Search results for: deep networks

Authors: Eugene Stepanov, Arkadi Ponossov

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Ordinary differential equations with switching nonlinearities constitute a very useful tool in many applications. The solutions of such equations can usually be calculated analytically if they cross the discontinuities transversally. Otherwise, one has trajectories that slides along the discontinuity, and the calculations become less straightforward in this case. For instance, one of the problems one faces is non-uniqueness of the sliding modes. In the presentation, it is proposed to apply the theory of hybrid dynamical systems to calculate the solutions that are ‘hidden’ in the discontinuities. Roughly, one equips the underlying switched system with an explicitly designed discrete dynamical system (‘automaton’), which governs the dynamics of the switched system. This construction ‘splits’ the dynamics, which, as it is shown in the presentation, gives uniqueness of the resulting hybrid trajectories and at the same time provides explicit formulae for them. Projecting the hybrid trajectories back onto the original continuous system explains non-uniqueness of its trajectories. The automaton is designed with the help of the attractors of the specially constructed adjoint dynamical system. Several examples are provided in the presentation, which supports the efficiency of the suggested scheme. The method can be of interest in control theory, gene regulatory networks, neural field models and other fields, where switched dynamics is a part of the analysis.

Keywords: hybrid dynamical systems, singular perturbation analysis, sliding modes, switched dynamics

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Authors: Yufeng Li, Yinan Ma, Jing Wu, Chengnian Long

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Infrared object detection aims at separating small and dim target from clutter background and its capabilities extend beyond the limits of visible light, making it invaluable in a wide range of applications such as improving safety, security, efficiency, and functionality. However, existing methods are usually sensitive to the noise of the input infrared image, leading to a decrease in target detection accuracy and an increase in the false alarm rate in high-noise environments. To address this issue, an infrared small target detection algorithm called YOLO-IR is proposed in this paper to improve the robustness to high infrared noise. To address the problem that high noise significantly reduces the clarity and reliability of target features in infrared images, we design a soft-threshold coordinate attention mechanism to improve the model’s ability to extract target features and its robustness to noise. Since the noise may overwhelm the local details of the target, resulting in the loss of small target features during depth down-sampling, we propose a deep and shallow feature fusion neck to improve the detection accuracy. In addition, because the generalized Intersection over Union (IoU)-based loss functions may be sensitive to noise and lead to unstable training in high-noise environments, we introduce a Wasserstein-distance based loss function to improve the training of the model. The experimental results show that YOLO-IR achieves a 5.0% improvement in recall and a 6.6% improvement in F1-score over existing state-of-art model.

Keywords: infrared small target detection, high noise, robustness, soft-threshold coordinate attention, feature fusion

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Authors: Shivendra Pratap Singh, Rishabh Sharma

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The widespread adoption of mobile technology in recent years has revolutionized the way we communicate and access information. The evolution of mobile systems has been rapid and impactful, shaping our lives and changing the way we live and work. However, despite its significant influence, the history and development of mobile technology are not well understood by the general public. This research paper aims to examine the history, technology and future of mobile systems, exploring their evolution from early mobile phones to the latest smartphones and beyond. The study will analyze the technological advancements and innovations that have shaped the mobile industry, from the introduction of mobile internet and multimedia capabilities to the integration of artificial intelligence and 5G networks. Additionally, the paper will also address the challenges and opportunities facing the future of mobile technology, such as privacy concerns, battery life, and the increasing demand for high-speed internet. Finally, the paper will also provide insights into potential future developments and innovations in the mobile sector, such as foldable phones, wearable technology, and the Internet of Things (IoT). The purpose of this research paper is to provide a comprehensive overview of the history, technology, and future of mobile systems, shedding light on their impact on society and the challenges and opportunities that lie ahead.

Keywords: mobile technology, artificial intelligence, networking, iot, technological advancements, smartphones

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Authors: Huan Zhang, Darius K. S Chan

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Despite a large number of studies linking emotional labor and its detrimental impact for laborer, research on how emotional labor would influence the receiver is still in its infancy. Especially under the call for “people management”, supervisors inside the organization are more inclined to display happy mood to support their employees, thus endorsing emotional labor. The present study focuses on the employees in the service industry as emotional labor recipients and investigates how they respond to their supervisors’ emotional display, given their sensitivity to emotional cues. Targeted at a sample of 250 survey data from a wide range of customer service professions, this ongoing study examines how perceived supervisory emotional labor would moderate the relationship between employees surface acting and their well-being. Our major hypotheses are that employees’ surface acting predicts well-being level, and that perceived supervisory emotional labor to moderate the surface acting—outcome links. Preliminary findings have provided some support to the hypothesized model. Specifically, supervisors who are perceived to be high in surface acting are also regarded as fake and pseudo, hence the enhancing the detrimental effect of employees’ surface acting is attenuated, resulting in lower job satisfaction, higher physical stress and burnout; whereas perceived high supervisor’s deep acting, as associated with genuine and authenticity, buffers the negative impact and leads to higher job satisfaction, lower physical stress and burnout. This study first confirms the negative impacts of the surface acting on well-being for service industry employees as laborer and then extends the emotional labor studies by considering them as recipients of supervisory emotional labor. The findings provide insights for leaders by pointing out the importance of authentic emotional expression in workplace.

