Search results for: human machine interface

Authors: Tetsya Sok, Seong Jae Hong, Young Kyu Kim, Seung Woo Lee

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The temperature distribution for asphalt concrete (AC)-Concrete composite pavement is one of main influencing factor that affects to performance life of pavement. The temperature gradient in concrete slab underneath the AC layer results the critical curling stress and lead to causes de-bonding of AC-Concrete interface. These stresses, when enhanced by repetitive axial loadings, also contribute to the fatigue damage and eventual crack development within the slab. Moreover, the temperature change within concrete slab extremely causes the slab contracts and expands that significantly induces reflective cracking in AC layer. In this paper, the numerical prediction of pavement temperature was investigated using one-dimensional finite different method (FDM) in fully explicit scheme. The numerical predicted model provides a fundamental and clear understanding of heat energy balance including incoming and outgoing thermal energies in addition to dissipated heat in the system. By using the reliable meteorological data for daily air temperature, solar radiation, wind speech and variable pavement surface properties, the predicted pavement temperature profile was validated with the field measured data. Additionally, the effects of AC thickness and daily air temperature on the temperature profile in underlying concrete were also investigated. Based on obtained results, the numerical predicted temperature of AC-Concrete composite pavement using FDM provided a good accuracy compared to field measured data and thicker AC layer significantly insulates the temperature distribution in underlying concrete slab.

Keywords: asphalt concrete, finite different method (FDM), curling effect, heat transfer, solar radiation

Procedia PDF Downloads 254

Authors: Vijayalaxmi Khopade

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The Prima facie caste system is intrinsic to Indian society. It is an ancient system of intense social stratification based upon birth and enjoying religious sanction. The uppermost strata and privileges are ascribed and enjoyed by brahmins (priestly class), while the lowest strata are occupied by Dalits who are not ascribed with any privileges. The caste system is inherently hierarchical, patriarchal, and systematic and thrives solely on exploitation justified through means of the Brahminical system of hegemony based singularly on birth. The caste system has extended its tentacles to other religions like Christianity, Buddhism, Jainism, and Islam in South Asia. Term Dalit is colloquially used to categorize persons belonging to lower strata in the caste hierarchy. However, this category is heterogenous and highly stratified, following practices like untouchability and exclusion amongst themselves. The modern Indian legal system acknowledges the existence of Caste and its perils. Therefore, by virtue of the Indian Constitution, provisions for affirmative action for the protection and development of Dalits are made. Courts in India have liberally interpreted laws to benefit Dalits. However, the modern system of governance is not immune from Caste based biases. These biases are reflected in the implementation of governance, including the dispensation of justice. The economic reforms of the 1990s gave a huge boost to the Indian diaspora. Persons of Indian origin are now seen making great strides in almost every sector and enjoying positions of power globally. As one peels off the layer of ethnic Indian origin, a deep seated layer of Caste and Caste based patriarchy is clearly visible. Indian diaspora enjoying positions of power essentially belongs to upper castes and carry Caste based biases with them. These castes have long enjoyed the benefits of education; therefore, they were the first ones to benefit from LPG (Liberalization, Privatization, Globalization) model adopted in the 1990s. Dalits, however, had little formal education until recently. The western legal system, to the best of our knowledge, does not recognize Caste and, therefore, cannot afford protection for Dalits, wherein discrimination and exploitation take place solely on the basis of Caste. Therefore, Dalits are left with no legal remedy outside domestic jurisdiction. Countries like the UK have made an attempt to include Caste in their Equality Bill 2010. This has met with tough resistance from Upper caste Hindus who shy away from recognizing their caste privileges and, therefore, the existence of Caste. In this paper, an attempt for comparative analysis is made between various legal protections accorded to Dalits in India vis-à-vis international human rights as protected by the United Nations under its declaration of Universal Human rights. An attempt has been made to mark a distinction between race and Caste and to establish a position of women in Caste based hierarchy. The paper also makes an argument for the inclusion of atrocities committed against Dalits as a violation of international human rights, their protection by the United Nations, and the trial of their violations by International Courts. The paper puts into perspective the need for an external agency like the United Nations and International courts to interfere in rights guaranteed by the Indian Constitution, even with the existence of a modern legal system in a sovereign democratic country.

Keywords: atrocity, caste, diaspora, legal framework

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Authors: M. M. Tawfik, Ezzat M. Abd El Lateef, B. B. Mekki, Amany A. Bahr, Magda H. Mohamed, Gehan S. Bakhoom

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The rapid increase in the world’s population coupled by decrease the arable land per capita has resulted into an increased demand for food which has in turn led to the production of large amounts of agricultural wastes, both at the farmer, municipality and city levels. Agricultural wastes can be a valuable resource for improving food security. Unfortunately, agricultural wastes are likely to cause pollution to the environment or even harm to human health. This calls for increased public awareness on the benefits and potential hazards of agricultural wastes, especially in developing countries. Agricultural wastes (residual stalks, straw, leaves, roots, husks, shells etcetera) and animal waste (manures) are widely available, renewable and virtually free, hence they can be an important resource. They can be converted into heat, steam, charcoal, methanol, ethanol, bio diesel as well as raw materials (animal feed, composting, energy and biogas construction etcetera). agricultural wastes are likely to cause pollution to the environment or even harm to human health, if it is not used in a sustainable manner. Organic wastes could be considered an important source of biofertilizer for enhancing food security in the small holder farming communities that would not afford use of expensive inorganic fertilizers. Moreover, these organic wastes contain high levels of nitrogen, phosphorus, potassium, and organic matter important for improving nutrient status of soils in urban agriculture. Organic compost leading to improved crop yields and its nutritional values as compared with inorganic fertilization. This paper briefly reviews how agricultural wastes can be used to enhance food security and conserve the environment.

