Search results for: black hole attack

Authors: Thirsa Sherry, Utkarsh Shrivastav, Kannan B. T., Iynthezhuton K.

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The field of aerodynamics and aeroacoustics remains one of the most poignant and well-researched fields of today. The current paper aims to investigate the predominant problem concerning the effects of noise of varying frequencies and waveforms on airflow surrounding an airfoil. Using a single speaker beneath the airfoil at different positions, we wish to simulate the effects of sound directly impinging on an airfoil and study its direct effects on airflow. We wish to study the same using smoke visualization methods with incense as our smoke-generating material in a variable-speed subsonic wind tunnel. Using frequencies and wavelengths similar to those of common engine noise, we wish to simulate real-world conditions of engine noise interfering with airflow and document the arising trends. These results will allow us to look into the real-world effects of noise on airflow and how to minimize them and expand on the possible relation between waveforms and noise. The parameters used in the study include frequency, Reynolds number, waveforms, angle of attack, and the effects on airflow when varying these parameters.

Keywords: engine noise, aeroacoustics, acoustic excitation, low speed

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Authors: Perminder JitKaur, Santosh Satya, K. K. Pant, S. N. Naik

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Bamboo is extensively used in construction industry. Low durability of bamboo due to fungus infestation and termites attack under storage puts certain constrains for it usage as modern structural material. Looking at many chemical formulations for bamboo treatment leading to severe harmful environment effects, research on eco-friendly preservatives for bamboo treatment has been initiated world-over. In the present studies, eco-friendly preservative for bamboo treatment has been developed. To validate its application for structural purposes, investigation of effect of treatment on compressive strength has been investigated. Neem oil(25%) integrated with copper naphthenate (0.3%) on dilution with kerosene oil impregnated into bamboo culm at 2 bar pressure, has shown weight loss of only 3.15% in soil block analysis method. The results of compressive strength analysis using The results from compressive strength analysis using HEICO Automatic Compression Testing Machine, reveal that preservative treatment has not altered the structural properties of bamboo culms. Compressive strength of control (11.72 N/mm2) and above treated samples (11.71 N/mm2) was found to be comparable.

Keywords: D. strictus, bamboo, neem oil, presure treatment, compressive strength

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Authors: Sira Suren, Soorathep Kheawhom

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This work investigates the development of a high energy density zinc-air battery. Printed and flexible thin film zinc-air battery with an overall thickness of about 350 μm was fabricated by an inexpensive screen-printing technique. Commercial nano-silver ink was used as both current collectors and catalyst layer. Carbon black ink was used to fabricate cathode electrode. Polypropylene membrane was used as the cathode substrate and separator. 9 M KOH was used as the electrolyte. A mixture of Zn powder, ZnO, and Bi2O3 was used to prepare the anode electrode. The suitable concentration of Bi2O3 and types of binders (styrene-butadiene and sodium silicate) were investigated. Results showed that battery using 20% Bi2O3 and sodium silicate binder provided the best performance. The open-circuit voltage and energy density observed were 1.59 V and 690 Wh/kg, respectively. When the battery was discharged at 20 mA/cm2, the potential voltage observed was 1.3 V. Furthermore, the battery was tested for its flexibility. Upon bending, no significant loss in performance was observed.

Keywords: flexible, printed battery, screen printing, Zn-air

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Authors: Brianna Ross, John Sollers, Christopher Edwards

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In the age of heightened social and political discourse, there is a tendency for individuals and media sources to use dehumanization as a tool to influence group thoughts and attitudes. When considering individual interactions, there is a need to determine what characteristics increase or predict dehumanization. The present study investigated dehumanization tendencies related to social dominance orientation (SDO) and right-wing authoritarianism (RWA) while factoring in political affiliation. Two-hundred and seven individuals participated in an anonymous study to reveal that there was a significant relationship between high SDO and high RWA scores. There was also a significant correlation between the dehumanization of Black Lives Matter and SDO. These findings suggest that those who are “double high” (scoring highly on both SDO and RWA are more likely to dehumanize others, particularly social groups they disagree with. Acknowledging that there are significant changes occurring in the sociopolitical atmosphere, it is essential that researchers understand dehumanization tendencies in modern society to better define the concept of othering and its consequences on social interaction.

