Search results for: distribution network reconfiguration

Authors: Rahul Agarwal, Ashutosh Singh

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Cervical cancer is one of the women related cancers which starts from the pre-cancerous cells and a fraction of women with pre-cancers of the cervix will develop cervical cancer. Cervical pre-cancers if treated in pre-invasive stage can prevent almost all true cervical squamous cell carcinoma. The present study investigates the genes and pathways that are involved in the progression of cervical cancer and are responsible in transition from pre-invasive stage to other advanced invasive stages. The study used GDS3292 microarray data to identify the stage specific genes in cervical cancer and further to generate the network of the significant genes. The microarray data GDS3292 consists of the expression profiling of 10 normal cervices, 7 HSILs and 21 SCCs samples. The study identifies 70 upregulated and 37 downregulated genes in HSIL stage while 95 upregulated and 60 downregulated genes in SCC stages. Biological process including cell communication, signal transduction are highly enriched in both HSIL and SCC stages of cervical cancer. Further, the ppi interaction of genes involved in HSIL and SCC stages helps in identifying the interacting partners. This work may lead to the identification of potential diagnostic biomarker which can be utilized for early stage detection.

Keywords: cervical cancer, HSIL, microarray, SCC

Procedia PDF Downloads 235

Authors: Qiaosi Li, Frankie Kwan Kit Wong, Tung Fung

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Lightweight unmanned aerial vehicle (UAV) loading with novel sensors offers a low cost approach for data acquisition in complex environment. This study established a framework for applying UAV system in complex environment quick mapping and assessed the performance of UAV-based hyperspectral image and digital surface model (DSM) derived from photogrammetric point clouds for 13 species classification in wetland area Mai Po Inner Deep Bay Ramsar Site, Hong Kong. The study area was part of shallow bay with flat terrain and the major species including reedbed and four mangroves: Kandelia obovata, Aegiceras corniculatum, Acrostichum auerum and Acanthus ilicifolius. Other species involved in various graminaceous plants, tarbor, shrub and invasive species Mikania micrantha. In particular, invasive species climbed up to the mangrove canopy caused damage and morphology change which might increase species distinguishing difficulty. Hyperspectral images were acquired by Headwall Nano sensor with spectral range from 400nm to 1000nm and 0.06m spatial resolution image. A sequence of multi-view RGB images was captured with 0.02m spatial resolution and 75% overlap. Hyperspectral image was corrected for radiative and geometric distortion while high resolution RGB images were matched to generate maximum dense point clouds. Furtherly, a 5 cm grid digital surface model (DSM) was derived from dense point clouds. Multiple feature reduction methods were compared to identify the efficient method and to explore the significant spectral bands in distinguishing different species. Examined methods including stepwise discriminant analysis (DA), support vector machine (SVM) and minimum noise fraction (MNF) transformation. Subsequently, spectral subsets composed of the first 20 most importance bands extracted by SVM, DA and MNF, and multi-source subsets adding extra DSM to 20 spectrum bands were served as input in maximum likelihood classifier (MLC) and SVM classifier to compare the classification result. Classification results showed that feature reduction methods from best to worst are MNF transformation, DA and SVM. MNF transformation accuracy was even higher than all bands input result. Selected bands frequently laid along the green peak, red edge and near infrared. Additionally, DA found that chlorophyll absorption red band and yellow band were also important for species classification. In terms of 3D data, DSM enhanced the discriminant capacity among low plants, arbor and mangrove. Meanwhile, DSM largely reduced misclassification due to the shadow effect and morphological variation of inter-species. In respect to classifier, nonparametric SVM outperformed than MLC for high dimension and multi-source data in this study. SVM classifier tended to produce higher overall accuracy and reduce scattered patches although it costs more time than MLC. The best result was obtained by combining MNF components and DSM in SVM classifier. This study offered a precision species distribution survey solution for inaccessible wetland area with low cost of time and labour. In addition, findings relevant to the positive effect of DSM as well as spectral feature identification indicated that the utility of UAV-borne hyperspectral and photogrammetry deriving 3D data is promising in further research on wetland species such as bio-parameters modelling and biological invasion monitoring.