Keywords: agricultural waste, organic compost, environment, valuable resources

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Authors: Masoud Irannezhad, Sirpa Rasmus, Saghar Ahmadian, Deliang Chen, Bjorn Klove

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Variability and changes in thermal conditions play a crucial role in functioning of human society, particularly over cold climate regions like Finland. Accordingly, the frost-free season (FFS) parameters in terms of start (FFSS), end (FFSE) and length (FFSL) have substantial effects not only on natural environment (e.g. flora and fauna), but also on human requirements (e.g. agriculture, forestry and energy generation). Applying the 0°C threshold of minimum temperature (Tmin), the FFS was defined as the period between the last spring frost as FFSS and the first fall frost as FFSE. For this study, gridded (10 x 10 km2) daily minimum temperature datasets throughout Finland during 1961-2011 was used to investigate recent spatio-temporal variations and trends in frost-free season (FFS) parameters and their relationships with the well-known large-scale climate teleconnections (CTs). The FFS in Finland naturally increases from north (~60 days) to south (~190 days), in association with earlier FFSS (~24 April) and later FFSE (~30 October). Statistically significant (p<0.05) trends in FFSL were all positive (increasing) ranged between 0 and 13.5 (days/decade) and mainly observed in the east, upper west, centre and upper north of Finland. Such lengthening trends in FFS were attributable to both earlier FFSS and later FFSE mostly over central and upper northern Finland, while only to later FFSE in eastern and upper western parts. Variations in both FFSL and FFSS were significantly associated with the Polar (POL) pattern over northern Finland, while with the East Atlantic (EA) pattern over eastern and upper western areas. However, the POL and Scandinavia (SCA) patterns were most influential CTs for FFSE variability over northern Finland.

Keywords: climate teleconnections, Finland, frost-free season, trend analysis

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Authors: Danish Idrees, Vijay Kumar, Samudrala Gourinath

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Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease caused by misfolding and aggregation of Cu, Zn superoxide dismutase (SOD1). The use of small molecules has been shown to stabilize the SOD1 dimer and preventing its dissociation and aggregation. In this study, we employed molecular docking, molecular dynamics simulation and surface plasmon resonance (SPR) to study the interactions between SOD1 and natural polyphenolic compounds. In order to explore the noncovalent interaction between SOD1 and natural polyphenolic compounds, molecular docking and molecular dynamic (MD) simulations were employed to gain insights into the binding modes and free energies of SOD1-polyphenolic compounds. MM/PBSA methods were used to calculate free energies from obtained MD trajectories. The compounds, Hesperidin, Ergosterol, and Rutin showed the excellent binding affinity in micromolar range with SOD1. Ergosterol and Hesperidin have the strongest binding affinity to SOD1 and was subjected to further characterization. Biophysical experiments using Circular Dichroism and Thioflavin T fluorescence spectroscopy results show that the binding of these two compounds can stabilize SOD1 dimer and inhibit the aggregation of SOD1. Molecular simulation results also suggest that these compounds reduce the dissociation of SOD1 dimers through direct interaction with the dimer interface. This study will be helpful to develop other drug-like molecules which may have the effect to reduce the aggregation of SOD1.

Keywords: amyotrophic lateral sclerosis, molecular dynamics simulation, surface plasmon resonance, superoxide dismutase

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Authors: Raffaella Sesana, Nazanin Sheibanian, Luca Corsaro, Sedat Özbilen, Rocco Lupoi, Francesco Artusio

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High Entropy Alloy (HEA) coatings of Al0.1-0.5CoCrCuFeNi and MnCoCrCuFeNi on Mg substrates were prepared from mechanically alloyed HEA powder feedstocks and at three different Cold Spray (CS) process gas (N2) temperatures (650, 750 and 850°C). Mechanically alloyed and cold-sprayed HEA coatings were characterized by macro photography, OM, SEM+EDS study, micro-hardness testing, roughness, and porosity measurements. As a result of mechanical alloying (MA), harder particles are deformed and fractured. The particles in the Cu-rich region were coarser and more globular than those in the A1 phase, which is relatively soft and ductile. In addition to the A1 particles, there were some separate Cu-rich regions. Due to the brittle nature of the powder and the acicular shape, Mn-HEA powder exhibited a different trend with smaller particle sizes. It is observed that MA results in a loose structure characterized by many gaps, cracks, signs of plastic deformation, and small particles attached to the surface of the particle. Considering the experimental results obtained, it is not possible to conclude that the chemical composition of the high entropy alloy influences the roughness of the coating. It has been observed that the deposited volume increases with temperature only in the case of Al0.1 and Mg-based HEA, while for the rest of the Al-based HEA, there are no noticeable changes. There is a direct correlation between micro-hardness and the chemical composition of a coating: the micro-hardness of a coating increases as the percentage of aluminum increases in the sample. Compared to the substrate, the coating has a much higher hardness, and the hardness measured at the interface is intermediate.

