Search results for: DNA sequences classification

Authors: Kapil Pandey, Vishnu Goyal

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Spatial and temporal data analysis is very well known in the field of satellite image processing. When spatial data are correlated with time, series analysis it gives the significant results in change detection studies. In this paper the GIS and Remote sensing techniques has been used to find the change detection using time series satellite imagery of Uttarakhand state during the years of 1990-2010. Natural vegetation, urban area, forest cover etc. were chosen as main landuse classes to study. Landuse/ landcover classes within several years were prepared using satellite images. Maximum likelihood supervised classification technique was adopted in this work and finally landuse change index has been generated and graphical models were used to present the changes.

Keywords: GIS, landuse/landcover, spatial and temporal data, remote sensing

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Authors: F. Farzan Nasab, H. J. M. Geijselaers, I. Baran, A. De Boer

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A method is introduced for the coupled skin-rib optimization of a wing box where mass minimization is the objective and local buckling is the constraint. The structure is made of composite materials where continuity of plies in multiple adjacent panels (blending) has to be satisfied. Blending guarantees the manufacturability of the structure; however, it is a highly challenging constraint to treat and has been under debate in recent research in the same area. To fulfill design guidelines with respect to symmetry, balance, contiguity, disorientation and percentage rule of the layup, a reference for the stacking sequences (stacking sequence table or SST) is generated first. Then, an innovative fully gradient-based optimization approach in relation to a specific SST is introduced to obtain the optimum thickness distribution all over the structure while blending is fulfilled. The proposed optimization approach aims to turn the discrete optimization problem associated with the integer number of plies into a continuous one. As a result of a wing box deflection, a rib is subjected to load values which vary nonlinearly with the amount of deflection. The bending stiffness of a skin affects the wing box deflection and thus affects the load applied to a rib. This indicates the necessity of a coupled skin-rib optimization approach for a more realistic optimized design. The proposed method is examined with the optimization of the layup of a composite stiffened skin and rib of a wing torsion box subjected to in-plane normal and shear loads. Results show that the method can successfully prescribe a valid design with a significantly cheap computation cost.

Keywords: blending, buckling optimization, composite panels, wing torsion box

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Authors: Mahmoud M. S. Albattah

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Urbanization results in the expansion of administrative boundaries, mainly at the periphery, ultimately leading to changes in landcover. Agricultural land, naturally vegetated land, and other land types are converted into residential areas with a high density of constructs, such as transportation systems and housing. In urban regions of rapid growth and change, urban planners need regular information on up to date ground change. Amman (the capital of Jordan) is growing at unprecedented rates, creating extensive urban landscapes. Planners interact with these changes without having a global view of their impact. The use of aerial photographs and satellite images data combined with topographic information and field survey could provide effective information to develop urban change and growth inventory which could be explored towards producing a very important signature for the built-up area changes.

Keywords: highway design, satellite technologies, remote sensing, GIS, image segmentation, classification

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Authors: Piyush Samant, Ravinder Agarwal

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Complementary and Alternative Medicine (CAM) techniques are quite popular and effective for chronic diseases. Iridology is more than 150 years old CAM technique which analyzes the patterns, tissue weakness, color, shape, structure, etc. for disease diagnosis. The objective of this paper is to validate the use of iridology for the diagnosis of the diabetes. The suggested model was applied in a systemic disease with ocular effects. 200 subject data of 100 each diabetic and non-diabetic were evaluated. Complete procedure was kept very simple and free from the involvement of any iridologist. From the normalized iris, the region of interest was cropped. All 63 features were extracted using statistical, texture analysis, and two-dimensional discrete wavelet transformation. A comparison of accuracies of six different classifiers has been presented. The result shows 89.66% accuracy by the random forest classifier.

Keywords: complementary and alternative medicine, classification, iridology, iris, feature extraction, disease prediction

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Authors: Tharini N. de Silva, Xiao Zhibo, Zhao Rui, Mao Kezhi

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Causal relation identification is a crucial task in information extraction and knowledge discovery. In this work, we present two approaches to causal relation identification. The first is a classification model trained on a set of knowledge-based features. The second is a deep learning based approach training a model using convolutional neural networks to classify causal relations. We experiment with several different convolutional neural networks (CNN) models based on previous work on relation extraction as well as our own research. Our models are able to identify both explicit and implicit causal relations as well as the direction of the causal relation. The results of our experiments show a higher accuracy than previously achieved for causal relation identification tasks.

