Search results for: locally identifying coloring

Authors: Ebert Brea

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We propose a novel direct search algorithm for identifying at least a local minimum of mixed integer nonlinear unconstrained optimization problems. The Mixed Integer Randomized Pattern Search Algorithm (MIRPSA), so-called by the author, is based on a randomized pattern search, which is modified by the MIRPSA for finding at least a local minimum of our problem. The MIRPSA has two main operations over the randomized pattern search: moving operation and shrinking operation. Each operation is carried out by the algorithm when a set of conditions is held. The convergence properties of the MIRPSA is analyzed using a Markov chain approach, which is represented by an infinite countable set of state space λ, where each state d(q) is defined by a measure of the qth randomized pattern search Hq, for all q in N. According to the algorithm, when a moving operation is carried out on the qth randomized pattern search Hq, the MIRPSA holds its state. Meanwhile, if the MIRPSA carries out a shrinking operation over the qth randomized pattern search Hq, the algorithm will visit the next state, this is, a shrinking operation at the qth state causes a changing of the qth state into (q+1)th state. It is worthwhile pointing out that the MIRPSA never goes back to any visited states because the MIRPSA only visits any qth by shrinking operations. In this article, we describe the MIRPSA for mixed integer nonlinear unconstrained optimization problems for doing a deep study of its convergence properties using Markov chain viewpoint. We herein include a low dimension case for showing more details of the MIRPSA, when the algorithm is used for identifying the minimum of a mixed integer quadratic function. Besides, numerical examples are also shown in order to measure the performance of the MIRPSA.

Keywords: direct search, mixed integer optimization, random search, convergence, Markov chain

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Authors: Rojan Dahal

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One Health refers to a collaborative effort between multiple disciplines - locally, nationally, and globally - to attain optimal health. Although there were unprecedented intersectoral alliances between the animal and human health sectors during the avian influenza outbreak, there are different views and perceptions concerning institutionalizing One Health in South Asia. It is likely a structural barrier between the relevant professionals working in different entities or ministries when it comes to collaborating on One Health actions regarding zoonotic diseases. Politicians and the public will likely need to invest large amounts of money, demonstrate political will, and understand how One Health works to overcome these barriers. One Health might be hard to invest in South Asian countries, where the benefits are based primarily on models and projections and where numerous issues related to development and health need urgent attention. The other potential barrier to enabling the One Health concept in responding to zoonotic diseases is a failure to represent One Health in zoonotic disease control and prevention measures in the national health policy, which is a critical component of institutionalizing the One Health concept. One Health cannot be institutionalized without acknowledging the linkages between animal, human, and environmental sectors in dealing with zoonotic diseases. Efforts have been made in the past to prepare a preparedness plan for One Health implementation, but little has been done to establish a policy environment to institutionalize One Health. It is often assumed that health policy refers specifically to medical care issues and health care services. When drafting, reviewing, and redrafting the policy, it is important to engage a wide range of stakeholders. One Health institutionalization may also be hindered by the interplay between One Health professionals and bureaucratic inertia in defining the priorities of diseases due to competing interests on limited budgets. There is a possibility that policymakers do not recognize the importance of veterinary professionals in preventing human diseases originating in animals. Compared to veterinary medicine, the human health sector has produced most of the investment and research outputs related to zoonotic diseases. The public health profession may consider itself superior to the veterinary profession. Zoonotic diseases might not be recognized as threats to human health, impeding integrated policies. The effort of One Health institutionalization remained only among the donor agencies and multi-sectoral organizations. There is a need for strong political will and state capacity to overcome the existing institutional, financial, and professional barriers for its effective implementation. There is a need to assess the structural challenges, policy challenges, and the attitude of the professional working in the multiple disciplines related to One Health. Limited research has been conducted to identify the reasons behind the barriers to institutionalizing the One Health concept in South Asia. Institutionalizing One Health in responding to zoonotic diseases breaks down silos and integrates animals, humans, and the environment.

Keywords: one health, institutionalization, South Asia, institutionalizations

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Authors: Bela Lebedeva

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Characteristics of the Web as a channel of information dissemination - accessibility and openness, interactivity and multimedia news - become wider and cover the audience quickly, positively affecting the perception of content, but blur out the understanding of the journalistic work. As a result audience and advertisers continue migrating to the Internet. Moreover, online targeting allows monetizing not only the audience (as customarily given to traditional media) but also the content and traffic more accurately. While the users identify themselves with the qualitative characteristics of the new market, its actors are formed. Conflict of interests is laid in the base of the economy of their relations, the problem of traffic tax as an example. Meanwhile, content monetization actualizes fiscal interest of the state too. The balance of supply and demand is often violated due to the political risks, particularly in terms of state capitalism, populism and authoritarian methods of governance such social institutions as the media. A unique example of access to journalistic material, limited by monetization of content is a television channel Dozhd' (Rain) in Russian web space. Its liberal-minded audience has a better possibility for discussion. However, the channel could have been much more successful in terms of unlimited free speech. Avoiding state pressure and censorship its management has decided to save at least online performance and monetizing all of the content for the core audience. The study Methodology was primarily based on the analysis of journalistic content, on the qualitative and quantitative analysis of the audience. Reconstructing main events and relationships of actors on the market for the last six years researcher has reached some conclusions. First, under the condition of content monetization the capitalization of its quality will always strive to quality characteristics of user, thereby identifying him. Vice versa, the user's demand generates high-quality journalism. The second conclusion follows the previous one. The growth of technology, information noise, new political challenges, the economy volatility and the cultural paradigm change – all these factors form the content paying model for an individual user. This model defines him as a beneficiary of specific knowledge and indicates the constant balance of supply and demand other conditions being equal. As a result, a new economic quality of information is created. This feature is an indicator of the market as a self-regulated system. Monetized information quality is less popular than that of the Public Broadcasting Service, but this audience is able to make decisions. These very users keep the niche sectors which have more potential of technology development, including the content monetization ways. The third point of the study allows develop it in the discourse of media space liberalization. This cultural phenomenon may open opportunities for the development of social and economic relations architecture both locally and regionally.