Keywords: digital surface model (DSM), feature reduction, hyperspectral, photogrammetric point cloud, species mapping, unmanned aerial vehicle (UAV)

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Authors: Maria Areias, Diogo Simões, Ana Figueiredo, Anishur Rahman, Filipa Figueiredo, João Nunes

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It is expected that close to 7 billion people will live in urban areas by 2050. In order to improve the sustainability of the territories and its transition towards circular economy, it’s necessary to understand its metabolism and promote and guide the entrepreneurship answer. The study of a macroeconomic metabolism involves the quantification of the inputs, outputs and storage of energy, water, materials and wastes for an urban region. This quantification and analysis representing one opportunity for the promotion of green entrepreneurship. There are several methods to assess the environmental impacts of an urban territory, such as human and environmental risk assessment (HERA), life cycle assessment (LCA), ecological footprint assessment (EF), material flow analysis (MFA), physical input-output table (PIOT), ecological network analysis (ENA), multicriteria decision analysis (MCDA) among others. However, no consensus exists about which of those assessment methods are best to analyze the sustainability of these complex systems. Taking into account the weaknesses and needs identified, the CiiM - Circular Innovation Inter-Municipality project aims to define an uniform and globally accepted methodology through the integration of various methodologies and dynamic approaches to increase the efficiency of macroeconomic metabolisms and promoting entrepreneurship in a circular economy. The pilot territory considered in CiiM project has a total area of 969,428 ha, comprising a total of 897,256 inhabitants (about 41% of the population of the Center Region). The main economic activities in the pilot territory, which contribute to a gross domestic product of 14.4 billion euros, are: social support activities for the elderly; construction of buildings; road transport of goods, retailing in supermarkets and hypermarkets; mass production of other garments; inpatient health facilities; and the manufacture of other components and accessories for motor vehicles. The region's business network is mostly constituted of micro and small companies (similar to the Central Region of Portugal), with a total of 53,708 companies identified in the CIM Region of Coimbra (39 large companies), 28,146 in the CIM Viseu Dão Lafões (22 large companies) and 24,953 in CIM Beiras and Serra da Estrela (13 large companies). For the construction of the database was taking into account data available at the National Institute of Statistics (INE), General Directorate of Energy and Geology (DGEG), Eurostat, Pordata, Strategy and Planning Office (GEP), Portuguese Environment Agency (APA), Commission for Coordination and Regional Development (CCDR) and Inter-municipal Community (CIM), as well as dedicated databases. In addition to the collection of statistical data, it was necessary to identify and characterize the different stakeholder groups in the pilot territory that are relevant to the different metabolism components under analysis. The CIIM project also adds the potential of a Geographic Information System (GIS) so that it is be possible to obtain geospatial results of the territorial metabolisms (rural and urban) of the pilot region. This platform will be a powerful visualization tool of flows of products/services that occur within the region and will support the stakeholders, improving their circular performance and identifying new business ideas and symbiotic partnerships.

Keywords: circular economy tools, life cycle assessment macroeconomic metabolism, multicriteria decision analysis, decision support tools, circular entrepreneurship, industrial and regional symbiosis

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Authors: Meet Shah, Ankita Aditya, Dhruv Bindra, V. S. Omkar, Aashruti Seervi

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In today's world, we need documents everywhere for a smooth workflow in the identification process or any other security aspects. The current system and techniques which are used for identification need one thing, that is ‘proof of existence’, which involves valid documents, for example, educational, financial, etc. The main issue with the current identity access management system and digital identification process is that the system is centralized in their network, which makes it inefficient. The paper presents the system which resolves all these cited issues. It is based on ‘blockchain’ technology, which is a 'decentralized system'. It allows transactions in a decentralized and immutable manner. The primary notion of the model is to ‘have everything with nothing’. It involves inter-linking required documents of a person with a single identity card so that a person can go anywhere without having the required documents with him/her. The person just needs to be physically present at a place wherein documents are necessary, and using a fingerprint impression and an iris scan print, the rest of the verification will progress. Furthermore, some technical overheads and advancements are listed. This paper also aims to layout its far-vision scenario of blockchain and its impact on future trends.

