Search results for: carbon nanotubes network

Authors: Ebipatei Victoria Tunyan, T. A. Cao, Cheol Young Ock

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Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.

Keywords: subjective bias detection, machine learning, BERT–BiLSTM–Attention, text classification, natural language processing

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Authors: Kaushik Sathupadi, Sandesh Achar

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Pervasive computing is a growing research field that aims to acknowledge human physical life routines (HPLR) based on body-worn sensors such as MEMS sensors-based technologies. The use of these technologies for human activity recognition is progressively increasing. On the other hand, personalizing human life routines using numerous machine-learning techniques has always been an intriguing topic. In contrast, various methods have demonstrated the ability to recognize basic movement patterns. However, it still needs to be improved to anticipate the dynamics of human living patterns. This study introduces state-of-the-art techniques for recognizing static and dy-namic patterns and forecasting those challenging activities from multi-fused sensors. Further-more, numerous MEMS signals are extracted from one self-annotated IM-WSHA dataset and two benchmarked datasets. First, we acquired raw data is filtered with z-normalization and denoiser methods. Then, we adopted statistical, local binary pattern, auto-regressive model, and intrinsic time scale decomposition major features for feature extraction from different domains. Next, the acquired features are optimized using maximum relevance and minimum redundancy (mRMR). Finally, the artificial neural network is applied to analyze the whole system's performance. As a result, we attained a 90.27% recognition rate for the self-annotated dataset, while the HARTH and KU-HAR achieved 83% on nine living activities and 90.94% on 18 static and dynamic routines. Thus, the proposed HPLR system outperformed other state-of-the-art systems when evaluated with other methods in the literature.

Keywords: artificial intelligence, machine learning, gait analysis, local binary pattern (LBP), statistical features, micro-electro-mechanical systems (MEMS), maximum relevance and minimum re-dundancy (MRMR)

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Authors: Anna Rhodora A. Solar, Jan Emil N. Langomez

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Social Media plays a crucial role in influencing Philippine public opinion with regard to a variety of socio-political issues. This became evident in the massacre of 44 members of the Special Action Force (SAF 44) tasked by the Philippine government to capture one of the US Federal Bureau of Investigation’s most wanted terrorists. The incident was said to be perpetrated by members of the Moro Islamic Liberation Front and the Bangsamoro Islamic Freedom Fighters. Part of the online discourse within Philippine cyberspace sparked intense debates on Filipino Muslim identity, with several Facebook viral posts linking Islam as a factor to the tragic event. Facebook is considered to be the most popular social media platform in the Philippines. As such, this begs the question of the extent to which social media, specifically Facebook, shape the perceptions of Filipinos on Filipino Muslims. This study utilizes Habermas’ theory of communicative action as it offers an explanation on how public sphere such as social media could be a network for communicating information and points of view through free and open dialogue among equal citizens to come to an understanding or common perception. However, the paper argues that communicative action which is aimed at reaching understanding free from force, and strategic action which is aimed at convincing someone through argumentation may not necessarily be mutually exclusive since reaching an understanding can also be considered as a result of convincing someone through argumentation. Moreover, actors may clash one another in their ideas before reaching common understanding, hence the presence of force. Utilizing content analysis on the Facebook posts with Islamic component that went viral after the massacre of the SAF 44, this paper argues that framing the image of Filipino Muslims through Facebook reflects both communicative and strategic actions. Moreover, comment threads on viral posts manifest force albeit implicit.

Keywords: communication, Muslim, Philippines, social media

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Authors: Abubakar Muhammad Hammari, Usman Dadum Hamza, Maryam Ibrahim, Kabir Garba, Idris Muhammad Misau, .

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Pharmaceuticals are increasingly present in water systems, posing threats to ecosystems and human health. The effective treatment of pharmaceutical wastewater presents a significant challenge due to the complex and diverse organic and inorganic contaminants it contains. Conventional treatment methods often struggle to completely remove these pollutants due to their stability and water solubility, leading to environmental concerns and potential health risks. This research proposes the use of cellulose nanocrystals (CNCs) derived from agricultural waste as efficient and sustainable adsorbents for pharmaceutical wastewater treatment. CNCs offer high surface area, biodegradability, and low cost compared to existing options. This study evaluates the production, characterization, adsorption properties, and reusability of cellulose nanocrystals (CNCs) derived from waste paper (CNC-WP), rice husk (CNC-RH), and groundnut shell (CNC-GS). The percentage yield of CNCs was highest from wastepaper at 50.67%, followed by groundnut shell at 33.40% and rice husk at 26.46%. X-ray diffraction (XRD) confirmed the cellulose crystalline structure across all samples while scanning electron microscopy (SEM) revealed a needle-like morphology with size distribution variations. Energy-dispersive X-ray spectroscopy (EDX) identified carbon and oxygen as the primary elements, with minor residual inorganic materials varying by source. BET analysis indicated high surface areas for all CNCs, with CNC-RH exhibiting the highest value (464.592 m²/g), suggesting a more porous structure. The pore sizes of all samples fell within the meso-pore range (2.108 nm to 2.153 nm). Adsorption studies focused on metronidazole (MNZ) removal using CNC-WP. Isotherm models, including Langmuir and Sips, described the equilibrium between MNZ concentration and adsorption onto CNC-WP, showing the best fit with R² values exceeding 0.95. The adsorption process was favourable, with monolayer coverage and potential binding energy heterogeneity. Kinetic modelling identified the pseudo-second-order model as the best fit (R² = 1, SSE = 5.00 x 10-₇), indicating chemisorption as the predominant mechanism. Thermodynamic analysis revealed negative ΔG values at all temperatures, indicating spontaneous adsorption, with more favourable adsorption at higher temperatures. The adsorption process was exothermic, as indicated by negative ΔH values. Reusability studies demonstrated that CNC-WP retained high MNZ removal efficiency, with a modest decrease from 99.59% to 89.11% over ten regeneration cycles. This study highlights the efficiency of wastepaper as a raw material for CNC production and its potential for effective and reusable MNZ adsorption.

Keywords: cellulose nanocrystals (CNCs), adsorption efficiency, metronidazole removal, reusability

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Authors: Anuradha Sajjanhar

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The rise of authoritarian populist regimes has been accompanied by hardened nationalism and heightened divisions between 'us' and 'them'. Political actors reinforce these sentiments through coercion, but also through inciting fear about imagined threats and by transforming public discourse about policy concerns. Extremist ideas can penetrate national policy, as newly appointed intellectuals and 'experts' in knowledge-producing institutions, such as government committees, universities, and think tanks, succeed in transforming public discourse. While attacking left and liberal academics, universities, and the press, the current Indian government is building new institutions to provide authority to its particularly rigid, nationalist discourse. This paper examines the building of a Hindu-nationalist intellectual ecosystem in India, interrogating the key role of hyper-nationalist think tanks. While some are explicit about their political and ideological leanings, others claim neutrality and pursue their agenda through coded technocratic language and resonant historical narratives. Their key is to change thinking by normalizing it. Six years before winning the election in 2014, India’s Hindu-nationalist party, the BJP, put together its own network of elite policy experts. In a national newspaper, the vice-president of the BJP described this as an intentional shift: from 'being action-oriented to solidifying its ideological underpinnings in a policy framework'. When the BJP came to power in 2014, 'experts' from these think tanks filled key positions in the central government. The BJP has since been circulating dominant ideas of Hindu supremacy through regional parties, grassroots political organisations, and civil society organisations. These think tanks have the authority to articulate and legitimate Hindu nationalism within a credible technocratic policy framework. This paper is based on ethnography and over 50 interviews in New Delhi, before and after the BJP’s staggering election victory in 2019. It outlines the party’s attempt to take over existing institutions while developing its own cadre of nationalist policy-making professionals.

