Search results for: Daniel Mills

Authors: Rema Daher, Theodor Chakhachiro, Daniel Asmar

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In the era of autonomous robot mapping, assessing the goodness of the generated maps is important, and is usually performed by aligning them to ground truth. Map alignment is difficult for two reasons: first, the query maps can be significantly distorted from ground truth, and second, establishing what constitutes ground truth for different settings is challenging. Most map alignment techniques to this date have addressed the first problem, while paying too little importance to the second. In this paper, we propose a benchmark dataset, which consists of synthetically transformed maps with their corresponding displacement fields. Furthermore, we propose a new system for comparison, where the displacement field of any map alignment technique can be computed and compared to the ground truth using statistical measures. The local information in displacement fields renders the evaluation system applicable to any alignment technique, whether it is linear or not. In our experiments, the proposed method was applied to different alignment methods from the literature, allowing for a comparative assessment between them all.

Keywords: assessment methods, benchmark, image deformation, map alignment, robot mapping, robot motion

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Authors: Yu. Mateyshina, A. Ulihin, N. Uvarov

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Supercapacitors are one of the most promising devices for energy storage applications as they can provide higher power density than batteries and higher energy density than conventional dielectric capacitors. Carbon materials with various microtextures are considered as main candidates for supercapacitors in terms of high surface area, interconnected pore structure, controlled pore size, high electrical conductivity and environmental friendliness. The specific capacitance (C) of the electrode material of the Electrochemical Double Layer Capacitors (EDLC) is known to depend on the specific surface area (Ss) and the pore structure. Activated carbons are most commonly used in supercapacitors because of their high surface area (Ss ≥ 1000 m2/g), good adhesion to electrolytes and low cost. In this work, electrochemical properties of new microporous and mesoporous carbon electrode materials were studied. The aim of the work was to investigate the relationship between the specific capacitance and specific surface area in a series of materials prepared from different organic precursors.. As supporting matrixes different carbon samples with Ss = 100-2000 m2/g were used. The materials were modified by treatment in acids (H2SO4, HNO3, acetic acid) in order to enable surface hydrophilicity. Then nanoparticles of transition metal oxides (for example NiO) were deposited on the carbon surfaces using methods of salts impregnation, mechanical treatment in ball mills and the precursors decomposition. The electrochemical characteristics of electrode hybrid materials were investigated in a symmetrical two-electrode cell using an impedance spectroscopy, voltammetry in both potentiodynamic and galvanostatic modes. It was shown that the value of C for the materials under study strongly depended on the preparation method of the electrode and the type of electrolyte (1 M H2SO4, 6 M KOH, 1 M LiClO4 in acetonitryl). Specific capacity may be increased by the introduction of nanoparticles from 50-100 F/g for initial carbon materials to 150-300 F/g for nanocomposites which may be used in supercapacitors. The work is supported by the по SC-14.604.21.0013.

Keywords: supercapacitors, carbon electrode, mesoporous carbon, electrochemistry

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Authors: Khen Cohen, Daniel Yankelevich, David Mendlovic, Dan Raviv

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We present a 3D stereo system for high-resolution sensing in both the spatial and the temporal domains by combining a frame-based camera and an event-based camera. We establish a method to merge both devices into one unite system and introduce a calibration process, followed by a correspondence technique and interpolation algorithm for 3D reconstruction. We further provide quantitative analysis about our system in terms of depth resolution and additional parameter analysis. We show experimentally how our system performs temporal super-resolution up to effectively 1ms and can detect fast-moving objects and human micro-movements that can be used for micro-expression analysis. We also demonstrate how our method can extract colored events for an event-based camera without any degradation in the spatial resolution, compared to a colored filter array.