Keywords: content monetization, state capitalism, media liberalization, media economy, information quality

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Authors: Kyung Hwa Hong, Eunmi Koh

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Wool and cotton fabrics are pretreated by a tannic acid aqueous solution to increase their dyeability and then dyed by Purple-Fleshed Sweet Potato (PSP) extract. The dyed fabrics are then investigated by various analysis techniques. The results revealed that wool and cotton fabrics can be dyed bluish red through the pretreatment and dyeing process. Both wool and cotton fabrics only pretreated with tannic acid display decreased L* value but no significant changes in a* and b* values as the concentration of tannic acid increases. And, as expected, the pretreated fabrics are even darker and show a richer purple color after the dyeing process with the PSP extract. With regard to the colorfastness of wool and cotton fabrics dyed by PSP extract in cleaning circumstances, such as dry-cleaning (for wool) and washing (for cotton), the wool and cotton fabrics had a 4.0 and 4.0 grade of colorfastness to dry-cleaning and washing, respectively. However, they both exhibited significantly inferior colorfastness to light (grade of 1.5). Thus, it was found that there is still a need for improvement with regard to color fastness, particularly against light. On the other hand, the wool and cotton fabrics also showed antibacterial and antioxidant characteristics. In addition, both the wool and cotton fabrics showed potential antibacterial ability (>99%) against Staphylococcus aureus; however, they showed somewhat insufficient antibacterial ability (60.8% for wool and 94.8% for cotton) against Klebsiella pneumoniae. Also, their antioxidant abilities increased up to ca. 90% with an increase in the tannic acid concentration (up to 0.5%). However, after the dyeing process, the antibacterial and antioxidant ability tended to decrease. This is assumed to have occurred because functional moieties such as phenolic acids were detached from the pretreated fabrics into the hot water (the dyeing solution) during the dyeing process. Therefore, further study would be necessary to derive the optimum treatment and dyeing conditions so as to maximize the coloring effect and functionalities of the fabrics.

Keywords: antibacterial activity, antioxidant activity, purple-fleshed sweet potato, fabrics

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Authors: Aigerim Uyzbayeva, Valeriya Tyo, Nurlan Ibrayev

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Kazakhstan is currently one of the dynamically developing states in its region. The stable growth in all sectors of the economy leads to a corresponding increase in energy consumption. Thus, country consumes a significant amount of energy due to the high level of industralisation and the presence of energy-intensive manufacturing such as mining and metallurgy which in turn leads to low energy efficiency. With allowance for this the Government has set several priorities to adopt a transition of Republic of Kazakhstan to a “green economy”. This article provides an overview of Kazakhstan’s energy efficiency situation in for the period of 1991-2014. First, the dynamics of production and consumption of conventional energy resources are given. Second, the potential of renewable energy sources is summarised, followed by the description of GHG emissions trends in the country. Third, Kazakhstan’ national initiatives, policies and locally implemented projects in the field of energy efficiency are described.

Keywords: energy efficiency in Kazakhstan, greenhouse gases, renewable energy, sustainable development

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Authors: Terence Maisah Seka

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This paper examines democratic governance within the private and public sectors in economies in transition (Cameroon) by exploring how they influence development in terms of resource allocation to priorities that are locally conceptualized. The benefit of this is an improvement in indigenous and the quality of life for the local population. Using an ethnographic approach, this paper suggests that institutional corruption and state bureaucracy has limited the impact of democratic governance in influencing development. This has seen funds for developments being embezzled; local projects are not being done to satisfaction among others. The paper contributes by proposing measures to eliminate corruption to improve democratic governance, which will improve resource allocation and utilization.

Keywords: democratic governance, resource allocation, utilisation, Cameroon

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Authors: Sarah Smail

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Algeria has been subject to countless conquests and invasions that resulted in having a diverse linguistic repertoire. The sociolinguistic situation of the country made linguistic landscape analysis pertinent. This in fact, has led to the growth of diverse linguistic landscape studies that mainly focused on identifying the sociolinguistic situation of the country through shop names analysis. The present research adds to the existing literature by offering another perspective to the analysis of signs by combining the physical and digital semiotic landscape. The powerful oil, gas and agri-food industries in Algeria make it interesting to focus on the commodification of natural resources for the sake of identifying the language and semiotic resources deployed in the Algerian public scene in addition to the identification of the visibility of linguistic inequalities and minorities in the business domain. The study discusses the semiotic landscape of three trade cities: Bejaia, Setif and Hassi-Messaoud. In addition to interviews conducted with business owners and graphic designers and questionnaires with business employees. Withal, the study relies on Gorter’s multilingual inequalities in public space (MIPS) model (2021) and Irvine and Gal’s language ideology and linguistic differentiation (2000). The preliminary results demonstrate the sociolinguistic injustice existing in the business domain, e.g., the exclusion of the official languages, the dominance of foreign languages, and the excessive use of the roman script.