Keywords: ideology, politics, South Asia, technocracy

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Authors: Mohsin Ejaz, Shiao-Wei Kuo

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The growing production and exploitation of fossil fuels have placed human society in serious environmental issues. As a result, it's critical to design efficient and eco-friendly energy production and storage techniques. Porous organic polymers (POPs) are multi-dimensional porous network materials developed through the formation of covalent bonds between different organic building blocks that possess distinct geometries and topologies. POPs have tunable porosities and high surface area making them a good candidate for an effective electrode material in energy storage applications. Herein, we prepared a fully benzoxazine-based porous organic polymers (TPA–DHTP–BZ POP) through sonogashira coupling of dihydroxyterephthalaldehyde (DHPT) and triphenylamine (TPA) containing benzoxazine (BZ) monomers. Firstly, both BZ monomers (TPA-BZ-Br and DHTP-BZ-Ea) were synthesized by three steps, including Schiff base, reduction, and mannich condensation reaction. Finally, the TPA–DHTP–BZ POP was prepared through the sonogashira coupling reaction of brominated monomer (TPA-BZ-Br) and ethynyl monomer (DHTP-BZ-Ea). Fourier transform infrared (FTIR) and solid-state nuclear magnetic resonance (NMR) spectroscopy confirmed the successful synthesis of monomers as well as POP. The porosity of TPA–DHTP–BZ POP was investigated by the N₂ absorption technique and showed a Brunauer–Emmett–Teller (BET) surface area of 196 m² g−¹, pore size 2.13 nm and pore volume of 0.54 cm³ g−¹, respectively. The TPA–DHTP–BZ POP experienced thermal ring-opening polymerization, resulting in poly (TPA–DHTP–BZ) POP having strong inter and intramolecular hydrogen bonds formed by phenolic groups and Mannich bridges, thereby enhancing CO₂ capture and supercapacitive performance. The poly(TPA–DHTP–BZ) POP demonstrated a remarkable CO₂ capture of 3.28 mmol g−¹ and a specific capacitance of 67 F g−¹ at 0.5 A g−¹. Thus, poly(TPA–DHTP–BZ) POP could potentially be used for energy storage and CO₂ capture applications.

Keywords: porous organic polymer, benzoxazine, sonogashira coupling, CO₂, supercapacitor

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Authors: Geanderson Eduardo Ambrósio, Dênis Antônio Da Cunha, Marcel Viana Pires

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Historically, human development has been based on economic gains associated with intensive energy activities, which often are exhaustive in the emission of Greenhouse Gases (GHGs). It requires the establishment of targets for mitigation of GHGs in order to disassociate the human development from emissions and prevent further climate change. Brazil presents itself as one of the most GHGs emitters and it is of critical importance to discuss such reductions in intra-national framework with the objective of distributional equity to explore its full mitigation potential without compromising the development of less developed societies. This research displays some incipient considerations about which Brazil’s micro-regions should reduce, when the reductions should be initiated and what its magnitude should be. We started with the methodological assumption that human development and GHGs emissions arise in the future as their behavior was observed in the past. Furthermore, we assume that once a micro-region became developed, it is able to maintain gains in human development without the need of keep growing GHGs emissions rates. The human development index and the carbon dioxide equivalent emissions (CO2e) were extrapolated to the year 2050, which allowed us to calculate when the micro-regions will become developed and the mass of GHG’s emitted. The results indicate that Brazil must throw 300 GT CO2e in the atmosphere between 2011 and 2050, of which only 50 GT will be issued by micro-regions before it’s develop and 250 GT will be released after development. We also determined national mitigation targets and structured reduction schemes where only the developed micro-regions would be required to reduce. The micro-region of São Paulo, the most developed of the country, should be also the one that reduces emissions at most, emitting, in 2050, 90% less than the value observed in 2010. On the other hand, less developed micro-regions will be responsible for less impactful reductions, i.e. Vale do Ipanema will issue in 2050 only 10% below the value observed in 2010. Such methodological assumption would lead the country to issue, in 2050, 56.5% lower than that observed in 2010, so that the cumulative emissions between 2011 and 2050 would reduce by 130 GT CO2e over the initial projection. The fact of associating the magnitude of the reductions to the level of human development of the micro-regions encourages the adoption of policies that favor both variables as the governmental planner will have to deal with both the increasing demand for higher standards of living and with the increasing magnitude of reducing emissions. However, if economic agents do not act proactively in local and national level, the country is closer to the scenario in which emits more than the one in which mitigates emissions. The research highlighted the importance of considering the heterogeneity in determining individual mitigation targets and also ratified the theoretical and methodological feasibility to allocate larger share of contribution for those who historically emitted more. It is understood that the proposals and discussions presented should be considered in mitigation policy formulation in Brazil regardless of the adopted reduction target.

Keywords: greenhouse gases, human development, mitigation, intensive energy activities

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Authors: Guilherme M. Pereira, Kimmo Teinïla, Danilo Custódio, Risto Hillamo, Célia Alves, Pérola de C. Vasconcellos

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South American large cities often present serious air pollution problems and their atmosphere composition is influenced by a variety of emissions sources. The South American Emissions Megacities, and Climate project (SAEMC) has focused on the study of emissions and its influence on climate in the South American largest cities and it also included Lima (Peru) and Medellin (Colombia), sites where few studies of the genre were done. Lima is a coastal city with more than 8 million inhabitants and the second largest city in South America. Medellin is a 2.5 million inhabitants city and second largest city in Colombia; it is situated in a valley. The samples were collected in quartz fiber filters in high volume samplers (Hi-Vol), in 24 hours of sampling. The samples were collected in intensive campaigns in both sites, in July, 2010. Several species were determined in the aerosol samples of Lima and Medellin. Organic and elemental carbon (OC and EC) in thermal-optical analysis; biomass burning tracers (levoglucosan - Lev, mannosan - Man and galactosan - Gal) in high-performance anion exchange ion chromatography with mass spectrometer detection; water soluble ions in ion chromatography. The average particulate matter was similar for both campaigns, the PM10 concentrations were above the recommended by World Health Organization (50 µg m⁻³ – daily limit) in 40% of the samples in Medellin, while in Lima it was above that value in 15% of the samples. The average total ions concentration was higher in Lima (17450 ng m⁻³ in Lima and 3816 ng m⁻³ in Medellin) and the average concentrations of sodium and chloride were higher in this site, these species also had better correlations (Pearson’s coefficient = 0,63); suggesting a higher influence of marine aerosol in the site due its location in the coast. Sulphate concentrations were also much higher at Lima site; which may be explained by a higher influence of marine originated sulphate. However, the OC, EC and monosaccharides average concentrations were higher at Medellin site; this may be due to the lower dispersion of pollutants due to the site’s location and a larger influence of biomass burning sources. The levoglucosan average concentration was 95 ng m⁻³ for Medellin and 16 ng m⁻³ and OC was well correlated with levoglucosan (Pearson’s coefficient = 0,86) in Medellin; suggesting a higher influence of biomass burning over the organic aerosol in this site. The Lev/Man ratio is often related to the type of biomass burned and was close to 18, similar to the observed in previous studies done at biomass burning impacted sites in the Amazon region; backward trajectories also suggested the transport of aerosol from that region. Biomass burning appears to have a larger influence on the air quality in Medellin, in addition the vehicular emissions; while Lima showed a larger influence of marine aerosol during the study period.