Keywords: dehumanization, social dominance orientation, right-wing authoritarianism, political affiliation

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Authors: H. C. Woo, F. Bouanis, C. S. Cojocaur

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Graphene, which consists of a single layer of carbon atoms in a honeycomb lattice, is an interesting potential optoelectronic material because of graphene’s high carrier mobility, zero bandgap, and electron–hole symmetry. Graphene can absorb light and convert it into a photocurrent over a wide range of the electromagnetic spectrum, from the ultraviolet to visible and infrared regimes. Over the last several years, a variety of graphene-based photodetectors have been reported, such as graphene transistors, graphene-semiconductor heterojunction photodetectors, graphene based bolometers. It is also reported that there are several physical mechanisms enabling photodetection: photovoltaic effect, photo-thermoelectric effect, bolometric effect, photogating effect, and so on. In this work, we report a simple approach for the realization of graphene based resistive photo-detection devices and the measurements of their photoelectrical response. The graphene were synthesized directly on the glass substrate by novel growth method patented in our lab. Then, the metal electrodes were deposited by thermal evaporation on it, with an electrode length and width of 1.5 mm and 300 μm respectively, using Co to fabricate simple graphene based resistive photosensor. The measurements show that the graphene resistive devices exhibit a photoresponse to the illumination of visible light. The observed re-sistance response was reproducible and similar after many cycles of on and off operations. This photoelectrical response may be attributed not only to the direct photocurrent process but also to the desorption of oxygen. Our work shows that the simple graphene resistive devices have potential in photodetection applications.

Keywords: graphene, resistive sensor, optoelectronics, photoresponse

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Authors: Tushar K. Routh

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If inputs are engineered in certain manners, they can influence deep neural networks’ (DNN) performances by facilitating misclassifications, a phenomenon well-known as adversarial attacks that question networks’ vulnerability. Recent studies have unfolded the relationship between vulnerability of such networks with their complexity. In this paper, the distinctive influence of additional convolutional layers at the decision boundaries of several DNN architectures was investigated. Here, to engineer inputs from widely known image datasets like MNIST, Fashion MNIST, and Cifar 10, we have exercised One Step Spectral Attack (OSSA) and Fast Gradient Method (FGM) techniques. The aftermaths of adding layers to the robustness of the architectures have been analyzed. For reasoning, separation width from linear class partitions and local geometry (curvature) near the decision boundary have been examined. The result reveals that model complexity has significant roles in adjusting relative distances from margins, as well as the local features of decision boundaries, which impact robustness.

Keywords: DNN robustness, decision boundary, local curvature, network complexity

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Authors: Youngmok Yun, Bosung Kim, Sungho Lee, Kyeongsu Jeon, Hyunwook Hwangbo, Byounggun Choi

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A betavoltaic battery converts nuclear energy released as beta particles (β-) directly into electrical energy. Betavoltaic cells are analogous to photovoltaic cells. The beta particle’s kinetic energy enters a p-n junction and creates electron-hole pairs. Subsequently, the built-in potential of the p-n junction accelerates the electrons and ions to their respective collectors. The major challenges are electrical conversion efficiencies and exact evaluation. In this study, the performance of betavoltaic battery was evaluated. The betavoltaic cell was evaluated in the same condition as radiation from radioactive isotope using by FE-SEM(field emission scanning electron microscope). The average energy of the radiation emitted from the Ni-63 radioisotope is 17.42 keV. FE-SEM is capable of emitting an electron beam of 1-30keV. Therefore, it is possible to evaluate betavoltaic cell without radioactive isotopes. The betavoltaic battery consists of radioisotope that is physically connected on the surface of Si-based PN diode. The performance of betavoltaic battery can be estimated by the efficiency of PN diode unit cell. The current generated by scanning electron microscope with fixed accelerating voltage (17keV) was measured by using faraday cup. Electrical characterization of the p-n junction diode was performed by using Nano Probe Work Station and I-V measurement system. The output value of the betavoltaic cells developed by this research team was 0.162 μw/cm2 and the efficiency was 1.14%.

Keywords: betavoltaic, nuclear, battery, Ni-63, radio-isotope

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Authors: Denise F. Brown

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This proposal provides an explanation of the content for a Special Topics Course to be offered Spring of 2022. The course will be titled, Creative means to address mental health in the African American Community: Arts, Advocacy, and Awareness. Research shows that African Americans are less likely to seek treatment for mental illnesses. The stigma around mental illness influences negative ideas about having psychological problems within the African American community. Assessments of how African Americans perceive mental illness will also be provided. Current research suggests that understanding mental health is just as important as understanding mental illness. The distinguishment between mental illness and mental health provides a way to not negatively point out mental illness but to better understand that psychological and emotional well-being can be achieved whether a mental illness is present or not. The course will consist of defining mental health and mental illness and then what it means to utilize creative means to become a mental health advocate within the African American community.

