Search results for: deep wells

Authors: Fatima Al-Aswadi, Chan Yong

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With the large volume of unstructured data that increases day by day on the web, the motivation of representing the knowledge in this data in the machine processable form is increased. Ontology is one of the major cornerstones of representing the information in a more meaningful way on the semantic Web. The goal of Ontology learning from text is to elicit and represent domain knowledge in the machine readable form. This paper aims to give a follow-up review on the ontology learning systems from text and some of their defects. Furthermore, it discusses how far the ontology learning process will enhance in the future.

Keywords: concept discovery, deep learning, ontology learning, semantic relation, semantic web

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Authors: Tapas Acharya, Monalisa Mitra

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Overlay modeling is the most widely used conventional analysis for spatial decision support system. Overlay modeling requires a set of themes with different weightage computed in varied manners, which gives a resultant input for further integrated analysis. In spite of the popularity and most widely used technique; it gives inconsistent and erroneous results for similar inputs while processed in various GIS overlay techniques. This study is an attempt to compare and analyse the differences in the outputs of different overlay methods using GIS platform with same set of themes of the Precambrian metamorphic to obtain groundwater prospecting in Precambrian metamorphic rocks. The objective of the study is to emphasize the most suitable overlay method for groundwater prospecting in older Precambrian metamorphics. Seven input thematic layers like slope, Digital Elevation Model (DEM), soil thickness, lineament intersection density, average groundwater table fluctuation, stream density and lithology have been used in the spatial overlay models of fuzzy overlay, weighted overlay and weighted sum overlay methods to yield the suitable groundwater prospective zones. Spatial concurrence analysis with high yielding wells of the study area and the statistical comparative studies among the outputs of various overlay models using RStudio reveal that the Weighted Overlay model is the most efficient GIS overlay model to delineate the groundwater prospecting zones in the Precambrian metamorphic rocks.

Keywords: fuzzy overlay, GIS overlay model, groundwater prospecting, Precambrian metamorphics, weighted overlay, weighted sum overlay

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Authors: Raúl García de la Cruz

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In the state of Hidalgo and to the vicinity to the state of Mexico, there is a network of people who also share a valley bordered by hills with agave landscape of cacti and shared a bond of building traditions inherited from pre-Hispanic times and according to their material resources, habits and needs have been adapted in time. Weather has played an important role in the way buildings and roofs are constructed. Throughout the centuries, the population has developed very sophisticated building techniques like the flat roof, made out of a layer of earth; that is usually identified as belonging to architecture of the desert, but it can also be found in other climates, such as semi-arid and even template climates. It is an example of a constructive logic applied efficiently to various cultures proving its thermal isolation. So far it has done a review and analysis of the use of the roof in different areas, from pre-Hispanic architecture to traditional Moroccan architecture , finding great similarities in the elements of the system to be incorporated into the contemporary architecture. The rescue of a lore that dissolves with the changing environment, depends in principle on the links created towards the use of environmental resources as the anchor of the people to retain and preserve a building tradition which has viability deep league with the possibility of obtaining the raw material from the immediate environment. The objective of the research is the documentation of existing earth flat roofs in the state of Hidalgo and Mexico, as evidence of the importance of constructive system and its historical value in the area, considering its environmental, social aspects, also understanding the process of transformation of public housing at the time replaced the traditional techniques for industrial materials on a path towards urbanization. So far it has done a review and analysis of the use of the roof in different areas, from pre-Hispanic architecture to traditional Moroccan architecture, finding great similarities in the elements of the system to be incorporated into the contemporary architecture. The rescue of a lore that dissolves with the changing environment, depends in principle on the links created towards the use of environmental resources as the anchor of the people to retain and preserve a building tradition which has viability deep league with the possibility of obtaining the raw material from the immediate environment.

Keywords: earth roof, low impact building system, sustainable architecture, vernacular architecture

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Authors: Sebahat Seker

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Since there is a parallel connection between drinking water quality and public health, studies on drinking and domestic water are of vital importance. Ardahan Province is one of the provinces located in the Northeast Anatolian Region, where animal husbandry and agriculture are carried out economically. City mains water uses underground spring water as a source and is chlorinated and given to the city center by gravity. However, mains water cannot be used outside the central district of the city, and the majority of the people meet their drinking and utility water needs from the wells they have opened individually. The water element, which is vital for all living things, is the most important substance that sustains life for humans. Under normal conditions, a healthy person consumes approximately 1.8-2 liters of water. The quality and use of potable water is one of the most important issues in terms of health. The quality parameters of drinking and utility water have been revealed by the scientific world. Scientific studies on drinking water quality in the world and its impact on public health are among the most popular topics. Although our country is surrounded by water on three sides, potable water resources are very few. In the Eastern Anatolia Region, it is difficult for the public to access drinking and utility water due to the difficult conditions both climatically and geographically. In this study, samples taken from drinking and utility water at certain intervals from the stations determined, and water quality parameters will be determined. The fact that such a study has not been carried out in the region before and the knowledge of the local people about water quality is very important in terms of its original and widespread effect.

