Search results for: cloud and channel discharges

Authors: Sumera, Sanila Amber, Fatima Javed Mirza, Amjad Ali, Saadia Zahid

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Glioblastoma multiforme (GBM) is a widely spread and fatal primary brain tumor with an increased risk of relapse in spite of aggressive treatment. The current procedures for GBM diagnosis include invasive procedures i.e. resection or biopsy, to acquire tumor mass. Implementation of negligibly invasive tests as a potential diagnostic technique and biofluid-based monitoring of GBM stresses on discovering biomarkers in CSF and blood. Therefore, we performed a comprehensive in silico analysis to identify potential circulating biomarkers for GBM. Initially, six gene and protein databases were utilized to mine brain-specific proteins. The resulting proteins were filtered using a channel of five tools to predict the secretory proteins. Subsequently, the expression profile of the secreted proteins was verified in the brain and blood using two databases. Additional verification of the resulting proteins was done using Plasma Proteome Database (PPD) to confirm their presence in blood. The final set of proteins was searched in literature for their relationship with GBM, keeping a special emphasis on secretome proteome. 2145 proteins were firstly mined as brain-specific, out of which 69 proteins were identified as secretory in nature. Verification of expression profile in brain and blood eliminated 58 proteins from the 69 proteins, providing a final list of 11 proteins. Further verification of these 11 proteins further eliminated 2 proteins, giving a final set of nine secretory proteins i.e. OPCML, NPTX1, LGI1, CNTN2, LY6H, SLIT1, CREG2, GDF1 and SERPINI1. Out of these 9 proteins, 7 were found to be linked to GBM, whereas 2 proteins are not investigated in GBM so far. We propose that these secretory proteins can serve as potential circulating biomarker signatures of GBM and will facilitate the development of minimally invasive diagnostic methods and novel therapeutic interventions for GBM.

Keywords: glioblastoma multiforme, secretory proteins, brain secretome, biomarkers

Procedia PDF Downloads 152

Authors: Govind Kumar

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The concept of ‘e-governance’ that was brought about by the new wave of reforms, namely ‘LPG’ in the early 1990s, has been enabling governments across the globe to digitally transform themselves. Digital transformation is leading the governments with qualitative decisions, optimization in rational use of resources, facilitation of cost-benefit analyses, and elimination of redundancy and corruption with the help of ICT-based applications interface. ICT-based applications/technologies have enormous potential for impacting positive change in the social lives of the global citizenry. Supercomputers test and analyze millions of drug molecules for developing candidate vaccines to combat the global pandemic. Further, e-commerce portals help distribute and supply household items and medicines, while videoconferencing tools provide a visual interface between the clients and hosts. Besides, crop yields are being maximized with the help of drones and machine learning, whereas satellite data, artificial intelligence, and cloud computing help governments with the detection of illegal mining, tackling deforestation, and managing freshwater resources. Such e-applications have the potential to take governance an extra mile by achieving 5 Es (effective, efficient, easy, empower, and equity) of e-governance and six Rs (reduce, reuse, recycle, recover, redesign and remanufacture) of sustainable development. If such digital transformation gains traction within the government framework, it will replace the traditional administration with the digitalization of public administration. On the other hand, it has brought in a new set of challenges, like the digital divide, e-illiteracy, technological divide, etc., and problems like handling e-waste, technological obsolescence, cyber terrorism, e-fraud, hacking, phishing, etc. before the governments. Therefore, it would be essential to bring in a rightful mixture of technological and humanistic interventions for addressing the above issues. This is on account of the reason that technology lacks an emotional quotient, and the administration does not work like technology. Both are self-effacing unless a blend of technology and a humane face are brought in into the administration. The paper will empirically analyze the significance of the technological framework of digital transformation within the government set up for the digitalization of public administration on the basis of the synthesis of two case studies undertaken from two diverse fields of administration and present a future framework of the study.

Keywords: digital transformation, electronic governance, public administration, knowledge framework

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Authors: Karolina Kowalczyk-Skoczylas

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The hybrid SPD process called DRECE (Dual Rolls Equal Channel Extrusion) combines the concepts of ECAP method and CONFORM extrusion, and is intended for processing sheet-metal workpieces. The material in the fоrm оf a metal strip is subjected tо plastic defоrmation by passing thrоugh the shaping tоol at a given angle α. Importantly, in this process the dimensions of the metal strip dо nоt change after the pass is cоmpleted. Subsequent DRECE passes allоw fоr increasing the effective strain in the tested material. The methоd has a significant effect оn the micrоstructure and mechanical prоperties оf the strip. The experimental tests have been conducted on the unconventional DRECE device in VŠB Ostrava, the Czech Republic. The DC03 steel strips have been processed in several passes - up to six. Then, both Erichsen cupping tests as well as static tensile tests have been performed to evaluate the effect of DRECE process on drawability, plastic anisotropy and mechanical properties of the investigated steel. Both yield strength and ultimate tensile strength increase significantly after consecutive passes. Drawability decreases slightly after the first and second pass. Then it stabilizes on a reasonably high level, which means that the steel is characterized by useful drawability for technological processes. It was investigated in the material is characterized by a normal anisotropy. In the microstructure, an intensification of the development of microshear bands and their mutual intersection is observed, which leads to the fragmentation of the grain into smaller volumes and, consequently, to the formation of an ultrafine grained structure. "The project was co-financed by the European Union within the programme "The European Funds for Śląsk (Silesia) 2021-2027".

Keywords: SPD process, low carbon steel, mechanical properties, plastic deformation, microstructure evolution

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Authors: Chun-Han Li, Tien-Fu Yang, Chen-Yu Chen, Wei-Mon Yan

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The conventional dehumidification method in air-conditioning system mostly utilizes a cooling coil to remove the moisture in the air via cooling the supply air down below its dew point temperature. During the process, it needs to reheat the supply air to meet the set indoor condition that consumes a considerable amount of energy and affect the coefficient of performance of the system. If the processes of dehumidification and cooling are separated and operated respectively, the indoor conditions will be more efficiently controlled. Therefore, decoupling the dehumidification and cooling processes in heating, ventilation and air conditioning system is one of the key technologies as membrane dehumidification processes for the next generation. The membrane dehumidification method has the advantages of low cost, low energy consumption, etc. It utilizes the pore size and hydrophilicity of the membrane to transfer water vapor by mass transfer effect. The moisture in the supply air is removed by the potential energy and driving force across the membrane. The process can save the latent load used to condense water, which makes more efficient energy use because it does not involve heat transfer effect. In this work, the performance measurements including the permeability and selectivity of water vapor and air with the composite and commercial membranes were conducted. According to measured data, we can choose the suitable dehumidification membrane for designing the flow channel length and components of the planar dehumidifier. The vacuum membrane dehumidification system was set up to examine the effects of temperature, humidity, vacuum pressure, flow rate, the coefficient of performance and other parameters on the dehumidification efficiency. The results showed that the commercial Nafion membrane has better water vapor permeability and selectivity. They are suitable for filtration with water vapor and air. Meanwhile, Nafion membrane has promising potential in the dehumidification process.