Keywords: arts, advocacy, black mental health, mental illness

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Authors: Noel Chellan

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Energy is the life-blood of development. All human societies have been and still are dependent on energy – some societies more than others. With regard to energy in South Africa, previous policies of the apartheid regime neglected the energy needs of poor black communities in general – and rural communities in particular. Since South Africa’s first democratic elections in 1994 – whilst millions of South African households have received electricity from the national electricity grid, there are still many rural communities that are still experiencing challenges in relation to both electricity deprivation as well as provision. This paper looks at the energy-mix of the Mnweni rural community in South Africa and argues that understanding energy is key to understanding the nature and forms of development of any community or country, for that matter. The paper engages with the energy trends in the rural community of Mnweni from the days of apartheid until 2021. It also looks at agricultural practises from an energy perspective. Such an energy perspective will enable one to assess the pace and scale of development in rural Mnweni.

Keywords: rural, energy, development, apartheid

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Authors: Ahmed Abdulla Ashlam, Atta Badii, Frederic Stahl

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In recent years, SQL injection attacks have been identified as being prevalent against web applications. They affect network security and user data, which leads to a considerable loss of money and data every year. This paper presents the use of classification algorithms in machine learning using a method to classify the login data filtering inputs into "SQLi" or "Non-SQLi,” thus increasing the reliability and accuracy of results in terms of deciding whether an operation is an attack or a valid operation. A method Web-App auto-generated twin data structure replication. Shielding against SQLi attacks (WebAppShield) that verifies all users and prevents attackers (SQLi attacks) from entering and or accessing the database, which the machine learning module predicts as "Non-SQLi" has been developed. A special login form has been developed with a special instance of data validation; this verification process secures the web application from its early stages. The system has been tested and validated, up to 99% of SQLi attacks have been prevented.

Keywords: SQL injection, attacks, web application, accuracy, database

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Authors: Kumar Sankaran, Santanu Chattopadhyay, Golok Behari Nando, Sujith Nair, Sreejesh Arayambath, Unnikrishnan Govindan

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Rubber nanocomposites based on Bromobutyl rubber (BIIR), Polyepichlorohydrin rubber (CO), Carbon black (CB) and organically modified montmorillonite clay (NC) were prepared via melt compounding technique. The developed quaternary nanocomposites were characterized analytically and their properties were compared against the standard BIIR compound. BIIR-CO nanocomposites showed improved physico-mechanical properties as compared to that of the standard BIIR compound. Hybrid microstructure (NC-CB) development, clay exfoliation and better filler dispersion in the quaternary nanocomposite significantly contributed to the overall enhancement of properties. Introduction of CO in the system increased the specific gravity and hardness of the compound as compared to that of the standard compound. XRD analysis, AFM imaging and HR-TEM measurements confirmed exfoliation and a good level of dispersion of the NC in the composites. Permeability of developed BIIR-CO nanocomposites decreases significantly as compared to that of the standard BIIR compound.

Keywords: rubber nanocomposites, morphology, permeability, BIIR

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Authors: Asma Perveen, M. P. Jahan

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Ni alloys have managed to cover wide range of applications such as automotive industries, oil gas industries, and aerospace industries. However, these alloys impose challenges while using conventional machining technologies. On the other hand, Micro-Electro-Discharge machining (micro-EDM) is a non-conventional machining method that uses controlled sparks energy to remove material irrespective of the materials hardness. There has been always a huge interest from the industries for developing optimum methodology and parameters in order to enhance the productivity of micro-EDM in terms of reducing machining time and tool wear for different alloys. Therefore, the aims of this study are to investigate the effects of the micro-EDM process parameters, in order to find their optimal values. The input process parameters include voltage, capacitance, and electrode rotational speed, whereas the output parameters considered are machining time, entrance diameter of hole, overcut, tool wear, and crater size. The surface morphology and element characterization are also investigated with the use of SEM and EDX analysis. The experimental result indicates the reduction of machining time with the increment of discharge energy. Discharge energy also contributes to the enlargement of entrance diameter as well as overcut. In addition, tool wears show reduction with the increase of discharge energy. Moreover, crater size is found to be increased in size along with the increment of discharge energy.

Keywords: micro holes, micro EDM, Ni Alloy, discharge energy

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Authors: Miroslav Popelka, Jakub Nožička

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In this paper we deal with using Lego Mindstorms in simulation of robotic systems with respect to cost reduction. Lego Mindstorms kit contains broad variety of hardware components which are required to simulate, program and test the robotics systems in practice. Algorithm programming went in development environment supplied together with Lego kit as in programming language C# as well. Algorithm following the line, which we dealt with in this paper, uses theoretical findings from area of controlling circuits. PID controller has been chosen as controlling circuit whose individual components were experimentally adjusted for optimal motion of robot tracking the line. Data which are determined to process by algorithm are collected by sensors which scan the interface between black and white surfaces followed by robot. Based on discovered facts Lego Mindstorms can be considered for low-cost and capable kit to simulate real robotics systems.