Keywords: water quality, modelling, evaluation, northeastern anatolia

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Authors: Ali Haratian, Soroosh Emami Meybodi

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Using viable microbial cultures within hydrocarbon reservoirs so as to the enhancement of oil recovery through metabolic activities is exactly what we recognize as microbial enhanced oil recovery (MEOR). In similar to many other processes in industries, there are some cons and pros following with MEOR. The creation of sulfides such as hydrogen sulfide as a result of injecting the sulfate-containing seawater into hydrocarbon reservoirs in order to maintain the required reservoir pressure leads to production and growth of sulfate reducing bacteria (SRB) approximately near the injection wells, turning the reservoir into sour; however, SRB is not considered as the only microbial process stimulating the formation of sulfides. Along with SRB, thermochemical sulfate reduction or thermal redox reaction (TSR) is also known to be highly effective at resulting in having extremely concentrated zones of ?2S in the reservoir fluids eligible to cause corrosion. Owing to extent of the topic, more information on the formation of ?₂S is going to be put finger on. Besides, confronting the undesirable production of sulfide species in the reservoirs can lead to serious operational, environmental, and financial problems, in particular the transporting pipelines. Consequently, conjuring up reservoir souring control strategies on the way production of oil and gas is the only way to prevent possible damages in terms of environment, finance, and manpower which requires determining the compound’s reactivity, origin, and partitioning behavior. This article is going to provide a comprehensive review of progress made in this field and the possible advent of new strategies in this technologically advanced world of the petroleum industry.

Keywords: corrosion, hydrogen sulfide, NRB, reservoir souring, SRB

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Authors: Dilek Yalız Solmaz

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Meta-cognition is an important factor for educating conscious individuals who are aware of their cognitive processes. With this respect, the purposes of this article is to find out the perceived metacognition level of Physical Education and Sports School students at Anadolu University and to identify whether metacognition levels display significant differences in terms of various variables. 416 Anadolu University Physical Education and Sports School students were formed the research universe. "The Meta-Cognitions Questionnaire (MCQ-30)" developed by Cartwright-Hatton and Wells and later developed the 30-item short form (MCQ-30) was used. The MCQ-30 which was adapted into Turkish by Tosun and Irak is a four-point agreement scale. In the data analysis, arithmethic mean, standard deviation, t-test and ANOVA were used. There is no statistical difference between mean scores of uncontrollableness and danger, cognitive awareness, cognitive confidence and the positive beliefs of girls and boys students. There is a statistical difference between mean scores of the need to control thinking. There is no statistical difference according to departments of students between mean scores of uncontrollableness and danger, cognitive awareness, cognitive confidence, need to control thinking and the positive beliefs. There is no statistical difference according to grade level of students between mean scores of the positive beliefs, cognitive confidence and need to control thinking. There is a statistical difference between mean scores of uncontrollableness and danger and cognitive awareness.

Keywords: meta cognition, physical education, sports school students, thinking

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Authors: Athena Johnson

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Veganism has seen a rapid increase in members over recent years. Understanding the mechanisms of social change associated with these dietary practices in relation to gender is significant as these groups may seem small, but they have a large impact as they influence many and change the food market. This research article's basic methodology is primarily a deep article research literature review with empirical research. The research findings show that the popularity of veganism is growing, in large part due to the extensive use of social media, which dispels longstanding gendered connotations with food, such as the correlations between meat and masculinity.

Keywords: diversity, gender roles, social media, veganism

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Authors: Madhavi S. Apte, Milind Bhitre

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In pharmaceutical research and new drug development, medicinal plants have important roles. Similarly, Indian dhak tree belonging to family Fabaceae has been widely used in the traditional Indian medical system of ‘Ayurveda’ for the treatment of a variety of ailments. Hence the cell viability study was undertaken to evaluate and compare the activity of extracts of various parts like flower, bark, leaf, seed by conducting MTT assay method along with other pharmacognostical studies. The methanolic extracts of bark, flowers, leaves, and seeds were used for the study. The cell viability MTT assay was performed using the standard operating procedures. The extracts were dissolved in DMSO and serially diluted with complete medium to get the concentrations range of test concentration. DMSO concentration was kept < 0.1% in all the samples. HUVEC cells maintained in appropriate conditions were seeded in 96 well plates and treated with different concentrations of the test samples and incubated at 37°C, 5% CO₂ for 96 hours. MTT reagent was added to the wells and incubated for 4 hours; the dark blue formazan product formed by the cells was dissolved in DMSO under a safety cabinet and read at 550nm. Percentage inhibitions were calculated and plotted with the concentrations used to calculate the IC50 values. The bark, flower, leaves and seed extracts have shown the cytotoxicity activity and can be further studied for antiangiogenesis activity.

