Search results for: supervised dimension reduction

Authors: Muhammad Ajmal, Muhammad Siddiq, Nurettin Sahiner

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We prepared poly(methacrylic acid-co-acrylonitrile) (p(MAc-co-AN)) microgels by inverse suspension polymerization, and converted the nitrile groups into amidoxime groups to obtain more hydrophilic amidoximated poly(methacrylic acid-co-acrylonitile) (amid-p(MAc-co-AN)) microgels. Amid-microgels were used as microreactors for in situ synthesis of copper and cobalt nanoparticles. Cu (II) and Co (II) ions were loaded into microgels from their aqueous metal salt solutions and then converted to corresponding metal nanoparticle (MNP) by treating the loaded metal ions with sodium borohydride (NaBH4). The characterization of the prepared microgels and microgel metal nanoparticle composites was carried out by SEM, TEM and TG analysis. The amounts of metal nanoparticles within microgels were estimated by AAS measurements by dissolving the MNP entrapped within microgels by concentrated HCl acid treatment. Catalytic performances of the prepared amid-p(MAc-co-AN)-M (M: Cu, Co) microgel composites were investigated by using them as catalyst for the degradation of cationic and anionic organic dyes such as eosin Y (EY), methylene blue (MB) and methyl Orange (MO), and for the reduction of nitro aromatic pollutants like 2-nitrophenol (2-NP) and 4-nitrophenol (4-NP) to their corresponding amino phenols. Here, we also report for the first time, the simultaneous degradation/reduction of MB, EY, and 4-NP by amid-p(MAc-co-AN)-Cu microgel composites. Different parameters affecting the reduction rates such as metal types, amount of catalysts, temperature and the amount of reducing agent were investigated.

Keywords: microgels, nanoparticles, catalyst, pollutants

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Authors: Najmul Hasan, Shiping Li, Chunli Liu

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The synergy effect of surface modifications using the acid treatment and noble metal (Au) deposition on the efficiency of SnFe2O4 (SFO) nano-octahedron photocatalyst has been investigated. Inorganic acids (H2SO4 and HNO3) were employed to compare the effects of different acids. It has been found that after corrosion treatment using H2SO4 and deposition of Au nanoparticles, SnFe2O4 nano-octahedron (Au-S-SFO) showed significantly enhanced photocatalytic activity under simulated light irradiation. Au-S-SFO was characterized by XRD, XPS, EDS, FTIR, Uv-vis-DRS, SEM, PL, and EIS analysis. The mechanism for CO2 reduction was investigated by scavenger tests. The stability of Au-S-SFO was confirmed by continuously repeated tests followed by XRD analysis. The surface corrosion treatment of SFO octahedron with H2SO4 could produce hydroxyl group (-OH) and sulfonic acid group (-SO3H) as reaction sites. These active sites not only enhanced the Au nanoparticles deposition to the acid treated SFO surface but also acted as the Brønsted acid sites that enhance the water adsorption and provide protons for CTC degradation and CO2 reduction. These effects improved the carrier separation and transfer efficiency. In addition, the photocatalytic efficiency was further enhanced by the surface plasmon resonance (SPR) effect of Au nanoparticles deposited on the surface of acid-treated SFO. As a result of the synergy of both acid treatment and SPR effect from the Au NPs, Au-S-SFO exhibited the highest CO2 reduction activity with 2.81, 1.92, and 2.69 times higher evolution rates for CO, CH4, and H2, respectively than that of pure SFO.

Keywords: surface modification, CO2 reduction, Au deposition, Gas-liquid interfacial plasma

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Authors: Mahmoud Ashraf Farouk

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Shipping transportation is the foremost imperative mode of transportation in universal coordination. At display, more than 2/3 of the full worldwide exchange volume accounts for shipping transportation. Ships are utilized as an implies of marine transportation, introducing large-power diesel motors with exhaust containing nitrogen oxide NOx, sulfur oxide SOx, carbo di-oxide CO₂, particular matter PM10, hydrocarbon HC and carbon mono-oxide CO which are the most dangerous contaminants found in exhaust gas from ships. Ships radiating a large amount of exhaust gases have become a significant cause of pollution in the air in coastal areas, harbors and oceans. Therefore, IMO (the International Maritime Organization) has established rules to reduce this emission. This experiment shows the measurement of the exhaust gases emitted from the Aida IV ship's main engine using marine diesel oil fuel (MDO). The measurement is taken by the Sensonic2000 device on 85% load, which is the main sailing load. Moreover, the paper studies different emission reduction technologies as an alternative fuel, which as liquefied natural gas (LNG) applied to the system and reduction technology which is represented as selective catalytic reduction technology added to the marine diesel oil system (MDO+SCR). The experiment calculated the amount of nitrogen oxide NOx, sulfur oxide SOx, carbon-di-oxide CO₂, particular matter PM10, hydrocarbon HC and carbon mono-oxide CO because they have the most effect on the environment. The reduction technologies are applied on the same ship engine with the same load. Finally, the study found that MDO+SCR is the more efficient technology for the Aida IV ship as a training and supply ship due to low consumption and no need to modify the engine. Just add the SCR system to the exhaust line, which is easy and cheapest. Moreover, the differences between them in the emission are not so big.

