Search results for: smart beta

Authors: Mahdi Salarian, Xi Xu, Rashid Ansari

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Accurate localization of mobile devices based on camera-acquired visual media information usually requires a search over a very large GPS-referenced image database. This paper proposes an efficient method for limiting the search space for image retrieval engine by extracting and leveraging additional media information about Estimated Positional Error (EP E) to address complexity and accuracy issues in the search, especially to be used for compensating GPS location inaccuracy in dense urban areas. The improved performance is achieved by up to a hundred-fold reduction in the search area used in available reference methods while providing improved accuracy. To test our procedure we created a database by acquiring Google Street View (GSV) images for down town of Chicago. Other available databases are not suitable for our approach due to lack of EP E for the query images. We tested the procedure using more than 200 query images along with EP E acquired mostly in the densest areas of Chicago with different phones and in different conditions such as low illumination and from under rail tracks. The effectiveness of our approach and the effect of size and sector angle of the search area are discussed and experimental results demonstrate how our proposed method can improve performance just by utilizing a data that is available for mobile systems such as smart phones.

Keywords: localization, retrieval, GPS uncertainty, bag of word

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Authors: Panpan Feng

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The concept of green infrastructure originated in Europe and the United States. It aims to ensure smart growth of urban and rural ecosystems and achieve sustainable urban and rural ecological, social, and economic development by combining it with gray infrastructure in traditional planning. Based on the literature review of the theoretical origin, value connotation, and measurement methods of green infrastructure, this study summarizes the research content of green infrastructure at different scales from the three spatial levels of region, city, and block and divides it into functional dimensions, spatial dimension, and strategic dimension. The results show that in the functional dimension, from region-city-block, the research on green infrastructure gradually shifts from ecological function to social function. In the spatial dimension, from region-city-block, the research on the spatial form of green infrastructure has shifted from two-dimensional to three-dimensional, and the spatial structure of green infrastructure has shifted from single ecological elements to multiple composite elements. From a strategic perspective, green infrastructure research is more of a spatial planning tool based on land management, environmental livability and ecological psychology, providing certain decision-making support.

Keywords: green infrastructure, multi-scale, social and ecological functions, spatial strategic decision-making tools

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Authors: Aqsa Ali, Aleem Mushtaq, Attaullah Memon, Monna

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In this paper, we present a low cost design for a smart glove that can perform sign language recognition to assist the speech impaired people. Specifically, we have designed and developed an Assistive Hand Gesture Interpreter that recognizes hand movements relevant to the American Sign Language (ASL) and translates them into text for display on a Thin-Film-Transistor Liquid Crystal Display (TFT LCD) screen as well as synthetic speech. Linear Bayes Classifiers and Multilayer Neural Networks have been used to classify 11 feature vectors obtained from the sensors on the glove into one of the 27 ASL alphabets and a predefined gesture for space. Three types of features are used; bending using six bend sensors, orientation in three dimensions using accelerometers and contacts at vital points using contact sensors. To gauge the performance of the presented design, the training database was prepared using five volunteers. The accuracy of the current version on the prepared dataset was found to be up to 99.3% for target user. The solution combines electronics, e-textile technology, sensor technology, embedded system and machine learning techniques to build a low cost wearable glove that is scrupulous, elegant and portable.

Keywords: American sign language, assistive hand gesture interpreter, human-machine interface, machine learning, sensing glove

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Authors: Fernando M. Soto, Gaetano Di Mino

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The design of an unmodified bituminous mixture and three rubber-aggregate mixtures containing rubber-aggregate by a dry process (RUMAC) was evaluated, using an empirical-analytical approach based on experimental findings obtained in the laboratory with the volumetric mix design by gyratory compaction. A reference dense-graded bituminous sub-ballast mixture (3% of air voids and a bitumen 4% over the total weight of the mix), and three rubberized mixtures by dry process (1,5 to 3% of rubber by total weight and 5-7% of binder) were used applying the Superpave mix-design for a level 3 (high-traffic) design rail lines. The railway trackbed section analyzed was a granular layer of 19 cm compacted, while for the sub-ballast a thickness of 12 cm has been used. In order to evaluate the effect of increasing the specimen density (as a percent of its theoretical maximum specific gravity), in this article, are illustrated the results obtained after different comparative analysis into the influence of varying the binder-rubber percentages under the sub-ballast layer mix-design. This work demonstrates that rubberized blends containing crumb and ground rubber in bituminous asphalt mixtures behave at least similar or better than conventional asphalt materials. By using the same methodology of volumetric compaction, the densification curves resulting from each mixture have been studied. The purpose is to obtain an optimum empirical parameter multiplier of the number of gyrations necessary to reach the same compaction energy as in conventional mixtures. It has provided some experimental parameters adopting an empirical-analytical method, evaluating the results obtained from the gyratory-compaction of bituminous mixtures with an HMA and rubber-aggregate blends. An extensive integrated research has been carried out to assess the suitability of rubber-modified hot mix asphalt mixtures as a sub-ballast layer in railway underlayment trackbed. Design optimization of the mixture was conducted for each mixture and the volumetric properties analyzed. Also, an improved and complete manufacturing process, compaction and curing of these blends are provided. By adopting this increase-parameters of compaction, called 'beta' factor, mixtures modified with rubber with uniform densification and workability are obtained that in the conventional mixtures. It is found that considering the usual bearing capacity requirements in rail track, the optimal rubber content is 2% (by weight) or 3.95% (by volumetric substitution) and a binder content of 6%.

