Search results for: deep drawing

Authors: Nargiz Ismayilova

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The issue of modernism and the concept of postmodernism has been the focus of world researchers for many years, and there are very few researchers who have come to a common denominator about this term. During the independence period, the expansion of the relations of Azerbaijani literature with the world has led to the spread of many currents and tendencies formed in the West to the literary environment in our country. In this context, the works created in our environment are distinguished by their extreme richness in terms of subject matter and diversity in terms of genre. As an interesting example of contemporary postmodern prose in Azerbaijan, Parviz Jabrayil's novel "In a Foreign Language" pays attention with its more different plotline. The disagreement exists among the critics about the novel. Some are looking for high artistry in work; others are satisfied with the elements of postmodernism in work. Delimitation of the border between modernism and postmodernism can serve to carry out a deep scientific study of the novel. The novel depicts the world in the author's consciousness against the background of water shortage (thirst) in the Old City (Icharishahar). The author deconstructs today's Ichari Shahar mould. Along with modernism, elements of postmodernism occupy a large place in the work. When we look at the general tendencies of postmodernist art, we see that science and individuality are questioned, criticizing the sharp boundaries of modernism and the negativity of these restrictions, and modernism offers alternatives to artistic production by identifying its negatives and shortcomings in the areas of artistic freedom. The novel is extremely interesting in this point of view.

Keywords: concept of postmodernism, modernism, delimitation, political postmodernism, modern postmodern prose, Azerbaijani literature, novel, comparison, world literature, analysis

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Authors: A. M. John-Otumu, M. M. Rahman, M. C. Onuoha, E. P. Ojonugwa

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A Convolutional Neural Network (CNN) model for predicting Lassa fever was built using Python 3.8.0 programming language, alongside Keras 2.2.4 and TensorFlow 2.6.1 libraries as the development environment in order to reduce the current high risk of Lassa fever in West Africa, particularly in Nigeria. The study was prompted by some major flaws in existing conventional laboratory equipment for diagnosing Lassa fever (RT-PCR), as well as flaws in AI-based techniques that have been used for probing and prognosis of Lassa fever based on literature. There were 15,679 blood smear microscopic image datasets collected in total. The proposed model was trained on 70% of the dataset and tested on 30% of the microscopic images in avoid overfitting. A 3x3x3 convolution filter was also used in the proposed system to extract features from microscopic images. The proposed CNN-based model had a recall value of 96%, a precision value of 93%, an F1 score of 95%, and an accuracy of 94% in predicting and accurately classifying the images into clean or infected samples. Based on empirical evidence from the results of the literature consulted, the proposed model outperformed other existing AI-based techniques evaluated. If properly deployed, the model will assist physicians, medical laboratory scientists, and patients in making accurate diagnoses for Lassa fever cases, allowing the mortality rate due to the Lassa fever virus to be reduced through sound decision-making.

Keywords: artificial intelligence, ANN, blood smear, CNN, deep learning, Lassa fever

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Authors: Dionisio Andujar, Juan lópez-Correa, Hugo Moreno, Angela Ri

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The increased number of weeds in tomato crops highly lower yields. Weed identification with the aim of machine learning is important to carry out site-specific control. The last advances in computer vision are a powerful tool to face the problem. The analysis of RGB (Red, Green, Blue) images through Artificial Neural Networks had been rapidly developed in the past few years, providing new methods for weed classification. The development of the algorithms for crop and weed species classification looks for a real-time classification system using Object Detection algorithms based on Convolutional Neural Networks. The site study was located in commercial corn fields. The classification system has been tested. The procedure can detect and classify weed seedlings in tomato fields. The input to the Neural Network was a set of 10,000 RGB images with a natural infestation of Cyperus rotundus l., Echinochloa crus galli L., Setaria italica L., Portulaca oeracea L., and Solanum nigrum L. The validation process was done with a random selection of RGB images containing the aforementioned species. The mean average precision (mAP) was established as the metric for object detection. The results showed agreements higher than 95 %. The system will provide the input for an online spraying system. Thus, this work plays an important role in Site Specific Weed Management by reducing herbicide use in a single step.

Keywords: deep learning, object detection, cnn, tomato, weeds

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Authors: Tae-Uk Yun, Pullip Chung, Kee-Young Kwahk, Hyunchul Ahn

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Fake news is defined as the news articles that are intentionally and verifiably false, and could mislead readers. Spread of fake news may provoke anxiety, chaos, fear, or irrational decisions of the public. Thus, detecting fake news and preventing its spread has become very important issue in our society. However, due to the huge amount of fake news produced every day, it is almost impossible to identify it by a human. Under this context, researchers have tried to develop automated fake news detection using machine learning techniques over the past years. But, there have been no prior studies proposed an automated fake news detection method for Korean news to our best knowledge. In this study, we aim to detect Korean fake news using text mining and machine learning techniques. Our proposed method consists of two steps. In the first step, the news contents to be analyzed is convert to quantified values using various text mining techniques (topic modeling, TF-IDF, and so on). After that, in step 2, classifiers are trained using the values produced in step 1. As the classifiers, machine learning techniques such as logistic regression, backpropagation network, support vector machine, and deep neural network can be applied. To validate the effectiveness of the proposed method, we collected about 200 short Korean news from Seoul National University’s FactCheck. which provides with detailed analysis reports from 20 media outlets and links to source documents for each case. Using this dataset, we will identify which text features are important as well as which classifiers are effective in detecting Korean fake news.

