Search results for: random generation

Authors: Saahith M. S., Sivakami R.

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In the realm of football analytics, particularly focusing on predicting football player performance, the ability to forecast player success accurately is of paramount importance for teams, managers, and fans. This study introduces an elaborate examination of predicting football player performance through the integration of data visualization methods and machine learning algorithms. The research entails the compilation of an extensive dataset comprising player attributes, conducting data preprocessing, feature selection, model selection, and model training to construct predictive models. The analysis within this study will involve delving into feature significance using methodologies like Select Best and Recursive Feature Elimination (RFE) to pinpoint pertinent attributes for predicting player performance. Various machine learning algorithms, including Random Forest, Decision Tree, Linear Regression, Support Vector Regression (SVR), and Artificial Neural Networks (ANN), will be explored to develop predictive models. The evaluation of each model's performance utilizing metrics such as Mean Squared Error (MSE) and R-squared will be executed to gauge their efficacy in predicting player performance. Furthermore, this investigation will encompass a top player analysis to recognize the top-performing players based on the anticipated overall performance scores. Nationality analysis will entail scrutinizing the player distribution based on nationality and investigating potential correlations between nationality and player performance. Positional analysis will concentrate on examining the player distribution across various positions and assessing the average performance of players in each position. Age analysis will evaluate the influence of age on player performance and identify any discernible trends or patterns associated with player age groups. The primary objective is to predict a football player's overall performance accurately based on their individual attributes, leveraging data-driven insights to enrich the comprehension of player success on the field. By amalgamating data visualization and machine learning methodologies, the aim is to furnish valuable tools for teams, managers, and fans to effectively analyze and forecast player performance. This research contributes to the progression of sports analytics by showcasing the potential of machine learning in predicting football player performance and offering actionable insights for diverse stakeholders in the football industry.

Keywords: football analytics, player performance prediction, data visualization, machine learning algorithms, random forest, decision tree, linear regression, support vector regression, artificial neural networks, model evaluation, top player analysis, nationality analysis, positional analysis

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Authors: Anupama Singh, Papia Raj

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Though Municipal Solid Waste (MSW) is a worldwide problem, yet its implications are enormous in developing countries, as they are unable to provide proper Municipal Solid Waste Management (MSWM) for the large volume of MSW. As a result, the collected wastes are dumped in open dumping at landfilling sites while the uncollected wastes remain strewn on the roadside, many-a-time clogging drainage. Such unsafe and inadequate management of MSW causes various public health hazards. For example, MSW directly on contact or by leachate contaminate the soil, surface water, and ground water; open burning causes air pollution; anaerobic digestion between the piles of MSW enhance the greenhouse gases i.e., carbon dioxide and methane (CO2 and CH4) into the atmosphere. Moreover, open dumping can cause spread of vector borne disease like cholera, typhoid, dysentery, and so on. Patna, the capital city of Bihar, one of the most underdeveloped provinces in India, is a unique representation of this situation. Patna has been identified as the ‘garbage city’. Over the last decade there has been an exponential increase in the quantity of MSW generation in Patna. Though a large proportion of such MSW is recyclable in nature, only a negligible portion is recycled. Plastic constitutes the major chunk of the recyclable waste. The chemical composition of plastic is versatile consisting of toxic compounds, such as, plasticizers, like adipates and phthalates. Pigmented plastic is highly toxic and it contains harmful metals such as copper, lead, chromium, cobalt, selenium, and cadmium. Human population becomes vulnerable to an array of health problems as they are exposed to these toxic chemicals multiple times a day through air, water, dust, and food. Based on analysis of health data it can be emphasized that in Patna there has been an increase in the incidence of specific diseases, such as, diarrhoea, dysentry, acute respiratory infection (ARI), asthma, and other chronic respiratory diseases (CRD). This trend can be attributed to improper MSWM. The results were reiterated through a survey (N=127) conducted during 2014-15 in selected areas of Patna. Random sampling method of data collection was used to better understand the relationship between different variables affecting public health due to exposure to MSW and lack of MSWM. The results derived through bivariate and logistic regression analysis of the survey data indicate that segregation of wastes at source, segregation behavior, collection bins in the area, distance of collection bins from residential area, and transportation of MSW are the major determinants of public health issues. Sustainable recycling is a robust method for MSWM with its pioneer concerns being environment, society, and economy. It thus ensures minimal threat to environment and ecology consequently improving public health conditions. Hence, this paper concludes that sustainable recycling would be the most viable approach to manage MSW in Patna and would eventually reduce public health hazards.

Keywords: municipal solid waste, Patna, public health, sustainable recycling

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Authors: Manpreet Kaur

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When legitimate credit card users are mistakenly labelled as fraudulent in numerous financial delated applications, there are numerous ethical problems. The innovative machine learning approach we have suggested in this research outperforms the current models and shows how to model a data set for credit card fraud detection while minimizing false positives. As a result, we advise using random forests as the best machine learning method for predicting and identifying credit card transaction fraud. The majority of victims of these fraudulent transactions were discovered to be credit card users over the age of 60, with a higher percentage of fraudulent transactions taking place between the specific hours.