Keywords: perceived supervisory emotional labor, surface acting, well-being

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Authors: Padmini S. Navalgund, Manasi Naik, Ujwala Patil

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Road hump is a semi-cylindrical elevation on the road made across specific locations of the road. The vehicle needs to maneuver the hump by reducing the speed to avoid car damage and pass over the road hump safely. Road Humps on road surfaces, if identified in advance, help to maintain the security and stability of vehicles, especially in adverse visibility conditions, viz. night scenarios. We have proposed a deep learning architecture adaptation by implementing the MISH activation function and developing a new classification loss function called "Effective Focal Loss" for Indian road humps detection in adverse light scenarios. We captured images comprising of marked and unmarked road humps from two different types of cameras across South India to build a heterogeneous dataset. A heterogeneous dataset enabled the algorithm to train and improve the accuracy of detection. The images were pre-processed, annotated for two classes viz, marked hump and unmarked hump. The dataset from these images was used to train the single-stage object detection algorithm. We utilised an algorithm to synthetically generate reduced visible road humps scenarios. We observed that our proposed framework effectively detected the marked and unmarked hump in the images in clear and ad-verse light environments. This architectural adaptation sets up an option for early detection of Indian road humps in reduced visibility conditions, thereby enhancing the autonomous driving technology to handle a wider range of real-world scenarios.

Keywords: Indian road hump, reduced visibility condition, low light condition, adverse light condition, marked hump, unmarked hump, YOLOv9

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Authors: Dixon, Lieh-Chi Su, Hsiao-Ling Yu, Ren-Yi Huang, Yung-Tan Lee

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The present paper analyzed the major, trace elements, rare earth elements of these Cenozoic basalts and combined with Sr-Nd isotopic compositions to discuss the petrogenesis of these basalts and the tectonic setting of the study area. Based on major, trace elements and fractional crystallization model we suggest that the basaltic magma has experienced olivine, clinopyroxene, and plagioclase fractionation during its evolution. Spidergrams and REE patterns reveal that Cenozoic basalts found in the Jiashan County, Anhui Province have geochemical characteristics similar to those of ocean island basalts(OIB) suggesting a derivation related to OIB-like mantle source. The slight positive Nb and Ti anomalies found in basaltic rocks of this study suggest the presence of Ti-bearing minerals in the mantle source and these Ti-bearing minerals had contributed to basaltic magma during partial melting, indicating a metasomatic event might have occurred before the partial melting. Based on 143Nd/144Nd vs. 87Sr/86Sr diagram we suggest that basalts of this study can be produced by MORB and EM-I components mixing and small degree of partial melting may be the major controlling factor during generation of basaltic magma. Some basaltic magma may be derived from partial melting of EM-Ⅰ heated by the upwelling asthenospheric mantle. The basalts fall within the WPB field in the discriminant plot of 2Nb-Zr/4-Y indicate that the volcanic activities in this region may be closely related to deep continental rifting process.

Keywords: geochemistry, cenozoic basalts, Anhui Province, Nushan Geopark, tectonic setting, fractionation

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Authors: Raghavi C. Janaswamy

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In the healthcare sector, heterogenous data elements such as patients, diagnosis, symptoms, conditions, observation text from physician notes, and prescriptions form the essentials of the Electronic Health Record (EHR). The data in the form of clear text and images are stored or processed in a relational format in most systems. However, the intrinsic structure restrictions and complex joins of relational databases limit the widespread utility. In this regard, the design and development of realistic mapping and deep connections as real-time objects offer unparallel advantages. Herein, a graph neural network-based classification of EHR data has been developed. The patient conditions have been predicted as a node classification task using a graph-based open source EHR data, Synthea Database, stored in Tigergraph. The Synthea DB dataset is leveraged due to its closer representation of the real-time data and being voluminous. The graph model is built from the EHR heterogeneous data using python modules, namely, pyTigerGraph to get nodes and edges from the Tigergraph database, PyTorch to tensorize the nodes and edges, PyTorch-Geometric (PyG) to train the Graph Neural Network (GNN) and adopt the self-supervised learning techniques with the AutoEncoders to generate the node embeddings and eventually perform the node classifications using the node embeddings. The model predicts patient conditions ranging from common to rare situations. The outcome is deemed to open up opportunities for data querying toward better predictions and accuracy.