Keywords: marine, emissions, reduction, shipping

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Authors: Qaiser Akram, Ahsan Naeem, Hafiz Muhammad Rizwan, Waqas Ahmad, Rubeena Yasmeen

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Aspergillus has good secretory potential for phytases. Morphologically and microscopically identified Aspergillus terreus (A. terreus) (n=20) were screened for phytase production and non-toxicity. Phytases produced by non-toxigenic A. terreus under optimum conditions were quantified. Phytases of highest producer A. terreus were evaluated for stability after exposure to temperature (35, 55, 75 and 95ºC) and pH (2, 4, 6 and 8). Effect of metal ions (Fe⁺³, Ba⁺², Ca⁺², Cu⁺², Mg⁺², Mn⁺², K⁺¹ and Na⁺¹) was assessed on phytase activity. Log reduction in phytase activity was calculated. The highest activity units of phytase produced by A. terreus were 271.49 ± 8.14 phytase unit / mL (FTU/ mL). The lowest reduction in phytase activity was 50.20 ± 7.36 (18.5%) and 68.22 ± 10.3 FTU/mL (25.13%) at 35ºC and pH 6, respectively for 15 minutes. The highest reduction 259 ± 0.84 (95.5%) and 211.99 ± 4.39 FTU/mL (78.1%) was recorded at 95ºC for 60 minutes and pH 2.0 for 45 minutes exposure, respectively. All metal ions negatively affected phytase activity. Phytase activity was inhibited minimum (45.32 ± 28.54 FTU/mL, 16.69%) by K⁺¹(1 mM) and maximum (231.48 ± 3.68 FTU/mL, 80.8%) by Cu⁺² (10 mM). It was concluded that A. terreus phytase stability and activity was dependent on physio-chemical factors.

Keywords: stability, phytase, aspergillus terreus, physio-chemical factors and metal ions

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Authors: Ligia Florio, João Mauricio Castaldelli-Maia

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Background: Food addiction (FA) emerged in the 1990s as a possible contributor to the increasing prevalence of obesity and overweight, in conjunction with changing food environments and mental health conditions. However, FA is not yet listed as one of the disorders in the DSM-5 and/or the ICD-11. Although there are controversies and debates in the literature about the classification and construct of FA, the most common approach to access it is the use of a research tool - the Yale Food Addiction Scale (YFAS) - which approximates the concept of FA to the concept diagnosis of dependence on psychoactive substances. There is a need to explore the dimensional phenotypes accessed by YFAS in different population groups for a better understanding and scientific support of FA diagnoses. Methods: The primary objective of this project was to investigate the construct validity of the FA concept by mYFAS 2.0 in individuals who underwent bariatric surgery (n = 100) at the Hospital Estadual Mário Covas since 2011. Statistical analyzes were conducted using the STATA software. In this sense, structural or factor validity was the type of construct validity investigated using exploratory factor analysis (EFA) and item response theory (IRT) techniques. Results: EFA showed that the one-dimensional model was the most parsimonious. The IRT showed that all criteria contributed to the latent structure, presenting discrimination values greater than 0.5, with most presenting values greater than 2. Conclusion: This study reinforces a FA dimension in patients who underwent bariatric surgery. Within this dimension, we identified the most severe and discriminating criteria for the diagnosis of FA.

Keywords: obesity, food addiction, bariatric surgery, regain

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Authors: Kunihisa Kakumoto

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“Purpose”: Global environmental issues are now being raised in a global dimension. By predicting sprawl phenomena beyond the limits of nature with algorithms, we can expect to protect our social life within the limits of nature. It turns out that the sustainable state of the planet now consists in maintaining a balance between the capabilities of nature and the possibilities of our social life. The amount of water on earth is finite. Sustainability is therefore highly dependent on water capacity. A certain amount of water is stored in the forest by planting and green space, and the amount of water can be considered in relation to the green space. CO2 is also absorbed by green plants. "Possible measurements and methods": The concept of the solar community has been introduced in technical papers on the occasion of many international conferences. The solar community concept is based on data collected from one solar model house. This algorithmic study simulates the amount of water stored by lush green vegetation. In addition, we calculated and compared the amount of CO2 emissions from the Taiyo Community and the amount of CO2 reduction from greening. Based on the trial calculation results of these solar communities, we are simulating the sustainable state of the earth as an algorithm trial calculation result. We believe that we should also consider the composition of this solar community group using digital technology as control technology. "Conclusion": We consider the solar community as a prototype for finding sustainable conditions for the planet. The role of water is very important as the supply capacity of water is limited. However, the circulation of social life is not constructed according to the mechanism of nature. This simulation trial calculation is explained using the total water supply volume as an example. According to this process, algorithmic calculations consider the total capacity of the water supply and the population and habitable numbers of the area. Green vegetated land is very important to keep enough water. Green vegetation is also very important to maintain CO2 balance. A simulation trial calculation is possible from the relationship between the CO2 emissions of the solar community and the amount of CO2 reduction due to greening. In order to find this total balance and sustainable conditions, the algorithmic simulation calculation takes into account lush vegetation and total water supply. Research to find sustainable conditions is done by simulating an algorithmic model of the solar community as a prototype. In this one prototype example, it's balanced. The activities of our social life must take place within the permissive limits of natural mechanisms. Of course, we aim for a more ideal balance by utilizing auxiliary digital control technology such as AI.