Keywords: automated fraud detection, isolation forest method, local outlier factor, ML algorithm, credit card

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Authors: Amit Gill, Lalith Wijerathne, Sebastian Poledna

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This research presents the details of the implementation of high performance computing (HPC) extension of agent-based economic models (ABEMs) to simulate hundreds of millions of heterogeneous agents. ABEMs offer an alternative approach to study the economy as a dynamic system of interacting heterogeneous agents, and are gaining popularity as an alternative to standard economic models. Over the last decade, ABEMs have been increasingly applied to study various problems related to monetary policy, bank regulations, etc. When it comes to predicting the effects of local economic disruptions, like major disasters, changes in policies, exogenous shocks, etc., on the economy of the country or the region, it is pertinent to study how the disruptions cascade through every single economic entity affecting its decisions and interactions, and eventually affect the economic macro parameters. However, such simulations with hundreds of millions of agents are hindered by the lack of HPC enhanced ABEMs. In order to address this, a scalable Distributed Memory Parallel (DMP) implementation of ABEMs has been developed using message passing interface (MPI). A balanced distribution of computational load among MPI-processes (i.e. CPU cores) of computer clusters while taking all the interactions among agents into account is a major challenge for scalable DMP implementations. Economic agents interact on several random graphs, some of which are centralized (e.g. credit networks, etc.) whereas others are dense with random links (e.g. consumption markets, etc.). The agents are partitioned into mutually-exclusive subsets based on a representative employer-employee interaction graph, while the remaining graphs are made available at a minimum communication cost. To minimize the number of communications among MPI processes, real-life solutions like the introduction of recruitment agencies, sales outlets, local banks, and local branches of government in each MPI-process, are adopted. Efficient communication among MPI-processes is achieved by combining MPI derived data types with the new features of the latest MPI functions. Most of the communications are overlapped with computations, thereby significantly reducing the communication overhead. The current implementation is capable of simulating a small open economy. As an example, a single time step of a 1:1 scale model of Austria (i.e. about 9 million inhabitants and 600,000 businesses) can be simulated in 15 seconds. The implementation is further being enhanced to simulate 1:1 model of Euro-zone (i.e. 322 million agents).

Keywords: agent-based economic model, high performance computing, MPI-communication, MPI-process

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Authors: Mokhlisur Rahman

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Consumers have developed a sense of responsibility in the past decade, reflecting on their purchasing behavior after viewing an advertisement. Consumers tend to buy ideal products that enable them to be judged by their close network in the opinion world. In such value considerations, any information that feeds consumers' desire for social status helps, which becomes capital for educating consumers on the importance of purchasing green products for manufacturing companies. Companies' effort in manufacturing green products to get high conversion demands a good deal of promotion with quality information and engaging representation. Additionally, converting people from traditional to eco-friendly products requires innovative alternatives to replace the existing product. Considering consumers' understanding of products and their purchasing behavior, it becomes essential for the brands to know the extent to which consumers' level of awareness of the ecosystem is to make them more responsive to green products. Another is brand image plays a vital role in consumers' perception regarding the credibility of the claim regarding the product. Brand image is a significant positive influence on the younger generation, and younger generations tend to engage more in pro-environmental behavior, including purchasing sustainable products. For example, Adidas senses the necessity of satisfying consumers with something that brings more profits and serves the planet. Several of their eco-friendly products are already in the market, and one is UltraBOOST DNA parley, made from 3D-printed recycled ocean waste. As a big brand image, Adidas has leveraged an interest among the younger generation by incorporating sustainability into its advertising. Therefore, influential brands' effort in the sustainable revolution through engaging advertisement makes it more prominent by educating consumers about the reason behind launching the product. This study investigates younger consumers' attitudes toward sustainability, brand recognition, exposure to green advertising, willingness to receive more green advertising, purchasing green products, and motivation. The study conducts a market experiment by creating two video advertisements: a sustainable product video advertisement and a non-sustainable product video advertisement. Both the videos have similar content design and the same length of 2 minutes, but the messages are different based on the identical product type college bags. The first video advertisement promotes eco-friendly college bags made from biodegradable raw materials, and the second promotes non-sustainable college bags made from plastics. After viewing the videos, consumers make purchasing decisions and complete an online survey to collect their attitudes toward sustainable products. The study finds the importance of a sense of responsibility to the consumers for climate change issues. Also, it empowers people to take a step, even small, and increases environmental awareness. This study provides companies with the knowledge to participate in sustainable product launches by collecting consumers' perceptions and attitudes toward green products. Also, it shows how important it is to build a brand's image for the younger generation.

Keywords: brand-image, environment, green-advertising, sustainability, younger-consumer

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Authors: Shiva Ebrahimian Dehaghani, Afsaneh Doosti, Morteza Zare

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Background: There is no consensus regarding the association between dysphagia and cognition. Purpose: The aim of this study was to quantitatively and qualitatively analyze the available evidence on the direction and strength of association between dysphagia and cognition. Methodology: PubMed, Scopus, Embase and Web of Science were searched about the association between dysphagia and cognition. A random-effects model was used to determine weighted odds ratios (OR) and 95% confidence intervals (CI). Sensitivity analysis was performed to determine the impact of each individual study on the pooled results. Results: A total of 1427 participants showed that some cognitive disorders were significantly associated with dysphagia (OR = 3.23; 95% CI, 2.33–4.48). Conclusion: The association between cognition and swallowing disorders suggests that multiple neuroanatomical systems are involved in these two functions.

Keywords: adult, association, cognitive impairment, dysphagia, systematic review

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Authors: Johannes J. Schneider, Mathias S. Weyland, Peter Eggenberger Hotz, William D. Jamieson, Oliver Castell, Alessia Faggian, Rudolf M. Füchslin

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Agglomerations of polydisperse systems of spherical particles are created in computer simulations using a simplified stochastic-hydrodynamic model: Particles sink to the bottom of the cylinder, taking into account gravity reduced by the buoyant force, the Stokes friction force, the added mass effect, and random velocity changes. Two types of particles are considered, with one of them being able to create connections to neighboring particles of the same type, thus forming a network within the agglomeration at the bottom of a cylinder. Decreasing the fraction of these particles, a percolation transition occurs. The critical regime is determined by investigating the maximum cluster size and the percolation susceptibility.