Keywords: pharmacognosy, Cell viability, MTT assay, anti-angiogenesis

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Authors: Maisarah Jaafar, Neil I. Ward

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Volcanic and geothermal activity can result in the release of arsenic (As), manganese (Mn), iron, selenium (Se), molybdenum (Mo) and uranium (U) into natural waters. Several studies have reported high levels of these elements in surface and groundwater in Argentina. The main focus has been on As associated with volcanic ash deposits. This study reports the trace element levels of groundwater from an agricultural region of south-eastern La Pampa and southern Buenos Aires provinces, Argentina which have reported high levels of human health problems (bone/teeth disorders, depression, arthritis, etc). Fifty-eight groundwater samples were collected from wells adjacent to Ruta 35 and an Agilent 7700x inductively coupled plasma mass spectrometer (ICP-MS) were used for total elemental analysis. Physicochemical analysis confirmed pH range of 7.05-8.84 and variable conductivity (988-3880 µS/cm) with total dissolved solid content of 502-1989 mg/l. The majority water samples are in an oxidizing environment (Eh= 45-146 mV). Total As levels ranged from (µg/l): 13.08 – 319.4 for La Pampa (LP) and 39.6 – 189.4 for Buenos Aires (BA); all above the WHO Guideline for Drinking Water, 10 µg/l As. Interestingly, Mo (LP: 1.85 – 85.39 µg/l; BA: 4.61– 55.55 µg/l;), Se (LP: 1.2 – 16.59 µg/l; BA: 0.3– 6.94 µg/l;) and U (LP: 1.85 – 85.39 µg/l; BA: 4.61– 55.55 µg/l;) levels are lower than reported values for northern La Pampa. Inter-elemental correlation displayed positive statistically significant between As-Mo, A-Se, As-U while negative statistically significant between As-Mn and As-Fe. This confirms that the source of the trace element is similar to that reported for other region of Argentina, namely volcanic ash deposition.

Keywords: Argentina, groundwater, trace element, volcanic activity

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Authors: Constanza Levicán, Andrés Aparicio, Rodrigo F. Cádiz

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The artistic usage of Brain-computer interfaces (BCI), initially intended for medical purposes, has increased in the past few years as they become more affordable and available for the general population. One interesting question that arises from this practice is whether it is possible to compose or perform music by using only the brain as a musical instrument. In order to approach this question, we propose a BCI for musical composition, based on the representation of some mental states as the musician thinks about sounds. We developed software, called Insight2OSC, that allows the usage of the Emotiv Insight device as a musical instrument, by sending the EEG data to audio processing software such as MaxMSP through the OSC protocol. We provide two compositional applications bundled with the software, which we call Mapping your Mental State and Thinking On. The signals produced by the brain have different frequencies (or rhythms) depending on the level of activity, and they are classified as one of the following waves: delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), beta (13-30 Hz), gamma (30-50 Hz). These rhythms have been found to be related to some recognizable mental states. For example, the delta rhythm is predominant in a deep sleep, while beta and gamma rhythms have higher amplitudes when the person is awake and very concentrated. Our first application (Mapping your Mental State) produces different sounds representing the mental state of the person: focused, active, relaxed or in a state similar to a deep sleep by the selection of the dominants rhythms provided by the EEG device. The second application relies on the physiology of the brain, which is divided into several lobes: frontal, temporal, parietal and occipital. The frontal lobe is related to abstract thinking and high-level functions, the parietal lobe conveys the stimulus of the body senses, the occipital lobe contains the primary visual cortex and processes visual stimulus, the temporal lobe processes auditory information and it is important for memory tasks. In consequence, our second application (Thinking On) processes the audio output depending on the users’ brain activity as it activates a specific area of the brain that can be measured using the Insight device.

Keywords: BCI, music composition, emotiv insight, OSC

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Authors: Ahmad Aridah, Maria Fay Rola-Rubzen, Zora Singh

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This study investigated the effectiveness of various types of irrigation systems in regards to the impact that these have on the productivity of date palms in the semi-arid and arid region of Sebha, Southwest Libya. The date palm is an economically important crop in Libya and contributes to the agriculture industry, foreign exchange earnings, farmers’ income, and employment in the country. The date palm industry relies on large amounts of water for growing the crop. Farmers in Southwest Libya use a variety of irrigation systems, but the quality and quantity of water varies between systems and this affects the productivity and income of farmers. Using survey data from 210 farmers, this study estimated and assessed the pros and cons of different types of irrigation systems for date palm production under various irrigation systems currently used in Sebha, Libya. The number of years farmers have used irrigation, the area, irrigation water consumption, time of irrigation, number of farm workers (including family labour) and inputs used were measured for surface, sprinkler and drip irrigation methods. Findings from this research provide new insights into the advantages and disadvantages of the various irrigation systems, problems encountered by farmers and the factors that affect the quality and quantity of the irrigation system. The paper discussed proposed solutions to deal with the problems including timing of irrigation, canal maintenance, repair of wells and water control.