Keywords: causal realtion extraction, relation extracton, convolutional neural network, text representation

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Authors: Professor Jo Angouri, Polina Mesinioti, Chris Turner

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In order for a group of ad-hoc professional to perform as a team, a shared understanding of the problem at hand and an agreed action plan are necessary components. This is particularly significant in complex, time sensitive professional settings such as in trauma emergencies. In this context, team briefings prior to the patient arrival (pre-briefings) constitute a critical event for the performance of the team; they provide the necessary space for co-constructing a shared understanding of the situation through summarising information available to the team: yet the act of summarising is widely assumed in medical practice but not systematically researched. In the vast teamwork literature, terms such as ‘shared mental model’, ‘mental space’ and ‘cognate labelling’ are used extensively, and loosely, to denote the outcome of the summarising process, but how exactly this is done interactionally remains under researched. This paper reports on the forms and functions of pre-briefings in a major trauma centre in the UK. Taking an interactional approach, we draw on 30 simulated and real-life trauma emergencies (15 from each dataset) and zoom in on the use of pre-briefings, which we consider focal points in the management of trauma emergencies. We show how ad hoc teams negotiate sharedness of future orientation through summarising, synthesising information, and establishing common understanding of the situation. We illustrate the role, characteristics, and structure of pre-briefing sequences that have been evaluated as ‘efficient’ in our data and the impact (in)effective pre-briefings have on teamwork. Our work shows that the key roles in the event own the act of summarising and we problematise the implications for leadership in trauma emergencies. We close the paper with a model for pre-briefing and provide recommendations for clinical practice, arguing that effective pre-briefing practice is teachable.

Keywords: summarising, medical emergencies, interaction analysis, shared/mental models

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Authors: Zhao Haoyue

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Due to the combined effects of climate change, urban expansion, and population growth, various environmental issues, such as urban heat islands and pollution, arise. Therefore, reliable information on urban environmental climate is needed to address and mitigate the negative effects. The emergence of urban climate maps provides a practical basis for urban climate regulation and improvement. This article takes Shapingba District, Chongqing City, as an example to study the construction method of urban thermal environment climate maps based on GIS spatial analysis technology. The thermal load, ventilation potential analysis map, and thermal environment comprehensive analysis map were obtained. Based on the classification criteria obtained from the climate map, corresponding protection and planning mitigation measures have been proposed.

Keywords: urban climate, GIS, heat island analysis, urban thermal environment

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Authors: Loai Abdallah, Malik Yousef

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A domain space for the data should reflect the actual similarity between objects. Since objects belonging to the same cluster usually share some common traits even though their geometric distance might be relatively large. In general, the Euclidean distance of data points that represented by large number of features is not capturing the actual relation between those points. In this study, we propose a new method to construct a different space that is based on clustering to form a new distance metric. The new distance space is based on ensemble clustering (EC). The EC distance space is defined by tracking the membership of the points over multiple runs of clustering algorithm metric. Over this distance, we train the decision trees classifier (DT-EC). The results obtained by applying DT-EC on 10 datasets confirm our hypotheses that embedding the EC space as a distance metric would improve the performance.

Keywords: ensemble clustering, decision trees, classification, K nearest neighbors

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Authors: H. M. Soroush

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The problem of scheduling products and services for on-time deliveries is of paramount importance in today’s competitive environments. It arises in many manufacturing and service organizations where it is desirable to complete jobs (products or services) with different weights (penalties) on or before their due dates. In such environments, schedules should frequently decide whether to schedule a job based on its processing time, due-date, and the penalty for tardy delivery to improve the system performance. For example, it is common to measure the weighted number of late jobs or the percentage of on-time shipments to evaluate the performance of a semiconductor production facility or an automobile assembly line. In this paper, we address the problem of scheduling a set of jobs on a server where processing times or due-dates of jobs are random variables and fixed weights (penalties) are imposed on the jobs’ late deliveries. The goal is to find the schedule that minimizes the expected weighted number of tardy jobs. The problem is NP-hard to solve; however, we explore three scenarios of the problem wherein: (i) both processing times and due-dates are stochastic; (ii) processing times are stochastic and due-dates are deterministic; and (iii) processing times are deterministic and due-dates are stochastic. We prove that special cases of these scenarios are solvable optimally in polynomial time, and introduce efficient heuristic methods for the general cases. Our computational results show that the heuristics perform well in yielding either optimal or near optimal sequences. The results also demonstrate that the stochasticity of processing times or due-dates can affect scheduling decisions. Moreover, the proposed problem is general in the sense that its special cases reduce to some new and some classical stochastic single machine models.