Keywords: vacuum membrane dehumidification, planar membrane dehumidifier, water vapour and air permeability, air conditioning

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Authors: Sahar Iqrar, Malik Adeel Anwar, Zain Akram, Maria Noor

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Introduction: Oral lichen planus is a chronic inflammatory condition of unknown etiology. Oral lichen planus may be related with several other diseases. Grinspan's Syndrome is characterized by a triad of oral lichen planus, hypertension, and diabetes mellitus. Other associations reported in the literature are with chronic liver disease and, with dyslipidemia. The nature of these associations is still not fully understood. Material and methods: Study was conducted in Department of Oral Medicine, Fatima Memorial Hospital College of Medicine and Dentistry, Lahore, Pakistan. A total of n=89 clinically diagnosed patients of oral lichen planus of both gender and all age groups were recruited and detailed history were recorded in the designed performs. Results: A total of n=89 patients were taken with male to female ratio of 3:8 in which 24 were male and 65 females. Mean age was 48.8 ± 13.8 years. Age range of 10-74 years was seen. Among these patients suffering from oral lichen planus, 41.6% (n=37) had a positive history for hypertension with 59.5% (n=22) of these patients were taking different medication for their condition. Whereas Diabetes Mellitus was found in 24.7% (n=22) patients with 72.7% (n=16) of these patients using the hypoglycemic drug (oral or injectable) to control their blood glucose levels. Out of these n=89 lichen planus patients 21.3% had both hypertension and diabetes mellitus (fulfilling the criteria for Grinspan's Syndrome). Out of this Grinspan's Syndrome pool 94.7% (n=19) were taking drug atleast for one of the two conditions. Conclusion: As noticed form the medical history of the patients, most of them were using hypoglycemic drugs for diabetes mellitus and beta blockers, diuretics and calcium channel blockers for hypertension. These drugs are known for lichenoid reaction. Therefore, it should be ruled out at histopathological/ immunological and molecular level whether these patients are suffering from lichen planus or lichenoid drug reaction to truly declare them as patients with Grinspan’s Syndrome.

Keywords: diabetes mellitus, grinspan's syndrome, lichenoid drug reaction, oral lichen planus

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Authors: Shreya Goyal

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The study aims to build user-friendly software to understand patient arrival patterns and compute the number of potential patients who will visit a particular health facility for a given period by using a machine learning algorithm. The underlying machine learning algorithm used in this study is the Support Vector Machine (SVM). Accurate prediction of patient arrival allows hospitals to operate more effectively, providing timely and efficient care while optimizing resources and improving patient experience. It allows for better allocation of staff, equipment, and other resources. If there's a projected surge in patients, additional staff or resources can be allocated to handle the influx, preventing bottlenecks or delays in care. Understanding patient arrival patterns can also help streamline processes to minimize waiting times for patients and ensure timely access to care for patients in need. Another big advantage of using this software is adhering to strict data protection regulations such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States as the hospital will not have to share the data with any third party or upload it to the cloud because the software can read data locally from the machine. The data needs to be arranged in. a particular format and the software will be able to read the data and provide meaningful output. Using software that operates locally can facilitate compliance with these regulations by minimizing data exposure. Keeping patient data within the hospital's local systems reduces the risk of unauthorized access or breaches associated with transmitting data over networks or storing it in external servers. This can help maintain the confidentiality and integrity of sensitive patient information. Historical patient data is used in this study. The input variables used to train the model include patient age, time of day, day of the week, seasonal variations, and local events. The algorithm uses a Supervised learning method to optimize the objective function and find the global minima. The algorithm stores the values of the local minima after each iteration and at the end compares all the local minima to find the global minima. The strength of this study is the transfer function used to calculate the number of patients. The model has an output accuracy of >95%. The method proposed in this study could be used for better management planning of personnel and medical resources.

Keywords: machine learning, SVM, HIPAA, data

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Authors: Jung-Il Kang, Jeon Eon Park, Yu-Jin Moon, Young-Seok Ahn, Eun-Sook Yoo, Hee-Kyoung Kang

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This study was conducted to evaluate the effect of Undariopsis peterseniana, a seaweed native to Jeju Island, Korea, on the growth of hair. The dermal papilla cells (DPCs) have known to regulate hair growth cycle and length of hair follicle through interact with epithelial cells. When immortalized vibrissa DPCs were treated with the U. peterseniana extract, the U. peterseniana extract significantly increased the proliferation of DPCs. The effect of U. peterseniana extract on the growth of vibrissa follicles was also examined. U. peterseniana extract significantly increased the hair-fiber lengths of the vibrissa follicles. Hair loss is partly caused by dihydrotestosterone (DHT) binding to androgen receptor in hair follicles, and the inhibition of 5α-reductase activity can prevent hair loss through the decrease of DHT level. The U. peterseniana extract inhibited 5α-reductase activity. Minoxidil, a potent hair-growth agent, can induce proliferation in NIH3T3 fibroblasts by opening KATP channels. We thus examined the proliferative effects of U. peterseniana extract in NIH3T3 fibroblasts. U. peterseniana extract significantly increased the proliferation of NIH3T3 fibroblasts. Tetraethylammonium chloride (TEA), a K+ channel blocker, inhibited U. peterseniana-induced proliferation in NIH3T3 fibroblasts. These results suggest that U. peterseniana could have the potential to treat alopecia through the proliferation of DPCs, the inhibition of 5α-reductase activity and the opening of KATP channels. [Acknowledgement] This research was supported by The Leading Human Resource Training Program of Regional Neo industry through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT and future Planning (2016H1D5A1908786).