Keywords: Libya, factors, irrigation method, date palm

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Authors: Anoop T. R., Otman Basir, Robert F. Hess, Eileen E. Birch, Brooke A. Koritala, Reed M. Jost, Becky Luu, David Stager, Ben Thompson

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Strabismus refers to a misalignment of the eyes. Early detection and treatment of strabismus in childhood can prevent the development of permanent vision loss due to abnormal development of visual brain areas. We developed a two-stage method for strabismus detection and classification based on photographs of the face. The first stage detects the presence or absence of strabismus, and the second stage classifies the type of strabismus. The first stage comprises face detection using Haar cascade, facial landmark estimation, face alignment, aligned face landmark detection, segmentation of the eye region, and detection of strabismus using VGG 16 convolution neural networks. Face alignment transforms the face to a canonical pose to ensure consistency in subsequent analysis. Using facial landmarks, the eye region is segmented from the aligned face and fed into a VGG 16 CNN model, which has been trained to classify strabismus. The CNN determines whether strabismus is present and classifies the type of strabismus (exotropia, esotropia, and vertical deviation). If stage 1 detects strabismus, the eye region image is fed into stage 2, which starts with the estimation of pupil center coordinates using mask R-CNN deep neural networks. Then, the distance between the pupil coordinates and eye landmarks is calculated along with the angle that the pupil coordinates make with the horizontal and vertical axis. The distance and angle information is used to characterize the degree and direction of the strabismic eye misalignment. This model was tested on 100 clinically labeled images of children with (n = 50) and without (n = 50) strabismus. The True Positive Rate (TPR) and False Positive Rate (FPR) of the first stage were 94% and 6% respectively. The classification stage has produced a TPR of 94.73%, 94.44%, and 100% for esotropia, exotropia, and vertical deviations, respectively. This method also had an FPR of 5.26%, 5.55%, and 0% for esotropia, exotropia, and vertical deviation, respectively. The addition of one more feature related to the location of corneal light reflections may reduce the FPR, which was primarily due to children with pseudo-strabismus (the appearance of strabismus due to a wide nasal bridge or skin folds on the nasal side of the eyes).

Keywords: strabismus, deep neural networks, face detection, facial landmarks, face alignment, segmentation, VGG 16, mask R-CNN, pupil coordinates, angle deviation, horizontal and vertical deviation

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Authors: Alona Faktor

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In this work, we present a NN-based computational model that can perform attention shifts according to high-level instruction. The instruction specifies the type of attentional shift using explicit geometrical relation. The instruction also can be of cognitive nature, specifying more complex human-human interaction or human-object interaction, or object-object interaction. Applying this approach sequentially allows obtaining a structural description of an image. A novel data-set of interacting humans and objects is constructed using a computer graphics engine. Using this data, we perform systematic research of relational segmentation shifts.

Keywords: cognitive science, attentin, deep learning, generalization

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Authors: Atif Zafar, Fan Haijun

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A sequence of different Reservoir Engineering methods and tools in reservoir characterization and field development are presented in this paper. The real data of Jin Gas Field of L-Basin of Pakistan is used. The basic concept behind this work is to enlighten the importance of well test analysis in a broader way (i.e. reservoir characterization and field development) unlike to just determine the permeability and skin parameters. Normally in the case of reservoir characterization we rely on well test analysis to some extent but for field development plan, the well test analysis has become a forgotten tool specifically for locations of new development wells. This paper describes the successful implementation of well test analysis in Jin Gas Field where the main uncertainties are identified during initial stage of field development when location of new development well was marked only on the basis of G&G (Geologic and Geophysical) data. The seismic interpretation could not encounter one of the boundary (fault, sub-seismic fault, heterogeneity) near the main and only producing well of Jin Gas Field whereas the results of the model from the well test analysis played a very crucial rule in order to propose the location of second well of the newly discovered field. The results from different methods of well test analysis of Jin Gas Field are also integrated with and supported by other tools of Reservoir Engineering i.e. Material Balance Method and Volumetric Method. In this way, a comprehensive way out and algorithm is obtained in order to integrate the well test analyses with Geological and Geophysical analyses for reservoir characterization and field development. On the strong basis of this working and algorithm, it was successfully evaluated that the proposed location of new development well was not justified and it must be somewhere else except South direction.

