The current and the next issues of “Spazio Filosofico”, both devoted to Festival (Festival I and II respectively), are dedicated to Ugo Perone on the occasion of his 70th birthday. Perone’s friends and colleagues have chosen to celebrate his birthday in a philosophical way, namely, with a reflection on the concept of festival/holiday [festa] and its meaning for us today. Thrifty spirits might object that a journal issue is like a gift – one is enough. Are these not times of (...) economic crisis? There is no real festival, however, without a Zugabe: without an addition, an encore, or a supplement. Hence, two issues, both devoted to a single concept. The choice of the theme has not been accidental – the concept of “festival/holiday” plays in fact an important role in Perone’s thought. In an essay that is often quoted in various contributions to the two issues, Perone understands the pair of concepts “ultimate/penultimate,” which has been discussed by Dietrich Bonhoeffer, in terms of “holidays/everydayness.” For Bonhoeffer, God is present not where human abilities fail but rather “at the center of the village.” Likewise, for Perone, the square, which is the “symbol for the holiday time,” is the center of town. It is even, “at the same time, the center of town and its interruption.” . (shrink)

Short introduction to the V2 publication of "The War of Appearances: Transparency, Opacity, Radiance" (2016). An anthology with Matteo Pasquinelli, Luciana Parisi, Graham Harman, Tomas Saraceno, René ten Bos, Tim Morton, McKenzie Wark, Wim Delvoye, Diana Scherer, Paolo Cirio, Paul Frissen, and Willem Schinkel.

Short introduction to the V2 publication of "The War of Appearances: Transparency, Opacity, Radiance" (2016). An anthology with Matteo Pasquinelli, Luciana Parisi, Graham Harman, Tomas Saraceno, René ten Bos, Tim Morton, McKenzie Wark, Wim Delvoye, Diana Scherer, Paolo Cirio, Paul Frissen, and Willem Schinkel.

Short introduction to the V2 publication of "The War of Appearances: Transparency, Opacity, Radiance" (2016). An anthology with Matteo Pasquinelli, Luciana Parisi, Graham Harman, Tomas Saraceno, René ten Bos, Tim Morton, McKenzie Wark, Wim Delvoye, Diana Scherer, Paolo Cirio, Paul Frissen, and Willem Schinkel.

“There is a long tradition in Latin American debates that is not well known in Europe and the United States…” (p. 89). This sentence, almost read in passing in the middle of the book in relation to two different conceptions of the nation, can be said to summarize the main spirit behind Biglieri and Cadahia’s populist actualization of Mariátegui’s classic, Seven Interpretative Essays on Peruvian Reality (1928). In this case, the book we have in our hands is difficult to define (...) or classify. Clearly, it is not a purely “academic” enterprise –as the very authors disclaim in the first lines of their Introduction (p. xxii). It has no full presumption of “objectivity” or “neutrality” because it takes a self-reflected partisan point of view. Conversely, it is not a “manifesto” either, since it engages deeply in theoretical debates after rigorously reviewing the existing literature. Perhaps the best way to define these Essays on Populism is finding rescue in Althusser’s notion of “theoretical intervention”, and Biglieri and Cadahia develop a total of seven placing “populism” in relation to different conjunctures: its own methodology (empirical or ontological), the Left/Right imaginary, neoliberal fascism, (plebeian) Republicanism, (inter)nationalism and feminism. However, the result is not a concatenation of isolated “papers”, but a constellation illuminated by a similar light, which I take it to be no other than the laudable attempt to bring to the fore a series of militant experiences, philosophical theses and heated debates with Latin American autonomists and Spanish republicans which are not always well known in the English-speaking literature, despite they have the power to dislocate the question around populism. (shrink)

Resumen: Los trabajos abordan, desde diferentes perspectivas a la categoría de sujeto como una categoría crucial del pensamiento contemporáneo. El ámbito de preocupaciones es amplio: la perspectiva del filósofo norteamericano S Cavell quien hace una originalísima recepción de la herencia de Austin y Wittgenstein; la perspectiva fenomenológica de Sartre en diálogo y conflicto con la del psicoanálisis lacaniano y las reconceptualizaciones de la ideología realizadas por Louis Althusser; la constitución del sujeto en tensión entre la sujeción al poder y las (...) posibilidadesde resistencia según la perspectiva de Judith Butler; una relectura de la implicación de estructura y sujeto en la perspectiva estructural abierta por Saussure y continuada por Lévi-Strauss, Benveniste y Lacan, tema que recibe un tratamiento circunscripto al pensamiento del argentino Ernesto Laclau, en el que se distinguen distintas etapas; las implicaciones que los eventos fundamentales de la historia del siglo XX acarrean para una conceptualización de la subjetividad en la perspectiva de Theodor Adorno y las limitaciones que la conceptualización de la obra de arte como juego en la obra de Gadamer impone a la concepción moderna de la subjetividad. -/- Índice: Presentación del compilador La crítica de Heidegger a la noción de sujeto: un análisis a partir de la incidencia de su reflexión sobre la técnica y el lenguaje, Luciana Carrera Aizpitarte El juego como auto-representación y modo de ser de la obra de arte en la estética hermenéutica de Gadamer, Paola Belén El yo sobre la línea de ficción: análisis de las concepciones de Sartre y Lacan, Luisina Bolla El poder y el sujeto. Sujeción, norma y resistencia en Judith Butler, Matías Abeijón Theodor W. Adorno: la crítica al sujeto después de Auschwitz, Gustavo Robles Estructura, discurso y subjetividad, Pedro Karczmarczyk Transformaciones, rupturas y continuidades entre la perspectiva de Ernesto Laclau y la tradición (post)estructuralista, Hernán Fair La recuperación del sujeto: escepticismo, autoconocimiento y escritura en S. Cavell, Guadalupe Reinoso . (shrink)