Keywords: aerosol transport, atmospheric particulate matter, biomass burning, SAEMC project

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Authors: Kuo-Dung Chiou, Yen-Xue Chen, Chia-Ying Chang

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This study uses AI technology to establish an expert system and establish a fruit appearance database for pineapples and custard apples. It collects images based on appearance defects and fruit maturity. It uses deep learning to detect the location of the fruit and can detect the appearance of the fruit in real-time. Flaws and maturity. In addition, a hyperspectral camera was used to scan pineapples and custard apples, and the light reflection at different frequency bands was used to find the key frequency band for pectin softening in post-ripe fruits. Conducted a large number of multispectral image collection and data analysis to establish a database of Pineapple Custard Apple and Big Eyed Custard Apple, which includes a high-definition color image database, a hyperspectral database in the 377~1020 nm frequency band, and five frequency band images (450, 500, 670, 720, 800nm) multispectral database, which collects 4896 images and manually labeled ground truth; 26 hyperspectral pineapple custard apple fruits (520 images each); multispectral custard apple 168 fruits (5 images each). Using the color image database to train deep learning Yolo v4's pre-training network architecture and adding the training weights established by the fruit database, real-time detection performance is achieved, and the recognition rate reaches over 97.96%. We also used multispectral to take a large number of continuous shots and calculated the difference and average ratio of the fruit in the 670 and 720nm frequency bands. They all have the same trend. The value increases until maturity, and the value will decrease after maturity. Subsequently, the sub-bands will be added to analyze further the numerical analysis of sugar content and moisture, and the absolute value of maturity and the data curve of maturity will be found.

Keywords: hyperspectral image, fruit firmness, deep learning, automatic detection, automatic measurement, intelligent labor saving

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Authors: L. Asaro, M. Gratton, S. Seghar, N. Poirot, N. Ait Hocine

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Rubber waste disposal is an environmental problem. Particularly, many researches are centered in the management of discarded tires. In spite of all different ways of handling used tires, the most common is to deposit them in a landfill, creating a stock of tires. These stocks can cause fire danger and provide ambient for rodents, mosquitoes and other pests, causing health hazards and environmental problems. Because of the three-dimensional structure of the rubbers and their specific composition that include several additives, their recycling is a current technological challenge. The technique which can break down the crosslink bonds in the rubber is called devulcanization. Strictly, devulcanization can be defined as a process where poly-, di-, and mono-sulfidic bonds, formed during vulcanization, are totally or partially broken. In the recent years, super critical carbon dioxide (scCO₂) was proposed as a green devulcanization atmosphere. This is because it is chemically inactive, nontoxic, nonflammable and inexpensive. Its critical point can be easily reached (31.1 °C and 7.38 MPa), and residual scCO₂ in the devulcanized rubber can be easily and rapidly removed by releasing pressure. In this study thermomechanical devulcanization of ground tire rubber (GTR) was performed in a twin screw extruder under diverse operation conditions. Supercritical CO₂ was added in different quantities to promote the devulcanization. Temperature, screw speed and quantity of CO₂ were the parameters that were varied during the process. The devulcanized rubber was characterized by its devulcanization percent and crosslink density by swelling in toluene. Infrared spectroscopy (FTIR) and Gel permeation chromatography (GPC) were also done, and the results were related with the Mooney viscosity. The results showed that the crosslink density decreases as the extruder temperature and speed increases, and, as expected, the soluble fraction increase with both parameters. The Mooney viscosity of the devulcanized rubber decreases as the extruder temperature increases. The reached values were in good correlation (R= 0.96) with de the soluble fraction. In order to analyze if the devulcanization was caused by main chains or crosslink scission, the Horikx's theory was used. Results showed that all tests fall in the curve that corresponds to the sulfur bond scission, which indicates that the devulcanization has successfully happened without degradation of the rubber. In the spectra obtained by FTIR, it was observed that none of the characteristic peaks of the GTR were modified by the different devulcanization conditions. This was expected, because due to the low sulfur content (~1.4 phr) and the multiphasic composition of the GTR, it is very difficult to evaluate the devulcanization by this technique. The lowest crosslink density was reached with 1 cm³/min of CO₂, and the power consumed in that process was also near to the minimum. These results encourage us to do further analyses to better understand the effect of the different conditions on the devulcanization process. The analysis is currently extended to monophasic rubbers as ethylene propylene diene monomer rubber (EPDM) and natural rubber (NR).

Keywords: devulcanization, recycling, rubber, waste

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Authors: Giang Ngo Tinh Nguyen

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Agriculture plays an important role in the economy of Vietnam and coffee is one of most crucial agricultural commodities for exporting but the current farming methods and processing infrastructure could not keep up with the development of the sector. There are many catastrophic impacts on the environment such as deforestation; soil degradation that leads to a decrease in the quality of coffee beans. Therefore, improving supply chain to develop the cultivation of sustainable coffee is one of the most important strategies to boost the coffee industry and create a competitive advantage for Vietnamese coffee in the worldwide market. If all stakeholders in the supply chain network unite together; the sustainable production of coffee will be scaled up and the future of coffee industry will be firmly secured. Buon Ma Thuot city, Dak Lak province is the principal growing region for Vietnamese coffee which accounted for a third of total coffee area in Vietnam. It plays a strategically crucial role in the development of sustainable Vietnamese coffee. Thus, the research is to improve the supply chain of sustainable Vietnamese coffee production in Buon Ma Thuot city, Dak Lak province, Vietnam for the purpose of increasing the yields and export availability as well as helping coffee farmers to be more flexible in an ever-changing market situation. It will help to affirm Vietnamese coffee brand when entering international market; improve the livelihood of farmers and conserve the environment of this area. Besides, after analyzing the data, a logistic regression model is established to explain the relationship between the dependent variable and independent variables to help sustainable coffee organizations forecast the probability of farmer will be having a sustainable certificate with their current situation and help them choose promising candidates to develop sustainable programs. It investigates opinions of local farmers through quantitative surveys. Qualitative interviews are also used to interview local collectors and staff of Trung Nguyen manufacturing company to have an overview of the situation.