Keywords: electronic health record, graph neural network, heterogeneous data, prediction

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Authors: Keundong Lee, Dongha Yoo, Youngbin Tchoe, Gyu-Chul Yi

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Light emitting diode (LED) array is an ideal optical stimulation tool for optogenetics, which controls inhibition and excitation of specific neurons with light-sensitive ion channels or pumps. Although a fiber-optic cable with an external light source, either a laser or LED mechanically connected to the end of the fiber-optic cable has widely been used for illumination on neural tissue, a new approach to use micro LEDs (µLEDs) has recently been demonstrated. The LEDs can be placed directly either on the cortical surface or within the deep brain using a penetrating depth probe. Accordingly, this method would not need a permanent opening in the skull if the LEDs are integrated with miniature electrical power source and wireless communication. In addition, multiple color generation from single µLED cell would enable to excite and/or inhibit neurons in localized regions. Here, we demonstrate flexible and color tunable µLEDs for the optogenetic device applications. The flexible and color tunable LEDs was fabricated using multifaceted gallium nitride (GaN) nanorod arrays with GaN nanorods grown on InxGa1−xN/GaN single quantum well structures (SQW) anisotropically formed on the nanorod tips and sidewalls. For various electroluminescence (EL) colors, current injection paths were controlled through a continuous p-GaN layer depending on the applied bias voltage. The electric current was injected through different thickness and composition, thus changing the color of light from red to blue that the LED emits. We believe that the flexible and color tunable µLEDs enable us to control activities of the neuron by emitting various colors from the single µLED cell.

Keywords: light emitting diode, optogenetics, graphene, flexible optoelectronics

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Authors: B. Farahani, R. Fadil, A. Aboonabi, B. Hoffmann, J. Loscheider, K. Tavakolian, S. Arzanpour

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Wheelchair users spend long hours in a sitting position, and selecting the right cushion is highly critical in preventing pressure ulcers in that demographic. Pressure mapping systems (PMS) are typically used in clinical settings by therapists to identify the sitting profile and pressure points in the sitting area to select the cushion that fits the best for the users. A PMS is a flexible mat composed of arrays of distributed networks of flexible sensors. The output of the PMS systems is a color-coded image that shows the intensity of the pressure concentration. Therapists use the PMS images to compare different cushions fit for each user. This process is highly subjective and requires good visual memory for the best outcome. This paper aims to develop an image processing technique to analyze the images of PMS and provide an objective measure to assess the cushions based on their pressure distribution mappings. In this paper, we first reviewed the skeletal anatomy of the human sitting area and its relation to the PMS image. This knowledge is then used to identify the important features that must be considered in image processing. We then developed an algorithm based on those features to analyze the images and rank them according to their fit to the users' needs.

Keywords: dynamic cushion, image processing, pressure mapping system, wheelchair

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Authors: E. Karimi-Sibaki, A. Kharicha, M. Wu, A. Ludwig

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The standard electroslag remelting (ESR) process can ideally control the solidification of an ingot and produce homogeneous structure with minimum defects. However, the melt rate of electrode is rather low that makes the whole process uneconomical especially to produce small ingot sizes. In contrast, continuous casting is an economical process to produce small ingots such as billets at high casting speed. Unfortunately, deep liquid melt pool forms in the billet ingot of continuous casting that leads to center porosity and segregation. As such, continuous casting is not suitable to produce segregation prone alloys like tool steel or several super alloys. On the other hand, the electro slag rapid remelting (ESRR) process has advantages of both traditional ESR and continuous casting processes to produce billets. In the ESRR process, a T-shaped mold is used including a graphite ring that takes major amount of current through the mold. There are only a few reports available in the literature discussing about this topic. The research on the ESRR process is currently ongoing aiming to improve the design of the T-shaped mold, to decrease overall heat loss in the process, and to obtain a higher temperature at metal meniscus. In the present study, a 3D model is proposed to investigate the electromagnetic, thermal, and flow fields in the whole process as well as solidification of the billet ingot. We performed a fully coupled numerical simulation to explore the influence of the electromagnetically driven flow (MHD) on the thermal field in the slag and ingot. The main goal is to obtain some fundamental understanding of the formation of melt pool of the solidifying billet ingot in the ESRR process.

Keywords: billet ingot, magnetohydrodynamics (mhd), numerical simulation, remelting, solidification, t-shaped mold.

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Authors: B. Kenny

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The complications associated with transfusions are well documented, with the serious hazards of transfusion (SHOT) reporting system continuing to report deaths and serious morbidity due to the transfusion of allogenic blood. Many different sources including the TRICC trial, NHMRC and Cochrane recommending similar transfusion triggers/guidelines. Recent studies found the rate of infection (deep infection, wound infection, chest infection, urinary tract infection, and others) were purely a dose response relationship, increasing the Relative Risk by 3.44. It was also noted that each transfused patient stayed in hospital for one additional day. We hypothesise that providing an approved/standardised, guideline with a graphical summary of decision pathways for anaemic patients will reduce unnecessary transfusions. We retrospectively assessed patients undergoing primary knee or hip arthroplasties over a 4 year period, 1459 patients. Of these, 339 (23.24%) patients received allogenic blood transfusions and 858 units of blood were transfused, 9.14% of patients transfused had haemoglobin levels above 100 g/L, 7.67% of patients were transfused without knowing the haemoglobin level, 24 hours prior to transfusion initiation and 4.5% had possible transfusion reactions. Overall, 17% of allogenic transfusions topatients admitted to the Orthopaedic department within a 4 year period were outside NHMRC and Cochrane guidelines/recommendations. If our transfusion frequency is compared with that of other authors/hospitals, transfusion rates are consistently being high. We subsequently implemented a simple guideline for transfusion initiation. This guideline was then assessed. We found the transfusion rate post transfusion implementation to be significantly lower, without increase in patient morbidity or mortalitiy, p <0.001). Transfusion rates and patient outcome can be optimized by a simple graphical aid for decision making.