RELAÇÃO E EFEITOS BIOQUÍMICO-NUTRICIONAIS SOBRE OS TRANSTORNOS DO CICLO ESTRAL DE VACAS -/- Emanuel Isaque Cordeiro da Silva Departamento de Agropecuária – IFPE Campus Belo Jardim [email protected] ou [email protected] WhatsApp: (82)98143-8399 -/- •__6. Transtornos do ciclo estral -/- Qualquer alteração na frequência, duração ou intensidade do ciclo estral é considerada uma perturbação do ciclo, cujas origens variam etiologicamente. As perturbações do ciclo podem originar-se em qualquer das partes do eixo hipotálamo-hipófise-ovário (FRAZER, 2005; GORDON, 1996). Pode ou não ser do tipo (...) permanente e pode depender de sua origem, momento e intensidade cursar com outras alterações reprodutivas, por exemplo uma retenção do corpo lúteo, dá lugar a prolongamento da fase lútea, altos níveis de progesterona circulante e pode, finalmente, desencadear em um cisto luteal ou em uma metrite. Entre os fatores desencadeadores da falha do ciclo estral estão os fatores de origem nutricional, dentre eles: 6.1 Minerais 6.1.1 Relação Na:K (Sódio: Potássio) A deficiência de sódio pode causar distúrbios do ciclo estral, isto porque as células animais intracelularmente possuem uma alta concentração de K e uma baixa concentração de Na, esta relação pode chegar a 10:1 ou mais, em relação ao meio externo. Com esta relação, as concentrações intracelulares estão em equilíbrio com o meio externo. A absorção e secreção de cátions pela célula para conseguir o equilíbrio é simultânea, gerada por um sistema de transporte específico chamado "bomba Na-K". Se a nível celular não existe um balanço iônico de K:Na, a maior prioridade das células tubulares do rim é a de conseguir novamente um equilíbrio, o mecanismo destas células é o da reabsorção do íon que se encontre em excesso de água, diminuindo a quantidade deste no líquido para manter as funções em equilíbrio dinâmico. Os desequilíbrios não compensados a nível celular ou renal, levam a alterações na condutividade nervosa por alteração da bomba de transmissão elétrica. O ciclo estral é alterado por diminuir a expressividade dos sinais comportamentais de estro, que são produzidos por concentrações crescentes de estrogênio mas com alta necessidade de adequação nervosa para a exposição corporal do cio e a aceitação da monta. O potássio, em particular, desempenha um papel fundamental como coator em certas interações enzimáticas, incluindo a transferência de energia, a síntese de proteínas e o metabolismo de hidratos de carbono, em especial nos sistemas em que o ADP está envolvido, as hexoquinases e a anidrase carbônica. O sódio, por sua vez, é o principal cátion extracelular, regula o equilíbrio hídrico no organismo e a mecânica de fluidos, desta forma regula a pressão osmótica e a troca aquosa nos tecidos. Devido a esta função, um dos fatores importantes do fluxo Na:K é o rim, que é controlado pela aldosterona, a principal hormona reguladora da absorção de sódio e excreção de potássio. Qualquer desequilíbrio na relação Na:K, afetará o ciclo estral, de maneira direta e indireta, através da alteração na síntese de proteínas e da perda da regulação hídrica, fator importante pelas secreções que devem acompanhar as manifestações de cio/estro. 6.1.2 Relação Cobalto (Co) A deficiência de cobalto gera um efeito biológico determinado pela sua presença na molécula da vitamina B12, a qual regula a hematopoese (Ativa a síntese de protoporfirina) e afeta o metabolismo do nitrogênio e dos carboidratos. A vitamina B12 atua como uma coenzima da transmetilação (síntese do glutamato mutase, metilmalonil-CoA-Mutase, diol-dehidratase e redução dos ribonucleótidos a desoxirribonucleótidos, isomerização da a-lisina, etc.). Especialmente em ruminantes, a reação mutase da metilmalonina-CoA está relacionada com o metabolismo do ácido propiônico e, portanto, com a síntese de glicose e o equilíbrio energético. O cobalto também está envolvido na carboxilação da propionil-CoA à metilmalonil-CoA e na isomerização deste último para succinil-CoA. O metabolismo do ácido propiônico ocorre no fígado e é reduzido pelo fato do metilmalonil não poder ser convertido em succinil-CoA, impedindo a sua passagem para oxalacetato e glicose, gerando uma relação inversa entre os níveis de energia e proteína; causando uma diminuição de GnRH que afeta negativamente a liberação de LH que, por sua vez, cria um aumento na FSH. Isso produz uma anulação da ovulação e, consequentemente, ausência de um ciclo estral verdadeiro. Vale reforçar que, para prevenção da deficiência do cobalto, o criador pode optar pelo fornecimento de volumosos que dispõem de quantidades de cobalto que suprem as exigências dos animais, ou pela inserção de sais de cobalto à mistura da ração, sempre no intervalo sugerido de 0,07 e 0,11 mg/kg para cada animal, suprindo a necessidade do mesmo e garantindo assim a prevenção dos transtornos do ciclo estral ou outras afecções do sistema reprodutivo. 6.1.3 Relação Cobre (Cu) e Molibdênio (Mo) A deficiência de cobre gera, indiretamente, molibdênio, durante esse processo, tanto o macho como a fêmea são inférteis ou sub-férteis, mas, em geral, os transtornos surgem não por molibdeniose mas por hipocuprose condicionada por excesso de molibdênio nas pastagens e pelos sulfatos presentes na água de bebida (BREM, 2016). Isso leva à formação de tiomolibdato no rúmen, que por sua vez combina com o cobre para formar tiomolibdato de cobre, sal muito insolúvel. O tiomolibdato presente, formado em excesso e que não encontra cobre suficiente, contribuirá para produzir a diarreia, limitando ainda mais a absorção de cobre. A interferência mais importante do molibdênio ocorre no processo metabólico do cobre, interferindo sua atividade enzimática. O molibdênio atua sobre o complexo sulfeto-oxidase hepático. A enzima que está envolvida na oxidação de metabolitos sulfurados, reduz a sua atividade na presença de altos teores de molibdênio, especialmente quando a quantidade de cobre é baixa. Daqui resulta a formação de sulfureto de cobre, muito insolúvel e, portanto, pouco ou nada utilizável pelas células e/ou tecidos (QUIROZ-ROCHA & BOUDA, 2001). O excesso de molibdênio nas pastagens ou na água de bebida reduz a quantidade de cobre no fígado, mas para uma dada dose de molibdênio, esta redução é diretamente proporcional ao aumento dos sulfatos na ingestão, porque só na presença de sulfatos o molibdênio exerce sua ação limitante. O melhor modo de tratar o molibdênio e a ação dos sulfatos sobre o cobre, é aumentar a quantidade de cobre disponível pelos animais, seja por via bucal ou parenteral. Desta forma, há aumentos na cupremia e no ganho de peso. É conveniente, para o efeito, efetuar um controle dos resultados mediante a observação clínica, pesagem dos animais e análise de cobre no sangue. Isso permitirá estabelecer as doses ideais e adequadas para cada estabelecimento e efetuar um estudo econômico da suplementação (BAVERA, 2002). Como já foi tratado o requerimento do cobre para evitar os problemas reprodutivos das vacas, falemos do molibdênio (Mo). O Mo é um elemento primordial para bovinos leiteiros, uma vez que é componente de uma enzima presente no leite (xantina oxidasse). A deficiência de Mo a nível prático não foi relatada, porém casos podem acontecer. Para ovinos, que é uma espécie ruminante, a concentração exigida pelo animal em Mo presente na MS é de 5 a 10 mg/kg, porém deve levar em consideração a relação crítica entre o Mo e o Cu que deve ser no máximo 20 e nunca superior. O nível crítico de toxidade de Mo nos alimentos volumosos (forrageiras, gramíneas e leguminosas) não pode ultrapassar os 6% por kg de MS. Através de todos esses cuidados, o criador poderá obter sucesso tanto na prevenção contra os distúrbios do ciclo estral das vacas, quanto de outras complicações como toxidade, desnutrição, etc. 6.2 Relação energia:proteína Em relação ao aumento do consumo de proteína crua ou de deficiência de energia, aumenta-se a quantidade de ureia no sangue e produz-se uma toxicidade tecidular, afetando o endométrio e diminuindo a produção de prostaglandinas, que são as encarregadas de manter o corpo lúteo, caso não se mantenha acaba provocando um ciclo estral longo. A situação pode ser explicada a nível do eixo hipotálamo-hipófise, no qual os baixos níveis de glicose inibem a secreção de GnRH e resultam na diminuição da pulsatilidade da LH, seja por ação direta ou mediada através das ß-endorfinas. Outro fator que afeta o crescimento folicular é a nutrição, especificamente a perda da condição corporal, quando o animal não se alimenta direito ou quando se alimenta não tem uma condição balanceada que supra suas exigências nutricionais e que tenha um aceitável ganho de peso diário (GPD), acaba perdendo massa muscular ou de gordura, em outras palavras altera-se a condição corporal do mesmo, e se a perda for de 22 a 24 % de peso corporal (PC), os animais que perdem essa condição entram em anestro o que acaba tornando um animal inviável para a reprodução e também para o abate, uma vez que encontra-se fora do peso ideal. Tanto as proteínas quanto a energia foram tratados em trabalhos anteriores, porém nunca é tarde para salientar que ambas devem ser fornecidas em qualidade e quantidade que consiga favorecer ao desenvolvimento do animal e aos mecanismos fisiológicos do mesmo. 6.3 Fito-toxidade Finalmente, um fator adicional que induz a alteração da ciclicidade estral são os fitoestrógenos, plantas com altos teores de isoflavonas que possuem, no organismo animal, uma ação estrogênica. Os fitoestrógenos estão amplamente difundidos, nos trevos, alfafa, milho e nas pastagens de cultivo intensivo. Os fitoestrogênios são diferentes dos estrogênios produzidos pelo animal, mas a sua ação é idêntica nos receptores do trato reprodutivo; o seu metabolismo e excreção é diferente (por exemplo, desmetilização) e a sua excreção renal através dos glicoronosidos, assim mesmo a formação de ésteres sulfatos no tecido hepático é menor, acumulando-se em circulação e alterando a duração da fase estrogênica do ciclo, isso leva à ninfomania das vacas e com ela a perda da função reprodutiva. Deve-se estar atento ao pasto que se cultiva e ao solo em que se implanta o pasto, uma vez que o solo pode ter excessos de minerais prejudiciais ao animal e que o coloque em uma situação de toxidade, já que a planta absorve do solo o excesso e da planta vai para o animal por meio direto ou pela silagem. Um exemplo é o teor de molibdênio na planta que não pode ser maior que 6%, se for ocorrerá inúmeras transformações fisiológicas maléficas ao animal, que acabará sendo descartado do objetivo que seria a reprodução na fazenda. -/- Apoio -/- Realização -/- REFERÊNCIAS BIBLIOGRÁFICAS BAVERA, Guillermo Alejandro. Aguas y aguadas para el ganado. Rio Cuarto: Inter-Medica Editorial, 2009. BERCHIELLI, Telma Teresinha; PIRES, Alexandre Vaz; OLIVEIRA, SG de. Nutrição de ruminantes. Jaboticabal: funep, 2006. BINDARI, Yugal Raj et al. Effects of nutrition on reproduction-A review. Adv. Appl. Sci. Res, v. 4, n. 1, p. 421-429, 2013. BOLAND, M. P. Efectos nutricionales en la reproducción del ganado. XXXI Jornadas Uruguayas de Buiatría, 2003. BREM, J. J. et al. Alteraciones del ciclo estral provocadas por un alto ingreso de molibdeno en vaquillonas Brangus y respuesta a la suplementación con cobre. Revista Veterinaria, v. 12, n. 1 y 2, p. 28-33, 2016. DEHNING, R. Interrelaciones entre nutrición y fertilidad. In: Curso Manejo de la Fertilidad Bovina18-23 May 1987Medellín (Colombia). CICADEP, Bogotá (Colombia) Universidad de La Salle, Medellín (Colombia) Instituto Colombiano Agropecurio, Bogotá (Colombia) Sociedad Alemana de Cooperación Técnica-GTZ (Alemania), 1987. DE LUCA, Leonardo J. Nutrición y fertilidad en el ganado lechero. XXXVI Jornadas Uruguayas de Buiatría, 2008. FRAZER, Grant S. Bovine theriogenology. Veterinary Clinics: Food Animal Practice, v. 21, n. 2, p. xiii-xiv, 2005. GORDON, Ian. Controlled reproduction in farm animals series. Nova Iorque: CAB International, 1996. GRAHAM, Thomas W. Trace element deficiencies in cattle. Veterinary clinics of North America: food animal practice, v. 7, n. 1, p. 153-215, 1991. GUEDES, Luciana Freitas et al. A importância do cobre, molibdênio e enxofre na alimentação de ovinos. Nucleus Animalium, v. 10, n. 2, p. 7-22, 2018. HURLEY, W. L.; DOANE, R. M. Recent developments in the roles of vitamins and minerals in reproduction. Journal of Dairy Science, v. 72, n. 3, p. 784-804, 1989. KUMAR, Sudhir et al. Importance of micro minerals in reproductive performance of livestock. Veterinary world, v. 4, n. 5, p. 230, 2011. MAAS, John. Relationship between nutrition and reproduction in beef cattle. The Veterinary Clinics of North America. Food Animal Practice, v. 3, n. 3, p. 633-646, 1987. MILLS, C. F. Cobalt deficiency and cobalt requirements of ruminants. Recent advances in animal nutrition, p. 129-141, 1981. NICODEMO, M. L. F.; SERENO, J. R. B.; AMARAL, T. B. Minerais na eficiência reprodutiva de bovinos. Embrapa Pecuária Sudeste-Documentos (INFOTECA-E), São Carlos, 2008. PASA, Camila. Relação reprodução animal e os minerais. Biodiversidade, v. 9, n. 1, 2011. QUIROZ-ROCHA, Gerardo F.; BOUDA, Jan. Fisiopatología de las deficiencias de cobre en rumiantes y su diagnóstico. Vet. Méx, v. 32, n. 4, p. 289, 2001. SHORT, Robert E.; ADAMS, D. C. Nutritional and hormonal interrelationships in beef cattle reproduction. Canadian Journal of Animal Science, v. 68, n. 1, p. 29-39, 1988. YASOTHAI, R. Importance of minerals on reproduction in dairy cattle. International Journal of Science, Environment and Technology, v. 3, n. 6, p. 2051-2057, 2014. Emanuel Isaque Cordeiro da Silva Belo Jardim, 29 de março de 2020. (shrink)