Keywords: hair growth, Undariopsis peterseniana, vibrissa follicles, dermal papilla cells, 5α-reductase, KATP channels

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Authors: Amira Benabdelkader

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Communication presents the channel by which humankind create and maintain their relationship with others, express themselves, exchange information, learn and teach etc. The context of communication plays a distinctive role in deciding about the language to be used. The term context is mainly used to refer to the interlocutors, their cultures, languages, relationship, physical surrounding that is the communication setting, type of the information to be transmitted, the topic etc. Cultures, on one hand, impose on humans certain behaviours, attitudes, gestures and beliefs. On the other hand, the focus on language is inevitable as it is with its verbal and non-verbal components, a key tool in and for communication. Moreover, each language has its particularity in how people voice, address and express their thoughts, feelings and beliefs. Being in the same setting with people from different cultures and languages and having conversations with them would call upon the intercultural communicative competence. This latter would promote the success of their conversations. Additionally, this competence could manifest in several ways during their interactions, to the extent that no one can predict when and how the interlocutors would use it. The only thing probably that could be confirmed is that the setting and culture would in a way or another intervene and often shape the flow of their communication, if not the whole communication. Therefore, this paper will look at the intercultural communicative competence of language learners when introducing their cultures to each other in an online language tandem (henceforth OLT) using their second and/or foreign language with the L1 language speakers. The participants of this study are Algerian (use L2: French, FL: English), British (L1: English, L2/FL: French). In other words, this current paper will provide a qualitative analysis of the OLT experiment by emphasising how language learners can overcome the cultural differences in an intercultural setting while communicating online using Skype (video conversations) with people from different countries, cultures and L1. The non-verbal cues will have the lion share in the analysis by focusing on how they have been used to maintain this intercultural communication or hinder it through the misinterpretation of gestures, head movements, grimaces etc.

Keywords: intercultural communicative competence, non-verbal cues, online language tandem, Skype

Procedia PDF Downloads 280

Authors: Pragathi Gurumurthy, Christina Hagen, Patricia Ulloa, Martin A. Koch, Thorsten M. Buzug

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Obstructive sleep apnea (OSA) is a sleep disorder where the patient suffers a disturbed airflow during sleep due to partial or complete occlusion of the pharyngeal airway. Recently, numerical simulations have been used to better understand the mechanism of pharyngeal collapse. However, to gain confidence in the solutions so obtained, an experimental validation is required. Therefore, in this study an experimental validation of computational fluid dynamics (CFD) used for the study of human pharyngeal flow patterns during OSA is performed. A stationary incompressible Navier-Stokes equation solved using the finite element method was used to numerically study the flow patterns in a computed tomography-based human pharynx model. The inlet flow rate was set to 250 ml/s and such that a flat profile was maintained at the inlet. The outlet pressure was set to 0 Pa. The experimental technique used for the validation of CFD of fluid flow patterns is phase contrast-MRI (PC-MRI). Using the same computed tomography data of the human pharynx as in the simulations, a phantom for the experiment was 3 D printed. Glycerol (55.27% weight) in water was used as a test fluid at 25°C. Inflow conditions similar to the CFD study were simulated using an MRI compatible flow pump (CardioFlow-5000MR, Shelley Medical Imaging Technologies). The entire experiment was done on a 3 T MR system (Ingenia, Philips) with 108 channel body coil using an RF-spoiled, gradient echo sequence. A comparison of the axial velocity obtained in the pharynx from the numerical simulations and PC-MRI shows good agreement. The region of jet impingement and recirculation also coincide, therefore validating the numerical simulations. Hence, the experimental validation proves the reliability and correctness of the numerical simulations.

Keywords: computational fluid dynamics, experimental validation, phase contrast-MRI, obstructive sleep apnea

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Authors: Matthew Baucum

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With the increasing popularity of fMRI as an experimental method, psychology and neuroscience can greatly benefit from advanced techniques for summarizing and synthesizing large amounts of data from brain imaging studies. One promising avenue is automated meta-analyses, in which natural language processing methods are used to identify the brain regions consistently associated with certain semantic concepts (e.g. “social”, “reward’) across large corpora of studies. This study builds on this approach by demonstrating how, in fMRI meta-analyses, individual voxels can be treated as vectors in a semantic space and evaluated for their “proximity” to terms of interest. In this technique, a low-dimensional semantic space is built from brain imaging study texts, allowing words in each text to be represented as vectors (where words that frequently appear together are near each other in the semantic space). Consequently, each voxel in a brain mask can be represented as a normalized vector sum of all of the words in the studies that showed activation in that voxel. The entire brain mask can then be visualized in terms of each voxel’s proximity to a given term of interest (e.g., “vision”, “decision making”) or collection of terms (e.g., “theory of mind”, “social”, “agent”), as measured by the cosine similarity between the voxel’s vector and the term vector (or the average of multiple term vectors). Analysis can also proceed in the opposite direction, allowing word cloud visualizations of the nearest semantic neighbors for a given brain region. This approach allows for continuous, fine-grained metrics of voxel-term associations, and relies on state-of-the-art “open vocabulary” methods that go beyond mere word-counts. An analysis of over 11,000 neuroimaging studies from an existing meta-analytic fMRI database demonstrates that this technique can be used to recover known neural bases for multiple psychological functions, suggesting this method’s utility for efficient, high-level meta-analyses of localized brain function. While automated text analytic methods are no replacement for deliberate, manual meta-analyses, they seem to show promise for the efficient aggregation of large bodies of scientific knowledge, at least on a relatively general level.

Keywords: FMRI, machine learning, meta-analysis, text analysis

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Authors: Sultan Mahmud, Qamar Zaman, Travis Esau, Young Chang

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Strawberry powdery mildew (PM) is a serious disease that has a significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVMs) and k-nearest neighbors (kNNs). The methodology of the proposed study is based on image processing which is composed of five main steps including image acquisition, pre-processing, segmentation, features extraction and classification. Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM (Sphaerotheca macularis) disease under artificial cloud lighting condition. Colour thresholding was utilized to segment all images before textural analysis. Colour co-occurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to a physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The normalized feature data were utilized for training and validation, respectively, using developed classifiers. The classifiers have experimented with internal, external and cross-validations. The best classifier was selected based on their performance and accuracy. Experimental results suggested that SVMs classifier showed 98.33%, 85.33%, 87.33%, 93.33% and 95.0% of accuracy on internal, external-I, external-II, 4-fold cross and 5-fold cross-validation, respectively. Whereas, kNNs results represented 90.0%, 72.00%, 74.66%, 89.33% and 90.3% of classification accuracy, respectively. The outcome of this study demonstrated that SVMs classified PM disease with a highest overall accuracy of 91.86% and 1.1211 seconds of processing time. Therefore, overall results concluded that the proposed study can significantly support an accurate and automatic identification and recognition of strawberry PM disease with SVMs classifier.