Keywords: binary system, maximum cluster size, percolation, polydisperse

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Authors: Rexa Pasha

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The aim of this study was to examine the relationship between depression, stress and life satisfaction with sleep disturbance among Islamic Azad University Ahvaz Branch students. Samples in the study included 230 students who were selected by stratified random sampling. For data collection, the Beck Depression Inventory, stress, life satisfaction and quality of sleep (PSQI) was used. Which all have acceptable reliability and validity. This study was correlation and Data analysis using Pearson correlation and multivariate regression significance level (pKeywords: depression, life satisfaction, sleep disorder, sleep disturbane

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Authors: Ripon Sarkar, Kabita Chaterjee, Ananya Barui

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Smoking is one of the leading causes of oral cancer. Cigarette smoke affects various cellular parameters and alters molecular metabolism of cells. Epithelial cells losses their cytoskeleton structure, membrane integrity, cellular polarity that subsequently initiates the process of epithelial cells to mesenchymal transition due to long exposure of cigarette smoking. It changes the normal cellular metabolic activity which induces oxidative stress and enhances the reactive oxygen spices (ROS) formation. Excessive ROS and associated oxidative stress are considered to be a driving force in alteration in cellular phenotypes, polarity distribution and mitochondrial metabolism. Noninvasive assessment of such parameters plays essential role in development of routine screening system for early diagnosis of oral cancer. Electrical cell-substrate impedance sensing (ECIS) is one of such method applied for detection of cellular membrane impedance which can be correlated to cell membrane integrity. Present study intends to explore the alteration in cellular impedance along with the expression of cellular polarity molecules and cytoskeleton distributions in oral epithelial cells of habitual smokers and to correlate the outcome to that of clinically diagnosed oral leukoplakia and oral squamous cell carcinoma patients. Total 80 subjects were categorized into four study groups: nonsmoker (NS), cigarette smoker (CS), oral leukoplakia (OLPK) and oral squamous cell carcinoma (OSCC). Cytoskeleton distribution was analyzed by staining of actin filament and generation of ROS was measured using assay kit using standard protocol. Cell impedance was measured through ECIS method at different frequencies. Expression of E-cadherin and protease-activated receptor (PAR) proteins were observed through immune-fluorescence method. Distribution of actin filament is well organized in NS group however; distribution pattern was grossly varied in CS, OLPK and OSCC. Generation of ROS was low in NS which subsequently increased towards OSCC. Expressions of E-cadherin and change in cellular electrical impedance in different study groups indicated the hallmark of cancer progression from NS to OSCC. Expressions of E-cadherin, PAR protein, and cell impedance were decreased from NS to CS and farther OSCC. Generally, the oral epithelial cells exhibit apico-basal polarity however with cancer progression these cells lose their characteristic polarity distribution. In this study expression of polarity molecule and ECIS observation indicates such altered pattern of polarity among smoker group. Overall the present study monitored the alterations in intracellular ROS generation and cell metabolic function, membrane integrity in oral epithelial cells in cigarette smokers. Present study thus has clinical significance, and it may help in developing a noninvasive technique for early diagnosis of oral cancer amongst susceptible individuals.

Keywords: cigarette smoking, early oral cancer detection, electric cell-substrate impedance sensing, noninvasive screening

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Authors: Benjamin Sonnenreich

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Brittle fracture failure probability is best described using a stochastic approach which is based on the 'weakest link concept' and the connection between a microstructure and macroscopic fracture scale. A general theoretical and experimental framework is presented to predict the uniaxial strength distribution according to independent uniaxial test data. The framework takes as input the applied stresses, the geometry, the materials, the defect distributions and the relevant random variables from uniaxial test results and gives as output an overall failure probability that can be used to improve the reliability of practical designs. Additionally, the method facilitates comparisons of strength data from several sources, uniaxial tests, and sample geometries.

Keywords: brittle fracture, strength distribution, uniaxial, weakest link concept

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Authors: S. Nishat Fatima Rizvi, Tulika Chandra, Abbas Ali Mahdi, Devisha Agarwal

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Introduction: Blood components are an unexplored area prone to numerous discoveries which influence patient’s care. Experiments at different levels will further change the present concept of blood banking. Hyperlipidemia is a condition of elevated plasma level of low-density lipoprotein (LDL) as well as decreased plasma level of high-density lipoprotein (HDL). Studies show that platelets play a vital role in the progression of atherosclerosis and thrombosis, a major cause of death worldwide. They are activated by many triggers like elevated LDL in the blood resulting in aggregation and formation of plaques. Hyperlipidemic platelets are frequently transfused to patients with various disorders. Screening the random donor platelets for hyperlipidemia and correlating the condition with other donor criteria such as lipid rich diet, oral contraceptive pills intake, weight, alcohol intake, smoking, sedentary lifestyle, family history of heart diseases will lead to further deciding the exclusion criteria for donor selection. This will help in making the patients safe as well as the donor deferral criteria more stringent to improve the quality of blood supply. Technical evaluation and assessment will enable blood bankers to supply safe blood and improve the guidelines for blood safety. Thus, we try to study the correlation between hyperlipidemic platelets with platelets parameters, weight, and specific history of the donors. Methodology: This case control study included 100 blood samples of Blood donors, out of 100 only 30 samples were found to be hyperlipidemic and were included as cases, while rest were taken as controls. Lipid Profile were measured by fully automated analyzer (TRIGL:triglycerides),(LDL-C:LDL –Cholesterol plus 2nd generation),CHOL 2: Cholesterol Gen 2), HDL C 3: HDL-Cholesterol plus 3rdgeneration)-(Cobas C311-Roche Diagnostic).And Platelets parameters were analyzed by the Sysmex KX21 automated hematology analyzer. Results: A significant correlation was found amongst hyperlipidemic level in single time donor. In which 80% donors have history of heart disease, 66.66% donors have sedentary life style, 83.3% donors were smokers, 50% donors were alcoholic, and 63.33% donors had taken lipid rich diet. Active physical activity was found amongst 40% donors. We divided donors sample in two groups based on their body weight. In group 1, hyperlipidemic samples: Platelet Parameters were 75% in normal 25% abnormal in >70Kg weight while in 50-70Kg weight 90% were normal 10% were abnormal. In-group 2, Non Hyperlipidemic samples: platelet Parameters were 95% normal and 5% abnormal in >70Kg weight, while in 50-70Kg Weight, 66.66% normal and 33.33% abnormal. Conclusion: The findings indicate that Hyperlipidemic status of donors may affect the platelet parameters and can be distinguished on history by their weight, Smoking, Alcoholic intake, Sedentary lifestyle, Active physical activity, Lipid rich diet, Oral contraceptive pills intake, and Family history of heart disease. However further studies on a large sample size will affirm this finding.