Keywords: DVS-CIS stereo vision, micro-movements, temporal super-resolution, 3D reconstruction

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Authors: Kehinde K. Agbele, Kehinde Daniel Aruleba, Eniafe F. Ayetiran

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When using Information Retrieval Systems (IRS), users often present search queries made of ad-hoc keywords. It is then up to the IRS to obtain a precise representation of the user’s information need and the context of the information. This paper investigates optimization of IRS to individual information needs in order of relevance. The study addressed development of algorithms that optimize the ranking of documents retrieved from IRS. This study discusses and describes a Document Ranking Optimization (DROPT) algorithm for information retrieval (IR) in an Internet-based or designated databases environment. Conversely, as the volume of information available online and in designated databases is growing continuously, ranking algorithms can play a major role in the context of search results. In this paper, a DROPT technique for documents retrieved from a corpus is developed with respect to document index keywords and the query vectors. This is based on calculating the weight (

Keywords: information retrieval, document relevance, performance measures, personalization

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Authors: Henry Lee, Daniel Shiu

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Educational organizations are currently exploring ways to increase equity, diversity, and inclusion (EDI), and this is now evident within the K-12 school system, universities, and teacher unions. These organizations have been creating and implementing new EDI specific policies. Their goal is to provide the framework and supports needed to establish EDI into the organizational culture. However, the implementation of EDI policies does not always lead to the intended outcomes. The purpose of this paper is to explore some factors regarding why the implementation of EDI policies within educational organizations can be problematic. This includes how Whiteness is replicated, promoted, and celebrated in educational leadership. How Whiteness and White supremacy are operationalized by BIPOC leaders within educational spaces, and how EDI specific training fails to understand the different training needed for both IBPOC (Indigenous, Black, People of Colour) and non-IBPOC leaders. This paper also addresses the model minority myth and how this informs and guides IBPOC identity and leadership within a predominately White dominant leadership in education.

Keywords: critical race theory, equity & diversity & inclusion, educational leadership, intersectionality

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Authors: F. L. Bernardo, R. A. S. Zacarias

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The ways to translate are manifold since textual genres undergoing translations are diverse. In this essay, our goal is to give special attention to the literary genre and to the online translation tool Google Translate (GT), widely used either by nonprofessionals or by scholars, in order to show evidence of the indispensability of human wit in a good translation. Our study has its basis on a literary review of prominent authors, with emphasis on translation categories. Also highlighting the issue of polysemous literary translation, we aim to shed light on the translator’s craft and the fallible nature of online translation. To better illustrate these principles, the methodology consisted on performing a comparative analysis involving the original text Moll Flanders by Daniel Defoe in English to its online translation given by GT and to a translation into Brazilian Portuguese performed by a human. We proceeded to identifying and analyzing the degrees of textual equivalence according to the following categories: volume, levels and order. The results have attested the unsuitability in a translation done by a computer connected to the World Wide Web.

Keywords: Google Translator, human translation, literary translation, Moll Flanders

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Authors: Daniel C. S. Lim, W. Y. Tan

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The world is facing a growing food crisis. The concerns of food nutritional value, food safety and food security are becoming increasingly real. There is also a direct relationship to the risk of diseases, particularly chronic diseases, to the food we consume. So, there are increasing concerns about the modern day food ecosystem creating foods that can provide the nutritional components for organ function sustenance, as well as, taking a serious view on diet-related diseases. This paper addresses some of the above concerns and gives an overview of the current global situation relating to food nutrition and safety. The paper reviews nutritional aspects of food today compared to those of the last century, compares whole foods found in supermarkets versus those organically grown, as well as population behaviour towards food choices. It provides scientific insights into the effects of some of the global trends such as climate change and other changes environmental changes, and presents what individuals and corporations are doing to use the latest nutritional technologies as strategic assets. Finally, it briefly highlights some of the innovative solutions that are being applied to address several of the above concerns.