Keywords: empirical approach, rubber-asphalt, sub-ballast, superpave mix-design

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Authors: Hanbyul Kim, Hye-Jin Kin, Taehun Park, Woo Jun Sul, Susun An

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Skin is the largest organ of the human body and can provide the diverse habitat for various microorganisms. The ecology of the skin surface selects distinctive sets of microorganisms and is influenced by both endogenous intrinsic factors and exogenous environmental factors. The diversity of the bacterial community in the skin also depends on multiple host factors: gender, age, health status, location. Among them, age-related changes in skin structure and function are attributable to combinations of endogenous intrinsic factors and exogenous environmental factors. Skin aging is characterized by a decrease in sweat, sebum and the immune functions thus resulting in significant alterations in skin surface physiology including pH, lipid composition, and sebum secretion. The present study gives a comprehensive clue on the variation of skin microbiota and the correlations between ages by analyzing and comparing the metagenome of skin microbiome using Next Generation Sequencing method. Skin bacterial diversity and composition were characterized and compared between two different age groups: younger (20 – 30y) and older (60 - 70y) Xian, Chinese women. A total of 73 healthy women meet two conditions: (I) living in Xian, China; (II) maintaining healthy skin status during the period of this study. Based on Ribosomal Database Project (RDP) database, skin samples of 73 participants were enclosed with ten most abundant genera: Chryseobacterium, Propionibacterium, Enhydrobacter, Staphylococcus and so on. Although these genera are the most predominant genus overall, each genus showed different proportion in each group. The most dominant genus, Chryseobacterium was more present relatively in Young group than in an old group. Similarly, Propionibacterium and Enhydrobacter occupied a higher proportion of skin bacterial composition of the young group. Staphylococcus, in contrast, inhabited more in the old group. The beta diversity that represents the ratio between regional and local species diversity showed significantly different between two age groups. Likewise, The Principal Coordinate Analysis (PCoA) values representing each phylogenetic distance in the two-dimensional framework using the OTU (Operational taxonomic unit) values of the samples also showed differences between the two groups. Thus, our data suggested that the composition and diversification of skin microbiomes in adult women were largely affected by chronological and physiological skin aging.

Keywords: next generation sequencing, age, Xian, skin microbiome

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Authors: Natan C. G. Silva, Carlos A. C. Girao Neto, Marcele M. S. Vasconcelos, Luciana R. B. Goncalves, Maria Valderez P. Rocha

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Galactooligosaccharides (GOS) are sugars with prebiotic function that can be synthesized chemically or enzymatically, and this last one can be promoted by the action of β-galactosidases. In addition to favoring the transgalactosylation reaction to form GOS, these enzymes can also catalyze the hydrolysis of lactose. A highly studied type of GOS is lactulose because it presents therapeutic properties and is a health promoter. Among the different raw materials that can be used to produce lactulose, whey stands out as the main by-product of cheese manufacturing, and its discarded is harmful to the environment due to the residual lactose present. Therefore, its use is a promising alternative to solve this environmental problem. Thus, lactose from whey is hydrolyzed into glucose and galactose by β-galactosidases. However, in order to favor the transgalactosylation reaction, the medium must contain fructose, due this sugar reacts with galactose to produce lactulose. Then, the glucose-isomerase enzyme can be used for this purpose, since it promotes the isomerization of glucose into fructose. In this scenario, the aim of the present work was first to develop β-galactosidase biocatalysts of Kluyveromyces lactis and to apply it in the integrated reactions of hydrolysis, isomerization (with the glucose-isomerase from Streptomyces murinus) and transgalactosylation reaction, using whey as a substrate. The immobilization of β-galactosidase in chitosan previously functionalized with 0.8% glutaraldehyde was evaluated using different enzymatic loads (2, 5, 7, 10, and 12 mg/g). Subsequently, the hydrolysis and transgalactosylation reactions were studied and conducted at 50°C, 120 RPM for 20 minutes. In parallel, the isomerization of glucose into fructose was evaluated under conditions of 70°C, 750 RPM for 90 min. After, the integration of the three processes for the production of lactulose was investigated. Among the evaluated loads, 7 mg/g was chosen because the best activity of the derivative (44.3 U/g) was obtained, being this parameter determinant for the reaction stages. The other parameters of immobilization yield (87.58%) and recovered activity (46.47%) were also satisfactory compared to the other conditions. Regarding the integrated process, 94.96% of lactose was converted, achieving 37.56 g/L and 37.97 g/L of glucose and galactose, respectively. In the isomerization step, conversion of 38.40% of glucose was observed, obtaining a concentration of 12.47 g/L fructose. In the transgalactosylation reaction was produced 13.15 g/L lactulose after 5 min. However, in the integrated process, there was no formation of lactulose, but it was produced other GOS at the same time. The high galactose concentration in the medium probably favored the reaction of synthesis of these other GOS. Therefore, the integrated process proved feasible for possible production of prebiotics. In addition, this process can be economically viable due to the use of an industrial residue as a substrate, but it is necessary a more detailed investigation of the transgalactosilation reaction.

Keywords: beta-galactosidase, glucose-isomerase, galactooligosaccharides, lactulose, whey

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Authors: Jacob Wahl, Jane Zhang

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This paper describes the development and characterization of a prototype IoT network for use with agricultural imaging and monitoring applications. The sensor and gateway nodes are designed using the ESP32 SoC with integrated Bluetooth Low Energy 4.2 and Wi-Fi. A development board, the Arducam IoTai ESP32, is used for prototyping, testing, and power measurements. Google’s Firebase is used as the cloud storage site for image data collected by the sensor. The sensor node captures images using the OV2640 2MP camera module and transmits the image data to the gateway via Bluetooth Low Energy. The gateway then uploads the collected images to Firebase via a known nearby Wi-Fi network connection. This image data can then be processed and analyzed by computer vision and machine learning pipelines to assess crop growth or other needs. The sensor node achieves a wireless transmission data throughput of 220kbps while consuming 150mA of current; the sensor sleeps at 162µA. The sensor node device lifetime is estimated to be 682 days on a 6600mAh LiPo battery while acquiring five images per day based on the development board power measurements. This network can be utilized by any application that requires high data rates, low power consumption, short-range communication, and large amounts of data to be transmitted at low-frequency intervals.

