Search results for: dispersed region growing algorithm (DRGA)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11451

Search results for: dispersed region growing algorithm (DRGA)

6411 The Challenges and Opportunities Faced by Women in Geomatics Engineering: The Case of the SADC Region

Authors: Moreblessings Shoko

Abstract:

Polymersomes are materials which are considered as artificial counterparts of natural vesicles. The nanotechnology of such smart nanovesicles is very useful to enhance the efficiency of many therapeutic and diagnostic drugs. Those compounds show a higher stability, flexibility, and mechanical strength to the membrane compared to natural liposomes. Also, they can be designed in detail, the permeability of the membrane can be controlled by different stimuli, and the surface can be functionalized with different biological molecules to facilitate monitoring and target. For this purpose, this study demonstrates the formation of multifunctional and pH sensitive polymersomes and their functionalization with different reactive groups or biomolecules inside and outside of polymersomes´ membrane providing by crossing the membrane and docking/undocking processes for biomedical applications. Overall, they are highly versatile and thus present new opportunities for the design of targeted and selective recognition systems, for example, in mimicking cell functions and in synthetic biology.

Keywords: women, geomatics, challenges, capacity building

Procedia PDF Downloads 570
6410 Efficient Passenger Counting in Public Transport Based on Machine Learning

Authors: Chonlakorn Wiboonsiriruk, Ekachai Phaisangittisagul, Chadchai Srisurangkul, Itsuo Kumazawa

Abstract:

Public transportation is a crucial aspect of passenger transportation, with buses playing a vital role in the transportation service. Passenger counting is an essential tool for organizing and managing transportation services. However, manual counting is a tedious and time-consuming task, which is why computer vision algorithms are being utilized to make the process more efficient. In this study, different object detection algorithms combined with passenger tracking are investigated to compare passenger counting performance. The system employs the EfficientDet algorithm, which has demonstrated superior performance in terms of speed and accuracy. Our results show that the proposed system can accurately count passengers in varying conditions with an accuracy of 94%.

Keywords: computer vision, object detection, passenger counting, public transportation

Procedia PDF Downloads 145
6409 How Geant4 Hadronic Models Handle Tracking of Pion Particles Resulting from Antiproton Annihilation

Authors: M. B. Tavakoli, R. Reiazi, M. M. Mohammadi, K. Jabbari

Abstract:

From 2003, AD4/ACE experiment in CERN tried to investigate different aspects of antiproton as a new modality in particle therapy. Because of lack of reliable absolute dose measurements attempts to find out the radiobiological characteristics of antiproton have not reached to a reasonable result yet. From the other side, application of Geant4 in medical approaches is increased followed by Geant4-DNA project which focuses on using this code to predict radiation effects in the cellular scale. This way we can exploit Geant4-DNA results for antiproton. Unfortunately, previous studies showed there are serious problem in simulating an antiproton beam using Geant4. Since most of the problem was in the Bragg peak region which antiproton annihilates there, in this work we tried to understand if the problem came from the way in which Geant4 handles annihilation products especially pion particles. This way, we can predict the source of the dose discrepancies between Geant4 simulations and dose measurements done in CERN.

Keywords: Geant4, antiproton, annihilation, pion plus, pion minus

Procedia PDF Downloads 654
6408 Insights into the Perception of Sustainable Technology Adoption among Malaysian Small and Medium-Sized Enterprises

Authors: Majharul Talukder, Ali Quazi

Abstract:

The use of sustainable technology is being increasingly driven by the demand for saving resources, long-term cost savings, and protecting the environment. A transitional economy such as Malaysia is an example where traditional technologies are being replaced by sustainable ones. The antecedents that are driving Malaysian SMEs to integrate sustainable technology into their business operations have not been well researched. This paper addresses this gap in our knowledge through an examination of attitudes and ethics as antecedents of acceptance of sustainable technology among Malaysian SMEs. The database comprised 322 responses that were analysed using the PLS-SEM path algorithm. Results indicated that effective and altruism attitudes have high predictive ability for the usage of sustainable technology in Malaysian SMEs. This paper identifies the implications of the findings, along with the major limitations of the research and explores future areas of research in this field.

Keywords: sustainable technology, innovation management, Malaysian SMEs, organizational attitudes and ethical belief

Procedia PDF Downloads 328
6407 Texture-Based Image Forensics from Video Frame

Authors: Li Zhou, Yanmei Fang

Abstract:

With current technology, images and videos can be obtained more easily than ever. It is so easy to manipulate these digital multimedia information when obtained, and that the content or source of the image and video could be easily tampered. In this paper, we propose to identify the image and video frame by the texture-based approach, e.g. Markov Transition Probability (MTP), which is in space domain, DCT domain and DWT domain, respectively. In the experiment, image and video frame database is constructed, and is used to train and test the classifier Support Vector Machine (SVM). Experiment results show that the texture-based approach has good performance. In order to verify the experiment result, and testify the universality and robustness of algorithm, we build a random testing dataset, the random testing result is in keeping with above experiment.