Keywords: blood donors, hyperlipidemia, platelet, weight

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Authors: L. Petrovičová, Ž. Balážová, Z. Gálová, M. Wójcik-Jagła, M. Rapacz

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In the present study, RAPD-PCR was used to assess genetic diversity of the rye including landrances and new rye cultivars coming from Central Europe and the Union of Soviet Socialist Republics (SUN). Five arbitrary random primers were used to determine RAPD polymorphism in the set of 38 rye genotypes. These primers amplified altogether 43 different DNA fragments with an average number of 8.6 fragments per genotypes. The number of fragments ranged from 7 (RLZ 8, RLZ 9 and RLZ 10) to 12 (RLZ 6). DI and PIC values of all RAPD markers were higher than 0.8 that generally means high level of polymorphism detected between rye genotypes. The dendrogram based on hierarchical cluster analysis using UPGMA algorithm was prepared. The cultivars were grouped into two main clusters. In this experiment, RAPD proved to be a rapid, reliable and practicable method for revealing of polymorphism in the rye cultivars.

Keywords: genetic diversity, polymorphism, RAPD markers, Secale cereale L.

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Authors: Ahmed Emad Ahmed

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This paper aims to address the concept of human resources information systems (HRIS) and how to link it to new technologies such as artificial intelligence (AI) to be implemented in two human resources processes. A literature view has been collected to cover the main points related to HRIS, AI, and BC. A study case has been presented by generating a random HRIS to apply some AI operations to it. Then, an algorithm was applied to the database to complete some human resources processes, including training and performance appraisal, using a pre-trained AI model. After that, outputs and results have been presented and discussed briefly. Finally, a conclusion has been introduced to show the ability of new technologies such as AI and ML to be applied to the human resources management processes.

Keywords: human resources new technologies, HR artificial intelligence, HRIS AI models, construction AI HRIS

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Authors: Routsukol Sunalai

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This research purpose is to study and compare the administration of Buddhist monks at northeastern Thailand. The samples used in the study are the priest in the Northeast by simple random sampling for 190 sampling. The tools used in this study is questioner were created in the 40 question items. The statistics used for data analysis were percentage, average, and standard deviation. The research found that the human resources management for the Buddhist monks as a whole is moderate. But it was found that the highest average is the policy followed by the management information. The Buddhist monks aged less than 25 years old with the overall difference was not significant. The priests who are less than 10 years in the monk experience and the priest has long held in the position for 10 years are not different in the significant level.

Keywords: employee job-related outcomes, ethical institutionalization, quality of work life, stock exchange of Thailand

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Authors: Amal Machtalay

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In this survey, we aim to review the rapidly growing literature on numerical methods to solve different forms of mean field problems, namely mean field games (MFG), mean field controls (MFC), potential MFGs, and master equations, as well as their corresponding recent applications. Here, we distinguish two families of numerical methods: iterative methods based on mesh generation and those called mesh-free, normally related to neural networking and learning frameworks.

Keywords: mean-field games, numerical schemes, partial differential equations, complex systems, machine learning

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Authors: Choi Younshick, Lee Wonseok, Lee Jaemeun, Park Sun-Hyun, Kim Sunwoung, Park Sua, Kim Eun Ho, Kim Jong-Ki

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Iron accumulation in the brain accelerates Alzheimer’s disease progression. To cure iron toxicity, we assessed the therapeutic effects of noncontact transcranial electric field stimulation to the brain on toxic iron deposits in either the Aβ-fibril structure or the Aβ plaque in a mouse model of Alzheimer’s disease (AD). A capacitive electrode-based alternating electric field (AEF) was applied to a suspension of magnetite (Fe₃O₄) to measure the field-sensitized electro-Fenton effect and resultant reactive oxygen species (ROS) generation. The increase in ROS generation compared to the untreated control was both exposure-time and AEF-frequency dependent. The frequency-specific exposure of AEF to 0.7–1.4 V/cm on a magnetite-bound Aβ-fibril or a transgenic Alzheimer’s disease (AD) mouse model revealed the removal of intraplaque ferrous magnetite iron deposit and Aβ-plaque burden together at the same time compared to the untreated control. The results of the behavioral tests show an improvement in impaired cognitive function following AEF treatment on the AD mouse model. Western blot assay found some disease-modifying biological responses, including down-regulating ferroptosis, neuroinflammation and reactive astrocytes that eventually made cognitive improvement feasible. Tissue clearing and 3D-imaging analysis revealed no induced damage to the neuronal structures of normal brain tissue following AEF treatment. In conclusion, our results suggest that the effective degradation of magnetite-bound amyloid fibrils or plaques in the AD brain by the electro-Fenton effect from electric field-sensitized magnetite offers a potential electroceutical treatment option for AD.