Keywords: powdery mildew, image processing, textural analysis, color co-occurrence matrix, support vector machines, k-nearest neighbors

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Authors: Ali Alshumrani, Nathan Clarke, Bogdan Ghite, Stavros Shiaeles

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Digital forensics has become an essential tool in the investigation of cyber and computer-assisted crime. Arguably, given the prevalence of technology and the subsequent digital footprints that exist, it could have a significant role across almost all crimes. However, the variety of technology platforms (such as computers, mobiles, Closed-Circuit Television (CCTV), Internet of Things (IoT), databases, drones, cloud computing services), heterogeneity and volume of data, forensic tool capability, and the investigative cost make investigations both technically challenging and prohibitively expensive. Forensic tools also tend to be siloed into specific technologies, e.g., File System Forensic Analysis Tools (FS-FAT) and Network Forensic Analysis Tools (N-FAT), and a good deal of data sources has little to no specialist forensic tools. Increasingly it also becomes essential to compare and correlate evidence across data sources and to do so in an efficient and effective manner enabling an investigator to answer high-level questions of the data in a timely manner without having to trawl through data and perform the correlation manually. This paper proposes a Unified Forensic Analysis Tool (U-FAT), which aims to establish a common language for electronic information and permit multi-source forensic analysis. Core to this approach is the identification and development of forensic analyses that automate complex data correlations, enabling investigators to investigate cases more efficiently. The paper presents a systematic analysis of major crime categories and identifies what forensic analyses could be used. For example, in a child abduction, an investigation team might have evidence from a range of sources including computing devices (mobile phone, PC), CCTV (potentially a large number), ISP records, and mobile network cell tower data, in addition to third party databases such as the National Sex Offender registry and tax records, with the desire to auto-correlate and across sources and visualize in a cognitively effective manner. U-FAT provides a holistic, flexible, and extensible approach to providing digital forensics in technology, application, and data-agnostic manner, providing powerful and automated forensic analysis.

Keywords: digital forensics, evidence correlation, heterogeneous data, forensics tool

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Authors: Scott Draper, Nat Benjanuvatra, Grant Landers, Terry Griffiths, Justin Geldard

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Open water swimming has been an Olympic sport since 2008 and is growing in popularity world-wide as a low impact form of exercise. Unlike pool swimming, open water swimmers experience a range of different environmental conditions, including surface waves, variable water temperature, aquatic life, and ocean currents. This presentation will describe experimental research to investigate how freestyle swimming behaviour and performance is influenced by surface waves. A group of 12 swimmers were instructed to swim freestyle in the 54 m long wave flume located at The University of Western Australia’s Coastal and Offshore Engineering Laboratory. A variety of different regular waves were simulated, varying in height (up to 0.3 m), period (1.25 – 4s), and direction (with or against the swimmer). Swimmer’s velocity and acceleration, respectively, were determined from video recording and inertial sensors attached to five different parts of the swimmer’s body. The results illustrate how the swimmers stroke rate and the wave encounter frequency influence their forward speed and how particular wave conditions can benefit or hinder performance. Comparisons to simplified mathematical models provide insight into several aspects of performance, including: (i) how much faster swimmers can travel when swimming with as opposed to against the waves, and (ii) why swimmers of lesser ability are expected to be affected proportionally more by waves than elite swimmers. These findings have implications across the spectrum from elite to ‘weekend’ swimmers, including how they are coached and their ability to win (or just successfully complete) iconic open water events such as the Rottnest Channel Swim held annually in Western Australia.

Keywords: open water, surface waves, wave height/length, wave flume, stroke rate

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Authors: Gurbanova Lamiya

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The Republic of Azerbaijan is considered a region with limited water resources, as up to 70% of surface water is formed outside the country's borders, and most of its territory is an arid (dry) climate zone. It is located at the lower limit of transboundary flows, which is the weakest source of natural water resources in the South Caucasus. It is essential to correctly assess the quality of natural, collector-drainage and groundwater of the area and their suitability for irrigation in order to properly carry out land reclamation measures, provide the normal water-salt regime, and prevent repeated salinization. Through the 141-km-long main Mil-Mugan collector, groundwater, household waste, and floodwaters generated during floods and landslides are poured into the Caspian Sea. The hydrochemical composition of the samples taken from the Sabir irrigation canal passing through the center of the Kura-Araz plain, the Main Mil-Mugan Collector, and the groundwater of the region, which we chose as our research object, were studied and the obtained results were compared by periods. A model is proposed that allows for a complete visualization of the primary materials collected for the study area. The practical use of the established digital model provides all possibilities. The practical use of the established digital model provides all possibilities. An extensive database was created with the ArcGis 10.8 package, using publicly available LandSat satellite images as primary data in addition to ground surveys to build the model. The principles of the construction of the geographic information system of modern GIS technology were developed, the boundary and initial condition of the research area were evaluated, and forecasts and recommendations were given.

Keywords: irrigation channel, groundwater, collector, meliorative measures

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Authors: Alilu Getahun Sulito

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Exceptional floods are now prevalent in many places in Ethiopia, resulting in a large number of human deaths and property destruction. Lake Boyo watershed, in particular, had also traditionally been vulnerable to flash floods throughout the Boyo watershed. The goal of this research is to create flood and inundation maps for the Boyo Catchment. The integration of Geographic information system(GIS) technology and the hydraulic model (HEC-RAS) were utilized as methods to attain the objective. The peak discharge was determined using Fuller empirical methodology for intervals of 5, 10, 15, and 25 years, and the results were 103.2 m3/s, 158 m3/s, 222 m3/s, and 252 m3/s, respectively. River geometry, boundary conditions, manning's n value of varying land cover, and peak discharge at various return periods were all entered into HEC-RAS, and then an unsteady flow study was performed. The results of the unsteady flow study demonstrate that the water surface elevation in the longitudinal profile rises as the different periods increase. The flood inundation charts clearly show that regions on the right and left sides of the river with the greatest flood coverage were 15.418 km2 and 5.29 km2, respectively, flooded by 10,20,30, and 50 years. High water depths typically occur along the main channel and progressively spread to the floodplains. The latest study also found that flood-prone areas were disproportionately affected on the river's right bank. As a result, combining GIS with hydraulic modelling to create a flood inundation map is a viable solution. The findings of this study can be used to care again for the right bank of a Boyo River catchment near the Boyo Lake kebeles, according to the conclusion. Furthermore, it is critical to promote an early warning system in the kebeles so that people can be evacuated before a flood calamity happens. Keywords: Flood, Weira River, Boyo, GIS, HEC- GEORAS, HEC- RAS, Inundation Mapping