Keywords: number of late jobs, scheduling, single server, stochastic

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Authors: Shuai Zhao, Shalendra D. Sharma, Jin Xu

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This research uses advanced machine learning models to learn a number of hypotheses regarding political executives. Specifically, it analyses the impact these powerful leaders have on economic growth by using leaders’ data from the Archigos database from 1835 to the end of 2015. The data is processed by the AutoGluon, which was developed by Amazon. Automated Machine Learning (AutoML) and AutoGluon can automatically extract features from the data and then use multiple classifiers to train the data. Use a linear regression model and classification model to establish the relationship between leaders and economic growth (GDP per capita growth), and to clarify the relationship between their characteristics and economic growth from a machine learning perspective. Our work may show as a model or signal for collaboration between the fields of statistics and artificial intelligence (AI) that can light up the way for political researchers and economists.

Keywords: comparative politics, political executives, leaders’ characteristics, artificial intelligence

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Authors: Ilirian Laçi, Alketa Spahiu

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Modality of treatment in hepatocellular carcinoma (HCC) patients depends on the stage of the disease. The Barcelona Clinic Liver Cancer Classification (BCLC) is the preferred staging system. There are many patients initially present with intermediate-stage disease. For these patients, transarterial chemoembolization (TACE) is the treatment of choice. The differences in individual factors that are not captured by the BCLC framework, such as the tumor growth pattern, degree of hypervascularity, and vascular supply, complicate further evaluation of these patients. Because of these differences, not all patients benefit equally from TACE. Several tools have been devised to aid the decision-making process, which have shown promising initial results but have failed external evaluation and have not been translated to the clinic aspects. Criteria for treatment decisions in daily clinical practice are needed in all stages of the disease.

Keywords: hepatocellular carcinoma, transarterial chemoembolization, TACE, liver

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Authors: Rahul Patel, S. P. Dave, M. V Shah

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Ahmedabad is a rapidly growing city in western India that is experiencing significant urbanization and industrialization. With projections indicating that it will become a metropolitan city in the near future, various construction activities are taking place, making soil testing a crucial requirement before construction can commence. To achieve this, construction companies and contractors need to periodically conduct soil testing. This study focuses on the process of creating a spatial database that is digitally formatted and integrated with geotechnical data and a Geographic Information System (GIS). Building a comprehensive geotechnical Geo-database involves three essential steps. Firstly, borehole data is collected from reputable sources. Secondly, the accuracy and redundancy of the data are verified. Finally, the geotechnical information is standardized and organized for integration into the database. Once the Geo-database is complete, it is integrated with GIS. This integration allows users to visualize, analyze, and interpret geotechnical information spatially. Using a Topographic to Raster interpolation process in GIS, estimated values are assigned to all locations based on sampled geotechnical data values. The study area was contoured for SPT N-Values, Soil Classification, Φ-Values, and Bearing Capacity (T/m2). Various interpolation techniques were cross-validated to ensure information accuracy. The GIS map generated by this study enables the calculation of SPT N-Values, Φ-Values, and bearing capacities for different footing widths and various depths. This approach highlights the potential of GIS in providing an efficient solution to complex phenomena that would otherwise be tedious to achieve through other means. Not only does GIS offer greater accuracy, but it also generates valuable information that can be used as input for correlation analysis. Furthermore, this system serves as a decision support tool for geotechnical engineers. The information generated by this study can be utilized by engineers to make informed decisions during construction activities. For instance, they can use the data to optimize foundation designs and improve site selection. In conclusion, the rapid growth experienced by Ahmedabad requires extensive construction activities, necessitating soil testing. This study focused on the process of creating a comprehensive geotechnical database integrated with GIS. The database was developed by collecting borehole data from reputable sources, verifying its accuracy and redundancy, and organizing the information for integration. The GIS map generated by this study is an efficient solution that offers greater accuracy and generates valuable information that can be used as input for correlation analysis. It also serves as a decision support tool for geotechnical engineers, allowing them to make informed decisions during construction activities.