Keywords: Bluetooth low energy, ESP32, firebase cloud, IoT, smart farming

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Authors: A. Chandra, M. Arthur, L. Mize, A. Pomeroy-Stevens

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Background: Lower and middle-income countries (LMICs) in Asia face rapid urbanization resulting in both economic opportunities (the urban advantage) and emerging health challenges. Urban health risks are magnified in informal settlements and include infectious disease outbreaks, inadequate access to health services, and poor air quality. Over the coming years, urban spaces in Asia will face accelerating public health risks related to migration, climate change, and environmental health. These challenges are complex and require multi-sectoral and multi-stakeholder solutions. The Building Health Cities (BHC) program is funded by the United States Agency for International Development (USAID) to work with smart city initiatives in the Asia region. BHC approaches urban health challenges by addressing policies, planning, and services through a health equity lens, with a particular focus on informal settlements and migrant communities. The program works to develop data-driven decision-making, build inclusivity through stakeholder engagement, and facilitate the uptake of appropriate technology. Methodology: The BHC program has partnered with the smart city initiatives of Indore in India, Makassar in Indonesia, and Da Nang in Vietnam. Implementing partners support municipalities to improve health delivery and equity using two key approaches: political economy analysis and participatory systems mapping. Political economy analyses evaluate barriers to collective action, including corruption, security, accountability, and incentives. Systems mapping evaluates community health challenges using a cross-sectoral approach, analyzing the impact of economic, environmental, transport, security, health system, and built environment factors. The mapping exercise draws on the experience and expertise of a diverse cohort of stakeholders, including government officials, municipal service providers, and civil society organizations. Results: Systems mapping and political economy analyses identified significant barriers for health care in migrant populations. In Makassar, migrants are unable to obtain the necessary card that entitles them to subsidized health services. This finding is being used to engage with municipal governments to mitigate the barriers that limit migrant enrollment in the public social health insurance scheme. In Indore, the project identified poor drainage of storm and wastewater in migrant settlements as a cause of poor health. Unsafe and inadequate infrastructure placed residents of these settlements at risk for both waterborne diseases and injuries. The program also evaluated the capacity of urban primary health centers serving migrant communities, identifying challenges related to their hours of service and shortages of health workers. In Da Nang, the systems mapping process has only recently begun, with the formal partnership launched in December 2019. Conclusion: This paper explores lessons learned from BHC’s systems mapping, political economy analyses, and stakeholder engagement approaches. The paper shares progress related to the health of migrants in informal settlements. Case studies feature barriers identified and mitigating steps, including governance actions, taken by local stakeholders in partner cities. The paper includes an update on ongoing progress from Indore and Makassar and experience from the first six months of program implementation from Da Nang.

Keywords: informal settlements, migration, stakeholder engagement mapping, urban health

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Authors: Savvas Rogotis, Nikolaos Kalatzis, Stergios Dimou-Sakellariou, Nikolaos Marianos

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As precision holds the key for the introduction of distinct benefits in agriculture (e.g., energy savings, reduced labor costs, optimal application of inputs, improved products, and yields), it steadily becomes evident that new initiatives should focus on rendering Precision Agriculture (PA) more accessible to the average farmer. PA leverages on technologies such as the Internet of Things (IoT), earth observation, robotics and positioning systems (e.g., the Global Navigation Satellite System – GNSS - as well as individual positioning systems like GPS, Glonass, Galileo) that allow: from simple data georeferencing to optimal navigation of agricultural machinery to even more complex tasks like Variable Rate Applications. An identified customer pain point is that, from one hand, typical triangulation-based positioning systems are not accurate enough (with errors up to several meters), while on the other hand, high precision positioning systems reaching centimeter-level accuracy, are very costly (up to thousands of euros). Within this paper, a Ground-Based Augmentation System (GBAS) is introduced, that can be adapted to any existing IoT field-sensing station infrastructure. The latter should cover a minimum set of requirements, and in particular, each station should operate as a fixed, obstruction-free towards the sky, energy supplying unit. Station augmentation will allow them to function in pairs with GNSS rovers following the differential GNSS base-rover paradigm. This constitutes a key innovation element for the proposed solution that encompasses differential GNSS capabilities into an IoT field-sensing infrastructure. Integrating this kind of information supports the provision of several additional PA beneficial services such as spatial mapping, route planning, and automatic field navigation of unmanned vehicles (UVs). Right at the heart of the designed system, there is a high-end GNSS toolkit with base-rover variants and Real-Time Kinematic (RTK) capabilities. The GNSS toolkit had to tackle all availability, performance, interfacing, and energy-related challenges that are faced for a real-time, low-power, and reliable in the field operation. Specifically, in terms of performance, preliminary findings exhibit a high rover positioning precision that can even reach less than 10-centimeters. As this precision is propagated to the full dataset collection, it enables tractors, UVs, Android-powered devices, and measuring units to deal with challenging real-world scenarios. The system is validated with the help of Gaiatrons, a mature network of agro-climatic telemetry stations with presence all over Greece and beyond ( > 60.000ha of agricultural land covered) that constitutes part of “gaiasense” (www.gaiasense.gr) smart farming (SF) solution. Gaiatrons constantly monitor atmospheric and soil parameters, thus, providing exact fit to operational requirements asked from modern SF infrastructures. Gaiatrons are ultra-low-cost, compact, and energy-autonomous stations with a modular design that enables the integration of advanced GNSS base station capabilities on top of them. A set of demanding pilot demonstrations has been initiated in Stimagka, Greece, an area with a diverse geomorphological landscape where grape cultivation is particularly popular. Pilot demonstrations are in the course of validating the preliminary system findings in its intended environment, tackle all technical challenges, and effectively highlight the added-value offered by the system in action.

Keywords: GNSS, GBAS, precision agriculture, RTK, smart farming

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Authors: Hassan Manouchehri

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The present study aimed to identify and evaluate the factors affecting violence against women. The statistical population included all couples referring to family counseling centers in Tehran due to domestic violence during the past year. A number of 305 people were selected as a statistical sample using simple random sampling and Cochran's formula in unlimited conditions. A researcher-made questionnaire including 110 items was used for data collection. The face validity and content validity of the questionnaire were confirmed by 30 experts and its reliability was obtained above 0.7 for all studied variables in a preliminary test with 30 subjects and it was acceptable. In order to analyze the data, descriptive statistical methods were used with SPSS software version 22 and inferential statistics were used for modeling structural equations in Smart PLS software version 2. Evaluating the theoretical framework and domestic and foreign studies indicated that, in general, four main factors, including cultural and social factors, economic factors, legal factors, as well as medical factors, underlie violence against women. In addition, structural equation modeling findings indicated that cultural and social factors, economic factors, legal factors, and medical factors affect violence against women.