Keywords: transfusion, morbidity, mortality, neck of femur, fracture, arthroplasty, rehabilitation

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Authors: Nicanor Garcia Alvarez, Belarmino Adenso-Diaz, Laura Calzada Infante

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In recent years, researchers have shown an interest in modelling maritime traffic as a complex network. In this paper, we propose a bipartite weighted network to model maritime traffic and detect port maritime communities. The bipartite weighted network considers two different types of nodes. The first one represents Spanish ports, while the second one represents the countries with which there is major import/export activity. The flow among both types of nodes is modeled by weighting the volume of product transported. To illustrate the model, the data is segmented by each type of traffic. This will allow fine tuning and the creation of communities for each type of traffic and therefore finding similar ports for a specific type of traffic, which will provide decision-makers with tools to search for alliances or identify their competitors. The traffic with the greatest impact on the Spanish gross domestic product is selected, and the evolution of the communities formed by the most important ports and their differences between 2019 and 2009 will be analyzed. Finally, the set of communities formed by the ports of the Spanish port system will be inspected to determine global similarities between them, analyzing the sum of the membership of the different ports in communities formed for each type of traffic in particular.

Keywords: bipartite networks, competition, infomap, maritime traffic, port communities

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Authors: Kruti Dave

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Social media marketing is an essential component of 21st-century business. Social media platforms enable small and medium-sized businesses to enhance brand recognition, generate leads and sales. However, the research on social media marketing is still fragmented and focuses on specific topics, such as effective communication techniques. Since the various ways in which social media impacts individuals and companies alike, the authors of this article focus on the origin, impacts, and current state of Social Media, emphasizing their significance as customer empowerment agents. It illustrates their potential and current responsibilities as part of the corporate business strategy and also suggests several methods to engage them as marketing tools. The focus of social media marketing ranges from defenders to explorers, the culture of Social media marketing encompasses the poles of conservatism and modernity, social media marketing frameworks lie between hierarchies and networks, and its management goes from autocracy to anarchy. This research proposes an integrative framework for small and medium-sized businesses through social media, and the influence of the same will be measured. This strategy will help industry experts to understand this new era. We propose an axiom: Social Media is always a function of marketing as a revenue generator.

Keywords: social media, marketing strategy, media marketing, brand awareness, customer engagement, revenue generator, brand recognition

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Authors: Thelma Mort

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This empirical, qualitative research uses interviews of four intermediate phase English language student teachers at one university in South Africa and is an exploration of student teacher learning on their teaching practicum in their penultimate year of the initial teacher education course. The country’s post-apartheid language in education policy provides a context to this study in that children move from mother tongue language of instruction in foundation phase to English as a language of instruction in Intermediate phase. There is another layer of context informing this study which is the school context; the student teachers’ reflections are from their teaching practicum in resource constrained schools, which make up more than 75% of schools in South Africa. The findings were that in these schools, deep biases existed to local languages, that language was being used as a proxy for social class, and that conditions necessary for language acquisition were absent. The student teachers’ attitudes were in contrast to those found in the schools, namely that they had various pragmatic approaches to overcoming obstacles and that they saw language as enabling interdisciplinary work. This study describes language issues, tensions created by policy in South African schools and also supplies a regional account of learning to teach in resource constrained schools in Cape Town, where such language tensions are more inflated. The central findings in this research illuminate attitudes to language and language education in these teaching practicum schools and the complexity of learning to be a language teacher in these contexts. This study is one of the few local empirical studies regarding language teaching in the classroom and language teacher education; as such it offers some background to the country’s poor performance in both international and national literacy assessments.

Keywords: language teaching, narrative, post apartheid, South Africa, student teacher

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Authors: Mona Hassan Aburahma, Alaa Hamed Salama

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Ufasomes “unsaturated fatty acids liposomes” are unique nano-sized self-assembled bilayered vesicles that can be easily created from the readily available unsaturated fatty acid. Ufasomes are formed due to weak associative interaction of the fully ionized and unionized fatty acids into bilayers structures. In the ufasomes constructs, the fatty acid molecules are oriented with their hydrocarbon tails directed toward the membrane interior and the carboxyl groups are in contact with water. Although ufasomes can be employed as a safe vesicular carrier for drugs, the extreme instability of their aqueous dispersions hinders their effective use in drug delivery field. Accordingly, in our study, lyophilized gels containing ufasomes were prepared using a simple assembling technique form the readily available oleic acid to overcome the colloidal instability of the ufasomes dispersions and convert them into accurate unit dosage forms. The influence of changing cholesterol percentage relative to oleic acid on the ufasomes vesicles were investigated using factorial design. The optimized oleic acid ufasomes comprised nanoscaled spherical vesicles. Scanning electron micrographs of the lyophilized gels revealed that the included ufasomes were intact, non-aggregating, and preserved their spherical morphology. Rheological characterization (viscosity and shear stress versus shear rate) of reconstituted ufasomal lyophilized gel ensured the ease of application. The capability of the ufasomes, included in the gel, to penetrate deep through the mucosa layers was illustrated using ex-vivo confocal laser imaging, thereby, highlighting the feasibility of stabilizing ufasomes using lyophilized gel platforms.

