In the limited literature on gender and climate change, two themes predominate – women as vulnerable or virtuous in relation to the environment. Two viewpoints become obvious: women in the South will be affected more by climate change than men in those countries and that men in the North pollute more than women. The debates are structured in specific ways in the North and the South and the discussion in the article focuses largely on examples from Sweden and India. The (...) article traces the lineage of the arguments to the women, environment and development discussions, examining how they recur in new forms in climate debates. Questioning assumptions about women's vulnerability and virtuousness, it highlights how a focus on women's vulnerability or virtuousness can deflect attention from inequalities in decision-making. By reiterating statements about poor women in the South and the pro-environmental women of the North, these assumptions reinforce North–South biases. Generalizations about women's vulnerability and virtuousness can lead to an increase in women's responsibility without corresponding rewards. There is need to contextualise debates on climate change to enable action and to respond effectively to its adverse effects in particular places. -/- . (shrink)

he importance of gender equality and of women’s work in relation to the environment is regarded as a crucial question for development in “third‐world” rural societies. “Development” and a certain standard of welfare make these issues appear to be less urgent in a wealthier country such as Sweden. In this article, I trace some of the contradictions and connections in the ways in which gender equality is conceptualized in women’s struggles vis‐à‐vis environmental issues in rural areas in Sweden and India. (...) The article throws light on two important insights: First, in Sweden, where gender equality has been actively pursued as the bedrock of modern societal organizing, the space to organize as women in relation to environmental issues was fraught with ambiguity. Second, development discourses about equality and empowerment of oppressed third‐world women not only bear on how gender equality is conceptualized and practiced in the global South but also shape the space for gender equality in the North. Analyzing the two cases in relation to each other reveals the travel of ideas and conversations across distant geographical spaces. While ideas about the independent, empowered woman are used to deny agency to women’s collectives in India, gendered discrimination has taken different forms in Sweden, making it more difficult to contest. Understanding how this takes place opens an opportunity for interruption in an order and a space that appears to have become narrower under the umbrella of development, welfare, and growth. It brings into question the category of development in a southern but particularly so in a northern context, where the North, and especially Sweden, is taken as a referent for questions of development and gender equality. -/- . (shrink)

Great religions to pragmatic capacities sporadically abound in the stories of supernatural phenomena which subsumes telepathy, clairvoyance and precognition. However, unfortunately treated as the topics of spiritualism, witchcraft and edification, not the materials of Scientific Enquiry. Whatsoever, have been deciphered about these queer speculations, the most prevalent sole concept is : namely, that there can be senseexperiences from the realm which is not accessible to human brain and sense organs. Possessor of these senses which are not currently accessible to average (...) humans can be a omniscient being tapping to his full potential. Presently, we have no language or any communication system to describe them intelligibly. When inquiring about these affairs we cannot avoid absurdity as presently we lack any linguistic convention on it. Our linguistic convention is derived from the physical world in which the supernatural is not considered as "Normal". It is considerably strained with "Abnormality" in the first place. My aim in this paper is to reconcile this Orthodox Psychology with Science and Philosophy which certainly appears conflicting. This inquiry leads me to enable the 10 percent brain myth. (shrink)

This article views gender dynamics and strategies for change in a small Swedish village from a systems perspective. In the context of the struggle for the communal management of forests, tensions arose in the relations among the people in the village who differed in their opinions as to how to approach village development. Some village women argued for the importance of issues other than only community forestry in the development of the community's future livelihoods and well-being. They also believed that (...) linking these activities with each other are vital for the community. Co-operative inquiry with women in the village reveals that, in their view, the community's overall needs are the most meaningful point of departure and not just individual resource management initiatives. They believed that it was vital to link resource management with other developmental activities in the village. The inquiry process also shows how the differences that may arise between men and women are dependent on the context, their relationships, and the networks they activate rather than the differences emerging solely from gender roles or the structure. Attention to how women and men “draw boundaries” around their activities and relationships expands our understanding of the diverse means they use for reaching their objectives. It also highlights the role of innovators who cross these boundaries and work toward change. (shrink)