Keywords: blockchain, decentralized system, fingerprint impression, identity management, iris scan

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Authors: Mete Kazaz, Birol Gülnar

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Television news has gained a new dimension in terms of ideological approaches as a result of such factors as globalization, cross monopolization, presence of international companies etc. and certain strategies have been developed at the production, presentation and distribution stages of news. In this study, television news about a process called “settlement process” was investigated. In this framework, news about the settlement process on TV channels of TRT 1, ATV, FOX TV, NTV, HABERTÜRK, TRT HABER and STV was investigated using the content analysis method in terms of the strategies the ideology construction, attitude towards the party in power, attitude towards parties in opposition and attitude towards BDP (Peace and Democracy Part) and Imrali (the island where Abdullah Ocalan, head of PKK, is kept). First, the aforementioned TV channels were selected randomly from 3 groups in order to be able to reveal the representational capacity of commercial, news and public channels. The study covers 557 news items broadcast in the main news bulletins between the dates of 15 March 2013 and 15 March 2013. While there was a positive attitude towards the government in a sizable portion of the news about the settlement process (63.6%), the attitude of 25.3% of the news was impartial towards the government and 11.3% had a negative attitude. On the other hand, there was a negative attitude towards the Opposition in a considerable portion of the news about the settlement process (56.1%). The attitude of 35.9% of the news towards the Opposition was impartial whereas 8.0% had a positive attitude. While 34.9% of the news about the settlement process used the legitimization strategy from among the ideology construction strategies, 22.8% used the unification strategy, 15.7% the reification strategy, 15.6% fractional and 11% concealment/mystification strategy.

Keywords: attitude, ideological framing, television news, social sciences

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Authors: Hamid Yazdani, Fatemeh Abbasi

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Understanding the natural potentials, as the basis for the prevailing context of human activities, environmental planning, and land-use form shows. In this regard, regional characteristics and spatial distribution of the dominant elements in shaping human behavior and environment play a role Knndhayy. As far as today's studies of human Byvklymay basis for urban planning, settlement, architecture, Tourism and so on. In this study, comfort or lack of comfort in Shiraz in Horn of models and indices based on eco-Baker, Trjvng, were examined and the best time to do-using 39 years of data (TCI) stress, and the effective temperature Environmental activities and tourism in the city was established. The results showed that the worth parameters used, the ability to detect Terms of comfort and discomfort are Shiraz, despite minor differences, relatively homogenous aspects of the city provide a comfortable climate. Studies showed that having diversity in the worth of Shiraz during the year, the situation is heating up much coolness; during winter and summer Find out eco comfort zone and during the transition from cold to warm in spring and autumn (April) and warm to cold (November) climate Iran is close to human comfort. Totally, unique human comfort conditions in spring, the best season for environmental activities Tourism in Shiraz.

Keywords: BIO comfort Klymayy, Trjvng, baker, effective temperature, stress and (TCI)

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Authors: Orathai Srithongtham, Ubonsri Thabuddha

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The youth with HIV positive is not difference from the general youth in term of sexual needs. Sexual health is crucial the most to support the youth with HIV positive to be sexual well-being. This study aims to elucidate the sexual health on protection from STDs (Sexual Transmitted Diseases) and HIV transmission and to explain sexual risk behavior of the youth with HIV positive. The target group was the youth with HIV positive about 23 cases from two provinces in northeastern part of Thailand. Qualitative method was applied for collecting data by in-depth interview. Content analysis was use for data analysis. The youth with HIV positive was protection from STDs and HIV transmission by using the condom during sexual activity. The reason to deny the condom use were ashamed, condom is not a part of life, no have fit size, and the youth fear to stigmatized as a mental disorder and fear to stigmatized as going to fuck someone. The youth who trust with nurse in clinic was dare to request the condom by face. Sexual activity without condom use is sexual risk behavior. The major causes were couple trust and the sexual enjoyment first and sexual active competition with friend without condom use. The concern on HIV was the boyfriend or girlfriend not accepts the HIV positive people, worry about the HIV transmutation, and finally not compliance to ARV drug. The youth with HIV positive was lacking of the knowledge on sexual health on the issues of access to condom and the concern to keep on relationship with the boyfriend or girlfriend. This concern issues was led to the non-adherence of ARV drug and HIV distribution. To provide the sexual health service is more essential to the youth with HIV positive.