It is crucial to actively detect the risks of transactions in a financial company to improve customer experience and minimize financial loss. In this study, we compare different machine learning algorithms to effectively and efficiently predict the legitimacy of financial transactions. The algorithms used in this study were: MLP Repressor, Random Forest Classifier, Complement NB, MLP Classifier, Gaussian NB, Bernoulli NB, LGBM Classifier, Ada Boost Classifier, K Neighbors Classifier, Logistic Regression, Bagging Classifier, Decision Tree Classifier and Deep Learning. The dataset (...) was collected from Kaggle depository. It consists of 6362620 rows and 10 columns. The best classifier with unbalanced dataset was the Random Forest Classifier. The Accuracy 99.97%, precession 99.96%, Recall 99.97% and the F1-score 99.96%. However, the best classifier with balanced dataset was the Bagging Classifier. The Accuracy 99.96%, precession 99.95%, Recall 99.98% and the F1-score 99.96%. (shrink)

Artificial intelligence (AI), deep learning, machine learning and neural networks represent extremely exciting and powerful machine learning-based techniques used to solve many real-world problems. Artificial intelligence is the branch of computer sciences that emphasizes the development of intelligent machines, thinking and working like humans. For example, recognition, problem-solving, learning, visual perception, decision-making and planning. Deep learning is a subset of machine learning in artificial intelligence that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Deep learning (...) is a technique used to generate face detection and recognize it for real or fake by using profile images and determine the differences between them. In this study, we used deep learning techniques to generate models for Real and Fake face detection. The goal is determining a suitable way to detect real and fake faces. The model was designed and implemented, including both Dataset of images: Real and Fake faces detection through the use of Deep learning algorithms based on neural networks. We have trained dataset which consists of 9,000 images for total in 150 epochs, and got the ResNet50 model to be the best model of network architectures used with 100% training accuracy, 99.18% validation accuracy, training loss 0.0003, validation loss 0.0265, and testing accuracy 99%. (shrink)