A child, according to Nigerian law (2019), "is a conceptualized term used for anybody that is 14 years old and below." Anshana Arora (2020) found that Africa’s child population will reach 1 billion by 2055, making it the largest child population among all continents. Yet, according to a recent report by UNICEF (2020), between 2005 and 2020, more than 93,000 children were verified as "child soldiers," used in different armed conflicts in Africa. Other cases document girls being treated as (...) slaves, forced to work day and night peddling goods in the market. Additionally, there is widespread systemic abuse of children in Africa. This paper, therefore, explores the children of Africa: child soldiers and child labour; and the potential solutions for ending the plight of exploited children. Using the analytic method, an endeavor was made to show the implication of child labor and child soldiers in Africa. The paper concluded that ending the recruitment of children into violent conflict is possible by addressing the root causes of child exploitation, which can be achieved through the proactive creation of good policies, re-education, and skill development training and advocacy programs. (shrink)

What does it mean to study places in ‘crisis’ and how does that affect the research done on the ‘rural’? To be considered to be in crisis is not really new as any literature review of rural studies indicates. And yet, we live now in a new context, with new challenges for ‘rural’ research, in particular that of sustainability. Sustainability is the new policy focus and is increasingly reflected in research on rural Europe. Although scholars are beginning to theorize on (...) what is sustainable in and for rural areas, our intention is to take this further. We theorize on what the focus on crisis and, increasingly on sustainability, means for the research we do and the knowledge we produce on rural Europe. Our aim is to bring attention to the politics of past and present knowledge production on the rural to be able to imagine just and sustainable futures. In an analysis of literature primarily from Sweden and the UK, we argue that two construals, that of a rural crisis and that of rural–urban polarization, have set the tone for rural studies and may have overshadowed a more plural approach. We outline what might be needed from rural research to meet future challenges and what the notion of sustainability, with its emphasis on the entanglements of the social, economic and environmental, might mean for the future of rural research. (shrink)

Feminist decolonial scholars have called for disengaging from the current system built on a hierarchical logic of race and gender central to modern, colonial thinking. They have looked to worlds outside the modern system to lead us out of current unjust practices harming both humans and the environment. Although policymaking may be seen as the stronghold of the current political agenda and of the structures that have led to the climate crisis, we argue that climate policies too, are also crucial (...) for rethinking and transforming societies. Our examination of climate adaptation policies in Sweden and the literature from Europe shows how policy documents ignore and unknow the oppressive intersections of gender and power despite the knowledge that exists on these issues in the public domain. Drawing on the tools of agnotology, we examine how this is achieved by strategies of ‘denial, dismissal, diversion and displacement.’ Building on feminist post and decolonial scholarship, we make explicit the gendered and racial hierarchies and dichotomies underpinning these policy documents. At the same time, we bring attention to the nuances in the policy documents we study and look for the openings that might be used to bring about transformation by making these hierarchies explicit and calling them into question. We argue that a transformation is possible through a feminist post and decolonial intervention, even in policymaking otherwise ignorant of culture, values and the colonial histories that have produced contemporary society. (shrink)

This special issue contributes to a grounded understanding about 'sustainability' in a range of rural contexts and in so doing sheds light on accompanying tensions and implications for the future of rural areas in Europe. It also brings attention to how the rural might be changing as a result of this new focus on sustainability. The 17 contributions bring to light crucial dimensions of sustainability: (1) the imperative of wellbeing, belonging and care; (2) dimensions of power and identity; (3) the (...) apprehension of time and space - in other words, sustainability as a process and always in transition; (4) social and spatial justice; and (5) the question of knowledge production on the rural and on sustainability. (shrink)

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)