Keywords: sexual health, sexual risk behavior, youth, HIV

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Authors: Iftikhar Ahmad, Abulhakim Almajid

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Alumina (Al2O3) is an attractive structural ceramic however; brittleness turns Al2O3 down for advanced applications. Development of multi-phase phase ceramics systems is promising to curtail the brittleness and the incorporation of strong/elastic graphene, as third phase, into dual phase (Al2O3-SiC) is striking for mechanical upgrading purpose. Thin graphene nanosheets (GNS) were prepared by thermal exfoliation process and reinforced into dual phase ceramic system. The hybrid nanocomposite was consolidated by novel HF-IH (high-frequency induction heating) sintering furnace at 1500 °C under 50 MPa in vacuum conditions. Structural features and grain size of the resulting nanocomposite were analyzed by SEM and TEM whilst the mechanical properties were assessed by microhardness and nanoindentation techniques. The fracture toughness of the hybrid nanocomposites was appraised by direct crack measurement method. Electron microscopic investigations confirmed the preparation of thin (< 10 nm) graphene nanosheets (GNS). HF-IH sintering route condensed the three-phase (GNS-Al2O3-SiC) hybrid nanocomposite system to > 99% relative densities. SEM of the hybrid nanocomposites fractured surfaces revealed even distribution of the nanocomposite constituents and changed in fracture-mode. Structurally, 88% grain reduction into hybrid nanocomposite was also obtained. Mechanically, enhanced fracture toughness (50%) and hardness (53%) were also achieved for hybrid nanocomposites were attained against bench marked monolithic Al2O3.

Keywords: alumina, graphene, hybrid nanocomposites, rapid sintering

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Authors: Ganga Sagar Bhattarai, Swastika Gurung

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Antibiotics were being misused in both humans and animals, which led to the development of multidrug-resistant microorganisms. Antibiotic abuse is likely rampant among goats, cows, and buffaloes in order to boost growth and reduce production losses. The aim of this study is to know the multidrug resistance (MDR) bacteria in goats, cows, and buffaloes. Out of 68 samples that were examined, S. aureus, Bacillus spp., E. coli, Shigella spp., Klebsiella spp., S. epidremidis, and Salmonella spp. were isolated. S. aureus was the highest isolated bacteria (91.17%), Bacillus spp. (61.76%), E. coli (48.52%), Shigella spp. (22.05%), Klebsiella spp. (17.64%), S. epidermidis (13.23%), and the Salmonella spp. (7.35%). Salmonella spp. and E. coli showed multidrug resistance to at least four antibiotics, including Amoxicillin, Tetracycline, Piperacillin, and Ciprofloxacin, in Salmonella and to at least three antibiotics, including Amoxicillin, Tetracycline, and Nalidic acid. The highest resistance bacteria Salmonella spp. showed (57.14%) E. coli and Bacillus spp. showed (42.85%) S. aureus, S. epidermidis, and Shigella spp. showed (28.57%), and Klebsiella spp. showed (14.28%). This study showed that antibiotic-resistant bacteria with high levels of Amoxicillin, Penicillin, and Tetracycline resistance are present in healthy farm animals such as goats, cows, and buffaloes. Options for antibiotic therapy in both humans and animals will likely be limited as a result. The use, distribution, storage, and sale of antibiotics in veterinary practices must consequently be under strict control.

Keywords: multidrug resistance, multidrug resistance bacteria, susceptibility testing, bacterial infections

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Authors: Karen Yang

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In China, college admissions follow a single-route system where students compete primarily based on academic performance. In contrast, the U.S. uses a multi-route system, offering pathways that consider non-academic achievements such as sports, art, or writing, allowing students to select the route that best suits them. We developed a tournament model to explore which system is more effective at reducing student anxiety. Our analysis indicates that the performance depends on factors such as the overall admission rate, the distribution of quotas among the different routes, and societal norms regarding comparison benchmarks of getting anxious. Since allocating quotas to non-academic routes functions similarly to affirmative action, students with lower academic performance benefit from the multi-route system, while those with higher academic performance may be disadvantaged. Anxiety levels in a multi-route system can surpass those in a single-route system when the proportion of high-ability students is greater than that of low-ability students and the admission opportunities in the academic route fall below the anxiety-inducing benchmark. In societies where being at the average level triggers anxiety, the multi-route system can significantly elevate anxiety rates compared to the single-route system. Even when students can exert effort, the results remain consistent, with effort levels in the multi-route system potentially being lower than in the single-route system. Survey data largely support the model's assumptions and predictions.