Keywords: violence against women, cultural and social factors, economic factors, legal factors, medical factors

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Authors: Muhammad Kamran, Xue Pu, Naveed Ahmed

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Sandwich foam structures are efficient in impact energy absorption and making components lightweight; however their efficient use require a detailed understanding of its mechanical response. In this study, the foam core, laminated facings’ sandwich panel with internal triangular rib configuration is impacted by a spherical steel projectile at different angles using ABAQUS finite element package and damage mechanics is studied. Laminated ribs’ structure is sub-divided into three formations; all zeros, all 45 and optimized combination of zeros and 45 degrees. Impact velocity is varied from 250 m/s to 500 m/s with an increment of 50 m/s. The impact damage can significantly demolish the structural integrity and energy absorption due to fiber breakage, matrix cracking, and de-bonding. Macroscopic fracture study of the panel and core along with load-displacement responses and failure modes are the key parameters in the design of smart ballistic resistant structures. Ballistic impact characteristics of panels are studied on different speed, different inclination angles and its dependency on the base, and core materials, ribs formation, and cross-sectional spaces among them are determined. Impact momentum, penetration and kinetic energy absorption data and curves are compiled to predict the first and proximity impact in an effort to enhance the dynamic energy absorption.

Keywords: dynamic energy absorption, proximity impact, sandwich panels, impact momentum

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Authors: Chaithanya Pothuganti

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Open and semi-open spaces in educational buildings like corridors, mid landings, seating spaces, lobby, courtyards are traditionally have been the places of social communion and interaction which helps in promoting the knowledge, performance, activeness, and motivation in students. Factors like availability of land, commercialization, of educational facilities, especially in e-techno and smart schools, led to closed classrooms to accommodate students thereby lack quality open and semi-open spaces. This insufficient attention towards open space design which is a means of informal learning misses an opportunity to encourage the student’s skill development, behavior and learning skills. The core objective of this paper is to find the level of impact on student learning behavior and to identify the suitable proportions and configuration of spaces that shape the schools. In order to achieve this, different types of open spaces in schools and their impact on student’s performance in various existing models are analysed using case studies to draw some design principles. The study is limited to indoor open spaces like corridors, break out spaces and courtyards. The expected outcome of the paper is to suggest better design considerations for the development of semi-open and open spaces which functions as an element for informal learnings. Its focus is to provide further thinking on designing and development of open spaces in educational buildings.

Keywords: configuration of spaces and proportions, informal learning, open spaces, schools, student’s behavior

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Authors: Yang Zhou, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

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Traffic prediction is a fundamental problem in urban environment, facilitating the smart management of various businesses, such as taxi dispatching, bike relocation, and stampede alert. Most earlier methods rely on identifying the intrinsic spatial-temporal correlation to forecast. However, the complex nature of this problem entails a more sophisticated solution that can simultaneously capture the mutual influence of both adjacent and far-flung areas, with the information of time-dimension also incorporated seamlessly. To tackle this difficulty, we propose a new multi-phase architecture, DSTDS (Dual Spatial-Temporal Data Scheme for traffic prediction), that aims to reveal the underlying relationship that determines future traffic trend. First, a graph-based neural network with an attention mechanism is devised to obtain the static features of the road network. Then, a multi-granularity recurrent neural network is built in conjunction with the knowledge from a grid-based model. Subsequently, the preceding output is fed into a spatial-temporal super-resolution module. With this 3-phase structure, we carry out extensive experiments on several real-world datasets to demonstrate the effectiveness of our approach, which surpasses several state-of-the-art methods.

Keywords: traffic prediction, spatial-temporal, recurrent neural network, dual data scheme

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Authors: Fahad Alam

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Work stress directly affects job performance, specifically in a worse environment. Consequently, a social provision plays a crucial part for enhancement. Therefore, the current research investigates the direct and moderating effect between religious activities, sustainability and peer support on job performance at hospitals in Khyber PakhtunKhwa (KPK), Pakistan. Both primary and secondary data are collected through 261 questionnaires of medical employees from four district hospitals in Khyber PakhtunKhwa, Pakistan, in 2018. The analysis was carried out by SPSS16 and SMART PLS3, to test the direct effect of religious activities, sustainability and social support on job performance and the effect of moderating variable 'work environment' on job performance. The finding confirmed that direct and moderating variables play a significant positive effect among religious activities, sustainability and peer support on job performance, the variables help to diminish the strain level or the stress level, consequently helps in the job completed. Affirmative social approaches produce desirable effects on job performance. The research revealed that social provisions are significant triggers for superior practices. Moreover, the results are stimulating because some of the past literature revealed an insignificant correlation between social provision and performance. This study found that there is a significant relationship which persuades health care organizations.

Keywords: job performance, peer’s support, religious activities, sustainability, work environment

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Authors: Paul Barasa Wanyama, Tom Wanyama

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Governments and development partners in low-income countries often prioritize building Water Sanitation and Hygiene (WaSH) infrastructure of healthcare facilities to improve maternal healthcare outcomes. However, the operation, maintenance, and utilization of this infrastructure are almost never considered. Many healthcare facilities in these countries use untreated water that is not monitored for quality or quantity. Consequently, it is common to run out of water while a patient is on their way to or in the operating theater. Further, the handwashing stations in healthcare facilities regularly run out of water or soap for months, and the latrines are typically not clean, in part due to the lack of water. In this paper, we present a system that uses Internet of Things (IoT), big data, cloud computing, and AI to initiate WaSH security in healthcare facilities, with a specific focus on maternal health. We have implemented smart sensors and actuators to monitor and control WaSH systems from afar to ensure their objectives are achieved. We have also developed a cloud-based system to analyze WaSH data in real time and communicate relevant information back to the healthcare facilities and their stakeholders (e.g., medical personnel, NGOs, ministry of health officials, facilities managers, community leaders, pregnant women, and new mothers and their families) to avert or mitigate problems before they occur.

Keywords: WaSH, internet of things, artificial intelligence, maternal health, rural communities, healthcare facilities

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Authors: Aswini M. S.