Keywords: multimedia forensics, video frame, LBP, MTP, SVM

Procedia PDF Downloads 423
6406 A Molding Surface Auto-inspection System

Authors: Ssu-Han Chen, Der-Baau Perng

Abstract:

Molding process in IC manufacturing secures chips against the harms done by hot, moisture or other external forces. While a chip was being molded, defects like cracks, dilapidation, or voids may be embedding on the molding surface. The molding surfaces the study poises to treat and the ones on the market, though, differ in the surface where texture similar to defects is everywhere. Manual inspection usually passes over low-contrast cracks or voids; hence an automatic optical inspection system for molding surface is necessary. The proposed system is consisted of a CCD, a coaxial light, a back light as well as a motion control unit. Based on the property of statistical textures of the molding surface, a series of digital image processing and classification procedure is carried out. After training of the parameter associated with above algorithm, result of the experiment suggests that the accuracy rate is up to 93.75%, contributing to the inspection quality of IC molding surface.

Keywords: molding surface, machine vision, statistical texture, discrete Fourier transformation

Procedia PDF Downloads 427
6405 Data-Driven Market Segmentation in Hospitality Using Unsupervised Machine Learning

Authors: Rik van Leeuwen, Ger Koole

Abstract:

Within hospitality, marketing departments use segmentation to create tailored strategies to ensure personalized marketing. This study provides a data-driven approach by segmenting guest profiles via hierarchical clustering based on an extensive set of features. The industry requires understandable outcomes that contribute to adaptability for marketing departments to make data-driven decisions and ultimately driving profit. A marketing department specified a business question that guides the unsupervised machine learning algorithm. Features of guests change over time; therefore, there is a probability that guests transition from one segment to another. The purpose of the study is to provide steps in the process from raw data to actionable insights, which serve as a guideline for how hospitality companies can adopt an algorithmic approach.

Keywords: hierarchical cluster analysis, hospitality, market segmentation

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6404 Perceived Family Functioning 12 Months after the COVID-19 Outbreak Has Been Declared a Global Pandemic

Authors: Snezana Svetozarevic

Abstract:

The aim of the research was to determine whether there were significant changes in perceptions of family functioning by families in Serbia 12 months after the coronavirus (COVID-19) outbreak has been declared a global pandemic. Above all, what has protected families in the face of the global crisis caused by COVID-19. The Self-Report Family Inventory, II version (SFI-II; Beavers and Hampson, 2013) and the Inventory of Family Protective Factors (IFPF; Gardner et al., 2008) were used to assess family functioning and protective factors. Currently, families perceive their functioning as more problematic regarding family emotional expressiveness, conflict, cohesion, and global family health/competence. Adaptive appraisal based on positive coping experiences significantly predicted values on emotional expressiveness, conflict, leadership, and global family health/competence dimensions -a higher prevalence of this factor was associated with more optimal family functioning and fewer problems. The growing problem in family functioning with the beginning of the pandemic is inevitable. However, our research confirmed that it is not enough to take into account what families do to survive. It is equally important to learn about what they do to thrive i.e., to study the family resilience.

Keywords: family, coping, resilience, pandemic, COVID-19

Procedia PDF Downloads 94
6403 An Observation Approach of Reading Order for Single Column and Two Column Layout Template

Authors: In-Tsang Lin, Chiching Wei

Abstract:

Reading order is an important task in many digitization scenarios involving the preservation of the logical structure of a document. From the paper survey, it finds that the state-of-the-art algorithm could not fulfill to get the accurate reading order in the portable document format (PDF) files with rich formats, diverse layout arrangement. In recent years, most of the studies on the analysis of reading order have targeted the specific problem of associating layout components with logical labels, while less attention has been paid to the problem of extracting relationships the problem of detecting the reading order relationship between logical components, such as cross-references. Over 3 years of development, the company Foxit has demonstrated the layout recognition (LR) engine in revision 20601 to eager for the accuracy of the reading order. The bounding box of each paragraph can be obtained correctly by the Foxit LR engine, but the result of reading-order is not always correct for single-column, and two-column layout format due to the table issue, formula issue, and multiple mini separated bounding box and footer issue. Thus, the algorithm is developed to improve the accuracy of the reading order based on the Foxit LR structure. In this paper, a creative observation method (Here called the MESH method) is provided here to open a new chance in the research of the reading-order field. Here two important parameters are introduced, one parameter is the number of the bounding box on the right side of the present bounding box (NRight), and another parameter is the number of the bounding box under the present bounding box (Nunder). And the normalized x-value (x/the whole width), the normalized y-value (y/the whole height) of each bounding box, the x-, and y- position of each bounding box were also put into consideration. Initial experimental results of single column layout format demonstrate a 19.33% absolute improvement in accuracy of the reading-order over 7 PDF files (total 150 pages) using our proposed method based on the LR structure over the baseline method using the LR structure in 20601 revision, which its accuracy of the reading-order is 72%. And for two-column layout format, the preliminary results demonstrate a 44.44% absolute improvement in accuracy of the reading-order over 2 PDF files (total 18 pages) using our proposed method based on the LR structure over the baseline method using the LR structure in 20601 revision, which its accuracy of the reading-order is 0%. Until now, the footer issue and a part of multiple mini separated bounding box issue can be solved by using the MESH method. However, there are still three issues that cannot be solved, such as the table issue, formula issue, and the random multiple mini separated bounding boxes. But the detection of the table position and the recognition of the table structure are out of the scope in this paper, and there is needed another research. In the future, the tasks are chosen- how to detect the table position in the page and to extract the content of the table.

Keywords: document processing, reading order, observation method, layout recognition

Procedia PDF Downloads 175
6402 Data Mining As A Tool For Knowledge Management: A Review

Authors: Maram Saleh

Abstract:

Knowledge has become an essential resource in today’s economy and become the most important asset of maintaining competition advantage in organizations. The importance of knowledge has made organizations to manage their knowledge assets and resources through all multiple knowledge management stages such as: Knowledge Creation, knowledge storage, knowledge sharing and knowledge use. Researches on data mining are continues growing over recent years on both business and educational fields. Data mining is one of the most important steps of the knowledge discovery in databases process aiming to extract implicit, unknown but useful knowledge and it is considered as significant subfield in knowledge management. Data miming have the great potential to help organizations to focus on extracting the most important information on their data warehouses. Data mining tools and techniques can predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. This review paper explores the applications of data mining techniques in supporting knowledge management process as an effective knowledge discovery technique. In this paper, we identify the relationship between data mining and knowledge management, and then focus on introducing some application of date mining techniques in knowledge management for some real life domains.

Keywords: Data Mining, Knowledge management, Knowledge discovery, Knowledge creation.

Procedia PDF Downloads 203
6401 The Effect of the Rain Intensity on the Hydrodynamic Behavior of the Low-Floor ChéLiffe

Authors: Ahmed Abbas

Abstract:

Land degradation in the Lower Cheliff region leads to loss of their fertility, physical and chemical properties by secondary salinization and film forming surface or surface crust. The main factor related to runoff and soil erosion is their susceptibility to crusting caused by the impact of raindrops, which causes the reduction of the filterability of the soil. The present study aims to investigate the hydrodynamic behavior of five types of soil taken from the plain of low Cheliff under simulated rainfall by using two intensities, one moderate, and others correspond to heavy rains at low kinetic energies. Experimental results demonstrate the influence of chemical and mechanical physical properties of soils on their hydrodynamic behavior and the influence of heavy rain on the modality of the reduction in the filterability and the amount of transported sediment.

Keywords: erosion, hydrodynamic behavior, rain simulation, soil

Procedia PDF Downloads 282
6400 Landslide Susceptibility Analysis in the St. Lawrence Lowlands Using High Resolution Data and Failure Plane Analysis

Authors: Kevin Potoczny, Katsuichiro Goda

Abstract:

The St. Lawrence lowlands extend from Ottawa to Quebec City and are known for large deposits of sensitive Leda clay. Leda clay deposits are responsible for many large landslides, such as the 1993 Lemieux and 2010 St. Jude (4 fatalities) landslides. Due to the large extent and sensitivity of Leda clay, regional hazard analysis for landslides is an important tool in risk management. A 2018 regional study by Farzam et al. on the susceptibility of Leda clay slopes to landslide hazard uses 1 arc second topographical data. A qualitative method known as Hazus is used to estimate susceptibility by checking for various criteria in a location and determine a susceptibility rating on a scale of 0 (no susceptibility) to 10 (very high susceptibility). These criteria are slope angle, geological group, soil wetness, and distance from waterbodies. Given the flat nature of St. Lawrence lowlands, the current assessment fails to capture local slopes, such as the St. Jude site. Additionally, the data did not allow one to analyze failure planes accurately. This study majorly improves the analysis performed by Farzam et al. in two aspects. First, regional assessment with high resolution data allows for identification of local locations that may have been previously identified as low susceptibility. This then provides the opportunity to conduct a more refined analysis on the failure plane of the slope. Slopes derived from 1 arc second data are relatively gentle (0-10 degrees) across the region; however, the 1- and 2-meter resolution 2022 HRDEM provided by NRCAN shows that short, steep slopes are present. At a regional level, 1 arc second data can underestimate the susceptibility of short, steep slopes, which can be dangerous as Leda clay landslides behave retrogressively and travel upwards into flatter terrain. At the location of the St. Jude landslide, slope differences are significant. 1 arc second data shows a maximum slope of 12.80 degrees and a mean slope of 4.72 degrees, while the HRDEM data shows a maximum slope of 56.67 degrees and a mean slope of 10.72 degrees. This equates to a difference of three susceptibility levels when the soil is dry and one susceptibility level when wet. The use of GIS software is used to create a regional susceptibility map across the St. Lawrence lowlands at 1- and 2-meter resolutions. Failure planes are necessary to differentiate between small and large landslides, which have so far been ignored in regional analysis. Leda clay failures can only retrogress as far as their failure planes, so the regional analysis must be able to transition smoothly into a more robust local analysis. It is expected that slopes within the region, once previously assessed at low susceptibility scores, contain local areas of high susceptibility. The goal is to create opportunities for local failure plane analysis to be undertaken, which has not been possible before. Due to the low resolution of previous regional analyses, any slope near a waterbody could be considered hazardous. However, high-resolution regional analysis would allow for more precise determination of hazard sites.

Keywords: hazus, high-resolution DEM, leda clay, regional analysis, susceptibility

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6399 First-Generation College Students and Persistence: A Phenomenological Study of Students’ Experiences in Indonesian Higher Education

Authors: Taufik Mulyadin

Abstract:

The tuition reform for public colleges that the Indonesian government initiated and has implemented since 2013 resulted in the growing number of college students from low-income families, many of whose parents did not attend college. This study sought to examine the experiences of persistence for Indonesian first-generation college students in public universities utilizing social capital as a framework. It is a qualitative study with a phenomenological approach primarily to capture the essence of how Indonesian first-generation college students interpret, process, and experience their persistence during college years. Fifteen Indonesian young college graduates were involved as well as questionnaire and interview were employed for data collection in this study. It revealed certain themes from the experiences that first-generation college students attributed to their persistence: (a) family encouragement, (b) support from friends, (c) guidance from faculty and staff, (d) fund of knowledge they bring with them, (e) financial aid availability, and (f) self-motivation. By examining first-generation college students’ voices, Indonesian public universities can better support, engage, and retain this group of students who were historically struggled to persist in college and complete their degree.

Keywords: first-generation student, Indonesian higher education, persistence, public universities

Procedia PDF Downloads 258
6398 Energy Saving Techniques for MIMO Decoders

Authors: Zhuofan Cheng, Qiongda Hu, Mohammed El-Hajjar, Basel Halak

Abstract:

Multiple-input multiple-output (MIMO) systems can allow significantly higher data rates compared to single-antenna-aided systems. They are expected to be a prominent part of the 5G communication standard. However, these decoders suffer from high power consumption. This work presents a design technique in order to improve the energy efficiency of MIMO systems; this facilitates their use in the next generation of battery-operated communication devices such as mobile phones and tablets. The proposed optimization approach consists of the use of low complexity lattice reduction algorithm in combination with an adaptive VLSI implementation. The proposed design has been realized and verified in 65nm technology. The results show that the proposed design is significantly more energy-efficient than conventional K-best MIMO systems.

Keywords: energy, lattice reduction, MIMO, VLSI

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6397 From Two-Way to Multi-Way: A Comparative Study for Map-Reduce Join Algorithms

Authors: Marwa Hussien Mohamed, Mohamed Helmy Khafagy

Abstract:

Map-Reduce is a programming model which is widely used to extract valuable information from enormous volumes of data. Map-reduce designed to support heterogeneous datasets. Apache Hadoop map-reduce used extensively to uncover hidden pattern like data mining, SQL, etc. The most important operation for data analysis is joining operation. But, map-reduce framework does not directly support join algorithm. This paper explains and compares two-way and multi-way map-reduce join algorithms for map reduce also we implement MR join Algorithms and show the performance of each phase in MR join algorithms. Our experimental results show that map side join and map merge join in two-way join algorithms has the longest time according to preprocessing step sorting data and reduce side cascade join has the longest time at Multi-Way join algorithms.