Essa pesquisa elege como material específico de análise uma sequência de cursos oferecidos pelo “YouTube Academy” para a criação, gerenciamento e divulgação de uma empresa associada à plataforma de vídeos do YouTube. O objetivo é investigar os modos de imbricação e/ou separação entre o sujeito e a empresa. Para construir os procedimentos analíticos, delimitamos as seguintes perguntas: Como as formas imaginárias do sujeito (o “eu”, a identidade e a individualidade) estão relacionadas com a criação e o funcionamento de uma empresa (...) no YouTube? Como o trabalho e as relações de trabalho são significados nessa discursividade? A pesquisa é filiada à Análise de Discurso Materialista, em diálogo com autores que analisam as relações de trabalho contemporâneas. O olhar discursivo chega a três regularidades: 1) homogeneização das diferentes condições de produção no trabalho dos youtubers; 2) o paralelismo discursivo entre sujeito, canal e empresa (negócio); 3) uma retórica do equilíbrio entre “vida profissional” e “vida pessoal”. O material se sustenta no funcionamento de uma busca pela saturação dos sentidos com soluções e cursos para cada uma das etapas da (re)produção desse trabalho, para a suposta totalidade do processo. The specific analysis material for this essay was chosen from a sequence of courses, offered by the “YouTube Academy”, with the aim of creating, managing and announcing a company associated with the YouTube video platform. Its goal is to examine the ways of imbrication and/or separation between the subject and the company. In order to build the analytical procedures, we delineated the following questions: How are the imaginary for ms of the subject (the “self” as identity and individuality) related to the creation and operation of a company on YouTube? How are work and work relations meant in this discursivity? The research is affiliated with Materialist Discourse Analysis, in dialogue with authors who analyze contemporary work relations. The discursive look reaches three regularities: 1) homogenization of the different production conditions in the work of “youtubers”; 2) the discursive parallelism between subject, channel and company (busi-ness); 3) a rhetoric of the balance between “professional life” and “personal life”. The material is based on the operation of a search for the saturation of the senses with solutions and courses for each of the stages of the (re)production of this work, for the supposed totality of the process. (shrink)

Abstract: Heart diseases are increasing daily at a rapid rate and it is alarming and vital to predict heart diseases early. The diagnosis of heart diseases is a challenging task i.e. it must be done accurately and proficiently. The aim of this study is to determine which patient is more likely to have heart disease based on a number of medical features. We organized a heart disease prediction model to identify whether the person is likely to be diagnosed with a (...) heart disease or not using the medical features of the person. We used many different algorithms of machine learning such as Gaussian Mixture, Nearest Centroid, MultinomialNB, Logistic RegressionCV, Linear SVC, Linear Discriminant Analysis, SGD Classifier, Extra Tree Classifier, Calibrated ClassifierCV, Quadratic Discriminant Analysis, GaussianNB, Random Forest Classifier, ComplementNB, MLP Classifier, BernoulliNB, Bagging Classifier, LGBM Classifier, Ada Boost Classifier, K Neighbors Classifier, Logistic Regression, Gradient Boosting Classifier, Decision Tree Classifier, and Deep Learning to predict and classify the patient with heart disease. A quite helpful approach was used to regulate how the model can be used to improve the accuracy of prediction of heart diseases in any person. The strength of the proposed model was very satisfying and was able to predict evidence of having a heart disease in a particular person by using Deep Learning and Random Forest Classifier which showed a good accuracy in comparison to the other used classifiers. The proposed heart disease prediction model will enhances medical care and reduces the cost. This study gives us significant knowledge that can help us predict the person with heart disease. The dataset was collected from Kaggle depository and the model is implemented using python. (shrink)

Abstract: Sarcasm is commonly used in news and detecting sarcasm in headline news is challenging for humans and thus for computers. The media regularly seem to engage sarcasm in their news headline to get the attention of people. However, people find it tough to detect the sarcasm in the headline news, hence receiving a mistaken idea about that specific news and additionally spreading it to their friends, colleagues, etc. Consequently, an intelligent system that is able to distinguish between can sarcasm (...) none sarcasm automatically is very important. The aim of the study is to build a sarcasm model that detect headline news using machine and deep learning and attempt to understand how a computer learns the patterns of sarcasm. The dataset used in this study was collected from Kaggle depository. We examined 21 algorithms of machine learning and one deep learning algorithm for detecting sarcasm in headline news. The evaluation metric used in this study are Accuracy, F1-measure, Recall, Precision, and Time needed for training and evaluation. The deep learning model achieved accuracy (95.27%), recall (96.62%), precision (94.15%), F1-score (95.37%) and time needed to train the mode (400 seconds), with loss of around 0.3398. However, the algorithm of machine learning that achieved the highest F1-Score is Passive Aggressive Classifier. It was the top classier for sarcasm detection among the machine learning algorithms with accuracy (95.50%), recall (96.09 %), precision (94.30%), F1-score (95.19%) and time needed to train the mode (0.31 seconds). (shrink)

Abstract: Sarcasm is commonly used in news and detecting sarcasm in headline news is challenging for humans and thus for computers. The media regularly seem to engage sarcasm in their news headline to get the attention of people. However, people find it tough to detect the sarcasm in the headline news, hence receiving a mistaken idea about that specific news and additionally spreading it to their friends, colleagues, etc. Consequently, an intelligent system that is able to distinguish between can sarcasm (...) none sarcasm automatically is very important. The aim of the study is to build a sarcasm model that detect headline news using machine and deep learning and attempt to understand how a computer learns the patterns of sarcasm. The dataset used in this study was collected from Kaggle depository. We examined 21 algorithms of machine learning and one deep learning algorithm for detecting sarcasm in headline news. The evaluation metric used in this study are Accuracy, F1-measure, Recall, Precision, and Time needed for training and evaluation. The deep learning model achieved accuracy (95.27%), recall (96.62%), precision (94.15%), F1-score (95.37%) and time needed to train the mode (400 seconds), with loss of around 0.3398. However, the algorithm of machine learning that achieved the highest F1-Score is Passive Aggressive Classifier. It was the top classier for sarcasm detection among the machine learning algorithms with accuracy (95.50%), recall (96.09 %), precision (94.30%), F1-score (95.19%) and time needed to train the mode (0.31 seconds). (shrink)

Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and react like humans. Some of the activities computers with artificial intelligence are designed for include, Speech, recognition, Learning, Planning and Problem solving. Deep learning is a collection of algorithms used in machine learning, It is part of a broad family of methods used for machine learning that are based on learning representations of data. Deep learning is a technique used (...) to produce Pneumonia detection and classification models using x-ray imaging for rapid and easy detection and identification of pneumonia. In this thesis, we review ways and mechanisms to use deep learning techniques to produce a model for Pneumonia detection. The goal is find a good and effective way to detect pneumonia based on X-rays to help the chest doctor in decision-making easily and accuracy and speed. The model will be designed and implemented, including both Dataset of image and Pneumonia detection through the use of Deep learning algorithms based on neural networks. The test and evaluation will be applied to a range of chest x-ray images and the results will be presented in detail and discussed. This thesis uses deep learning to detect pneumonia and its classification. (shrink)