Background: Mint is a grassy, perennial plant, belonging to the oral platoon, fast growing and spreading, its leaves are green in color, fragrant, tart, refreshing, square-shaped leg, bifurcated, erect, ranging in height from (10 - 201 cm). Home to Europe and Asia. The mint plant has many benefits, the most important of which are pain relief, treatment of gallbladder disorders, the expulsion of gases, anti-inflammatory, and relaxing nerves. While the mint plant is the ideal option for the start of gardens, (...) it is prone to some common diseases that affect the plant's growth. Objectives: The main goal of this expert system is to get the appropriate diagnosis of disease and the correct treatment. Methods: In this paper, the design of the proposed Expert System was produced to help Farmers and those interested in agriculture in diagnosing many of the Mint diseases such as Mint rust, Verticillium wilt, Anthracnose, Powdery mildew, Black Stem Rot, Stem and stolon canker, Septoria leaf spot. The proposed expert system presents an overview of mint diseases are given, the cause of diseases 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 Mint diseases diagnosis expert system was evaluated by Agricultural Students at AL Azhar University and some friends interested in agriculture and they were satisfied with its performance. Conclusions: The proposed expert system is very useful for Farmers and those interested in agriculture. (shrink)

Plant diseases are numerous in the world of agriculture. These diseases cause a lot of trouble to most farmers. Among these common diseases, we single out the diseases that affect the Passion fruit, which is affected by about seven diseases, with different symptoms for each disease. Today, technology is facilitating human life in all areas of life, and among these facilities are expert system, a computer program that uses artificial-intelligence methods to solve problems within a specialized domain that ordinarily requires (...) human expertise. The first expert system was developed in 1965 by Edward Feigen Baum and Joshua Lederberg of Stanford University in California, U.S. Dendral, as their expert system was later known, was designed to analyses chemical compounds. Expert systems now have commercial applications in fields as diverse as medical diagnosis, petroleum engineering, and financial investing 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 Passion diseases using CLIPS Expert System language. The system was used to design and implement the proposed expert system. The system facilitates the diagnosis of Passion -related diseases. There is no doubt that this expert system will help farmers and those involved in the agricultural field to diagnose Passion -related diseases. Objectives: is to help farmers diagnose Passion diseases in the correct way and how to treat these diseases. Method: The system contains a program project that diagnoses 7 diseases that affect Passion and the seven diseases are: Brown spot, Septoria spot, Root and crown rot, Fusarium wilt, Anthracnose, Woodiness virus, Scab. Results: The expert system was evaluated by farmers and praised for helping them with it. Conclusion: The expert system for diagnosing Passion diseases is effective and usable. (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)

Papaya is a tropical fruit with a green cover, yellow pulp, and a taste between mango and cantaloupe, having commercial importance because of its high nutritive and medicinal value. The process of sorting papaya fruit based on maturely is one of the processes that greatly determine the mature of papaya fruit that will be sold to consumers. The manual grading of papaya fruit based on human visual perception is time-consuming and destructive. The objective of this paper is to the status (...) classification of papaya fruits if it's mature or partially matured or unmatured. A deep learning technique that was extensively applied to image recognition was used. The trained model achieved an accuracy of 100% on a held-out test set, demonstrating the feasibility of this approach. Classification model of VGG16 achieved a 100% accuracy and 112 seconds of training time. (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)

Deep learning may transform health care, but model development has largely been dependent on availability of advanced technical expertise. The aim of this study is to develop a deep learning model to predict the gender from retinal fundus images. The proposed model was based on the Xception pre-trained model. The proposed model was trained on 20,000 retinal fundus images from Kaggle depository. The dataset was preprocessed them split into three datasets (training, validation, Testing). After training and cross-validating the proposed model, (...) it was evaluated using the testing dataset. The result of testing, the area under receiver operating characteristic curve (AUROC) of the model was 0.99, precision, recall, f1-score and accuracy were 99%, precision, recall, f1-score and accuracy were 96.83%, 96.83%, 96.82% and 96.83% respectively.. Clinicians are presently unaware of dissimilar retinal feature variants between females and males, stressing the importance of model explain ability for the prediction of gender from retinal fundus images. The proposed deep learning may enable clinician-driven automated discovery of novel visions and disease biomarkers. (shrink)

