Search results for: image registration techniques

Authors: Akbar Khodavirdizadeh, Ali Nemati Babaylou, Hassan Moomivand

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The history of human access to water technique has been one of the factors in the formation of human civilizations in the ancient world. The technique that makes surface water and groundwater accessible to humans on the ground has been a clever technique in human life to reach the water. In this study, while examining the water technique of ancient Iran using the Qanats technique, the water supply system of different regions of the ancient world were also studied and compared. Six groups of the ancient region of ancient Greece (Archaic 480-750 BC and Classical 223-480 BC), Urartu in Tuspa (600-850 BC), Petra (106-168 BC), Ancient Rome (265 BC), and the ancient United States (1450 BC) and ancient Iranian water technologies were studied under water supply systems. Past water technologies in these areas: water transmission systems in primary urban centers, use of water structures in water control, use of bridges in water transfer, construction of waterways for water transfer, storage of rainfall, construction of various types of pottery- ceramic, lead, wood and stone pipes have been used in water transfer, flood control, water reservoirs, dams, channel, wells, and Qanat. The central plateau of Iran is one of the arid and desert regions. Archaeological, geomorphological, and paleontological studies of the central region of the Iranian plateau showed that without the use of Qanats, the possibility of urban civilization in this region was difficult and even impossible. Zarch aqueduct is the most important aqueduct in Yazd region. Qanat of Zarch is a plain Qanat with a gallery length of 80 km; its mother well is 85 m deep and has 2115 well shafts. The main purpose of building the Qanat of Zārch was to access the groundwater source and transfer it to the surface of the ground. Regarding the structure of the aqueduct and the technique of transferring water from the groundwater source to the surface, it has a great impact on being different from other water techniques in the ancient world. The results show that the use of water technologies in ancient is very important to understand the history of humanity in the use of hydraulic techniques.

Keywords: ancient water technologies, groundwaters, qanat, human history, Ancient Iran

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Authors: Arda Ozkurt, Ozlem Bozkurt

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Brain-computer interfaces (BCIs) are devices that output commands by interpreting the data collected from the brain. Electroencephalography (EEG) is a non-invasive method to measure the brain's electrical activity. Since it was invented by Hans Berger in 1929, it has led to many neurological discoveries and has become one of the essential components of non-invasive measuring methods. Despite the fact that it has a low spatial resolution -meaning it is able to detect when a group of neurons fires at the same time-, it is a non-invasive method, making it easy to use without possessing any risks. In EEG, electrodes are placed on the scalp, and the voltage difference between a minimum of two electrodes is recorded, which is then used to accomplish the intended task. The recordings of EEGs include, but are not limited to, the currents along dendrites from synapses to the soma, the action potentials along the axons connecting neurons, and the currents through the synaptic clefts connecting axons with dendrites. However, there are some sources of noise that may affect the reliability of the EEG signals as it is a non-invasive method. For instance, the noise from the EEG equipment, the leads, and the signals coming from the subject -such as the activity of the heart or muscle movements- affect the signals detected by the electrodes of the EEG. However, new techniques have been developed to differentiate between those signals and the intended ones. Furthermore, an EEG device is not enough to analyze the data from the brain to be used by the BCI implication. Because the EEG signal is very complex, to analyze it, artificial intelligence algorithms are required. These algorithms convert complex data into meaningful and useful information for neuroscientists to use the data to design BCI devices. Even though for neurological diseases which require highly precise data, invasive BCIs are needed; non-invasive BCIs - such as EEGs - are used in many cases to help disabled people's lives or even to ease people's lives by helping them with basic tasks. For example, EEG is used to detect before a seizure occurs in epilepsy patients, which can then prevent the seizure with the help of a BCI device. Overall, EEG is a commonly used non-invasive BCI technique that has helped develop BCIs and will continue to be used to detect data to ease people's lives as more BCI techniques will be developed in the future.

Keywords: BCI, EEG, non-invasive, spatial resolution

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Authors: Mohamad Saeed Ahrari-Khafi, Abutorab Tabatabai-Naini, Niloofar Ajvadi

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Scapular fracture is not common in horses, due to the proper protection of scapular muscles. However, if it happens, it can cause lameness in horses. Because of the overlapping of the scapula on the contralateral scapula and the thorax, usually radiography cannot be helpful in evaluation, except in small amount of its ventral part. Although ultrasonography is mainly used for diagnosis of soft tissue injuries, it also can be used for evaluation of bone surface abnormalities. This study was intended to document the normal ultrasonographic appearance of the equine scapula. Right forelimb of six horses was used. To facilitate the image assessment, a zoning system was developed. Ultrasonography was performed by using a 5-11 MHz linear array transducer. Ultrasonographic anatomy of scapula in different parts and planes was imaged and documented, hoping to help practitioners to diagnose fractures and injuries. Results showed that ultrasonography is capable to depict different parts of the scapula and regional muscles, and can be used for detecting fractures and other abnormalities.

Keywords: horse, scapula, scapular fracture, ultrasonography

Procedia PDF Downloads 278

Authors: Shoeb Ahmed Adeel, Vivek Paul, K. Prajwal, Michael Fenelon

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Techniques have been used to tether and stabilize a multi-rotor MAV but carrying out the same process to a fixed wing MAV is a novel method which can be utilized in order to reduce damage occurring to the fixed wing MAVs while conducting flight test trials and PID tuning. A few sensors and on board controller is required to carry out this experiment in horizontal and vertical plane of the vehicle. Here we will be discussing issues such as sensitivity of the air vehicle, endurance and external load of the string acting on the vehicle.