Keywords: ufasomes, lyophilized gel, confocal scanning microscopy, rheological characterization, oleic acid

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Authors: Taras Agryzkov, Jose L. Oliver, Leandro Tortosa, Jose Vicent

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This paper aims to demonstrate how network models can be used to understand and to deal with some aspects of urban complexity. As it is well known, the Theory of Architecture and Urbanism has been using for decades’ intellectual tools based on the ‘sciences of complexity’ as a strategy to propose theoretical approaches about cities and about architecture. In this sense, it is possible to find a vast literature in which for instance network theory is used as an instrument to understand very diverse questions about cities: from their commercial activity to their heritage condition. The contribution of this research consists in adding one step of complexity to this process: instead of working with one single primal graph as it is usually done, we will show how new network models arise from the consideration of two different primal graphs interacting in two layers. When we model an urban network through a mathematical structure like a graph, the city is usually represented by a set of nodes and edges that reproduce its topology, with the data generated or extracted from the city embedded in it. All this information is normally displayed in a single layer. Here, we propose to separate the information in two layers so that we can evaluate the interaction between them. Besides, both layers may be composed of structures that do not have to coincide: from this bi-layer system, groups of interactions emerge, suggesting reflections and in consequence, possible actions.

Keywords: graphs, mathematics, networks, urban studies

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Authors: Amir Andria Gad Shehata

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Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: spare part, spare part inventory, inventory model, optimization, maintenanceneural network, LSTM, MLP, forecasting demand, inventory management

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Authors: C. C. Liang

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MSN used to be the most popular application for communicating among social networks, but Facebook chat is now the most popular. Facebook and MSN have similar characteristics, including usefulness, ease-of-use, and a similar function, which is the exchanging of information with friends. Facebook outperforms MSN in both of these areas. However, the adoption of Facebook and abandonment of MSN have occurred for other reasons. Functions can be improved, but users’ willingness to use does not just depend on functionality. Flow status has been established to be crucial to users’ adoption of cyber applications and to affects users’ adoption of software applications. If users experience flow in using software application, they will enjoy using it frequently, and even change their preferred application from an old to this new one. However, no investigation has examined choice behavior related to switching from Facebook to MSN based on a consideration of flow experiences and functions. This investigation discusses the flow experiences and functions of social-networking applications. Flow experience is found to affect perceived ease of use and perceived usefulness; perceived ease of use influences information ex-change with friends, and perceived usefulness; information exchange influences perceived usefulness, but information exchange has no effect on flow experience.

Keywords: consumer behavior, social media, technology acceptance model, flow experience

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Authors: Maria Ezziani, Rabie Zine, Amine Amar, Ilhame Kissani

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This paper introduces a predictive model for urban transportation engineering, which is vital for efficient traffic management. Utilizing comprehensive datasets and advanced statistical techniques, the model accurately forecasts travel times by considering temporal variations and traffic dynamics. Machine learning algorithms, including regression trees and neural networks, are employed to capture sequential dependencies. Results indicate significant improvements in predictive accuracy, particularly during peak hours and holidays, with the incorporation of traffic flow and speed variables. Future enhancements may integrate weather conditions and traffic incidents. The model's applications range from adaptive traffic management systems to route optimization algorithms, facilitating congestion reduction and enhancing journey reliability. Overall, this research extends beyond travel time estimation, offering insights into broader transportation planning and policy-making realms, empowering stakeholders to optimize infrastructure utilization and improve network efficiency.

Keywords: predictive analytics, traffic flow, travel time estimation, urban transportation, machine learning, traffic management

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Authors: Syed Tahir Shah, Fazal Muhammad, Syed Kashif Shah, Maleeha Gul

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In recent days, natural gas has become a relatively clean and quality source of energy, which is recovered from deep wells by expensive drilling activities. The recovered substance is purified by processing in multiple stages to remove the unwanted/containments like dust, dirt, crude oil and other particles. Mostly, gas utilities are concerned with essential objectives of quantity/quality of natural gas delivery, financial outcome and safe natural gas volumetric inventory in the transmission gas pipeline. Gas quantity and quality are primarily related to standards / advanced metering procedures in processing units/transmission systems, and the financial outcome is defined by purchasing and selling gas also the operational cost of the transmission pipeline. SNGPL (Sui Northern Gas Pipelines Limited) Pakistan has a wide range of diameters of natural gas transmission pipelines network of over 9125 km. This research results in answer a few of the issues in accuracy/metering procedures via multiple advanced gadgets for gas flow attributes after being utilized in the transmission system and research. The effects of good pressure management in transmission gas pipeline network in contemplation to boost the gas volume deposited in the existing network and finally curbing gas losses UFG (Unaccounted for gas) for financial benefits. Furthermore, depending on the results and their observation, it is directed to enhance the maximum allowable working/operating pressure (MAOP) of the system to 1235 PSIG from the current round about 900 PSIG, such that the capacity of the network could be entirely utilized. In gross, the results depict that the current model is very efficient and provides excellent results in the minimum possible time.