Abstract: Fruits are a rich source of energy, minerals and vitamins. They also contain fiber. There are many fruits types such as: Apple and pears, Citrus, Stone fruit, Tropical and exotic, Berries, Melons, Tomatoes and avocado. Classification of fruits can be used in many applications, whether industrial or in agriculture or services, for example, it can help the cashier in the hyper mall to determine the price and type of fruit and also may help some people to determining whether a (...) certain type of fruit meets their nutritional requirement. In this paper, machine learning based approach is presented for classifying and identifying 10 different fruit with a dataset that contains 6847 images use 4793 images for training, 1027 images for validation and 1027 images for testing. A deep learning technique that extensively applied to image recognition was used. We used 70% from image for training and 15% from image for validation 15% for testing. Our trained model achieved an accuracy of 100% on a held-out test set, demonstrating the feasibility of this approach. (shrink)

In computer science, Artificial Intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Deep Learning is a new field of research. One of the branches of Artificial Intelligence Science deals with the creation of theories and algorithms that (...) allow the machine to learn by simulating neurons in the human body. Most in-depth learning research focuses on finding high-level methods. The strippers analyze a large data set using linear and nonlinear transformations. The method of deep learning is used in the detection of several diseases including blood cell diseases and their classification using the radiography of blood cells to help decision makers to know the type of blood cell and its associated diseases and the results will be presented in detail and discussed. This thesis is using python language and deep learning to detect blood cell diseases and their classifications. The proposed deep learning model was trained, validated and the tested. The accuracy of proposed model was 98.00%. (shrink)

All parties involved in researching, developing, manufacturing, and distributing COVID-19 vaccines need guidance on their ethical obligations. We focus on pharmaceutical companies' obligations because their capacities to research, develop, manufacture, and distribute vaccines make them uniquely placed for stemming the pandemic. We argue that an ethical approach to COVID-19 vaccine production and distribution should satisfy four uncontroversial principles: optimising vaccine production, including development, testing, and manufacturing; fair distribution; sustainability; and accountability. All parties' obligations should be coordinated and mutually consistent. For (...) instance, companies should not be obligated to provide host countries with additional booster shots at the expense of fulfilling bilateral contracts with countries in which there are surges. Finally, any satisfactory approach should include mechanisms for assurance that all parties are honouring their obligations. This assurance enables countries, pharmaceutical companies, global organisations, and others to verify compliance with the chosen approach and protect ethically compliant stakeholders from being unfairly exploited by unethical behaviour of others. (shrink)

Autogestão, autoempreendedorismo, infotrabalho, trabalho intermitente, criptomoeda, uberização, proletariado de serviços e servidão digital delineiam uma série de designações indicativas das mudanças das condições de (re)produção do Capital nas suas formas contemporâneas. Grandes corporações como Google, Facebook e Amazon participam desse processo tanto no eixo da infraestrutura econômica, quanto na produção discursiva que sustenta ideologicamente as relações de trabalho determinadas pelo Aparelho Digital. Essa pesquisa elege como material específico de análise uma sequência de cursos oferecidos pelo “YouTube Academy” para a criação, (...) gerenciamento e divulgação de uma empresa associada à plataforma de vídeos do YouTube. O objetivo é investigar os modos de imbricação e/ou separação entre o sujeito e a empresa. Para construir os procedimentos analíticos, delimitamos as seguintes perguntas: Como as formas imaginárias do sujeito (o “eu”, a identidade e a individualidade) estão relacionadas com a criação e o funcionamento de uma empresa no YouTube? Como o trabalho e as relações de trabalho são significados nessa discursividade? O olhar discursivo é ainda guiado por compreensões de pesquisas anteriores: o modo como o “eu” é discursivizado em produto, o funcionamento da “empresa de si” como modelo de identificação e a empresarialidade. As referências passam por Michel Pêcheux, Eni Orlandi, Suzy Lagazzi, Luciana Nogueira, Guilherme Adorno, Joel Bombardelli, Pierre Dardot, Christian Laval e Ricardo Antunes. O conceito de político, compreendido discursivamente como conflito e disputa pelos sentidos - e seus efeitos de deslocamento, assim como o apagamento do político do lugar que lhe seria próprio - e o conceito de exterioridade discursiva são mais enfaticamente mobilizados na pesquisa, além das discussões em torno do discurso neoliberal e da psicologização do sujeito pelos efeitos discursivos de liberdade e autonomia. Um trabalho de análise da constituição da discursividade que tem o “sentido (já) lá” como resultado do efeito de exterioridade. Esperamos mostrar, assim, como, nas condições de produção sócio-históricas de um “Imperialismo Digital”, uma mudança da “economia política do poder-dizer” afeta os modos de circulação não só dos discursos, mas do próprio Capital. (shrink)

In fact, people get neck problems due to something such as sports or woke and Wrong sleep habits. In this paper an expert system was designed to help users to correctly diagnose neck problems world (muscle spasm, Muscle aches, Meningitis, herniated cervical disc, Fibromyalgia, Cervical spondylosis, Trigger points) with some information about the disease and self-care. Java language was used to design and implement this expert system.

There is no doubt that custard apple diseases are among the important reasons that destroy the Custard Apple plant and its agricultural crops. This leads to obvious damage to these plants and they become inedible. Discovering these diseases is a good step to provide the appropriate and correct treatment. Determining the treatment with high accuracy depends on the method used to correctly diagnose the disease, expert systems can greatly help in avoiding damage to these plants. The expert system correctly diagnoses (...) Custard Apple disease to make it easier for farmers to find the right treatment based on the appropriate diagnosis. Objectives: A specialized syllable language system was established for the diagnosis of Custard Apple plant disease. (shrink)

Abstract cantaloupe and honeydew melons are part of the muskmelon family, which originated in the Middle East. When picking either cantaloupe or honeydew melons to eat, you should choose a firm fruit that is heavy for its size, with no obvious signs of bruising. They can be stored at room temperature until you cut them, after which they should be kept in the refrigerator in an airtight container for up to five days. You should always wash and scrub the rind (...) of your melon before you cut it to remove any dirt or bacteria on the outside. In this paper, cantaloupe classification approach is presented with a dataset that contains approximately 1,312 of Cantaloupes and honeydews. Convolutional Neural Network (CNN) algorithms, a deep learning technique extensively applied to image recognition was used, for this task. The results found that CNN-driven classification applications when used in farming automation have the latent to enhance crop harvest and improve output and productivity when designed properly. The trained model achieved an accuracy of 99.74% on a held-out test set, demonstrating the feasibility of this approach. (shrink)