Keywords: arcGIS, borehole data, geographic information system (GIS), geo-database, interpolation, SPT N-value, soil classification, φ-value, bearing capacity

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Authors: Alfonsina Buoniconto

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The aim of this study is to investigate the degree of cross-linguistic and intra-linguistic variation in the encoding of motion events (MEs) in English and Italian, these being typologically different languages both showing signs of disobedience to their respective types. As a matter of fact, the traditional typological classification of MEs encoding distributes languages into two macro-types, based on the preferred locus for the expression of Path, the main ME component (other components being Figure, Ground and Manner) characterized by conceptual and structural prominence. According to this model, Satellite-framed (SF) languages typically express Path information in verb-dependent items called satellites (e.g. preverbs and verb particles) with main verbs encoding Manner of motion; whereas Verb-framed languages (VF) tend to include Path information within the verbal locus, leaving Manner to adjuncts. Although this dichotomy is valid altogether, languages do not always behave according to their typical classification patterns. English, for example, is usually ascribed to the SF type due to the rich inventory of postverbal particles and phrasal verbs used to express spatial relations (i.e. the cat climbed down the tree); nevertheless, it is not uncommon to find constructions such as the fog descended slowly, which is typical of the VF type. Conversely, Italian is usually described as being VF (cf. Paolo uscì di corsa ‘Paolo went out running’), yet SF constructions like corse via in lacrime ‘She ran away in tears’ are also frequent. This paper will try to demonstrate that such a typological overlapping is due to the fact that the semantic units making up MEs are distributed within several loci of the sentence –not only verbs and satellites– thus determining a number of different constructions stemming from convergent factors. Indeed, the linguistic expression of motion events depends not only on the typological nature of languages in a traditional sense, but also on a series morphological, lexical, and syntactic resources, as well as on inferential, discursive, usage-related, and cultural factors that make semantic information more or less accessible, frequent, and easy to process. Hence, rather than describe English and Italian in dichotomic terms, this study focuses on the investigation of cross-linguistic and intra-linguistic variation in the use of all the strategies made available by each linguistic system to express motion. Evidence for these assumptions is provided by parallel corpora analysis. The sample texts are taken from two contemporary Italian novels and their respective English translations. The 400 motion occurrences selected (200 in English and 200 in Italian) were scanned according to the MODEG (an acronym for Motion Decoding Grid) methodology, which grants data comparability through the indexation and retrieval of combined morphosyntactic and semantic information at different levels of detail.

Keywords: construction typology, motion event encoding, parallel corpora, satellite-framed vs. verb-framed type

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Authors: Marina Yurievna Aleksandrova

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Research of the Holocaust retains value not only for history but also for sociology and psychology. One of the most important fields of study is how people were coping during and after this traumatic event. The aim of this paper is to identify the main contexts of the topic of love and to determine which contexts are more characteristic for different groups of victims of the Holocaust (gender, nationality, age). In this research, transcripts of interviews with Holocaust victims that were collected during 1946 for the "Voices of the Holocaust" project were used as data. Main contexts were analyzed with methods of network analysis and latent semantic analysis and classified by gender, age, and nationality with random forest. The results show that love is articulated and described significantly differently for male and female informants, nationality is shown results with lower values of quality metrics, as well as the age.

Keywords: Holocaust, latent semantic analysis, network analysis, text-mining, random forest

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Authors: Rolando Barradas, Salviano Soares, António Valente, José Alberto Lencastre, Paulo Oliveira

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This article reviews the Ant Colony Optimization, a nature-inspired algorithm, and its implementation in the Scratch/m-Block programming environment. The Ant Colony Optimization is a part of Swarm Intelligence-based algorithms and is a subset of biological-inspired algorithms. Starting with a problem in which one has a maze and needs to find its path to the center and return to the starting position. This is similar to an ant looking for a path to a food source and returning to its nest. Starting with the implementation of a simple wall follower simulator, the proposed solution uses a dynamic graphical interface that allows young students to observe the ants’ movement while the algorithm optimizes the routes to the maze’s center. Things like interface usability, Data structures, and the conversion of algorithmic language to Scratch syntax were some of the details addressed during this implementation. This gives young students an easier way to understand the computational concepts of sequences, loops, parallelism, data, events, and conditionals, as they are used through all the implemented algorithms. Future work includes the simulation results with real contest mazes and two different pheromone update methods and the comparison with the optimized results of the winners of each one of the editions of the contest. It will also include the creation of a Digital Twin relating the virtual simulator with a real micromouse in a full-size maze. The first test results show that the algorithm found the same optimized solutions that were found by the winners of each one of the editions of the Micromouse contest making this a good solution for maze pathfinding.