Keywords: Hadoop, MapReduce, multi-way join, two-way join, Ubuntu

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6396 Root Biomass Growth in Different Growth Stages of Wheat and Barley Cultivars

Authors: H. Akman, A. Topal

Abstract:

This work was conducted in greenhouse conditions in order to investigate root biomass growth of two bread wheat, two durum wheat and two barley cultivars that were grown in irrigated and dry lands, respectively. This work was planned with four replications at a Completely Randomized Block Design in 2011-2012 growing season. In the study, root biomass growth was evaluated at stages of stem elongation, complete of anthesis and full grain maturity. Results showed that there were significant differences between cultivars grown at dry and irrigated lands in all growth stages in terms of root biomass (P < 0.01). According to research results, all of growth stages, dry typed-bread and durum wheats generally had higher root biomass than irrigated typed-cultivars, furthermore that dry typed-barley cultivar, had higher root biomass at GS 31 and GS 69, however lower at GS 92 than Larende. In all cultivars, root biomass increased between GS 31 and GS 69 so that dry typed-cultivars had more root biomass increase than irrigated typed-cultivars. Root biomass of bread wheat increased between GS 69 and GS 92, however root biomass of barley and durum wheat decreased.

Keywords: bread and durum wheat, barley, root biomass, different growth stage

Procedia PDF Downloads 603
6395 A Review on Predictive Sound Recognition System

Authors: Ajay Kadam, Ramesh Kagalkar

Abstract:

The proposed research objective is to add to a framework for programmed recognition of sound. In this framework the real errand is to distinguish any information sound stream investigate it & anticipate the likelihood of diverse sounds show up in it. To create and industrially conveyed an adaptable sound web crawler a flexible sound search engine. The calculation is clamor and contortion safe, computationally productive, and hugely adaptable, equipped for rapidly recognizing a short portion of sound stream caught through a phone microphone in the presence of frontal area voices and other predominant commotion, and through voice codec pressure, out of a database of over accessible tracks. The algorithm utilizes a combinatorial hashed time-recurrence group of stars examination of the sound, yielding ordinary properties, for example, transparency, in which numerous tracks combined may each be distinguished.

Keywords: fingerprinting, pure tone, white noise, hash function

Procedia PDF Downloads 318
6394 A Laser Instrument Rapid-E+ for Real-Time Measurements of Airborne Bioaerosols Such as Bacteria, Fungi, and Pollen

Authors: Minghui Zhang, Sirine Fkaier, Sabri Fernana, Svetlana Kiseleva, Denis Kiselev

Abstract:

The real-time identification of bacteria and fungi is difficult because they emit much weaker signals than pollen. In 2020, Plair developed Rapid-E+, which extends abilities of Rapid-E to detect smaller bioaerosols such as bacteria and fungal spores with diameters down to 0.3 µm, while keeping the similar or even better capability for measurements of large bioaerosols like pollen. Rapid-E+ enables simultaneous measurements of (1) time-resolved, polarization and angle dependent Mie scattering patterns, (2) fluorescence spectra resolved in 16 channels, and (3) fluorescence lifetime of individual particles. Moreover, (4) it provides 2D Mie scattering images which give the full information on particle morphology. The parameters of every single bioaerosol aspired into the instrument are subsequently analysed by machine learning. Firstly, pure species of microbes, e.g., Bacillus subtilis (a species of bacteria), and Penicillium chrysogenum (a species of fungal spores), were aerosolized in a bioaerosol chamber for Rapid-E+ training. Afterwards, we tested microbes under different concentrations. We used several steps of data analysis to classify and identify microbes. All single particles were analysed by the parameters of light scattering and fluorescence in the following steps. (1) They were treated with a smart filter block to get rid of non-microbes. (2) By classification algorithm, we verified the filtered particles were microbes based on the calibration data. (3) The probability threshold (defined by the user) step provides the probability of being microbes ranging from 0 to 100%. We demonstrate how Rapid-E+ identified simultaneously microbes based on the results of Bacillus subtilis (bacteria) and Penicillium chrysogenum (fungal spores). By using machine learning, Rapid-E+ achieved identification precision of 99% against the background. The further classification suggests the precision of 87% and 89% for Bacillus subtilis and Penicillium chrysogenum, respectively. The developed algorithm was subsequently used to evaluate the performance of microbe classification and quantification in real-time. The bacteria and fungi were aerosolized again in the chamber with different concentrations. Rapid-E+ can classify different types of microbes and then quantify them in real-time. Rapid-E+ enables classifying different types of microbes and quantifying them in real-time. Rapid-E+ can identify pollen down to species with similar or even better performance than the previous version (Rapid-E). Therefore, Rapid-E+ is an all-in-one instrument which classifies and quantifies not only pollen, but also bacteria and fungi. Based on the machine learning platform, the user can further develop proprietary algorithms for specific microbes (e.g., virus aerosols) and other aerosols (e.g., combustion-related particles that contain polycyclic aromatic hydrocarbons).