Keywords: electroceutical, intraplaque magnetite, alzheimer’s disease, transcranial electric field, electro-fenton effect

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Authors: Ramazan Hasanzadeh, Leyla Vatandoust

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This study examined the efficacy of motivation management training for students’ academic achievement and self-concept. The pretest–posttest quasi-experimental study used a cluster random sampling method to select subjects for the experimental (20 subjects) and control (20 subjects) groups. posttest was conducted with both groups to determine the effect of the training. An academic achievement and academic self-concept questionnaire (grade point average requirement) was used for the pretest and posttest. The results showed that the motivation management training increased academic self-concept and academic achievement.

Keywords: motivation management, academic self-concept, academic achievement, students

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Authors: Ahmad FAROOQ, Xinfeng Zhang, Fahad Sabah, Raheem Sarwar

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In Traditional Chinese Medicine, tongue diagnosis is a vital inspection tool (TCM). In this study, we explore the potential of machine learning in tongue diagnosis. It begins with the cataloguing of the various classifications and characteristics of the human tongue. We infer 24 kinds of tongues from the material and coating of the tongue, and we identify 21 attributes of the tongue. The next step is to apply machine learning methods to the tongue dataset. We use the Weka machine learning platform to conduct the experiment for performance analysis. The 457 instances of the tongue dataset are used to test the performance of five different machine learning methods, including SVM, Random Forests, Decision Trees, and Naive Bayes. Based on accuracy and Area under the ROC Curve, the Support Vector Machine algorithm was shown to be the most effective for tongue diagnosis (AUC).

Keywords: medical imaging, image retrieval, machine learning, tongue

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Authors: Fang Tang

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A major Confucian masterpiece and the earliest-known poetry anthology (composed approximately 1046-771 BCE), The Classic of Poetry, reflects different cultures in ancient China. It is regarded as a Chinese classic and one of the world’s most significant written works, an essential part of our global cultural heritage. This paper explores how the ancient Chinese classic became transformed into part of popular culture, found in folk songs circulated in Fangxian county, a mountainous location in Hubei province in central mainland China. It is the hometown of one of the most well-known authors of The Classic of Poetry, whose name is Yin Jifu. Local villagers process, refine, and recreate these poems into popular folk songs, which have been handed down from generation to generation. The folk songs based on The Classic of Poetry vividly reflect local customs, life styles, and various cultural activities. After thousands of years of singing these traditional songs, the region has become an important area to maintain part of Chinese cultural heritages; here, the original high culture is converted into a popular culture that is absorbed into people’s daily life. Based on a year’s field research and many interviews with local singers, this paper explores the ways in which locals have transformed the contents of The Classic of Poetry. It examines how today these popular folk songs become part of much-treasured culture heritage, illustrating the transformation of traditional high culture into popular culture. The paper argues that the modern adaptations of the traditional poems of The Classic of Poetry combine both oral and written cultural heritage and reflects the interaction between ancient Chinese official literature and folk literature. The paper also explores the reasons why the folk songs of The Classic of Poetry are so popular in the area, including the influences of its author Yin Jifu, the impact of ancient diasporic culture from the political centre to remote rural areas, and the interactions of local cultures (famous as Chu culture) and Chinese mainstream cultural policies.

Keywords: high/low culture, The Classic of Poetry, the functions of media, cultural policy

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Authors: Sarre Nzaba, Bulelwa Ntsendwana, Bekkie Mamba, Alex Kuvarega

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The discharge of azo dyes such as Brilliant black (BB) into the water bodies has carcinogenic and mutagenic effects on humankind and the ecosystem. Conventional water treatment techniques fail to degrade these dyes completely thereby posing more problems. Advanced oxidation processes (AOPs) are promising technologies in solving the problem. Anatase type nitrogen-platinum (N, Pt) co-doped TiO₂ photocatalysts were prepared by a modified sol-gel method using amine terminated polyamidoamine generation 1 (PG1) as a template and source of nitrogen. The resultant photocatalysts were characterized by X‐ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X‐ray photoelectron spectroscopy (XPS), UV‐Vis diffuse reflectance spectroscopy, photoluminescence spectroscopy (PL), Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy (RS), thermal gravimetric analysis (TGA). The results showed that the calcination atmosphere played an important role in the morphology, crystal structure, spectral absorption, oxygen vacancy concentration, and visible light photocatalytic performance of the catalysts. Anatase phase particles ranging between 9- 20 nm were also confirmed by TEM, SEM, and analysis. The origin of the visible light photocatalytic activity was attributed to both the elemental N and Pd dopants and the existence of oxygen vacancies. Co-doping imparted a shift in the visible region of the solar spectrum. The visible light photocatalytic activity of the samples was investigated by monitoring the photocatalytic degradation of brilliant black dye. Co-doped TiO₂ showed greater photocatalytic brilliant black degradation efficiency compared to singly doped N-TiO₂ or Pd-TiO₂ under visible light irradiation. The highest reaction rate constant of 3.132 x 10-2 min⁻¹ was observed for N, Pd co-doped TiO₂ (2% Pd). The results demonstrated that the N, Pd co-doped TiO₂ (2% Pd) sample could completely degrade the dye in 3 h, while the commercial TiO₂ showed the lowest dye degradation efficiency (52.66%).