Keywords: field development plan, reservoir characterization, reservoir engineering, well test analysis

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Authors: Maged El Osta, Milad Masoud

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Al Jabal Al Akhdar in the north-eastern part of Libya represents a region with promising ecological underpinning for grazing and other agricultural developments. The groundwater potential of both Upper Cretaceous and Eocene aquifers was studied based the available literature and a complete database for about 112 water wells drilled in the period 2003-2009. In this research, the hydrogeological methods will be integrated with the Geographic Information System (GIS) that played a main role in highlighting the spatial characteristics of the groundwater system. The results indicate that the depth to water for the Upper Cretaceous aquifer ranges from 150 to 458 m, and the piezometric surface decreases from over 500 m (m.s.l) in the northern parts to -20 m (m.s.l) in southeastern part. Salinity ranges between 303 and 1329 mg/l indicating that groundwater belongs to the slightly fresh water class. In the Eocene aquifer, the depth to groundwater ranges from 120 to 290.5 m and the potentiometric level decreases gradually southwards from 220 to -51 m (m.s.l) and characterized by steep slope in the southeastern part of the study area, where the aquifer characterized by relatively high productivity (specific capacity ranges between 10.08 and 332.3 m2/day). The groundwater salinity within this aquifer ranges between 198 and 2800 mg/l (fresh to brackish water class). The annual average rainfall (from 280 to 500 mm) plays a significant role in the recharge of the two aquifers. The priority of groundwater quality and potentiality increases towards the central and northern portions of the concerned area.

Keywords: Eocene and Upper Cretaceous aquifers, rainfall, potentiality, Geographic Information System (GIS)

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Authors: Isahakyan Heghine

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Intertextuality, being in the centre of attention of both linguists and literary critics, is vividly expressed in the outstanding British novelist and philosopher J. Fowles' works. 'The Magus’ is a deep psychological and philosophical novel with vivid intertextual links with the Greek mythology and authors from different epochs. The aim of the paper is to show how intertextuality might serve as a dialogue between two authors (J. Fowles and J. Donne) disguised in the dialogue of two protagonists of the novel : Conchis and Nicholas. Contrastive viewpoints concerning man's isolation, loneliness are stated in the dialogue. Due to the conceptual analysis of the text it becomes possible both to decode the conceptual information of the text and find out its intertextual links.

Keywords: dialogue, conceptual analysis, isolation, intertextuality

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Authors: Rakesh Dogra, Arun Kumar, Arvind Kumar Sharma

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This paper reports the thermoluminescence as well as optical properties of rare earth doped lithium fluoride (LiF) nanophosphor, synthesized via chemical route. The rare earth impurities (Yb and Sm) have been observed to increase the deep trap center capacity, which, in turn, enhance the radiation resistance of the LiF. This suggests the viability of these materials to be used as high dose thermoluminescent detectors at high temperature. Further, optical absorption measurements revealed the formation of radiation induced stable color centers in LiF at room temperature, which are independent of the rare earth dopant.

Keywords: lithium flouride, thermoluminescence, UV-VIS spectroscopy, Gamma radiations

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Authors: Qianwei Cheng, A. K. M. Mahbubur Rahman, Anis Sarker, Abu Bakar Siddik Nayem, Ovi Paul, Amin Ahsan Ali, M. Ashraful Amin, Ryosuke Shibasaki, Moinul Zaber

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Thomas Friedman, in his famous book, argued that the world in this 21st century is flat and will continue to be flatter. This is attributed to rapid globalization and the interdependence of humanity that engendered tremendous in-flow of human migration towards the urban spaces. In order to keep the urban environment sustainable, policy makers need to plan based on extensive analysis of the urban environment. With the advent of high definition satellite images, high resolution data, computational methods such as deep neural network analysis, and hardware capable of high-speed analysis; urban planning is seeing a paradigm shift. Legacy data on urban environments are now being complemented with high-volume, high-frequency data. However, the first step of understanding urban space lies in useful categorization of the space that is usable for data collection, analysis, and visualization. In this paper, we propose a pragmatic categorization method that is readily usable for machine analysis and show applicability of the methodology on a developing world setting. Categorization to plan sustainable urban spaces should encompass the buildings and their surroundings. However, the state-of-the-art is mostly dominated by classification of building structures, building types, etc. and largely represents the developed world. Hence, these methods and models are not sufficient for developing countries such as Bangladesh, where the surrounding environment is crucial for the categorization. Moreover, these categorizations propose small-scale classifications, which give limited information, have poor scalability and are slow to compute in real time. Our proposed method is divided into two steps-categorization and automation. We categorize the urban area in terms of informal and formal spaces and take the surrounding environment into account. 50 km × 50 km Google Earth image of Dhaka, Bangladesh was visually annotated and categorized by an expert and consequently a map was drawn. The categorization is based broadly on two dimensions-the state of urbanization and the architectural form of urban environment. Consequently, the urban space is divided into four categories: 1) highly informal area; 2) moderately informal area; 3) moderately formal area; and 4) highly formal area. In total, sixteen sub-categories were identified. For semantic segmentation and automatic categorization, Google’s DeeplabV3+ model was used. The model uses Atrous convolution operation to analyze different layers of texture and shape. This allows us to enlarge the field of view of the filters to incorporate larger context. Image encompassing 70% of the urban space was used to train the model, and the remaining 30% was used for testing and validation. The model is able to segment with 75% accuracy and 60% Mean Intersection over Union (mIoU). In this paper, we propose a pragmatic categorization method that is readily applicable for automatic use in both developing and developed world context. The method can be augmented for real-time socio-economic comparative analysis among cities. It can be an essential tool for the policy makers to plan future sustainable urban spaces.