Keywords: bioaerosols, laser-induced fluorescence, Mie-scattering, microorganisms

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6393 Trusting Smart Speakers: Analysing the Different Levels of Trust between Technologies

Authors: Alec Wells, Aminu Bello Usman, Justin McKeown

Abstract:

The growing usage of smart speakers raises many privacy and trust concerns compared to other technologies such as smart phones and computers. In this study, a proxy measure of trust is used to gauge users’ opinions on three different technologies based on an empirical study, and to understand which technology most people are most likely to trust. The collected data were analysed using the Kruskal-Wallis H test to determine the statistical differences between the users’ trust level of the three technologies: smart speaker, computer and smart phone. The findings of the study revealed that despite the wide acceptance, ease of use and reputation of smart speakers, people find it difficult to trust smart speakers with their sensitive information via the Direct Voice Input (DVI) and would prefer to use a keyboard or touchscreen offered by computers and smart phones. Findings from this study can inform future work on users’ trust in technology based on perceived ease of use, reputation, perceived credibility and risk of using technologies via DVI.

Keywords: direct voice input, risk, security, technology, trust

Procedia PDF Downloads 188
6392 Exploring Non-Governmental Organizations’ Performance Management: Bahrain Athletics Association as a Case Study

Authors: Nooralhuda Aljlas

Abstract:

In the ever-growing field of non-governmental organizations, the enhancement of performance management and measurement systems has been increasingly acknowledged by political, economic, social, legal, technological and environmental factors. Within Bahrain Athletics Association, such enhancement results from the key factors leading performance management including collaboration, feedback, human resource management, leadership and participative management. The exploratory, qualitative research conducted reviewed performance management theory. As reviewed, the key factors leading performance management were identified. Drawing on a non-governmental organization case study, the key factors leading Bahrain Athletics Association’s performance management were explored. By exploring the key factors leading Bahrain Athletics Association’s performance management, the research study proposed a theoretical framework of the key factors leading performance management in non-governmental organizations in general. The research study recommended further investigation of the role of the two key factors of command and control and leadership, combining military and civilian approaches to enhancing non-governmental organizations’ performance management.

Keywords: Bahrain athletics association, exploratory, key factor, performance management

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6391 Review of Ultrasound Image Processing Techniques for Speckle Noise Reduction

Authors: Kwazikwenkosi Sikhakhane, Suvendi Rimer, Mpho Gololo, Khmaies Oahada, Adnan Abu-Mahfouz

Abstract:

Medical ultrasound imaging is a crucial diagnostic technique due to its affordability and non-invasiveness compared to other imaging methods. However, the presence of speckle noise, which is a form of multiplicative noise, poses a significant obstacle to obtaining clear and accurate images in ultrasound imaging. Speckle noise reduces image quality by decreasing contrast, resolution, and signal-to-noise ratio (SNR). This makes it difficult for medical professionals to interpret ultrasound images accurately. To address this issue, various techniques have been developed to reduce speckle noise in ultrasound images, which improves image quality. This paper aims to review some of these techniques, highlighting the advantages and disadvantages of each algorithm and identifying the scenarios in which they work most effectively.

Keywords: image processing, noise, speckle, ultrasound

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6390 The Vision Baed Parallel Robot Control

Authors: Sun Lim, Kyun Jung

Abstract:

In this paper, we describe the control strategy of high speed parallel robot system with EtherCAT network. This work deals the parallel robot system with centralized control on the real-time operating system such as window TwinCAT3. Most control scheme and algorithm is implemented master platform on the PC, the input and output interface is ported on the slave side. The data is transferred by maximum 20usecond with 1000byte. EtherCAT is very high speed and stable industrial network. The control strategy with EtherCAT is very useful and robust on Ethernet network environment. The developed parallel robot is controlled pre-design nonlinear controller for 6G/0.43 cycle time of pick and place motion tracking. The experiment shows the good design and validation of the controller.