Keywords: solar community, sustainability, prototype, algorithmic simulation

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Authors: S. Anuradha, V. Sandeep Kumar

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The high Peak to Average Power Ratio (PAR) in Filter Bank Multicarrier with Offset Quadrature Amplitude Modulation (FBMC-OQAM) can significantly reduce power efficiency and performance. In this paper, we address the problem of PAPR reduction for FBMC-OQAM systems using Tone Reservation (TR) technique. Due to the overlapping structure of FBMCOQAM signals, directly applying TR schemes of OFDM systems to FBMC-OQAM systems is not effective. We improve the tone reservation (TR) technique by employing sliding window with Active Constellation Extension for the PAPR reduction of FBMC-OQAM signals, called sliding window tone reservation Active Constellation Extension (SW-TRACE) technique. The proposed SW-TRACE technique uses the peak reduction tones (PRTs) of several consecutive data blocks to cancel the peaks of the FBMC-OQAM signal inside a window, with dynamically extending outer constellation points in active(data-carrying) channels, within margin-preserving constraints, in order to minimize the peak magnitude. Analysis and simulation results compared to the existing Tone Reservation (TR) technique for FBMC/OQAM system. The proposed method SW-TRACE has better PAPR performance and lower computational complexity.

Keywords: FBMC-OQAM, peak-to-average power ratio, sliding window, tone reservation Active Constellation Extension

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Authors: James Jr. Mashiyane, Risuna Nkolele, Stephanie J. Müller, Gciniwe S. Dlamini, Rebone L. Meraba, Darlington S. Mapiye

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When performing language tasks in natural language processing (NLP), the dimensionality of word embeddings is chosen either ad-hoc or is calculated by optimizing the Pairwise Inner Product (PIP) loss. The PIP loss is a metric that measures the dissimilarity between word embeddings, and it is obtained through matrix perturbation theory by utilizing the unitary invariance of word embeddings. Unlike in natural language, in genomics, especially in genome sequence processing, unlike in natural language processing, there is no notion of a “word,” but rather, there are sequence substrings of length k called k-mers. K-mers sizes matter, and they vary depending on the goal of the task at hand. The dimensionality of word embeddings in NLP has been studied using the matrix perturbation theory and the PIP loss. In this paper, the sufficiency and reliability of applying word-embedding algorithms to various genomic sequence datasets are investigated to understand the relationship between the k-mer size and their embedding dimension. This is completed by studying the scaling capability of three embedding algorithms, namely Latent Semantic analysis (LSA), Word2Vec, and Global Vectors (GloVe), with respect to the k-mer size. Utilising the PIP loss as a metric to train embeddings on different datasets, we also show that Word2Vec outperforms LSA and GloVe in accurate computing embeddings as both the k-mer size and vocabulary increase. Finally, the shortcomings of natural language processing embedding algorithms in performing genomic tasks are discussed.

Keywords: word embeddings, k-mer embedding, dimensionality reduction

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Authors: Ashwaq Alsulami, Jianhua Shao

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Various organisations often need to understand discussions on social media, such as what trending topics are and characteristics of the people engaged in the discussion. A number of approaches have been proposed to extract attributes that would characterise a discussion group. However, these approaches are largely based on supervised learning, and as such they require a large amount of labelled data. We propose an approach in this paper that does not require labelled data, but rely on lexical sources to detect meaningful attributes for online discussion groups. Our findings show an acceptable level of accuracy in detecting attributes for Twitter discussion groups.

Keywords: attributed community, attribute detection, community, social network

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Authors: Rajani S. Pujar, Pandurangarao N. Kulkarni

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Increased temporal masking affects the speech perception in persons with sensorineural hearing impairment especially under adverse listening conditions. This paper presents a cascaded scheme, which employs a noise reduction algorithm as well as temporal splitting of the speech signal. Earlier investigations have shown that by splitting the speech temporally and presenting alternate segments to the two ears help in reducing the effect of temporal masking. In this technique, the speech signal is processed by two fading functions, complementary to each other, and presented to left and right ears for binaural dichotic presentation. In the present study, half cosine signal is used as a fading function with crossover gain of 6 dB for the perceptual balance of loudness. Temporal splitting is combined with noise reduction algorithm to improve speech perception in the background noise. Two noise reduction schemes, namely spectral subtraction and Wiener filter are used. Listening tests were conducted on six normal-hearing subjects, with sensorineural loss simulated by adding broadband noise to the speech signal at different signal-to-noise ratios (∞, 3, 0, and -3 dB). Objective evaluation using PESQ was also carried out. The MOS score for VCV syllable /asha/ for SNR values of ∞, 3, 0, and -3 dB were 5, 4.46, 4.4 and 4.05 respectively, while the corresponding MOS scores for unprocessed speech were 5, 1.2, 0.9 and 0.65, indicating significant improvement in the perceived speech quality for the proposed scheme compared to the unprocessed speech.