Keywords: MAV, PID tuning, tethered flight, UAV

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Authors: Daniel Dahis, Haim Azhari

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Noninvasive image-guided intracranial treatments using high intensity focused ultrasound (HIFU) are on the course of translation into clinical applications. They include, among others, tumor ablation, hyperthermia, and blood-brain-barrier (BBB) penetration. Since many of these procedures are associated with local temperature elevation, thermal monitoring is essential. MRI constitutes an imaging method with high spatial resolution and thermal mapping capacity. It is the currently leading modality for temperature guidance, commonly under the name MRgHIFU (magnetic-resonance guided HIFU). Nevertheless, MRI is a very expensive non-portable modality which jeopardizes its accessibility. Ultrasonic thermal monitoring, on the other hand, could provide a modular, cost-effective alternative with higher temporal resolution and accessibility. In order to assess the feasibility of ultrasonic brain thermal monitoring, this study investigated the usage of brain tissue attenuation coefficient (AC) temporal changes as potential estimators of thermal changes. Newton's law of cooling describes a temporal exponential decay behavior for the temperature of a heated object immersed in a relatively cold surrounding. Similarly, in the case of cerebral HIFU treatments, the temperature in the region of interest, i.e., focal zone, is suggested to follow the same law. Thus, it was hypothesized that the AC of the irradiated tissue may follow a temporal exponential behavior during cool down regime. Three ex-vivo bovine brain tissue specimens were inserted into plastic containers along with four thermocouple probes in each sample. The containers were placed inside a specially built ultrasonic tomograph and scanned at room temperature. The corresponding pixel-averaged AC was acquired for each specimen and used as a reference. Subsequently, the containers were placed in a beaker containing hot water and gradually heated to about 45ᵒC. They were then repeatedly rescanned during cool down using ultrasonic through-transmission raster trajectory until reaching about 30ᵒC. From the obtained images, the normalized AC and its temporal derivative as a function of temperature and time were registered. The results have demonstrated high correlation (R² > 0.92) between both the brain AC and its temporal derivative to temperature. This indicates the validity of the hypothesis and the possibility of obtaining brain tissue temperature estimation from the temporal AC thermal changes. It is important to note that each brain yielded different AC values and slopes. This implies that a calibration step is required for each specimen. Thus, for a practical acoustic monitoring of the brain, two steps are suggested. The first step consists of simply measuring the AC at normal body temperature. The second step entails measuring the AC after small temperature elevation. In face of the urging need for a more accessible thermal monitoring technique for brain treatments, the proposed methodology enables a cost-effective high temporal resolution acoustical temperature estimation during HIFU treatments.

Keywords: attenuation coefficient, brain, HIFU, image-guidance, temperature

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Authors: Chitra Rajagopal, Indra Deo Kumar, Ila Chauhan, Ruchi Joshi, Binoy Bhargavan

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Reliability and safety are essential for the success of mission-critical and safety-critical defense systems. Humans are part of the entire life cycle of defense systems development and deployment. The majority of industrial accidents or disasters are attributed to human errors. Therefore, considerations of human performance and human reliability are critical in all complex systems, including defense systems. Defense systems are operating from the ground, naval and aerial platforms in diverse conditions impose unique physical and psychological challenges to the human operators. Some of the safety and mission-critical defense systems with human-machine interactions are fighter planes, submarines, warships, combat vehicles, aerial and naval platforms based missiles, etc. Human roles and responsibilities are also going through a transition due to the infusion of artificial intelligence and cyber technologies. Human operators, not accustomed to such challenges, are more likely to commit errors, which may lead to accidents or loss events. In such a scenario, it is imperative to understand the human factors in defense systems for better systems performance, safety, and cost-effectiveness. A case study using Task Analysis (TA) based methodology for assessment and reduction of human errors in the Air and Missile Defense System in the context of emerging technologies were presented. Action-oriented task analysis techniques such as Hierarchical Task Analysis (HTA) and Operator Action Event Tree (OAET) along with Critical Action and Decision Event Tree (CADET) for cognitive task analysis was used. Human factors assessment based on the task analysis helps in realizing safe and reliable defense systems. These techniques helped in the identification of human errors during different phases of Air and Missile Defence operations, leading to meet the requirement of a safe, reliable and cost-effective mission.

Keywords: defence systems, reliability, risk, safety

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Authors: H. H. Elewa, E. M. Ramadan, A. M. Nosair

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Rainfall water harvesting is considered as an important tool for overcoming water scarcity in arid and semi-arid region. Wadi Watir in the southeastern part of Sinai Peninsula is considered as one of the main and active basins in the Gulf of Aqaba drainage system. It is characterized by steep hills mainly consist of impermeable rocks, whereas the streambeds are covered by a highly permeable mixture of gravel and sand. A comprehensive approach involving the integration of geographic information systems, remote sensing and watershed modeling was followed to identify the RWH capability in this area. Eight thematic layers, viz volume of annual flood, overland flow distance, maximum flow distance, rock or soil infiltration, drainage frequency density, basin area, basin slope and basin length were used as a multi-parametric decision support system for conducting weighted spatial probability models (WSPMs) to determine the potential areas for the RWH. The WSPMs maps classified the area into five RWH potentiality classes ranging from the very low to very high. Three performed WSPMs' scenarios for W. Watir reflected identical results among their maps for the high and very high RWH potentiality classes, which are the most suitable ones for conducting surface water harvesting techniques. There is also a reasonable match with respect to the potentiality of runoff harvesting areas with a probability of moderate, low and very low among the three scenarios. WSPM results have shown that the high and very high classes, which are the most suitable for the RWH are representing approximately 40.23% of the total area of the basin. Accordingly, several locations were decided for the establishment of water harvesting dams and cisterns to improve the water conditions and living environment in the study area.