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Tomato (Solanum lycopersicum L.) is one of the most significant vegetable crops in terms of its economic benefits. Both fresh and processed tomatoes are consumed. Tomatoes have a limited genetic base, which makes breeding extremely challenging. Plant breeding has become much simpler and more effective with genome editing tools of CRISPR and CRISPR-associated 9 protein (CRISPR/Cas9), which address the problems with traditional breeding, chemical/physical mutagenesis, and transgenics. With the use of CRISPR/Cas9, a number of tomato traits have been functionally distinguished and edited. These traits include plant architecture as well as flower characters (leaf, flower, male sterility, and parthenocarpy), fruit ripening, quality and nutrition (lycopene, carotenoid, GABA, TSS, and shelf-life), disease resistance (late blight, TYLCV, and powdery mildew), tolerance to abiotic stress (heat, drought, and salinity) and resistance to herbicides. This study explores the potential of CRISPR/Cas9 genome editing for enhancing yield in tomato plants. The study utilized the CRISPR/Cas9 genome editing technology to functionally edit various traits in tomatoes. The de novo domestication of elite features from wild cousins to cultivated tomatoes and vice versa has been demonstrated by the introgression of CRISPR/Cas9. The CycB (Lycopene beta someri) gene-mediated Cas9 editing increased the lycopene content in tomato. Also, Cas9-mediated editing of the AGL6 (Agamous-like 6) gene resulted in parthenocarpic fruit development under heat-stress conditions. The advent of CRISPR/Cas has rendered it possible to use digital resources for single guide RNA design and multiplexing, cloning (such as Golden Gate cloning, GoldenBraid, etc.), creating robust CRISPR/Cas constructs, and implementing effective transformation protocols like the Agrobacterium and DNA free protoplast method for Cas9-gRNAs ribonucleoproteins (RNPs) complex. Additionally, homologous recombination (HR)-based gene knock-in (HKI) via geminivirus replicon and base/prime editing (Target-AID technology) remains possible. Hence, CRISPR/Cas facilitates fast and efficient breeding in the improvement of tomatoes.

Keywords: CRISPR-Cas, biotic and abiotic stress, flower and fruit traits, genome editing, polygenic trait, tomato and trait introgression

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Authors: Choon Seong Ng, P. Petrick, C. L. Lau

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Background: Carbapenem-resistant isolates have been increasingly reported recently. Carbapenem stewardship is designed to optimize its usage particularly among medical wards with high prevalence of carbapenem prescriptions to combat such emerging resistance. Carbapenem stewardship programmes (CSP) can reduce antibiotic use but clinical outcome of such measures needs further evaluation. We examined this in a prospective manner using feedback mechanism. Methods: Our single-center prospective cohort study involved all carbapenem prescriptions across the medical wards (including medical patients admitted to intensive care unit) in a tertiary university hospital setting. The impact of such stewardship was analysed according to the accepted and the rejected groups. The primary endpoint was safety. Safety measure applied in this study was the death at 1 month. Secondary endpoints included length of hospitalisation and readmission. Results: Over the 19 months’ period, input from 144 carbapenem prescriptions was analysed on the basis of acceptance of our CSP recommendations on the use of carbapenems. Recommendations made were as follows : de-escalation of carbapenem; stopping the carbapenem; use for a short duration of 5-7 days; required prolonged duration in the case of carbapenem-sensitive Extended Spectrum Beta-Lactamases bacteremia; dose adjustment; and surgical intervention for removal of septic foci. De-escalation, shorten duration of carbapenem and carbapenem cessation comprised 79% of the recommendations. Acceptance rate was 57%. Those who accepted CSP recommendations had no increase in mortality (p = 0.92), had a shorter length of hospital stay (LOS) and had cost-saving. Infection-related deaths were found to be higher among those in the rejected group. Moreover, three rejected cases (6%) among all non-indicated cases (n = 50) were found to have developed carbapenem-resistant isolates. Lastly, Pitt’s bacteremia score appeared to be a key element affecting the carbapenem prescription’s behaviour in this trial. Conclusions: Carbapenem stewardship program in the medical wards not only saves money, but most importantly it is safe and does not harm the patients with added benefits of reducing the length of hospital stay. However, more time is needed to engage the primary clinical teams by formal clinical presentation and immediate personal feedback by senior Infectious Disease (ID) personnel to increase its acceptance.

Keywords: audit and feedback, carbapenem stewardship, medical wards, university hospital

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Authors: Ei Ei Hlaing, Narissara Lailerd, Sittiruk Roytrakul, Pichapat Piamrojanaphat

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Type 2 diabetes is one of the most common metabolic diseases all over the world. The pathogenesis of type 2 diabetes is not the only dysfunction of pancreatic beta cells but also insulin resistance in muscle, liver and adipose tissue. High levels of circulating free fatty acids, an increased lipid content of muscle cells, impaired insulin-mediated glucose uptake and diminished mitochondrial functioning are pathophysiological hallmarks of diabetic skeletal muscles. Purple rice (Oryza sativa L. indica) has been shown to have antidiabetic effects. However, the underlying mechanism(s) of antidiabetic activity of purple rice is still unraveled. In this research, to explore in-depth cellular mechanism(s), proteomic profile of purple rice supplemented type 2 diabetic rats’ skeletal muscle were analyzed contract with non-supplemented rats. Diabetic rats were induced high-fat diet combined with streptozotocin injection. By using one- dimensional gel electrophoresis (1-DE) and LC-MS/MS quantitative proteomic method, we analyzed proteomic profiles in skeletal muscle of normal rats, normal rats with purple rice supplementation, type 2 diabetic rats, and type 2 diabetic rats with purple rice supplementation. Total 2676 polypeptide expressions were identified. Among them, 24 peptides were only expressed in type 2 diabetic rats, and 24 peptides were unique peptides in type 2 diabetic rats with purple rice supplementation. Acetyl CoA carboxylase 1 (ACACA) found as unique protein in type 2 diabetic rats which is the major enzyme in lipid synthesis and metabolism. Interestingly, DNA damage response protein, heterogeneous nuclear ribonucleoprotein K [Mus musculus] (Hnrnpk), was upregulated in type 2 diabetic rats’ skeletal muscle. Meanwhile, unique proteins of type 2 diabetic rats with purple rice supplementation (bone morphogenetic 7 protein preproprotein, BMP7; and forkhead box protein NX4, Foxn4) involved with muscle cells growth through the regulation of TGF-β/Smad signaling network. Moreover, BMP7 may effect on insulin signaling through the downstream signaling of protein kinase B (Akt) which acts in protein synthesis, glucose uptake, and glycogen synthesis. In conclusion, our study supports that type 2 diabetes impairs muscular lipid metabolism. In addition, purple rice might recover the muscle cells growth and insulin signaling.