Keywords: MOS, PESQ, spectral subtraction, temporal splitting, wiener filter

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Authors: Chanchal Biswas, Anrin Bhattacharyya, Gopes Chandra Das, Mahua Ghosh Chaudhuri, Rajib Dey

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Boiler coals with low fixed carbon and higher ash content have always challenged the metallurgists to develop a suitable method for their utilization. In the present study, an attempt is made to establish an energy effective method for the reduction of iron ore fines in the form of nuggets by using ‘Syngas’. By devolatisation (expulsion of volatile matter by applying heat) of boiler coal, gaseous product (enriched with reducing agents like CO, CO2, H2, and CH4 gases) is generated. Iron ore nuggets are reduced by this syngas. For that reason, there is no direct contact between iron ore nuggets and coal ash. It helps to control the minimization of the sulphur intake of the reduced nuggets. A laboratory scale devolatisation furnace designed with reduction facility is evaluated after in-depth studies and exhaustive experimentations including thermo-gravimetric (TG-DTA) analysis to find out the volatile fraction present in boiler grade coal, gas chromatography (GC) to find out syngas composition in different temperature and furnace temperature gradient measurements to minimize the furnace cost by applying one heating coil. The nuggets are reduced in the devolatisation furnace at three different temperatures and three different times. The pre-reduced nuggets are subjected to analytical weight loss calculations to evaluate the extent of reduction. The phase and surface morphology analysis of pre-reduced samples are characterized using X-ray diffractometry (XRD), energy dispersive x-ray spectrometry (EDX), scanning electron microscopy (SEM), carbon sulphur analyzer and chemical analysis method. Degree of metallization of the reduced nuggets is 78.9% by using boiler grade coal. The pre-reduced nuggets with lesser sulphur content could be used in the blast furnace as raw materials or coolant which would reduce the high quality of coke rate of the furnace due to its pre-reduced character. These can be used in Basic Oxygen Furnace (BOF) as coolant also.

Keywords: alternative ironmaking, coal gasification, extent of reduction, nugget making, syngas based DRI, solid state reduction

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Authors: Julius Onyancha, Valentina Plekhanova

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One of the significant issues facing web users is the amount of noise in web data which hinders the process of finding useful information in relation to their dynamic interests. Current research works consider noise as any data that does not form part of the main web page and propose noise web data reduction tools which mainly focus on eliminating noise in relation to the content and layout of web data. This paper argues that not all data that form part of the main web page is of a user interest and not all noise data is actually noise to a given user. Therefore, learning of noise web data allocated to the user requests ensures not only reduction of noisiness level in a web user profile, but also a decrease in the loss of useful information hence improves the quality of a web user profile. Noise Web Data Learning (NWDL) tool/algorithm capable of learning noise web data in web user profile is proposed. The proposed work considers elimination of noise data in relation to dynamic user interest. In order to validate the performance of the proposed work, an experimental design setup is presented. The results obtained are compared with the current algorithms applied in noise web data reduction process. The experimental results show that the proposed work considers the dynamic change of user interest prior to elimination of noise data. The proposed work contributes towards improving the quality of a web user profile by reducing the amount of useful information eliminated as noise.

Keywords: web log data, web user profile, user interest, noise web data learning, machine learning

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Authors: Saleh Alumaran, Giampaolo Bella, Feng Chen

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The study of organisations’ information security cultures has attracted scholars as well as healthcare services industry to research the topic and find appropriate tools and approaches to develop a positive culture. The vast majority of studies in Saudi national health services are on the use of technology to protect and secure health services information. On the other hand, there is a lack of research on the role and impact of an organisation’s cultural dimensions on information security. This research investigated and analysed the role and impact of cultural dimensions on information security in Saudi Arabia health service. Hypotheses were tested and two surveys were carried out in order to collect data and information from three major hospitals in Saudi Arabia (SA). The first survey identified the main cultural-dimension problems in SA health services and developed an initial information security culture framework model. The second survey evaluated and tested the developed framework model to test its usefulness, reliability and applicability. The model is based on human behaviour theory, where the individual’s attitude is the key element of the individual’s intention to behave as well as of his or her actual behaviour. The research identified six cultural dimensions: Saudi national culture, Saudi health service leadership, employees’ trust, technology, multicultural interactions and employees’ job roles. The research also identified a set of cultural sub-dimensions. These include working values and norms, tribe values and norms, attitudes towards women, power sharing, vision, social interaction, respect and understanding, hospital intra-net, hospital employees’ language(s) used, multi-national culture, communication system, employees’ job satisfaction and job security. The research identified that (a) the human behaviour towards medical information in SA is one of the main threats to information security and one of the main challenges to SA health authority, (b) The current situation of SA hospitals’ IS cultures is falling short in protecting medical information due to the current value and norms towards information security, (c) Saudi national culture and employees’ job role are the main dimensions playing major roles in the employees’ attitude, and technology is the least important dimension playing a role in the employees’ attitudes.