Keywords: Sinai, Wadi Watir, remote sensing, geographic information systems, watershed modeling, runoff water harvesting

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Authors: Wen-Hsien Huang, Hsu-Ting Hsu

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While advertisers often use animal metaphors to promote product performance, representing through the use of a product image together with an animal-like messenger to imply the undesirable health states of not using the product, the effect of such metaphors on persuasion remains unclear. The current research addresses this issue by investigating how consumers perceive and react to animal metaphor advertising in the context of product promotion. Three studies are carried out using field and experimental data. The findings demonstrate that animal metaphor ads are less persuasive than non-metaphor ads and that ads with animal-like messengers (as opposed to human messengers) activate stronger dehumanization perceptions, which in turn lead to lower product choice, product evaluation and purchase intention, regardless of whether the animal metaphors are presented visually in the picture or verbally in the headline. Furthermore, when the metaphorical pairing includes a more disliked animal, consumer reaction was less favorable. The implications of the findings for advertisers considering the use of animalized messengers are discussed.

Keywords: animal metaphor, dehumanization, product evaluation, health communication

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Authors: Javeria Arain, Saad Malik

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The management of solid waste is a crucial and essential aspect of urban environmental management especially in a city with an ever increasing population such as Karachi. The total amount of municipal solid waste generated from Gulshan e Iqbal town on average is 444.48 tons per day and landfill sites are a widely accepted solution for final disposal of this waste. However, an improperly selected site can have immense environmental, economical and ecological impacts. To select an appropriate landfill site a number of factors should be kept into consideration to minimize the potential hazards of solid waste. The purpose of this research is to analyse the study area for the construction of an appropriate landfill site for disposal of municipal solid waste generated from Gulshan e-Iqbal Town by using geospatial techniques considering hydrological, geological, social and geomorphological factors. This was achieved using analytical hierarchy process and fuzzy analysis as a decision support tool with integration of geographic information sciences techniques. Eight most critical parameters, relevant to the study area, were selected. After generation of thematic layers for each parameter, overlay analysis was performed in ArcGIS 10.0 software. The results produced by both methods were then compared with each other and the final suitability map using AHP shows that 19% of the total area is Least Suitable, 6% is Suitable but avoided, 46% is Moderately Suitable, 26% is Suitable, 2% is Most Suitable and 1% is Restricted. In comparison the output map of fuzzy set theory is not in crisp logic rather it provides an output map with a range of 0-1, where 0 indicates least suitable and 1 indicates most suitable site. Considering the results it is deduced that the northern part of the city is appropriate for constructing the landfill site though a final decision for an optimal site could be made after field survey and considering economical and political factors.

Keywords: Analytical Hierarchy Process (AHP), fuzzy set theory, Geographic Information Sciences (GIS), Multi-Criteria Decision Analysis (MCDA)

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Authors: S. Jayasinghe, R. B. N. Dissanayake

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Optimization modelling together with the Network models and Linear Programming techniques is a powerful tool in problem solving and decision making in real world applications. This study developed a mathematical model to optimize the net profit by minimizing the transportation cost. This model focuses the transportation among decentralized production plants to a centralized distribution centre and then the distribution among island wide agencies considering the customer satisfaction as a requirement. This company produces basically 9 types of food items with 82 different varieties and 4 types of non-food items with 34 different varieties. Among 6 production plants, 4 were located near the city of Mawanella and the other 2 were located in Galewala and Anuradhapura cities which are 80 km and 150 km away from Mawanella respectively. The warehouse located in the Mawanella was the main production plant and also the only distribution plant. This plant distributes manufactured products to 39 agencies island-wide. The average values and average amount of the goods for 6 consecutive months from May 2013 to October 2013 were collected and then average demand values were calculated. The following constraints are used as the necessary requirement to satisfy the optimum condition of the model; there was one source, 39 destinations and supply and demand for all the agencies are equal. Using transport cost for a kilometer, total transport cost was calculated. Then the model was formulated using distance and flow of the distribution. Network optimization and linear programming techniques were used to originate the model while excel solver is used in solving. Results showed that company requires total transport cost of Rs. 146, 943, 034.50 to fulfil the customers’ requirement for a month. This is very much less when compared with data without using the model. Model also proved that company can reduce their transportation cost by 6% when distributing to island-wide customers. Company generally satisfies their customers’ requirements by 85%. This satisfaction can be increased up to 97% by using this model. Therefore this model can be used by other similar companies in order to reduce the transportation cost.

Keywords: mathematical model, network optimization, linear programming

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Authors: Hae-Yeoun Lee

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Quantification of cardiac function is performed by calculating blood volume and ejection fraction in routine clinical practice. However, these works have been performed by manual contouring,which requires computational costs and varies on the observer. In this paper, an automatic left ventricle segmentation algorithm on cardiac magnetic resonance images (MRI) is presented. Using knowledge on cardiac MRI, a K-mean clustering technique is applied to segment blood region on a coil-sensitivity corrected image. Then, a graph searching technique is used to correct segmentation errors from coil distortion and noises. Finally, blood volume and ejection fraction are calculated. Using cardiac MRI from 15 subjects, the presented algorithm is tested and compared with manual contouring by experts to show outstanding performance.