Keywords: college admissions, tournament, single route system, multi-route system, affirmative action

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Authors: Mohd Aftar Abu Bakar, Noratiqah Mohd Ariff, Abdul Aziz Jemain

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Storm Event Analysis (SEA) provides a method to define rainfalls events as storms where each storm has its own amount and duration. By modelling daily probability of different types of storms, the onset, offset and cycle of rainfall seasons can be determined and investigated. Furthermore, researchers from the field of meteorology will be able to study the dynamical characteristics of rainfalls and make predictions for future reference. In this study, four categories of storms; short, intermediate, long and very long storms; are introduced based on the length of storm duration. Daily probability models of storms are built for these four categories of storms in Peninsular Malaysia. The models are constructed by using Bernoulli distribution and by applying linear regression on the first Fourier harmonic equation. From the models obtained, it is found that daily probability of storms at the Eastern part of Peninsular Malaysia shows a unimodal pattern with high probability of rain beginning at the end of the year and lasting until early the next year. This is very likely due to the Northeast monsoon season which occurs from November to March every year. Meanwhile, short and intermediate storms at other regions of Peninsular Malaysia experience a bimodal cycle due to the two inter-monsoon seasons. Overall, these models indicate that Peninsular Malaysia can be divided into four distinct regions based on the daily pattern for the probability of various storm events.

Keywords: daily probability model, monsoon seasons, regions, storm events

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Authors: Shymaa S. Zaher, Howayda Abd El-Hady, Nehad Khalifa

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Lake Nasser is vital to Egypt as it is the main Nile water reservoir. One of the major challenges in ecological flood is to establish how environmental enrichment in nutrients availability may affect both the biochemical composition of phytoplankton and the species communities. Samples were collected from twenty sites representing different lake sectors along the main channel of the lake during 2017. Generally, phytoplankton distribution during flood season in Lake Nasser indicates the predominance of Cyanophyceae at all lake sectors. Increases in NO₂ (9.31 µg/l) and PO₄ (7.11µg/l) at the Abu-Simble sector are associated with changes in community structure and biochemical composition of phytoplankton, where Cyanophyceae blooming occur associated with retardation in biopolymeric particulate organic carbon. The maximum total biochemical contents (91.29 mg/l) and biopolymeric particulate organic carbon (37.15 mg/l) was found at El-Madiq sector where there was optimum nutrients (NO₂ 0.479 µg/l and PO₄ 5.149µg/l), a highly positive correlation was found between Cyanophyceae and NO₂ in the lake (r = 0.956). A highly positive correlation was detected between carbohydrates and both transparency and pH in the lake (r = 0.974 and 0.787). Also carbohydrates had a positive relation with Bacillariophyceae (r = 0.610). Flood positively alter the water quality of the lake by increasing dissolved oxygen and nutrients enrichment to the aquatic ecosystem, affecting other aquatic organisms of higher trophic levels as economic fishes inhabiting the lake.

Keywords: aquatic microalgae, Aswan high dam lake, biochemical composition, fresh water

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Authors: Mei Hong, Wei Liu, Xuemin Dai, Yanxiong Pan, Xiangling Ji

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Polyamic acid (PAA) is the precursor of polyimide (PI) prepared by a two-step method, its molecular weight and molecular weight distribution not only play an important role during the preparation and processing, but also influence the final performance of PI. However, precise characterization on molecular weight of PAA is still a challenge because of the existence of very complicated interactions in the solution system, including the electrostatic interaction, hydrogen bond interaction, dipole-dipole interaction, etc. Thus, it is necessary to establisha suitable strategy which can completely suppress these complex effects and get reasonable data on molecular weight. Herein, the gel permeation chromatography (GPC) coupled with differential refractive index (RI) and multi-angle laser light scattering (MALLS) detectors were applied to measure the molecular weight of (6FDA-DMB) PAA using different mobile phases, LiBr/DMF, LiBr/H3PO4/THF/DMF, LiBr/HAc/THF/DMF, and LiBr/HAc/DMF, respectively. It was found that combination of LiBr with HAc can shield the above-mentioned complex interactions and is more conducive to the separation of PAA than only addition of LiBr in DMF. LiBr/HAc/DMF was employed for the first time as a mild mobile phase to effectively separate PAA and determine its molecular weight. After a series of conditional experiments, 0.02M LiBr/0.2M HAc/DMF was fixed as an optimized mobile phase to measure the relative and absolute molecular weights of (6FDA-DMB) PAA prepared, and the obtained Mw from GPC-MALLS and GPC-RI were 35,300 g/mol and 125,000 g/mol, respectively. Particularly, such a mobile phase is also applicable to other PAA samples with different structures, and the final results on molecular weight are also reproducible.