Keywords: semiotic landscaping, digital scapes, language commodification, linguistic inequalities, business signage

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Authors: Dongxu Chen, Yipeng Li

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This paper presents an information geometry NonlocalMeans(NLM) algorithm for Poisson denoising. NLM estimates a noise-free pixel as a weighted average of image pixels, where each pixel is weighted according to the similarity between image patches in Euclidean space. In this work, every pixel is a Poisson distribution locally estimated by Maximum Likelihood (ML), all distributions consist of a statistical manifold. A NLM denoising algorithm is conducted on the statistical manifold where Fisher information matrix can be used for computing distribution geodesics referenced as the similarity between patches. This approach was demonstrated to be competitive with related state-of-the-art methods.

Keywords: image denoising, Poisson noise, information geometry, nonlocal-means

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Authors: Elimhan N. Mahmudov

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The paper concerns the necessary and sufficient conditions of optimality for Cauchy problem of fourth order discrete (PD) and discrete-approximate (PDA) inclusions. The main problem is formulation of the fourth order adjoint discrete and discrete-approximate inclusions and transversality conditions, which are peculiar to problems including fourth order derivatives and approximate derivatives. Thus the necessary and sufficient conditions of optimality are obtained incorporating the Euler-Lagrange and Hamiltonian forms of inclusions. Derivation of optimality conditions are based on the apparatus of locally adjoint mapping (LAM). Moreover in the application of these results we consider the fourth order linear discrete and discrete-approximate inclusions.

Keywords: difference, optimization, fourth, approximation, transversality

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Authors: Tannia Vindel, Angel Matute, Erik Elvir, Kelvin Santos

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Currently in Honduras, is been incentivized the generation of energy using renewable fonts, such as: hydroelectricity, wind power, biomass and, more recently with the strongest growth, photovoltaic energy. In July 2015 were installed 455.2 MW of photovoltaic energy, increasing by 24% the installed capacity of the national interconnected system existing in 2014, according the National Energy Company (NEC), that made possible reduce the thermoelectric dependency of the system. Given the good results of those large-scale photovoltaic plants, arises the question: is it interesting for the distribution utility and for the consumers the integration of photovoltaic systems in micro-scale in the urban and rural areas? To answer that question has been researched the insertion of photovoltaic energy in the residential sector in Tegucigalpa and Comayagüela (Central District), Honduras to determine the technical and economic viability. Francisco Morazán department, according the National Statistics Institute (NSI), in 2001 had more than 180,000 houses with power service. Tegucigalpa, department and Honduras capital, and Comayagüela, both, have the highest population density in the region, with 1,300,000 habitants in 2014 (NSI). The residential sector in the south-central region of Honduras represents a high percentage being 49% of total consumption, according with NEC in 2014; where 90% of this sector consumes in a range of 0 to 300 kWh / month. All this, in addition to the high level of losses in the transmission and distribution systems, 31.3% in 2014, and the availability of an annual average solar radiation of 5.20 kWh/(m2∙day) according to the NASA, suggests the feasibility of the implementation of photovoltaic systems as a solution to give a level of independency to the households, and besides could be capable of injecting the non-used energy to the grid. The capability of exchange of energy with the grid could make the photovoltaic systems acquisition more affordable to the consumers, because of the compensation energy programs or other kinds of incentives that could be created. Technical viability of the photovoltaic systems insertion has been analyzed, considering the solar radiation monthly average to determine the monthly average of energy that would be generated with the technology accessible locally and the effects of the injection of the energy locally generated on the grid. In addition, the economic viability has been analyzed too, considering the photovoltaic systems high costs, costs of the utility, location and monthly energy consumption requirements of the families. It was found that the inclusion of photovoltaic systems in Tegucigalpa and Comayagüela could decrease in 6 MW the demand for the region if 100% of the households use photovoltaic systems, which acquisition may be more accessible with the help of government incentives and/or the application of energy exchange programs.

Keywords: grid connected, photovoltaic, residential, technical analysis

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Authors: Sylvia Tumelo Nthutang, Nehemiah Mavetera

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Educational institutions are under pressure from their competitors. Regulators and community groups need educational institutions to adopt appropriate business and organizational practices. Globally, educational institutions are now using e-learning as the best teaching and learning approach. E-learning is becoming the center of attention to the learning institutions, educational systems and software inventors. North-West University (NWU) is currently using eFundi, a Learning Management System (LMS). LMS are all information systems and procedures that adds value to students learning and support the learning material in text or any multimedia files. With various e-learning tools, students would be able to access all the materials related to the course in electronic copies. The study was tasked with identifying the e-learning components at the NWU, Mafikeng campus. Quantitative research methodology was considered in data collection and descriptive statistics for data analysis. The Activity Theory (AT) was used as a theory to guide the study. AT outlines the limitations amongst e-learning at the macro-organizational level (plan, guiding principle, campus-wide solutions) and micro-organization (daily functioning practice, collaborative transformation, specific adaptation). On a technological environment, AT gives people an opportunity to change from concentrating on computers as an area of concern but also understand that technology is part of human activities. The findings have identified the university’s current IT tools and knowledge on e-learning elements. It was recommended that university should consider buying computer resources that consumes less power and practice e-learning effectively.