Keywords: fake news detection, Korean news, machine learning, text mining

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Authors: Araya Yordchim, Rosjana Chandhasa, Suwaree Yordchim

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This research aims to study guidelines on the development of management process for research journals in order to develop Suan Sunandha Rajabhat University to international standards. This research investigated affecting elements ranging from the format of the article, evaluation form for research article quality, the process of creating a scholarly journal, satisfaction level of those with knowledge and competency to conduct research, arisen problems, and solutions. Drawing upon the sample size of 40 persons who had knowledge and competency in conducting research and creating scholarly journal articles at an international level, the data for this research were collected using questionnaires as a tool. Through the usage of computer software, data were analyzed by using the statistics in the forms of frequency, percentage, mean, standard deviation, and multiple regression analysis. The majority of participants were civil servants with a doctorate degree, followed by civil servants with a master's degree. Among them, the suitability of the article format was rated at a good level while the evaluation form for research articles quality was assessed at a good level. Based on participants' viewpoints, the process of creating scholarly journals was at a good level, while the satisfaction of those who had knowledge and competency in conducting research was at a satisfactory level. The problems encountered were the difficulty in accessing the website. The solution to the problem was to develop a website with user-friendly accessibility, including setting up a Google scholar profile for the purpose of references counting and the articles being used for reference in real-time. Research article format influenced the level of satisfaction of those who had the knowledge and competency to conduct research with statistical significance at the 0.01 level. The research article quality assessment form (preface section, research article writing section, preparation for research article manuscripts section, and the original article evaluation form for the author) affected the satisfaction of those with knowledge and competency to conduct research with the statistical significance at the level of 0.01. The process of establishing journals had an impact on the satisfaction of those with knowledge and ability to conduct research with statistical significance at the level of .05

Keywords: guidelines, development of management, research journals, international standards

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Authors: Dr. Dionysis Panos Dpt. Communication, Internet Studies Cyprus University of Technology

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The widespread use of New Media and particularly Social Media, through fixed or mobile devices, has changed in a staggering way our perception about what is “intimate" and "safe" and what is not, in interpersonal communication and social relationships. The distribution of self and identity-related information in communication now evolves under new and different conditions and contexts. Consequently, this new framework forces us to rethink processes and mechanisms, such as what "exposure" means in interpersonal communication contexts, how the distinction between the "private" and the "public" nature of information is being negotiated online, how the "audiences" we interact with are understood and constructed. Drawing from an interdisciplinary perspective that combines sociology, communication psychology, media theory, new media and social networks research, as well as from the empirical findings of a longitudinal comparative research, this work proposes an integrative model for comprehending mechanisms of personal information management in interpersonal communication, which can be applied to both types of online (Computer-Mediated) and offline (Face-To-Face) communication. The presentation is based on conclusions drawn from a longitudinal qualitative research study with 458 new media users from 24 countries for almost over a decade. Some of these main conclusions include: (1) There is a clear and evidenced shift in users’ perception about the degree of "security" and "familiarity" of the Web, between the pre- and the post- Web 2.0 era. The role of Social Media in this shift was catalytic. (2) Basic Web 2.0 applications changed dramatically the nature of the Internet itself, transforming it from a place reserved for “elite users / technical knowledge keepers" into a place of "open sociability” for anyone. (3) Web 2.0 and Social Media brought about a significant change in the concept of “audience” we address in interpersonal communication. The previous "general and unknown audience" of personal home pages, converted into an "individual & personal" audience chosen by the user under various criteria. (4) The way we negotiate the nature of 'private' and 'public' of the Personal Information, has changed in a fundamental way. (5) The different features of the mediated environment of online communication and the critical changes occurred since the Web 2.0 advance, lead to the need of reconsideration and updating the theoretical models and analysis tools we use in our effort to comprehend the mechanisms of interpersonal communication and personal information management. Therefore, is proposed here a new model for understanding the way interpersonal communication evolves, based on a revision of social penetration theory.

Keywords: new media, interpersonal communication, social penetration theory, communication exposure, private information, public information

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Authors: Liwen Wang, Yuting Chen, Tong Wu, Shaolei Hu

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In order to enhance the security of critical financial infrastructure, this study carries out a transformation of the architecture of a financial trading terminal to a zero trust architecture (ZTA), constructs an active defense system for cybersecurity, improves the security level of trading services in the Internet environment, enhances the ability to prevent network attacks and unknown risks, and reduces the industry and security risks brought about by cybersecurity risks. This study introduces the SDP technology of ZTA, adapts and applies it to a financial trading terminal to achieve security optimization and fine-grained business grading control. The upgraded architecture of the trading terminal moves security protection forward to the user access layer, replaces VPN to optimize remote access, and significantly improves the security protection capability of Internet transactions. The study achieves 1. deep integration with the access control architecture of the transaction system; 2. no impact on the performance of terminals and gateways, and no perception of application system upgrades; 3. customized checklist and policy configuration; 4. introduction of industry-leading security technology such as single-packet authorization (SPA) and secondary authentication. This study carries out a successful application of ZTA in the field of financial trading and provides transformation ideas for other similar systems while improving the security level of financial transaction services in the Internet environment.