Keywords: Polyamic acids, Polyelectrolyte effects, Gel permeation chromatography, Mobile phase, Molecular weight

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Authors: Loai AbdAllah, Mahmoud Kaiyal

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Missing values in real-world datasets are a common problem. Many algorithms were developed to deal with this problem, most of them replace the missing values with a fixed value that was computed based on the observed values. In our work, we used a distance function based on Bhattacharyya distance to measure the distance between objects with missing values. Bhattacharyya distance, which measures the similarity of two probability distributions. The proposed distance distinguishes between known and unknown values. Where the distance between two known values is the Mahalanobis distance. When, on the other hand, one of them is missing the distance is computed based on the distribution of the known values, for the coordinate that contains the missing value. This method was integrated with Wikaya, a digital health company developing a platform that helps to improve prevention of chronic diseases such as diabetes and cancer. In order for Wikaya’s recommendation system to work distance between users need to be measured. Since there are missing values in the collected data, there is a need to develop a distance function distances between incomplete users profiles. To evaluate the accuracy of the proposed distance function in reflecting the actual similarity between different objects, when some of them contain missing values, we integrated it within the framework of k nearest neighbors (kNN) classifier, since its computation is based only on the similarity between objects. To validate this, we ran the algorithm over diabetes and breast cancer datasets, standard benchmark datasets from the UCI repository. Our experiments show that kNN classifier using our proposed distance function outperforms the kNN using other existing methods.

Keywords: missing values, incomplete data, distance, incomplete diabetes data

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Authors: Shohei Maruyama, Yasuo Matsuyama, Sachiyo Aburatani

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The development of the method to annotate unknown gene functions is an important task in bioinformatics. One of the approaches for the annotation is The identification of the metabolic pathway that genes are involved in. Gene expression data have been utilized for the identification, since gene expression data reflect various intracellular phenomena. However, it has been difficult to estimate the gene function with high accuracy. It is considered that the low accuracy of the estimation is caused by the difficulty of accurately measuring a gene expression. Even though they are measured under the same condition, the gene expressions will vary usually. In this study, we proposed a feature extraction method focusing on the variability of gene expressions to estimate the genes' metabolic pathway accurately. First, we estimated the distribution of each gene expression from replicate data. Next, we calculated the similarity between all gene pairs by KL divergence, which is a method for calculating the similarity between distributions. Finally, we utilized the similarity vectors as feature vectors and trained the multiclass SVM for identifying the genes' metabolic pathway. To evaluate our developed method, we applied the method to budding yeast and trained the multiclass SVM for identifying the seven metabolic pathways. As a result, the accuracy that calculated by our developed method was higher than the one that calculated from the raw gene expression data. Thus, our developed method combined with KL divergence is useful for identifying the genes' metabolic pathway.

Keywords: metabolic pathways, gene expression data, microarray, Kullback–Leibler divergence, KL divergence, support vector machines, SVM, machine learning

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Authors: Hui Shi

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This study investigates a newly emerged usage of Chinese numeral classifier mei (枚) in the cyberspace. In modern Chinese grammar, mei as a classifier should occupy the pre-nominal position, and its valid accompanying nouns are restricted to small, flat, fragile inanimate objects rather than humans. To examine the semantic change of mei, two types of data from Weibo.com were collected. First, 500 mei-included Weibo posts constructed a corpus for analyzing this classifier's word order distribution (post-nominal or pre-nominal) as well as its accompanying nouns' semantics (inanimate or human). Second, considering that mei accompanies a remarkable number of human nouns in the first corpus, the second corpus is composed of mei-involved Weibo IDs from users located in first and third-tier cities (n=8 respectively). The findings show that in the cyber community, mei frequently classifies human-related neologisms at the archaic post-normal position. Besides, the 23 to 29-year-old females as well as Weibo users from third-tier cities are the major populations who adopt mei in their user IDs for self-description and identity expression. This paper argues that the creative usage of mei gains popularity in the Chinese internet due to a humor effect. The marked word order switch and semantic misapplication combined to trigger incongruity and jocularity. This study has significance for research on Chinese cyber neologism. It may also lay a foundation for further studies on Chinese classifier change and Chinese internet communication.