Automatic detection of diseases and anatomical landmarks in medical images by the use of computers is important and considered a challenging process that could help medical diagnosis and reduce the cost and time of investigational procedures and refine health care systems all over the world. Recently, gastrointestinal (GI) tract disease diagnosis through endoscopic image classification is an active research area in the biomedical field. Several GI tract disease classification methods based on image processing and machine learning techniques have been proposed (...) by diverse research groups in the recent past. However, yet effective and comprehensive deep ensemble neural network-based classification model with high accuracy classification results is not available in the literature. In this thesis, we review ways and mechanisms to use deep learning techniques to research on multi-disease computer-aided detection about gastrointestinal and identify these images. We re-trained five state-of-the-art neural network architectures, VGG16, ResNet, MobileNet, Inception-v3, and Xception on the Kvasir dataset to classify eight categories that include an anatomical landmark (pylorus, z-line, cecum), a diseased state (esophagitis, ulcerative colitis, polyps), or a medical procedure (dyed lifted polyps, dyed resection margins) in the Gastrointestinal Tract. Our models have showed results with a promising accuracy which is a remarkable performance with respect to the state-of-the-art approaches. The resulting accuracies achieved using VGG, ResNet, MobileNet, Inception-v3, and Xception were 98.3%, 92.3%, 97.6%, 90% and 98.2%, respectively. As it appears, the most accurate result has been achieved when retraining VGG16 and Xception neural networks with accuracy reache to 98% due to its high performance on training on ImageNet dataset and internal structure that support classification problems. (shrink)

Background: There is no doubt that strawberry diseases are one of the most important reasons that led to the destruction of strawberry plants and their crops. This leads to obvious 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 in avoiding damage to these plants. The expert system correctly diagnoses (...) strawberry disease to make it easier for farmers to find the right treatment based on the appropriate diagnosis. Objectives: The main goal of this expert system is to get the appropriate diagnosis of disease and the correct treatment. Methods: In this paper the design of the proposed Expert System which was produced to help Farmers and students interested in agriculture strawberry in diagnosing many of the strawberry diseases such as: Leaf Spots, Grey Mold, Red Stele/Red Core, Wilt, Powdery Mildew, Alternaria Spot, Black Root Rot, Anthracnose (black spot), and Angular Leaf Spot. The proposed expert system presents an overview about strawberry diseases are given, the cause of diseases are outlined and the treatment of disease whenever possible is given out. CLIPS language was used for designing and implementing the proposed expert system. Results: The proposed strawberry diseases diagnosis expert system was evaluated by Farmers and they were satisfied with its performance. Conclusions: The Proposed expert system is very useful for Farmers with strawberry problem and students interested in agriculture strawberry. (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)

Background: Broccoli is an edible green plant in the cabbage family (family Brassicaceae, genus Brassica) whose large flowering head, stalk and small associated leaves are eaten as a vegetable. A leaf of Broccoli might be affected of Several Diseases descriped in this paper . When symptoms is encountered, it requires some kind of medical care. If appropriate Survival of Broccoli Diseases is not taken quickly, it can lead to Broccoli to die . Objectives: The main goal of this expert system (...) is to get the appropriate diagnosis of disease and the correct treatment. Methods: In this paper the design of the proposed Expert System which was produced to help Farmers in diagnosing many of the broccoli diseases such as : Damping Off,Club root of crucifers or Finger and toe disease,Alternaria leaf spot,Black rot,Downy mildew, and White rust. (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)

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)

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 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.