Keywords: supply chain management, sustainable agricultural development, sustainable coffee, Vietnamese coffee

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Authors: Havva Nur Tarakci, Bahar Urhan Torun

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The transformation that is seen in every area of life by technology, especially internet technology changes the structure of political communications too. Internet, which is at the top of new communication technologies, affects political communications with its structure in a way that no traditional communication tools ever have and enables interaction and the channel between receiver and sender, and it becomes one of the most effective tools preferred among the political communication applications. This state as a result of technological convergence makes Internet an unobtainable place for political communication campaigns. Political communications, which means every kind of communication strategies that political parties called 'actors of political communications' use with the aim of messaging their opinions and party programmes to their present and potential voters who are a target group for them, is a type of communication that is frequently used also among social media tools at the present day. The electorate consisting of different structures is informed, directed, and managed by social media tools. Political parties easily reach their electorate by these tools without any limitations of both time and place and also are able to take the opinions and reactions of their electorate by the element of interaction that is a feature of social media. In this context, Facebook, which is a place that political parties use in social media at most, is a communication network including in our daily life since 2004. As it is one of the most popular social networks today, it is among the most-visited websites in the global scale. In this way, the research is based on the question, “How do the political parties use Facebook at the campaigns, which they conduct during the election periods, for informing their voters?” and it aims at clarifying the Facebook using practices of the political parties. In direction of this objective the official Facebook accounts of the four political parties (JDP–AKParti, PDP–BDP, RPP-CHP, NMP-MHP), which reach their voters by social media besides other communication tools, are treated, and a frame for the politics of Turkey is formed. The time of examination is constricted with totally two weeks, one week before the mayoral elections and one week after the mayoral elections, when it is supposed that the political parties use their Facebook accounts in full swing. As a research method, the method of content analysis is preferred, and the texts and the visual elements that are gotten are interpreted based on this analysis.

Keywords: Facebook, political communications, social media, electrorate

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Authors: Yaolin Tian, Shanxiong Chen, Fujia Zhao, Xiaoyu Lin, Hailing Xiong

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Ancient books are significant culture inheritors and their background textures convey the potential history information. However, multi-style texture recovery of ancient books has received little attention. Restricted by insufficient ancient textures and complex handling process, the generation of ancient textures confronts with new challenges. For instance, training without sufficient data usually brings about overfitting or mode collapse, so some of the outputs are prone to be fake. Recently, image generation and style transfer based on deep learning are widely applied in computer vision. Breakthroughs within the field make it possible to conduct research upon multi-style texture recovery of ancient books. Under the circumstances, we proposed a network of layout analysis and image fusion system. Firstly, we trained models by using Deep Convolution Generative against Networks (DCGAN) to synthesize multi-style ancient textures; then, we analyzed layouts based on the Position Rearrangement (PR) algorithm that we proposed to adjust the layout structure of foreground content; at last, we realized our goal by fusing rearranged foreground texts and generated background. In experiments, diversified samples such as ancient Yi, Jurchen, Seal were selected as our training sets. Then, the performances of different fine-turning models were gradually improved by adjusting DCGAN model in parameters as well as structures. In order to evaluate the results scientifically, cross entropy loss function and Fréchet Inception Distance (FID) are selected to be our assessment criteria. Eventually, we got model M8 with lowest FID score. Compared with DCGAN model proposed by Radford at el., the FID score of M8 improved by 19.26%, enhancing the quality of the synthetic images profoundly.

Keywords: deep learning, image fusion, image generation, layout analysis

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Authors: Carl-Philipp Valentin Beichert, Marcel Seger

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Digital transformation and climate change require small and medium-sized enterprises (SME) to rethink their way of doing business. Inter-firm collaboration is recognized as helpful means of promoting innovation and competitiveness. In this context, collaborations with start-ups offer valuable opportunities through their innovative products, services, and business models. SMEs, and in particular German craft enterprises, play an important role in the country’s society and economy. Companies in this heterogeneous economic sector have unique characteristics and are limited in their ability to innovate due to their small size and lack of resources. Collaborating with start-ups could help to overcome these shortcomings. To investigate how collaborations emerge and what factors are decisive to successfully drive collaboration, we apply an explorative, qualitative research design. A sample of ten case studies was selected, with the collaboration between a start-up and a craft enterprise forming the unit of analysis. Semi-structured interviews with 20 company representatives allow for a two-sided perspective on the respective collaboration. The interview data is enriched by publicly available data and three expert interviews. As a result, objectives, initiation practices, applied collaboration types, barriers, as well as key success factors could be identified. The results indicate a three-phase collaboration process comprising an initiation, concept, and partner phase (ICP). The ICP framework proposed accordingly highlights the success factors (personal fit, communication, expertise, structure, network) for craft enterprises and start-ups for each collaboration phase. The role of a mediator in the start-up company, with strong expertise in the respective craft sector, is considered an important lever for overcoming barriers such as cultural and communication differences. The ICP framework thus provides promising directions for further research and can help practitioners establish successful collaborations.

Keywords: open innovation, SME, craft businesses, startup collaboration, qualitative research

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Authors: Peifang Hsieh

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New Taipei city faces increasing number of migrant families, in which the needs of children are sometimes neglected due to insufficient support from communities. Moreover, the traditional mindset of disengagement discourages citizens from preemptively identifying families in need in their communities, resulting in delay of prompt intervention from authorities concerned. To safeguard these vulnerable families, New Taipei city develops the 'Integrated Safety-Net Program for High-Risk Families' from 2011 by implementing the following measures: (A) New attitude and action: Instead of passively receiving reported case of high-risk families, the program takes proactive and preemptive approach to detect and respond at early stage, so the cases are prevented from worsening. In addition, cross-departmental integration mechanism is established to meet multiple needs of high-risk families. The children number added to the government care network is greatly increased to over 10,000, which is around 4.4 times the original number before the program. (B) New service points: 2000 city-wide convenience stores are added as service stations so that children in less privileged families can go to any of 24-hour convenience stores across the city to pick up free meals. This greatly increases the approachability to high-risk families. Moreover, the social welfare institutes will be notified with information left in convenience stores by children and follow up with further assistance, greatly enhancing chances of less privileged families being identified. (C) New Key Figures: Mobilize community officers and volunteers to detect and offer on-site assistance. Volunteer organizations within communities are connected to report and offer follow-up services in a more active manner. In total, from 2011 to 2015, 54,789 cases are identified through active care, benefiting 82,124 children. In addition, 87.49% family-cases in the program receiving comprehensive social assistance are no longer at high risk.