Keywords: characterisation, cold spraying, HEA coatings, SEM+EDS

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Authors: Baldev Ram Khandoliyan, Ram Kishor

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India has a classical tradition of Sanskrit Lexicons. Research work has been done on the study of Indian lexicography. India has seen amazing strides in Information and Communication Technology (ICT) applications for Indian languages in general and for Sanskrit in particular. Since Machine Translation from Sanskrit to other Indian languages is often the desired goal, traditional Sanskrit lexicography has attracted a lot of attention from the ICT and Computational Linguistics community. From Nighaŋţu and Nirukta to Amarakośa and Medinīkośa, Sanskrit owns a rich history of lexicography. As these kośas do not follow the same typology or standard in the selection and arrangement of the words and the information related to them, several types of Kośa-styles have emerged in this tradition. The model of a grammar given by Aṣṭādhyāyī is well appreciated by Indian and western linguists and grammarians. But the different models provided by lexicographic tradition also have importance. The general usefulness of Sanskrit traditional Kośas is well discussed by some scholars. That is most of the matter made available in the text. Some also have discussed the good arrangement of lexica. This paper aims to discuss some more use of the different models of Sanskrit lexicography especially focusing on its computational modeling and its use in different computational operations.

Keywords: computational lexicography, Sanskrit Lexicons, nighanṭu, kośa, Amarkosa

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Authors: Ahmed M. Gamal, Adel M. Belal, S. A. Elsoud

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This article aims to study the effect of reinforcement inclusions (geogrids) on the sand dunes bearing capacity under strip footings. In this research experimental physical model was carried out to study the effect of the first geogrid reinforcement depth (u/B), the spacing between the reinforcement (h/B) and its extension relative to the footing length (L/B) on the mobilized bearing capacity. This paper presents the numerical modeling using the commercial finite element package (PLAXIS version 8.2) to simulate the laboratory physical model, studying the same parameters previously handled in the experimental work (u/B, L/B & h/B) for the purpose of validation. In this study the soil, the geogrid, the interface element and the boundary condition are discussed with a set of finite element results and the validation. Then the validated FEM used for studying real material and dimensions of strip foundation. Based on the experimental and numerical investigation results, a significant increase in the bearing capacity of footings has occurred due to an appropriate location of the inclusions in sand. The optimum embedment depth of the first reinforcement layer (u/B) is equal to 0.25. The optimum spacing between each successive reinforcement layer (h/B) is equal to 0.75 B. The optimum Length of the reinforcement layer (L/B) is equal to 7.5 B. The optimum number of reinforcement is equal to 4 layers. The study showed a directly proportional relation between the number of reinforcement layer and the Bearing Capacity Ratio BCR, and an inversely proportional relation between the footing width and the BCR.

Keywords: reinforced soil, geogrid, sand dunes, bearing capacity

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Authors: Sikiru Oluwarotimi Ismail, Hom Nath Dhakal, Anish Roy, Dong Wang, Ivan Popov

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The ultrasonically-assisted drilling (UAD) is a non-traditional technique which involves the superimposition of a high frequency and low amplitude vibration, usually greater than 18kHz and less than 20µm respectively, on a drill bit along the feed direction. UAD has remarkable advantages over the conventional drilling (CD), especially the high drilling-force reduction. Force reduction improves the quality of the drilled holes, reduces power consumption rate and cost of production. Nevertheless, in addition to the setbacks of UAD including expensiveness of set-up, unpredicted results and chipping effects, this paper presents the problems of insignificant force reduction and poor surface quality during UAD of hemp fibre-reinforced composites (HFRCs), a natural composite, with polycaprolactone (PCL) matrix. The experimental results obtained depict that HFRCs/PCL samples have more burnt chip-materials attached on the drilled holes during UAD than CD. This effect produced a very high surface roughness (Ra), up to 13µm. In a bid to reduce these challenges, different drilling parameters (feed rates and cutting speeds, frequencies and amplitudes for UAD), conditions (dry machining and airflow cooling) and diameters of drill bits (3mm and 6mm of high speed steel), as well as HFRCs/PCL samples of various fibre aspect ratios, including 0 (neat), 19, 26, 30 and 38 have been used. However, the setbacks still persisted. Evidently, the benefits of UAD are not obtainable for the drilling of the HFRCs/PCL laminates. These problems occurred due to the 60 °C melting temperature of PCL, quite lower than 56-90.2 °C and 265–290.8 °C composite-tool interface temperature during CD and UAD respectively.

Keywords: force reduction, hemp fibre-reinforced composites, ultrasonically-assisted drilling, surface quality

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Authors: Sandeep Singh Sandhua, Karanvir Singh Ghuman, Arun Kumar

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Stellite 21 is cobalt based super alloy used in improving the wear performance of stainless steel engineering components subjected to harsh environmental conditions. This piece of research focuses on the wear analysis of satellite 21 cladded on AISI 304 L substrate using SMAW process. Bead on plate experiments were carried out by varying current and electrode manipulation techniques to optimize the dilution and microhardness. 80 Amp current and weaving technique was found to be optimum set of parameters for overlaying which were further used for multipass multilayer cladding of AISI 304 L substrate. The wear performance was examined on pin on dics wear testing machine under room temperature conditions. The results from this study show that Stellite 21 overlays show a significant improvement in the frictional wear resistance after TIG remelting. It is also established that low dilution procedures are important in controlling the metallurgical composition of these overlays which has a consequent effect in enhancing hardness and wear resistance of these overlays.

Keywords: surfacing, stellite 21, dilution, SMAW, frictional wear, micro-hardness

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Authors: Abdul Basit Kiani, Maryam Kiani

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Content Management Systems (CMS) have transformed the landscape of web development by providing an accessible and efficient platform for creating and managing digital content. This abstract explores the key features and benefits of CMS in web development, highlighting its impact on website creation and maintenance. CMS offers a user-friendly interface that empowers individuals to create, edit, and publish content without requiring extensive technical knowledge. With customizable templates and themes, users can personalize the design and layout of their websites, ensuring a visually appealing online presence. Furthermore, CMS facilitates efficient content organization through categorization and tagging, enabling visitors to navigate and search for information effortlessly. It also supports version control, allowing users to track and manage revisions effectively. Scalability is a notable advantage of CMS, as it offers a wide range of plugins and extensions to integrate additional features into websites. From e-commerce functionality to social media integration, CMS adapts to evolving business needs. Additionally, CMS enhances collaborative workflows by allowing multiple user roles and permissions. This enables teams to collaborate effectively on content creation and management, streamlining processes and ensuring smooth coordination. In conclusion, CMS serves as a powerful tool in web development, simplifying content creation, customization, organization, scalability, and collaboration. With CMS, individuals and businesses can create dynamic and engaging websites, establishing a strong online presence with ease.