Keywords: cultural dimension, electronic health record, information security, privacy

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Authors: Xingxing Peng

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With the development of society, there are more and more online communication scenarios such as teleconference and online education. In the process of conference communication, the quality of voice communication is a very important part, and noise may cause the communication effect of participants to be greatly reduced. Therefore, voice noise reduction has an important impact on scenarios such as voice calls. This research focuses on the key technologies of the sound transmission process. The purpose is to maintain the audio quality to the maximum so that the listener can hear clearer and smoother sound. Firstly, to solve the problem that the traditional speech enhancement algorithm is not ideal when dealing with non-stationary noise, an adaptive speech noise reduction algorithm is studied in this paper. Traditional noise estimation methods are mainly used to deal with stationary noise. In this chapter, we study the spectral characteristics of different noise types, especially the characteristics of non-stationary Burst noise, and design a noise estimator module to deal with non-stationary noise. Noise features are extracted from non-speech segments, and the noise estimation module is adjusted in real time according to different noise characteristics. This adaptive algorithm can enhance speech according to different noise characteristics, improve the performance of traditional algorithms to deal with non-stationary noise, so as to achieve better enhancement effect. The experimental results show that the algorithm proposed in this chapter is effective and can better adapt to different types of noise, so as to obtain better speech enhancement effect.

Keywords: speech noise reduction, speech enhancement, self-adaptation, Wiener filter algorithm

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Authors: Jana Soler Libran

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The primary aim of this paper is to analyze the relationship between power and knowledge suggested in Michel Foucault's theory. Taking into consideration the role of power in knowledge production, the goal is to evaluate to what extent genealogy can be presented as a practical method for epistemic resistance. To do so, the methodology used consists of a revision of Foucault’s literature concerning the topic discussed. In this sense, conceptual analysis is applied in order to understand the effect of the double dimension of power on knowledge production. In its negative dimension, power is conceived as an organ of repression, vetoing certain instances of knowledge considered deceitful. In opposition, in its positive dimension, power works as an organ of the production of truth by means of institutionalized discourses. This double declination of power leads to the first main findings of the present analysis: no truth or knowledge can lie outside power’s action, and power is constituted through accepted forms of knowledge. To second these statements, Foucaultian discourse formations are evaluated, presenting external exclusion procedures as paradigmatic practices to demonstrate how power creates and shapes the validity of certain epistemes. Thus, taking into consideration power’s mechanisms to produce and reproduce institutionalized truths, this paper accounts for the Foucaultian praxis of genealogy as a method to reveal power’s intention, instruments, and effects in the production of knowledge. In this sense, it is suggested to consider genealogy as a practice which, firstly, reveals what instances of knowledge are subjugated to power and, secondly, promotes aforementioned peripherical discourses as a form of epistemic resistance. In order to counterbalance these main theses, objections to Foucault’s work from Nancy Fraser, Linda Nicholson, Charles Taylor, Richard Rorty, Alvin Goldman, or Karen Barad are discussed. In essence, the understanding of the Foucaultian relationship between power and knowledge is essential to analyze how contemporary discourses are produced by both traditional institutions and new forms of institutionalized power, such as mass media or social networks. Therefore, Michel Foucault's practice of genealogy is relevant, not only for its philosophical contribution as a method to uncover the effects of power in knowledge production but also because it constitutes a valuable theoretical framework for political theory and sociological studies concerning the formation of societies and individuals in the contemporary world.

Keywords: epistemic resistance, Foucault’s genealogy, knowledge, power, truth

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Authors: Omar A. Shaneb, Adell S. Amer

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Reduction of CO2 emissions has become a priority for several countries due to increasing concerns about global warming and climate change, especially in the developed countries. Residential sector is considered one of the most important sectors for considerable reduction of CO2 emissions since it represents a significant amount of the total consumed energy in those countries. A significant CO2 reduction cannot be achieved unless some initiatives have been adopted in the policy of these countries. Introducing micro combined heat and power (µCHP) systems into residential energy systems is one of these initiatives, since such a technology offers several advantages. Moreover, µCHP technology has the opportunity to be operated not only by natural gas but it could also be operated by renewable fuels. However, this technology can be operated by different operation strategies. Each strategy has some advantages and disadvantages. This paper provides a review of different operation strategies of such a technology used for residential energy systems, especially for single dwellings. The review summarizes key points that outline the trend of previous research carried out in this field.

Keywords: energy management, µCHP systems, residential energy systems, sustainable houses, operation strategy.

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Authors: Mohammad O. Diab, Sahera A. Saleh, Mustapha M. Dichari, Nijez Aloulou, Omar Hamoui, Feras Chehade

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This study sought to evaluate the efficiency of lead-free sterile radiation shield (Radionex) in the reduction of physician's exposure dose during interventional cardiology procedures. Cardiac catheterization procedures are often associated with high radiation doses and high levels of secondary radiation emitted by the patient's body. This study compares physician exposure dose rate during cardiac catheterization procedures done through the femoral artery with sterile radiation shielding to same procedures made without the shielding. The mean operator radiation dose rate without using the shield was found to be 18.4µSv/min compared to a mean dose rate of 5.1 µSv/min when using the shield, rendering a reduction of 72.5% of radiation received by the physician. Sterile radiation shielding is consequently an effective addition to a cardiac catheterization lab radiation protection system.