Keywords: Chinese classifier, humor, neologism, semantic change

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Authors: El Oualid Mokhnache, Noureddine Ramdani

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The choice of gun barrel materials is crucial to ensure the maximum high rate of fire. The high rate of fire causes wear-out damage and shuts off mechanical properties (hardness, strength, wear resistance, etc.) and ballistic properties (bullet speed, dispersion and precision, longevity of barrel, etc). To overcome these kinds of problems, a deep understanding of the effect of the firing cycle on the mechanical and ballistic properties of the barrel is regarded as crucial to improving its characteristics. In the present work, a real experimental test of firing by using a high steel barrel with 7.62x39 ammunition was carried. Microstructural observations by using SEM were investigated. Hardness evolution through the barrel of both barrels labeled as reference barrels and as fired barrels were compared and discussed. Ballistic properties during the firing test, including speed of projectile and precision dispersion, are revealed and discussed as well. The aim of the present communication is about to discuss the relationship between pressure distribution versus mechanical properties through the wall barrel. Ballistic properties, including speed of the projectile, dispersion, and precision results during the shooting process, were investigated. Microstructure observations of the as-rifled barrel in comparison with the as-reference barrel were performed as well.

Keywords: barrel, ballistic, pressure, microstructure evolution, hardness

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Authors: Shriya Shukla, Lachin Fernando

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Pneumonia, a leading cause of mortality in young children globally, presents significant diagnostic challenges, particularly in resource-limited settings. This study presents an approach to diagnosing pediatric pneumonia using Chest X-Ray (CXR) images, employing a lightweight MobileNetV2 model enhanced with synthetic data augmentation. Addressing the challenge of dataset scarcity and imbalance, the study used a Variational Autoencoder-Generative Adversarial Network (VAE-GAN) to generate synthetic CXR images, improving the representation of normal cases in the pediatric dataset. This approach not only addresses the issues of data imbalance and scarcity prevalent in medical imaging but also provides a more accessible and reliable diagnostic tool for early pneumonia detection. The augmented data improved the model’s accuracy and generalization, achieving an overall accuracy of 95% in pneumonia detection. These findings highlight the efficacy of the MobileNetV2 model, offering a computationally efficient yet robust solution well-suited for resource-constrained environments such as mobile health applications. This study demonstrates the potential of synthetic data augmentation in enhancing medical image analysis for critical conditions like pediatric pneumonia.

Keywords: pneumonia, MobileNetV2, image classification, GAN, VAE, deep learning

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Authors: Sufia Khowaja, Nishat Fatima

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Social networking sites are significant for visually impaired to overcome the unique challenges they face and access the resources they need to succeed in their education and beyond which might be difficult to obtain through traditional means. It provides them an opportunity to build relationships, stay connected with their support network as well as to develop social skills which give them emotional support to fell less isolated. In this connection the study is conducted with the aim to determine the use of social networking sites, purpose of using and activities performed by visually impaired at Delhi University, Delhi, Jawaharlal Nehru University, Delhi and Jamia Milia Islamia, Delhi. The study followed survey technique in which structured interview is followed to collect data from 137 visually impaired students and analysed using ‘SPSS ver23’. The findings of the study revealed that mostly used social networking sites are whatsapp by 89.23% students of DU, 95.12% of JNU, 87.09% of JMI, followed by e-mail by 78.46% of DU, 78.04% of JNU, 64.51%; youtube by 73.84% DU, 90.24% JNU, 80.64% JMI. Purpose for using these sites is for academics mentioned by 96.92% DU, 100% JNU, 93.54% JMI. Activities performed on sites are sending and receiving messaging 96.92% DU, 92.68% JNU, 93.55% JMI, communicating with friends and family as well as getting academic information. Findings of the study will be helpful for libraries to disseminate their services and resources as well as latest updates to their visually impaired users with the help of most used tools.

Keywords: social networking sites, visually impaired, Delhi University, Jawaharlal Nehru University, Jamia Milia Islamia

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Authors: Jay L. Fu

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Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients.

Keywords: Alzheimer's disease, clinical diagnosis, magnetic resonance imaging, machine learning prediction

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Authors: Javier A. Maldonado E., Duvert A. Puentes T., Diego F. Villegas B.