Keywords: e-learning, information and communication technology (ICT), teaching, virtual learning environment

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Authors: G. Sandhya Devi, G. Suvarna Kumar, S. Chandini

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This research work aims to develop a system that will analyze and identify students who indulge in malpractices/suspicious activities during the course of an academic offline examination. Automated Video Surveillance provides an optimal solution which helps in monitoring the students and identifying the malpractice event immediately. This work is organized into three modules. The first module deals with performing an impersonation check using a PCA-based face recognition method which is done by cross checking his profile with the database. The presence or absence of the student is even determined in this module by implementing an image registration technique wherein a grid is formed by considering all the images registered using the frontal camera at the determined positions. Second, detecting such facial malpractices in which a student gets involved in conversation with another, trying to obtain unauthorized information etc., based on the threshold range evaluated by considering his/her mouth state whether open or closed. The third module deals with identification of unauthorized material or gadgets used in the examination hall by training the positive samples of the object through various stages. Here, a top view camera feed is analyzed to detect the suspicious activities. The system automatically alerts the administration when any suspicious activities are identified, thereby reducing the error rate caused due to manual monitoring. This work is an improvement over our previous work published in identifying suspicious activities done by examinees in an offline examination.

Keywords: impersonation, image registration, incrimination, object detection, threshold evaluation

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Authors: Kothuri Sriraman, Mattupalli Komal Teja

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In this paper, a novel algorithm is proposed for the recognition of hulls in a hand written images that might be irregular or digit or character shape. Identification of objects and internal objects is quite difficult to extract, when the structure of the image is having bulk of clusters. The estimation results are easily obtained while going through identifying the sub-regional objects by using the SASK algorithm. Focusing mainly to recognize the number of internal objects exist in a given image, so as it is shadow-free and error-free. The hard clustering and density clustering process of obtained image rough set is used to recognize the differentiated internal objects, if any. In order to find out the internal hull regions it involves three steps pre-processing, Boundary Extraction and finally, apply the Hull Detection system. By detecting the sub-regional hulls it can increase the machine learning capability in detection of characters and it can also be extend in order to get the hull recognition even in irregular shape objects like wise black holes in the space exploration with their intensities. Layered hulls are those having the structured layers inside while it is useful in the Military Services and Traffic to identify the number of vehicles or persons. This proposed SASK algorithm is helpful in making of that kind of identifying the regions and can useful in undergo for the decision process (to clear the traffic, to identify the number of persons in the opponent’s in the war).

Keywords: chain code, Hull regions, Hough transform, Hull recognition, Layered Outline Extraction, SASK algorithm

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Authors: Virender Singh, Mathew Rees, Simon Hampton, Sivaram Annadurai

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Plant identification is a challenging task that aims to identify the family, genus, and species according to plant morphological features. Automated deep learning-based computer vision algorithms are widely used for identifying plants and can help users narrow down the possibilities. However, numerous morphological similarities between and within species render correct classification difficult. In this paper, we tested custom convolution neural network (CNN) and vision transformer (ViT) based models using the PyTorch framework to classify plants. We used a large dataset of 88,000 provided by the Royal Horticultural Society (RHS) and a smaller dataset of 16,000 images from the PlantClef 2015 dataset for classifying plants at genus and species levels, respectively. Our results show that for classifying plants at the genus level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420 and other state-of-the-art CNN-based models suggested in previous studies on a similar dataset. ViT model achieved top accuracy of 83.3% for classifying plants at the genus level. For classifying plants at the species level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420, with a top accuracy of 92.5%. We show that the correct set of augmentation techniques plays an important role in classification success. In conclusion, these results could help end users, professionals and the general public alike in identifying plants quicker and with improved accuracy.

Keywords: plant identification, CNN, image processing, vision transformer, classification

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Authors: Ibrahim A. Al-Sulaihi, Khalid S. Al-Gahtani, Abdullah M. Al-Sugair, Aref A. Abadel

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Achieving environmental sustainability is one of the important issues considered in many countries’ vision. Green/Sustainable building is widely used terminology for describing a friendly environmental construction. Applying sustainable practices has a significant importance in various fields, including construction field that consumes an enormous amount of resource and causes a considerable amount of waste. The need for sustainability is increased in the regions that suffering from the limitation of natural resource and extreme weather conditions such as Saudi Arabia. Since buildings designs are getting sophisticated, the need for tools, which support decision-making for sustainability issues, is increasing, especially in the design and preconstruction stages. In this context, Building Information Modeling (BIM) can aid in performing complex building performance analyses to ensure an optimized sustainable building design. Accordingly, this paper introduces a roadmap towards developing a systematic approach for presenting the sustainability of buildings using BIM. The approach includes set of main processes including; identifying the sustainability parameters that can be used for sustainability assessment in Saudi Arabia, developing sustainability assessment method that fits the special circumstances in the Kingdom, identifying the sustainability requirements and BIM functions that can be used for satisfying these requirements, and integrating these requirements with identified functions. As a result, the sustainability-BIM approach can be developed which helps designers in assessing the sustainability and exploring different design alternatives at the early stage of the construction project.

Keywords: green buildings, sustainability, BIM, rating systems, environment, Saudi Arabia

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Authors: Bekir Dogan

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The genus Jurinea is one of the larger genera within Asteraceae, comprising about 200 species. Jurinea is naturally distributed in central Asia, Turkey, Iran and the Mediterranean region. Jurinea has 23 species within the Mediterranean and Irano-Turanian phytogeographic regions of Turkey. Jurinea brevicaulis is locally endemic in Turkey. It grows Erzincan province in Turkey. Between 2005 and 2007, as a part of a revisional study of Jurinea in Turkey, the author carried out extensive field studies and herbaria and collected an enough number of specimens. In the field, the specimens' GPS coordinates, habitat and relevant field observations were recorded. International Union for Conservation of Nature (IUCN) threat category was given. The present study reviews the chorology of the Jurinea brevicaulis in Turkey based on recent taxonomic revision and available specimen data.