Keywords: web development, content management systems, information technology, programming

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Authors: Junjie Peng, Jinbao Chen, Shuai Kong, Danxu Liu

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On the basis of traditional resource allocation strategies, the usage of resources on physical servers in cloud data center is great uncertain. It will cause waste of resources if the assignment of tasks is not enough. On the contrary, it will cause overload if the assignment of tasks is too much. This is especially obvious when the applications are the same type because of its resource preferences. Considering CPU intensive application is one of the most common types of application in the cloud, we studied the optimization strategy for CPU intensive applications on the same server. We used resource preferences to analyze the case that multiple CPU intensive applications run simultaneously, and put forward a model which can predict the execution time for CPU intensive applications which run simultaneously. Based on the prediction model, we proposed the method to select the appropriate number of applications for a machine. Experiments show that the model can predict the execution time accurately for CPU intensive applications. To improve the execution efficiency of applications, we propose a scheduling model based on priority for CPU intensive applications. Extensive experiments verify the validity of the scheduling model.

Keywords: cloud computing, CPU intensive applications, resource optimization, strategy

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Authors: Vivian Guo, Yan Qu

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Online marketplaces are not only digital places where consumers buy and sell merchandise, and they are also destinations for brands to connect with real consumers at the moment when customers are in the shopping mindset. For many marketplaces, brands have been important partners through advertising. There can be, however, a risk of advertising impacting a consumer’s shopping journey if it hurts the use experience or takes the user away from the site. Both could lead to the loss of transaction revenue for the marketplace. In this paper, we present user-based methods for cannibalization control by selectively turning off ads to users who are likely to be cannibalized by ads subject to business objectives. We present ways of measuring cannibalization of advertising in the context of an online marketplace and propose novel ways of measuring cannibalization through purchase propensity and uplift modeling. A/B testing has shown that our methods can significantly improve user purchase and engagement metrics while operating within business objectives. To our knowledge, this is the first paper that addresses cannibalization mitigation at the user-level in the context of advertising.

Keywords: cannibalization, machine learning, online marketplace, revenue optimization, yield optimization

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Authors: Yasam Palguna, Rajesh Korla

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The efficiency of thermally operated systems can be improved by increasing the operating temperature, thereby decreasing the fuel consumption and carbon footprint. Hence, there is a continuous need for replacing the existing materials with new alloys with higher temperature working capabilities. During the last decade, multi principal element alloys, commonly known as high entropy alloys are getting more attention because of their superior high temperature strength along with good high temperature corrosion and oxidation resistance, The present work focused on the microstructure and high temperature tensile behavior of Al0.2CoCrFeNiMo0.5 high entropy alloy (HEA). Wrought Al0.2CoCrFeNiMo0.5 high entropy alloy, produced by vacuum induction melting followed by thermomechanical processing, is tested in the temperature range of 200 to 900oC. It is exhibiting very good resistance to softening with increasing temperature up to 700oC, and thereafter there is a rapid decrease in the strength, especially beyond 800oC, which may be due to simultaneous occurrence of recrystallization and precipitate coarsening. Further, it is exhibiting superplastic kind of behavior with a uniform elongation of ~ 275 % at 900 oC temperature and 1 x 10-3 s-1 strain rate, which may be due to the presence of fine stable equi-axed grains. Strain rate sensitivity of 0.3 was observed, suggesting that solute drag dislocation glide might be the active mechanism during superplastic kind of deformation. Post deformation microstructure suggesting that cavitation at the sigma phase-matrix interface is the failure mechanism during high temperature deformation. Finally, high temperature properties of the present alloy will be compared with the contemporary high temperature materials such as ferritic, austenitic steels, and superalloys.

Keywords: high entropy alloy, high temperature deformation, super plasticity, post-deformation microstructures

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Authors: Khalid Ahmed Eldwaib

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In this study, Al-Mg alloy 5052 was used as the testing material. Corrosion fatigue life was studied for the alloy in 3.5% NaCl (pH=1, 3, 5, 7, 9, and 11), and 3.5% NaCl (pH=1) with inhibitors. The compound inhibitors were composed mainly of phosphate (PO4³-), adding a certain proportion of other nontoxic inhibitors so as to select alternatives to environmentally hazardous chromate (Cr2O7²-). The inhibitors were sodium dichromate Na2Cr2O7, sodium phosphate Na3PO4, sodium molybdate Na2MoO4, and sodium citrate Na3C6H5O7. The total amount of inhibiting pigments was at different concentrations (250,500,750, and 1000 ppm) in the solutions. Corrosion fatigue behavior was studied by using plane-bending corrosion fatigue machine with stress ratio R=0.5 and under the constant frequency of 13.3 Hz. Results show that in 3.5% NaCl the highest fatigue life (number of cycles to failure Nf) is obtained at pH=5 where the oxide film on aluminum has very low solubility, and the lowest number of cycles is obtained at pH=1, where the media is too aggressive (extremely acidic). When the concentration of inhibitor increases the cycles to failure increase. The surface morphology and fracture section of the specimens had been characterized through scanning electron microscope (SEM).