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)

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)

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)

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)

Background: Obstetrics and gynaecology are many and common, where a woman suffers from problems related to pregnancy or her reproductive organs. Any part of her body may be affected due to some symptoms that are completely related to the reproductive organs when she is in a critical period for her, whether in her menstrual cycle, pregnancy, or disease conditions. The bulk of cases of diseases related to women and childbirth are dealt with great care and special care, as all diseases (...) related to women are considered very sensitive diseases due to the presence of the disease in sensitive and not simple places. A gynaecologist is a specialist in all diseases and problems related to the female sexual organs. They perform regular preventive medical exams, such as cervical smear tests and breast exams. It also provides consultations for women of all ages about the problems of contraception, infertility and menopause. Objectives: The objective of this expert system is to help and facilitate women in diagnosing diseases related to their obstetrics and gynaecology, a simple expert system has been designed consisting of ten various common diseases that affect women whether During or without pregnancy, Methods: In this system, the system consists of a list of some common symptoms, the correct diagnosis adopted for these diseases, and how to treat diseases in the correct way with the help of a consultant obstetrician and gynaecologist, Dr. Fathi Muhammad Al-Habibi, and these diseases are: uterine cancer, cervical cancer, Infertility, double uterus, ectopic pregnancy, endometrial cancer, female sexual dysfunction, endometriosis, faecal incontinence, female infertility, CLIPS Expert System language was used to design and implement the proposed expert system. Results: The proposed ten obstetrics and gynaecology diagnostic expert system was evaluated by medical students and they were satisfied with its performance. Conclusions: The proposed expert system is very useful for obstetricians and gynaecologists, patients with reproductive system problems, and recent graduates. (shrink)

Introduction. The development of online marketing in social networks creates unique opportunities for personal selling. Especially these opportunities are manifested in online education when they buy a brand of an expert with experience in a particular field. That is why a competitive space is being formed in the Instagram social network, where a personal brand acts as a product or service. -/- Materials and methods. Studying the effectiveness of promoting a personal brand in social networks based on the Instagram platform (...) was chosen to have great visual opportunities for self-presentation. As part of the collection of empirical material, two methods were used: a survey (N-200) and content analysis of three blogger accounts with high rates of activity and popularity. -/- Results and discussion. Content analysis of bloggers showed that an algorithmic feed on a social network allows bloggers to control the content. To help them, Instagram provides statistical data on user reach, thereby capturing trends in the movement of the blogger’s audience. The main task of a blogger is to combine real and “virtual” images so as not to lose consumer confidence. A survey of social network users confirmed the importance of a personal brand for them. The survey also made it possible to identify the most popular audience requests that they expect from bloggers and their accounts: valuable reviews and recommendations, case studies and author’s solutions, storytelling, blogger’s reflections and motivating messages, live broadcasts, and stories are important. -/- Conclusions. The results obtained underline followers’ high level of interest in the bloggers’ personal brand on Instagram. The study results show that the most significant number of those involved (those who give feedback and are constantly involved in interaction with the account) is where the formation of a personal brand is built to a greater extent on the emotional level of perception of the individual. (shrink)

Contemporary republicanism is characterized by three main ideas: free persons, who are not subject to the arbitrary power of others; free states, which try to protect their citizens from such power without exercising it themselves; and vigilant citizenship, as a means to limit states to their protective role. This book advances an economic model of such republicanism that is ideologically centre-left. It demands an exit-oriented state interventionism, one that would require an activist government to enhance competition and resource exit from (...) dominating relationships within markets of all types, be they marital, labour, or residential. The substantial intervention and redistribution necessitated by such an approach make it leftist, while its tendency to work with rather than against the grain of markets makes it centrist. It is, in short, a contribution to progressive republican political thought, but one that is less social-democratic than market-democratic in character. (shrink)

Family members can provide crucial support to individuals participating in clinical trials. In research on the “newest frontier” of Deep Brain Stimulation (DBS)—the use of DBS for psychiatric conditions—family member support is frequently listed as a criterion for trial enrollment. Despite the significance of family members, qualitative ethics research on DBS for psychiatric conditions has focused almost exclusively on the perspectives and experiences of DBS recipients. This qualitative study is one of the first to include both DBS recipients and their (...) family members as interview participants. Using dyadic thematic analysis—an approach that takes both the individuals and the relationship as units of analyses—this study analyzes the complex ways in which family relationships can affect DBS trial participation, and how DBS trial participation in turn influences family relationships. Based on these findings, we propose ways to improve study designs to better take family relationships into account, and better support family members in taking on the complex, essential roles that they play in DBS trials for psychiatric conditions. (shrink)