Keywords: brilliant black, Co-doped TiO₂, polyamidoamine generation 1 (PAMAM G1), photodegradation

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Authors: Sereen Itani

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As the world aspires for technological innovation, Innovative Robotics Technology-Supported Pedagogic Models in STEAM Education (Science, Technology, Engineering, Arts, and Mathematics) are critical in our global education system to build and enhance the next generation 21st century skills. Thus, diverse international schools endeavor in attempts to construct an integrated robotics and technology enhanced curriculum based on interdisciplinary subjects. Accordingly, it is vital that the globe remains resilient in STEAM fields by equipping the future learners and educators with Innovative Technology Experiences through robotics to support such fields. A variety of advanced teaching methods is employed to learn about Robotics Technology-integrated pedagogic models. Therefore, it is only when STEAM and innovations in Robotic Technology becomes integrated with real-world applications that transformational learning can occur. Robotics STEAM education implementation faces major challenges globally. Moreover, STEAM skills and concepts are communicated in separation from the real world. Instilling the passion for robotics and STEAM subjects and educators’ preparation could lead to the students’ majoring in such fields by acquiring enough knowledge to make vital contributions to the global STEAM industries. Thus, this necessitates the establishment of Pedagogic models such as Innovative Robotics Technologies to enhance STEAM education and develop students’ 21st-century skills. Moreover, an ICT innovative supported robotics classroom will help educators empower and assess students academically. Globally, the Robotics Design System and platforms are developing in schools and university labs creating a suitable environment for the robotics cross-discipline STEAM learning. Accordingly, the research aims at raising awareness about the importance of robotics design systems and methodologies of effective employment of robotics innovative technology-supported pedagogic models to enhance and develop (STEAM) education globally and enhance the next generation 21st century skills.

Keywords: education, robotics, STEAM (Science, Technology, Engineering, Arts and Mathematics Education), challenges

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Authors: Ezana Haddis Weldeghebrael

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Addis Ababa City Administration is engaged in a massive facelift of the inner-city. The paper, therefore, aims to analyze the challenges of the current urban regeneration effort by paying special attention to Lideta and Basha Wolde Chilot projects. To this end, the paper has adopted a documentary research strategy to collect the data and Institutionalist perspective as well as the concept of urban regeneration to analyze the data. The sources were selected based on relevance and recency. Academic research outputs were used primarily. However, where much scholastic publications are not available institutional reports, newspaper articles, and expert presentations were used. The major findings of the research revealed that although the second generation of urban redevelopment projects have attempted to involve affected groups and succeeded in designing better neighborhoods, they are riddled with three major drawbacks. The first one is institutional constraints, i.e. absence of urban redevelopment strategy as well as housing policy, broad definition of ‘public purpose’, little regard for informal businesses, limitation on rights groups, negotiation power not devolved at sub-city level and no plan for groups that cannot afford to pay the down payment for low-cost apartments. The second one is planning limitation, i.e. absence of genuine affected group participation as well as consultative level of public engagement. The third one is implementation failure, i.e. no regard to maintaining social bond, non-participatory and ill-informed resettlement, interference from senior government officials, failure to protect the poor from speculators, corruption and disregard to heritage buildings. Based on the findings, the paper concluded that the current inner-city redevelopment has failed to be socially sustainable and calls for enactment of housing policy as well as redevelopment strategy, affected group participation, on-site resettlement, empowering the Sub-city to manage the project and allowing housing rights groups to advocate for the poor slum dwellers.

Keywords: participation, redevelopment, planning, implementation, consultation

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Authors: Pauliasi Tony Fakahau

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This paper provides an overview of the impact of the revenue reform programme on vulnerable communities in the Kingdom of Tonga. Economic turmoil and mismanagement during the late 1990s forced the government to seek technical and financial assistance from the Asian Development Bank to undertake a comprehensive Economic and Public Sector Reform (EPSR) programme. The EPSR is a Western model recommended by donor agencies as the solution to Tonga’s economic challenges. The EPSR programme included public sector reform, private sector growth, and revenue generation. Tax reform was the main tool for revenue generation, which set out to strengthen tax compliance and administration as well as implement a value-added consumption tax. The EPSR is based on Western values and ideology but failed to recognise that Tongan cultural values are important to the local community. Two participant groups were interviewed. Participant group one consisted of 51 people representing vulnerable communities. Participant group two consisted of six people from the government and business sector who were from the elite of Tongan society. The Kakala Research Methodology provided the framework for the research, and the Talanoa Research Method was used to conduct semi-structured interviews in the homes of the first group and in the workplaces of the second group. The research found a heavy burden of the consumption tax on the purchasing power of participant group one (vulnerable participants), having an impact on nearly every financial transaction they made. Participant group ones’ main financial priorities were kavenga fakalotu (obligations to the church), kavenga fakafāmili (obligations to the family) and kavenga fakafonua (obligations to cultural events for the village, nobility, and royalty). The findings identified inequalities of the revenue reform, especially from consumption tax, for vulnerable people and communities compared to the elite of society. The research concluded that government and donor agencies need ameliorating policies to reduce the burden of tax on vulnerable groups more susceptible to the impact of revenue reform.

Keywords: tax reform, tonga vulnerable community revenue, revenue reform, public sector reform

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Authors: Elmira Solati, Atousa Mehrani, Davoud Dorranian

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Generation of ZnO-Au nanocomposite under laser irradiation of a mixture of the ZnO and Au colloidal suspensions are experimentally investigated. In this work, firstly ZnO and Au nanoparticles are prepared by pulsed laser ablation of the corresponding metals in water using the 1064 nm wavelength of Nd:YAG laser. In a second step, the produced ZnO and Au colloidal suspensions were mixed in different volumetric ratio and irradiated using the second harmonic of a Nd:YAG laser operating at 532 nm wavelength. The changes in the size of the nanostructure and optical properties of the ZnO-Au nanocomposite are studied as a function of the volumetric ratio of ZnO and Au colloidal suspensions. The crystalline structure of the ZnO-Au nanocomposites was analyzed by X-ray diffraction (XRD). The optical properties of the samples were examined at room temperature by a UV-Vis-NIR absorption spectrophotometer. Transmission electron microscopy (TEM) was done by placing a drop of the concentrated suspension on a carbon-coated copper grid. To further confirm the morphology of ZnO-Au nanocomposites, we performed Scanning electron microscopy (SEM) analysis. Room temperature photoluminescence (PL) of the ZnO-Au nanocomposites was measured to characterize the luminescence properties of the ZnO-Au nanocomposites. The ZnO-Au nanocomposites were characterized by Fourier transform infrared (FTIR) spectroscopy. The X-ray diffraction pattern shows that the ZnO-Au nanocomposites had the polycrystalline structure of Au. The behavior observed by images of transmission electron microscope reveals that soldering of Au and ZnO nanoparticles include their adhesion. The plasmon peak in ZnO-Au nanocomposites was red-shifted and broadened in comparison with pure Au nanoparticles. By using the Tauc’s equation, the band gap energy for ZnO-Au nanocomposites is calculated to be 3.15–3.27 eV. In this work, the formation of ZnO-Au nanocomposites shifts the FTIR peak of metal oxide bands to higher wavenumbers. PL spectra of the ZnO-Au nanocomposites show that several weak peaks in the ultraviolet region and several relatively strong peaks in the visible region. SEM image indicates that the morphology of ZnO-Au nanocomposites produced in water was spherical. The TEM images of ZnO-Au nanocomposites demonstrate that with increasing the volumetric ratio of Au colloidal suspension the adhesion increased. According to the size distribution graphs of ZnO-Au nanocomposites with increasing the volumetric ratio of Au colloidal suspension the amount of ZnO-Au nanocomposites with the smaller size is further.

