Patch-based Denoising Algorithms for Single and Multi-view Images

In general, all single and multi-view digital images are captured using sensors, where they are often contaminated with noise, which is an undesired random signal. Such noise can also be produced during transmission or by lossy image compression. Reducing the noise and enhancing those images is among the fundamental digital image processing tasks. Improving the performance of image denoising methods, would greatly contribute to single or multi-view image processing techniques, e.g. segmentation, computing disparity maps, etc. Patch-based denoising methods have recently emerged as the state-of-the-art denoising approaches for various additive noise levels. This thesis proposes two patch-based denoising methods for single and multi-view images, respectively. A modification to the block matching 3D algorithm is proposed for single image denoising. An adaptive collaborative thresholding filter is proposed which consists of a classification map and a set of various thresholding levels and operators. These are exploited when the collaborative hard-thresholding step is applied. Moreover, the collaborative Wiener filtering is improved by assigning greater weight when dealing with similar patches. For the denoising of multi-view images, this thesis proposes algorithms that takes a pair of noisy images captured from two different directions at the same time (stereoscopic images). The structural, maximum difference or the singular value decomposition-based similarity metrics is utilized for identifying locations of similar search windows in the input images. The non-local means algorithm is adapted for filtering these noisy multi-view images. The performance of both methods have been evaluated both quantitatively and qualitatively through a number of experiments using the peak signal-to-noise ratio and the mean structural similarity measure. Experimental results show that the proposed algorithm for single image denoising outperforms the original block matching 3D algorithm at various noise levels. Moreover, the proposed algorithm for multi-view image denoising can effectively reduce noise and assist to estimate more accurate disparity maps at various noise levels

American and Iraqi Prose Fiction of the Iraq War: Traumas of the Self, Traumas of the Nation

War is so omnipresent in our contemporary world that the story of war is too important to be left to fiction writers to frame and give meaning for. This dissertation provides an analysis of two dominant patterns in contemporary Iraqi and American prose fictional representations of the Iraq War: the individualistic trauma hero narrative and the nationalistic, collective narrative. I argue that the trauma hero myth that dominates American representations of the Iraq War psychologizes and de-politicizes war experience alienating the victim of trauma by decontextualizing their experience and negating the Other. On the other hand, the sweeping nationalistic narrative in Iraqi war writing overstates the political dimension of the war experience of Iraqis, representing them as collectivities under war, which negates their individual experiences as mere trajectories for the collective trauma of the nation. These two narrative patterns epistemologically disserve readers by mystifying war and framing war experience according to different ideological agenda. Examining the Iraqi and American literary traditions of war writing before and after 2003, the dissertation contextualizes the development of these patterns exposing their discursive limitations. Reading Iraqi and American narratives of the Iraq War against each other provides a comparative understanding of the war experience from opposite sides. In addition to reading the texts as narratives and counternarratives of certain ideological constructions of the war story, I examine texts that exemplify these patterns and others that oppose and undermine them creatively. I read selected novels and short story collections that represent civilian and military people’s perspectives on the war. I find similar tropes, stereotypes and some genuine intercultural connections in the texts and the cultures they come from. The study highlights how this literature can help veterans and non-military individuals navigate their war traumas and restore their sense of identity and meaning to their lives. However, I stress the critical drawback of indulging in cultures that perpetuate trauma and alienate individuals to serve the existing power structures. Studying the literature of the Iraq War comparatively is necessary for a cross-cultural understanding of the human experience of war and for a productive cultural conversation to emerge

Intelligent data-driven decision-making to mitigate or stop lost circulation

”Lost circulation is a challenging problem in the oil and gas industry. Each year, millions of dollars are spent to mitigate or stop this problem. The aim of this work is to utilize machine learning and other intelligent solutions to help to make better decision to mitigate or stop lost circulation. A detailed literature review on the applications of decision tree analysis, expected monetary value, and artificial neural networks in the oil and gas industry was provided. Data for more than 3000 wells were gathered from many sources around the world. Detailed economics and probability analyses for lost circulation treatments’ strategies were conducted for three formations in southern Iraq which are the Dammam, Hartha, and Shuaiba formations. Multiple machine learning methods such as support vector machine, decision trees, logistic regression, artificial neural networks, and ensemble trees were used to create models that can predict lost circulation and recommend the best lost circulation treatment based on the type of loss and reason of loss. The results showed that the created models can predict lost circulation and recommend the best lost circulation strategy within a reasonable margin of error. The created models can be used globally which avoids the shortcoming in the literature. Intelligence solutions and machine learning have proven their applicability to solve complicated problems and make better future decisions. With the large data available in the oil and gas industry, these methods can help the decision-makers to make better future decisions that will save time and money”--Abstract, page iv