Keywords: Al-Mg alloy 5052, corrosion, fatigue, inhibitors

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Authors: Hong Lu, Wei Fan, Yongquan Zhang, Junbo Zhang

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A cross coupling sliding synchronization control strategy is proposed for the dual-driving feed system. This technology will minimize the position error oscillation and achieve the precise synchronization performance in the high speed and high precision drive system, especially some high speed and high precision machine. Moreover, a cross coupling compensation matrix is provided to offset the mismatched disturbance and the disturbance observer is established to eliminate the chattering phenomenon. Performance comparisons of proposed dual-driving cross coupling sliding mode control (CCSMC), normal cross coupling control （CCC） strategy with PID control, and electronic virtual main shaft control (EVMSC) strategy with SMC control are investigated by simulation and a dual-driving control system; the results show the effectiveness of the proposed control scheme.

Keywords: cross coupling matrix, dual motors, synchronization control, sliding mode control

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Authors: D. Glamowska, K. Szymkowska, K. Mojsiewicz- Pieńkowska, K. Cal, Z. Jankowski

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Introduction: The integrity of the outermost layer of skin (stratum corneum) is vital to the penetration of various compounds, including toxic substances. Barrier function of skin depends of its structure. The barrier function of the stratum corneum is provided by patterned lipid lamellae (binlayer). However, a lot of substances, including the low molecular methyl siloxanes (volatile methyl siloxanes, VMS) have an impact on alteration the skin barrier due to damage of stratum corneum structure. VMS belong to silicones. They are widely used in the pharmaceutical as well as cosmetic industry. Silicones fulfill the role of ingredient or excipient in medicinal products and the excipient in personal care products. Due to the significant human exposure to this group of compounds, an important aspect is toxicology of the compounds and safety assessment of products. Silicones in general opinion are considered as a non-toxic substances, but there are some data about their negative effect on living organisms through the inhaled or oral application. However, the transdermal route has not been described in the literature as a possible alternative route of penetration. The aim of the study was to verify the possibility of penetration of the stratum corneum, further permeation into the deeper layers of the skin (epidermis and dermis) as well as to the fluid acceptor by VMS. Methods: Research methodology was developed based on the OECD and WHO guidelines. In ex-vivo study, the fluorescence microscope and ATR FT-IR spectroscopy was used. The Franz- type diffusion cells were used to application of the VMS on the sample of human skin (A=0.65 cm) for 24h. The stratum corneum at the application site was tape-stripped. After separation of epidermis, relevant dyes: fluorescein, sulforhodamine B, rhodamine B hexyl ester were put on and observations were carried in the microscope. To confirm the penetration and permeation of the cyclic or linear VMS and thus the presence of silicone in the individual layers of the skin, spectra ATR FT-IR of the sample after application of silicone and H2O (control sample) were recorded. The research included comparison of the intesity of bands in characteristic positions for silicones (1263 cm-1, 1052 cm-1 and 800 cm-1). Results: and Conclusions The results present that cyclic and linear VMS are able to overcome the barrier of the skin. Influence of them on damage of corneocytes of the stratum corneum was observed. This phenomenon was due to distinct disturbances in the lipid structure of the stratum corneum. The presence of cyclic and linear VMS were identified in the stratum corneum, epidermis as well as in the dermis by both fluorescence microscope and ATR FT-IR spectroscopy. This confirms that the cyclic and linear VMS can penetrate to stratum corneum and permeate through the human skin layers. Apart from this they cause changes in the structure of the skin. Results show to possible absorption into the blood and lymphathic vessels by the VMS with linear and cyclic structure.

Keywords: low molecular methyl siloxanes, volatile methyl siloxanes, linear and cyclic siloxanes, skin penetration, skin permeation

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Authors: Jia Xin Low, Keng Wah Choo

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This paper presents an automatic normal and abnormal heart sound classification model developed based on deep learning algorithm. MITHSDB heart sounds datasets obtained from the 2016 PhysioNet/Computing in Cardiology Challenge database were used in this research with the assumption that the electrocardiograms (ECG) were recorded simultaneously with the heart sounds (phonocardiogram, PCG). The PCG time series are segmented per heart beat, and each sub-segment is converted to form a square intensity matrix, and classified using convolutional neural network (CNN) models. This approach removes the need to provide classification features for the supervised machine learning algorithm. Instead, the features are determined automatically through training, from the time series provided. The result proves that the prediction model is able to provide reasonable and comparable classification accuracy despite simple implementation. This approach can be used for real-time classification of heart sounds in Internet of Medical Things (IoMT), e.g. remote monitoring applications of PCG signal.

Keywords: convolutional neural network, discrete wavelet transform, deep learning, heart sound classification

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Authors: S. B. Mayil Vealan, C. Sekar

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Bisphenol A (BIS A) and 4 Nitrophenol (4N) are the most prevalent environmental endocrine-disrupting chemicals which mimic hormones and have a direct relationship to the development and growth of animal and human reproductive systems. Moreover, intensive exposure to the compound is related to prostate and breast cancer, infertility, obesity, and diabetes. Hence, accurate and reliable determination techniques are crucial for preventing human exposure to these harmful chemicals. Lanthanum Copper Oxide (La₂Cu₂O₅) nanoparticles were synthesized and investigated through various techniques such as scanning electron microscopy, high-resolution transmission electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, and electrochemical impedance spectroscopy. Cyclic voltammetry and square wave voltammetry techniques are employed to evaluate the electrochemical behavior of as-synthesized samples toward the electrochemical detection of Bisphenol A and 4-Nitrophenol. Under the optimal conditions, the oxidation current increased linearly with increasing the concentration of BIS A and 4-N in the range of 0.01 to 600 μM with a detection limit of 2.44 nM and 3.8 nM. These are the lowest limits of detection and the widest linear ranges in the literature for this determination. The method was applied to the simultaneous determination of BIS A and 4-N in real samples (food packing materials and river water) with excellent recovery values ranging from 95% to 99%. Better stability, sensitivity, selectivity and reproducibility, fast response, and ease of preparation made the sensor well-suitable for the simultaneous determination of bisphenol and 4 Nitrophenol. To the best of our knowledge, this is the first report in which La₂Cu₂O₅ nano particles were used as efficient electron mediators for the fabrication of endocrine disruptor (BIS A and 4N) chemical sensors.