Keywords: Weira River, Boyo, GIS, HEC- GEORAS, HEC- RAS, Inundation Mapping

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Authors: Sweeti, Anoop Kant Godiyal, Neha Singh, Sneh Anand, B. K. Panigrahi, Jayasree Santhosh

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This work is about developing a tool for visualization and segmentation of Electroencephalograph (EEG) signals based on frequency domain features. Change in the frequency domain characteristics are correlated with change in mental state of the subject under study. Proposed algorithm provides a way to represent the change in the mental states using the different frequency band powers in form of segmented EEG signal. Many segmentation algorithms have been suggested in literature having application in brain computer interface, epilepsy and cognition studies that have been used for data classification. But the proposed method focusses mainly on the better presentation of signal and that’s why it could be a good utilization tool for clinician. Algorithm performs the basic filtering using band pass and notch filters in the range of 0.1-45 Hz. Advanced filtering is then performed by principal component analysis and wavelet transform based de-noising method. Frequency domain features are used for segmentation; considering the fact that the spectrum power of different frequency bands describes the mental state of the subject. Two sliding windows are further used for segmentation; one provides the time scale and other assigns the segmentation rule. The segmented data is displayed second by second successively with different color codes. Segment’s length can be selected as per need of the objective. Proposed algorithm has been tested on the EEG data set obtained from University of California in San Diego’s online data repository. Proposed tool gives a better visualization of the signal in form of segmented epochs of desired length representing the power spectrum variation in data. The algorithm is designed in such a way that it takes the data points with respect to the sampling frequency for each time frame and so it can be improved to use in real time visualization with desired epoch length.

Keywords: de-noising, multi-channel data, PCA, power spectra, segmentation

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Authors: Ahmad Mohammad Sharqi, Mohamed Hechmi El Ouni, Saleh Alsulamy

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Due to the emerging technologies revolution worldwide, the need to exploit and employ innovative technologies for other functions and purposes in different aspects has become a remarkable matter. Saudi Arabia is considered one of the most powerful economic countries in the world, where the construction sector participates effectively in its economy. Thus, the construction sector in KSA should convoy the rapid digital revolution and transformation and implement smart devices on sites. A Smart Construction Site (SCS) includes smart devices, artificial intelligence, the internet of things, augmented reality, building information modeling, geographical information systems, and cloud information. This paper aims to study the level of implementation of SCS in KSA, analyze the obstacles and challenges of adopting SCS and find out critical success factors for its implementation. A survey of close-ended questions (scale and multi-choices) has been conducted on professionals in the construction sector of Saudi Arabia. A total number of twenty-nine questions has been prepared for respondents. Twenty-four scale questions were established, and those questions were categorized into several themes: quality, scheduling, cost, occupational safety and health, technologies and applications, and general perception. Consequently, the 5-point Likert scale tool (very low to very high) was adopted for this survey. In addition, five close-ended questions with multi-choice types have also been prepared; these questions have been derived from a previous study implemented in the United Kingdom (UK) and the Dominic Republic (DR), these questions have been rearranged and organized to fit the structured survey in order to place the Kingdom of Saudi Arabia in comparison with the United Kingdom (UK) as well as the Dominican Republic (DR). A total number of one hundred respondents have participated in this survey from all regions of the Kingdom of Saudi Arabia: southern, central, western, eastern, and northern regions. The drivers, obstacles, and success factors for implementing smart devices and technologies in KSA’s construction sector have been investigated and analyzed. Besides, it has been concluded that KSA is on the right path toward adopting smart construction sites with attractive results comparable to and even better than the UK in some factors.

Keywords: artificial intelligence, construction projects management, internet of things, smart construction sites, smart devices

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Authors: А. I. Dovgyalo, S. O. Nekrasova, D. V. Sarmin, A. A. Shimanov, D. A. Uglanov

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Usually liquefied natural gas (LNG) gasification is performed due to atmospheric heat. In order to produce a liquefied gas a sufficient amount of energy is to be consumed (about 1 kW∙h for 1 kg of LNG). This study offers a number of solutions, allowing using a cold energy of LNG. In this paper it is evaluated the application turbines installed behind the evaporator in LNG complex due to its work additional energy can be obtained and then converted into electricity. At the LNG consumption of G=1000kg/h the expansion work capacity of about 10 kW can be reached. Herewith-open Rankine cycle is realized, where a low capacity cryo-pump (about 500W) performs its normal function, providing the cycle pressure. Additionally discussed an application of Stirling engine within the LNG complex also gives a possibility to realize cold energy. Considering the fact, that efficiency coefficient of Stirling engine reaches 50 %, LNG consumption of G=1000 kg/h may result in getting a capacity of about 142 kW of such a thermal machine. The capacity of the pump, required to compensate pressure losses when LNG passes through the hydraulic channel, will make 500 W. Apart from the above-mentioned converters, it can be proposed to use thermoelectric generating packages (TGP), which are widely used now. At present, the modern thermoelectric generator line provides availability of electric capacity with coefficient of efficiency up to 15%. In the proposed complex, it is suggested to install the thermoelectric generator on the evaporator surface is such a way, that the cold end is contacted with the evaporator’s surface, and the hot one – with the atmosphere. At the LNG consumption of G=1000 kgг/h and specified coefficient of efficiency the capacity of the heat flow Qh will make about 32 kW. The derivable net electric power will be P=4,2 kW, and the number of packages will amount to about 104 pieces. The carried out calculations demonstrate the research perceptiveness in this field of propulsion plant development, as well as allow realizing the energy saving potential with the use of liquefied natural gas and other cryogenics technologies.