Through engagement with key informants and review of ethical theories applicable to refugee policy, this paper examines the ethical and policy considerations that policy-level stakeholders believe should factor into setting the refugee resettlement ceiling. We find that the ceiling traditionally has been influenced by policy goals, underlying values, and practical considerations. These factors map onto several ethical approaches to resettlement. There is significant alignment between U.S. policy interests and ethical obligations toward refugees. We argue that the refugee ceiling should be (...) restored to historical norms, and that there exists a corresponding obligation to counter negative public perceptions about refugees and the costs of resettlement. (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 nation’s economy runs on the knowledge and skills of its people.Quality assurance mechanisms for higher education institutions must take cognizance of the graduates' acquisition of skills to become productive and contributory for societal development. The study is a quantitative survey assessing the attainment of the immediate program learning outcomes of the graduating Bachelor of Science in Information Technology of one campus of a public higher education institution in the Philippines. It also assessed the introspection and level of satisfaction of (...) the graduates in their studies. Findings disclosed that the graduates have a high level of attainment of the program's learning outcomes and a high level of satisfaction. The high school where the respondents graduated is the single variable that defined the difference in attainment of program intended learning outcomes. As to the graduates' introspections, themost significant percentage of them learned the program from family, relatives, and friends. Reasons for pursuing the degree program are because of parents’ influence, prestige of IT profession. Meanwhile, the university's reputation, affordable tuition fees, and proximity to home were the factors affecting the enrolment in the BSIT program. The findings will be the basis for strategic program interventions of the program. (shrink)

Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and reacts like humans, some of the computer activities with artificial intelligence are designed to 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 used as a (...) technique to produce brain tumor detection and classification models using Magnetic Resonance Imaging (MRI) imaging for rapid and easy detection and identification of brain tumor. In this thesis, some ways and mechanisms will be reviewed to use deep learning techniques to produce a model for brain tumor detection. The goal is to find a good and effective way to detect brain tumor based on MRI to help the brain doctor in making decisions easily, accurately and rapidly. A recent report by the World Health Organization in February 2018 showed that the death rate from brain cancer or central nervous system (CNS) is the highest in the Asian continent. It is important to detect cancer early so that many of these lives can be saved. The model has been designed and implemented, including a dataset which consist of 10,000 images for brain tumor detection through the use of Deep learning algorithms based on neural networks. For testing, we have used our model, Inception, VGG16, MobileNet and ResNet models. The f-score accuracy we got for each model was as follows: Our model was 98.28, VGG16 was 99.86%, ResNet50 was 98.14%, MobileNet was 88,98%, and InceptionV3 was 99.88%. (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)

Organizations are increasingly finding it challenging to balance economic and environmental performance particularly those that face competitive, regulatory and community pressure. With the increasing pressures for environmental sustainability, this calls for the new formulation of strategies by the manufacturers in order to minimize their products and services negative impact on the environment. Hence, Green Human Resource Management (GHRM) continues to be an important research agenda among the researchers. In Palestine, green issues are new and still developing. Constant study is needed (...) to fully understand and update information regarding this area. Objective: The aim of this paper is to explore the views and level of acceptance of GHRM practices among manufacturing firms in Palestine. Results: Through the use of e-mail survey, 121 responses were obtained to generate the results of the study. The result showed GHRM practices have been practiced to somewhat to a greater extent a firms in Palestine. Findings can be extended to study on the issues in further. Academicians and practitioners can apply this result to their research and business strategies on how to improve sustainable performance and to effectively implement GHRM practices. (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: Purpose - This study aimed to analyze the relationship between the determinants of organizational justice and their relationship to conscientious behavior from the point of view of officers working in the Palestinian police in Gaza Strip. Methodology - The study relied on the descriptive and analytical approach, using the questionnaire, targeting a stratified random sample of (400) officers, who hold the rank of captain and above, from the study population of 1550 officers. The study tool was distributed among the (...) sample members in all departments and governorates. Police in Gaza Strip. (353) questionnaires were retrieved, with a recovery rate of (88.3%). Findings - The existence of a positive correlation between the determinants of organizational justice and the behavior of conscience, and the existence of organizational justice in general in a medium degree and the order of its determinants is as follows: fairness of dealings and to a large degree, followed by fairness of procedures and a medium degree, and finally distribution fairness was to a small degree, while the behavior of conscience awareness came to a large extent. Significance - The existence of statistically significant differences between the respondents' averages of responding to the searched relationship due to the variables (type of administration, age group, job title, military rank, years of service). Recommendations - Work to take into account the fairness of distribution by providing adequate and fair salaries, granting bonuses for the additional efforts exerted, and budgeting in the distribution of duties and job burdens, as well as recommending attention to the interests of employees when making decisions and involving them in formulating them, explaining their justifications, and creating an organizational climate dominated by a sense of justice. (shrink)