Keywords: nature inspired algorithms, scratch, micromouse, problem-solving, computational thinking

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Authors: Omair Ghori, Anton Stadler, Stefan Wilk, Wolfgang Effelsberg

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Fire-related incidents account for extensive loss of life and material damage. Quick and reliable detection of occurring fires has high real world implications. Whereas a major research focus lies on the detection of outdoor fires, indoor camera-based fire detection is still an open issue. Cameras in combination with computer vision helps to detect flames and smoke more quickly than conventional fire detectors. In this work, we present a computer vision-based smoke detection algorithm based on contrast changes and a multi-step classification. This work accelerates computer vision-based fire detection considerably in comparison with classical indoor-fire detection.

Keywords: contrast analysis, early fire detection, video smoke detection, video surveillance

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Authors: Jayant Kumar, Aarcha Jayachandran Sasikala, Barry Adrian Shepherd

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Public Distribution System is a flagship welfare programme of the Government of India with both historical and political significance. Targeted at lower sections of society,it is one of the largest supply chain networks in the world. There has been several studies by academics and planning commission about the effectiveness of the system. Our study focuses on applying predictive analytics to aid the central body to keep track of the problem of breach of service level agreement between the two echelons of food supply chain. Each shop breach is leading to a potential additional inventory carrying cost. Thus, through this study, we aim to show that aided with such analytics, the network can be made more cost effective. The methods we illustrate in this study are applicable to other commercial supply chains as well.

Keywords: PDS, analytics, cost effectiveness, Karnataka, inventory cost, service level JEL classification: C53

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Authors: Paata Sitchinava

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It has been studied phenomena subjected on the water physical (hydrophysical, mineralogy containing, specific hydrophysical) class of heavy clay soils of the Colchis lowland, according to various categories and forms of the porous water, which will be the base of the distributed used methods of the engineering practice and reclamation effectiveness evaluation. According to of clay grounds data, it has been chosen three research bases section in the central part of lowland, where has implemented investigation works by using a special program. It has been established, that three of cuts are somewhat identical, and by morphological grounds separated layers are the difference by Gallic quality. It has been implemented suitable laboratory experimental research at the samples taken from the cuts, at the base of these created classification mark of physical-technical characteristic, which is the base of suitable calculation of hydrophysical researches.

Keywords: Colchis lowland, drainage, water, soil-ground

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Authors: Daniela Panico

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Framed by language socialization and family language policy theories, the present study explores the ways the language choice patterns of bilingual siblings contribute to the shaping of the language environment and the language practices of Italian/English families residing in Sydney. The main source of data is video recordings of naturally occurring parent-children and child-to-child interactions during everyday routines (i.e., family mealtimes and siblings playtime) in the home environment. Recurrent interactional practices are analyzed in detail through a conversational analytical approach. This presentation focuses on the interactional trajectories developing during the negotiation of language choices between all family members and between siblings in face-to-face interactions. Fine-grained analysis is performed on language negotiation sequences of multiparty bilingual conversations in order to uncover the sequential patterns through which a) the children respond to the parental strategies aiming to minority language maintenance, and b) the siblings influence each other’s language use and choice (e.g., older siblings positioning themselves as language teachers and language brokers, younger siblings accepting the role of apprentices). The findings show that, along with the parents, children are active socializing agents in the family and, with their linguistic behavior, they contribute to the establishment of a bilingual or a monolingual context in the home. Moreover, by orienting themselves towards the use of one or the other language in family talk, bilingual siblings are a major internal micro force in the language ecology of a bilingual family and can strongly support language maintenance or language shift processes in such domain. Overall, the study provides insights into the dynamic ways in which family language policy is interactionally negotiated and instantiated in bilingual homes as well as the challenges of intergenerational language transmission.