Keywords: food crisis, food safety, global trends, nutritional aspects

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Authors: David A. Harness

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Natural evolution of ATP cognitive systems is to meet AI peer review standards. ATP process of axiom selection from Mizar to prove a conjecture would be further refined, as in all human and machine learning, by solving the real world problem of the proposed AI peer review challenge: Determine which conjecture forms the higher confidence level constructive proof between Standard Model of Physics SU(n) lattice gauge group operation vs. present non-standard 4D GEM EOS SU(n) lattice gauge group spatially extended operation in which the photon and electron are the first two trace angular momentum invariants of a gravitoelectromagnetic (GEM) energy momentum density tensor wavetrain integration spin-stress pressure-volume equation of state (EOS), initiated via 32 lines of Mathematica code. Resulting gravitoelectromagnetic spectrum ranges from compressive through rarefactive of the central cosmological constant vacuum energy density in units of pascals. Said self-adjoint group operation exclusively operates on the stress energy momentum tensor of the Einstein field equations, introducing quantization directly on the 4D spacetime level, essentially reformulating the Yang-Mills virtual superpositioned particle compounded lattice gauge groups quantization of the vacuum—into a single hyper-complex multi-valued GEM U(1) × SU(1,3) lattice gauge group Planck spacetime mesh quantization of the vacuum. Thus the Mizar corpus already contains all of the axioms required for relevant DeepMath premise selection and unambiguous formal natural language parsing in context deep learning.

Keywords: automated theorem proving, constructive quantum field theory, information theory, neural networks

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Authors: Daniel Benson, Yundan Gong, Hannah Kirk

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Advancement in national language processing techniques has led to increased data processing speeds, and reduced the need for cumbersome, manual data processing that is often required when processing data from multilateral organizations for specific purposes. As such, using named entity recognition (NER) modeling and the Organisation of Economically Developed Countries (OECD) Creditor Reporting System database, we present the first geotagged dataset of OECD donor Official Development Assistance (ODA) projects on a global, subnational basis. Our resulting data contains 52,086 ODA projects geocoded to subnational locations across 115 countries, worth a combined $87.9bn. This represents the first global, OECD donor ODA project database with geocoded projects. We use this new data to revisit old questions of how ‘well’ donors allocate ODA to the developing world. This understanding is imperative for policymakers seeking to improve ODA effectiveness.

Keywords: international aid, geocoding, subnational data, natural language processing, machine learning

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Authors: Corazon Virtudazo-Ligaray, Mark Daniel G. de Luna, Meng-Wei Wan, Ming-Chun Lu

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A series of ternary compound catalyst with nanocomposites of ceria, tungsten trioxide and titania (CeO2-WOx-TiO2) with different WOx mole fraction (10, 20, 30, 40) have been synthesized by sol-gel method. These nanocomposite catalysts were used for oxidative extractive desulfurization of model fuel oil, which were composed of dibenzothiophene (DBT) dissolved in toluene. The 30% hydrogen peroxide, H2O2 was used as oxidant and acetonitrile as extractant. These catalysts were characterized by SEM-EDS to determine the morphology. Catalytic oxidation results show that the catalysts have high selectivity in refractory fuel oil with organo sulfur contents. The oxidative removal of DBT increases as the HPW content increases. The nanocomposites CeO2-WOx-TiO2 also shows high selectivity for DBT oxidation in the DBT–toluene acetonitrile system. The catalytic oxidative desulfurization ratio of model fuel reached to 100% with nanocomposites CeO2-WOx-TiO2 (35-30-35) mol percent catalyst nanocomposition under 333 K in 30 minutes.

Keywords: ceria, oxidative desulfurization, titania, phosphotungstic acid

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Authors: Daniel Ecler

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The aim of this paper was to find out how Chinese university students perceive distance learning compared to full-time teaching, to reveal its advantages and disadvantages, and to try to find what elements could be implemented in regular full-time teaching in order to make it more effective. Recent events have shown that online teaching has a significant role to play in the field of education and needs to be given increased attention and scrutiny. For this purpose, a research survey was conducted using semi-structured questionnaires, which aimed to determine the attitudes of Chinese university students to the phenomenon of distance learning. The results of this survey revealed that most students prefer distance learning to full-time teaching, mainly because it gives them more freedom to participate in teaching, regardless of the environment in which they are currently located. In conclusion, it is necessary to mention that the possibility to participate virtually in teaching from anywhere is a huge advantage that could become part of regular teaching in the future. However, further research into this issue will be necessary.