Keywords: cold energy, gasification, liquefied natural gas, electricity

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Authors: Najla Alhkalaf

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The focus of this study is answering the following question: How do e-government services in Bahrain support the productivity of SMEs? This study examines the current E-government function in enhancing SME productivity in Bahrain through analysing the efficiency of e- government by viewing its facilitators and barriers from the perspective of different stakeholders. The study aims to identify and develop best practice guidelines with the end-goal of creating a standardised channel of communication between e-government and SMEs that fulfil the requirement of SME owners, and thus achieve the prime objective of e-government. E-government services for SMEs have been offered in Bahrain since 2005. However, the current services lack the required mechanism for SMEs to fully take advantage of these services because of lagging communication between service provider and end-user. E-government employees believe that a lack of awareness and trust are the main stumbling block, whereas the SME owners believe that there is a lack of sufficiency in the content and efficiency provided through e- services. A questionnaire has been created based on a pilot study that highlighted the main indicators of e-government efficiency and SMEs productivity as well as previous studies conducted on this subject. This allowed for quantitative data to be extracted. Also interviews were conducted with SME owners and government employees from both case studies, which formed the qualitative data for this study. The findings portray that both the service provider and service receiver largely agree on the existence of most of the technical and administrative barriers. However, the data reflects a level of dissatisfaction from the SME side, which contradicts with the perceived level of satisfaction from the government employees. Therefore, the data supports the argument that assures the existence of a communication gap between stakeholders. To this effect, this research would help build channels of communication between stakeholders, and then induces a plan unlocking the potential of e-government application. The conclusions of this study will help devise an optimised E-government strategy for Bahrain.

Keywords: e-government, SME, e-services, G2B, government employees' perspective, entrepreneurs' perspective, enterprise

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Authors: Ruthanne Tobin

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As our data-driven, cloud-based, knowledge-centric lives become ever more global, mobile, and digital, educational systems everywhere are struggling to keep pace. Schools need to prepare students to become critical-thinking, tech-savvy, life-long learners who are engaged and adaptable enough to find their unique calling in a post-industrial world of work. Recognizing that no nation can afford poor achievement or high dropout rates without jeopardizing its social and economic future, the thirty-two nations of the OECD are launching initiatives to redesign schools, generally under the banner of Personalized Learning or 21st Century Learning. Their intention is to transform education by situating students as co-enquirers and co-contributors with their teachers of what, when, and how learning happens for each individual. In this focused review of the 2007-2017 literature on personalized learning, the author sought answers to two main questions: “What are the theoretical frameworks that guide personalized learning?” and “What is the conceptual understanding of the model?” Ultimately, the review reveals that, although the research area is overly theorized and under-substantiated, it does provide a significant body of knowledge about this potentially transformative educational restructuring. For example, it addresses the following questions: a) What components comprise a PL model? b) How are teachers facilitating agency (voice & choice) in their students? c) What kinds of systems, processes and procedures are being used to guide the innovation? d) How is learning organized, monitored and assessed? e) What role do inquiry based models play? f) How do teachers integrate the three types of knowledge: Content, pedagogical and technological? g) Which kinds of forces enable, and which impede, personalizing learning? h) What is the nature of the collaboration among teachers? i) How do teachers co-regulate differentiated tasks? One finding of the review shows that while technology can dramatically expand access to information, expectations of its impact on teaching and learning are often disappointing unless the technologies are paired with excellent pedagogies in order to address students’ needs, interests and aspirations. This literature review fills a significant gap in this emerging field of research, as it serves to increase conceptual clarity that has hampered both the theorizing and the classroom implementation of a personalized learning model.

Keywords: curriculum change, educational innovation, personalized learning, school reform

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Authors: D. López-Mancilla, J. M. Roblero-Villa

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Since 1990, the research on chaotic dynamics has received considerable attention, particularly in light of potential applications of this phenomenon in secure communications. Data encryption using chaotic systems was reported in the 90's as a new approach for signal encoding that differs from the conventional methods that use numerical algorithms as the encryption key. The algorithms for image encryption have received a lot of attention because of the need to find security on image transmission in real time over the internet and wireless networks. Known algorithms for image encryption, like the standard of data encryption (DES), have the drawback of low level of efficiency when the image is large. The encrypting based on chaos proposes a new and efficient way to get a fast and highly secure image encryption. In this work, a user interface for image encryption and a novel and easiest way to encrypt images using chaos are presented. The main idea is to reshape any image into a n-dimensional vector and combine it with vector extracted from a chaotic system, in such a way that the vector image can be hidden within the chaotic vector. Once this is done, an array is formed with the original dimensions of the image and turns again. An analysis of the security of encryption from the images using statistical analysis is made and is used a stage of optimization for image encryption security and, at the same time, the image can be accurately recovered. The user interface uses the algorithms designed for the encryption of images, allowing you to read an image from the hard drive or another external device. The user interface, encrypt the image allowing three modes of encryption. These modes are given by three different chaotic systems that the user can choose. Once encrypted image, is possible to observe the safety analysis and save it on the hard disk. The main results of this study show that this simple method of encryption, using the optimization stage, allows an encryption security, competitive with complicated encryption methods used in other works. In addition, the user interface allows encrypting image with chaos, and to submit it through any public communication channel, including internet.

Keywords: image encryption, chaos, secure communications, user interface

Procedia PDF Downloads 489

Authors: Syed Noaman Shah

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The current paper evaluates the effect of external public debt risk on the borrowing cost of private non-financial firms in euro zone. Further, the study also treats the impact of austerity measures on syndicated-loan spreads of private firm followed by euro area member states to revive the economic growth in the region. To test these hypotheses, we follow multivariate ordinary least square estimation method to assess the effect of external public debt on the borrowing cost of private firms. By using foreign syndicated-loan issuance data of non-financial private firms from 2005 to 2011, we attempt to gauge how the private financing cost varies with high levels of sovereign external debt prevalent in the euro zone. Our results suggest significant effect of external public debt on the borrowing cost of private firm. In particular, an increase in external public debt by one standard deviation from its sample mean raises syndicated-loan spread by 89 bps. Furthermore, weak creditor rights protection prevalent in member states deepens this effect. However, we do not find any significant effect of domestic public debt on the private sector borrowing cost. In addition, the results show significant effect of austerity measures on private financing cost, both in normal and in crisis period in the euro zone. In particular, one standard deviation change in fiscal consolidation conditional mean reduces the syndicated-loan spread by 22 bps. In turn, it indicates strong presence of credibility channel due to austerity measures in euro area region.