Abstract: Heart diseases are increasing daily at a rapid rate and it is alarming and vital to predict heart diseases early. The diagnosis of heart diseases is a challenging task i.e. it must be done accurately and proficiently. The aim of this study is to determine which patient is more likely to have heart disease based on a number of medical features. We organized a heart disease prediction model to identify whether the person is likely to be diagnosed with a (...) heart disease or not using the medical features of the person. We used many different algorithms of machine learning such as Gaussian Mixture, Nearest Centroid, MultinomialNB, Logistic RegressionCV, Linear SVC, Linear Discriminant Analysis, SGD Classifier, Extra Tree Classifier, Calibrated ClassifierCV, Quadratic Discriminant Analysis, GaussianNB, Random Forest Classifier, ComplementNB, MLP Classifier, BernoulliNB, Bagging Classifier, LGBM Classifier, Ada Boost Classifier, K Neighbors Classifier, Logistic Regression, Gradient Boosting Classifier, Decision Tree Classifier, and Deep Learning to predict and classify the patient with heart disease. A quite helpful approach was used to regulate how the model can be used to improve the accuracy of prediction of heart diseases in any person. The strength of the proposed model was very satisfying and was able to predict evidence of having a heart disease in a particular person by using Deep Learning and Random Forest Classifier which showed a good accuracy in comparison to the other used classifiers. The proposed heart disease prediction model will enhances medical care and reduces the cost. This study gives us significant knowledge that can help us predict the person with heart disease. The dataset was collected from Kaggle depository and the model is implemented using python. (shrink)

A presente dissertação se propõe analisar, a partir do pensamento aristotélico, a noção de causalidade acidental no tocante a sua fusikh; ejpisthvmh. Aristóteles, buscando encontrar as causas que explicam o vir-a-ser dos seres por natureza, se deparou com os acidentes e, não podendo deixar nenhum evento sem causa, postulou a existência de causas acidentais. Apesar de o acidente não ser objeto de ciência, a possibilidade de seu vir a ser salvaguarda o mundo da fuvsi" de um determinismo causal absoluto: eis (...) o papel e a importância de uma causalidade acidental no mundo físico aristotélico. (shrink)

The aim of this paper was to present ongoing research on the social representations relating to ritalin in Brazil between 1998 and 2008. Over this period, there was a considerable increase in ritalin usage and expansion of its use to purposes other than therapeutic use. Ritalin has been used not only for treating attention disorders, but also to enhance cognitive functions in healthy individuals. The research has developed through two fields of investigation with different methodologies. In the first field, Brazilian (...) scientific and popular publications have been investigated, with analysis on the arguments justifying ritalin usage and how scientific results are disseminated to the lay public in large-circulation newspapers. In the second field, focus groups have been used to explore the social representations that university students, students' parents and healthcare professionals have in relation to the use of ritalin for enhancing cognitive performance. -/- . (shrink)

The study zeroed in on the perception of college students who are exposed to sights of poverty in their immediate environment. The student-participants were asked to provide their perception, understanding, and behaviour towards poverty using the photographs that they took on their own. In qualitative research practice, this methodology is called photo elicitation. It was revealed, among others, that the participants have shown negative perceptions about poverty. They strongly felt bad about each photograph that they took and what these images (...) portrayed. The participants visualized their community and thereby weaved analyses and opinions that encroached on various philosophical and sociological theories. There are four interrelated dominant images that were drawn: exteriority image, dirt-poor image, victim-blaming image, and hand-to-mouth image. (shrink)

Abstract: Sign language recognition is one of the most rapidly expanding fields of study today. Many new technologies have been developed in recent years in the fields of artificial intelligence the sign language-based communication is valuable to not only deaf and dumb community, but also beneficial for individuals suffering from Autism, downs Syndrome, Apraxia of Speech for correspondence. The biggest problem faced by people with hearing disabilities is the people's lack of understanding of their requirements. In this paper we try (...) to fill this gap. By trying to translate sign language using artificial intelligence algorithms, we focused in this paper using transfer learning technique based on deep learning by utilizing a MobileNet algorithm and compared it with the previous paper results[10a], where we get in the Mobilenet algorithm on the degree of Accuracy 93,48% but the VGG16 the accuracy was 100% For the same number of images (43500 in the dataset in size 64*64 pixel ) and the same data split training data into training dataset (70%) and validation dataset(15%) and testing dataset(15%) and 20 epoch . (shrink)

There are many eye diseases but the most two common retinal diseases are Age-Related Macular Degeneration (AMD), which the sharp, central vision and a leading cause of vision loss among people age 50 and older, there are two types of AMD are wet AMD and DRUSEN. Diabetic Macular Edema (DME), which is a complication of diabetes caused by fluid accumulation in the macula that can affect the fovea. If it is left untreated it may cause vision loss. Therefore, early detection (...) of diseases is a critical importance. Our main goal is to help doctors detect these diseases quickly before reaching a late stage of the disease. In ophthalmology, optical coherence tomography (OCT) is critical for evaluating retinal conditions. OCT is an imaging technique used to capture high-resolution cross-sections of the retinas of patient. In this thesis, we review ways and techniques to use deep learning classification of the optical coherence tomography images of diseases from which a Retinal is suffering. The models used to improve patient care are (VGG-16, MobileNet, ResNet-50, Inception V3, and Xception) to reduce costs and allow fast and reliable analysis in large studies. The obtained results are encouraging, since the best model ResNet-50 reaching 96.21% of testing accuracy, which is very useful for doctors, to diagnose retinal diseases. (shrink)

Abstract: Background: Hair loss is often a concern for women, men and children. It is normal to lose between 50 and 100 hairs a day, without us noticing it. Usually hair loss is a sign of a medical condition, some of them are hereditary, and some of them are temporary due to disease, stress, cancer treatment, weight loss, and iron deficiency. Objectives: The main goal of this expert system is to obtain an appropriate diagnosis of the cause of hair loss. (...) Methods: In this paper, the proposed expert system that was produced is designed to assist the physician in diagnosing hair loss disease such as seborrhea, lichen planus, ringworm, alopecia areata, thyroid disease and male-pattern baldness. The proposed expert system presents an overview about hair loss diseases are given, the cause of diseases are outlined and the treatment of disease whenever possible is given out. Clips Expert System language was used for designing and implementing the proposed expert system. Results: The proposed hair loss diseases diagnosis expert system was evaluated by Medical students and they were satisfied with its performance. Conclusions: The Proposed expert system is very useful for hair loss treatment physician, patients with hair loss problems and newly graduated physician. (shrink)

As these opening quotes acknowledge, the Prisoner’s Dilemma (PD) represents a core puzzle within the formal mathematics of game theory.3 Its rise in conspicuity is evident figure 2.1 above demonstrating a relatively steady rise in incidences of the phrase’s usage between 1960 to 1995, with a stable presence persisting into the twenty first century. This famous two-person “game,” with a stock narrative cast in terms of two prisoners who each independently must choose whether to remain silent or speak, each advancing (...) self-interest at the expense of the other and thereby achieving a mutually suboptimal outcome, mires any social interaction it is applied to into perplexity. The logic of this game proves the inverse of Adam Smith’s invisible hand: individuals acting on self interest will achieve a mutually suboptimal outcome. However, as this chapter illuminates, the assumptions underlying game theory drive this conclusion. (shrink)