Keywords: distance learning, full-time teaching, Chinese college students, cultural background

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Authors: Michael Leontiev, Danil Zhilikov, Dmitry Lobanov, Lenar Klimov, Vyacheslav Chertan, Daniel Bobrov, Vladislav Maslov, Vasilii Vologdin, Ksenia Balabaeva

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Pharmaceutical manufacturing is a complex process, where each stage requires a high level of safety and sterility. Personal Protective Equipment (PPE) is used for this purpose. Despite all the measures of control, the human factor (improper PPE wearing) causes numerous losses to human health and material property. This research proposes a solid computer vision system for ensuring safety in pharmaceutical laboratories. For this, we have tested a wide range of state-of-the-art object detection methods. Composing previously obtained results in this sphere with our own approach to this problem, we have reached a high accuracy ([email protected]) ranging from 0.77 up to 0.98 in detecting all the elements of a common set of PPE used in pharmaceutical laboratories. Our system is a step towards safe medicine production.

Keywords: sterility and safety in pharmaceutical development, personal protective equipment, computer vision, object detection, monitoring in pharmaceutical development, PPE

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Authors: Sergio Pérez-López, Daniel Tarrazó-Serrano, José M. Fuster, Pilar Candelas, Constanza Rubio

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Fresnel Zone Plates (FZPs) are widely used in many areas, such as optics, microwaves or acoustics. On the design of FZPs, plane wave incidence is typically considered, but that is not usually the case in ultrasounds, especially in applications where a piston emitter is placed at a certain distance from the lens. In these cases, having control of the focal distance is very important, and with the usual Fresnel equation a focal displacement from the theoretical distance is observed due to the plane wave supposition. In this work, a comparison between FZP with plane wave incidence design and FZP with point source design in the case of piston emitter is presented. Influence of the main parameters of the piston in the final focalization profile has been studied. Numerical models and experimental results are shown, and they prove that when spherical wave incidence is considered for the piston case, it is possible to have a fine control of the focal distance in comparison with the classical design method.

Keywords: focusing, Fresnel zone plates, FZP, ultrasound

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Authors: M. M. Ali, Ahmed Al- Ani, Derek Eamus, Daniel K. Y. Tan

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In this glasshouse study, we developed the new image-based non-destructive technique for detecting leaf P status of different crops such as cotton, tomato and lettuce. Plants were allowed to grow on nutrient media containing different P concentrations, i.e. 0%, 50% and 100% of recommended P concentration (P0 = no P, L; P1 = 2.5 mL 10 L-1 of P and P2 = 5 mL 10 L-1 of P as NaH2PO4). After 10 weeks of growth, plants were harvested and data on leaf P contents were collected using the standard destructive laboratory method and at the same time leaf images were collected by a handheld crop image sensor. We calculated leaf area, leaf perimeter and RGB (red, green and blue) values of these images. This data was further used in the linear discriminant analysis (LDA) to estimate leaf P contents, which successfully classified these plants on the basis of leaf P contents. The data indicated that P deficiency in crop plants can be predicted using the image and morphological data. Our proposed non-destructive imaging method is precise in estimating P requirements of different crop species.

Keywords: image-based techniques, leaf area, leaf P contents, linear discriminant analysis

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Authors: Janine Sommer, Mariana Daus, Mariana Simon, Maria Smith, Daniel Luna

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The technologies and communication advances contributed to new tools development which allows patients to have an active role in their own health. In the light of information needs and paradigms changes about health, the patient self-manages their care. This line of care focuses on patients; specific portals come up to people with particular requirements like pregnant women. Thinking of a portal design to this sector of the population, in September 2016 a survey was made to users with the objective to knowing and understanding information’s needs at the moment to use an application for pregnant. Also, prototypes of the portal´s features were designed to try and validate with users, using the methodology of human-centered design. Investigations have made possible the identification of needs of this population and develop a tool who try to satisfy, providing timely information for each part of pregnancy and allowing the patients to make a physical check and the follow up of pregnancy seeking advice from our obstetricians.