Keywords: natural gas, pipeline network, UFG, transmission pack, AGA

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Authors: Harshan Baskar, Anirudh S. Chakravarthy, Prateek Garg, Divyam Goel, Abhijith S. Raj, Kshitij Kumar, Lakshya, Ravichandra Parvatham, V. Sushant, Bijay Kumar Rout

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In this paper, we introduce a new computer vision task called nighttime dehaze-enhancement. This task aims to jointly perform dehazing and lightness enhancement. Our task fundamentally differs from nighttime dehazing – our goal is to jointly dehaze and enhance scenes, while nighttime dehazing aims to dehaze scenes under a nighttime setting. In order to facilitate further research on this task, we release a new benchmark dataset called Reside-β Night dataset, consisting of 4122 nighttime hazed images from 2061 scenes and 2061 ground truth images. Moreover, we also propose a new network called NDENet (Nighttime Dehaze-Enhancement Network), which jointly performs dehazing and low-light enhancement in an end-to-end manner. We evaluate our method on the proposed benchmark and achieve SSIM of 0.8962 and PSNR of 26.25. We also compare our network with other baseline networks on our benchmark to demonstrate the effectiveness of our approach. We believe that nighttime dehaze-enhancement is an essential task, particularly for autonomous navigation applications, and we hope that our work will open up new frontiers in research. Our dataset and code will be made publicly available upon acceptance of our paper.

Keywords: dehazing, image enhancement, nighttime, computer vision

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Authors: Qiongpeng Dan, Xiyao Li, Qiong Zhang, Yongzhen Peng

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The nutrients removal from wastewater is of great significance for global wastewater recycling and sustainable reuse. Traditional nitrogen and phosphorus removal processes are very dependent on the input of aeration and carbon sources, which makes it difficult to meet the low-carbon goal of energy saving and emission reduction. This study reported a proof-of-concept demonstration of integrating anammox and enhanced biological phosphorus removal (EBPR) by flocs management in a single-stage hybrid bioreactor (biofilms and flocs) for simultaneous nitrogen and phosphorus removal (SNPR). Excellent removal efficiencies of nitrogen (97.7±1.3%) and phosphorus (97.4±0.7%) were obtained in low C/N ratio (3.0±0.5) municipal wastewater treatment. Interestingly, with the loss of flocs, anammox bacteria (Ca. Brocadia) was highly enriched in biofilms, with relative and absolute abundances reaching up to 12.5% and 8.3×1010 copies/g dry sludge, respectively. The anammox contribution to nitrogen removal also rose from 32.6±9.8% to 53.4±4.2%. Endogenous denitrification by flocs was proven to be the main contributor to both nitrite and nitrate reduction, and flocs loss significantly promoted nitrite flow towards anammox, facilitating AnAOB enrichment. Moreover, controlling the floc's solid retention time at around 8 days could maintain a low poly-phosphorus level of 0.02±0.001 mg P/mg VSS in the flocs, effectively addressing the additional phosphorus removal burden imposed by the enrichment of phosphorus-accumulating organisms in biofilms. This study provides an update on developing a simple and feasible strategy for integrating anammox and EBPR for SNPR in mainstream municipal wastewater.

Keywords: anammox process, enhanced biological phosphorus removal, municipal wastewater, sustainable nutrients removal

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Authors: Parvin Berenjkar, Qiuyan Yuan, Richard Sparling, Stan Lozecznik

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Landfills highly contribute to anthropological global warming through CH₄ emissions. Landfills are usually capped by a conventional soil cover to control the migration of gases. Methane is consumed by CH₄-oxidizing microorganisms known as methanotrophs that naturally exist in the landfill soil cover. The growth of methanotrophs can be optimized in a bio-cover that typically consists of a gas distribution layer (GDL) to homogenize landfill gas fluxes and an overlying oxidation layer composed of suitable materials that support methanotrophic populations. Materials such as mature yard waste composts can provide an inexpensive and favourable porous support for the growth and activity of methanotrophs. In areas with seasonal cold climates, it is valuable to know if methanotrophs in a bio-cover can survive in winter until the next spring, and how deep they are active in the bio-cover to mitigate CH₄. In this study, a pilot bio-cover was constructed in a closed landfill cell in Winnipeg that has a very cold climate in Canada. The bio-cover has a surface area of 2.5 m x 3.5 m and 1.5 m of depth, filled with 50 cm of gravel as a GDL and 70 cm of biosolids compost amended with yard and leaf waste compost. The observed in situ potential of methanotrophs for CH₄ oxidation was investigated at a specific period of time from December 2016 to April 2017 as well as November 2017 to April 2018, when the transition to surface frost and thawing happens in the bio-cover. Compost samples taken from different depths of the bio-cover were incubated in the laboratory under standardized conditions; an optimal air: methane atmosphere, at 22ºC, but at in situ moisture content. Results showed that the methanotrophs were alive oxidizing methane without a lag, indicating that there was the potential for methanotrophic activity at some depths of the bio-cover.