Keywords: cardiac MRI, graph searching, left ventricle segmentation, K-means clustering

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Authors: Koray U. Erbas

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Neural networks are appealing for many applications since they are able to learn complex non-linear relationships between input and output data. As the number of neurons and layers in a neural network increase, it is possible to represent more complex relationships with automatically extracted features. Nowadays Deep Neural Networks (DNNs) are widely used in Computer Vision problems such as; classification, object detection, segmentation image editing etc. In this work, Facial Emotion Recognition task is performed by proposed Convolutional Neural Network (CNN)-based DNN architecture using FER2013 Dataset. Moreover, the effects of different hyperparameters (activation function, kernel size, initializer, batch size and network size) are investigated and ablation study results for Pooling Layer, Dropout and Batch Normalization are presented.

Keywords: convolutional neural network, deep learning, deep learning based FER, facial emotion recognition

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: Tiee-Jian Wu, Chih-Yuan Hsu

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Mode estimation is an important task, because it has applications to data from a wide variety of sources. We propose a semi-parametric approach to estimate the mode of an unknown continuous multivariate density function. Our approach is based on a weighted average of a parametric density estimate using the Box-Cox transform and a non-parametric kernel density estimate. Our semi-parametric mode estimate improves both the parametric- and non-parametric- mode estimates. Specifically, our mode estimate solves the non-consistency problem of parametric mode estimates (at large sample sizes) and reduces the variability of non-parametric mode estimates (at small sample sizes). The performance of our method at practical sample sizes is demonstrated by simulation examples and two real examples from the fields of climatology and image recognition.

Keywords: Box-Cox transform, density estimation, mode seeking, semiparametric method

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Authors: Mohamed F. Sadek, Safaa M. Hassan, Safwat S. Gabr

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Several alteration zones hosting gold mineralization are wide spreading in the South Eastern Desert of Egypt where gold has been mined from many localities since the time of the Pharaohs. The Sukkari is the only mine currently producing gold in the Eastern Desert of Egypt. Therefore, it is necessary to conduct more detailed studies on these locations using modern exploratory methods. The remote sensing plays an important role in lithological mapping and detection of associated hydrothermal mineralization particularly the exploration of gold mineralization. This study is focused on three localities in South Eastern Desert of Egypt, namely Beida, Defiet and Hoteib-Eiqat aiming to detect the gold-bearing hydrothermal alteration zones using the integrated data of remote sensing, field study and mineralogical investigation. Generally, these areas are dominated by Precambrian basement rocks including metamorphic and magmatic assemblages. They comprise ophiolitic serpentinite-talc carbonate, island-arc metavolcanics which were intruded by syn to late orogenic mafic and felsic intrusions mainly gabbro, granodiorite and monzogranite. The processed data of Advanced Spaceborne Thermal Emission and Reflection (ASTER) and Landsat-8 images are used in the present study to map the gold bearing-hydrothermal alteration zones. Band rationing and principal component analysis techniques are used to discriminate the different lithologic units exposed in the studied three areas. Field study and mineralogical investigation have been used to verify the remote sensing data. This study concluded that, the integrated remote sensing data with geological, field and mineralogical investigations are very effective in lithological discrimination, detailed geological mapping and detection of the gold-bearing hydrothermal alteration zones. More detailed exploration for gold mineralization with the help of remote sensing techniques is recommended to evaluate its potentiality in the study areas.

Keywords: pan-african, Egypt, landsat-8; ASTER, gold, alteration zones

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Authors: Talha Ali Khan

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Discovering different energy resources to full fill the world growing demand is now one of the society’s bigger challenge for the next half-century. The main task is to convert the sun radiation into electricity via photovoltaic solar cells which is suddenly decreasing $/watt of delivered solar electricity. Therefore, in this context, the sun trackers are those devices that can be used to ameliorate efficiency. In this paper, a variety of the sun tracking systems are evaluated and their merits and demerits are highlighted. The most adept and proficient sun-tracking devices are polar axis and azimuth-elevation types.

Keywords: dual axis, fixed axis, sun tracker, MPPT

Procedia PDF Downloads 563

Authors: Fabricio Costa Silva, Samuel Xavier de Souza

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A Global Positioning System (GPS) receiver is responsible to determine position, velocity and timing information by using satellite information. To get this information's are necessary to combine an incoming and a locally generated signal. The procedure called acquisition need to found two information, the frequency and phase of the incoming signal. This is very time consuming, so there are several techniques to reduces the computational complexity, but each of then put projects issues in conflict. I this papers we present a method that can reduce the computational complexity by reducing the search space and paralleling the search.

Keywords: GPS, acquisition, low complexity, parallelism

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Authors: Sikiru Ademola Adewale, Joe Thomas, Bolanle Hafiz Matti, Tosin Ige

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This project demonstrates the implementation and use of an encoder-decoder model to perform a many-to-many mapping of video data to text captions. The many-to-many mapping occurs via an input temporal sequence of video frames to an output sequence of words to form a caption sentence. Data preprocessing, model construction, and model training are discussed. Caption correctness is evaluated using 2-gram BLEU scores across the different splits of the dataset. Specific examples of output captions were shown to demonstrate model generality over the video temporal dimension. Predicted captions were shown to generalize over video action, even in instances where the video scene changed dramatically. Model architecture changes are discussed to improve sentence grammar and correctness.