Keywords: Au nanoparticles, pulsed laser ablation, ZnO-Au nanocomposites, ZnO nanoparticles

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Authors: Roza Dzierzak, Waldemar Wojcik, Piotr Kacejko

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Analysis of the texture of medical images consists of determining the parameters and characteristics of the examined tissue. The main goal is to assign the analyzed area to one of two basic groups: as a healthy tissue or a tissue with pathological changes. The CT images of the thoracic lumbar spine from 15 healthy patients and 15 with confirmed osteoporosis were used for the analysis. As a result, 120 samples with dimensions of 50x50 pixels were obtained. The set of features has been obtained based on the histogram, gradient, run-length matrix, co-occurrence matrix, autoregressive model, and Haar wavelet. As a result of the image analysis, 290 descriptors of textural features were obtained. The dimension of the space of features was reduced by the use of three selection methods: Fisher coefficient (FC), mutual information (MI), minimization of the classification error probability and average correlation coefficients between the chosen features minimization of classification error probability (POE) and average correlation coefficients (ACC). Each of them returned ten features occupying the initial place in the ranking devised according to its own coefficient. As a result of the Fisher coefficient and mutual information selections, the same features arranged in a different order were obtained. In both rankings, the 50% percentile (Perc.50%) was found in the first place. The next selected features come from the co-occurrence matrix. The sets of features selected in the selection process were evaluated using six classification tree methods. These were: decision stump (DS), Hoeffding tree (HT), logistic model trees (LMT), random forest (RF), random tree (RT) and reduced error pruning tree (REPT). In order to assess the accuracy of classifiers, the following parameters were used: overall classification accuracy (ACC), true positive rate (TPR, classification sensitivity), true negative rate (TNR, classification specificity), positive predictive value (PPV) and negative predictive value (NPV). Taking into account the classification results, it should be stated that the best results were obtained for the Hoeffding tree and logistic model trees classifiers, using the set of features selected by the POE + ACC method. In the case of the Hoeffding tree classifier, the highest values of three parameters were obtained: ACC = 90%, TPR = 93.3% and PPV = 93.3%. Additionally, the values of the other two parameters, i.e., TNR = 86.7% and NPV = 86.6% were close to the maximum values obtained for the LMT classifier. In the case of logistic model trees classifier, the same ACC value was obtained ACC=90% and the highest values for TNR=88.3% and NPV= 88.3%. The values of the other two parameters remained at a level close to the highest TPR = 91.7% and PPV = 91.6%. The results obtained in the experiment show that the use of classification trees is an effective method of classification of texture features. This allows identifying the conditions of the spongy tissue for healthy cases and those with the porosis.

Keywords: classification, feature selection, texture analysis, tree algorithms

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Authors: Zina Benouaret, Djamil Aissani

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In this work, we introduce the qualitative and quantitative concept of the strong stability method in the risk process modeling two lines of business of the same insurance company or an insurance and re-insurance companies that divide between them both claims and premiums with a certain proportion. The approach proposed is based on the identification of the ruin probability associate to the model considered, with a stationary distribution of a Markov random process called a reversed process. Our objective, after clarifying the condition and the perturbation domain of parameters, is to obtain the stability inequality of the ruin probability which is applied to estimate the approximation error of a model with disturbance parameters by the considered model. In the stability bound obtained, all constants are explicitly written.

Keywords: Markov chain, risk models, ruin probabilities, strong stability analysis

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Authors: Safee Chaudhary, Mahnoor Naseer Gondal, Hira Anees Awan, Abdul Rehman, Ammar Arif, Risham Hussain, Huma Khawar, Zainab Arshad, Muhammad Faizyab Ali Chaudhary, Waleed Ahmed, Muhammad Umer Sultan, Bibi Amina, Salaar Khan, Muhammad Moaz Ahmad, Osama Shiraz Shah, Hadia Hameed, Muhammad Farooq Ahmad Butt, Muhammad Ahmad, Sameer Ahmed, Fayyaz Ahmed, Omer Ishaq, Waqar Nabi, Wim Vanderbauwhede, Bilal Wajid, Huma Shehwana, Muhammad Tariq, Amir Faisal

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Cancer is a manifestation of multifactorial deregulations in biomolecular pathways. These deregulations arise from the complex multi-scale interplay between cellular and extracellular factors. Such multifactorial aberrations at gene, protein, and extracellular scales need to be investigated systematically towards decoding the underlying mechanisms and orchestrating therapeutic interventions for patient treatment. In this work, we propose ‘TISON’, a next-generation web-based multiscale modeling platform for clinical systems oncology. TISON’s unique modeling abstraction allows a seamless coupling of information from biomolecular networks, cell decision circuits, extra-cellular environments, and tissue geometries. The platform can undertake multiscale sensitivity analysis towards in silico biomarker identification and drug evaluation on cellular phenotypes in user-defined tissue geometries. Furthermore, integration of cancer expression databases such as The Cancer Genome Atlas (TCGA) and Human Proteome Atlas (HPA) facilitates in the development of personalized therapeutics. TISON is the next-evolution of multiscale cancer modeling and simulation platforms and provides a ‘zero-code’ model development, simulation, and analysis environment for application in clinical settings.