Keywords: Asteraceae, endemic, Jurinea, Turkey

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Authors: Tasneem Halawani, Yamen Khateeb

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With customers’ ever-increasing expectations for fast services provisioning for all their business needs, information technology (IT) organizations, as business partners, have to cope with this demanding environment and deliver their services in the most effective and efficient way. The purpose of this paper is to identify optimization and automation opportunities for the top requested IT services in a heterogenic digital environment and widely spread customer base. In collaboration with systems, processes, and subject matter experts (SMEs), the processes in scope were approached by analyzing four-year related historical data, identifying and surveying stakeholders, modeling the as-is processes, and studying systems integration/automation capabilities. This effort resulted in identifying several pain areas, including standardization, unnecessary customer and IT involvement, manual steps, systems integration, and performance measurement. These pain areas were addressed by standardizing the top five requested IT services, eliminating/automating 43 steps, and utilizing a single platform for end-to-end process execution. In conclusion, the optimization of IT service request processes in a heterogenic digital environment and widely spread customer base is challenging, yet achievable without compromising the service quality and customers’ added value. Further studies can focus on measuring the value of the eliminated/automated process steps to quantify the enhancement impact. Moreover, a similar approach can be utilized to optimize other IT service requests, with a focus on business criticality.

Keywords: automation, customer value, heterogenic, integration, IT services, optimization, processes

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Authors: Nagui A. Abdel-Khalek, Khaled A. Selim, Ahmed Hamdy

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Kaolin is naturally occurring ore predominantly containing kaolinite mineral in addition to some gangue minerals. Typical impurities present in kaolin ore are quartz, iron oxides, titanoferrous minerals, mica, feldspar, organic matter, etc. The main coloring impurity, particularly in the ultrafine size range, is titanoferrous minerals. Kaolin is used in many industrial applications such as sanitary ware, table ware, ceramic, paint, and paper industries, each of which should be of certain specifications. For most industrial applications, kaolin should be processed to obtain refined clay so as to match with standard specifications. For example, kaolin used in paper and paint industries need to be of high brightness and low yellowness. Egyptian kaolin is not subjected to any beneficiation process and the Egyptian companies apply selective mining followed by, in some localities, crushing and size reduction only. Such low quality kaolin can be used in refractory and pottery production but not in white ware and paper industries. This paper aims to study the amenability of beneficiation of an Egyptian kaolin ore of El-Teih locality, Sinai, to be suitable for different industrial applications. Attrition scrubbing and classification followed by magnetic separation are applied to remove the associated impurities. Attrition scrubbing and classification are used to separate the coarse silica and feldspars. Wet high intensity magnetic separation was applied to remove colored contaminants such as iron oxide and titanium oxide. Different variables affecting of magnetic separation process such as solid percent, magnetic field, matrix loading capacity, and retention time are studied. The results indicated that substantial decrease in iron oxide (from 1.69% to 0.61% ) and TiO2 (from 3.1% to 0.83%) contents as well as improving iso-brightness (from 63.76% to 75.21% and whiteness (from 79.85% to 86.72%) of the product can be achieved.

Keywords: Kaolin, titanoferrous minerals, beneficiation, magnetic separation, attrition scrubbing, classification

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Authors: Ying-Jung Hsieh, Angela S. Huang, Chu-Ming Chiu, Yu-Min Chou, Chin-Hui Yang

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Background and Objectives: Hepatitis A is primarily acquired by the fecal-oral route through person-to-person contact or ingestion of contaminated food or water. During 2010 to 2014, an average of 83 cases of locally-acquired disease was reported to Taiwan’s notifiable disease system. Taiwan Centers for Disease Control (TCDC) identified an outbreak of acute hepatitis A which began in June 2015. Of the 126 cases reported in 2015, 103 (82%) cases were reported during June–December and 95 cases (92%) of them were male. The average age of all male cases was 31 years (median, 29 years; range, 15–76 years). Among the 95 male cases, 49 (52%) were also infected with HIV, and all reported to have had sex with other men. To control this outbreak, TCDC launched a free hepatitis A vaccination program in January 2016 for close contacts of confirmed hepatitis A cases, including family members, sexual partners, and household contacts. Effect of the vaccination program was evaluated. Methods: All cases of hepatitis A reported to the National Notifiable Disease Surveillance System were included. A case of hepatitis A was defined as a locally-acquired disease in a person who had acute clinical symptoms include fever, malaise, loss of appetite, nausea or abdominal discomfort compatible with hepatitis, and tested positive for anti-HAV IgM during June 2015 to June 2016 in Taiwan. The rate of case accumulation was calculated using a simple regression model. Results: During January–June 2016, there were 466 cases of hepatitis A reported; of the 243 (52%) who were also infected with HIV, 232 (95%) had a history of having sex with men. Of the 346 cases that were followed up, 259 (75%) provided information on contacts but only 14 (5%) of them provided the name of their sexual partners. Among the 602 contacts reported, 349 (58%) were family members, 14 (2%) were sexual partners, and 239 (40%) were other household contacts. Among the 602 contacts eligible for free hepatitis A vaccination, 440 (73%) received the vaccine. There were 87 (25%) cases that refused to disclose their close contacts. The average case accumulation rate during January–June 2016 was 21.7 cases per month, which was 6.8 times compared to the average case accumulation rate during June–December 2015 of 3.2 cases per month. Conclusions: Despite vaccination program aimed to provide free hepatitis A vaccine to close contacts of hepatitis A patients, the outbreak continued and even gained momentum in transmission. Refusal by hepatitis A patients to provide names of their close contacts and rejection of contacts to take the hepatitis A vaccine may have contributed to the poor effect of the program. Targeted vaccination efforts of all MSM may be needed to control the outbreak among this population in the short term. In the long term, universal vaccination program is needed to prevent the infection of hepatitis A.