Keywords: semantic segmentation, urban environment, deep learning, urban building, classification

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Authors: Leila Keshavarz Afshar, Hedieh Sajedi

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Estimation of biological brain age from MR images is a topic that has been much addressed in recent years due to the importance it attaches to early diagnosis of diseases such as Alzheimer's. In this paper, we use a 3D Convolutional Neural Network (CNN) to provide a method for estimating the biological age of the brain. The 3D-CNN model is trained by MRI data that has been normalized. In addition, to reduce computation while saving overall performance, some effectual slices are selected for age estimation. By this method, the biological age of individuals using selected normalized data was estimated with Mean Absolute Error (MAE) of 4.82 years.

Keywords: brain age estimation, biological age, 3D-CNN, deep learning, T1-weighted image, SPM, preprocessing, MRI, canny, gray matter

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Authors: Esther Liyanage, Indrajith Liyanage, A. A. J. Rajaratne

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During the 30 year civil war in Sri Lanka, a large number of individuals were injured and disabled. These disabilities have reduced their daily physical activities which may cause reduction in flexibility of upper limb, shoulder girdle, lower back and lower limb. Muscle flexibility is important for a healthy lifestyle. The main objective of the study was to assess the upper limb, shoulder girdle and lower back, hamstring flexibility of the intact lower limb in disabled individuals in the North and Eastern parts of Sri Lanka. Back saver sits and reach test and shoulder scratch test described in FITNESS GRAM was used in the study. A total of 125 disabled soldiers with lower limb disabilities were recruited for the study. Flexibility of the lower back and hamstring muscles of uninjured lower limb was measured using back saver sit and reach test described by Wells and Dillon (1952). Upper limb and shoulder girdle flexibility was assessed using shoulder stretch test. Score 0-3 was given according to the ability to reach Superior medial angle of the opposite scapula, top of the head or the mouth. The results indicate that 31 (24.8%) disabled soldiers have lower limb flexibility less than 8, 2 (1.6 % ) have flexibility of 8, 2 (1.6 %) have flexibility of 8.5, 11 ( 8.8% ) have flexibility of 9, 14 (11.2 %) have flexibility of 9.5, 23 (18.4 %) have flexibility of 10, 17 (13.6 %) have 10.5 flexibility, 13 (10.4%) have 11 flexibility, 2 (1.6%) have 11.5 flexibility, 10 (8 %) have flexibility of 12 and 3 (2.34 %) have flexibility of 12.5. Six disabled soldiers (4.8%) have upper limb flexibility of 2 and remaining 95.2% have normal upper limb flexibility (score 3). A reduction in the flexibility of muscles in lower body and lower limbs was seen in 25% disabled soldiers which could be due to reduction in their daily physical activities.

Keywords: disability, flexibility, rehabilitation, quality of life

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Authors: Asmaa Zaki M., Ahmed Abd El Aziz, Heba A. Fayed, Moustafa H. Aly

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ISLs are the most popular choice for deep space communications because these links are attractive alternatives to present day microwave links. This paper explored the allowable high data rate in this link over different orbits, which is affected by variation in modulation scheme and detector type. Moreover, the objective of this paper is to optimize and analyze the performance of ISL in terms of Q-factor and Minimum Bit Error Rate (Min-BER) based on different detectors comprising some parameters.

Keywords: free space optics (FSO), field of view (FOV), inter satellite link (ISL), optical wireless communication (OWC)

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Authors: Nita Rukminasari

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The aim of this study is to select microalgae strains, which were isolated from agriculture and municipal wastewater drain, Reno, Nevada that has highest growth rate and lipid contents. The experiments in this study were carried out in two consecutive stages. The first stage is aimed at testing the survival capability of all isolated microalgae strains and determining the best candidates to grow in centrate cultivation system. The second stage was targeted at determination the highest growth rate and highest lipid content of the selected top performing algae strain when cultivated on centrate wastewater. 26 microalgae strains, which were isolated from municipal and agriculture waste water, were analyzed using Flow cytometer for FACS of lipid with BODIPY and Nile Red as a lipid dyes and they grew on 96 wells plate for 31 days to determine growth rate as a based line data for growth rate. The result showed that microalgae strains which showed a high mean of fluorescence for BODIPY and Nile Red were F3.BP.1, F3.LV.1, T1.3.1, and T1.3.3. Five microalgae strains which have high growth rate were T1.3.3, T2.4.1. F3.LV.1, T2.12.1 and T3.3.1. In conclusion, microalgae strain which showed the highest starch content was F3.LV.1. T1.3.1 had the highest mean of fluorescence for Nile Red and BODIPY. Microalgae strains were potential for biofuel feedstock such as F3.LV.1 and T1.3.1, those microalgae strains showed a positive correlation between growth rate at stationary phase, biomass and meant of fluorescence for Nile Red and BODIPY.