Keywords: cardiac catheterization, physician exposure dose, sterile radiation shielding, lead-free sterile radiation shields

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Authors: Valdir Moura, Raniele dos Anjos de Souza, Fernando Gomes de Souza, Jose Vagner da Silva, Jerry Adriani Johann

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The estimate of the Area of Land to be planted with annual crops and its stratification by the municipality are important variables in crop forecast. Nowadays in Brazil, these information’s are obtained by the Brazilian Institute of Geography and Statistics (IBGE) and published under the report Assessment of the Agricultural Production. Due to the high cloud cover in the main crop growing season (October to March) it is difficult to acquire good orbital images. Thus, one alternative is to work with remote sensing data from dates before the crop growing season. This work presents the use of multitemporal Landsat data gathered on July and September (before the summer growing season) in order to estimate the area of land to be planted with summer crops in an area of São Paulo State, Brazil. Geographic Information Systems (GIS) and digital image processing techniques were applied for the treatment of the available data. Supervised and non-supervised classifications were used for data in digital number and reflectance formats and the multitemporal Normalized Difference Vegetation Index (NDVI) images. The objective was to discriminate the tracts with higher probability to become planted with summer crops. Classification accuracies were evaluated using a sampling system developed basically for this study region. The estimated areas were corrected using the error matrix derived from these evaluations. The classification techniques presented an excellent level according to the kappa index. The proportion of crops stratified by municipalities was derived by a field work during the crop growing season. These proportion coefficients were applied onto the area of land to be planted with summer crops (derived from Landsat data). Thus, it was possible to derive the area of each summer crop by the municipality. The discrepancies between official statistics and our results were attributed to the sampling and the stratification procedures. Nevertheless, this methodology can be improved in order to provide good crop area estimates using remote sensing data, despite the cloud cover during the growing season.

Keywords: area intended for summer culture, estimated area planted, agriculture, Landsat, planting schedule

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Authors: Yuta Moriyama, Tsuyoshi Yamazaki, Etsuo Morishita

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Several aerodynamic devices currently attract engineers and research students. The plasma actuator is one of them, and it is very effective to control the flow. The actuator recovers a separated flow to an attached one. The actuator is also inversely applied to a spoiler. The model aircraft might be controlled by this actuator. We develop a model aircraft with the plasma actuator. Another interesting device is the Wells turbine which rotates in one direction. The present authors propose a bicycle with the Wells turbine in the wheels. Power reduction is measured when the turbine is driven by an electric motor at the exit of a wind tunnel. Several Watts power reduction might be possible. This means that the torque of the bike can be augmented by the turbine in the cross wind. These devices are tested in the wind tunnel with a three-component balance and the aerodynamic forces and moment are obtained. In this paper, we introduce these devices and their aerodynamic characteristics. The control force and moment of the plasma actuator are clarified and the power reduction of the bicycle is quantified.

Keywords: aerodynamics, model aircraft, plasma actuator, Wells turbine

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Authors: Djamila Benhaddouche, Abdelkader Benyettou

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In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: biomedical data, learning, classifier, algorithms decision tree, knowledge extraction

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Authors: Chhaya Sharma, Dushyant Kumar

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The present work deals with the treatment of wastewater generated by paper industry by using aluminium as anode material. The quantitative and qualitative analyses of chloropenolics have been carried out by using primary clarifier effluent with the help of gas chromatography mass spectrometry. Sixteen chlorophenolics compounds have been identified and estimated. Results indicated that among 16 identified compounds, 7 are 100% removed and overall 66% reduction in chorophenolics compounds have been detected. Moreover, during the treatment, the biodegradability index of wastewater significantly increases, along with 70 % reduction in chemical oxygen demand and 99 % in color.

Keywords: aluminium anode, chlorophenolics, electrocoagulation, pollution load, wastewater

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Authors: Chong Zhang, Guoming Tang, Bin Ge, Jiuyang Tang

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With the fast growing road traffic and increasingly severe traffic congestion, more and more citizens choose to use the public transportation for daily travelling. Meanwhile, the shared bike provides a convenient option for the first and last mile to the public transit. As of 2016, over one thousand cities around the world have deployed the bike-sharing system. The combination of these two transportations have stimulated the development of each other and made significant contribution to the reduction of carbon footprint. A lot of work has been done on mining the riding behaviors in various bike-sharing systems. Most of them, however, treated the bike-sharing system as an isolated system and thus their results provide little reference for the public transit construction and optimization. In this work, we treat the bike-sharing and public transit as a whole and investigate the customers’ bike-and-ride behaviors. Specifically, we develop a spatio-temporal traffic delivery model to study the riding patterns between the two transportation systems and explore the traffic characteristics (e.g., distributions of customer arrival/departure and traffic peak hours) from the time and space dimensions. During the model construction and evaluation, we make use of large open datasets from real-world bike-sharing systems (the CitiBike in New York, GoBike in San Francisco and BIXI in Montreal) along with corresponding public transit information. The developed two-dimension traffic model, as well as the mined bike-and-ride behaviors, can provide great help to the deployment of next-generation intelligent transportation systems.