Keywords: zero trust, trading terminal, architecture, network security, cybersecurity

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Authors: Neeru Deep, Kimberly McAlister

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Mental health issues have been increasing worldwide for many decades, but the COVID-19 pandemic has brought mental health issues into the spotlight. Within higher education, promoting the well-being of students has dramatically increased in focus. The Northwestern State University of Louisiana opened the Center for Positivity, Well-being, and Hope using the action research process of reflecting, planning, acting, and observing. The study’s purpose is two-fold: First, it highlights how to create a collaborative team to reflect, plan, and act to develop a well-being culture in higher education institutions. Second, it investigates the efficacy of the center through Seligman’s lenses. The researchers shared their experience in the first three phases of the action research process and then applied an identical concurrent mixed methods design. A purposive sample evaluated the efficacy of the center through Seligman’s lenses. The researcher administered PERMA-Profiler Measure, the PERMA-Profiler Measure overview, the CoPWH Evaluation I, and the CoPWH Evaluation II questionnaires to collect qualitative and quantitative data. The thematic analysis for qualitative and descriptive statistics for quantitative data concluded that the center creates a well-being culture and promotes well-being in college students. In conclusion, this action research shares the successful implementation of the cyclic process of research in promoting a well-being culture in higher education with the implications for promoting a well-being culture in various educational settings, workplaces, and communities.

Keywords: action research, mixed methods research design, Seligman, well-being.

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Authors: Arth J. Shah, Madhu R. Kamble

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Voice biometric liveness detection is customized to certify an authentication process of the voice data presented is genuine and not a recording or synthetic voice. With the rise of deepfakes and other equivalently sophisticated spoofing generation techniques, it’s becoming challenging to ensure that the person on the other end is a live speaker or not. Voice Liveness Detection (VLD) system is a group of security measures which detect and prevent voice spoofing attacks. Motivated by the recent development of the Kolmogorov-Arnold Network (KAN) based on the Kolmogorov-Arnold theorem, we proposed KAN for the VLD task. To date, multilayer perceptron (MLP) based classifiers have been used for the classification tasks. We aim to capture not only the compositional structure of the model but also to optimize the values of univariate functions. This study explains the mathematical as well as experimental analysis of KAN for VLD tasks, thereby opening a new perspective for scientists to work on speech and signal processing-based tasks. This study emerges as a combination of traditional signal processing tasks and new deep learning models, which further proved to be a better combination for VLD tasks. The experiments are performed on the POCO and ASVSpoof 2017 V2 database. We used Constant Q-transform, Mel, and short-time Fourier transform (STFT) based front-end features and used CNN, BiLSTM, and KAN as back-end classifiers. The best accuracy is 91.26 % on the POCO database using STFT features with the KAN classifier. In the ASVSpoof 2017 V2 database, the lowest EER we obtained was 26.42 %, using CQT features and KAN as a classifier.

Keywords: Kolmogorov Arnold networks, multilayer perceptron, pop noise, voice liveness detection

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Authors: Q. Toufeeq, R. Kauser, U. R. Jamil, N. Sohaib

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Foundation design of a structure needs soil investigation to avoid failures due to settlements. This soil investigation is expensive and time-consuming. Developments of new residential societies involve huge leveling of large sites that is accompanied by heavy land filling. Poor practices of land fill for deep depths cause differential settlements and consolidations of underneath soil that sometimes result in the collapse of structures. The extent of filling remains unknown to the individual developer unless soil investigation is carried out. Soil investigation cannot be performed on each available site due to involved costs. However, fair estimate of bearing capacity can be made if such tests are already done in the surrounding areas. The geotechnical guidance maps can provide a fair assessment of soil properties. Previously, GIS-based approaches have been used to develop maps using extrapolation and interpolations techniques for bearing capacities, underground recharge, soil classification, geological hazards, landslide hazards, socio-economic, and soil liquefaction mapping. Standard penetration test (SPT) data of surrounding sites were already available. Google Earth is used for digitization of collected data. Few points were considered for data calibration and validation. Resultant Geographic information system (GIS)-based guidance maps are helpful to anticipate the bearing capacity in the real estate industry.

Keywords: bearing capacity, soil classification, geographical information system, inverse distance weighted, radial basis function