Keywords: corporate debt, fiscal consolidation, sovereign debt, syndicated-loan spread

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Authors: Ali Alsawayeh, Ibrahim Eldanfour

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This paper examines the extent of disclosure of oil and gas reserve quantum in annual reports of international oil and gas exploration and production companies, particularly companies in untested international markets, such as Canada, the UK and the US, and seeks to determine the underlying factors that affect the level of disclosure on oil reserve quantum. The study is concerned with the usefulness of disclosure of oil and gas reserves quantum to investors and other users. Given the primacy of the annual report (10-k) as a source of supplemental reserves data about the company and as the channel through which companies disseminate information about their performance, the annual reports for one year (2009) were the central focus of the study. This comparative study seeks to establish whether differences exist between the sample companies, based on new disclosure requirements by the Securities and Exchange Commission (SEC) in respect of reserves classification and definition. The extent of disclosure of reserve is provided and compared among the selected companies. Statistical analysis is performed to determine whether any differences exist in the extent of disclosure of reserve under the determinant variables. This study shows that some factors would affect the extent of disclosure of reserve quantum in the above-mentioned countries, namely: company’s size, leverage and quality of auditor. Companies that provide reserves quantum in detail appear to display higher size. The findings also show that the level of leverage has affected companies’ reserves quantum disclosure. Indeed, companies that provide detailed reserves quantum disclosure tend to employ a ‘high-quality auditor’. In addition, the study found significant independent variable such as Profit Sharing Contracts (PSC). This factor could explain variations in the level of disclosure of oil reserve quantum between the contractor and host governments. The implementation of SEC oil and gas reporting requirements do not enhance companies’ valuation because the new rules are based only on past and present reserves information (proven reserves); hence, future valuation of oil and gas companies is missing for the market.

Keywords: comparison, company characteristics, disclosure, reserve quantum, regulation

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Authors: Ella Sèdé Maforikan

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Accurate land cover mapping is essential for effective environmental monitoring and natural resources management. This study focuses on assessing the classification performance of two satellite datasets and evaluating the impact of different input feature combinations on classification accuracy in the Beterou catchment, situated in the northern part of Benin. Landsat-8 and Sentinel-2 images from June 1, 2020, to March 31, 2021, were utilized. Employing the Random Forest (RF) algorithm on Google Earth Engine (GEE), a supervised classification categorized the land into five classes: forest, savannas, cropland, settlement, and water bodies. GEE was chosen due to its high-performance computing capabilities, mitigating computational burdens associated with traditional land cover classification methods. By eliminating the need for individual satellite image downloads and providing access to an extensive archive of remote sensing data, GEE facilitated efficient model training on remote sensing data. The study achieved commendable overall accuracy (OA), ranging from 84% to 85%, even without incorporating spectral indices and terrain metrics into the model. Notably, the inclusion of additional input sources, specifically terrain features like slope and elevation, enhanced classification accuracy. The highest accuracy was achieved with Sentinel-2 (OA = 91%, Kappa = 0.88), slightly surpassing Landsat-8 (OA = 90%, Kappa = 0.87). This underscores the significance of combining diverse input sources for optimal accuracy in land cover mapping. The methodology presented herein not only enables the creation of precise, expeditious land cover maps but also demonstrates the prowess of cloud computing through GEE for large-scale land cover mapping with remarkable accuracy. The study emphasizes the synergy of different input sources to achieve superior accuracy. As a future recommendation, the application of Light Detection and Ranging (LiDAR) technology is proposed to enhance vegetation type differentiation in the Beterou catchment. Additionally, a cross-comparison between Sentinel-2 and Landsat-8 for assessing long-term land cover changes is suggested.

Keywords: land cover mapping, Google Earth Engine, random forest, Beterou catchment

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Authors: Kristina Jansen, Maximilian Lennartz, Patrick Lebok, Guido Sauter, Ronald Simon, David Dum, Stefan Steurer

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DOG1 (Discovered on GIST1) is a voltage-gated calcium-activated chloride and bicarbonate channel that is highly expressed in interstitial cells of Cajal and in gastrointestinal stromal tumors (GIST) derived from Cajal cells. To systematically determine in what tumor entities and normal tissue types DOG1 may be further expressed, a tissue microarray (TMA) containing 15,965 samples from 121 different tumor types and subtypes as well as 608 samples of 76 different normal tissue types were analyzed by immunohistochemistry. DOG1 immunostaining was found in 67 tumor types, including GIST (95.7%), esophageal squamous cell carcinoma (31.9%), pancreatic ductal adenocarcinoma (33.6%), adenocarcinoma of the Papilla Vateri (20%), squamous cell carcinoma of the vulva (15.8%) and the oral cavity (15.3%), mucinous ovarian cancer (15.3%), esophageal adenocarcinoma (12.5%), endometrioid endometrial cancer (12.1%), neuroendocrine carcinoma of the colon (11.1%) and diffuse gastric adenocarcinoma (11%). Low level-DOG1 immunostaining was seen in 17 additional tumor entities. DOG1 expression was unrelated to histopathological parameters of tumor aggressiveness and/or patient prognosis in cancers of the breast (n=1,002), urinary bladder (975), ovary (469), endometrium (173), stomach (233), and thyroid gland (512). High DOG1 expression was linked to estrogen receptor expression in breast cancer (p<0.0001) and the absence of HPV infection in squamous cell carcinomas (p=0.0008). In conclusion, our data identify several tumor entities that can show DOG1 expression levels at similar levels as in GIST. Although DOG1 is tightly linked to a diagnosis of GIST in spindle cell tumors, the differential diagnosis is much broader in DOG1 positive epithelioid neoplasms.

Keywords: biomarker, DOG1, immunohistochemistry, tissue microarray

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Authors: R. C. Tiwari, N. P. Bhandary, D. B. Thapa Chhetri, R. Yatabe

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The research enlightens the various issues of lake expansion and stability of the moraine dam of Imja lake. The Imja lake considered that the world highest altitude lake (5010m from m.s.l.), located in the Khumbu, Sagarmatha region of Nepal (27.90 N and 86.90 E) was reported as one of the fast growing glacier lakes in the Nepal Himalaya. The research explores a common phenomenon of lake expansion and stability issues of moraine dam to justify the necessity of lake lowering efforts if any in future in other glacier lakes in Nepal Himalaya. For this, we have explored the root causes of rapid lake expansion along with crucial factors responsible for the stability of moraine mass. This research helps to understand the structure of moraine dam and the ice, water and moraine interactions to the strength of moraine dam. The nature of permafrost layer and its effects on moraine dam stability is also studied here. The detail Geo-Technical properties of moraine mass of Imja lake gives a clear picture of the strength of the moraine material and their interactions. The stability analysis of the moraine dam under the consideration of strong ground motion of 7.8Mw 2015 Barpak-Gorkha and its major aftershock 7.3Mw Kodari, Sindhupalchowk-Dolakha border, Nepal earthquakes have also been carried out here to understand the necessity of lake lowering efforts. The lake lowering effort was recently done by Nepal Army by constructing an open channel and lowered 3m. And, it is believed that the entire region is now safe due to continuous draining of lake water by 3m. But, this option does not seem adequate to offer a significant risk reduction to downstream communities in this much amount of volume and depth, lowering as in the 75 million cubic meter water impounded with an average depth of 148.9m.