Keywords: cross department, high-risk families, public-private partnership, integrated safety net

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Authors: Lei Li, Ping Yin, Haneen Khreis

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Stroke is the second leading cause of death and a third leading cause of death and disability worldwide in 2019. Given the significant role of environmental factors in stroke development and progression, it is essential to investigate the effect of air pollution on stroke occurrence while considering the modifying effects of meteorological variables. This study aimed to evaluate the association between short-term exposure to air pollution and the incidence of stroke subtypes in Shenzhen, China, and to explore the potential interactions of meteorological factors with air pollutants. The study analyzed data from January 1, 2006, to December 31, 2014, including 88,214 cases of ischemic stroke and 30,433 cases of hemorrhagic stroke among residents of Shenzhen. Using a time-stratified case–crossover design with conditional quasi-Poisson regression, the study estimated the percentage changes in stroke morbidity associated with short-term exposure to nitrogen dioxide (NO₂), sulfur dioxide (SO₂), particulate matter less than 10 mm in aerodynamic diameter (PM10), carbon monoxide (CO), and ozone (O₃). A five-day moving average of air pollution was applied to capture the cumulative effects of air pollution. The estimates were further stratified by sex, age, education level, and season. The additive and multiplicative interaction between air pollutants and meteorologic variables were assessed by the relative excess risk due to interaction (RERI) and adding the interactive term into the main model, respectively. The study found that NO₂ was positively associated with ischemic stroke occurrence throughout the year and in the cold season (November through April), with a stronger effect observed among men. Each 10 μg/m³ increment in the five-day moving average of NO₂ was associated with a 2.38% (95% confidence interval was 1.36% to 3.41%) increase in the risk of ischemic stroke over the whole year and a 3.36% (2.04% to 4.69%) increase in the cold season. The harmful effect of CO on ischemic stroke was observed only in the cold season, with each 1 mg/m³ increment in the five-day moving average of CO increasing the risk by 12.34% (3.85% to 21.51%). There was no statistically significant additive interaction between individual air pollutants and temperature or relative humidity, as demonstrated by the RERI. The interaction term in the model showed a multiplicative antagonistic effect between NO₂ and temperature (p-value=0.0268). For hemorrhagic stroke, no evidence of the effects of any individual air pollutants was found in the whole population. However, the RERI indicated a statistically additive and multiplicative interaction of temperature on the effects of PM10 and O₃ on hemorrhagic stroke onset. Therefore, the insignificant conclusion should be interpreted with caution. The study suggests that environmental NO₂ and CO might increase the morbidity of ischemic stroke, particularly during the cold season. These findings could help inform policy decisions aimed at reducing air pollution levels to prevent stroke and other health conditions. Additionally, the study provides valuable insights into the interaction between air pollution and meteorological variables, which underscores the need for further research into the complex relationship between environmental factors and health.

Keywords: air pollution, meteorological variables, interactive effect, seasonal pattern, stroke

Procedia PDF Downloads 89

Authors: Cristobal Miralles Insa

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The network of chairs of the "Valencian Public System of Social Services" (VPSSS) is sponsored by the Valencian Institute of Training, Research, and Quality in Social Services and aims to promote research, dissemination, and evaluation of the needs that arise in the field of the public system of social services. It also seeks to transfer knowledge to foster the development of public policies in this field. Given that it is an Interuniversity Chair among the five public universities in Valencia, there is coordination of complementary themes and roles for this objective, with Universitat Politènica de València focusing primarily on promoting innovation and social entrepreneurship to address multiple social challenges through its platform INSSPIRA. This approach is aimed at the entire university community and its various interest groups, carrying out research, teaching, and dissemination activities that promote social inclusion, personal development, and autonomy for groups in situations of vulnerability, lack of protection, dependence, or social urgency. Although it focuses on the Valencian context, both the issues in this context and the tools in process to address them, often have a universal and scalable character and has been inspiring for the innovation system of UPV. This entrepreneurial incubator goes along from early stages of students on the campus until the so-called “StartUPV” system, where students are challenged with social problems that require creative solutions. Therefore, the Chair is conceived with a holistic spirit and an inspiring vocation that engages the whole university community. In this communication, it is described the entities and individuals participating in this UPV Chair of VPSSS, followed by the presentation of different work lines and objectives for the chair. Subsequently, a description of various activities undertaken to promote innovation in social services are described, where support to teaching and extracurricular activities in this field are exposed. It must be noted that some awareness and dissemination of activities are carried out in a transversal mode as they contribute to different objectives simultaneously; with special focus on Learning-Service approaches that achieved very good results which are also summarized.

Keywords: social innovation, entrepeneurship, university, vulnerable sectors

Procedia PDF Downloads 58

Authors: Younis Jabarzadeh, Rahim Sarvari, Negar Ahmadi Alghalandis

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Entrepreneurship at both individual and organizational level is one of the most driving forces in economic development and leads to growth and competition, job generation and social development. Especially in developing countries, the role of entrepreneurship in economic and social prosperity is more emphasized. But the effect of global economic development on the environment is undeniable, especially in negative ways, and there is a need to rethink current business models and the way entrepreneurs act to introduce new businesses to address and embed environmental issues in order to achieve sustainable development. In this paper, green or sustainable entrepreneurship is addressed in Iran to identify challenges and barriers entrepreneurs in the economic and social sectors face in developing green business solutions. Sustainable or green entrepreneurship has been gaining interest among scholars in recent years and addressing its challenges and barriers need much more attention to fill the gap in the literature and facilitate the way those entrepreneurs are pursuing. This research comprised of two main phases: qualitative and quantitative. At qualitative phase, after a thorough literature review, fuzzy Delphi method is utilized to verify those challenges and barriers by gathering a panel of experts and surveying them. In this phase, several other contextually related factors were added to the list of identified barriers and challenges mentioned in the literature. Then, at the quantitative phase, Interpretive Structural Modeling is applied to construct a network of interactions among those barriers identified at the previous phase. Again, a panel of subject matter experts comprised of academic and industry experts was surveyed. The results of this study can be used by policymakers in both the public and industry sector, to introduce more systematic solutions to eliminate those barriers and help entrepreneurs overcome challenges of sustainable entrepreneurship. It also contributes to the literature as the first research in this type which deals with the barriers of sustainable entrepreneurship and explores their interaction.

Keywords: green entrepreneurship, barriers, fuzzy Delphi method, interpretive structural modeling

Procedia PDF Downloads 167

Authors: Léa Caban, Lucile Soudani, Julien Berger, Armelle Nouviaire, Emilio Bastidas-Arteaga

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Improvement of the thermal performance of buildings is a high concern for the construction industry. With the increase in environmental issues, new types of construction materials are being developed. These include bio-based insulation materials. They capture carbon dioxide, can be produced locally, and have good thermal performance. However, their behavior with respect to moisture transfer is still facing some issues. With a high porosity, the mass transfer is more important in those materials than in mineral insulation ones. Therefore, they can be more sensitive to moisture disorders such as mold growth, condensation risks or decrease of the wall energy efficiency. For this reason, the initial moisture content on the construction site is a piece of crucial knowledge. Measuring moisture content in a laboratory is a mastered task. Diverse methods exist but the easiest and the reference one is gravimetric. A material is weighed dry and wet, and its moisture content is mathematically deduced. Non-destructive methods (NDT) are promising tools to determine in an easy and fast way the moisture content in a laboratory or on construction sites. However, the quality and reliability of the measures are influenced by several factors. Classical NDT portable devices usable on-site measure the capacity or the resistivity of materials. Water’s electrical properties are very different from those of construction materials, which is why the water content can be deduced from these measurements. However, most moisture meters are made to measure wooden materials, and some of them can be adapted for construction materials with calibration curves. Anyway, these devices are almost never calibrated for insulation materials. The main objective of this study is to determine the reliability of moisture meters in the measurement of biobased insulation materials. The determination of which one of the capacitive or resistive methods is the most accurate and which device gives the best result is made. Several biobased insulation materials are tested. Recycled cotton, two types of wood fibers of different densities (53 and 158 kg/m3) and a mix of linen, cotton, and hemp. It seems important to assess the behavior of a mineral material, so glass wool is also measured. An experimental campaign is performed in a laboratory. A gravimetric measurement of the materials is carried out for every level of moisture content. These levels are set using a climatic chamber and by setting the relative humidity level for a constant temperature. The mass-based moisture contents measured are considered as references values, and the results given by moisture meters are compared to them. A complete analysis of the uncertainty measurement is also done. These results are used to analyze the reliability of moisture meters depending on the materials and their water content. This makes it possible to determine whether the moisture meters are reliable, and which one is the most accurate. It will then be used for future measurements on construction sites to assess the initial hygrothermal state of insulation materials, on both new-build and renovation projects.