Keywords: proteomics, purple rice bran, skeletal muscle, type 2 diabetic rats

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Authors: M. M. Essa, S. Subash, M. Akbar, S. Al-Adawi, A. Al-Asmi, G. J. Guillemein

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Objective: Transgenic (tg) mice which contain an amyloid precursor protein (APP) gene mutation, develop extracellular amyloid beta (Aβ) deposition in the brain, and severe memory and behavioural deficits with age. These mice serve as an important animal model for testing the efficacy of novel drug candidates for the treatment and management of symptoms of Alzheimer's disease (AD). Several reports have suggested that oxidative stress is the underlying cause of Aβ neurotoxicity in AD. Pomegranates contain very high levels of antioxidants and several medicinal properties that may be useful for improving the quality of life in AD patients. In this study, we investigated the effect of dietary supplementation of Omani pomegranate extract on the memory, anxiety and learning skills along with inflammation in an AD mouse model containing the double Swedish APP mutation (APPsw/Tg2576). Methods: The experimental groups of APP-transgenic mice from the age of 4 months were fed custom-mix diets (pellets) containing 4% pomegranate. We assessed spatial memory and learning ability, psychomotor coordination, and anxiety-related behavior in Tg and wild-type mice at the age of 4-5 months and 18-19 months using the Morris water maze test, rota rod test, elevated plus maze test, and open field test. Further, inflammatory parameters also analysed. Results: APPsw/Tg2576 mice that were fed a standard chow diet without pomegranates showed significant memory deficits, increased anxiety-related behavior, and severe impairment in spatial learning ability, position discrimination learning ability and motor coordination along with increased inflammation compared to the wild type mice on the same diet, at the age of 18-19 months In contrast, APPsw/Tg2576 mice that were fed a diet containing 4% pomegranates showed a significant improvements in memory, learning, locomotor function, and anxiety with reduced inflammatory markers compared to APPsw/Tg2576 mice fed the standard chow diet. Conclusion: Our results suggest that dietary supplementation with pomegranates may slow the progression of cognitive and behavioural impairments in AD. The exact mechanism is still unclear and further extensive research needed.

Keywords: Alzheimer's disease, pomegranates, oman, cognitive decline, memory loss, anxiety, inflammation

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Authors: Sontana Mimapan, Phattarawadee Wattanasuntorn, Phanom Saijit

Abstract:

Aflatoxin contamination in maize, one of several agriculture crops grown for livestock feeding, is still a problem throughout the world mainly under hot and humid weather conditions like Thailand. In this study Aspergillus flavus (A. Flavus), the key fungus for aflatoxin production especially aflatoxin B1 (AFB1), isolated from naturally infected maize were identified and characterized according to colony morphology and PCR using ITS, Beta-tubulin and calmodulin genes. The strains were analysed for the presence of four aflatoxigenic biosynthesis genes in relation to their capability to produce AFB1, Ver1, Omt1, Nor1, and aflR. Aflatoxin production was then confirmed using immunoaffinity column technique. A loop-mediated isothermal amplification (LAMP) was applied as an innovative technique for rapid detection of target nucleic acid. The reaction condition was optimized at 65C for 60 min. and calcein flurescent reagent was added before amplification. The LAMP results showed clear differences between positive and negative reactions in end point analysis under daylight and UV light by the naked eye. In daylight, the samples with AFB1 producing A. Flavus genes developed a yellow to green color, but those without the genes retained the orange color. When excited with UV light, the positive samples become visible by bright green fluorescence. LAMP reactions were positive after addition of purified target DNA until dilutions of 10⁻⁶. The reaction products were then confirmed and visualized with 1% agarose gel electrophoresis. In this regards, 50 maize samples were collected from dairy farms and tested for the presence of four aflatoxigenic biosynthesis genes using LAMP technique. The results were positive in 18 samples (36%) but negative in 32 samples (64%). All of the samples were rechecked by PCR and the results were the same as LAMP, indicating 100% specificity. Additionally, when compared with the immunoaffinity column-based aflatoxin analysis, there was a significant correlation between LAMP results and aflatoxin analysis (r= 0.83, P < 0.05) which suggested that positive maize samples were likely to be a high- risk feed. In conclusion, the LAMP developed in this study can provide a simple and rapid approach for detecting AFB1 producing A. Flavus genes from maize and appeared to be a promising tool for the prediction of potential aflatoxigenic risk in livestock feedings.

Keywords: Aflatoxin B1, Aspergillus flavus genes, maize, loop-mediated isothermal amplification

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Authors: Lorena Caires Moreira, Marcos Kauffman

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This paper outlines the results of experimental research on deploying an emerging augmented reality (AR) system for real-time task assistance of highly customized and high-risk manual operations. The focus is on operators’ training capabilities and the aim is to test if such technologies can support achieving higher levels of knowledge retention and accuracy of task execution to improve health and safety (H and S) levels. The proposed solution is tested and validated using a real-world case study of electric vehicles’ battery module assembly. The experimental results revealed that the proposed AR method improved the training practices by increasing the knowledge retention levels from 40% to 84% and improved the accuracy of task execution from 20% to 71%, compared to the traditional paper-based method. The results of this research can be used as a demonstration of how emerging technologies are advancing the choice of manual, hybrid, or fully automated processes by promoting the connected worker (Industry 5.0) and supporting manufacturing in becoming more resilient in times of constant market changes.