Keywords: endocrine disruptors, electrochemical sensor, Food contacting materials, lanthanum cuprates, nanomaterials

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Authors: Amal Alshahrani, Allan Ramsay

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Paraphrasing is one of the important tasks in natural language processing; i.e. alternative ways to express the same concept by using different words or phrases. Paraphrases can be used in many natural language applications, such as Information Retrieval, Machine Translation, Question Answering, Text Summarization, or Information Extraction. To obtain pairs of sentences that are paraphrases we create a system that automatically extracts paraphrases from a corpus, which is built from different sources of news article since these are likely to contain paraphrases when they report the same event on the same day. There are existing simple standard approaches (e.g. TF-IDF vector space, cosine similarity) and alignment technique (e.g. Dynamic Time Warping (DTW)) for extracting paraphrase which have been applied to the English. However, the performance of these approaches could be affected when they are applied to another language, for instance Arabic language, due to the presence of phenomena which are not present in English, such as Free Word Order, Zero copula, and Pro-dropping. These phenomena will affect the performance of these algorithms. Thus, if we can analysis how the existing algorithms for English fail for Arabic then we can find a solution for Arabic. The results are promising.

Keywords: natural language processing, TF-IDF, cosine similarity, dynamic time warping (DTW)

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Authors: Jana Atteah, Wid Jan, Yara AlHibshi, Rahaf AlRougi

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Anyword is an AI copywriting tool that helps marketers create effective campaigns for specific audiences. It offers a wide range of templates for various platforms, brand voice guidelines, and valuable analytics insights. Anyword is used by top global companies and has been recognized as one of the "Fastest Growing Products" in the 2023 software awards. A recent study examined the utilization and impact of AI-powered writing tools, specifically focusing on the adoption of AI in writing pursuits and the use of the Anyword platform. The results indicate that a majority of respondents (52.17%) had not previously used Anyword, but those who had were generally satisfied with the platform. Notable productivity improvements were observed among 13% of the participants, while an additional 34.8% reported a slight increase in productivity. A majority (47.8%) maintained a neutral stance, suggesting that their productivity remained unaffected. Only a minimal percentage (4.3%) claimed that their productivity did not improve with the usage of Anyword AI. In terms of the quality of written content generated, the participants responded positively. Approximately 91% of participants gave Anyword AI a score of 5 or higher, with roughly 17% giving it a perfect score. A small percentage (approximately 9%) gave a low score between 0-2. The mode result was a score of 7, indicating a generally positive perception of the quality of content generated using Anyword AI. These findings suggest that AI can contribute to increased productivity and positively influence the quality of written content. Further research and exploration of AI tools in writing pursuits are warranted to fully understand their potential and limitations.

Keywords: artificial intelligence, marketing platforms, productivity, user interface

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Authors: Tathiana Yesenia Coy Mondragón, Jossitt William Vargas Cruz, Cristian Leonardo Gutiérrez Gómez

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The study of cosmic rays is based on two fundamental pillars: the detection of secondary cosmic rays on the Earth's surface and the detection of the source and origin of the cascade. In addition, the constant flow of RC generates a lot of interest for study due to the incidence of various natural phenomena, which makes it relevant to characterize their incidence parameters to determine their effect not only at subsoil or terrestrial surface levels but also throughout the atmosphere. To determine the physical parameters of the primary cosmic ray, the implementation of robust algorithms capable of reconstructing the cascade from the measured values is required, with a high level of reliability. Therefore, it is proposed to build a machine learning system that will be fed from the cosmic ray simulations in CORSIKA at different energies that lie in a range [10⁹-10¹²] eV. in order to generate a trained particle and pattern recognition system to obtain greater efficiency when inferring the nature of the origin of the cascade for EAS in the atmosphere considering atmospheric models.

Keywords: CORSIKA, cosmic rays, eas, Colombia

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Authors: K. Rumchev, S. Gilbey

Abstract:

Airborne particulate matter is a known hazard to human health, with a considerable body of evidence linking agricultural dust exposures to adverse human health effects in exposed populations. It is also known that agricultural workers are exposed to high levels of soil dust and other types of airborne particulate matter within the farming environment. The aim of this study was to examine exposure to agricultural dust among farm workers during the seeding season. Twenty-one wheat-belt farms consented to participate in the study with 30 workers being monitored for dust exposure whilst seeding or undertaking seeding associated tasks. Each farm was visited once and farmers’ were asked to wear a personal air sampler for a 4-hour sampling period. Simultaneous, real-time, tractor cabin air quality monitoring was also undertaken. Data for this study was collected using real-time aerosol dust monitors to determine in-tractor cabin PM exposure to five size fractions (total, PM10, respirable, PM2.5 and PM1), and personal sampling was undertaken to establish individual exposure to inhalable and respirable dust concentrations. The study established a significant difference between personal exposures and simultaneous real-time in-cabin exposures for both inhalable and respirable fractions. No significant difference was shown between in-cabin and personal inhalable dust concentrations during seeding and spraying tasks, although both in-cabin and personal concentrations were two times greater for seeding than spraying. Future research should focus on educating and providing farm owners and workers with more information on adopting safe work practices to minimise harmful exposures to agricultural dust.