Keywords: capacitance method, electrical resistance method, insulation materials, moisture transfer, non-destructive testing

Procedia PDF Downloads 127

Authors: Yananda Siraphatthada

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The objectives of this research were to study the level of influencing factors, leadership, supply chain management, innovation, competitive advantages, business success, and affecting factors to the business success of the mobile phone system service providers in Bangkok Metropolitan. This research was done by the quantitative approach and the qualitative approach. The quantitative approach was used for questionnaires to collect data from the 331 mobile service shop managers franchised by AIS, Dtac and TrueMove. The mobile phone system service providers/shop managers were randomly stratified and proportionally allocated into subgroups exclusive to the number of the providers in each network. In terms of qualitative method, there were in-depth interviews of 6 mobile service providers/managers of Telewiz and Dtac and TrueMove shop to find the agreement or disagreement with the content analysis method. Descriptive Statistics, including Frequency, Percentage, Means and Standard Deviation were employed; also, the Structural Equation Model (SEM) was used as a tool for data analysis. The content analysis method was applied to identify key patterns emerging from the interview responses. The two data sets were brought together for comparing and contrasting to make the findings, providing triangulation to enrich result interpretation. It revealed that the level of the influencing factors – leadership, innovation management, supply chain management, and business competitiveness had an impact at a great level, but that the level of factors, innovation and the business, financial success and nonbusiness financial success of the mobile phone system service providers in Bangkok Metropolitan, is at the highest level. Moreover, the business influencing factors, competitive advantages in the business of mobile system service providers which were leadership, supply chain management, innovation management, business advantages, and business success, had statistical significance at .01 which corresponded to the data from the interviews.

Keywords: mobile service providers, facilitating factors, Bangkok Metropolitan, business success

Procedia PDF Downloads 350

Authors: Pahirangan Sivapatham, Barbara Esser, Andreas Grimmel

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In times of limited public funds and, in particular, an increased social, environmental awareness, as well as the limited availability of construction materials, sustainable and resource-saving pavement management system, is becoming more and more important. Therefore, the knowledge about the condition of the structural substances, particularly bearing capacity and its consideration while planning the maintenance measures of the subordinate network, i.e., state and municipal roads unavoidable. According to the experience, the recommended ride speed of the Traffic Speed Deflectometer (TSD) shall be higher than 40 km/h. Holding of this speed on the intra-urban roads is nearly not possible because of intersections and traffic lights as well as the speed limit. A sufficient background of experience for the evaluation of bearing capacity measurements with TSD in the range of lower speeds is not available yet. The aim of this study is to determine the possible lowest ride speed of the TSD while the bearing capacity measurement on the intra-urban roads. The manufacturer of the TSD used in this study states that the measurements can be conducted at a ride speed of higher than 5 km/h. It is well known that with decreasing ride speed, the viscous fractions in the response of the asphalt pavement increase. This must be taken into account when evaluating the bearing capacity data. In the scope of this study, several measurements were carried out at different speeds between 10 km/h and 60 km/h on the selected intra-urban roads with Pavement-Scanner of the University of Wuppertal, which is equipped with TSD. Pavement-Scanner is able to continuously determine the deflections of asphalt roads in flowing traffic at speeds of up to 80 km/h. The raw data is then aggregated to 10 m mean values so that, as a rule, a bearing capacity characteristic value can be determined for each 10 m road section. By means of analysing of obtained test results, the quality and validity of the determined data rate subject to the riding speed of TSD have been determined. Moreover, the data and pictures of the additional measuring systems of Pavement-Scanners such as High-Speed Road Monitor, Ground Penetration Radar and front cameras can be used to determine and eliminate irregularities in the pavement, which could influence the bearing capacity.

Keywords: bearing capacity measurement, traffic speed deflectometer, inter-urban roads, Pavement-Scanner, structural substance

Procedia PDF Downloads 238

Authors: Saheli Mitra, Ramesh Karri, Praveen K. Mylapalli, Arka. B. Dey, Gourav Bhattacharya, Gouriprasanna Roy, Syed M. Kamil, Surajit Dhara, Sunil K. Sinha, Sajal K. Ghosh

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The most well-known structures of lyotropic liquid crystalline systems are the two dimensional hexagonal phase of cylindrical micelles with a positive interfacial curvature and the lamellar phase of flat bilayers with zero interfacial curvature. In aqueous solution of surfactants, the concentration dependent phase transitions have been investigated extensively. However, instead of changing the surfactant concentrations, the local curvature of an aggregate can be altered by tuning the electrostatic interactions among the constituent molecules. Intermediate phases with non-uniform interfacial curvature are still unexplored steps to understand the route of phase transition from hexagonal to lamellar. Understanding such structural evolution in lyotropic liquid crystalline systems is important as it decides the complex rheological behavior of the system, which is one of the main interests of the soft matter industry. Sodium dodecyl sulfate (SDS) is an anionic surfactant and can be considered as a unique system to tune the electrostatics by cationic additives. In present study, imidazolium-based ionic liquids (ILs) with different number of carbon atoms in their single hydrocarbon chain were used as the additive in the aqueous solution of SDS. At a fixed concentration of total non-aqueous components (SDS and IL), the molar ratio of these components was changed, which effectively altered the electrostatic interactions between the SDS molecules. As a result, the local curvature is observed to modify, and correspondingly, the structure of the hexagonal liquid crystalline phases are transformed into other phases. Polarizing optical microscopy of SDS and imidazole-based-IL systems have exhibited different textures of the liquid crystalline phases as a function of increasing concentration of the ILs. The small angle synchrotron x-ray diffraction (SAXD) study has indicated the hexagonal phase of direct cylindrical micelles to transform to a rectangular phase at the presence of short (two hydrocarbons) chain IL. However, the hexagonal phase is transformed to a lamellar phase at the presence of long (ten hydrocarbons) chain IL. Interestingly, at the presence of a medium (four hydrocarbons) chain IL, the hexagonal phase is transformed to another hexagonal phase of direct cylindrical micelles through the lamellar phase. To the best of our knowledge, such a phase sequence has not been reported earlier. Even though the small angle x-ray diffraction study has revealed the lattice parameters of these phases to be similar to each other, their rheological behavior has been distinctly different. These rheological studies have shed lights on how these phases differ in their viscoelastic behavior. Finally, the packing parameters, calculated for these phases based on the geometry of the aggregates, have explained the formation of the self-assembled aggregates.