Keywords: hepatitis A, HIV, men who have sex with men, vaccination

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Authors: Jaejun Jong

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Fake news has recently become a serious international problem. Therefore, researchers and policymakers worldwide have sought to understand fake news and develop strategies to combat it. This study consists of two primary parts: (1) a literature review of how surveys were used to understand fake news and identify problems caused by fake news, and (2) a discussion of how surveys were used to fight back against fake news in educational settings. This second section specifically analyzes surveys used to evaluate a South Korean elementary school program designed to improve students’ metacognition and critical thinking. This section seeks to identify potential problems that may occur in the elementary school setting. The literature review shows that surveys can help people to understand fake news based on its traits rather than its definition due to the lack of agreement on the definition of fake news. The literature review also shows that people are not good at identifying fake news or evaluating their own ability to identify fake news; indeed, they are more likely to share information that aligns with their previous beliefs. In addition, the elementary school survey data shows that there may be substantial errors in the program evaluation process, likely caused by processing errors or the survey procedure, though the exact cause is not specified. Such a significant error in evaluating the effects of the educational program prevents teachers from making proper decisions and accurately evaluating the program. Therefore, identifying the source of such errors would improve the overall quality of education, which would benefit both teachers and students.

Keywords: critical thinking, elementary education, program evaluation, survey

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Authors: Mustafa Durmuş, Yesim Ozogul, Esra Balıkcı, Saadet Gokdoğan, Fatih Ozogul, Ali Rıza Köşker, İlknur Yuvka

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Food scientists and researchers have paid attention to develop new ways for improving the nutritional value of foods. The application of nanotechnology techniques to the food industry may allow the modification of food texture, taste, sensory attributes, coloring strength, processability, and stability during shelf life of products. In this research, the effects of nanoemulsions based on commercial oils for vacuum-packed sea bass fillets stored at 2±2°C were investigated in terms of the sensory, chemical (total volatile basic nitrogen (TVB-N), thiobarbituric acid (TBA), peroxide value (PV) and free fatty acids (FFA), pH, water holding capacity (WHC)) and microbiological qualities (total anaerobic bacteria and total lactic acid bacteria). Physical properties of emulsions (viscosity, the particle size of droplet, thermodynamic stability, refractive index, and surface tension) were determined. Nanoemulsion preparation method was based on high energy principle, with ultrasonic homojenizator. Sensory analyses of raw fish showed that the demerit points of the control group were found higher than those of treated groups. The sensory score (odour, taste and texture) of the cooked fillets decreased with storage time, especially in the control. Results obtained from chemical and microbiological analyses also showed that nanoemulsions significantly (p<0.05) decreased the values of biochemical parameters and growth of bacteria during storage period, thus improving quality of vacuum-packed sea bass.

Keywords: quality parameters, nanoemulsion, sea bass, shelf life, vacuum packing

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Authors: Regina R. Gunawan, Indwiani Astuti, H. Raden Danarto

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Cancer is the leading cause of death worldwide. Cancer is caused by mutations that alter the function of normal human genes and give rise to cancer genes. MicroRNA (miRNA) is a small non-coding RNA that regulates the gen through complementary bond towards mRNA target and cause mRNA degradation. miRNA works by either promoting or suppressing cell proliferation. miRNA level expression in cancer may offer another value of miRNA as a biomarker in cancer diagnostic. miRNA-21 is believed to have a role in carcinogenesis by enhancing proliferation, anti-apoptosis, cell cycle progression and invasion of tumor cells. Hsa-miR-21-5p marker has been identified in Prostate Cancer (PCa) and Benign Prostatic Hyperplasia (BPH) patient’s urine. This research planned to explore the diagnostic performance of miR-21 to differentiate PCa and BPH patients. In this study, urine samples were collected from 20 PCa patients and 20 BPH patients. miR-21 relative expression against the reference gene was analyzed and compared between the two. miRNA expression was analyzed using the comparative quantification method to find the fold change. miR-21 validity in identifying PCa patients was performed by quantifying the sensitivity and specificity with the contingency table. miR-21 relative expression against miR-16 in PCa patient and in BPH patient has 12,98 differences in fold change. From a contingency table of Cq expression of miR-21 in identifying PCa patients from BPH patient, Cq miR-21 has 100% sensitivity and 75% specificity. miR-21 relative expression can be used in discriminating PCa from BPH by using a urine sample. Furthermore, the expression of miR-21 has higher sensitivity compared to PSA (Prostate specific antigen), therefore miR-21 has a high potential to be analyzed and developed more.

Keywords: benign prostate hyperplasia, biomarker, miRNA-21, prostate cancer

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Authors: James Rigor Camacho, Wansu Lim

Abstract:

Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

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Authors: Fatima Akhmedova, Simon Liao

Abstract:

One of the most critical decision points in the design of a face recognition system is the choice of an appropriate face representation. Effective feature descriptors are expected to convey sufficient, invariant and non-redundant facial information. In this work, we propose a set of Hahn moments as a new approach for feature description. Hahn moments have been widely used in image analysis due to their invariance, non-redundancy and the ability to extract features either globally and locally. To assess the applicability of Hahn moments to Face Recognition we conduct two experiments on the Olivetti Research Laboratory (ORL) database and University of Notre-Dame (UND) X1 biometric collection. Fusion of the global features along with the features from local facial regions are used as an input for the conventional k-NN classifier. The method reaches an accuracy of 93% of correctly recognized subjects for the ORL database and 94% for the UND database.