Keywords: riding pattern mining, bike-sharing system, public transportation, bike-and-ride behavior

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Authors: Pello Alfonso-Muniozguren, Madeleine Bussemaker, Ralph Chadeesingh, Caryn Jones, David Oakley, Judy Lee, Devendra Saroj

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Current industrialized livestock agriculture is growing every year leading to an increase in the generation of wastewater that varies considerably in terms of organic content and microbial population. Therefore, suitable wastewater treatment methods are required to ensure the wastewater quality meet regulations before discharge. In the present study, a combined lab scale activated sludge-filtration-ozonation system was used to treat a pre-treated abattoir wastewater. A hydraulic retention time of 24 hours and a solid retention time of 13 days were used for the activated sludge process, followed by a filtration step (4-7 µm) and using ozone as tertiary treatment. An average reduction of 93% and 98% was achieved for Chemical Oxygen Demand (COD) and Biological Oxygen Demand (BOD), respectively, obtaining final values of 128 mg/L COD and 12 mg/L BOD. For the Total Suspended Solids (TSS), the average reduction increased to 99% in the same system, reducing the final value down to 3 mg/L. Additionally, 98% reduction in Phosphorus (P) and a complete inactivation of Total Coliforms (TC) was obtained after 17 min ozonation time. For Total Viable Counts (TVC), a drastic reduction was observed with 30 min ozonation time (6 log inactivation) at an ozone dose of 71 mg O3/L. Overall, the combined process was sufficient to meet discharge requirements without further treatment for the measured parameters (COD, BOD, TSS, P, TC, and TVC).

Keywords: abattoir waste water, activated sludge, ozone, waste water treatment

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Authors: S. Khan, A. Khan, Abdul R. Soomrani, Raja F. Zafar, A. Waqas, G. Akbar

Abstract:

This paper proposes a low-complexity image interpolation method. Image interpolation is used to convert a low dimension video/image to high dimension video/image. The objective of a good interpolation method is to upscale an image in such a way that it provides better edge preservation at the cost of very low complexity so that real-time processing of video frames can be made possible. However, low complexity methods tend to provide real-time interpolation at the cost of blurring, jagging and other artifacts due to errors in slope calculation. Non-linear methods, on the other hand, provide better edge preservation, but at the cost of high complexity and hence they can be considered very far from having real-time interpolation. The proposed method is a linear method that uses gradient orientation for slope calculation, unlike conventional linear methods that uses the contrast of nearby pixels. Prewitt edge detection is applied to separate uniform regions and edges. Simple line averaging is applied to unknown uniform regions, whereas unknown edge pixels are interpolated after calculation of slopes using gradient orientations of neighboring known edge pixels. As a post-processing step, bilateral filter is applied to interpolated edge regions in order to enhance the interpolated edges.

Keywords: edge detection, gradient orientation, image upscaling, linear interpolation, slope tracing

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

Abstract:

Due to increasing cost pressure in global markets, artificial intelligence is becoming a technology that is decisive for competition. Predictive quality enables machinery and plant manufacturers to ensure product quality by using data-driven forecasts via machine learning models as a decision-making basis for test results. The use of cross-process Bosch production data along the value chain of hydraulic valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: predictive quality, hydraulics, machine learning, classification, supervised learning

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Authors: Mona Lisa M. Oliveira, Nara A. Policarpo, Ana Luiza B. P. Barros, Carla A. Silva

Abstract:

Selective catalytic reduction systems for nitrogen oxides reduction by ammonia has been the chosen technology by most of diesel vehicle (i.e. bus and truck) manufacturers in Brazil, as also in Europe. Furthermore, at some conditions, over-stoichiometric ammonia availability is also needed that increases the NH₃ slips even more. Ammonia (NH₃) by this vehicle exhaust aftertreatment system provides a maximum efficiency of NOx removal if a significant amount of NH₃ is stored on its catalyst surface. In the other words, the practice shows that slightly less than 100% of the NOx conversion is usually targeted, so that the aqueous urea solution hydrolyzes to NH₃ via other species formation, under relatively low temperatures. This paper presents a model based on neural networks integrated with a road vehicle simulator that allows to estimate NH₃-slip emission factors for different driving conditions and patterns. The proposed model generates high NH₃slips which are not also limited in Brazil, but more efforts needed to be made to elucidate the contribution of vehicle-emitted NH₃ to the urban atmosphere.

Keywords: ammonia slip, neural-network, vehicles emissions, SCR-NOx

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Authors: William Burdick

Abstract:

Manmade climate change is an existential threat that must be mitigated at the earliest opportunity. The role of government in climate change mitigation is enacting and enforcing law and policy to affect substantial reductions in greenhouse gasses, in the short and long term, without substantial increases in the cost of energy. To be optimally effective those laws and policies must be established and enforced based on peer reviewed evidence and scientific facts and result in substantial outcomes in years, not decades. Over the next fifty years, New York’s 2019 Climate Change and Community Protection Act and 2021 All Electric Building Act that mandate replacing natural gas heating systems with heat pumps will, immediately double annual heating costs and by 2075, yield less than 16.2% reduction in CO₂ emissions from heating systems in new housing units, less than a 13% reduction in total CO₂ emissions, and affect a $40B in cumulative additional heating cost, compared to natural gas fueled heating systems.