Keywords: parallel robot control, etherCAT, nonlinear control, parallel robot inverse kinematic

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6389 A Multi-Agent Urban Traffic Simulator for Generating Autonomous Driving Training Data

Authors: Florin Leon

Abstract:

This paper describes a simulator of traffic scenarios tailored to facilitate autonomous driving model training for urban environments. With the rising prominence of self-driving vehicles, the need for diverse datasets is very important. The proposed simulator provides a flexible framework that allows the generation of custom scenarios needed for the validation and enhancement of trajectory prediction algorithms. Its controlled yet dynamic environment addresses the challenges associated with real-world data acquisition and ensures adaptability to diverse driving scenarios. By providing an adaptable solution for scenario creation and algorithm testing, this tool proves to be a valuable resource for advancing autonomous driving technology that aims to ensure safe and efficient self-driving vehicles.

Keywords: autonomous driving, car simulator, machine learning, model training, urban simulation environment

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6388 A Web-Based Self-Learning Grammar for Spoken Language Understanding

Authors: S. Biondi, V. Catania, R. Di Natale, A. R. Intilisano, D. Panno

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One of the major goals of Spoken Dialog Systems (SDS) is to understand what the user utters. In the SDS domain, the Spoken Language Understanding (SLU) Module classifies user utterances by means of a pre-definite conceptual knowledge. The SLU module is able to recognize only the meaning previously included in its knowledge base. Due the vastity of that knowledge, the information storing is a very expensive process. Updating and managing the knowledge base are time-consuming and error-prone processes because of the rapidly growing number of entities like proper nouns and domain-specific nouns. This paper proposes a solution to the problem of Name Entity Recognition (NER) applied to a SDS domain. The proposed solution attempts to automatically recognize the meaning associated with an utterance by using the PANKOW (Pattern based Annotation through Knowledge On the Web) method at runtime. The method being proposed extracts information from the Web to increase the SLU knowledge module and reduces the development effort. In particular, the Google Search Engine is used to extract information from the Facebook social network.

Keywords: spoken dialog system, spoken language understanding, web semantic, name entity recognition

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6387 Effect of Viscosity in Void Structure with Interacting Variable Charge Dust Grains

Authors: Nebbat El Amine

Abstract:

The void is a dust free region inside the dust cloud in the plasma. It is found that the dust grain charge variation lead to the extension of the void. Moreover, for bigger dust grains, it is seen that the wave-like structure recedes when charge variation is dealt with. Furthermore, as the grain-grain distance is inversely proportional to density, the grain-grain interaction gets more important for a denser dust population and is to be included in momentum equation. For the result indicate above, the plasma is considered non viscous. But in fact, it’s not always true. Some authors measured experimentally the viscosity of this background and found that the viscosity of dusty plasma increase with background gas pressure. In this paper, we tack account the viscosity of the fluid, and we compare the result with that found in the recent work.

Keywords: voids, dusty plasmas, variable charge, viscosity

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6386 An Automated R-Peak Detection Method Using Common Vector Approach

Authors: Ali Kirkbas

Abstract:

R peaks in an electrocardiogram (ECG) are signs of cardiac activity in individuals that reveal valuable information about cardiac abnormalities, which can lead to mortalities in some cases. This paper examines the problem of detecting R-peaks in ECG signals, which is a two-class pattern classification problem in fact. To handle this problem with a reliable high accuracy, we propose to use the common vector approach which is a successful machine learning algorithm. The dataset used in the proposed method is obtained from MIT-BIH, which is publicly available. The results are compared with the other popular methods under the performance metrics. The obtained results show that the proposed method shows good performance than that of the other. methods compared in the meaning of diagnosis accuracy and simplicity which can be operated on wearable devices.

Keywords: ECG, R-peak classification, common vector approach, machine learning

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6385 Improvement of Low Delta-9 Tetrahydrocannabinol (THC) Hemp Cultivars for High Fiber Content

Authors: Sarita Pinmanee, Saipan Krapbia, Rataya Yanaphan

Abstract:

Hemp (Cannabis sativa L.) is multi-purpose crop delivering fibers, shives, and seed. The fiber is used today for special paper, insulation material, and biocomposites. This research was to improve low delta-9 Tetrahydrocannabinol (THC) hemp variety for high fiber contents. Mass selection for increased fiber content in four low THC Thai cultivars (including RPF1, RPF2, RPF3, and RPF4) was carried out in highland areas in the northern Thailand. Research work was conducted for three consecutive growing seasons during 2012 to 2014 at Pangda Royal Agricultural Station, Samoeng District, Chiang Mai Province, Thailand. Results of selection indicated that after selecting for three successive generations, the average fiber content of four low THC Thai cultivars increased to 28-36 %. The resulted of selection was found that fiber content of RPF1, RPF2, RPF3 and RPF4 increased to 20.6, 19.1, 19.9 and 22.8%, respectively. In addition, THC contents of these four varieties were 0.07, 0.138, 0.08 and 0.072 % respectively. As well, mass selection method was considered as an effective and suitable method for improving this fiber content.