Keywords: LEGO Mindstorms, PID controller, low-cost robotics systems, line follower, sensors, programming language C#, EV3 Home Edition Software

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Authors: Babak Azari, Afshin Pourahmad, Babak Sadeghi, Masuod Mokhtari

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In this work, Equisetnm arvense plant extract was used for preparing amorphous SiO₂. For preparing of SiO₂/zeolitic imidazolate framework-8 (ZIF-8) nanocomposite by solvothermal method, the synthesized SiO₂ was added to the synthesis mixture ZIF-8. The nanocomposite was characterized using a range of techniques. The photocatalytic activity of SiO₂/ZIF-8 was investigated systematically by degrading crystal violet as a cationic dye under Ultraviolet light irradiation. Among synthesized samples (SiO₂, ZIF-8 and SiO₂/ZIF-8), the SiO₂/ZIF-8 exhibited the highest photocatalytic activity and improved stability compared to pure SiO₂ and ZIF-8. As evidenced by Scanning Electron Microscopy and Transmission electron microscopy images, ZIF-8 particles without aggregation are located over SiO₂. The SiO₂ not only provides structured support for ZIF-8 but also prevents the aggregation of ZIF-8 Metal-organic framework in comparison to the isolated ZIF-8. The superior activity of this photocatalyst was attributed to the synergistic effects from SiO₂ owing to (I) an electron acceptor (from ZIF-8) and an electron donor (to O₂ molecules), (II) preventing recombination of electron-hole in ZIF-8, and (III) maximum interfacial contact ZIF-8 with the SiO₂ surface without aggregation or prevent the accumulation of ZIF-8. The results demonstrate that holes (h+) and •O₂- are primary reactive species involved in the photocatalytic oxidation process. Moreover, the SiO₂/ZIF-8 photocatalyst did not show any obvious loss of photocatalytic activity during five-cycle tests, which indicates that the heterostructured photocatalyst was highly stable and could be used repeatedly.

Keywords: nano, zeolit, potocatalist, nanocomposite

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Authors: Suzan Anwar, Utkarsh Goyal

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Heart rate (HR) is a predictor of cardiovascular, cerebrovascular, and all-cause mortality in the general population, as well as in patients with cardio and cerebrovascular diseases. Machine learning (ML) significantly improves the accuracy of cardiovascular risk prediction, increasing the number of patients identified who could benefit from preventive treatment while avoiding unnecessary treatment of others. This research examines relationship between the individual's various heart health inputs like age, sex, cp, trestbps, thalach, oldpeaketc, and the likelihood of developing heart disease. Machine learning techniques like logistic regression and decision tree, and Python are used. The results of testing and evaluating the model using the Heart Failure Prediction Dataset show the chance of a person having a heart disease with variable accuracy. Logistic regression has yielded an accuracy of 80.48% without data handling. With data handling (normalization, standardscaler), the logistic regression resulted in improved accuracy of 87.80%, decision tree 100%, random forest 100%, and SVM 100%.

Keywords: heart rate, machine learning, SVM, decision tree, logistic regression, random forest

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Authors: Salima Smiti, Ines Gasmi, Makram Soui

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Credit risk is the most important issue for financial institutions. Its assessment becomes an important task used to predict defaulter customers and classify customers as good or bad payers. To this objective, numerous techniques have been applied for credit risk assessment. However, to our knowledge, several evaluation techniques are black-box models such as neural networks, SVM, etc. They generate applicants’ classes without any explanation. In this paper, we propose to assess credit risk using rules classification method. Our output is a set of rules which describe and explain the decision. To this end, we will compare seven classification algorithms (JRip, Decision Table, OneR, ZeroR, Fuzzy Rule, PART and Genetic programming (GP)) where the goal is to find the best rules satisfying many criteria: accuracy, sensitivity, and specificity. The obtained results confirm the efficiency of the GP algorithm for German and Australian datasets compared to other rule-based techniques to predict the credit risk.