A comprehensive analysis of lost circulation materials and treatments with applications in Basra\u27s oil fields, Iraq: Guidelines and recommendations

Lost circulation materials (LCM\u27s) have been widely used to avoid or stop losses. Due to a large number of current available LCM\u27s and their different applications, classification of LCM\u27s is very important. The most recent LCM classification was published around 50 years ago, and this paper intends to fill this gap with an updated classification including conventional and new technologies. Lost circulation materials and treatments are re-classified into various categories based on their appearance, applications, chemical and physical properties. Wells in Basra\u27s oil fields are highly susceptible to lost circulation problems when drilling through the Dammam, Hartha, and Shuaiba formations. This paper discusses the most recent treatments, which are used in Basra\u27s fields with integrated analysis and updated classification. In addition, the best lost circulation strategy of remedies will be presented to mitigate or stop this problem. Sometimes it is difficult to regulate mud losses by using conventional lost circulation materials. Also, the cost of these materials are expensive, so it is important to find techniques and mechanism to live with some degree of losses. This work will also demonstrate methods that were used to ameliorate lost circulation without the use of lost circulation materials like liner hanger and casing-while-drilling, floating mud cap drilling, aerated mud, foam, air or mist with cases histories in Basra\u27s fields. This paper discusses the most recent developments in lost circulation materials and treatments, in addition to the presentation of a comprehensive summary of today\u27s available LCM\u27s, treatments and alternative approaches with their applications --Abstract, page iv

Models of training needs assessment for the Iraqi construction industry

Construction companies are the engines that drive a nation’s economy and must train their workforce effectively to enhance their performance. It has been recognised that training is the most effective tool for improving the performance and efficiency of the construction workforce; practitioners, academics, government agencies, professional institutions and clients of the construction industry all agree. In recognition of this, the industry must endeavour to provide a truly professional service or product, which is qualitatively superior and gives value for money. The on-going skills deficiency in the Iraqi construction industry calls for urgent remedies, of which training is one solution which is becoming an important issue in this sector at present. The aim of the present research is to develop models that will help to assess skills and knowledge needs for the Iraqi construction industry. This research is also concerned with finding an appropriate body of skills and knowledge related to the Iraqi construction industry, based on what construction site managers, project managers, civil engineers and architects actually do; how they perceive the importance of such tasks now and in the future. This study explains all of the issues concerning TNA practices in terms of how TNA is conducted, i.e., how training needs are assessed and how assessment is delivered. This study also investigates all the drivers and challenges that face TNA activities. The perception of the importance of the TNA outcome is also considered. This research is mainly focused on construction engineers: site managers, civil engineers, project leaders and architects; their attitudes, perceptions and viewpoints towards the research objectives.The data presented is derived from a study of 239 Iraqi construction employees and subsequently analysed using the Statistical Package for Social Science (SPSS) software. This study reveals that the level of adoption of organizational training needs assessment procedures among training managers in the selected organizations is moderately high. However, the level of adoption of occupational and individual training needs assessment is lower. Most training managers are using surveys or interviews as methods to solicit information for training needs assessment purposes. The job analysis method is occasionally used in conducting training needs assessment, while measurement of the knowledge and skills of individuals is seldom done. It is also indicated that the respondents agree that training should be focused mostly on project management skills and site management administration knowledge; priority must be given to training needs through performance appraisal and site visits. The author thinks that the findings of this study might face an uphill struggle, in trying to get it accepted and then taken on-aboard by the construction industry. Nevertheless, there are strong and powerful signs (or at least a very strong indicators) of economic improvement in Iraq, that makes this study an important and extremely relevant lever, in the process of such economic improvement.To the best of the researcher’s knowledge, this study will be the first of its kind in the Iraqi construction industry to be undertaken. The findings will enrich the existing literature on the quality of training programmes in the construction industry and fill the gaps in knowledge of studies on Iraq in particular. This study makes a contribution to knowledge on both the academic and practical levels. It raises the general understanding of the current TNA practices and management in the Iraqi construction industry. It has brought together a large body of knowledge on construction management problems in Iraq, TNA in Arab countries and combined a variety of schools of thought into one integrated model. This research integrates, refines and extends the empirical work conducted in the field of TNA in Iraq, since until the present there has been a lack of such studies in this country. It is hoped that the outcome of this research will lead to a better understanding of the need for training construction engineers in Iraq and will encourage other researchers to extend this study through further work