Keywords: bio-cover, global warming, landfill, methanotrophic activity

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Authors: Gurukiran Veerapur, Nytik Birudavolu, Seetharam U. N., Chandravva Hebbi, R. Praneeth Reddy

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This work presents a robust approach for the recognition of characters in Telugu and Kannada, two South Indian scripts with structural similarities in characters. To recognize the characters exhaustive datasets are required, but there are only a few publicly available datasets. As a result, we decided to create a dataset for one language (source language),train the model with it, and then test it with the target language.Telugu is the target language in this work, whereas Kannada is the source language. The suggested method makes use of Canny edge features to increase character identification accuracy on pictures with noise and different lighting. A dataset of 45,150 images containing printed Kannada characters was created. The Nudi software was used to automatically generate printed Kannada characters with different writing styles and variations. Manual labelling was employed to ensure the accuracy of the character labels. The deep learning models like CNN (Convolutional Neural Network) and Visual Attention neural network (VAN) are used to experiment with the dataset. A Visual Attention neural network (VAN) architecture was adopted, incorporating additional channels for Canny edge features as the results obtained were good with this approach. The model's accuracy on the combined Telugu and Kannada test dataset was an outstanding 97.3%. Performance was better with Canny edge characteristics applied than with a model that solely used the original grayscale images. The accuracy of the model was found to be 80.11% for Telugu characters and 98.01% for Kannada words when it was tested with these languages. This model, which makes use of cutting-edge machine learning techniques, shows excellent accuracy when identifying and categorizing characters from these scripts.

Keywords: base characters, modifiers, guninthalu, aksharas, vattakshara, VAN

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Authors: Seyed Reza Aghili, Tahereh Shokohi, Lotfollah Davoodi, Zahra Kashi, Azam Moslemi, Mahdi Abastabar, Iman Haghani, Sabah Mayahi, Asoudeh A.

Abstract:

Introduction: In diabetic foot ulcers, if fungal agents such as Candida species penetrate into the cutaneous or depth of ulcer, can increase the degree of the wound and cause Candia infection and make it more difficult to heal. Material & Methods: A cross-sectional study was performed on 100 diabetic foot ulcer patients in 2020 in Sari, Iran. patient's data and wound grade were recorded in a questionnaire. Candida infection was diagnosed with direct microscopic examination and culture of samples. Colony-PCR molecular method was used for ITS region of DNA and then PCR-RFLP with Msp1 enzyme and using HWP1 specific gene to determine species of Candida agent. Results: Of 100 patients, the mean age 62.1 ± 10.8 years, 95% type 2 diabetes, 83%>10 years duration diabetes, 59% male, 66%> poor education level, 99% married, 52% rural, 95% neuropathic symptoms, 88% using antibiotics, 69%HbA1C >9%, and mean ulcer degree 2.6±1.05 were. Candida infection was seen in 13% of the deep tissue of the wound and 7% cutaneous around the wound. The predominant Candida isolated was C. parapsilosis (71.5%), C .albicans (14.3%). Fungal infections caused by mold fungi were not detected. There was a statistically significant relationship between yeast infection and gender, rural, HbA1C and ulcer degree. Conclusion: Mycological evaluations often are ignored. Candida parapsilosis is the most common infectious agent in these patients and may require specific treatment. Therefore, more attention of physicians to Candida infections particularly, early diagnosis and effective treatment can help faster recovery and prevent amputation.

Keywords: diabetic foot ulcer, candida infection, risk factors, c. parapsilosis

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Authors: Kamyar Fakhr, Roozbeh Salmani

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Alphonse Bertillon developed the first biometric security system in the 1800s. Today, many governments and giant companies are considering or have procured biometrically enabled security schemes. Iris is a kaleidoscope of patterns and colors. Each individual holds a set of irises more unique than their thumbprint. Every single day, giant companies like Google and Apple are experimenting with reliable biometric systems. Now, after almost 200 years of improvements, face ID does not work with masks, it gives access to fake 3D images, and there is no global usage of biometric recognition systems as national identity (ID) card. The goal of this paper is to demonstrate the advantages of iris recognition overall biometric recognition systems. It make two extensions: first, we illustrate how a very large amount of internet fraud and cyber abuse is happening due to bugs in face recognition systems and in a very large dataset of 3.4M people; second, we discuss how establishing a secure global network of iris recognition devices connected to authoritative convolutional neural networks could be the safest solution to this dilemma. Another aim of this study is to provide a system that will prevent system infiltration caused by cyber-attacks and will block all wireframes to the data until the main user ceases the procedure.