The cucumber is a creeping vine that roots in the ground and grows up trellises or other supporting frames, wrapping around supports with thin, spiraling tendrils. The plant may also root in a soilless medium, whereby it will sprawl along the ground in lieu of a supporting structure. The vine has large leaves that form a canopy over the fruits. Among these common diseases, we single out the diseases that affect the cucumber, which is affected by about 22 diseases, with (...) different symptoms for each disease. Today, technology is facilitating human life in all areas of life, and among these facilities are expert systems that have become an integral part of human life as they contain several systems and areas, for example: Artificial Intelligence (AI), which refers to systems or devices that simulate Human intelligence to perform tasks that can improve itself based on some human information, and other areas, and with reference to expert systems and their importance to humans, an integrated expert system has been created in the agricultural field that diagnoses cucumber diseases using CLIPS Expert System language Delphi language. The system was used to design and implement the proposed expert system. The system facilitates the diagnosis of cucumber-related diseases. There is no doubt that this expert system will help farmers and those involved in the agricultural field to diagnose cucumber-related diseases. Objectives: is to help farmers diagnose pear diseases in the correct way and how to treat these diseases. Method: The system contains a program that diagnoses 22 diseases that affect cucumber. Results: The expert system was evaluated by farmers and praised for helping them with it. Conclusion: The expert system for diagnosing cucumber diseases is effective and usable. (shrink)

Water quality assessment is critical for environmental sustainability and public health. This research employs neural networks to predict water quality, utilizing a dataset of 21 diverse features, including metals, chemicals, and biological indicators. With 8000 samples, our neural network model, consisting of four layers, achieved an impressive 94.22% accuracy with an average error of 0.031. Feature importance analysis revealed arsenic, perchlorate, cadmium, and others as pivotal factors in water quality prediction. This study offers a valuable contribution to enhancing water quality (...) monitoring and decision-making for stakeholders and policymakers. (shrink)

There is no doubt that tomato diseases are one of the important reasons that destroy the tomato plant and its crops. This leads to clear damage to these plants and they become inedible. Discovering these diseases after a good step for proper and correct treatment. Determining the treatment with high accuracy depends on the method used in the diagnosis. Correctly, expert systems can greatly help to avoid damage to these plants. The expert system diagnoses tomato disease correctly to facilitate farmers (...) to find the correct treatment based on the appropriate diagnosis. Objectives: An expert system has been established based on CLIPS to diagnose tomato plant disease. (shrink)

Intelligent tutoring system (ITS) is a computer system which aims to provide immediate and customized or reactions to learners, usually without the intervention of human teacher's instructions. Secretariats professional to have the common goal of learning a meaningful and effective manner through the use of a variety of computing technologies enabled. There are many examples of professional Secretariats used in both formal education and in professional settings that have proven their capabilities. There is a close relationship between private lessons intelligent, (...) cognitive learning and design theories; and there are ongoing to improve the effectiveness of ITS research. And it aims to find a solution to the problem of over-reliance on students' teachers for quality education. The program aims to provide access to high-quality education to every student, and therefore the reform of the education system as a whole. In this paper, we will use Intelligent Tutoring System Builder (ITSB) to build an education system on cloud computing in terms of the concept of cloud computing and components and how to take advantage of cloud computing in the field. (shrink)

Abstract Heart Attack is the Cardiovascular Disease (CVD) which causes the most deaths among CVDs. We collected a dataset from Kaggle website. In this paper, we propose an ANN model for the predicting whether a patient has a heart attack or not that. The dataset set consists of 9 features with 1000 samples. We split the dataset into training, validation, and testing. After training and validating the proposed model, we tested it with testing dataset. The proposed model reached an accuracy (...) of 98.01% on the Heart Disease Dataset. (shrink)

Sign Language Recognition (SLR) aims to translate sign language into text or speech in order to improve communication between deaf-mute people and the general public. This task has a large social impact, but it is still difficult due to the complexity and wide range of hand actions. We present a novel 3D convolutional neural network (CNN) that extracts discriminative spatial-temporal features from photo datasets. This article is about classification of sign languages are not universal and are usually not mutually intelligible (...) although there are also similarities among different sign languages. They are the foundation of local Deaf cultures and have evolved into effective means of communication. Although signing is primarily used by the deaf and hard of hearing, hearing people also use it when they are unable to speak, when they have difficulty speaking due to a health condition or disability (augmentative and alternative communication), or when they have deaf family members, such as children of deaf adults. In this article we use the 43500 image in the dataset in size 64*64 pixel by use CNN Architecture and achieved 100% accuracy. (shrink)

Abstract: The aim behind analyzing Google Stock Prices dataset is to get a fair idea about the relationships between the multiple attributes a day might have, such as: the opening price for each day, the volume of trading for each day. With over a hundred thousand days of trading data, there are some patterns that can help in predicting the future prices. We proposed an Artificial Neural Network (ANN) model for predicting the closing prices for future days. The prediction is (...) based on these features (date, opening price, highest price, lowest price, volume), which were used as input variables and (closing price) as output variable for our ANN model. Our model was created, trained, and validated using data set in JNN environment, which its title is “Google-Stock-Prices”. The model evaluation showed that the ANN model is able to predict correctly 99.48% of the validation samples. (shrink)

This article seeks to establish the development of rural communities, with up to 500 inhabitants, with the creation of a Rural Tourism Development Forum and a Tourism Development Program with local identity. It is proposed to capitalize on cultural assets and local knowledge, to strengthen the profile and tourist circuits, local services and enterprises, agro-tourism and other related economic and social activities. The objective is to contribute to territorial tourism development from an innovative perspective, which, based on the efficient use (...) of local resources, generates employment and improves the quality of life of its inhabitants, capitalizing on the advantages of tourist activity. The methodology used consisted in analyzing the problems of local development, identifying the obstacles and conceiving tourism as a solution and sustenance that allowed the elaboration of the model. (shrink)

Abstract: This study has effectively tackled the critical challenge of accurate calorie prediction in dishes by employing a robust neural network-based model. With an outstanding accuracy rate of 99.32% and a remarkably low average error of 0.009, our model has showcased its proficiency in delivering precise calorie estimations. This achievement equips individuals, healthcare practitioners, and the food industry with a powerful tool to promote healthier dietary choices and elevate awareness of nutrition. Furthermore, our in-depth feature importance analysis has shed light (...) on the indispensable role played by specific nutritional attributes in calorie estimation. This unveiling of crucial factors provides valuable insights for further research endeavors and practical applications. Notably, this research extends its impact beyond the immediate context by making substantial contributions to the domains of nutrition science and dietary planning. It underscores the transformative potential of artificial intelligence, demonstrating how it can revolutionize our approach to food, nutrition, and health. As the world grapples with the challenges of diet-related health issues and environmental concerns, the accuracy and precision achieved in calorie prediction through neural networks represent a significant stride towards more informed and conscientious dietary practices. In this era of data-driven decision-making, our research paves the way for healthier lifestyles, heightened nutritional awareness, and a more health-conscious society. (shrink)

Abstract: Classifying sea animals is an important problem in marine biology and ecology as it enables the accurate identification and monitoring of species populations, which is crucial for understanding and protecting marine ecosystems. This paper addresses the problem of classifying 19 different sea animals using convolutional neural networks (CNNs). The proposed solution is to use a pretrained MobileNetV2 model, which is a lightweight and efficient CNN architecture, and fine-tune it on a dataset of sea animals. The results of the study (...) show that the fine-tuned MobileNetV2 model is able to achieve an accuracy of 85% on the classification task, which is competitive with the state-of-the-art methods. Additionally, the study also found that data augmentation and regularization techniques such as dropout were important for preventing overfitting and improving the performance of the model. This study demonstrates the potential of using pretrained models and efficient CNN architectures for classifying sea animals, and it provides insights into the challenges and best practices for solving this important problem in marine biology and ecology. (shrink)