Keywords: electronic health record, health personal record, mobile applications, pregnant women

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Authors: Katleho Daniel Makatjane, Diteboho Lawrence Xaba, Ntebogang Dinah Moroke

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The current study investigates the behaviour of time-varying parameters that are based on the score function of the predictive model density at time t. The mechanism to update the parameters over time is the scaled score of the likelihood function. The results revealed that there is high persistence of time-varying, as the location parameter is higher and the skewness parameter implied the departure of scale parameter from the normality with the unconditional parameter as 1.5. The results also revealed that there is a perseverance of the leptokurtic behaviour in stock returns which implies the returns are heavily tailed. Prior to model estimation, the White Neural Network test exposed that the stock price can be modelled by a GAS model. Finally, we proposed further researches specifically to model the existence of time-varying parameters with a more detailed model that encounters the heavy tail distribution of the series and computes the risk measure associated with the returns.

Keywords: generalized autoregressive score model, South Africa, stock returns, time-varying

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Authors: Stuart W. Campbell, Alexander M. Galloway, Norman A. McPherson, Duncan Camilleri, Daniel Micallef

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Gas tungsten arc welding requires a gas shield to be present in order to protect the arc area from contamination by atmospheric gases. As a result of each gas having its own unique thermophysical properties, the shielding gas selected can have a major influence on the arc stability, welding speed, weld appearance and geometry, mechanical properties and fume generation. Alternating shielding gases is a relatively new method of discreetly supplying two different shielding gases to the welding region in order to take advantage of the beneficial properties of each gas, as well as the inherent pulsing effects generated. As part of an ongoing process to fully evaluate the effects of this novel supply method, a computational fluid dynamics model has been generated to include the gas dependent thermodynamic and transport properties in order to evaluate the effects that an alternating gas supply has on the arc plasma. Experimental trials have also been conducted to validate the model arc profile predictions.

Keywords: Alternating shielding gases, ANSYS CFX, Gas tungsten arc welding(GTAW), magnetohydrodynamics(MHD)

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Authors: Jorge Eliseo Muñiz-Gutierrez, Daniel Olvera-García, Cristina Sotelo-Salas

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The objective of this research is to allow the understanding of the hybridization process shown in culture through the architecture of mass production for the purpose of consumption, taking as a case study the mass-built housing of the city of Mexicali, Mexico. The methodology is born from the hermeneutical study of the meta-modified architectural object, which guided the research with a qualitative focus to be carried out in two stages, the first is based on the literature review regarding cultural hybridization, and the second stage is carried out in through an ethnographic study of the cultural exploration of the contextual landscape produced by the houses located in popular neighborhoods of the city of Mexicali, Mexico. The research shows that there is an unconscious hybridization process, the birth of a mixture of impositions guided by the popular and the personal aspirations of the inhabitant. The study presents the possibilities of a home and the relationship with its inhabitant and, in turn, its effects on the context and its contribution to culture through hybridization.

Keywords: hybridization, architectural landscape, architecture, mass housing

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Authors: Mihaela Alina Stanciu, Daniel Toma

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With a touristic and economic potential among the highest in our country, Neamț County has a large number of impressive storage lakes (Izvoru Muntelui – Bicaz, Bâtca Doamnei, Vaduri, Pângărați), with high hydrographic capacities, but also a diversity of biotopes and habitats. Being an area with frequent exceedances of environmental quality indicators, we analyzed in this work their impact on the water quality parameters in three of the most visited lakes of Neamț County: Bâtca Doamnei, Vaduri, and Pângărați. An additional reason is the risk of the water eutrophication process in these lakes, representing one of the first six most important pollution problems worldwide. During the research carried out over a period of four years (2020 – 2024), we identified the major sources of water pollution for the mentioned reservoirs. We analyzed the type of impact produced by each source separately, and we proposed preventiong and control measures detailed according to their action on water quality parameters.

Keywords: ecosystem, environment, eutrophication, lakes, nutrients, pollution, water quality

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Authors: Tsuu Faith Machingura, Doreen Nkala, Daniel Madzanire

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Higher and tertiary Education in Zimbabwe is driven by is a five-pillar Education 5.0 model, which thrusts upon teaching, community engagement, research, innovation and industrialisation. Migration from the previous three-pillar model, the focus of which was on teaching, research and community engagement, to the current one saw universities churning out prolific social entrepreneurs. Apart from examining challenges social entrepreneurs face, the study aimed to identify opportunities that are available for the country as a corollary of the proliferation of social entrepreneurs. A sample of 20 participants comprising 15 social entrepreneurs and five lecturers was purposively drawn. Focus group and face to face interviews were used to gather data. The study revealed that the current higher and tertiary education model in Zimbabwe has stimulated proliferation of social entrepreneurs. It was recommended that a sound financial support system was needed to support new entrepreneurs.