Keywords: decoder, encoder, many-to-many mapping, video captioning, 2-gram BLEU

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Authors: Luksanaporn Krungkraipetch

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A pterygium is an eye surface lesion that begins in the limbal conjunctiva and progresses to the cornea. The lesion is more common in the nasal limbus than in the temporal, and it has a distinctive wing-like aspect. Indications for surgery, in decreasing order of significance, are grown over the corneal center, decreased vision due to corneal deformation, documented growth, sensations of discomfort, and aesthetic concerns. Recurrent pterygium results in the loss of time, the expense of therapy, and the potential for vision impairment. The objective of this study is to find out how often the recurrence of pterygium after surgery occurs, what effect the surgery technique has, and what causes them to come back in people with pterygium. Materials and Methods: Observational case control in retrospect: the study involves a retrospective analysis of 164 patient samples. Data analysis is descriptive statistics analysis, i.e., basic data details about pterygium surgery and the risk of recurrent pterygium. For factor analysis, the inferential statistics odds ratio (OR) and 95% confidence interval (CI) ANOVA are utilized. A p-value of 0.05 was deemed statistically important. Results: The majority of patients, according to the results, were female (60.4%). Twenty-four of the 164 (14.6%) patients who underwent surgery exhibited recurrent pterygium. The average age is 55.33 years old. Postoperative recurrence was reported in 19 cases (79.3%) of bare sclera techniques and five cases (20.8%) of conjunctival autograft techniques. The recurrence interval is 10.25 months, with the most common (54.17 percent) being 12 months. In 91.67 percent of cases, all follow-ups are successful. The most common recurrence level is 1 (25%). A surgical complication is a subconjunctival hemorrhage (33.33 percent). Comparing the surgeries done on people with recurrent pterygium didn't show anything important (F = 1.13, p = 0.339). Age significantly affected the recurrence of pterygium (95% CI, 6.79-63.56; OR = 20.78, P 0.001). Conclusion: This study discovered a 14.6% rate of pterygium recurrence after pterygium surgery. Across all surgeries and patients, the rate of recurrence was four times higher with the bare sclera method than with conjunctival autograft. The researchers advise selecting a more conventional surgical technique to avoid a recurrence.

Keywords: pterygium, recurrence pterygium, pterygium surgery, excision pterygium

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Authors: Tamunotonye Mayowa Braide, Isaac Oluwatayo

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This study investigates multidimensional poverty, and its correlates among rural households in Sekhukhune and Capricorn District municipalities (SDM & CDM) in Limpopo Province, South Africa. Primary data were collected from 407 rural households selected through purposive and simple random sampling techniques. Analytical techniques employed include descriptive statistics, principal component analysis (PCA), and the Alkire Foster (A-F) methodology. The results of the descriptive statistics showed there are more females (66%) than males (34%) in rural areas of Limpopo Province, with about 45% of them having secondary school education as the highest educational level attained and only about 3% do not have formal education. In the analysis of deprivation, eight dimensions of deprivation, constructed from 21 variables, were identified using the PCA. These dimensions include type and condition of dwelling water and sanitation, educational attainment and income, type of fuel for cooking and heating, access to clothing and cell phone, assets and fuel for light, health condition, crowding, and child health. In identifying the poor with poverty cut-off (0.13) of all indicators, about 75.9% of the rural households are deprived in 25% of the total dimensions, with the adjusted headcount ratio (M0) being 0.19. Multidimensional poverty estimates showed higher estimates of poor rural households with 71%, compared to 29%, which fall below the income poverty line. The study conducted poverty decomposition, using sub-groups within the area by examining regions and household characteristics. In SDM, there are more multidimensionally poor households than in CDM. The water and sanitation dimension is the largest contributor to the multidimensional poverty index (MPI) in rural areas of Limpopo Province. The findings can, therefore, assist in better design of welfare policy and target poverty alleviation programs and as well help in efficient resource allocation at the provincial and local municipality levels.

Keywords: Alkire-Foster methodology, Limpopo province, multidimensional poverty, principal component analysis, South Africa

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Authors: O. J. Akinsola, Yinan Zheng, Rose Anorlu, F. T. Ogunsola, Lifang Hou, Robert Leo-Murphy