Keywords: agriculture, air quality, Australia, particulate matter

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Authors: Mohieddine Benghersallah, Mohamed Zakaria Zahaf, Ali Medjber, Idriss Tibakh

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The objective of this study is to analyse the effects of cutting parameters on surface roughness in dry face milling using statistical techniques. We studied the effect of the microstructure of AISI 52100 steel on machinability before and after hardening. The machining tests were carried out on a high rigidity vertical milling machine with a 25 mm diameter face milling cutter equipped with micro-grain bicarbide inserts with PVD (Ti, AlN) coating in GC1030 grade. A Taguchi L9 experiment plan is adopted. Analysis of variance (ANOVA) was used to determine the effects of cutting parameters (Vc, fz, ap) on the roughness (Ra) of the machined surface. Regression analysis to assess the machinability of steel presented mathematical models of roughness and the combination of parameters to minimize it. The recorded results show that feed per tooth has the most significant effect on the surface condition for both steel treatment conditions. The best roughnesses were obtained for the hardened AISI 52100 steel.

Keywords: machinability, heat treatment, microstructure, surface roughness, Taguchi method

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Authors: Uma Maheshwari V., Rajanikanth Aluvalu, Kumar Gautam

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The COVID-19 disease is a highly contagious viral infection with major worldwide health implications. The global economy suffers as a result of COVID. The spread of this pandemic disease can be slowed if positive patients are found early. COVID-19 disease prediction is beneficial for identifying patients' health problems that are at risk for COVID. Deep learning and machine learning algorithms for COVID prediction using X-rays have the potential to be extremely useful in solving the scarcity of doctors and clinicians in remote places. In this paper, a convolutional neural network (CNN) with deep layers is presented for recognizing COVID-19 patients using real-world datasets. We gathered around 6000 X-ray scan images from various sources and split them into two categories: normal and COVID-impacted. Our model examines chest X-ray images to recognize such patients. Because X-rays are commonly available and affordable, our findings show that X-ray analysis is effective in COVID diagnosis. The predictions performed well, with an average accuracy of 99% on training photographs and 88% on X-ray test images.

Keywords: deep CNN, COVID–19 analysis, feature extraction, feature map, accuracy

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Authors: Zhuo Job Chen, Kevin Nute

Abstract:

The work reported examines potential linkages between spatial and temporal prospects, and more specifically, between variations in the spatial depth and foreground obstruction of window views, and observers’ sense of connection to the future. It was found that external views from indoor spaces were strongly associated with a sense of the future, that partially obstructing such a view with foreground objects significantly reduced its association with the future, and replacing it with a pictorial representation of the same scene (with no real actual depth) removed most of its temporal association. A lesser change in the spatial depth of the view, however, had no apparent effect on association with the future. While the role of spatial depth has still to be confirmed, the results suggest that spatial prospects directly affect temporal ones. The word “prospect” typifies the overlapping of the spatial and temporal in most human languages. It originated in classical times as a purely spatial term, but in the 16th century took on the additional temporal implication of an imagined view ahead, of the future. The psychological notion of prospection, then, has its distant origins in a spatial analogue. While it is not yet proven that space directly structures our processing of time at a physiological level, it is generally agreed that it commonly does so conceptually. The mental representation of possible futures has been a central part of human survival as a species (Boyer, 2008; Suddendorf & Corballis, 2007). A sense of the future seems critical not only practically, but also psychologically. It has been suggested, for example, that lack of a positive image of the future may be an important contributing cause of depression (Beck, 1974; Seligman, 2016). Most people in the developed world now spend more than 90% of their lives indoors. So any direct link between external views and temporal prospects could have important implications for both human well-being and building design. We found that the ability to see what lies in front of us spatially was strongly associated with a sense of what lies ahead temporally. Partial obstruction of a view was found to significantly reduce that sense connection to the future. Replacing a view with a flat pictorial representation of the same scene removed almost all of its connection with the future, but changing the spatial depth of a real view appeared to have no significant effect. While foreground obstructions were found to reduce subjects’ sense of connection to the future, they increased their sense of refuge and security. Consistent with Prospect and Refuge theory, an ideal environment, then, would seem to be one in which we can “see without being seen” (Lorenz, 1952), specifically one that conceals us frontally from others, without restricting our own view. It is suggested that these optimal conditions might be translated architecturally as screens, the apertures of which are large enough for a building occupant to see through unobstructed from close by, but small enough to conceal them from the view of someone looking from a distance outside.

Keywords: foreground obstructions, prospection, spatial depth, window views

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Authors: Vesile Evrim, Aliyu Awwal

Abstract:

By the evolvement in technology, the way of expressing opinions switched the direction to the digital world. The domain of politics as one of the hottest topics of opinion mining research merged together with the behavior analysis for affiliation determination in text which constitutes the subject of this paper. This study aims to classify the text in news/blogs either as Republican or Democrat with the minimum number of features. As an initial set, 68 features which 64 are constituted by Linguistic Inquiry and Word Count (LIWC) features are tested against 14 benchmark classification algorithms. In the later experiments, the dimensions of the feature vector reduced based on the 7 feature selection algorithms. The results show that Decision Tree, Rule Induction and M5 Rule classifiers when used with SVM and IGR feature selection algorithms performed the best up to 82.5% accuracy on a given dataset. Further tests on a single feature and the linguistic based feature sets showed the similar results. The feature “function” as an aggregate feature of the linguistic category, is obtained as the most differentiating feature among the 68 features with 81% accuracy by itself in classifying articles either as Republican or Democrat.