Keywords: lyotropic liquid crystals, polarizing optical microscopy, rheology, surfactants, small angle x-ray diffraction

Procedia PDF Downloads 140

Authors: Rahul Paul, Peter Mctaggart, Luke Skinner

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Maintaining public safety and network reliability are the core objectives of all electricity distributors globally. For many electricity distributors, managing vegetation clearances from their above ground assets (poles and conductors) is the most important and costly risk mitigation control employed to meet these objectives. Light Detection And Ranging (LiDAR) is widely used by utilities as a cost-effective method to inspect their spatially-distributed assets at scale, often captured using high powered LiDAR scanners attached to fixed wing or rotary aircraft. The resulting 3D point cloud model is used by these utilities to perform engineering grade measurements that guide the prioritisation of vegetation cutting programs. Advances in computer vision and machine-learning approaches are increasingly applied to increase automation and reduce inspection costs and time; however, real-world LiDAR capture variables (e.g., aircraft speed and height) create complexity, noise, and missing data, reducing the effectiveness of these approaches. This paper proposes a method for identifying each conductor from LiDAR data via clustering methods that can precisely reconstruct conductors in complex real-world configurations in the presence of high levels of noise. It proposes 3D catenary models for individual clusters fitted to the captured LiDAR data points using a least square method. An iterative learning process is used to identify potential conductor models between pole pairs. The proposed method identifies the optimum parameters of the catenary function and then fits the LiDAR points to reconstruct the conductors.

Keywords: point cloud, LİDAR data, machine learning, computer vision, catenary curve, vegetation management, utility industry

Procedia PDF Downloads 101

Authors: Lauren B. Birney

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Summer STEM Institute for Middle and High School Students at Pace University The STEM Collaboratory NYC® Summer Fellows Institute takes place on Pace University’s New York City campus during July and provides the following key features for all participants: (i) individual meetings with Pace faculty to discuss and refine future educational goals; (ii) mentorship, guidance, and new friendships with program leaders; and (iii) guest lectures from professionals in STEM disciplines and businesses. The Summer STEM Institute allows middle school and high school students to work in teams to conceptualize, develop, and build native mobile applications that teach and reinforce skills in the sciences and mathematics. These workshops enhance students’STEM problem solving techniques and teach advanced methods of computer science and engineering. Topics include: big data and analytics at the Big Data lab at Seidenberg, Data Science focused on social and environmental advancement and betterment; Natural Disasters and their Societal Influences; Algal Blooms and Environmental Impacts; Green CitiesNYC; STEM jobs and growth opportunities for the future; renew able energy and sustainable infrastructure; and climate and the economy. In order to better align the existing Summer STEM, Institute with the CCERS model and expand the overall network, Pace is actively recruiting new content area specialists from STEM industries and private sector enterprises to participate in an enhanced summer institute in order to1) nurture student progress and connect summer learning to school year curriculum, 2) increase peer-to-peer collaboration amongst STEM professionals and private sector technologists, and 3) develop long term funding and sponsorship opportunities for corporate sector partners to support CCERS schools and programs directly.

Keywords: environmental restoration science, citizen science, data science, STEM

Procedia PDF Downloads 87

Authors: Emily Schuler, Cristina M. S. B. Dias

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The increase of human aging is a phenomenon observed in world scale and allows the experience of several roles within the family. Nowadays grandparents can see their grandchildren growing up and having children, becoming great-grandparents, and thus adding another generation in the network of relationships. Consequently, more and more multigenerational families are emerging, formed by four or even five generations, and therefore more vertically. Thus, the objective of this research was to understand the role of great-grandparents, as well as the intergenerational repercussions of this role in their lives and that of their relatives. More specifically it was intended: to analyze the meaning of being great-grandparents in the family, from the perspective of each generation; identify the activities performed by their great-grandparents; identify the legacy that the great-grandparents wish to convey; characterize the needs and feelings experienced by the great-grandparents and their families; understand intergenerational relations permeated by the presence of great-grandparents among family members. It is a multiple case study with four families consisting of four generations and a family with five generations, thus totaling twenty-two participants; three great-grandmothers, two great-grandfathers, and one great-great-grandmother. As for the other generations, five children, grandchildren, great-grandchildren, and a great-great-grandchild were interviewed. As a research instrument, a semi-directed interview was used, with a specific script for each generation, as well as a questionnaire with the sociodemographic data of the participants. The data were analyzed through thematic content analysis. The main results pointed out the following: 1) As for the feelings experienced when becoming great-grandparents, they reported joy, satisfaction, and gratitude; 2) The support provided by them, most of the time, is of the emotional type; 3) The family relationship appeared quite significant, being characterized especially in the form of visits; 4) Conflicts exist, but seem to be circumvented with wisdom and much respect; 5) The legacies transmitted by them are related to faith, solidarity, education, and order; 6) The meaning of being great-grandmother is intimately linked to the feeling of transcendence, the sense of having fulfilled the purpose of life and also its continuity in grandchildren and great-grandchildren. In other generations, the appreciation of the great-grandparents, perceived as wise people, has been observed and can contribute as teachers to the new generations. It is hoped to give visibility to this generation still little studied in our country.

Keywords: great-grandparents, intergenerational relation, multigenerational families, transgenerational legacies

Procedia PDF Downloads 172

Authors: Zahid Ullah, Atlas Khan

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The rapid advancements in data collection, storage, and processing capabilities have led to an explosion of data in various domains. In this era of big data, mathematical sciences play a crucial role in uncovering valuable insights and driving informed decision-making through data analytics. The purpose of this abstract is to present the latest advances in mathematical sciences and their application in harnessing the power of data analytics. This abstract highlights the interdisciplinary nature of data analytics, showcasing how mathematics intersects with statistics, computer science, and other related fields to develop cutting-edge methodologies. It explores key mathematical techniques such as optimization, mathematical modeling, network analysis, and computational algorithms that underpin effective data analysis and interpretation. The abstract emphasizes the role of mathematical sciences in addressing real-world challenges across different sectors, including finance, healthcare, engineering, social sciences, and beyond. It showcases how mathematical models and statistical methods extract meaningful insights from complex datasets, facilitating evidence-based decision-making and driving innovation. Furthermore, the abstract emphasizes the importance of collaboration and knowledge exchange among researchers, practitioners, and industry professionals. It recognizes the value of interdisciplinary collaborations and the need to bridge the gap between academia and industry to ensure the practical application of mathematical advancements in data analytics. The abstract highlights the significance of ongoing research in mathematical sciences and its impact on data analytics. It emphasizes the need for continued exploration and innovation in mathematical methodologies to tackle emerging challenges in the era of big data and digital transformation. In summary, this abstract sheds light on the advances in mathematical sciences and their pivotal role in unveiling the power of data analytics. It calls for interdisciplinary collaboration, knowledge exchange, and ongoing research to further unlock the potential of mathematical methodologies in addressing complex problems and driving data-driven decision-making in various domains.

