samples reinforced with fabric with large mesh, high thickness, and not facing of the meshes relative to each other. An index called energy absorption efficiency was defined, which means absorption energy of any kind of our composite divided by its fiber volume fraction. With using this index, the best EAE between the samples is 21.6 that occurs in the sample with large mesh, high thickness, and meshes facing each other. Also, the EAE of this sample is 15.6% better than the average EAE of other composite samples. Generally, the energy absorption on average has been increased 21.2% by increasing the thickness, 9.5% by increasing the size of the meshes from small to big, and 47.3% by changing the position of the meshes from facing to non-facing.

Keywords: composites, energy absorption efficiency, foam, geometrical parameters, low-velocity impact, warp-knitted spacer fabric

Procedia PDF Downloads 138

Authors: Mohammed A. Al-Ajmi, Reem S. Al-Kandari

Abstract:

This study is concerned with the behavior of engineering students in Kuwait University which became a concern due to the global issues of education in all levels. A survey has been conducted to identify academic and societal issues that affect the engineering student performance through. The study is drawing major conclusions with regard to private tutoring and the online availability of textbooks’ solution manuals.

Keywords: solution manual, engineering, textbook, ethics

Procedia PDF Downloads 464

Authors: Briante Barretto, Haley Carreon, Anesha-Maelene Ignacio

Abstract:

This research paper explores the dynamic process of cultural resilience within the context of the modern tourism of two traditional island communities (Bali, Indonesia and Guam, Micronesia). It asks the question: How do indigenous people hold on to their foundational values that define their culture while moving forward in the modern world? Both Bali and Guam serve as famous destinations for tourists from all over the world, with millions of visitors on an annual basis. Both are continually being shaped in profound ways by the forces of modernity through globalization. And both are demonstrating cultural resilience while striving to find creative ways to sustain, preserve and strengthen their values and traditions within the context of a thriving modern tourist economy. This research paper, drawing on ethnographic methodologies, and in particular participant observation and in-depth interviews, explores the many challenges both communities face and the strategies and approaches they are learning to employ that help promote sustainable tourism while contributing to cultural preservation. Drawing on the insights gained from field work in both island communities, as well as the growing literature in this field study, the paper posits important lessons that can guide and inform indigenous communities that are being drawn into the global tourism market. One powerful idea emerges in the research and one that seems to guide and shape tourism policy both indigenous communities - that this current generation should be thought of as the ancestors of future generations, and thus they have a weighty responsibility to continue to learn and strive to sustain and preserve their cultures and traditions, their natural environments, and spiritual foundations for the future.

Keywords: bali, culture, environment, guam, tourism, values

Procedia PDF Downloads 45

Authors: Pedro Mota Veiga

Abstract:

This study comprehensively evaluates the repercussions of innovation, digital advancements, and technological capabilities on the operational performance of companies across fifteen European Union countries following the initial wave of the COVID-19 pandemic. Drawing insights from longitudinal data sourced from the 2019 World Bank business surveys and subsequent 2020 World Bank COVID-19 follow-up business surveys, our extensive examination involves a diverse sample of 5763 family businesses. In exploring the relationships between these variables, we adopt a nuanced approach to assess the impact of innovation and digital and technological capabilities on performance. This analysis unfolds along two distinct perspectives: one rooted in necessity and the other insufficiency. The methodological framework employed integrates partial least squares structural equation modeling (PLS-SEM) with condition analysis (NCA), providing a robust foundation for drawing meaningful conclusions. The findings of the study underscore a positive influence on the performance of family firms stemming from both technological capabilities and digital advancements. Furthermore, it is pertinent to highlight the indirect contribution of innovation to enhanced performance, operating through its impact on digital capabilities. This research contributes valuable insights to the broader understanding of how innovation, coupled with digital and technological capabilities, can serve as pivotal factors in shaping the post-COVID-19 landscape for businesses across the European Union. The intricate analysis of family businesses, in particular adds depth to the comprehension of the dynamics at play in diverse economic contexts within the European Union.

Keywords: digital capabilities, technological capabilities, family firms performance, innovation, NCA, PLS-SEM

Procedia PDF Downloads 30

Authors: Fahimeh Palizban, Farshad Noravesh, Amir Hossein Saeidian, Mahya Mehrmohamadi

Abstract:

In the recent decade, the emergence of liquid biopsy has significantly improved cancer monitoring and detection. Dying cells, including those originating from tumors, shed their DNA into the blood and contribute to a pool of circulating fragments called cell-free DNA. Accordingly, identifying the tissue origin of these DNA fragments from the plasma can result in more accurate and fast disease diagnosis and precise treatment protocols. Open chromatin regions are important epigenetic features of DNA that reflect cell types of origin. Profiling these features by DNase-seq, ATAC-seq, and histone ChIP-seq provides insights into tissue-specific and disease-specific regulatory mechanisms. There have been several studies in the area of cancer liquid biopsy that integrate distinct genomic and epigenomic features for early cancer detection along with tissue of origin detection. However, multimodal analysis requires several types of experiments to cover the genomic and epigenomic aspects of a single sample, which will lead to a huge amount of cost and time. To overcome these limitations, the idea of predicting OCRs from WGS is of particular importance. In this regard, we proposed a computational approach to target the prediction of open chromatin regions as an important epigenetic feature from cell-free DNA whole genome sequence data. To fulfill this objective, local sequencing depth will be fed to our proposed algorithm and the prediction of the most probable open chromatin regions from whole genome sequencing data can be carried out. Our method integrates the signal processing method with sequencing depth data and includes count normalization, Discrete Fourie Transform conversion, graph construction, graph cut optimization by linear programming, and clustering. To validate the proposed method, we compared the output of the clustering (open chromatin region+, open chromatin region-) with previously validated open chromatin regions related to human blood samples of the ATAC-DB database. The percentage of overlap between predicted open chromatin regions and the experimentally validated regions obtained by ATAC-seq in ATAC-DB is greater than 67%, which indicates meaningful prediction. As it is evident, OCRs are mostly located in the transcription start sites (TSS) of the genes. In this regard, we compared the concordance between the predicted OCRs and the human genes TSS regions obtained from refTSS and it showed proper accordance around 52.04% and ~78% with all and the housekeeping genes, respectively. Accurately detecting open chromatin regions from plasma cell-free DNA-seq data is a very challenging computational problem due to the existence of several confounding factors, such as technical and biological variations. Although this approach is in its infancy, there has already been an attempt to apply it, which leads to a tool named OCRDetector with some restrictions like the need for highly depth cfDNA WGS data, prior information about OCRs distribution, and considering multiple features. However, we implemented a graph signal clustering based on a single depth feature in an unsupervised learning manner that resulted in faster performance and decent accuracy. Overall, we tried to investigate the epigenomic pattern of a cell-free DNA sample from a new computational perspective that can be used along with other tools to investigate genetic and epigenetic aspects of a single whole genome sequencing data for efficient liquid biopsy-related analysis.

Keywords: open chromatin regions, cancer, cell-free DNA, epigenomics, graph signal processing, correlation clustering

Procedia PDF Downloads 109

Authors: Shankaran Sitarama

Abstract:

New Product Development (NPD) is invariably a team effort and involves effective teamwork. NPD team has members from different disciplines coming together and working through the different phases all the way from conceptual design phase till the production and product roll out. Creativity and Innovation are some of the key factors of successful NPD. Team members going through the different phases of NPD interact and work closely yet challenge each other during the design phases to brainstorm on ideas and later converge to work together. These two traits require the teams to have a divergent and a convergent thinking simultaneously. There needs to be a good balance. The team dynamics invariably result in conflicts among team members. While some amount of conflict (ideational conflict) is desirable in NPD teams to be creative as a group, relational conflicts (or discords among members) could be detrimental to teamwork. Team communication truly reflect these tensions and team dynamics. In this research, team communication (emails) between the members of the NPD teams is considered for analysis. The email communication is processed through a semantic analysis algorithm (LSA) to analyze the content of communication and a semantic similarity analysis to arrive at a social network graph that depicts the communication amongst team members based on the content of communication. The amount of communication (content and not frequency of communication) defines the interaction strength between the members. Social network adjacency matrix is thus obtained for the team. Standard social network analysis techniques based on the Adjacency Matrix (AM) and Dichotomized Adjacency Matrix (DAM) based on network density yield network graphs and network metrics like centrality. The social network graphs are then rendered for visual representation using a Metric Multi-Dimensional Scaling (MMDS) algorithm for node placements and arcs connecting the nodes (representing team members) are drawn. The distance of the nodes in the placement represents the tie-strength between the members. Stronger tie-strengths render nodes closer. Overall visual representation of the social network graph provides a clear picture of the team’s interactions. This research reveals four distinct patterns of team interaction that are clearly identifiable in the visual representation of the social network graph and have a clearly defined computational scheme. The four computational patterns of team interaction defined are Central Member Pattern (CMP), Subgroup and Aloof member Pattern (SAP), Isolate Member Pattern (IMP), and Pendant Member Pattern (PMP). Each of these patterns has a team dynamics implication in terms of the conflict level in the team. For instance, Isolate member pattern, clearly points to a near break-down in communication with the member and hence a possible high conflict level, whereas the subgroup or aloof member pattern points to a non-uniform information flow in the team and some moderate level of conflict. These pattern classifications of teams are then compared and correlated to the real level of conflict in the teams as indicated by the team members through an elaborate self-evaluation, team reflection, feedback form and results show a good correlation.