Keywords: feature selection, LIWC, machine learning, politics

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Authors: Takuro Kida, Yuichi Kida

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We show a base of the new trend of algorithm mathematically that treats a historical reason of continuous discrimination in the world as well as its solution by introducing new concepts of parallel world that includes an invisible set of errors as its companion. With respect to a matrix operator-filter bank that the matrix operator-analysis-filter bank H and the matrix operator-sampling-filter bank S are given, firstly, we introduce the detailed algorithm to derive the optimum matrix operator-synthesis-filter bank Z that minimizes all the worst-case measures of the matrix operator-error-signals E(ω) = F(ω) − Y(ω) between the matrix operator-input-signals F(ω) and the matrix operator-output signals Y(ω) of the matrix operator-filter bank at the same time. Further, feedback is introduced to the above approximation theory and it is indicated that introducing conversations with feedback does not superior automatically to the accumulation of existing knowledge of signal prediction. Secondly, the concept of category in the field of mathematics is applied to the above optimum signal approximation and is indicated that the category-based approximation theory is applied to the set-theoretic consideration of the recognition of humans. Based on this discussion, it is shown naturally why the narrow perception that tends to create isolation shows an apparent advantage in the short term and, often, why such narrow thinking becomes intimate with discriminatory action in a human group. Throughout these considerations, it is presented that, in order to abolish easy and intimate discriminatory behavior, it is important to create a parallel world of conception where we share the set of invisible error signals, including the words and the consciousness of both worlds.

Keywords: signal prediction, pseudo inverse matrix, artificial intelligence, conditional optimization

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Authors: Josselyn Mata Calidonio, Arianna I. Maddox, Kimberly Hamad-Schifferli

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Rapid diagnostics are critical infectious disease tools that are designed to detect a known biomarker using antibodies specific to that biomarker. However, a way to detect unknown viruses has not yet been achieved in a paper test format. We describe here a route to make an adaptable paper immunoassay that can detect an unknown biomarker, demonstrating it on SARS-CoV-2 variants. The immunoassay repurposes cross-reactive antibodies raised against the alpha variant. Gold nanoparticles of two different colors conjugated to two different antibodies create a colorimetric signal, and machine learning of the resulting colorimetric pattern is used to train the assay to discriminate between variants of alpha and Omicron BA.5. By using principal component analysis, the colorimetric test patterns can pick up and discriminate an unknown that it has not encountered before, Omicron BA.1. The test has an accuracy of 100% and a potential calculated discriminatory power of 900. We show that it can be used adaptively and that it can be used to pick up emerging variants without the need to raise new antibodies.

Keywords: adaptive immunoassay, detecting unknown viruses, gold nanoparticles, paper immunoassay, repurposing antibodies

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Authors: B. R. Campomanes-Alvarez, P. Quiros, B. Fernandez

Abstract:

Automatic Speech Recognition (ASR) is a machine-based process of decoding and transcribing oral speech. A typical ASR system receives acoustic input from a speaker or an audio file, analyzes it using algorithms, and produces an output in the form of a text. Some speech recognition systems use Hidden Markov Models (HMMs) to deal with the temporal variability of speech and Gaussian Mixture Models (GMMs) to determine how well each state of each HMM fits a short window of frames of coefficients that represents the acoustic input. Another way to evaluate the fit is to use a feed-forward neural network that takes several frames of coefficients as input and produces posterior probabilities over HMM states as output. Deep neural networks (DNNs) that have many hidden layers and are trained using new methods have been shown to outperform GMMs on a variety of speech recognition systems. Acoustic models for state-of-the-art ASR systems are usually training on massive amounts of data. However, audio files with their corresponding transcriptions can be difficult to obtain, especially in the Spanish language. Hence, in the case of these low-resource scenarios, building an ASR model is considered as a complex task due to the lack of labeled data, resulting in an under-trained system. Semi-supervised learning approaches arise as necessary tasks given the high cost of transcribing audio data. The main goal of this proposal is to develop a procedure based on acoustic semi-supervised learning for Spanish ASR systems by using DNNs. This semi-supervised learning approach consists of: (a) Training a seed ASR model with a DNN using a set of audios and their respective transcriptions. A DNN with a one-hidden-layer network was initialized; increasing the number of hidden layers in training, to a five. A refinement, which consisted of the weight matrix plus bias term and a Stochastic Gradient Descent (SGD) training were also performed. The objective function was the cross-entropy criterion. (b) Decoding/testing a set of unlabeled data with the obtained seed model. (c) Selecting a suitable subset of the validated data to retrain the seed model, thereby improving its performance on the target test set. To choose the most precise transcriptions, three confidence scores or metrics, regarding the lattice concept (based on the graph cost, the acoustic cost and a combination of both), was performed as selection technique. The performance of the ASR system will be calculated by means of the Word Error Rate (WER). The test dataset was renewed in order to extract the new transcriptions added to the training dataset. Some experiments were carried out in order to select the best ASR results. A comparison between a GMM-based model without retraining and the DNN proposed system was also made under the same conditions. Results showed that the semi-supervised ASR-model based on DNNs outperformed the GMM-model, in terms of WER, in all tested cases. The best result obtained an improvement of 6% relative WER. Hence, these promising results suggest that the proposed technique could be suitable for building ASR models in low-resource environments.

Keywords: automatic speech recognition, deep neural networks, machine learning, semi-supervised learning

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