Procedia PDF Downloads 135

Authors: Veliswa Nonfundo Hoho, Jabulani Gilford Kheswa

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This paper reports on teenage motherhood and its adverse outcomes on the academic performance, emotional well-being and sexual relationships that adolescent females encounter. Drawing from Ryff’s six dimensions of psychological well-being and Bronfenbrenner’s ecological model which underpinned this study, teenage motherhood has been found to link with multiple factors such as poverty, negative self-esteem, substance abuse, cohabitation, intimate partner violence and ill-health. Furthermore, research indicates that in schools where educators fail to perform their duties as loco-parentis to motivate adolescent females learners who are mothers, absenteeism, poor academic performance and learned helplessness, are likely. The aim of this research was two-fold, namely; (i) to determine the impact of teenage motherhood on the psychological well-being of the teenage mothers and (ii) to investigate the policies which protect the human rights of teenage mothers attending secondary schools. In a qualitative study conducted in one secondary school, Fort Beaufort, Eastern Cape, South Africa, fifteen Xhosa-speaking teenage mothers, aged 15-18 years old, were interviewed. The sample was recruited by means of snow-ball sampling. To safeguard the human dignity of the respondents, informed consent, confidentiality, anonymity and privacy of the respondents were assured. For trustworthiness, this research ensured that credibility, neutrality, and transferability, are met. Following an axial and open coding of responses, five themes were identified; Health issues of teenage mothers, lack of support, violation of human rights, impaired sense of purpose in life and intimate partner-violence. From these findings, it is clear that teenage mothers lack resilience and are susceptible to contract sexually transmitted infections and HIV/AIDS because they are submissive and hopeless. Furthermore, owing to stigma that the teenage mothers' experience from family members, they resort to alcohol and drug abuse, and feel demotivated to bond with their babies. In conclusion, the recommendations are that the Health and Social Development departments collaborate to empower the psychological well-being of teenage mothers. Furthermore, school policies on discrimination should be enacted and consistently implemented.

Keywords: depression, discrimination, self-esteem, teenage mothers

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Authors: J. Aliyu, A. O. Raji, A. A. Ibrahim

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The study was carried out to assess the fertility, early and late embryonic mortalities as well as hatchability by strain, season and hen’s weight in Nigerian indigenous chickens reared on deep litter. Four strains (normal feathered, naked neck, frizzle and dwarf) of hens maintained at a mating ratio of 1 cock to 4 hens, fed breeders mash and water ad libitum were used in a three year experiment. The data generated were subjected to analysis of variance using the SAS package and the means, where significant, were separated using the least significant difference (LSD). There were significant effects (P < 0.05) of strain on all the traits studied. Fertility was generally high (84.29 %) in all the strains. Early embryonic mortality was significantly lowest (P < 0.01) in naked neck which had the highest late embryonic mortality (P < 0.001). Hatchability was significantly highest (P < 0.01) in normal feathered (80.23 %) and slightly depressed in frizzle (74.95 %) and dwarf (72.27 %) while naked neck had the lowest (60.80 %). Season of the year had significant effects on early embryonic mortality. Dry hot season significantly (P < 0.05) depressed fertility while early embryonic mortality was depressed in the wet season (15.33 %). Early and late embryonic mortalities significantly increased (P < 0.05) with increasing weight of hen. Dwarf, frizzle and normal feathered hens could be used to improve hatchability as well as reduce early and late embryonic mortalities in Nigerian indigenous chickens.

Keywords: chicken, fertility, hatchability, indigenous, strain

Procedia PDF Downloads 416

Authors: Bal Deep Sharma, Suresh Ray Yadav

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Local soils are often chosen due to their widespread availability and low cost. However, these soils typically have poor durability, which can lead to significant limitations in their use for construction. To address this issue, various soil stabilization techniques have been developed and used over the years. This study investigates the viability of employing the mineral polymerization (MIP) technique to stabilize black soils, intending to enhance their suitability for construction applications. This technique involves the microstructural transformation of certain clay minerals into solid and stable compounds exhibiting characteristics similar to hydroxy sodalite, feldspathoid, or zeolite. This transformation occurs through the action of an alkaline reactant at atmospheric pressure and low temperature. The soil sample was characterized using grain size distribution, Atterberg limit test, organic content test, and pH-value tests. The unconfined compressive strength of the soil specimens, prepared with varying percentages of sodium hydroxide as an additive and sand as a filler by weight, was determined at the optimum moisture content. The unconfined compressive strength of the specimens was tested under three different conditions: dry, wet, and cycling. The maximum unconfined compressive strengths were 77.568 kg/cm², 38.85 kg/cm², and 56.3 kg/cm² for the dry, wet, and cycling specimens, respectively, while the unconfined compressive strength of the untreated soil was 7.38 kg/cm². The minimum unconfined compressive strength of the wet and cycling specimens was greater than that of the untreated soil. Based on these findings, it can be concluded that these soils can be effectively used as construction material after treatment with sodium hydroxide.

Keywords: soil stabilization technique, soft soil treatment, sodium hydroxide, unconfined compressive strength

Procedia PDF Downloads 80

Authors: Nor Ruba’Yah Binti Abd Rahim, Norsyahidah Binti Jaafar

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Translating Malay idiomatic expressions into other languages presents unique challenges due to the deep cultural nuances and linguistic intricacies embedded within these expressions. This study examined these challenges through a two-pronged methodology: a comparative analysis using survey questionnaires and a quiz administered to 50 semester 6 students who are taking Translation 1 course, and in-depth interviews with their lecturers. The survey aimed to capture students’ experiences and difficulties in translating selected Malay idioms into English, highlighting common errors and misunderstandings. Complementing this, interviews with lecturers provided expert insights into the nuances of these expressions and effective translation strategies. The findings revealed that literal translations often fail to convey the intended meanings, underscoring the importance of cultural competence and contextual awareness. The study also identified key factors that contribute to successful translations, such as the translator’s familiarity with both source and target cultures and their ability to adapt expressions creatively. This research contributed to the field of translation studies by offering practical recommendations for improving the translation of idiomatic expressions, thereby enhancing cross-cultural communication. The insights gained from this study are valuable for translators, educators, and students, emphasizing the need for a nuanced approach that respects the cultural richness of the source language while ensuring clarity in the target language.