Keywords: bilingual siblings, family interactions, family language policy, language maintenance

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Authors: Nebi Gedik

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One of the significant and continual public health problems in the world is breast cancer. Early detection is very important to fight the disease, and mammography has been one of the most common and reliable methods to detect the disease in the early stages. However, it is a difficult task, and computer-aided diagnosis (CAD) systems are needed to assist radiologists in providing both accurate and uniform evaluation for mass in mammograms. In this study, a multiresolution statistical method to classify mammograms as normal and abnormal in digitized mammograms is used to construct a CAD system. The mammogram images are represented by wave atom transform, and this representation is made by certain groups of coefficients, independently. The CAD system is designed by calculating some statistical features using each group of coefficients. The classification is performed by using support vector machine (SVM).

Keywords: wave atom transform, statistical features, multi-resolution representation, mammogram

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Authors: Yi-Ling Chen, Dung-Ying Lin

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In the manufacturing process, computer numerical control (CNC) machining plays a crucial role. CNC enables precise machinery control through computer programs, achieving automation in the production process and significantly enhancing production efficiency. However, traditional CNC production lines often require manual intervention for loading and unloading operations, which limits the production line's operational efficiency and production capacity. Additionally, existing CNC automation systems frequently lack sufficient intelligence and fail to achieve optimal configuration efficiency, resulting in the need for substantial time to reconfigure production lines when producing different products, thereby impacting overall production efficiency. Using the NSGA-II algorithm, we generate production line layout configurations that consider field constraints and select robotic arm specifications from an arm list. This allows us to calculate loading and unloading times for each job order, perform demand allocation, and assign processing sequences. The NSGA-II algorithm is further employed to determine the optimal processing sequence, with the aim of minimizing demand completion time and maximizing average machine utilization. These objectives are used to evaluate the performance of each layout, ultimately determining the optimal layout configuration. By employing this method, it enhance the configuration efficiency of CNC production lines and establish an adaptive capability that allows the production line to respond promptly to changes in demand. This will minimize production losses caused by the need to reconfigure the layout, ensuring that the CNC production line can maintain optimal efficiency even when adjustments are required due to fluctuating demands.

Keywords: evolutionary algorithms, multi-objective optimization, pareto optimality, layout optimization, operations sequence

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Authors: Thobela Conco, Sheena Kumari, Chika Nnadozie, Mahmoud Nasr, Thor A. Stenström, Mushal Ali, Arshad Ismail, Faizal Bux

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The discharge of antibiotics and its residues into the wastewater treatment plants (WWTP’s) create a conducive environment for the development of antibiotic resistant pathogens. This presents a risk of potential dissemination of antibiotic resistant pathogens and antibiotic resistance genes into the environment. It is, therefore, necessary to study the level of antibiotic resistance genes (ARG’s) among bacterial pathogens that proliferate in biological wastewater treatment systems. In the current study, metagenomic and meta-transcriptomic sequences of samples collected from the influents, secondary effluents and post chlorinated effluents of three wastewater treatment plants treating domestic and hospital effluents in Durban, South Africa, were analyzed for profiling of ARG’s among bacterial pathogens. Results show that a variety of ARG’s, mostly, aminoglycoside, β-lactamases, tetracycline and sulfonamide resistance genes were harbored by diverse bacterial genera found at different stages of treatment. A significant variation in diversity of pathogen and ARGs between the treatment plant was observed; however, treated final effluent samples from all three plants showed a significant reduction in bacterial pathogens and detected ARG’s. Both pre- and post-chlorinated samples showed the presence of mobile genetic elements (MGE’s), indicating the inefficiency of chlorination to remove of ARG’s integrated with MGE’s. In conclusion, the study showed the wastewater treatment plant efficiently caused the reduction and removal of certain ARG’s, even though the initial focus was the removal of biological nutrients.

Keywords: antibiotic resistance, mobile genetic elements, wastewater, wastewater treatment plants

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Authors: Adrien Marque, Daniel Delahaye, Pierre Maréchal, Isabelle Berry

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Wind direction and uncertainty are crucial in aircraft or unmanned aerial vehicle trajectories. By computing wind covariance matrices on each spatial grid point, these spatial grids can be defined as images with symmetric positive definite matrix elements. A data pre-processing step, a specific convolution, a specific max-pooling, and a specific flatten layers are implemented to process such images. Then, the neural network is applied to spatial grids, whose elements are wind covariance matrices, to solve classification problems related to the feasibility of unmanned aerial vehicles based on wind direction and wind uncertainty.