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)

The past four decades of research in the social sciences have shed light on two important phenomena. One is that human decision-making is full of predicable errors and biases that often lead individuals to make choices that defeat their own ends (i.e., the bad choice phenomenon), and the other is that individuals’ decisions and behaviors are powerfully shaped by their environment (i.e., the influence phenomenon). Some have argued that it is ethically defensible that the influence phenomenon be utilized to address (...) the bad choice phenomenon. They propose that “choice architects” learn about the various ways in which choices can be influenced and directed by the environment, and then work to design environments, broadly construed, that influence individuals towards choices that make them better off. Those who advocate intentionally creating choice environments that lead people to better choices believe that doing so is ethically permissible because (1) it makes people better off, and (2) it does so in a way that is entirely compatible with individual liberty. The evaluation of these two claims is the main focus of this paper. (shrink)

Background: Persimmon is a grassy, perennial plant, belonging to the oral platoon, square-shaped leg, bifurcated, erect, and ranging in height from (10 - 201 cm). Home to Europe and Asia. The Persimmon plant has many benefits, the most important of which are pain relief, treatment of gallbladder disorders, the expulsion of gases, anti-inflammatory, and relaxing nerves. While the Persimmon plant is the ideal option for the start of gardens, it is prone to some common diseases that affect the plant's growth. (...) Objectives: The main goal of this expert system is to get the appropriate diagnosis of disease and the correct treatment. Methods: In this paper, the design of the proposed Expert System was produced to help Farmers and those interested in agriculture in diagnosing many of the Persimmon diseases such as Persimmon rust, Verticillium wilt, Anthracnose, Powdery mildew, Black Stem Rot, Stem and stolon canker, Septoria leaf spot. The proposed expert system presents an overview of Persimmon diseases are given, the cause of diseases 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 Persimmon diseases diagnosis expert system was evaluated by Agricultural Students at AL Azhar University and some friends interested in agriculture and they were satisfied with its performance. Conclusions: The proposed expert system is very useful for Farmers and those interested in agriculture. (shrink)

This essay represents a novel contribution to Nietzschean studies by combining an assessment of Friedrich Nietzsche’s challenging uses of “truth” and the “eternal return” with his insights drawn from Indian philosophies. Specifically, drawing on Martin Heidegger’s Nietzsche, I argue that Nietzsche’s critique of a static philosophy of being underpinning conceptual truth is best understood in line with the Theravada Buddhist critique of “self ” and “ego” as transitory. In conclusion, I find that Nietzsche’s “eternal return” can be understood as a (...) direct inversion of “nirvana”: Nietzsche celebrates profound attachment to each and every moment, independent from its pleasurable or distasteful registry. (shrink)