Keywords: face recognition, Hahn moments, recognition-by-parts, time-lapse

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Authors: Areej Salaymeh, Loren Schwiebert, Stephen Remias, Jonathan Waddell

Abstract:

Extracting information from new data sources has emerged as a crucial task in many traffic planning processes, such as identifying traffic patterns, route planning, traffic forecasting, and locating infrastructure improvements. Given the advanced technologies used to collect Global Positioning System (GPS) data from dedicated GPS devices, GPS equipped phones, and navigation tools, intelligent data analysis methodologies are necessary to mine this raw data. In this research, an automatic detection framework is proposed to help identify and classify the locations of stopped GPS waypoints into two main categories: signalized intersections or highway congestion. The Delaunay triangulation is used to perform this assessment in the clustering phase. While most of the existing clustering algorithms need assumptions about the data distribution, the effectiveness of the Delaunay triangulation relies on triangulating geographical data points without such assumptions. Our proposed method starts by cleaning noise from the data and normalizing it. Next, the framework will identify stoppage points by calculating the traveled distance. The last step is to use clustering to form groups of waypoints for signalized traffic and highway congestion. Next, a binary classifier was applied to find distinguish highway congestion from signalized stop points. The binary classifier uses the length of the cluster to find congestion. The proposed framework shows high accuracy for identifying the stop positions and congestion points in around 99.2% of trials. We show that it is possible, using limited GPS data, to distinguish with high accuracy.

Keywords: Delaunay triangulation, clustering, intelligent transportation systems, GPS data

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Authors: Daniel Pinheiro Da Silva Junior, Aline Paes, Daniel De Oliveira, Christiano Lacerda Ghuerren, Marcio Duran

Abstract:

The Courts of Accounts are institutions responsible for overseeing and point out irregularities of Public Administration expenses. They have a high demand for processes to be analyzed, whose decisions must be grounded on severity laws. Despite the existing large amount of processes, there are several cases reporting similar subjects. Thus, previous decisions on already analyzed processes can be a precedent for current processes that refer to similar topics. Identifying similar topics is an open, yet essential task for identifying similarities between several processes. Since the actual amount of topics is considerably large, it is tedious and error-prone to identify topics using a pure manual approach. This paper presents a tool based on Machine Learning and Natural Language Processing to assists in building a labeled dataset. The tool relies on Topic Modelling with Latent Dirichlet Allocation to find the topics underlying a document followed by Jensen Shannon distance metric to generate a probability of similarity between documents pairs. Furthermore, in a case study with a corpus of decisions of the Rio de Janeiro State Court of Accounts, it was noted that data pre-processing plays an essential role in modeling relevant topics. Also, the combination of topic modeling and a calculated distance metric over document represented among generated topics has been proved useful in helping to construct a labeled base of similar and non-similar document pairs.

Keywords: courts of accounts, data labelling, document similarity, topic modeling

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Authors: Jannis Kountouras, Nikolaos Kapetanakis, Stergios A. Polyzos, Apostolis Papaeftymiou, Panagiotis Katsinelos, Ioannis Venizelos, Christina Nikolaidou, Christos Zavos, Iordanis Romiopoulos, Elena Tsiaousi, Evangelos Kazakos, Michael Doulberis

Abstract:

Background & Aims: Helicobacter pylori infection (Hp-I) has been recognized as a substantial risk agent involved in gastrointestinal (GI) tract oncogenesis by stimulating cancer stem cells (CSCs), oncogenes, immune surveillance processes, and triggering GI microbiota dysbiosis. We aimed to investigate the possible involvement of active Hp-I in the sequence: chronic inflammation–adenoma–colorectal cancer (CRC) development. Methods: Four pillars were investigated: (i) endoscopic and conventional histological examinations of patients with CRC, colorectal adenomas (CRA) versus controls to detect the presence of active Hp-I; (ii) immunohistochemical determination of the presence of Hp; expression of CD44, an indicator of CSCs and/or bone marrow-derived stem cells (BMDSCs); expressions of oncogene Ki67 and anti-apoptotic Bcl-2 protein; (iii) expression of CD45, indicator of immune surveillance locally (assessing mainly T and B lymphocytes locally); and (iv) correlation of the studied parameters with the presence or absence of Hp-I. Results: Among 50 patients with CRC, 25 with CRA, and 10 controls, a significantly higher presence of Hp-I in the CRA (68%) and CRC group (84%) were found compared with controls (30%). The presence of Hp-I with accompanying immunohistochemical expression of CD44 in biopsy specimens was revealed in a high proportion of patients with CRA associated with moderate/severe dysplasia (88%) and CRC patients with moderate/severe degree of malignancy (91%). Comparable results were also obtained for Ki67, Bcl-2, and CD45 immunohistochemical expressions. Concluding Remarks: Hp-I seems to be involved in the sequence: CRA – dysplasia – CRC, similarly to the upper GI tract oncogenesis, by several pathways such as the following: Beyond Hp-I associated insulin resistance, the major underlying mechanism responsible for the metabolic syndrome (MetS) that increase the risk of colorectal neoplasms, as implied by other Hp-I related MetS pathologies, such as non-alcoholic fatty liver disease and upper GI cancer, the disturbance of the normal GI microbiota (i.e., dysbiosis) and the formation of an irritative biofilm could contribute to a perpetual inflammatory upper GIT and colon mucosal damage, stimulating CSCs or recruiting BMDSCs and affecting oncogenes and immune surveillance processes. Further large-scale relative studies with a pathophysiological perspective are necessary to demonstrate in-depth this relationship.