Keywords: agriculture and municipal wastewater, biofuel, centrate, microalgae

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Authors: Shimaa A. Higazy, Olfat E. El-Azabawy, Ahmed M. Al-Sabagh, Notaila M. Nasser, Eman A. Khamis

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In this work, two novel Schiff base polymers (PSB1 and PSB₂) with extra-high protective barrier features were facilely prepared via Polycondensation reactions. They were applied for the first time as effective corrosion inhibitors in the sour corrosive media of petroleum environments containing hydrogen sulfide (H₂S) gas. For studying the polymers' inhibitive action on the carbon steel, numerous corrosion testing methods including potentiodynamic polarization (PDP), open circuit potential, and electrochemical impedance spectroscopy (EIS) have been employed at various temperatures (298-328 K) in the oil wells formation water with H₂S concentrations of 100, 400, and 700 ppm as aggressive media. The activation energy (Ea) and other thermodynamic parameters were computed to describe the mechanism of adsorption. The corrosion morphological traits and steel samples' surfaces composition were analyzed by field emission scanning electron microscope and energy dispersive X-ray analysis. The PSB2 inhibited sour corrosion more effectively than PSB1 when subjected to electrochemical testing. The 100 ppm concentration of PSB2 exhibited 82.18 % and 81.14 % inhibition efficiencies at 298 K in PDP and EIS measurements, respectively. While at 328 K, the inhibition efficiencies were 61.85 % and 67.4 % at the same dosage and measurements. These poly Schiff bases exhibited fascinating performance as corrosion inhibitors in sour environment. They provide a great corrosion inhibition platform for the sustainable future environment.

Keywords: schiff base polymers, corrosion inhibitors, sour corrosive media, potentiodynamic polarization, H₂S concentrations

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Authors: Megersa Olumana Dinka, Kassahun Birhanu Tadesse

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Irrigation suitability of shallow groundwater (SGW) was investigated by taking thirty groundwater samples from piezometers and hand-dug wells in Wonji Shoa Sugar Estate (WSSE) (Ethiopia). Many physicochemical parameters (Mg²⁺, Na⁺, Ca²⁺, K⁺, CO₃-, SO4²⁻, HCO₃⁻, Cl⁻, TH, EC, TDS and pH) were analyzed following standard procedures. Different irrigation indices (MAR, SSP, SAR, RSC, KR, and PI) were also used for SGW suitability assessment. If all SGW are blended and used for irrigation, the salinity problem would be slight to moderate, and 100% of potential sugarcane yield could be obtained. The infiltration and sodium ion toxicity problems of the blended water would be none to moderate, and slight to moderate, respectively. As sugarcane is semi-tolerant to sodium toxicity, no significant sodium toxicity problem would be expected from the use of blended water. Blending SGW would also reduce each chloride and boron ion toxicity to none. In general, the rating of SGW was good to excellent for irrigation in terms of average EC (salinity), and excellent in terms of average SAR (infiltration). The SGW of the WSSE was categorized under C3S1 (high salinity and low sodium hazard). In conclusion, the conjunctive use of groundwater for irrigation would help to reduce the potential effect of waterlogging and salinization and their associated problems on soil and sugarcane production and productivity. However, a high value of SSP and RSC indicate a high possibility of infiltration problem. Hence, it is advisable to use the SGW for irrigation after blending with surface water. In this case, the optimum blending ratio of the surface to SGW sources has to be determined for sustainable sugarcane productivity.

Keywords: blending, infiltration, salinity, sodicity, sugarcane, toxicity

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Authors: Volker Koch, Sigrid Swobodnik, Bernd M. Zunk

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The success of companies on globalized markets is significantly influenced by the performance of purchasing departments and, of course, the individuals employed as professional purchasers. Nonetheless, this is generally accepted in practice, in literature as well as in empirical research, only insufficient attention was given to the assessment of this relationship between the personality of professional purchasers and their individual performance. This paper aims to describe the relationship against the background of the 'Big Five Inventory'. Based on the five dimensions of a personality (openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism) a research model was designed. The research model divides the individual performance of professional purchasers into two major dimensions: operational and strategic. The operational dimension consists of the items 'cost', 'quality delivery' and 'flexibility'; the strategic dimension comprises the positions 'innovation', 'supplier satisfaction' as wells as 'purchasing and supply management integration in the organization'. To test the research model, a survey study was performed, and an online questionnaire was sent out to purchasing professionals in Austrian companies. The data collected from 78 responses was used to test the research model applying a group comparison. The comparison points out that there is (i) an influence of the purchasers’ personality on the individual performance of professional purchasers and (ii) a link between purchasers’ personality to a high or a low individual performance of professional purchasers. The findings of this study may help human resource managers during staff recruitment processes to identify the 'right performing personality' for an operational and/or a strategic position in purchasing departments.