Keywords: climate change, mandate, heat pump, natural gas

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Authors: Saeed Dehnavi, Zahra Hadadi, Marzieh Rezabeigi, Nader Monirpoor

Abstract:

This study has been performed with the goal of investigating the effectiveness of psychodrama in the reduction of social anxiety among the male adolescents in Kermanshah. 210 adolescents (13-14 year-olds) from four junior high schools in Kermanshah filled Liebowitz Social Anxiety Scale for Children and Adolescents (LSAS-CA) (Masia-Warner, Klien & Liebowitz, 2003). 30 of the adolescents who obtained the highest scores in LSAS-CA scale were chosen as the sample and were randomly assigned as experimental group (15 people) and control group (15 people). The experimental group participated in two-hour sessions of psychodrama twice a week for 6 weeks. The control group received no intervention. The findings of this study showed a significant reduction in the symptoms of social anxiety among the adolescents in experimental group in comparison to that of the control group. Also a three-month follow-up confirmed the stability of the results. Adolescents’ interactions in the psychodrama group, talking about their problems to the group, and achieving appropriate solutions by themselves are the useful factors of this intervention.

Keywords: psychodrama, social anxiety disorder, adolescents, male adolescents

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Authors: Masahiro Miyaji

Abstract:

When a driver happens to be involved in some traffic congestion or after traffic incidents, the driver may fall in a state of anger. State of anger may encounter decisive risk resulting in severer traffic accidents. Preventive safety function using driver’s psychosomatic state with regard to anger may be one of solutions which would avoid that kind of risks. Identifying driver’s anger state is important to create countermeasures to prevent the risk of traffic accidents. As a first step, this research figured out root cause of traffic incidents by means of using Internet survey. From statistical analysis of the survey, dominant psychosomatic states immediately before traffic incidents were haste, distraction, drowsiness and anger. Then, we replicated anger state of a driver while driving, and then, replicated it by means of using driving simulator on bench test basis. Six types of facial expressions including anger were introduced as alternative characteristics. Kohonen neural network was adopted to classify anger state. Then, we created a methodology to detect anger state of a driver in high accuracy. We presented a driving support safety function. The function adapts driver’s anger state in cooperation with an autonomous driving unit to reduce the number of traffic accidents. Consequently, e evaluated reduction rate of driver’s anger in the traffic accident. To validate the estimation results, we referred the reduction rate of Advanced Safety Vehicle (ASV) as well as Intelligent Transportation Systems (ITS).

Keywords: Kohonen neural network, driver’s anger state, reduction of traffic accidents, driver’s state adaptive driving support safety

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Authors: Yi Li, Rui Lu, Lianjun Wang

Abstract:

With the rapid development of chemical industry, the consumption of volatile organic compounds (VOCs) has increased extensively. In the process of VOCs production and application, plenty of them have been transferred to environment. As a result, it has led to pollution problems not only in soil and ground water but also to human beings. Thus, it is important to develop a sensitive and cost-effective analytical method for trace VOCs detection in environment. Surface-enhanced Raman Spectroscopy (SERS), as one of the most sensitive optical analytical technique with rapid response, pinpoint accuracy and noninvasive detection, has been widely used for ultratrace analysis. Based on the plasmon resonance on the nanoscale metallic surface, SERS technology can even detect single molecule due to abundant nanogaps (i.e. 'hot spots') on the nanosubstrate. In this work, a self-supported flexible silver nitrate (AgNO3)/ethylene-propylene copolymer (EPM) hybrid nanofibers was fabricated by electrospinning. After an in-situ chemical reduction using ice-cold sodium borohydride as reduction agent, numerous silver nanoparticles were formed on the nanofiber surface. By adjusting the reduction time and AgNO3 content, the morphology and dimension of silver nanoparticles could be controlled. According to the principles of solid-phase extraction, the hydrophobic substance is more likely to partition into the hydrophobic EPM membrane in an aqueous environment while water and other polar components are excluded from the analytes. By the enrichment of EPM fibers, the number of hydrophobic molecules located on the 'hot spots' generated from criss-crossed nanofibers is greatly increased, which further enhances SERS signal intensity. The as-prepared Ag/EPM hybrid nanofibers were first employed to detect common SERS probe molecule (p-aminothiophenol) with the detection limit down to 10-12 M, which demonstrated an excellent SERS performance. To further study the application of the fabricated substrate for monitoring hydrophobic substance in water, several typical VOCs, such as benzene, toluene and p-xylene, were selected as model compounds. The results showed that the characteristic peaks of these target analytes in the mixed aqueous solution could be distinguished even at a concentration of 10-6 M after multi-peaks gaussian fitting process, including C-H bending (850 cm-1), C-C ring stretching (1581 cm-1, 1600 cm-1) of benzene, C-H bending (844 cm-1 ,1151 cm-1), C-C ring stretching (1001 cm-1), CH3 bending vibration (1377 cm-1) of toluene, C-H bending (829 cm-1), C-C stretching (1614 cm-1) of p-xylene. The SERS substrate has remarkable advantages which combine the enrichment capacity from EPM and the Raman enhancement of Ag nanoparticles. Meanwhile, the huge specific surface area resulted from electrospinning is benificial to increase the number of adsoption sites and promotes 'hot spots' formation. In summary, this work provides powerful potential in rapid, on-site and accurate detection of trace VOCs using a portable Raman.

Keywords: electrospinning, ethylene-propylene copolymer, silver nanoparticles, SERS, VOCs

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