Keywords: wind direction, uncertainty level, unmanned aerial vehicle, convolution neural network, SPD matrices

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Authors: Malorzata Kmiotek, Anna Kucaba-Pietal, Robert Smusz

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Due to the miniaturisation process, in many technical devices, microchannels are used in cooling systems. Because of the small size of microchannels, the flow inside is laminar, which caused a slow heat exchange. In order to intensify the heat exchange, the flow must be disturbed, for example, by introducing obstacles. We present results on the influence of a thin obstacle, placed on microchannel wall, on the fluid and heat flow in the aspect of their use by constructors of heat exchangers. The obstacle is called 'thin' when its geometrical parameter (o=w/h, w- width, h - height of the obstacle) satisfies inequality: o < 0.5. In this work, we report numerical results on heat and mass transfer in the microchannels of 400 micrometer height (H - height of the microchannel), where thin obstacles are immersed on the walls, to disturb the flow. The Reynolds number of the flow in microchannel varies between 20 and 200 and is typical for the flow in micro heat exchangers. The equations describing the fluid and heat flows in microchannels were solved numerically by using the finite element method with an application of CFD&FSI package of ADINA R&D, Inc. 9.4 solver. In the case of flows in the microchannels with sequences of thin rectangular obstacles placed on the bottom and the top wall of a microchannel, the influence of distances s (s is the distance between two thin obstacles) and heights of obstacles on the fluid and heat transfer was investigated. Thermal and flow conditions of the application area of microchannels in electronic cooling systems, i.e., wall temperature of 60 °C, the fluid temperature of 20°C were used to solve equations. Additionally, the distance s between the thin obstacles in microchannels as a multiple of the amount of the channel height was determined. Results show that placing thin obstacles on microchannel walls increase the length of recirculation zones of the flow and improves the heat transfer.

Keywords: Finite Element Method, heat transfer, mechanical engineering, microchannel

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Authors: Muhammad Arslan Usman, Muhammad Rehan Usman, Soo Young Shin

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Live video streaming is one of the most widely used service among end users, yet it is a big challenge for the network operators in terms of quality. The only way to provide excellent Quality of Experience (QoE) to the end users is continuous monitoring of live video streaming. For this purpose, there are several objective algorithms available that monitor the quality of the video in a live stream. Subjective tests play a very important role in fine tuning the results of objective algorithms. As human perception is considered to be the most reliable source for assessing the quality of a video stream, subjective tests are conducted in order to develop more reliable objective algorithms. Temporal impairments in a live video stream can have a negative impact on the end users. In this paper we have conducted subjective evaluation tests on a set of video sequences containing temporal impairment known as frame freezing. Frame Freezing is considered as a transmission error as well as a hardware error which can result in loss of video frames on the reception side of a transmission system. In our subjective tests, we have performed tests on videos that contain a single freezing event and also for videos that contain multiple freezing events. We have recorded our subjective test results for all the videos in order to give a comparison on the available No Reference (NR) objective algorithms. Finally, we have shown the performance of no reference algorithms used for objective evaluation of videos and suggested the algorithm that works better. The outcome of this study shows the importance of QoE and its effect on human perception. The results for the subjective evaluation can serve the purpose for validating objective algorithms.

Keywords: objective evaluation, subjective evaluation, quality of experience (QoE), video quality assessment (VQA)

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Authors: Hyun-Koo Kim, Yonghun Kim, Yong-Hoon Kim, Ju Hee Lee, Myungho Song

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In this paper, we have described an efficient stereo matching method and pedestrian detection method using stereo types LWIR camera. We compared with three types stereo camera algorithm as block matching, ELAS, and SGM. For pedestrian detection using stereo LWIR camera, we used that SGM stereo matching method, free space detection method using u/v-disparity, and HOG feature based pedestrian detection. According to testing result, SGM method has better performance than block matching and ELAS algorithm. Combination of SGM, free space detection, and pedestrian detection using HOG features and SVM classification can detect pedestrian of 30m distance and has a distance error about 30 cm.