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Cervical Cancer (CC) is the 2nd most common cancer among women living in low and middle-income countries, with no associated symptoms during formative periods. With the advancement and innovative medical research, there are numerous preventive measures being utilized, but the incidence of cervical cancer cannot be truncated with the application of only screening tests. The mortality associated with this invasive cervical cancer can be nipped in the bud through the important role of early-stage detection. This study research selected an array of different top features selection techniques which was aimed at developing a model that could validly diagnose the risk factors of cervical cancer. A retrospective clinic-based cohort study was conducted on 178 HIV-associated cervical cancer patients in Lagos University teaching Hospital, Nigeria (U54 data repository) in April 2022. The outcome measure was the automated prediction of the HIV-associated cervical cancer cases, while the predictor variables include: demographic information, reproductive history, birth control, sexual history, cervical cancer screening history for invasive cervical cancer. The proposed technique was assessed with R and Python programming software to produce the model by utilizing the classification algorithms for the detection and diagnosis of cervical cancer disease. Four machine learning classification algorithms used are: the machine learning model was split into training and testing dataset into ratio 80:20. The numerical features were also standardized while hyperparameter tuning was carried out on the machine learning to train and test the data. Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN). Some fitting features were selected for the detection and diagnosis of cervical cancer diseases from selected characteristics in the dataset using the contribution of various selection methods for the classification cervical cancer into healthy or diseased status. The mean age of patients was 49.7±12.1 years, mean age at pregnancy was 23.3±5.5 years, mean age at first sexual experience was 19.4±3.2 years, while the mean BMI was 27.1±5.6 kg/m2. A larger percentage of the patients are Married (62.9%), while most of them have at least two sexual partners (72.5%). Age of patients (OR=1.065, p<0.001**), marital status (OR=0.375, p=0.011**), number of pregnancy live-births (OR=1.317, p=0.007**), and use of birth control pills (OR=0.291, p=0.015**) were found to be significantly associated with HIV-associated cervical cancer. On top ten 10 features (variables) considered in the analysis, RF claims the overall model performance, which include: accuracy of (72.0%), the precision of (84.6%), a recall of (84.6%) and F1-score of (74.0%) while LR has: an accuracy of (74.0%), precision of (70.0%), recall of (70.0%) and F1-score of (70.0%). The RF model identified 10 features predictive of developing cervical cancer. The age of patients was considered as the most important risk factor, followed by the number of pregnancy livebirths, marital status, and use of birth control pills, The study shows that data mining techniques could be used to identify women living with HIV at high risk of developing cervical cancer in Nigeria and other sub-Saharan African countries.

Keywords: associated cervical cancer, data mining, random forest, logistic regression

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Authors: Kishor Chandra Kandpal, Amit Kumar

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The Indian Himalaya region harbours approximately 1748 plants of medicinal importance, and as per International Union for Conservation of Nature (IUCN), the 112 plant species among these are threatened and endangered. To ease the pressure on these plants, the government of India is encouraging its in-situ cultivation. The Saussurea costus, Valeriana jatamansi, and Picrorhiza kurroa have also been prioritized for large scale cultivation owing to their market demand, conservation value and medicinal properties. These species are found from 1000 m to 4000 m elevation ranges in the Indian Himalaya. Identification of these plants in the field requires taxonomic skills, which is one of the major bottleneck in the conservation and management of these plants. In recent years, Hyperspectral remote sensing techniques have been precisely used for the discrimination of plant species with the help of their unique spectral signatures. In this background, a spectral library of the above 03 medicinal plants was prepared by collecting the spectral data using a handheld spectroradiometer (325 to 1075 nm) from farmer’s fields of Himachal Pradesh and Uttarakhand states of Indian Himalaya. The Random forest (RF) model was implied on the spectral data for the classification of the medicinal plants. The 80:20 standard split ratio was followed for training and validation of the RF model, which resulted in training accuracy of 84.39 % (kappa coefficient = 0.72) and testing accuracy of 85.29 % (kappa coefficient = 0.77). This RF classifier has identified green (555 to 598 nm), red (605 nm), and near-infrared (725 to 840 nm) wavelength regions suitable for the discrimination of these species. The findings of this study have provided a technique for rapid and onsite identification of the above medicinal plants in the field. This will also be a key input for the classification of hyperspectral remote sensing images for mapping of these species in farmer’s field on a regional scale. This is a pioneer study in the Indian Himalaya region for medicinal plants in which the applicability of hyperspectral remote sensing has been explored.

Keywords: himalaya, hyperspectral remote sensing, machine learning; medicinal plants, random forests

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Authors: Patrícia Pires, Renata Vaz, Bárbara Teles, Marco Pato, Pedro Beckert

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Introduction: The management of lateral third clavicle fractures can be challenging due to difficulty in distinguishing subtle variations in the fracture pattern, which may be suggestive of potential fracture instability. They occur most often in men between 30 and 50 years of age, and in individuals over 70 years of age, its distribution is equal between both men and women. These fractures account for 10%–30% of all clavicle fractures and roughly 30%–45% of all clavicle nonunion fractures. Lateral third clavicle fractures may be treated conservatively or surgically, and there is no gold standard, although the risk of nonunion or pseudoarthrosis impacts the recommendation of surgical treatment when these fractures are unstable. There are many strategies for surgical treatment, including locking plates, hook plates fixation, coracoclavicular fixation using suture anchors, devices or screws, tension band fixation with suture or wire, transacromial Kirschner wire fixation and arthroscopically assisted techniques. Whenever taking the hardware into consideration, we must not disregard that obtaining adequate lateral fixation of small fragments is a difficult task, and plates are more associated to local irritation. The aim of the appropriate treatment is to ensure fracture healing and a rapid return to preinjury activities of daily living but, as explained, definitive treatment strategies have not been established and the variety of techniques avalilable add up to the discussion of this topic. Methods and Results: We present a clinical case of a 43-year-old man with the diagnosis of a lateral third clavicle fracture (Neer IIC) in the sequence of a fall on his right shoulder after a bicycle fall. He was operated three days after the injury, and through K-wire temporary fixation and indirect reduction using a ZipTight, he underwent osteosynthesis with an interfragmentary figure-of-eight tension band with polydioxanone suture (PDS). Two weeks later, there was a good aligment. He kept the sling until 6 weeks pos-op, avoiding efforts. At 7-weeks pos-op, there was still a good aligment, starting the physiotherapy exercises. After 10 months, he had no limitation in mobility or pain and returned to work with complete recovery in strength. Conclusion: Some distal clavicle fractures may be conservatively treated, but it is widely accepted that unstable fractures require surgical treatment to obtain superior clinical outcomes. In the clinical case presented, the authors chose an osteosuture technique due to the fracture pattern, its location. Since there isn´t a consensus on the prefered fixation method, it is important for surgeons to be skilled in various techniques and decide with their patient which approach is most appropriate for them, weighting the risk-benefit of each method. For instance, with the suture technique used, there is no wire migration or breakage, and it doesn´t require a reoperation for hardware removal; there is also less tissue exposure since it requires a smaller approach in comparison to the plate fixation and avoids cuff tears like the hook plate. The good clinical outcome on this case report serves the purpose of expanding the consideration of this method has a therapeutic option.