Keywords: idiomatic expressions, cultural competence, translation strategies, cross-cultural communication, students’ difficulties

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Authors: Hala Alshamlan, Ghada Badr, Yousef Alohali

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Cancer is one of the dreadful diseases, which causes considerable death rate in humans. DNA microarray-based gene expression profiling has been emerged as an efficient technique for cancer classification, as well as for diagnosis, prognosis, and treatment purposes. In recent years, a DNA microarray technique has gained more attraction in both scientific and in industrial fields. It is important to determine the informative genes that cause cancer to improve early cancer diagnosis and to give effective chemotherapy treatment. In order to gain deep insight into the cancer classification problem, it is necessary to take a closer look at the proposed gene selection methods. We believe that they should be an integral preprocessing step for cancer classification. Furthermore, finding an accurate gene selection method is a very significant issue in a cancer classification area because it reduces the dimensionality of microarray dataset and selects informative genes. In this paper, we classify and review the state-of-art gene selection methods. We proceed by evaluating the performance of each gene selection approach based on their classification accuracy and number of informative genes. In our evaluation, we will use four benchmark microarray datasets for the cancer diagnosis (leukemia, colon, lung, and prostate). In addition, we compare the performance of gene selection method to investigate the effective gene selection method that has the ability to identify a small set of marker genes, and ensure high cancer classification accuracy. To the best of our knowledge, this is the first attempt to compare gene selection approaches for cancer classification using microarray gene expression profile.

Keywords: gene selection, feature selection, cancer classification, microarray, gene expression profile

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Authors: O. B. Citil, V. Sariyel, M. Akoz

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In this study, total fatty acid composition of muscle lipids of Cyprinus carpio L. living in Suğla Dam Lake, Altinapa Dam Lake, Eğirdir Lake and Burdur Lake were determined using GC. During this study, for the summer season of July was taken from each region of the land and they were stored in deep-freeze set to -20 degrees until the analysis date. At the end of the analyses, 30 different fatty acids were found in the composition of Cyprinus carpio L. which lives in different lakes. Cyprinus carpio Suğla Dam Lake of polyunsaturated fatty acids (PUFAs), were higher than other lakes. Cyprinus carpio L. was the highest in the major SFA palmitic acid. Polyunsaturated fatty acids (PUFA) of carp, the most abundant fish species in all lakes, were found to be higher than those of saturated fatty acids (SFA) in all lakes. Palmitic acid was the major SFA in all lakes. Oleic acid was identified as the major MUFA. Docosahexaenoic acid (DHA) was the most abundant in all lakes. ω3 fatty acid composition was higher than the percentage of the percentage ω6 fatty acids in all lake. ω3/ω6 rates of Cyprinus carpio L. Suğla Dam Lake, Altinapa Dam Lake, Eğirdir Lake and Burdur Lake, 2.12, 1.19, 2.15, 2.87, and 2.82, respectively. Docosahexaenoic acid (DHA) was the major PUFA in Eğirdir and Burdur lakes, whereas linoleic acid (LA) was the major PUFA in Altinapa and Suğla Dam Lakes. It was shown that the fatty acid composition in the muscle of carp was significantly influenced by different lakes.

Keywords: Cyprinus carpio L., fatty acid, composition, gas chromatography

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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: Mehwish Asghar

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Breast Cancer (BC) is a common type of cancer among women. Its screening is usually performed using different imaging modalities such as magnetic resonance imaging, mammogram, X-ray, CT, etc. Among these modalities’ mammogram is considered a powerful tool for diagnosis and screening of breast cancer. Sophisticated machine learning approaches have shown promising results in complementing human diagnosis. Generally, machine learning methods can be divided into two major classes: one is Radiomics analysis (RA), where image features are extracted manually; and the other one is the concept of convolutional neural networks (CNN), in which the computer learns to recognize image features on its own. This research aims to improve the incidence of early detection, thus reducing the mortality rate caused by breast cancer through the latest advancements in computer science, in general, and machine learning, in particular. It has also been aimed to ease the burden of doctors by improving and automating the process of breast cancer detection. This research is related to a relative analysis of different techniques for the implementation of different models for detecting and classifying breast cancer. The main goal of this research is to provide a detailed view of results and performances between different techniques. The purpose of this paper is to explore the potential of a convolutional neural network (CNN) w.r.t feature extractor and as a classifier. Also, in this research, it has been aimed to add the module of Radiomics for comparison of its results with deep learning techniques.