Keywords: finite element method, glacier, moraine, stability

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Authors: P. Karthick, K. Mahesh

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Video has become an increasingly significant component of our digital everyday contact. With the advancement of greater contents and shows of the resolution, its significant volume poses serious obstacles to the objective of receiving, distributing, compressing, and revealing video content of high quality. In this paper, we propose the primary beginning to complete a deep video compression model that jointly upgrades all video compression components. The video compression method involves splitting the video into frames, comparing the images using convolutional neural networks (CNN) to remove duplicates, repeating the single image instead of the duplicate images by recognizing and detecting minute changes using generative adversarial network (GAN) and recorded with long short-term memory (LSTM). Instead of the complete image, the small changes generated using GAN are substituted, which helps in frame level compression. Pixel wise comparison is performed using K-nearest neighbours (KNN) over the frame, clustered with K-means, and singular value decomposition (SVD) is applied for each and every frame in the video for all three color channels [Red, Green, Blue] to decrease the dimension of the utility matrix [R, G, B] by extracting its latent factors. Video frames are packed with parameters with the aid of a codec and converted to video format, and the results are compared with the original video. Repeated experiments on several videos with different sizes, duration, frames per second (FPS), and quality results demonstrate a significant resampling rate. On average, the result produced had approximately a 10% deviation in quality and more than 50% in size when compared with the original video.

Keywords: video compression, K-means clustering, convolutional neural network, generative adversarial network, singular value decomposition, pixel visualization, stochastic gradient descent, frame per second extraction, RGB channel extraction, self-detection and deciding system

Procedia PDF Downloads 187

Authors: Jaypalsinh Parmar, Pintu Nakrani, Bhaumik Shah

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Digital Elevation Model (DEM) is elevation data of the virtual grid on the ground. DEM can be used in application in GIS such as hydrological modelling, flood forecasting, morphometrical analysis and surveying etc.. For morphometrical analysis the stream flow network plays a very important role. DEM lacks accuracy and cannot match field data as it should for accurate results of morphometrical analysis. The present study focuses on comparing the Agree method and the conventional Shortest path method for finding out morphometric parameters in the flat region of the Lower Tapi Basin which is located in the western India. For the present study, open source SRTM (Shuttle Radar Topography Mission with 1 arc resolution) and toposheets issued by Survey of India (SOI) were used to determine the morphometric linear aspect such as stream order, number of stream, stream length, bifurcation ratio, mean stream length, mean bifurcation ratio, stream length ratio, length of overland flow, constant of channel maintenance and aerial aspect such as drainage density, stream frequency, drainage texture, form factor, circularity ratio, elongation ratio, shape factor and relief aspect such as relief ratio, gradient ratio and basin relief for 53 catchments of Lower Tapi Basin. Stream network was digitized from the available toposheets. Agree DEM was created by using the SRTM and stream network from the toposheets. The results obtained were used to demonstrate a comparison between the two methods in the flat areas.

Keywords: agree method, morphometric analysis, lower Tapi basin, shortest path method

Procedia PDF Downloads 239

Authors: Osamede Asowata, Christo Pienaar, Johan Bekker

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Photovoltaic (PV) modules may become a trend for future PV systems because of their greater flexibility in distributed system expansion, easier installation due to their nature, and higher system-level energy harnessing capabilities under shaded or PV manufacturing mismatch conditions. This is as compared to the single or multi-string inverters. Novel residential scale PV arrays are commonly connected to the grid by a single DC–AC inverter connected to a series, parallel or series-parallel string of PV panels, or many small DC–AC inverters which connect one or two panels directly to the AC grid. With an increasing worldwide interest in sustainable energy production and use, there is renewed focus on the power electronic converter interface for DC energy sources. Three specific examples of such DC energy sources that will have a role in distributed generation and sustainable energy systems are the photovoltaic (PV) panel, the fuel cell stack, and batteries of various chemistries. A high-efficiency inverter using Metal Oxide Semiconductor Field-Effect Transistors (MOSFETs) for all active switches is presented for a non-isolated photovoltaic and AC-module applications. The proposed configuration features a high efficiency over a wide load range, low ground leakage current and low-output AC-current distortion with no need for split capacitors. The detailed power stage operating principles, pulse width modulation scheme, multilevel bootstrap power supply, and integrated gate drivers for the proposed inverter is described. Experimental results of a hardware prototype, show that not only are MOSFET efficient in the system, it also shows that the ground leakage current issues are alleviated in the proposed inverter and also a 98 % maximum associated driver circuit is achieved. This, in turn, provides the need for a possible photovoltaic panel switching technique. This will help to reduce the effect of cloud movements as well as improve the overall efficiency of the system.

Keywords: grid connected photovoltaic (PV), Matlab efficiency simulation, maximum power point tracking (MPPT), module integrated converters (MICs), multilevel converter, series connected converter

Procedia PDF Downloads 127

Authors: Paolo Di Pietro, Matteo Lelli, Kinjal Parmar

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Water hazards are consistently identified as among the highest global risks in terms of impact. Riverbank protection plays a key role in flood risk management. For erosion control and scour protection, flexible solutions like gabions & mattresses are being used since quite some time now. The efficacy of erosion control systems depends both on the ability to prevent soil loss underneath, as well as to maintain their integrity under the effects of the water flow. The paper presents the results of a research carried out at the Colorado State University on the performance of double twisted wire mesh products, known as Reno Mattresses, used as soil erosion control system. Mattresses were subjected to various flow conditions on a 10m long flume where they were placed on a 0.30 m thick soil layer. The performance against erosion was evaluated by assessing the effect of the stone motion inside the mattress combined with the condition of incipient soil erosion underneath, in relationship to the mattress thickness, the filling stone properties and under variable hydraulic flow regimes. While confirming the stability obtained using a conventional design approach (commonly referred to tractive force theories), the results of the research allowed to introduce a new performance limit based on incipient soil erosion underneath the revetment. Based on the research results, the authors propose to express the shear resistance of mattresses used as soil erosion control system as a function of the size of the filling stones, their uniformity, their unit weight, the thickness of the mattress, and the presence of vertical connecting elements between the mattress lid and bottom.

Keywords: Reno Mattress, riverbank protection, hydraulics, full scale tests

Procedia PDF Downloads 24