Keywords: Hemp, mass selection, fiber content, low THC content

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6384 Casteism in United Punjab: A Socio-Cultural Perspective

Authors: Zahoor Ahmad

Abstract:

Casteism has played a pivotal role in the social setup and political manipulations in Punjab. This tradition dates back to pre-British history. A number of scholars produced valuable work attributing the caste prejudice and division among the local communities. As a matter of fact, the history of Punjab witnessed a tangible economic, Muslim-non-Muslim, hatred culture towards low-profile castes & professions, and so on. It is obvious that caste ridden system already existed in Punjab before the advent of the British, who tremendously supported the same, and this division evidently affected every aspect of the political as well as social life of the region. This article highlights the characteristics of different castes and the contemptuous behavior of the low castes & professions in the area further, how the caste system influenced the local people and their culture.

Keywords: casteism, caste prejudice, division, Punjab

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6383 Development of the Integrated Quality Management System of Cooked Sausage Products

Authors: Liubov Lutsyshyn, Yaroslava Zhukova

Abstract:

Over the past twenty years, there has been a drastic change in the mode of nutrition in many countries which has been reflected in the development of new products, production techniques, and has also led to the expansion of sales markets for food products. Studies have shown that solution of the food safety problems is almost impossible without the active and systematic activity of organizations directly involved in the production, storage and sale of food products, as well as without management of end-to-end traceability and exchange of information. The aim of this research is development of the integrated system of the quality management and safety assurance based on the principles of HACCP, traceability and system approach with creation of an algorithm for the identification and monitoring of parameters of technological process of manufacture of cooked sausage products. Methodology of implementation of the integrated system based on the principles of HACCP, traceability and system approach during the manufacturing of cooked sausage products for effective provision for the defined properties of the finished product has been developed. As a result of the research evaluation technique and criteria of performance of the implementation and operation of the system of the quality management and safety assurance based on the principles of HACCP have been developed and substantiated. In the paper regularities of influence of the application of HACCP principles, traceability and system approach on parameters of quality and safety of the finished product have been revealed. In the study regularities in identification of critical control points have been determined. The algorithm of functioning of the integrated system of the quality management and safety assurance has also been described and key requirements for the development of software allowing the prediction of properties of finished product, as well as the timely correction of the technological process and traceability of manufacturing flows have been defined. Based on the obtained results typical scheme of the integrated system of the quality management and safety assurance based on HACCP principles with the elements of end-to-end traceability and system approach for manufacture of cooked sausage products has been developed. As a result of the studies quantitative criteria for evaluation of performance of the system of the quality management and safety assurance have been developed. A set of guidance documents for the implementation and evaluation of the integrated system based on the HACCP principles in meat processing plants have also been developed. On the basis of the research the effectiveness of application of continuous monitoring of the manufacturing process during the control on the identified critical control points have been revealed. The optimal number of critical control points in relation to the manufacture of cooked sausage products has been substantiated. The main results of the research have been appraised during 2013-2014 under the conditions of seven enterprises of the meat processing industry and have been implemented at JSC «Kyiv meat processing plant».

Keywords: cooked sausage products, HACCP, quality management, safety assurance

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6382 Approaches and Strategies Used to Increase Student Engagement in Blended Learning Courses

Authors: Pinar Ozdemir Ayber, Zeina Hojeij

Abstract:

Blended Learning (BL) is a rapidly growing teaching and learning approach, which brings together the best of both face-to-face and online learning to expand learning opportunities for students. However, there is limited research on the practices, opportunities and quality of instruction in Blended Classrooms, and on the role of the teaching faculty as well as the learners in these types of classes. This paper will highlight the researchers’ experiences and reflections on blending their classes. It will focus on the importance of designing effective lesson plans that emphasize learner engagement and motivation in alignment with course learning outcomes. In addition, it will identify the changing roles of the teacher and the learners and suggest appropriate variations to the traditional classroom setting taking into consideration the benefits and the challenges of the Blended Classroom. It is hoped that this paper would provide sufficient input for participants to reflect on ways they can blend their own lessons to promote ubiquitous learning and student autonomy. Practical tips and ideas will be shared with the participants on various strategies and technologies that were used in the researchers’ classes.

Keywords: blended learning, learner autonomy, learner engagement, learner motivation, mobile learning tools

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