Keywords: breast cancer (BC), machine learning (ML), convolutional neural network (CNN), radionics, magnetic resonance imaging, artificial intelligence

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Authors: Fadlan Atmaja Nursiwan, Ugi Kurnia Gusti

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Garba Hill, located in Tekana Village, South Sumatera Province is comprised to South Sumatra Basin and classified as back arc basin. This area is entered as an active margin of Sundaland which experiences subduction several times since Mesozoic to recent time. The traces of Mesozoic subduction in the southern part of Sumatra island are exposed in Garba Hill area. The aim of this investigation is to study the tectonic changes in the first phase in Mesozoic era at the active margin of Sundaland which causes the rocks assemblage in Garba hill consist of continental and oceanic plate rocks which the correlation between those rocks show indistinct relation. This investigation is conducted by field observation in Tekana village and Lubar Village, Muara Dua, South Sumatra along with laboratory analysis included fossil and geochemistry analysis of radiolarian chert, petrography analysis of granite and basalt, and structural modelling. Fossil and geochemistry analysis of radiolarian chert and geochemistry of granite rocks shown the relation between the two rocks and Mesozoic subduction of Woyla terrane on western margin of Sundaland. Petrography analysis from granite and basalt depict the tectonic affinity of rocks. Moreover, structural analysis showed the changes of lineation direction from N-S to WNW-ESE.

Keywords: granite, mesozoic, radiolarian, subduction traces

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Authors: Ugochukwu Ejike Akpudo, Jank-Wook Hur

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The increasing demand for improved productivity, maintainability, and reliability has prompted rapidly increasing research studies on the emerging condition-based maintenance concept- Prognostics and health management (PHM). Varieties of fuel pumps serve critical functions in several hydraulic systems; hence, their failure can have daunting effects on productivity, safety, etc. The need for condition monitoring and assessment of these pumps cannot be overemphasized, and this has led to the uproar in research studies on standard feature extraction techniques for optimized condition assessment of fuel pumps. By extracting time-based, frequency-based and the more robust time-frequency based features from these vibrational signals, a more comprehensive feature assessment (and selection) can be achieved for a more accurate and reliable condition assessment of these pumps. With the aid of emerging deep classification and regression algorithms like the locally linear embedding (LLE), we propose a method for comprehensive condition assessment of electromagnetic fuel pumps (EMFPs). Results show that the LLE as a comprehensive feature extraction technique yields better feature fusion/dimensionality reduction results for condition assessment of EMFPs against the use of single features. Also, unlike other feature fusion techniques, its capabilities as a fault classification technique were explored, and the results show an acceptable accuracy level using standard performance metrics for evaluation.

Keywords: electromagnetic fuel pumps, comprehensive feature extraction, condition assessment, locally linear embedding, feature fusion

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Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

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Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: computer-aided system, detection, image segmentation, morphology

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Authors: Beier Zhu, Rui Zhang, Qi Song

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Text contained within fixed-layout documents can be of great semantic value and so requires a high localization accuracy, such as ID cards, invoices, cheques, and passports. Recently, algorithms based on deep convolutional networks achieve high performance on text detection tasks. However, for text localization in fixed-layout documents, such algorithms detect word bounding boxes individually, which ignores the layout information. This paper presents a novel architecture built on convolutional neural networks (CNNs). A global text localization network and a regional bounding-box regression network are introduced to tackle the problem in a coarse-to-fine manner. The text localization network simultaneously locates word bounding points, which takes the layout information into account. The bounding-box regression network inputs the features pooled from arbitrarily sized RoIs and refine the localizations. These two networks share their convolutional features and are trained jointly. A typical type of fixed-layout documents: ID cards, is selected to evaluate the effectiveness of the proposed system. These networks are trained on data cropped from nature scene images, and synthetic data produced by a synthetic text generation engine. Experiments show that our approach locates high accuracy word bounding boxes and achieves state-of-the-art performance.

Keywords: bounding box regression, convolutional networks, fixed-layout documents, text localization

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Authors: Lottie Lane

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It is habitually assumed and stated that the World Bank should engage and comply with international human rights standards. However, the basis for holding the Bank to such standards is unclear. Most advocates of the idea invoke aspects of international law to argue that the Bank has existing obligations to act in compliance with human rights standards. The Bank itself, however, does not appear to accept such arguments, despite having endorsed the importance of human rights for a considerable length of time. A substantial challenge is that under the current international human rights law framework, the World Bank is considered a non-state actor, and as such, has no direct human rights obligations. In the absence of clear legal duties for the Bank, it is necessary to look at the tools available beyond the international human rights framework to encourage the Bank to comply with human rights standards. This article critically examines several bases for arguing that the Bank should comply and engage with human rights through its policies and practices. Drawing on the Bank’s own ‘good governance’ approach as well as the United Nations’ ‘human rights-based-approach’ to development, a new basis is suggested. First, the relationship between the World Bank and human rights is examined. Three perspectives are considered: (1) the legal position – what the status of the World Bank is under international human rights law, and whether it can be said to have existing legal human rights obligations; (2) the Bank’s own official position – how the Bank envisages its relationship with and role in the protection of human rights; and (3) the relationship between the Bank’s policies and practices and human rights (including how its attitudes are reflected in its policies and how the Bank’s operations impact human rights enjoyment in practice). Here, the article focuses on two examples – the (revised) 2016 Environmental and Social Safeguard Policies and the 2012 case-study regarding Gambella, Ethiopia. Both examples are widely considered missed opportunities for the Bank to actively engage with human rights. The analysis shows that however much pressure is placed on the Bank to improve its human rights footprint, it is extremely reluctant to do so explicitly, and the legal bases available are insufficient for requiring concrete, ex ante action by the Bank. Instead, the Bank’s own ‘good governance’ approach to development – which it has been advocating since the 1990s – can be relied upon. ‘Good governance’ has been used and applied by many actors in many contexts, receiving numerous different definitions. This article argues that human rights protection can now be considered a crucial component of good governance, at least in the context of development. In doing so, the article explains the relationship and interdependence between the two concepts, and provides three rationales for the Bank to take a ‘human rights-based approach’ to good governance. Ultimately, this article seeks to look beyond international human rights law and take a governance approach to provide a convincing basis upon which to argue that the World Bank should comply with human rights standards.