Keywords: social entrepreneurs, education 5.0, innovation, industrialisation

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Authors: Daniel Olshansky, Ramiro Rodrıguez Colmeiro

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Relay Mining presents a scalable solution employing probabilistic mechanisms and crypto-economic incentives to estimate RPC volume usage, facilitating decentralized multitenant rate limiting. Network traffic from individual applications can be concurrently serviced by multiple RPC service providers, with costs, rewards, and rate limiting governed by a native cryptocurrency on a distributed ledger. Building upon established research in token bucket algorithms and distributed rate-limiting penalty models, our approach harnesses a feedback loop control mechanism to adjust the difficulty of mining relay rewards, dynamically scaling with network usage growth. By leveraging crypto-economic incentives, we reduce coordination overhead costs and introduce a mechanism for providing RPC services that are both geopolitically and geographically distributed.

Keywords: remote procedure call, crypto-economic, commit-reveal, decentralization, scalability, blockchain, rate limiting, token bucket

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Authors: Yohannes Yirga, Daniel Tesfay

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The convective heat and mass transfer in nanofluid flow through a porous media due to a permeable stretching sheet with magnetic field, viscous dissipation, and chemical reaction and Soret effects are numerically investigated. Two types of nanofluids, namely Cu-water and Ag-water were studied. The governing boundary layer equations are formulated and reduced to a set of ordinary differential equations using similarity transformations and then solved numerically using the Keller box method. Numerical results are obtained for the skin friction coefficient, Nusselt number and Sherwood number as well as for the velocity, temperature and concentration profiles for selected values of the governing parameters. Excellent validation of the present numerical results has been achieved with the earlier linearly stretching sheet problems in the literature.

Keywords: heat and mass transfer, magnetohydrodynamics, nanofluid, fluid dynamics

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Authors: Mohammad Mukarram, M. Masroor A. Khan, Daniel Kurjak, Marek Fabrika

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Lemongrass (Cymbopogon flexuosus (Steud.) Wats) is an aromatic grass with great industrial potential. It is cultivated for its essential oil (EO), which has great economic value due to its numerous medicinal, cosmetic, and culinary applications. The present study had the goal to evaluate whether the combined application of silicon nanoparticles (SiNPs) 150 mg L⁻¹ and irradiated chitosan (ICH) 120 mg L⁻¹ can upgrade lemongrass crop and render enhanced growth and productivity. The analyses of growth and photosynthetic parameters, leaf-nitrogen, and reactive oxygen species metabolism, as well as the content of total essential oil, indicated that combined foliar sprays of SiNPs and ICH can significantly (p≤0.05) trigger a general activation of lemongrass metabolism. Overall, the data indicate that concomitant SiNPs and ICH application elicit lemongrass physiology and defence system, and opens new possibilities for their biotechnological application on other related plant species with agronomic potential.

Keywords: photosynthesis, Cymbopogon, antioxidant metabolism, essential oil, ROS, nanoparticles, polysaccharides

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Authors: Siddhant Sahu, P. James Daniel Paul

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Technical analysis comprised by various technical indicators is a holistic way of representing price movement of stocks in the market. Various forms of indicators have evolved from the primitive ones in the past decades. There have been many attempts to introduce volume as a major determinant to determine strong patterns in market forecasting. The law of demand defines the relationship between the volume and price. Most of the traders are familiar with the volume game. Including the time dimension to the law of demand provides a different visualization to the theory. While attempting the same, it was found that there are different thresholds in the market for different companies. These thresholds have a significant influence on the price. This article is an attempt in determining the thresholds for companies using the three dimensional graphs for optimizing the portfolios. It also emphasizes on the magnitude of importance of volumes as a key factor for determining of predicting strong price movements, bullish and bearish markets. It uses a comprehensive data set of major companies which form a major chunk of the Indian automotive sector and are thus used as an illustration.