Keywords: lateral third, clavicle, suture, fixation

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Authors: Majid Aldalbahi

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In 2009, over 3.4 billion people in the world resided in urban areas as a result of rapid urban growth. This figure is estimated to increase to 6.5 billion by 2050. This urban growth phenomenon has raised challenges for many countries in both the developing and developed worlds. Urban growth is a complicated process involving the spatiotemporal changes of all socio-economic and physical components at different scales. The socio-economic components of urban growth are related to urban population growth and economic growth, while physical components of urban growth and economic growth are related to spatial expansion, land cover change and land use change which are the focus of this research. The interactions between these components are complex and no-linear. Several factors and forces cause these complex interactions including transportation and communication, internal and international migrations, public policies, high natural growth rates of urban populations and public policies. Urban growth has positive and negative consequences. The positive effects relates to planned and orderly urban growth, while negative effects relate to unplanned and scattered growth, which is called sprawl. Although urban growth is considered as necessary for sustainable urbanization, uncontrolled and rapid growth cause various problems including consumption of precious rural land resources at urban fringe, landscape alteration, traffic congestion, infrastructure pressure, and neighborhood conflicts. Traditional urban planning approaches in fast growing cities cannot accommodate the negative consequences of rapid urban growth. Microsimulation programme, and modelling techniques are effective means to provide new urban development, management and planning methods and approaches. This paper aims to use these techniques to understand and analyse the complex interactions for the case study of Riyadh city, a fast growing city in Saudi Arabia.

Keywords: policy implications, urban planning, traffic congestion, urban growth, Suadi Arabia, Riyadh

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Authors: Aleksandra Jonas, Aleksandra Gronowska, Maciej Ścigacz, Szymon Jadczak

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Exact Data is a smart tool which helps with meaningful marketing content creation. It helps marketers achieve this by analyzing the text of an advertisement before and after its publication on social media sites like Facebook or Instagram. In our research we focus on four areas of natural language processing (NLP): grammar correction, sentiment analysis, irony detection and advertisement interpretation. Our research has identified a considerable lack of NLP tools for the Polish language, which specifically aid online marketers. In light of this, our research team has set out to create a robust and versatile NLP tool for the Polish language. The primary objective of our research is to develop a tool that can perform a range of language processing tasks in this language, such as sentiment analysis, text classification, text correction and text interpretation. Our team has been working diligently to create a tool that is accurate, reliable, and adaptable to the specific linguistic features of Polish, and that can provide valuable insights for a wide range of marketers needs. In addition to the Polish language version, we are also developing an English version of the tool, which will enable us to expand the reach and impact of our research to a wider audience. Another area of focus in our research involves tackling the challenge of the limited availability of linguistically diverse corpora for non-English languages, which presents a significant barrier in the development of NLP applications. One approach we have been pursuing is the translation of existing English corpora, which would enable us to use the wealth of linguistic resources available in English for other languages. Furthermore, we are looking into other methods, such as gathering language samples from social media platforms. By analyzing the language used in social media posts, we can collect a wide range of data that reflects the unique linguistic characteristics of specific regions and communities, which can then be used to enhance the accuracy and performance of NLP algorithms for non-English languages. In doing so, we hope to broaden the scope and capabilities of NLP applications. Our research focuses on several key NLP techniques including sentiment analysis, text classification, text interpretation and text correction. To ensure that we can achieve the best possible performance for these techniques, we are evaluating and comparing different approaches and strategies for implementing them. We are exploring a range of different methods, including transformers and convolutional neural networks (CNNs), to determine which ones are most effective for different types of NLP tasks. By analyzing the strengths and weaknesses of each approach, we can identify the most effective techniques for specific use cases, and further enhance the performance of our tool. Our research aims to create a tool, which can provide a comprehensive analysis of advertising effectiveness, allowing marketers to identify areas for improvement and optimize their advertising strategies. The results of this study suggest that a smart tool for advertisement analysis can provide valuable insights for businesses seeking to create effective advertising campaigns.

Keywords: NLP, AI, IT, language, marketing, analysis

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Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

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Whereas currently the most prevalent deep learning methods require a large amount of data for training, few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: few-shot learning, triplet network, adaptive margin, deep learning

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Authors: M. Gazzah, B. Jaouachi, F. Sakli

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This research focuses on the yarn-to-yarn and metal-to-fabric friction effects on the residual bagging behavior expressed by residual bagging height, volume and recovery of some denim fabrics. The results show, that both residual bagging height and residual bagging volume, which is determined using image analysis method, are significantly affected due to the most influential fabric parameter variations, the weft yarns density and the mean frictional coefficients. After the applied number of fatigue cycles, the findings revealed that the weft yarn rigidity contributes on fabric bagging behavior accurately. Among the tested samples, our results show that the elastic fabrics present a high recovery ability to give low bagging height and volume values.