Keywords: advanced driver assistance system, pedestrian detection, stereo matching method, stereo long-wave IR camera

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Authors: Alhusein Almahjoub, Dongyu Qiu

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This paper deals with the random access procedure in next-generation networks and presents the solution to reduce total service time (TST) which is one of the most important performance metrics in current and future internet of things (IoT) based networks. The proposed solution focuses on the calculation of optimal transmission probability which maximizes the success probability and reduces TST. It uses the information of several idle preambles in every time slot, and based on it, it estimates the number of backlogged IoT devices using Naïve Bayes estimation which is a type of supervised learning in the machine learning domain. The estimation of backlogged devices is necessary since optimal transmission probability depends on it and the eNodeB does not have information about it. The simulations are carried out in MATLAB which verify that the proposed solution gives excellent performance.

Keywords: random access, LTE/LTE-A, 5G, machine learning, Naïve Bayes estimation

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Authors: Muhammad Yasir Latif

Abstract:

Industrial Engineering and Management (IEM) is a continuous, adaptable, and dynamic branch of engineering. The purpose of this study is to use a knowledge-based course classification method to investigate four IEM educational programs in Europe. Furthermore, the relative weight of each sector was determined using the credit value of the courses. IEM-specific locations and pooled areas were the two related kinds of areas that were used. The results show that, among the four program curricula, Production Management is the specific area with the largest weight, while the specialism field of IEM has a similar weight. This method has proved to be useful for curriculum analysis. The results show that one characteristic of IEM curriculum programs is diversity in the knowledge domains related to IEM specialism. The research also highlights the importance of an organized structure for defining IEM applications, allowing benchmarking efforts, and promoting communication between academics and the IEM community.

Keywords: industrial engineering and management, knowledge areas, curriculum analysis, community

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Authors: Hanane Sarnou, Sabri Koç

Abstract:

In this paper, the interconnection between curriculum development for basic education and the use of information and communication technologies (ICTs) in the classroom referring to the Licence, Master's and Doctorate (LMD) benefits under such link will be presented and analysed. This study seeks to achieve to what extent LMD, competency-based approach (CBA) and ICTs use are interrelated. Likewise, the data collected from the responses of our teachers and learners who are concerned with LMD impact on their learning and teaching through interviews will be discussed, analysed, and classified. This paper is divided into two sections. The first section is about the curriculum development for basic education and its relation with higher education under the LMD and its link with ICTs in the university while the second section is about the classification of learners’ and teachers’ positive/negative responses concerning their positive or negative attitudes towards the ICT integration. The focus will be on the positive aspects of students’ expectations, opinions and assumptions regarding the integration of ICTs into the classroom under LMD and CBA.

Keywords: LMD system, CBA approach, curriculum development, ICT

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Authors: Mahima Dubey, Girish Chandel

Abstract:

Minor millets are highly nutritious and climate resilient cereal crops. These features make them ideal candidates to excavate the physiology of the underlying mechanism. In an attempt to understand the basis of mineral nutrition in minor millets, a set of five Barnyard millet genotypes were analyzed for grain Fe and Zn content under contrasting Fe-Zn supply to identify genotypes proficient in tolerating mineral deficiency. This resulted in the identification of Melghat-1 genotype to be nutritionally superior with better ability to withstand deficiency. Expression analysis of several Nicotianamine synthase (NAS) genes showed that HvNAS1 and OsNAS2 genes were prominent in positively mediating mineral deficiency response in Barnyard millet. Further, strategic efforts were employed for fast-track identification of more effective orthologous NAS genes from Barnyard millet. This resulted in the identification of two genes namely EfNAS1 (orthologous to HvNAS1 of barley) and EfNAS2 (orthologous to OsNAS2 gene of rice). Sequencing and thorough characterization of these sequences revealed the presence of intact NAS domain and signature tyrosine and di-leucine motifs in their predicted proteins and thus established their candidature as functional NAS genes in Barnyard millet. Moreover, EfNAS1 showed structural superiority over previously known NAS genes and is anticipated to have role in more efficient metal transport. Findings of the study provide insight into Fe-Zn deficiency response and mineral nutrition in millets. This provides millets with a physiological edge over micronutrient deficient staple cereals such as rice in withstanding Fe-Zn deficiency and subsequently accumulating higher levels of Fe and Zn in millet grains.

Keywords: gene expression, micronutrient, millet, ortholog

Procedia PDF Downloads 231