Keywords: credit risk assessment, classification algorithms, data mining, rule extraction

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Authors: Rahim Ada, Mustafa Harmankaya, Sadiye Ayse Celik

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The safflower seed contains about 25-40% solvent extract and 20-33% fiber. It is well known that dietary phospholipids lower serum cholesterol levels effectively. The nutrient composition of safflower seed changes depending on region, soil and genotypes. This research was made by using of six natural selected (A22, A29, A30, C12, E1, F4, G8, G12, J27) and three commercial (Remzibey, Dincer, Black Sun1) varieties of safflower genotypes. The research was conducted on field conditions for two years (2009 and 2010) in randomized complete block design with three replications in Konya-Turkey ecological conditions. Oil contents, mineral contents and their correlations were determined in the research. According to the results, oil content was ranged from 22.38% to 34.26%, while the minerals were in between the following values: 1469, 04-2068.07 mg kg^-1 for Ca, 7.24-11.71 mg kg^-1 for B, 13.29-17.41 mg kg^-1 for Cu, 51.00-79.35 mg kg^-1 for Fe, 3988-6638.34 mg kg^-1 for K, 1418.61-2306.06 mg kg^-1 for Mg, 11.37-17.76 mg kg^-1 for Mn, 4172.33-7059.58 mg kg^-1 for P and 32.60-59.00 mg kg^-1 for Zn. Correlation analysis that was made separately for the commercial varieties and wild lines showed that high level of oil content was negatively affected by all the investigated minerals except for K and Zn in the commercial varieties.

Keywords: safflower, oil, quality, mineral content

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Authors: N. K. Bhute, B. B. Bhosle

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Field experiment was conducted during kharif 2005, at the experimental farm of the Department of Genetics and Plant Breeding, College of Agriculture, Marathwada Agricultural University, Parbhani, Maharashtra. F1 and F2 hybrids of 23 Bt and 5 non-Bt hybrids were grown in a randomized block design with two replications. The results showed that among F1 hybrids, open boll damage due to bollworm complex was not noticed in 4233 Bt and 4247 Bt cotton hybrids which were found significantly superior over MECH 6301 Bt (3.2 %), 4255 Bt (3.28 %) and it was at par with rest of the hybrids. Among F2 hybrids minimum open boll damage (3.10 %) was noticed in Proagro 144 Bt, which was found significantly superior over rest of the hybrids except 4234 Bt (4.17 %) and 4254 Bt (4.98 %) which were at par with each other. In respect of seed cotton yield, among F1 hybrids maximum yield (15.51 q/ha) was recorded in 4233 Bt which was found significantly superior over rest of the hybrids except 4237 Bt (15.24 q/ha). Among F2 maximum yield (15.44 q/ha) was recorded in 4233 Bt which was found significantly superior over rest of the hybrids except 4258 Bt (15.41 q/ha), 4239 Bt (15.098 q/ha) which were at par with each other. Thus F2 Bt cotton express Bt protein in segregated pattern in which bollworm attack was more as compared to F1 which affects yield as well as quality of lint.

Keywords: Bt cotton, bollworms, F1 and F2 generations, unprotected condition

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Authors: Cesar Maximo Oliva González, Javier Acevedo Cortez, Boris Kharisov, Thelma Serrano Quezada

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The importance of the crude oil refining process is due to the demand for petroleum products such as gasoline, kerosene, asphalt, etc., which are used in daily activities and have a high impact on the global economy. In the processes of oil obtaining and refining, it is common to find problems such as spills on seabed and high energy consumption in processing. In order to quickly and efficiently attack these problems, the use of adsorbents has taken on great importance due to its ease of implementation, as well as the possibility of their regeneration to be reused. In this work, the use of two types of adsorbents is proposed: the first is a natural adsorbent such as aloe vera or nopal, which were lyophilized and hydrophobized to achieve a selectivity in oil adsorption in oil / water mixtures. The second is a mixed iron/nickel oxide, which is specially designed to adsorb the asphaltenes in the heavy fractions of the oil; in addition, this type of adsorbents presents catalytic properties that manage to decompose the heavier fractions of the petroleum in light hydrocarbons, descending thus the energy required for the oil refining process.

Keywords: nanomaterials, oil spills, remediation, natural adsorbents, mixed oxides

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Authors: Albert Mufundirwa, Satoru Yoshioka, K. Ogi, Takeharu Sugiyama, George F. Harrington, Bretislav Smid, Benjamin Cunning, Kazunari Sasaki, Akari Hayashi, Stephen M. Lyth