Keywords: augmented reality, extended reality, connected worker, XR-assisted operator, manual assembly, industry 5.0, smart training, battery assembly

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Authors: Syeda Shawana Mahasan, Muhammad Farooq Akhtar

Abstract:

The objective of this study is to analyze the influence of the green marketing mix strategy and corporate social responsibility (CSR) on the performance of an organization, taking into account the mediating effect of corporate image. The impact of frugal innovation and corporate activism is being examined. The data was gathered from executives at various levels of management, including top, middle, and lower-level managers, from a total of 550 manufacturing enterprises of different sizes, ranging from small to medium to large. The collected replies are processed and analyzed using SMART PLS version 4.0.0.0. The application of PLS-SEM demonstrates that the green marketing mix strategy and corporate social responsibility have a significant impact on organizational performance. Therefore, it is imperative for organizations to effectively adopt environmentally sustainable and socially conscious methods within their operations. The results indicate that the corporate image has a key role in mediating the relationship between the green marketing mix strategy, corporate social responsibility, and organizational performance. This demonstrates the imperative for organizations to actively enhance their favorable reputation among stakeholders. The combination of frugal innovation and corporate activism enhances the connection between corporate image and organizational performance. The current study assists managers in recognizing the significance of these particular constructs in maintaining the long-term performance of the organization.

Keywords: green marketing mix strategy, CSR, corporate image, organizational performance, frugal innovation, corporate activism

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Authors: Anders S. Kristensen, Dewan Ahsan, Saqib Mehmood, Shakeel Ahmed

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Traffic accidents are a result of the convergence of hazards, malfunctioning of vehicles and human negligence that have adverse economic and health impacts and effects. Unfortunately, avoiding them completely is very difficult, but with quick response to rescue and first aid, the mortality rate of inflicted persons can be reduced significantly. Smart and innovative technologies can play a pivotal role to respond faster to traffic crash emergencies comparing conventional means of transportation. For instance, Rescue Emergency Drone (RED) can provide faster and real-time crash site risk assessment to emergency medical services, thereby helping them to quickly and accurately assess a situation, dispatch the right equipment and assist bystanders to treat inflicted person properly. To conduct a research in this regard, the case of a traffic roundabout that is prone to frequent traffic accidents on the outskirts of Esbjerg, a town located on western coast of Denmark is hypothetically considered. Along with manual calculations, Emergency Disaster Management Simulation (EDMSIM) has been used to verify the response time of RED from a fire station of the town to the presumed crash site. The results of the study demonstrate the robustness of RED into emergency services to help save lives. 

Keywords: automated external defibrillator, medical emergency, response time, unmanned aerial system

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Authors: Sarayu Agarwal

Abstract:

This paper aims to teach English (secondary language) by bridging the understanding between the Regional language (primary language) and the English Language (secondary language). Here primary language is the one a person has learned from birth or within the critical period, while secondary language would be any other language one learns or speaks. The paper also focuses on evolving old teaching methods to a contemporary participatory model of learning and teaching. Pilot studies were conducted to gauge an understanding of student’s knowledge of the English language. Teachers and students were interviewed and their academic curriculum was assessed as a part of the initial study. Extensive literature study and design thinking principles were used to devise a solution to the problem. The objective is met using a holistic learning kit/card game to teach children word recognition, word pronunciation, word spelling and writing words. Implication of the paper is a noticeable improvement in the understanding and grasping of English language. With increasing usage and applicability of English as a second language (ESL) world over, the paper becomes relevant due to its easy replicability to any other primary or secondary language. Future scope of this paper would be transforming the idea of participatory learning into self-regulated learning methods. With the upcoming govt. learning centres in rural areas and provision of smart devices such as tablets, the development of the card games into digital applications seems very feasible.

Keywords: English as a second language, vocabulary-building card games, learning through gamification, rural education

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Authors: Arth Bohra, Marwa Mahmoud

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In this paper, we utilize computer vision to develop a tool for youth coaches to formulate set-piece tactics for their players. We used the Soccernet database to extract the ResNet features and camera calibration data for over 3000 corner kick across 500 professional matches in the top 6 European leagues (English Premier League, UEFA Champions League, Ligue 1, La Liga, Serie A, Bundesliga). Leveraging the provided homography matrix, we construct a feature vector representing the formation of players on these corner kicks. Additionally, labeling the videos manually, we obtained the pass-trajectory of each of the 3000+ corner kicks by segmenting the field into four zones. Next, after determining the localization of the players and ball, we used event data to give the corner kicks a rating on a 1-4 scale. By employing a Convolutional Neural Network, our model managed to predict the success of a corner kick given the formations of players. This suggests that with the right formations, teams can optimize the way they approach corner kicks. By understanding this, we can help coaches formulate set-piece tactics for their own teams in order to maximize the success of their play. The proposed model can be easily extended; our method could be applied to even more game situations, from free kicks to counterattacks. This research project also gives insight into the myriad of possibilities that artificial intelligence possesses in transforming the domain of sports.

Keywords: soccer, corner kicks, AI, computer vision

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Authors: Byoungjoon Yu, Jihwan Park, Sujung Sin, Junghyun Im, Minsoo Park, Sehwan Park, Seunghee Park

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In this paper, we propose a technology to monitor the soundness of an Internet-based bridge using a non-conductive inspection function. There has been a collapse accident due to the aging of the bridge structure, and it is necessary to prepare for the deterioration of the bridge. The NDT/SHM system for maintenance of existing bridge structures requires a large number of inspection personnel and expensive inspection costs, and access of expensive and large equipment to measurement points is required. Because current drone inspection equipment can only be inspected through camera, it is difficult to inspect inside damage accurately, and the results of an internal damage evaluation are subjective, and it is difficult for non-specialists to recognize the evaluation results. Therefore, it is necessary to develop NDT/SHM techniques for maintenance of new-concept bridge structures that allow for free movement and real-time evaluation of measurement results. This work is financially supported by Korea Ministry of Land, Infrastructure, and Transport (MOLIT) as 'Smart City Master and Doctor Course Grant Program' and a grant (14SCIP-B088624-01) from Construction Technology Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Keywords: Structural Health Monitoring, SHM, non-contact sensing, nondestructive testing, NDT, Internet of Things, autonomous self-driving drone

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Authors: Felicia N. Obialo, Aliza Wingo, Thomas Wingo

Abstract:

Psychosocial factors such as personality traits and social networks influence cognitive aging and dementia outcomes both positively and negatively. The inherent complexity of these factors makes defining the underlying mechanisms of their influence difficult; however, exploring their interactions affords promise in the field of cognitive aging. The objective of this study was to elucidate some of these interactions by determining the relationship between social network size and dementia outcomes and by determining whether personality traits mediate this relationship. The longitudinal Alzheimer’s Disease (AD) database provided by Rush University’s Religious Orders Study/Memory and Aging Project was utilized to perform retrospective regression and mediation analyses on 3,591 participants. Participants who were cognitively impaired at baseline were excluded, and analyses were adjusted for age, sex, common chronic diseases, and vascular risk factors. Dementia outcome measures included cognitive trajectory, clinical dementia diagnosis, and postmortem beta-amyloid plaque (AB), and neurofibrillary tangle (NT) accumulation. Personality traits included agreeableness (A), conscientiousness (C), extraversion (E), neuroticism (N), and openness (O). The results show a positive correlation between social network size and cognitive trajectory (p-value = 0.004) and a negative relationship between social network size and odds of dementia diagnosis (p = 0.024/ Odds Ratio (OR) = 0.974). Only neuroticism mediates the positive relationship between social network size and cognitive trajectory (p < 2e-16). Agreeableness, extraversion, and neuroticism all mediate the negative relationship between social network size and dementia diagnosis (p=0.098, p=0.054, and p < 2e-16, respectively). All personality traits are independently associated with dementia diagnosis (A: p = 0.016/ OR = 0.959; C: p = 0.000007/ OR = 0.945; E: p = 0.028/ OR = 0.961; N: p = 0.000019/ OR = 1.036; O: p = 0.027/ OR = 0.972). Only conscientiousness and neuroticism are associated with postmortem AD pathologies; specifically, conscientiousness is negatively associated (AB: p = 0.001, NT: p = 0.025) and neuroticism is positively associated with pathologies (AB: p = 0.002, NT: p = 0.002). These results support the study’s objectives, demonstrating that social network size and personality traits are strongly associated with dementia outcomes, particularly the odds of receiving a clinical diagnosis of dementia. Personality traits interact significantly and beneficially with social network size to influence the cognitive trajectory and future dementia diagnosis. These results reinforce previous literature linking social network size to dementia risk and provide novel insight into the differential roles of individual personality traits in cognitive protection.

Keywords: Alzheimer’s disease, cognitive trajectory, personality traits, social network size

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Authors: Basem Kamal Abasakhiroun Farag

Abstract:

Fashion, like many other areas of design, has undergone numerous developments over the centuries. The aim of the article is to recognize and evaluate the importance of advanced technologies in fashion design and to examine how they are transforming the role of contemporary fashion designers by transforming the creative process. It also discusses how contemporary culture is involved in such developments and how it influences fashion design in terms of conceptualization and production. The methodology used is based on examining various examples of the use of technology in fashion design and drawing parallels between what was feasible then and what is feasible today. Comparison of case studies, examples of existing fashion designs and experiences with craft methods; We therefore observe patterns that help us predict the direction of future developments in this area. Discussing the technological elements in fashion design helps us understand the driving force behind the trend. The research presented in the article shows that there is a trend towards significantly increasing interest and progress in the field of fashion technology, leading to the emergence of hybrid artisanal methods. In summary, as fashion technologies advance, their role in clothing production is becoming increasingly important, extending far beyond the humble sewing machine.

Keywords: fashion, identity, such, textiles ambient intelligence, proximity sensors, shape memory materials, sound sensing garments, wearable technology bio textiles, fashion trends, nano textiles, new materials, smart textiles, techno textiles fashion design, functional aesthetics, 3D printing.

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Authors: Abdul Mannan Akhtar

Abstract:

In this paper a novel concept of a self learning smart personalized computer assistant (ACPCA) is established which is a context aware system. Based on user habits, moods, and other routines/situational reactions the system will manage various services and suggestions at appropriate times including what schedule to follow, what to watch, what software to be used, what should be deleted etc. This system will utilize a hybrid fuzzyNeural model to predict what the user will do next and support his actions. This will be done by establishing fuzzy sets of user activities, choices, preferences etc. and utilizing their combinations to predict his moods and immediate preferences. Various application of context aware systems exist separately e.g. on certain websites for music or multimedia suggestions but a personalized autonomous system that could adapt to user’s personality does not exist at present. Due to the novelty and massiveness of this concept, this paper will primarily focus on the problem establishment, product features and its functionality; however a small mini case is also implemented on MATLAB to demonstrate some of the aspects of ACPCA. The mini case involves prediction of user moods, activity, routine and food preference using a hybrid fuzzy-Neural soft computing technique.

Keywords: context aware systems, APCPCA, soft computing techniques, artificial intelligence, fuzzy logic, neural network, mood detection, face detection, activity detection

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Authors: Ayat E. Ali, Christeen R. Aziz, Merna A. Helmy, Mohammed M. Malek, Sherif H. El-Gohary

Abstract:

Goal: Purpose of the project was to make a plastic surgery prediction by using pre-operative images for the plastic surgeries’ patients and to show this prediction on a screen to compare between the current case and the appearance after the surgery. Methods: To this aim, we implemented a software which used data from the internet for facial skin diseases, skin burns, pre-and post-images for plastic surgeries then the post- surgical prediction is done by using K-nearest neighbor (KNN). So we designed and fabricated a smart mirror divided into two parts a screen and a reflective mirror so patient's pre- and post-appearance will be showed at the same time. Results: We worked on some skin diseases like vitiligo, skin burns and wrinkles. We classified the three degrees of burns using KNN classifier with accuracy 60%. We also succeeded in segmenting the area of vitiligo. Our future work will include working on more skin diseases, classify them and give a prediction for the look after the surgery. Also we will go deeper into facial deformities and plastic surgeries like nose reshaping and face slim down. Conclusion: Our project will give a prediction relates strongly to the real look after surgery and decrease different diagnoses among doctors. Significance: The mirror may have broad societal appeal as it will make the distance between patient's satisfaction and the medical standards smaller.

Keywords: k-nearest neighbor (knn), face detection, vitiligo, bone deformity

Procedia PDF Downloads 163