Keywords: technical analysis, expert system, law of demand, stocks, portfolio analysis, Indian automotive sector

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Authors: Martin Blaha, Ladislav Potužák, Daniel Holesz

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This paper focused on application support for technical control of artillery units – PVNPG-14M, especially on interpolation issue. Artillery units of the Army of the Czech Republic, reflecting the current global security neighborhood, can be used outside the Czech Republic. The paper presents principles, evolution and calculation in the process of complete preparation. The paper presents expertise using of application of current artillery communication and information system and suggests the perspective future system. The paper also presents problems in process of complete preparing of fire especially problems in permanently information (firing table) and calculated values. The paper presents problems of current artillery communication and information system and suggests requirements of the future system.

Keywords: Fire for Effect, Application, Fire Control, Interpolation method, Software development.

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Authors: ZhenlinJu, Christopher P. Vellano, RehanAkbani, Yiling Lu, Gordon B. Mills

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The epithelial–mesenchymal transition (EMT) is a process by which epithelial cells acquire mesenchymal characteristics, such as profound disruption of cell-cell junctions, loss of apical-basolateral polarity, and extensive reorganization of the actin cytoskeleton to induce cell motility and invasion. A hallmark of EMT is its capacity to promote metastasis, which is due in part to activation of several transcription factors and subsequent downregulation of E-cadherin. Unfortunately, current approaches have yet to uncover robust protein marker sets that can classify tumors as possessing strong EMT signatures. In this study, we utilize reverse phase protein array (RPPA) data and consensus clustering methods to successfully classify a subset of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) tumors into an EMT protein signaling group (EMT group). The overall survival (OS) of patients in the EMT group is significantly worse than those in the other Hormone and PI3K/AKT signaling groups. In addition to a shrinkage and selection method for linear regression (LASSO), we applied training/test set and Monte Carlo resampling approaches to identify a set of protein markers that predicts the EMT status of CESC tumors. We fit a logistic model to these protein markers and developed a classifier, which was fixed in the training set and validated in the testing set. The classifier robustly predicted the EMT status of the testing set with an area under the curve (AUC) of 0.975 by Receiver Operating Characteristic (ROC) analysis. This method not only identifies a core set of proteins underlying an EMT signature in cervical cancer patients, but also provides a tool to examine protein predictors that drive molecular subtypes in other diseases.

Keywords: consensus clustering, TCGA CESC, Silhouette, Monte Carlo LASSO

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Authors: Prathik Ranka, Sridhar K, Vasanth Daniel, Mithun Shankar

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With growing global food needs and climate uncertainties, informed crop choices are critical for increasing agricultural productivity. Here we propose a machine learning-based crop recommendation system to help farmers in choosing the most proper crops according to their geographical regions and soil properties. We can deploy algorithms like Decision Trees, Random Forests and Support Vector Machines on a broad dataset that consists of climatic factors, soil characteristics and historical crop yields to predict the best choice of crops. The approach includes first preprocessing the data after assessing them for missing values, unlike in previous jobs where we used all the available information and then transformed because there was no way such a model could have worked with missing data, and normalizing as throughput that will be done over a network to get best results out of our machine learning division. The model effectiveness is measured through performance metrics like accuracy, precision and recall. The resultant app provides a farmer-friendly dashboard through which farmers can enter their local conditions and receive individualized crop suggestions.