Keywords: systems oncology, cancer systems biology, cancer therapeutics, personalized therapeutics, cancer modelling

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Authors: Said Baadel

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The belief of a heavenly God is enshrined to all Abrahamic religions which form the three major religions of the world today. Muslims believe in Allah who is above the seven heavens. The youth in the United Arab Emirates (UAE) study Islamic courses as part of their high school curriculum and are required to take at least one Islamic course at the university level to gain credit hours towards their general education (GENED). This paper provides an insight of what the youth studying in the UAE think of where Allah was. Our analysis reveals that a big number of Muslim youth were not sure, especially those from the Middle Eastern and Arab countries bringing to the conclusion that this subject needs to be revisited again in the course work.

Keywords: Allah, Islam, Tawheed, religion

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Authors: Lydia Foucan, Laurent Larifla, Emmanuelle Durand, Christine Rambhojan, Veronique Dhennin, Jean-Marc Lacorte, Philippe Froguel, Amelie Bonnefond

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In the population of Guadeloupe Island (472,124 inhabitants and 80% of subjects of African descent), overweight and obesity were estimated at 23% and 9% respectively among children. High prevalence of diabetes has been reported (~10%) in the adult population. Nevertheless, no study has investigated the contribution of gene mutations to childhood obesity in this population. We aimed to investigate rare genetic mutations in genes involved in monogenic obesity or diabetes in obese Afro-Caribbean children from Guadeloupe Island using next-generation sequencing. The present investigation included unrelated obese children, from a previous study on overweight conducted in Guadeloupe Island in 2013. We sequenced coding regions of 59 genes involved in monogenic obesity or diabetes. A total of 25 obese schoolchildren (with Z-score of body mass index [BMI]: 2.0 to 2.8) were screened for rare mutations (non-synonymous, splice-site, or insertion/deletion) in 59 genes. Mean age of the study population was 12.4 ± 1.1 years. Seventeen children (68%) had insulin-resistance (HOMA-IR > 3.16). A family history of obesity (mother or father) was observed in eight children and three of the accompanying parent presented with type 2 diabetes. None of the children had gonadotrophic abnormality or mental retardation. We detected five rare heterozygous mutations, in four genes involved in monogenic obesity, in five different obese children: MC4R p.Ile301Thr and SIM1 p.Val326Thrfs*43 mutations which were pathogenic; SIM1 p.Ser343Pro and SH2B1 p.Pro90His mutations which were likely pathogenic; and NTRK2 p.Leu140Phe that was of uncertain significance. In parallel, we identified seven carriers of mutation in ABCC8 or KCNJ11 (involved in monogenic diabetes), which were of uncertain significance (KCNJ11 p.Val13Met, KCNJ11 p.Val151Met, ABCC8 p.Lys1521Asn and ABCC8 p.Ala625Val). Rare pathogenic or likely pathogenic mutations, linked to severe obesity were detected in more than 15% of this Afro-Caribbean population at high risk of obesity and type 2 diabetes.

Keywords: childhood obesity, MC4R, monogenic obesity, SIM1

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Authors: Henda Gnakate Biba, Ndassa Mouafon Issa

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Dictionaries modeled on the Western model [tonic accent languages] are not suitable and do not account for tonal languages phonologically, which is why the [prosodic and phonological] ethnographic dictionary was designed. It is a glossary that expresses the tones and the rhythm of words. It recreates exactly the speaking or singing of a tonal language, and allows the non-speaker of this language to pronounce the words as if they were a native. It is a dictionary adapted to tonal languages. It was built from ethnomusicological theorems and phonological processes, according to Jean. J. Rousseau 1776 hypothesis /To say and to sing were once the same thing/. Each word in the French dictionary finds its corresponding language, ekaη. And each word ekaη is written on a musical staff. This ethnographic dictionary is also an inventive, original and innovative research thesis, but it is also an inventive, original and innovative research thesis. A contribution to the theoretical, musicological, ethno musicological and linguistic conceptualization of languages, giving rise to the practice of interlocution between the social and cognitive sciences, the activities of artistic creation and the question of modeling in the human sciences: mathematics, computer science, translation automation and artificial intelligence. When you apply this theory to any text of a folksong of a world-tone language, you do not only piece together the exact melody, rhythm, and harmonies of that song as if you knew it in advance but also the exact speaking of this language. The author believes that the issue of the disappearance of tonal languages and their preservation has been structurally resolved, as well as one of the greatest cultural equations related to the composition and creation of tonal, polytonal and random music. The experimentation confirming the theorization designed a semi-digital, semi-analog application which translates the tonal languages of Africa (about 2,100 languages) into blues, jazz, world music, polyphonic music, tonal and anatonal music and deterministic and random music). To test this application, I use a music reading and writing software that allows me to collect the data extracted from my mother tongue, which is already modeled in the musical staves saved in the ethnographic (semiotic) dictionary for automatic translation ( volume 2 of the book). Translation is done (from writing to writing, from writing to speech and from writing to music). Mode of operation: you type a text on your computer, a structured song (chorus-verse), and you command the machine a melody of blues, jazz and, world music or, variety etc. The software runs, giving you the option to choose harmonies, and then you select your melody.

Keywords: music, language, entenglement, science, research

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