Keywords: bagging recovery, denim fabric, metal-to-fabric friction, residual bagging height, yarn-to-yarn friction

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Authors: Samuel Oye Bandele

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A policy is a system of principles to guide activities and strategic decisions of an organisation in order to achieve stated objectives and meeting expected outcomes. A Computer Based Test (CBT) policy is therefore a statement of intent to drive the CBT programmes, and should be implemented as a procedure or protocol. Policies are hence generally adopted by an organization or a nation. The concern here, in this paper, is the consideration and analysis of issues that are significant to evolving the acceptable policy that will drive the new CBT innovation in Nigeria. Public examinations and internal examinations in higher educational institutions in Nigeria are gradually making a radical shift from Paper Based or Paper-Pencil to Computer-Based Testing. The need to make an objective and empirical analysis of Policy issues relating to CBT became expedient. The following are some of the issues on CBT evolution in Nigeria that were identified as requiring policy backing. Prominent among them are requirements for establishing CBT centres, purpose of CBT, types and acquisition of CBT equipment, qualifications of staff: professional, technical and regular, security plans and curbing of cheating during examinations, among others. The descriptive research design was employed based on a population consisting of Principal Officers (Policymakers), Staff (Teaching and non-Teaching-Policy implementors), and CBT staff ( Technical and Professional- Policy supports) and candidates (internal and external). A fifty-item researcher-constructed questionnaire on policy issues was employed to collect data from 600 subjects drawn from higher institutions in South West Nigeria, using the purposive and stratified random sampling techniques. Data collected were analysed using descriptive (frequency counts, means and standard deviation) and inferential (t-test, ANOVA, regression and Factor analysis) techniques. Findings from this study showed, among others, that the factor loadings had significantly weights on the organizational and National policy issues on CBT innovation in Nigeria.

Keywords: computer-based testing, examination, innovation, paper-based testing, paper pencil based testing, policy issues

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Authors: E. Calil, L. A. Pereira

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The acquisition of orthography is a complex process, involving both lexical and grammatical questions. This learning occurs simultaneously with the domain of multiple textual aspects (e.g.: graphs, punctuation, etc.). However, most of the research on orthographic acquisition focus on this acquisition from an autonomous point of view, separated from the process of textual production. This means that their object of analysis is the production of words selected by the researcher or the requested sentences in an experimental and controlled setting. In addition, the analysis of the Spelling Problems (SP) are identified by the researcher on the sheet of paper. Considering the perspective of Textual Genetics, from an enunciative approach, this study will discuss the SPs recognized by dyads of newly literate students, while they are writing a text collaboratively. Six proposals of textual production were registered, requested by a 2nd year teacher of a Portuguese Primary School between January and March 2015. In our case study we discuss the SPs recognized by the dyad B and L (7 years old). We adopted as a methodological tool the Ramos System audiovisual record. This system allows real-time capture of the text in process and of the face-to-face dialogue between both students and their teacher, and also captures the body movements and facial expressions of the participants during textual production proposals in the classroom. In these ecological conditions of multimodal registration of collaborative writing, we could identify the emergence of SP in two dimensions: i. In the product (finished text): SP identification without recursive graphic marks (without erasures) and the identification of SPs with erasures, indicating the recognition of SP by the student; ii. In the process (text in progress): identification of comments made by students about recognized SPs. Given this, we’ve analyzed the comments on identified SPs during the text in progress. These comments characterize a type of reformulation referred to as Commented Oral Erasure (COE). The COE has two enunciative forms: Simple Comment (SC) such as ' 'X' is written with 'Y' '; or Unfolded Comment (UC), such as ' 'X' is written with 'Y' because...'. The spelling COE may also occur before or during the SP (Early Spelling Recognition - ESR) or after the SP has been entered (Later Spelling Recognition - LSR). There were 631 words entered in the 6 stories written by the B-L dyad, 145 of them containing some type of SP. During the text in progress, the students recognized orally 174 SP, 46 of which were identified in advance (ESRs) and 128 were identified later (LSPs). If we consider that the 88 erasure SPs in the product indicate some form of SP recognition, we can observe that there were twice as many SPs recognized orally. The ESR was characterized by SC when students asked their colleague or teacher how to spell a given word. The LSR presented predominantly UC, verbalizing meta-orthographic arguments, mostly made by L. These results indicate that writing in dyad is an important didactic strategy for the promotion of metalinguistic reflection, favoring the learning of spelling.

Keywords: collaborative writing, erasure, learning, metalinguistic awareness, spelling, text production

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Authors: J. L. Liu, L. Wang, B. Zhu, J. Zhou, W. D. Gao

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Fabric textures are very common in our daily life. However, we never explore the representation of fabric textures from neuroscience view. Theoretical studies suggest that primary visual cortex (V1) uses a sparse code to efficiently represent natural images. However, how the simple cells in V1 encode the artificial textures is still a mystery. So, here we will take fabric texture as stimulus to study the response of independent component analysis that is established to model the receptive field of simple cells in V1. Experimental results based on 140 classical fabric images indicate that the receptive fields of simple cells have obvious selectivity in orientation, frequency, and phase when drifting gratings are used to determine their tuning properties. Additionally, the distribution of optimal orientation and frequency shows that the patch size selected from each original fabric image has a significant effect on the frequency selectivity.

Keywords: fabric texture, receptive filed, simple cell, spare coding

Procedia PDF Downloads 455