Keywords: mathematical sciences, data analytics, advances, unveiling

Procedia PDF Downloads 95

Authors: Abdelhalim. N. Mohammed, Mohammed. Y. Esmail

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In the course of recent decades, medical imaging has been dominated by the use of costly film media for review and archival of medical investigation, however due to developments in networks technologies and common acceptance of a standard digital imaging and communication in medicine (DICOM) another approach in light of World Wide Web was produced. Web technologies successfully used in telemedicine applications, the combination of web technologies together with DICOM used to design a web-based and open source DICOM viewer. The Web server allowance to inquiry and recovery of images and the images viewed/manipulated inside a Web browser without need for any preinstalling software. The dynamic site page for medical images visualization and processing created by using JavaScript and HTML5 advancements. The XAMPP ‘apache server’ is used to create a local web server for testing and deployment of the dynamic site. The web-based viewer connected to multiples devices through local area network (LAN) to distribute the images inside healthcare facilities. The system offers a few focal points over ordinary picture archiving and communication systems (PACS): easy to introduce, maintain and independently platforms that allow images to display and manipulated efficiently, the system also user-friendly and easy to integrate with an existing system that have already been making use of web technologies. The wavelet-based image compression technique on which 2-D discrete wavelet transform used to decompose the image then wavelet coefficients are transmitted by entropy encoding after threshold to decrease transmission time, stockpiling cost and capacity. The performance of compression was estimated by using images quality metrics such as mean square error ‘MSE’, peak signal to noise ratio ‘PSNR’ and compression ratio ‘CR’ that achieved (83.86%) when ‘coif3’ wavelet filter is used.

Keywords: DICOM, discrete wavelet transform, PACS, HIS, LAN

Procedia PDF Downloads 162

Authors: Yimeng Zhang

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Major depressive disorder (MDD) is a prevalent mental health condition with a substantial economic impact and limited treatment options. Acupuncture has gained attention as a promising non-pharmacological intervention for alleviating depressive symptoms. However, its mechanisms and clinical effectiveness remain incompletely understood. This meta-analysis aims to (1) synthesize existing evidence on the mechanisms and clinical effectiveness of acupuncture for depression and (2) compare these findings with pharmacological interventions, providing insights for future research. Evidence from animal models and clinical studies indicates that acupuncture may enhance hippocampal and network neuroplasticity and reduce brain inflammation, potentially alleviating depressive disorders. Clinical studies suggest that acupuncture can effectively relieve primary depression, particularly in milder cases, and is beneficial in managing post-stroke depression, pain-related depression, and postpartum depression, both as a standalone and adjunctive treatment. Notably, combining acupuncture with antidepressant pharmacotherapy appears to enhance treatment outcomes and reduce medication side effects, addressing a critical issue in conventional drug therapy's high dropout rates. This meta-analysis, encompassing 12 studies and 710 participants, draws data from eight digital databases (PubMed, EMBASE, Web of Science, EBSCOhost, CNKI, CBM, Wangfang, and CQVIP) covering the period from 2012 to 2022. Utilizing Stata software 15.0, the meta-analysis employed random-effects and fixed-effects models to assess the distribution of depression in Traditional Chinese Medicine (TCM). The results underscore the substantial evidence supporting acupuncture's beneficial effects on depression. However, the small sample sizes of many clinical trials raise concerns about the generalizability of the findings, indicating a need for further research to validate these outcomes and optimize acupuncture's role in treating depression.

Keywords: Chinese medicine, acupuncture, depression, meta-analysis

Procedia PDF Downloads 37

Authors: Kevin Wang, Jian Ge, Yinan Zhao, Kevin Willis

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Kepler has discovered over 4000 exoplanets and candidates. However, current transit planet detection techniques based on the wavelet analysis and the Box Least Squares (BLS) algorithm have limited sensitivity in detecting minor planets with a low signal-to-noise ratio (SNR) and long periods with only 3-4 repeated signals over the mission lifetime of 4 years. This paper presents a novel precise-period transit signal detection methodology based on a new Graphics Processing Unit (GPU) Fast Folding algorithm in conjunction with a Convolutional Neural Network (CNN) to detect low SNR and/or long-period transit planet signals. A comparison with BLS is conducted on both simulated light curves and real data, demonstrating that the new method has higher speed, sensitivity, and reliability. For instance, the new system can detect transits with SNR as low as three while the performance of BLS drops off quickly around SNR of 7. Meanwhile, the GPU Fast Folding method folds light curves 25 times faster than BLS, a significant gain that allows exoplanet detection to occur at unprecedented period precision. This new method has been tested with all known transit signals with 100% confirmation. In addition, this new method has been successfully applied to the Kepler of Interest (KOI) data and identified a few new Earth-sized Ultra-short period (USP) exoplanet candidates and habitable planet candidates. The results highlight the promise for GPU Fast Folding as a replacement to the traditional BLS algorithm for finding small and/or long-period habitable and Earth-sized planet candidates in-transit data taken with Kepler and other space transit missions such as TESS(Transiting Exoplanet Survey Satellite) and PLATO(PLAnetary Transits and Oscillations of stars).

Keywords: algorithms, astronomy data analysis, deep learning, exoplanet detection methods, small planets, habitable planets, transit photometry

Procedia PDF Downloads 225

Authors: A. Aulinger, A. M. Backes, J. Bieser, V. Matthias, M. Quante

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High concentrations of particles pose a threat to human health. Thus, legal maximum concentrations of PM10 and PM2.5 in ambient air have been steadily decreased over the years. In central Europe, the inorganic species ammonium sulphate and ammonium nitrate make up a large fraction of fine particles. Many studies investigate the influence of emission reductions of sulfur- and nitrogen oxides on aerosol concentration. Here, we focus on the influence of ammonia (NH3) emissions. While emissions of sulphate and nitrogen oxides are quite well known, ammonia emissions are subject to high uncertainty. This is due to the uncertainty of location, amount, time of fertilizer application in agriculture, and the storage and treatment of manure from animal husbandry. For this study, we implemented a crop growth model into the SMOKE emission model. Depending on temperature, local legislation, and crop type individual temporal profiles for fertilizer and manure application are calculated for each model grid cell. Additionally, the diffusion from soils and plants and the direct release from open and closed barns are determined. The emission data was used as input for the Community Multiscale Air Quality (CMAQ) model. Comparisons to observations from the EMEP measurement network indicate that the new ammonia emission module leads to a better agreement of model and observation (for both ammonia and ammonium). Finally, the ammonia emission model was used to create emission scenarios. This includes emissions based on future European legislation, as well as a dynamic evaluation of the influence of different agricultural sectors on particle formation. It was found that a reduction of ammonia emissions by 50% lead to a 24% reduction of total PM2.5 concentrations during winter time in the model domain. The observed reduction was mainly driven by reduced formation of ammonium nitrate. Moreover, emission reductions during winter had a larger impact than during the rest of the year.

Keywords: ammonia, ammonia abatement strategies, ctm, seasonal impact, secondary aerosol formation

Procedia PDF Downloads 351