Keywords: team dynamics, team communication, team interactions, social network analysis, sna, new product development, latent semantic analysis, LSA, NPD teams

Procedia PDF Downloads 35

Authors: Ebru Cubukcu, Gozde Eksioglu Cetintahra, Burcin Hepguzel Hatip, Mert Cubukcu

Abstract:

Obesity and overweight cause serious health problems. Public and private organizations aim to encourage walking in various ways in order to cope with the problem of obesity and overweight. This study aims to understand how the spatial characteristics of urban street pattern, connectivity and complexity influence young people’s choice to walk or not. 185 public university students in Izmir, the third largest city in Turkey, participated in the study. Each participant had worn an accelerometer and a global positioning (GPS) device for a week. The accelerometer device records data on the intensity of the participant’s activity at a specified time interval, and the GPS device on the activities’ locations. Combining the two datasets, activity maps are derived. These maps are then used to differentiate the participants’ walk trips and motor vehicle trips. Given that, the frequency of walk and motor vehicle trips are calculated at the street segment level, and the street segments are then categorized into two as ‘preferred by pedestrians’ and ‘preferred by motor vehicles’. Graph Theory-based accessibility indices are calculated to quantify the spatial characteristics of the streets in the sample. Six different indices are used: (I) edge density, (II) edge sinuosity, (III) eta index, (IV) node density, (V) order of a node, and (VI) beta index. T-tests show that the index values for the ‘preferred by pedestrians’ and ‘preferred by motor vehicles’ are significantly different. The findings indicate that the spatial characteristics of the street network have a measurable effect on young people’s choice to walk or not. Policy implications are discussed. This study is funded by the Scientific and Technological Research Council of Turkey, Project No: 116K358.

Keywords: graph theory, walkability, accessibility, street network

Procedia PDF Downloads 185

Authors: Annika Stechemesser, Rachel Pounds, Emma Lucas, Chris Dawson, Julia Lipecki, Pavle Vrljicak, Jan Brosens, Sean Kehoe, Jason Yap, Lawrence Young, Sascha Ott

Abstract:

Advances in technology make it now possible to retrieve the genetic information of thousands of single cancerous cells. One of the key challenges in single cell analysis of cancerous tissue is to determine the number of different cell types and their characteristic genes within the sample to better understand the tumors and their reaction to different treatments. For this analysis to be possible, it is crucial to filter out background noise as it can severely blur the downstream analysis and give misleading results. In-depth analysis of the state-of-the-art filtering methods for single cell data showed that they do, in some cases, not separate noisy and normal cells sufficiently. We introduced an algorithm that filters and clusters single cell data simultaneously without relying on certain genes or thresholds chosen by eye. It detects communities in a Shared Nearest Neighbor similarity network, which captures the similarities and dissimilarities of the cells by optimizing the modularity and then identifies and removes vertices with a weak clustering belonging. This strategy is based on the fact that noisy data instances are very likely to be similar to true cell types but do not match any of these wells. Once the clustering is complete, we apply a set of evaluation metrics on the cluster level and accept or reject clusters based on the outcome. The performance of our algorithm was tested on three datasets and led to convincing results. We were able to replicate the results on a Peripheral Blood Mononuclear Cells dataset. Furthermore, we applied the algorithm to two samples of ovarian cancer from the same patient before and after chemotherapy. Comparing the standard approach to our algorithm, we found a hidden cell type in the ovarian postchemotherapy data with interesting marker genes that are potentially relevant for medical research.

Keywords: cancer research, graph theory, machine learning, single cell analysis

Procedia PDF Downloads 77

Authors: Dongqin Cheng

Abstract:

The n-dimensional balanced hypercube BHn (n ≥ 1) has been proved to be a bipartite graph. Let P be a set of edges whose induced subgraph consists of pairwise vertex-disjoint paths. For any two vertices u, v from different partite sets of V (BHn). In this paper, we prove that if |P| ≤ 2n − 2 and the subgraph induced by P has neither u nor v as internal vertices, or both of u and v as end-vertices, then BHn contains a Hamiltonian path joining u and v passing through P. As a corollary, if |P| ≤ 2n−1, then the BHn contains a Hamiltonian cycle passing through P.

Keywords: interconnection network, balanced hypercube, Hamiltonian cycle, prescribed edges

Procedia PDF Downloads 174

Authors: Haffaf Hafid

Abstract:

Hypergraphs, after being used to model the structural organization of System of Sytems (SoS) at macroscopic level, has recent trends towards generalizing this powerful representation at different stages of complex system modelling. In this paper, we first describe different applications of hypergraph theory, and step by step, introduce multilevel modeling of SoS by means of integrating Constraint Programming Langages (CSP) dealing with engineering system reconfiguration strategy. As an application, we give an A.C.T Terminal controlled by a set of Intelligent Automated Vehicle.

Keywords: hypergraph model, structural analysis, bipartite graph, monitoring, system of systems, reconfiguration analysis, hypernetwork

Procedia PDF Downloads 459

Authors: Ali Mohammadi

Abstract:

Whenever there is a need to dig the ground, the presence of a surveyor is required to control the map. In projects such as dams and tunnels, these controls are more important because any mistakes can increase the cost. Also, time is great importance in These projects have and one of the ways to reduce the drilling time is to use techniques that can reduce the mapping time in these projects. Nowadays, with the existence of mobile phones, we can design apps that perform calculations and drawing for us on the mobile phone. Also, if we have a device that requires a computer to access its information, by designing an app, we can transfer its information to the mobile phone and use it, so we will not need to go to the office.

Keywords: app, tunnel, excavation, dam

Procedia PDF Downloads 20