Keywords: biometric system, convolutional neural network, cyber-attack, secure

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Authors: Belhaj Mohamed, M. Saidi, I. Bouazizi, M. Soussi, M. Ben Jrad

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The Late Cenomanian-Early Turonian laminated, black, organic-rich limestones were described in Central Tunisia and attributed to the Bahloul Formation. It covers central and northern Tunisia, and the northern part of the Gulf of Gabes. The Bahloul Formation is considered as one of the main source rocks in Tunisia and is composed of outer-shelf to slop-laminated and dark-gray to black-colored limestones and marls. This formation had been deposited in a relatively deep-marine, calm, and anoxic environment. Rock-Eval analysis and vitrinite reflectance (Ro) measurements were performed on the basis of the organic carbon content. Several samples were chosen for molecular organic geochemistry. Saturate and aromatic hydrocarbons were analyzed by gas chromatography (GC) and GC–mass spectrometry. Geochemical data of the Bahloul Formation in northern and central Tunisia show this level to be a good potential source rock as indicated by the high content of type II organic matter. This formation exhibits high total organic carbon contents (as much as 14%), with an average value of 2% and a good to excellent petroleum potential, ranging between 2 and 50 kg of hydrocarbon/ton of rock. The extracts from the Bahloul Formation are characterized by Pr/Ph ratios ranging between 1.5 and 3, a moderate diasterane content, a C27 sterane approximately equal to C29 sterane, a high C28/C29 ratio, low gammacerane index, a C35/C34 homohopane ratio less than 1 and carbon isotope compositions between -24 and -26‰. The thermal maturity is relatively low, corresponding to the beginning of the oil window in the western area near the Algerian border, in the oil window in the eastern area (Sahel basin) and late mature in northern part.

Keywords: biomarkers, organic geochemistry, source rock, Tunisia

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Authors: Mengmeng Liu, J. David Frost

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Interstate highway system within the Atlanta Perimeter plays an important role in residents’ daily life. The serious influence of Atlanta I-85 Collapses implies that transportation system in the region lacks a cohesive and comprehensive transportation plan. Therefore, disaster resilience analysis of the transportation system is necessary. Resilience is the system’s capability to persist or to maintain transportation services when exposed to changes or shocks. This paper analyzed the resilience of the whole transportation system within the Perimeter and see how removing interstates within the Perimeter will affect the resilience of the transportation system. The data used in the paper are Atlanta transportation networks and LEHD Origin-Destination Employment Statistics data. First, we calculate the traffic flow on each road section based on LEHD data assuming each trip travel along the shortest travel time paths. Second, we calculate the measure of resilience, which is flow-based connectivity and centrality of the transportation network, and see how they will change if we remove each section of interstates from the current transportation system. Finally, we get the resilience function curve of the interstates and identify the most resilient interstates section. The resilience analysis results show that the framework of calculation resilience is effective and can provide some useful information for the transportation planning and sustainability analysis of the transportation infrastructures.

Keywords: connectivity, interstate highway system, network analysis, resilience analysis

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Authors: Jorge R. Santos, Pedro Sebastiao

Abstract:

In recent years there has been a great growth in the use of drones, being used in several areas such as security, agriculture, or research. The existence of some systems that allow the remote control of drones is a reality; however, these systems are quite simple and directed to specific functionality. This paper proposes the development of a web platform made in Vue.js and Node.js to control, manage, and monitor drones in real time. Using a microservice architecture, the proposed project will be able to integrate algorithms that allow the optimization of processes. Communication with remote devices is suggested via HTTP through 3G, 4G, and 5G networks and can be done in real time or by scheduling routes. This paper addresses the case of forest fires as one of the services that could be included in a system similar to the one presented. The results obtained with the elaboration of this project were a success. The communication between the web platform and drones allowed its remote control and monitoring. The incorporation of the fire detection algorithm in the platform proved possible a real time analysis of the images captured by the drone without human intervention. The proposed system has proved to be an asset to the use of drones in fire detection. The architecture of the application developed allows other algorithms to be implemented, obtaining a more complex application with clear expansion.

Keywords: drone control, microservices, node.js, unmanned aerial vehicles, vue.js

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Authors: Aparna Bandyopadhyay

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The proposed paper will examine how prostitution produced a vast corpus of literature in colonial Bengal. This corpus included autobiographical accounts by prostitutes themselves. While the authenticity of some of these has, at times, been doubted by contemporary observers, the sheer magnitude of such narrative prose demands critical attention. Many of these autobiographical narratives focused on the prostitute’s early life within respectable society and then proceeded to delineate the transgressions and the inescapable chain of circumstances that eventually rendered her a prostitute. Significantly, these serve to corroborate the findings of official investigations regarding the circumstances that led upper-caste Hindu women in Bengal to embrace prostitution in this period. The literary corpus that dwelt on prostitution also included a vast volume of fiction penned by celebrated writers. These foregrounded a prostitute as the central protagonist, telling the life-stories of prostitutes and the circumstances that made them what they were. Novels and short stories often represented the prostitute as an affective being – an individual capable of deep emotions despite her profession. She was seldom a person who had voluntarily embraced prostitution. She was always a figure of helplessness and suffering, a woman whose desire to love and be loved transcended the carnality of her livelihood. She was an outcast, but she experienced the entire repertoire of emotions experienced by her respectable counterparts. The proposed paper will examine the trends and characteristics of the available repertoire of prostitute-oriented literature in late colonial Bengal. It will begin by focusing on the existing perspectives on the origins of prostitution in late colonial Bengal. It will proceed to discuss the literary corpus supposedly penned by prostitutes themselves and then focus on the manner in which some of the stalwarts of high literature represented the prostitute in their literary creations.

Keywords: emotions, literature, prostitution, transgression

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