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Polymer electrolyte membrane fuel cells (PEMFCs) are electrochemical energy conversion devices used for portable, residential and vehicular applications due to their low emissions, high efficiency, and quick start-up characteristics. However, PEMFCs generally use expensive, Pt-based electrocatalysts as electrode catalysts. Due to the high cost and limited availability of platinum, research and development to either drastically reduce platinum loading, or replace platinum with alternative catalysts is of paramount importance. A combination of high surface area supports and nano-structured active sites is essential for effective operation of catalysts. We synthesize carbon foam supports by thermal decomposition of sodium ethoxide, using a template-free, gram scale, cheap, and scalable pyrolysis method. This carbon foam has a high surface area, highly porous, three-dimensional framework which is ideal for electrochemical applications. These carbon foams can have surface area larger than 2500 m²/g, and electron microscopy reveals that they have micron-scale cells, separated by few-layer graphene-like carbon walls. We applied this carbon foam as a platinum catalyst support, resulting in the improved electrochemical surface area and mass activity for the oxygen reduction reaction (ORR), compared to carbon black. Similarly, silver-decorated carbon foams showed higher activity and efficiency for electrochemical carbon dioxide conversion than silver-decorated carbon black. A promising alternative to Pt-catalysts for the ORR is iron-impregnated nitrogen-doped carbon catalysts (Fe-N-C). Doping carbon with nitrogen alters the chemical structure and modulates the electronic properties, allowing a degree of control over the catalytic properties. We have adapted our synthesis method to produce nitrogen-doped carbon foams with large surface area, using triethanolamine as a nitrogen feedstock, in a novel bottom-up protocol. These foams are then infiltrated with iron acetate (FeAc) and pyrolysed to form Fe-N-C foams. The resulting Fe-N-C foam catalysts have high initial activity (half-wave potential of 0.68 VRHE), comparable to that of commercially available Pt-free catalysts (e.g., NPC-2000, Pajarito Powder) in acid solution. In alkaline solution, the Fe-N-C carbon foam catalysts have a half-wave potential of 0.89 VRHE, which is higher than that of NPC-2000 by almost 10 mVRHE, and far out-performing platinum. However, the durability is still a problem at present. The lessons learned from X-ray absorption spectroscopy (XAS), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), and electrochemical measurements will be used to carefully design Fe-N-C catalysts for higher performance PEMFCs.

Keywords: carbon-foam, polymer electrolyte membrane fuel cells, platinum, Pt-free, Fe-N-C, ORR

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Authors: Mohammed T. Hayajneh

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Machining of Metal Matrix Composites (MMCs) is very significant process and has been a main problem that draws many researchers to investigate the characteristics of MMCs during different machining process. The poor machining properties of hard particles reinforced MMCs make drilling process a rather interesting task. Unlike drilling of conventional materials, many problems can be seriously encountered during drilling of MMCs, such as tool wear and cutting forces. Cutting tool wear is a very significant concern in industries. Cutting tool wear not only influences the quality of the drilled hole, but also affects the cutting tool life. Prediction the cutting tool life during drilling is essential for optimizing the cutting conditions. However, the relationship between tool life and cutting conditions, tool geometrical factors and workpiece material properties has not yet been established by any machining theory. In this research work, fuzzy subtractive clustering system has been used to model the cutting tool life in drilling of Al₂O₃ particle reinforced aluminum alloy composite to investigate of the effect of cutting conditions on cutting tool life. This investigation can help in controlling and optimizing of cutting conditions when the process parameters are adjusted. The built model for prediction the tool life is identified by using drill diameter, cutting speed, and cutting feed rate as input data. The validity of the model was confirmed by the examinations under various cutting conditions. Experimental results have shown the efficiency of the model to predict cutting tool life.

Keywords: composite, fuzzy, tool life, wear

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Authors: Gaurav Bansod, Swapnil Sutar, Abhijit Patil, Jagdish Patil

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This paper proposes an ultra-lightweight cipher NUX. NUX is a generalized Feistel network. It supports 128/80 bit key length and block length of 64 bit. For 128 bit key length, NUX needs only 1022 GEs which is less as compared to all existing cipher design. NUX design results into less footprint area and minimal memory size. This paper presents security analysis of NUX cipher design which shows cipher’s resistance against basic attacks like Linear and Differential Cryptanalysis. Advanced attacks like Biclique attack is also mounted on NUX cipher design. Two different F function in NUX cipher design results in high diffusion mechanism which generates large number of active S-boxes in minimum number of rounds. NUX cipher has total 31 rounds. NUX design will be best-suited design for critical application like smart grid, IoT, wireless sensor network, where memory size, footprint area and the power dissipation are the major constraints.

Keywords: lightweight cryptography, Feistel cipher, block cipher, IoT, encryption, embedded security, ubiquitous computing

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Authors: Ebrahim Hassan Kapeel, Ahmed Mohsen Kamel, Hossan Hendy, Yehia Z. Elhalwagy

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Interest in autopilot design has been raised intensely as a result of recent advancements in Unmanned Aerial vehicles (UAVs). Due to the enormous number of applications that UAVs can achieve, the number of applied control theories used for them has increased in recent years. These small fixed-wing UAVs are suffering high non-linearity, sensitivity to disturbances, and coupling effects between their channels. In this work, the nonlinear dynamic inversion (NDI) control lawisdesigned for a nonlinear small fixed-wing UAV model. The NDI is preferable for varied operating conditions, there is no need for a scheduling controller. Moreover, it’s applicable for high angles of attack. For the designed flight controller validation, a nonlinear Modified PI-D controller is performed with our model. A comparative study between both controllers is achieved to evaluate the NDI performance. Simulation results and analysis are proposed to illustrate the effectiveness of the designed controller based on NDI.