Keywords: crop recommendation, precision agriculture, crop, machine learning

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Authors: Mohd Amran, Chan Yi Jing, Chong Chien Hwa

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Production of biogas from POME requires anaerobic digestion (AD), thus, anaerobic digester performance in biogas plants is crucial. As POME from different sources have varying characteristics due to different process flows in mills, there is no ideal treatment parameters for POME. Hence, different treatment plants alter different parameters in anaerobic digestion to achieve desired biogas production levels and to meet POME waste discharge limits. The objective of this study is to evaluate the performance of mesophilic anaerobic digestion in four different biogas plants in Malaysia. Aspects of POME pre-treatment efficiency, analysis of treated POME and AD’s bottom sludge characteristics, including several parameters like chemical oxygen demand (COD), biological oxygen demand (BOD), total solid (TS) removal in the effluent, pH and temperature changes, total biogas produced, the composition of biogas including methane (CH₄), carbon dioxide (CO₂), hydrogen sulfide (H₂S) and oxygen (O₂) were investigated. The effect of organic loading rate (OLR) and hydraulic retention time (HRT) on anaerobic digester performance is also evaluated. In pre-treatment, it is observed that BGP B has the lowest average outlet temperature of 40.41°C. All BGP shows a high-temperature fluctuation (36 to 49 0C) and good pH readings (minimum 6.7), leaving the pre-treatment facility before entering the AD.COD removal of POME is considered good, with an average of 78% and maximum removal of 85%. BGP C has the lowest average COD and TS content in treated POME, 13,313 mg/L, and 12,048 mg/L, respectively. However, it is observed that the treated POME leaving all ADs, still contains high-quality organic substances (COD between 12,000 to 19,000 mg/L) that might be able to digest further to produce more biogas. The biogas produced in all four BGPs varies due to different COD loads. BGP B has the highest amount of biogas produced, 378,874.7 Nm³/month, while BGP D has the lowest biogas production of 272,378.5 Nm³/month. Furthermore, the composition of biogas produced in all plants is well within literature values (CH4 between 55 to 65% and CO₂ between 32 to 36%).

Keywords: palm oil mill effluent, in-ground lagoon anaerobic digester, anaerobic digestion, biogas

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Authors: Daniel Bulanda, Janusz A. Starzyk, Adrian Horzyk

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The electrocardiogram (ECG) is one of the most commonly used medical tests, essential for correct diagnosis and treatment of the patient. While ECG devices generate a huge amount of data, only a small part of them carries valuable medical information. To deal with this problem, many compression algorithms and filters have been developed over the past years. However, the rapid development of new machine learning techniques poses new challenges. To address this class of problems, we created the FlexPoints algorithm that searches for characteristic points on the ECG signal and ignores all other points that do not carry relevant medical information. The conducted experiments proved that the presented algorithm can significantly reduce the number of data points which represents ECG signal without losing valuable medical information. These sparse but essential characteristic points (flex points) can be a perfect input for some modern machine learning models, which works much better using flex points as an input instead of raw data or data compressed by many popular algorithms.

Keywords: characteristic points, electrocardiogram, ECG, machine learning, signal compression

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Authors: R. K. Agrawal, Shiv Agrawal

Abstract:

Fines and micro create fundamental problems of respiration. From mines to mills steel plants generate lot of pollutants. Legislation & Government laws are stricter day by day & each plant has to think of recycling, reuse &reintegration of pollutants generated during the process of steel making. This paper deals with experiments conducted in Bhilai Steel Plant and Real Ispat and Power Limited for reuse, recycle & reintegrate some of the steel making process fines. Iron ore fines with binders have been agglomerated to be used as a part of the charge for small furnaces. This will improve yield at nominal cost. Rolling mill fines have been recycled to increase the yield of sinter making. This will solve the problems of fine disposal. Huge saving on account of recycling will be achieved. Lime fines after briquetting is used along with prime lime. Lime fines have also been used as a binding material during production of fly ash bricks. These fines serve as low-cost binder. Experiments have been conducted along with coke breeze & gas cleaning plant sludge. As a result, the anti-sloping compound has been developed for converter vessels. Dolo char and Char during Sponge Iron production have been successfully used in power generation and brick making. Pellets have been made with ventilation dust & flue dust. These samples have been tried as a coolant in the converter. Pellets have been made with Sinter Plant electrostatic precipitator micro fines with liquid binder. Trials have been conducted to reuse these pellets in sinter making. Coke breeze from coke-ovens fines and mill scale along with binders were agglomerated. This was used in furnace after attaining required screening and reactivity index. These actions will definitely bring social, economic and environment-friendly universe.

Keywords: briquette, dolo char, electrostatic precipitator, pellet, sinter

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