Keywords: big five inventory, individual performance, personality, purchasing professionals

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Authors: Jonathan Gong

Abstract:

Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deep learning, image processing, machine learning

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Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

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Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: deep learning, disease prediction, end-to-end machine learning, metagenomics, multiple instance learning, precision medicine

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Authors: Michel Moliere

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In the next decades, the thermal power generation segment will survive only if it achieves deep mutations, including drastical abatements of CO2 emissions and strong efficiency gains. In this challenging perspective, stationary gas turbines appear as serious candidates to lead the energy transition. Indeed, during the past decades, these turbomachines have made brisk technological advances in terms of efficiency, reliability, fuel flex (including the combustion of hydrogen), and the ability to hybridize with regenrables. It is, therefore, timely to summarize the progresses achieved by gas turbines in the recent past and to examine what are their assets to face the challenges of the energy transition.

Keywords: energy transition, gas turbines, decarbonization, power generation

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Authors: Dumont Maxime, Correia Carlos, Sauvage Jean-François, Schwartz Noah, Gray Morgan

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Context: The concept of the segmented telescope is unavoidable to build extremely large telescopes (ELT) in the quest for spatial resolution, but it also allows one to fit a large telescope within a reduced volume of space (JWST) or into an even smaller volume (Standard Cubesat). Cubesats have tight constraints on the computational burden available and the small payload volume allowed. At the same time, they undergo thermal gradients leading to large and evolving optical aberrations. The pupil segmentation comes nevertheless with an obvious difficulty: to co-phase the different segments. The CubeSat constraints prevent the use of a dedicated wavefront sensor (WFS), making the focal-plane images acquired by the science detector the most practical alternative. Yet, one of the challenges for the wavefront sensing is the non-linearity between the image intensity and the phase aberrations. Plus, for Earth observation, the object is unknown and unrepeatable. Recently, several studies have suggested Neural Networks (NN) for wavefront sensing; especially convolutional NN, which are well known for being non-linear and image-friendly problem solvers. Aims: We study in this paper the prospect of using NN to measure the phasing aberrations of a segmented pupil from the focal-plane image directly without a dedicated wavefront sensing. Methods: In our application, we take the case of a deployable telescope fitting in a CubeSat for Earth observations which triples the aperture size (compared to the 10cm CubeSat standard) and therefore triples the angular resolution capacity. In order to reach the diffraction-limited regime in the visible wavelength, typically, a wavefront error below lambda/50 is required. The telescope focal-plane detector, used for imaging, will be used as a wavefront-sensor. In this work, we study a point source, i.e. the Point Spread Function [PSF] of the optical system as an input of a VGG-net neural network, an architecture designed for image regression/classification. Results: This approach shows some promising results (about 2nm RMS, which is sub lambda/50 of residual WFE with 40-100nm RMS of input WFE) using a relatively fast computational time less than 30 ms which translates a small computation burder. These results allow one further study for higher aberrations and noise.

Keywords: wavefront sensing, deep learning, deployable telescope, space telescope

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Authors: Stanley Ibuchukwu Onwukwe

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Most reservoir in mature oil fields are vulnerable to challenges of water and/or gas coning as the size of their oil column reduces due to long period of oil production. These often result to low oil production and excessive water and/or gas production. Since over 50 years of oil production in the Niger delta, it is apparent that most of the oil fields in the region have reached their mature stages, thereby susceptible to coning tendencies. As a result of these, a good number of wells have been shut-in and abandoned, with significant amount of oil left unproduced. Analysis of the movement of fluid contacts in the reservoir is a significant aspect of reservoir studies and can assist in the management of coning tendencies and production performance of reservoirs in a mature field. This study, therefore, seeks to evaluate the occurrence of coning through the movement of fluid contacts (GOC and OWC) and determine the critical rate for controlling coning tendencies in mature oil field. This study applies the principle of Nodal analysis to calibrate the thin oil column of a reservoir of a mature field, and was graphically evaluated using the Joshi’s equation of critical rate for gas-oil system and oil-water system respectively. A representative Proxy equation was developed and sensitivity analysis carried out to determine the trend of critical rate as the oil column is been depleted. The result shows the trend in the movement of the GOC and OWC, and the critical rate, beyond which will result in excessive water and gas production, resulting to decreasing oil production from the reservoir. This result of this study can be used as a first pass assessment in the development of mature oil field reservoirs anticipated to experience water and/or gas coning during production.

Keywords: coning, fluid contact movement, mature oil field, oil production

Procedia PDF Downloads 235