Keywords: UAV dynamic model, attitude control, nonlinear PID, dynamic inversion

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Authors: Aslı Şalcıoğlu, Grigorous Krey, Raşit Bilgin

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In this study, the effect of the Turkish Straits System (TSS), comprising a biogeographical boundary that forms the connection between the Mediterranean and the Black Sea, on the evolutionary history, phylogeography and intraspecific gene flow of the whiting (Merlangius merlangus) a demersal fish species, was investigated. For these purposes, the mitochondrial DNA (CO1, cyt-b) genes were used. In addition, genetic comparisons samples from other regions (Greece, France, Atlantic) obtained from GenBank and Barcode of Life Database were made to better understand the phylogeographic history of the species at a larger geographic scale. Within this study, high level of genetic differentiation was observed along the Turkish coastal waters based on cyt-b gene, suggesting that TSS is a barrier to dispersal. Two different sub-species were also observed based on mitochondrial DNA, one found in Turkish coastal waters and Greece (M.m euxinus) and other (M.m. merlangus) in Atlantic, France.

Keywords: genetic, phylogeography, TSS, whiting

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Authors: Rachid Belhachemi, Pierre Rostan, Alexandra Rostan

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This paper develops a discrete-time option pricing model for index options. The model consists of two key ingredients. First, daily stock return innovations are driven by a continuous hidden threshold mixed skew-normal (HTSN) distribution which generates conditional non-normality that is needed to fit daily index return. The most important feature of the HTSN is the inclusion of a latent state variable with a continuum of states, unlike the traditional mixture distributions where the state variable is discrete with little number of states. The HTSN distribution belongs to the class of univariate probability distributions where parameters of the distribution capture the dependence between the variable of interest and the continuous latent state variable (the regime). The distribution has an interpretation in terms of a mixture distribution with time-varying mixing probabilities. It has been shown empirically that this distribution outperforms its main competitor, the mixed normal (MN) distribution, in terms of capturing the stylized facts known for stock returns, namely, volatility clustering, leverage effect, skewness, kurtosis and regime dependence. Second, heteroscedasticity in the model is captured by a threeexogenous-factor GARCH model (GARCHX), where the factors are taken from the principal components analysis of various world indices and presents an application to option pricing. The factors of the GARCHX model are extracted from a matrix of world indices applying principal component analysis (PCA). The empirically determined factors are uncorrelated and represent truly different common components driving the returns. Both factors and the eight parameters inherent to the HTSN distribution aim at capturing the impact of the state of the economy on price levels since distribution parameters have economic interpretations in terms of conditional volatilities and correlations of the returns with the hidden continuous state. The PCA identifies statistically independent factors affecting the random evolution of a given pool of assets -in our paper a pool of international stock indices- and sorting them by order of relative importance. The PCA computes a historical cross asset covariance matrix and identifies principal components representing independent factors. In our paper, factors are used to calibrate the HTSN-GARCHX model and are ultimately responsible for the nature of the distribution of random variables being generated. We benchmark our model to the MN-GARCHX model following the same PCA methodology and the standard Black-Scholes model. We show that our model outperforms the benchmark in terms of RMSE in dollar losses for put and call options, which in turn outperforms the analytical Black-Scholes by capturing the stylized facts known for index returns, namely, volatility clustering, leverage effect, skewness, kurtosis and regime dependence.

Keywords: continuous hidden threshold, factor models, GARCHX models, option pricing, risk-premium

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Authors: Memar Ayalew Demeke, Solomon Gebreyohans Gebru

Abstract:

In Africa, Regional Economic Communities (RECs) were initially established to tackle the economic challenges of the continent. However, overtime, they expanded their mandate to deal with the security threats of the continent such as terrorism. In fact, the fight against terrorism has been internationalized following the September 9/11 terrorist attack in the U.S.A. Since then, RECs have been giving considerable attention to preventing and combating terrorism in their respective regions. Similarly, IGAD has been involved in preventing and combating terrorism. So far, however, little has been done with regard to what IGAD has performed in fighting terrorism. Therefore, this study was intended to describe and analyze the legal and practical activities carried out by IGAD in its fight against terrorism in the region general and in Somalia in particular. Both descriptive and analytical methods were employed and data were analyzed through qualitative approach. Finally, based on the findings, the study argues that, instead of over-reliance on hard power as a means of fighting terrorism, IGAD should invest more on the political and socio-economic problems of its member states so as to address the root causes.