Abstract: background: Dental and oral health is an essential part of your overall health and well-being. Poor oral hygiene can lead to dental cavities and gum disease, and has also been linked to heart disease, cancer, and diabetes. Maintaining healthy teeth and gums is a lifelong commitment. The earlier you learn proper oral hygiene habits — such as brushing, flossing, and limiting your sugar intake — the easier it’ll be to avoid costly dental procedures and long-term health issues. (Healthline, n.d.) (...) Objectives The main goal of this expert system is to get the appropriate diagnosis of disease and the correct treatment by presenting suggestions on Tooth Problems to the user by asking about symptoms. (shrink)

Abstract: Forests are areas with a high density of trees, and they play a vital role in the health of the planet. They provide a habitat for a wide variety of plant and animal species, and they help to regulate the climate by absorbing carbon dioxide from the atmosphere. While in 2010, the world had 3.92Gha of forest cover, covering 30% of its land area, in 2019, there was a loss of forest cover of 24.2Mha according to the Global Forest (...) Watch institute. Discovery and classification depend on human experience and effort, so the error in the results of this process can lead to forest fires and disasters. Therefore, deep learning algorithms from artificial intelligence and machine learning sciences have been applied to help specialists avoid false or inaccurate diagnoses when detecting Forest fires in images using a pre-trained convolutional neural network called VGG16. The model was customized to fit the Forest fires classification and then applied to a dataset consisting of (14,000) of the Forests collected from the Kaggle depository. We trained, validated, and tested the modified VGG16 model. The proposed VGG16 model obtained Precision (99.96%), Recall (99.96%), and F1-Score (99.96%). (shrink)

Abstract: Networking is one of the most important areas currently used for data transfer and enterprise management. It also includes the security aspect that enables us to protect our network to prevent hackers from accessing the organization's data. In this paper, we would like to learn what the network is and how it works. And what are the basics of the network since its emergence and know the mechanism of action components. After reading this paper - even if you do (...) not have a general background on networking - you will be able to manage your own network and be able to distribute and control your ip. (shrink)

Abstract: Fast food refers to quick, convenient, and ready-to-eat meals that are usually sold at chain restaurants or take-out establishments. Fast food is often criticized for its unhealthy ingredients, such as high levels of salt, sugar, and unhealthy fats, and its contribution to the growing obesity epidemic. Despite this, fast food remains popular due to its affordability, convenience, and widespread availability. Many fast food chains have attempted to respond to these criticisms by offering healthier options, such as salads and grilled (...) chicken sandwiches, and by using more natural and locally sourced ingredients. The aim in this paper to propose a deep learning model for the classification of fast food dishes. The proposed model, Xception, was trained on natural images and was fine-tuned to make up the fast food meals. The researchers collected the Fast Food V2 dataset from Kaggle depository, the dataset, contained 20,000 images. The dataset has ten labels of food images comprised of Baked Potato, Burger, Crispy Chicken, Donut, Fries, Hot Dog, Pizza, Sandwich, Taco, and Taquito. The dataset was split into three sets: training, validation and testing. The accuracy, F1-score, recall, precision on the separate test set showed that classification of fast food was accuracy (95.13%), Precision (95.34%), Recall (95.13%), and F1-Score (95.14%). (shrink)

The study aimed to investigate the reality of spreading the culture of entrepreneurship at Al-Azhar University from the point of view of students of the Faculty of Engineering and Information Technology and diagnose the most important obstacles that limit its activation. The researchers used the descriptive approach (survey) to achieve the objectives of the study, and relied on the questionnaire as a tool for applied study. The study concluded that: The reality of spreading the culture of entrepreneurship at Al-Azhar University (...) from the point of view of the students participating in the study came with an average degree of approval, while the most important obstacles and possible proposals for activating it came with a high degree of approval, which indicates the existence of strengths of Al-Azhar University in spreading the culture of entrepreneurship among students. Deficiencies must be corrected through proposals. In light of the results of the study, it was possible to develop a number of recommendations that can contribute to activating the culture of entrepreneurship at Al-Azhar University. Including the establishment of a specialized center for entrepreneurship within the university, develop a declared strategic plan to spread and develop the culture of entrepreneurship, allocate a sufficient budget to sponsor and support entrepreneurial ideas and projects for students and provide specialized cadres and certified trainers in the field of entrepreneurship. (shrink)

Abstract: People all over the world have been drinking tea for thousands of centuries, and for good reason. Many types of teas can help you stay healthy by boosting your immune system, reducing inflammation, and even preventing cancer and heart disease. There is sufficient material to show that regularly consuming tea can improve your health over the long term. A deep learning model that categorizes tea disorders has been completed. When focusing on the tea, we must also focus on and (...) take into account the diseases that harm it. The aim of this paper is to diagnose tea diseases based on a dataset containing 8000 picture and 8 classes .The model gave the final accuracy test with an F1-score of 99.41% in an estimated time 3 second, as with these results it proved its effectiveness and good ability in the classification test. (shrink)

The paper argues that the moral philosophy of Thomas Hobbes is unified by a complex conception of reason that imposes consistency norms of both rationality and reasonableness. Hobbes’s conceptions of rightness as reciprocity, and moral goodness as sociability belong to an original and attractive moral theory that is neither teleological nor classically deontological, nor as interpreters have variously argued, subjectivist, contractarian, egoist, or dependent on divine command.

In the summer of 2016, the University of Dallas and the Instituto Tecnológico Autónomo de México organized a conference to discuss the topic of the middle class and its continued decline—recognizing that, despite some historical, political and cultural differences, healthy democracies throughout the hemisphere depend upon a strong and prosperous middle class. This volume brings together contributions by nine scholars from both institutions. The chapters reflect diverse disciplinary perspectives that are historical, political, economic, anthropological, and philosophical. Despite this diversity, the (...) volume possesses a conceptual unity that stems from its foundation in Aristotle’s approach to the middle class. On this basis, the topic is given a rigorous study that is both theoretical and data-driven. The chapters include treatments of Aristotle, Montesquieu, Adam Smith and Sir James Steuart, Catholic social teaching, the problem of inequality in the US, the definition and measurement of the middle class in Mexico, as well as its values and political attitudes, the rise of middle-class politics in early-twentieth-century Latin America, and a comparative analysis of healthcare for the middle class in North America. (shrink)

As sustainable tourism gains increasing attention, understanding the factors that influence travelers' motivation to engage with sustainable travel agents becomes crucial. This study investigates the moderating effect of social media usage on the relationship between the perceived value of websites and motivational factors for sustainable travel agents. The study proposes that social media usage acts as a moderator in shaping the relationship between the perceived value of websites and motivational factors. This study has utilized smart tourism. Therefore, independent variable motivation (...) in terms of informativeness gratification and gratification acted as moderating variables. This study has utilized an online questionnaire adapted from a standardized questionnaire based on the literature review. Moreover, a total of 146 managers were surveyed in which they were required to respond to 55 items that elicited the 7 variables social media use, Propensity, perceived website value, motivating factors, entertainment gratification, informativeness gratification, sustainable smart tourism. The data were analyzed by SPSS and PLS-SEM. The findings indicated that relevance and importance of social media use and sustainable smart tourism. The result revealed that 7 hypotheses had a significant relationship. 3 hypotheses did not show a moderating effect. Overall, this study extends the understanding of sustainable smart tourism. These findings will benefit travel agents’ managers in Malaysia to better understand the role of social media use and utilize it towards developing sustainable sustainable smart tourism. (shrink)