Keywords: World Bank, international human rights law, good governance, human rights-based approach

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Authors: Samuel Owoade, Zainab Idowu, Idris Ajibade, Abel Uzoka

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Cloud computing adoption continues to soar, with 83% of enterprise workloads estimated to be in the cloud by 2022. However, this rapid migration raises security concerns, needing strong security management solutions to safeguard sensitive data and essential applications. This paper investigates the critical role of technical project managers in orchestrating security management initiatives for cloud environments, evaluating their responsibilities, challenges, and best practices for assuring the resilience and integrity of cloud infrastructures. Drawing from a comprehensive review of industry reports and interviews with cloud security experts, this research highlights the multifaceted landscape of security management in cloud environments. Despite the rapid adoption of cloud services, only 25% of organizations have matured their cloud security practices, indicating a pressing need for effective management strategies. This paper proposes a strategy framework adapted to the demands of technical project managers, outlining the important components of effective cloud security management. Notably, 76% of firms identify misconfiguration as a major source of cloud security incidents, underlining the significance of proactive risk assessment and constant monitoring. Furthermore, the study emphasizes the importance of technical project managers in facilitating cross-functional collaboration, bridging the gap between cybersecurity professionals, cloud architects, compliance officers, and IT operations teams. With 68% of firms seeing difficulties integrating security policies into their cloud systems, effective communication and collaboration are critical to success. Case studies from industry leaders illustrate the practical use of security management projects in cloud settings. These examples demonstrate the importance of technical project managers in using their expertise to address obstacles and generate meaningful outcomes, with 92% of firms reporting improved security practices after implementing proactive security management tactics. In conclusion, this research underscores the critical role of technical project managers in safeguarding cloud environments against evolving threats. By embracing their role as guardians of the cloud realm, project managers can mitigate risks, optimize resource utilization, and uphold the trust and integrity of cloud infrastructures in an era of digital transformation.

Keywords: cloud security, security management, technical project management, cybersecurity, cloud infrastructure, risk management, compliance

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Authors: Mohammad Hossein Badamchi

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As Leo Strauss demonstrates in his works, Political Philosophy in the western tradition is an epistemic-naturalistic tradition insofar Hanna Arendt mentioning the deep conflict between philosophy and politics, opposed to be named “political philosopher” prefer the title “political thinker” for herself. In fact, the Western political philosophy’s tendency to derive politics from natural law and epistemic argumentations makes a paradox between the actual “the political” and the theoretical “natural politics” in the western tradition. In this paper, we want to show that Hanna Arendt, in her exploration to find a new realm of the non-naturalistic way of thinking about the political is walking on a completely different tradition of political philosophy which was first established by Al-Farabi, the founder of Islamic political philosophy around thousand years after Greek Philosophy. Despite Aristotelian Polis which is a Natural community based on true natural rationality to reach the natural purposes of mankind, Al-Farabi’s Madine (his reconstructed concept of Aristotelian Polis) is completely constructed against natural cities, which are formulated by necessity logic of natural arguments and natural deception of humanity. In fact, Farabi considers the natural understanding of politics as Ignorant ideologies used by governments to suppress people. Madine in Farabi’s work is not a natural institution but is a collaborative constitution founded by citizens. So despite Aristotelian thinking, here we don’t have just A Polis that is the one true polis, but we have various multiple Madines among one, is virtuous not by definition but by real action of citizens and civil relations. Al-Farabi’s political philosophy is not a Naturalistic-epistemic Political Philosophy but is a Phronetic Political Philosophy which Hanna Arendt wants to establish outside of western contemplative anti-active political philosophy tradition.

Keywords: al-farabi, hanna arendt, natural politics, the political, political philosophy

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Authors: Mohd Iqbal Malik

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Ethical philosophy of Quran pinnacled virtue and economics as the part and parcel of human life. Human beings are to be imagined by the sign of morals. Soul and morality are both among the essences of human personality. Islam lays the foundation of ethics by installation of making a momentous variance between virtue and vice. It suggests for the distribution of wealth in-order to terminate accumulation of economic resources. Quran claims for the ambiguous pavement to attain virtue by saying, ‘Never will you attain the good (reward) until you spend (in the way of Allah) from that which you love. And whatever you spend indeed, Allah knows of it.’ The essence of Quran is to eliminate all the deep-seated approaches through which the wealth of nations is being accumulated within few hands. The paper will study the Quranic Philosophy Of Islamic Economic System. In recent times, to get out of the human resource development mystery of Muslims, Ismail Al-Raji Faruqi led the way in the so-called ‘Islamization’ of knowledge. Rahman and Faruqi formed opposite opinions on this project. Al-Faruqi thought of the Islamization of knowledge in terms of introducing Western learning into received Islamic values and vice versa. This proved to be a mere peripheral treatment of Islamic values in relation to Western knowledge. It is true that out of the programme of Islamization of knowledge arose Islamic universities in many Muslim countries. Yet the academic programmes of these universities were not founded upon a substantive understanding and application of the tawhidi epistemology.