The study aimed at identifying responsive flexibility and its role in improving service quality, from the point of view of the internal beneficiary in non-governmental hospitals in Gaza Strip. The study relied on the descriptive and analytical approach, and the questionnaire was designed as a tool to collect data, and the researchers used the comprehensive survey method, and the number of the study population was (536) single, where (434) questionnaires were retrieved, and the recovery rate was (80.97%). The study showed (...) many results, the most important of which were: The presence of moderate degree of approval by the study sample on the responsive flexibility, as it was evident through the response flexibility field obtaining a relative weight (60.50%), and the results of the study indicated that there is a high degree of approval by the members of the study sample. On the quality of service, as it was evident through the field of service quality obtaining a relative weight (79.90%). The results of the study revealed a statistically significant relationship between responsive flexibility and service quality in non-governmental hospitals in Gaza Strip, with a correlation coefficient of 0.418, and the results of the study revealed a statistically significant effect between responsive flexibility and service quality in non-governmental hospitals in Gaza Strip. The study reached many recommendations, the most important of which were: Finding mechanisms by which stored information can be used to enhance the decision-making process, and setting up an effective system to receive patients' complaints in a manner that ensures rapid response and treatment, to achieve continuous communication between patients and the hospital management, and to notify patients of abuse With the complaints that they submit, and working to provide all medical and health specialties in the hospitals under study, by making use of the medical delegations that visit Gaza Strip, involving them in the treatment processes, bringing in doctors and specialists from abroad, and updating the standards related to measuring the services provided to patients continuously, based on On patients' suggestions and complaints, developing facilities in hospitals, as well as updating medical devices and equipment used in hospitals periodically. (shrink)

Identification of factors that predict recurrent antisocial behavior is integral to the social sciences, criminal justice procedures, and the effective treatment of high-risk individuals. Here we show that error-related brain activity elicited during performance of an in- hibitory task prospectively predicted subsequent rearrest among adult offenders within 4 y of release (N =96). The odds that an offender with relatively low anterior cingulate activity would be rearrested were approximately double that of an offender with high activity in this region, holding (...) constant other observed risk factors. These results suggest a potential neurocognitive biomarker for persistent antisocial behavior. (shrink)

This paper proposes a philosophically informed decision-making methodology, inspired by Aristotle, that encourages constructive discussions amongst employers and employees; is directed towards shared higher-level goals; is consistent with planning frameworks already in place in many businesses; can be amended over time without disruptive disputes; and accounts for the particularities of each industry, enterprise, workplace, and job. It seeks to establish a more fundamental basis for discussions about remote vs. in-person office work: specifically, the purpose and nature of the work of (...) those affected. If these matters can be decided, then subsequent discussions might be focused more upon the shared outcomes to which stakeholders are committed and less upon individual preferences and ‘hunches.’. (shrink)

Abstract: This study aims to identify the level of creativity in the University of Palestine from the point of view of the employees, as the researchers used the descriptive and analytical method, through a questionnaire distributed to a sample of employees at the University of Palestine, where the size of the study population is (234) employees, and the size of the sample (117) employees, of which (90) employees responded. The study reached a set of results, the most important of which (...) are: A high degree of creativity from the employees 'point of view, and the study confirmed that there were no differences in the level of creativity at the University of Palestine from the Employees point of view, according to demographic variables. The study presented a set of recommendations, the most important of which are: The need for universities to enhance creativity. (shrink)

Teachers are the frontline workers in sustaining quality education; hence, assessing their knowledge, attitudes, and behaviors (KAB) allows them and the administrators to create better training, programs, and instructional materials. The objective is to develop and validate a quick and accessible online instrument to assess the teachers’ KAB towards sustainable development in the Philippine context, as part of a bigger project to integrate Pili (Canarium ovatum) into education. The researchers administered the instrument using a cross-sectional survey method through Google Forms (...) in which respondents (n = 206) had voluntarily answered. The 24-item tool, anchored on the 2030 sustainable development goals and their complex systems, is reliable and valid based on the confirmatory factor analysis, and Cronbach’s alpha and Fleiss’s kappa estimates. The results showed that having favorable knowledge and attitudes toward sustainable development is inadequate to create positive behaviors. The adaptation of the developed instrument, the use of findings for intercultural and cross-cultural studies, and further investigations are recommended. (shrink)