Keywords: Helicobacter pylori, colorectal cancer, colorectal adenomas, gastrointestinal oncogenesis

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Authors: ChunYi Peng, Wei Hsuan CHeng, Shyh Kuang Ueng

Abstract:

This study focuses on the application of self-organizing maps (SOM) technology in analyzing credit card transaction data, aiming to enhance the accuracy and efficiency of fraud detection. Som, as an artificial neural network, is particularly suited for pattern recognition and data classification, making it highly effective for the complex and variable nature of credit card transaction data. By analyzing transaction characteristics with SOM, the research identifies abnormal transaction patterns that could indicate potentially fraudulent activities. Moreover, this study has developed a specialized visualization tool to intuitively present the relationships between SOM analysis outcomes and transaction data, aiding financial institution personnel in quickly identifying and responding to potential fraud, thereby reducing financial losses. Additionally, the research explores the integration of SOM technology with composite intelligent system technologies (including finite state machines, fuzzy logic, and decision trees) to further improve fraud detection accuracy. This multimodal approach provides a comprehensive perspective for identifying and understanding various types of fraud within credit card transactions. In summary, by integrating SOM technology with visualization tools and composite intelligent system technologies, this research offers a more effective method of fraud detection for the financial industry, not only enhancing detection accuracy but also deepening the overall understanding of fraudulent activities.

Keywords: self-organizing map technology, fraud detection, information visualization, data analysis, composite intelligent system technologies, decision support technologies

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Authors: Chu-Tzu Chen, Angela S. Huang, Yu-Min Chou, Chin-Hui Yang

Abstract:

Dengue is a major public health concern throughout tropical and sub-tropical regions. Taiwan is located in the Pacific Ocean and overlying the tropical and subtropical zones. The island remains humid throughout the year and receives abundant rainfall, and the temperature is very hot in summer at southern Taiwan. It is ideal for the growth of dengue vectors and would be increasing the risk on dengue outbreaks. During the first half of the 20th century, there were three island-wide dengue outbreaks (1915, 1931, and 1942). After almost forty years of dormancy, a DEN-2 outbreak occurred in Liuchiu Township, Pingtung County in 1981. Thereafter, more dengue outbreaks occurred with different scales in southern Taiwan. However, there were more than ten thousands of dengue cases in 2014 and in 2015. It did not only affect human health, but also caused widespread social disruption and economic losses. The study would like to reveal the epidemiology of dengue on Taiwan, especially the severe outbreak in 2015, and try to find the effective interventions in dengue control including dengue vaccine development for the elderly. Methods: The study applied the Notifiable Diseases Surveillance System database of the Taiwan Centers for Disease Control as data source. All cases were reported with the uniform case definition and confirmed by NS1 rapid diagnosis/laboratory diagnosis. Results: In 2014, Taiwan experienced a serious DEN-1 outbreak with 15,492 locally-acquired cases, including 136 cases of dengue hemorrhagic fever (DHF) which caused 21 deaths. However, a more serious DEN-2 outbreak occurred with 43,419 locally-acquired cases in 2015. The epidemic occurred mainly at Tainan City (22,760 cases) and Kaohsiung City (19,723 cases) in southern Taiwan. The age distribution for the cases were mainly adults. There were 228 deaths due to dengue infection, and the case fatality rate was 5.25 ‰. The average age of them was 73.66 years (range 29-96) and 86.84% of them were older than 60 years. Most of them were comorbidities. To review the clinical manifestations of the 228 death cases, 38.16% (N=87) of them were reported with warning signs, while 51.75% (N=118) were reported without warning signs. Among the 87 death cases reported to dengue with warning signs, 89.53% were diagnosed sever dengue and 84% needed the intensive care. Conclusion: The year 2015 was characterized by large dengue outbreaks worldwide. The risk of serious dengue outbreak may increase significantly in the future, and the elderly is the vulnerable group in Taiwan. However, a dengue vaccine has been licensed for use in people 9-45 years of age living in endemic settings at the end of 2015. In addition to carry out the research to find out new interventions in dengue control, developing the dengue vaccine for the elderly is very important to prevent severe dengue and deaths.

Keywords: case fatality rate, dengue, dengue vaccine, the elderly

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Authors: Peng, Chun-Yi, Chen, Wei-Hsuan, Ueng, Shyh-Kuang

Abstract:

This study focuses on the application of self-organizing maps (SOM) technology in analyzing credit card transaction data, aiming to enhance the accuracy and efficiency of fraud detection. Som, as an artificial neural network, is particularly suited for pattern recognition and data classification, making it highly effective for the complex and variable nature of credit card transaction data. By analyzing transaction characteristics with SOM, the research identifies abnormal transaction patterns that could indicate potentially fraudulent activities. Moreover, this study has developed a specialized visualization tool to intuitively present the relationships between SOM analysis outcomes and transaction data, aiding financial institution personnel in quickly identifying and responding to potential fraud, thereby reducing financial losses. Additionally, the research explores the integration of SOM technology with composite intelligent system technologies (including finite state machines, fuzzy logic, and decision trees) to further improve fraud detection accuracy. This multimodal approach provides a comprehensive perspective for identifying and understanding various types of fraud within credit card transactions. In summary, by integrating SOM technology with visualization tools and composite intelligent system technologies, this research offers a more effective method of fraud detection for the financial industry, not only enhancing detection accuracy but also deepening the overall understanding of fraudulent activities.

Keywords: self-organizing map technology, fraud detection, information visualization, data analysis, composite intelligent system technologies, decision support technologies

Procedia PDF Downloads 34