Clarity and Visual Ratios of the Vibrant Place Making

One of the most important components of the city is the place, which generates interest in it being the city’s basic urban structure, This concern has led to the emergence of a new concept, the placemaking, where the concept of placemaking is not based on the dimensions of physical space, but also focuses on social dimensionsand the satisfaction of the population and their wishes and needs, And emerged several trends for the urban placemaking, and because the center of the city of Diwaniya suffers from neglect and deterioration and the migration of activities to the outskirts of the city, Where it is necessary to find a trend that reinvigorates thecenter, which is the orientation of the vibrant placemaking, which deals exclusively with the centers of cities and combines within it several other directions for the placemaking, The problem of research is reflected in the lack of clarity of the relationship between urban planning and urban design and the assumption that the relationship between design and urban planning is produced through the vibrant placemaking, and in order to determine the relationship and build indicators from the relationship between urban planning and urban design for the vibrant placemaking, The main vocabulary, which has been tested with the tasks and objectives of urban planning and urban design standards to extract the final indicators, which interact as a system and integrated unit, Two quantitative indicators, which are directly measurable and qualitative indicators, measured by the questionnaire, And the most important conclusions and recommendations increase the amount of diversity in activities and intensities and exclusion of inappropriate uses and attention to individuals and buildings heritage and the positive interaction resulting from the establishment of rituals, which creates perception and memory Assembly, Enhancing the spatial character through the human scale, adopting a clear methodology for urban development, preparing detailed plans, raising the functional efficiency of the planningstaff, and attracting large investments for the purpose of the vibrant placemaking in the city center of Diwaniyah city

TALAQIY AL-TAGHRIDAH AL-SYI’RIYAH HISAB AL-SYA’IR MOHAMMED ALMOQREN ANMUDZAJAN

This contemporary age faced large technical revolutions which have huge effects on all life areas. These technical revolutions cause dramatic changes in human natures particularly in terms of consumptions and communication. Therefore, the literature and its branches could not be separated from these technical age influences as the literature interacted with these evolutionary products and employed this age resources. Therefore, the focus of this study was the perception of poetical tweets on a Twitter account belonged to a poet namely Mohammed Almoqren. The steps of this study covered interjection, rerouting, written interaction, contradiction, visual shaping, dynamic shaping, summary and conclusion

FruitPAL: An IoT-Enabled Framework for Automatic Monitoring of Fruit Consumption in Smart Healthcare

This research proposes FruitPAL and FruitPAL 2.0. They are full automatic devices that can detect fruit consumption to reduce the risk of disease. Allergies to fruits can seriously impair the immune system. A novel device (FruitPAL) detecting fruit that can cause allergies is proposed in this thesis. The device can detect fifteen types of fruit and alert the caregiver when an allergic reaction may have happened. The YOLOv8 model is employed to enhance accuracy and response time in detecting dangers. The notification will be transmitted to the mobile device through the cloud, as it is a commonly utilized medium. The proposed device can detect the fruit with an overall precision of 86%. FruitPAL 2.0 is envisioned as a device that encourages people to consume fruit. Fruits contain a variety of essential nutrients that contribute to the general health of the human body. FruitPAL 2.0 is capable of analyzing the consumed fruit and then determining its nutritional value. FruitPAL 2.0 has been trained on YOLOv5 V6.0. FruitPAL 2.0 has an overall precision of 90% in detecting the fruit. The purpose of this study is to encourage fruit consumption unless it causes illness. Even though fruit plays an important role in people's health, it might cause dangers. The proposed work can not only alert people to fruit that can cause allergies, but also it encourages people to consume fruit that is beneficial for their health

Application of Artificial Neural Networks in the Drilling Processes: Can Equivalent Circulation Density Be Estimated Prior to Drilling?

As the drilling environment became more challenging nowadays, managing equivalent circulating density (ECD) is a key factor to minimize non-productive time (NPT) due to many drilling obstacles such as stuck pipe, formation fracturing, and lost circulation. The goal of this work was to predict ECD prior to drilling by using artificial neural network (ANN). Once ECD is recognized, the crucial drilling variables impact ECD can be modified to control ECD within the acceptable ranges. Data from over 2000 wells collected worldwide were used in this study to create an ANN to predict ECD prior to drilling. Into training, validation, and testing sets, the data were splitted. 70% of the data utilized for training, the other part used for validation and testing to avoid overfitting and create a generalized network that can perform well on new data. Based on the mean square of error (MSE), a decision was made to have one hidden layer with twelve neurons, this scenario was selected since it gave the lowest MSE among other scenarios. Multiple training functions were tested to train the network, Bayesian regularization (BR) algorithm was chosen from the other algorithms since it had the lowest MSE and the highest R-squared. After optimizing the weights and biases, the results revealed that the created network has the ability to estimate ECD with an overall R-squared of 0.982, which is very high. This result gives an indication that the created network can predict ECD prior to drilling globally within a very small margin of error. Due to the availability of large historical data sets in the petroleum industry, the ANN can be used to make better future decisions to minimize NPT and the cost of drilling