Keywords: ethical philosophy, modern Islamic finance, knowledge of finance, Islamic banking

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Authors: Shohreh Ghasemi

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Introduction: Melanoma is a complex disease with various clinical and histopathological features that impact prognosis and treatment decisions. Traditional methods of melanoma prognosis involve manual examination and interpretation of clinical and histopathological data by dermatologists and pathologists. However, the subjective nature of these assessments can lead to inter-observer variability and suboptimal prognostic accuracy. AI, with its ability to analyze vast amounts of data and identify patterns, has emerged as a promising tool for improving melanoma prognosis. Methods: A comprehensive literature search was conducted to identify studies that employed AI techniques for melanoma prognosis. The search included databases such as PubMed and Google Scholar, using keywords such as "artificial intelligence," "melanoma," and "prognosis." Studies published between 2010 and 2022 were considered. The selected articles were critically reviewed, and relevant information was extracted. Results: The review identified various AI methodologies utilized in melanoma prognosis, including machine learning algorithms, deep learning techniques, and computer vision. These techniques have been applied to diverse data sources, such as clinical images, dermoscopy images, histopathological slides, and genetic data. Studies have demonstrated the potential of AI in accurately predicting melanoma prognosis, including survival outcomes, recurrence risk, and response to therapy. AI-based prognostic models have shown comparable or even superior performance compared to traditional methods.

Keywords: artificial intelligence, melanoma, accuracy, prognosis prediction, image analysis, personalized medicine

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Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay

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Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.

Keywords: retail stores, faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition

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Authors: Chris Schoborg, Morgan C. Wang

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In the realm of the National Football League (NFL), substantial dedication of time and effort is invested by both players and coaches in meticulously analyzing the game footage of their opponents. The primary aim is to anticipate the actions of the opposing team. Defensive players and coaches are especially focused on deciphering their adversaries' intentions to effectively counter their strategies. Acquiring insights into the specific play type and its intended direction on the field would confer a significant competitive advantage. This study establishes pre-snap information as the cornerstone for predicting both the play type (e.g., deep pass, short pass, or run) and its spatial trajectory (right, left, or center). The dataset for this research spans the regular NFL season data for all 32 teams from 2013 to 2022. This dataset is acquired using the nflreadr package, which conveniently extracts play-by-play data from NFL games and imports it into the R environment as structured datasets. In this study, we employ a recently developed machine learning algorithm, XGBoost. The final predictive model achieves an impressive lift of 2.61. This signifies that the presented model is 2.61 times more effective than random guessing—a significant improvement. Such a model has the potential to markedly enhance defensive coaches' ability to formulate game plans and adequately prepare their players, thus mitigating the opposing offense's yardage and point gains.

Keywords: lift, NFL, sports analytics, XGBoost

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Authors: Estelle Ardanouy, Helene Delage, Pascal Zesiger

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Morphological awareness contributes to the acquisition of reading and spelling in typical learners as well as in children with learning disorders. Indeed, the acquisition of phoneme-grapheme correspondences is not sufficient to master spelling, especially in inconsistent orthographic systems such as English or French. Several meta-analyses show the benefit of explicit training in derivational morphology on reading and spelling in old children (who have already learned the main grapheme-phoneme correspondences), but highlight the lack of studies with younger children, particularly in French. In this study, we chose to focus on the efficiency of an intensive training in derivational morphology on spelling skills in French-speaking four-graders (9-10 years of age). The training consisted of 1) learning how to divide words into morphemes (ex: para/pente in French, paraglider in English), as well as 2) working on the meaning of affixes in relation to existing words (ex: para/pente: to protect against – para - the slope -pente). One group of pupils (N = 37, M age = 9.5) received this experimental group training in morphology while an alternative training group (N = 34, M age = 9.6) received a visuo-semantic training based on visual cues to memorize the spelling difficulties of complex words (such as the doubling of “r” in “verre” in French -or "glass" in English-which are represented by the drawing of two glasses). Both trainings lasted a total of 15 hours at a rate of four 45 minutes sessions per week, resulting in five weeks of training in the school setting. Our preliminary results show a significant improvement in the experimental group in the spelling of affixes on the trained (p < 0.001) and untrained word lists (p <0.001), but also in the root of words on the trained (p <0.001) and untrained word lists group (p <0.001). The training effect is also present on both trained and untrained morphologically composed words. By contrast, the alternative training group shows no progress on these previous measures (p >0.15). Further analyses testing the effects of both trainings on other measures such as morphological awareness and reading of morphologically compose words are in progress. These first results support the effectiveness of explicitly teaching derivational morphology to improve spelling in school-aged children. The study is currently extended to a group of children with developmental dyslexia because these children are known for their severe and persistent spelling difficulties.

Keywords: developmental dyslexia, derivational morphology, reading, school-aged children, spelling, training

Procedia PDF Downloads 176