Keywords: regional economic communities, IGAD, terrorism, treaties, conventions

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Authors: Ines Gasmi, Salima Smiti, Makram Soui, Khaled Ghedira

Abstract:

Credit risk is considered as one of the important issues for financial institutions. It provokes great losses for banks. To this objective, numerous methods for credit risk evaluation have been proposed. Many evaluation methods are black box models that cannot adequately reveal information hidden in the data. However, several works have focused on building transparent rules-based models. For credit risk assessment, generated rules must be not only highly accurate, but also highly interpretable. In this paper, we aim to build both, an accurate and transparent credit risk evaluation model which proposes a set of classification rules. In fact, we consider the credit risk evaluation as an optimization problem which uses a genetic programming (GP) algorithm, where the goal is to maximize the accuracy of generated rules. We evaluate our proposed approach on the base of German and Australian credit datasets. We compared our finding with some existing works; the result shows that the proposed GP outperforms the other models.

Keywords: credit risk assessment, rule generation, genetic programming, feature selection

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Authors: Xavier Ruiz Del Portal

Abstract:

This paper incorporates mobility between the legal and black economies into a model of tax evasion with endogenous labor supply in which underreporting is possible in one sector but impossible in the other. We have found that the results of the effects along the extensive margin (number of evaders) become more robust and conclusive than those along the intensive margin (hours of illegal work) usually considered by the literature. In particular, it is shown that the following policies reduce the number of evaders: (a) larger and more progressive evasion penalties; (b) higher detection probabilities; (c) an increase in the legal sector wage rate; (d) a decrease in the moonlighting wage rate; (e) higher costs for creating opportunities to evade; (f) lower opportunities to evade, and (g) greater psychological costs of tax evasion. When tax concealment and illegal work also are taken into account, the effects do not vary significantly under the assumptions in Cowell (1985), except for the fact that policies (a) and (b) only hold as regards low- and middle-income groups and policies (e) and (f) as regards high-income groups.

Keywords: income taxation, tax evasion, extensive margin responses, the penalty system

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Authors: Deng Zengming, Wang Mingjiang

Abstract:

As 3D video is explored as a hot research topic in the last few decades, free-viewpoint TV (FTV) is no doubt a promising field for its better visual experience and incomparable interactivity. View synthesis is obviously a crucial technology for FTV; it enables to render images in unlimited numbers of virtual viewpoints with the information from limited numbers of reference view. In this paper, a novel hybrid synthesis framework is proposed and blending priority is explored. In contrast to the commonly used View Synthesis Reference Software (VSRS), the presented synthesis process is driven in consideration of the temporal correlation of image sequences. The temporal correlations will be exploited to produce fine synthesis results even near the foreground boundaries. As for the blending priority, this scheme proposed that one of the two reference views is selected to be the main reference view based on the distance between the reference views and virtual view, another view is chosen as the auxiliary viewpoint, just assist to fill the hole pixel with the help of background information. Significant improvement of the proposed approach over the state-of –the-art pixel-based virtual view synthesis method is presented, the results of the experiments show that subjective gains can be observed, and objective PSNR average gains range from 0.5 to 1.3 dB, while SSIM average gains range from 0.01 to 0.05.

Keywords: fusion method, Gaussian mixture model, hybrid framework, view synthesis

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Authors: Sahil Kumar, Surinder Pal, Rahul Kapoor

Abstract:

This paper is focused on to define the basic difference between hot and cold chamber high pressure die casting process which is not fully defined in a research before paper which we have studied. The pressure die casting is basically defined into two types (1) Hot chamber Die Casting (2) Cold chamber Die Casting. Cold chamber die casting is used for casting alloys that require high pressure and have a high melting temperature, such as brass, aluminum, magnesium, copper based alloys and other high melting point nonferrous alloys. Hot chamber die casting is suitable for casting zinc, tin, lead, and low melting point alloys. In hot chamber die casting machine, the molten metal is an integral pan of the machine. It mainly consists of hot chamber and gooseneck type metal container made of cast iron. This machine is mainly used for low melting alloys and alloys of metals like zinc, lead etc. Metals and alloys having a high melting point and those which are having an affinity for iron cannot be cast by this machine, which could otherwise attack the shot sleeve and damage the machine.

Keywords: hot chamber die casting, cold chamber die casting, metals and alloys, casting technology

Procedia PDF Downloads 599