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The SLAP lesion (Superior Labral Anterior to Posterior) involves the labrum, causing pain and mobility problems in the glenohumeral joint. This injury is common in athletes practicing sports that requires throwing or those who receive traumatic impacts on the shoulder area. This paper determines the biomechanical behavior of soft tissues of the glenohumeral joint when type II SLAP lesion is present. This pathology is characterized for a tear in the superior labrum which is simulated in a 3D model of the shoulder joint. A 3D model of the glenohumeral joint was obtained using the free software Slice. Then, a Finite Element analysis was done using a general purpose software which simulates a compression test with external rotation. First, a validation was done assuming a healthy joint shoulder with a previous study. Once the initial model was validated, a lesion of the labrum built using a CAD software and the same test was done again. The results obtained were stress and strain distribution of the synovial capsule and the injured labrum. ANOVA was done for the healthy and injured glenohumeral joint finding significant differences between them. This study will help orthopedic surgeons to know the biomechanics involving this type of lesion and also the other surrounding structures affected by loading the injured joint.

Keywords: biomechanics, computational model, finite elements, glenohumeral joint, superior labral anterior to posterior lesion

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Authors: Hao Wang, Shengchun Wang, Weidong Wang

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On the influence of train vibration and environmental noise on the measurement of track wear, we proposed a method for automatic extraction of circular arc on the inner or outer side of the rail waist and achieved the high-precision registration of rail profile. Firstly, a polynomial fitting method based on truncated residual histogram was proposed to find the optimal fitting curve of the profile and reduce the influence of noise on profile curve fitting. Then, based on the curvature distribution characteristics of the fitting curve, the interval search algorithm based on dynamic window’s maximum curvature entropy was proposed to realize the automatic segmentation of small circular arc. At last, we fit two circle centers as matching reference points based on small circular arcs on both sides and realized the alignment from the measured profile to the standard designed profile. The static experimental results show that the mean and standard deviation of the method are controlled within 0.01mm with small measurement errors and high repeatability. The dynamic test also verified the repeatability of the method in the train-running environment, and the dynamic measurement deviation of rail wear is within 0.2mm with high repeatability.

Keywords: curvature entropy, profile registration, rail wear, structured light, train-running

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Authors: Matthew Olanrewaju Ibiyomi

Abstract:

The study examined the abundance of free-range natural inhabitants of the Federal University of Agriculture, Abeokuta (FUNAAB) Zoo Park. A baseline data of free-ranging inhabitants of the Park is essential to monitor trends and institute conservation plans through unsustainable natural resources exploitation and habitat destruction. Four transects were selected across the study area. Each transect was traversed for a period of four months and observations was carried out twice a day. The Four existing tracks explored during the study were the aviary, reptile, carnivore and primate tracks. Data were analyzed using descriptive statistics. The findings from this study revealed that 8 species of natural inhabitants were identified, which were the Vervet monkey (Chlorocebuspygerythrus), Maxwell duiker(Philantombamaxwellii), Mongoose (Herpestidaespp), Bushbuck(Tragelaphusscriptus), Cobra (Najanaja), Ground squirrel (Marmotinispp), Senegal coucal(Centropus senegalensis), Black kite (Milvus migrans). The result further showed that a total of 115 animals were encountered in the primate transect, 77 animals in the carnivores transect, 46 animals in the aviary transect and 34 animals in the ungulates transect by the representative of 43.3%, 28.3%, 15.8% and 12.5% respectively. Human activities and level of disturbance were observed to have affected the abundance and distribution of animals at Funaab Zoo Park. Continuous field inventory is recommended to ascertain the dynamics of animals observed as free-range inhabitants in this study.

Keywords: abundance, ecosystem, extinction, free-range

Procedia PDF Downloads 97

Authors: Hassan Hussin Zwida

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The liquified LPG (Liquefied Petroleum Gas) drying system at the Complex is designed to remove water and mercaptans from the LPG stream. Upon saturation of the desiccant beds, a regeneration cycle becomes necessary. The original design routed the regeneration gas, produced during the LPG dryer heating cycle, to the sulfur recovery unit to the incineration. However, concerns regarding high temperatures and potential unit disruptions led to a modification where the gas is currently vented to the acid flare for the initial hour before being diverted to the LP network fuel gas system. While this addresses the temperature concerns, it generates significant smoke due to the presence of liquid hydrocarbons. This paper proposes an approach to recover the regeneration gas and redirect it back to the gas plant's (off-gas compressors) instead of sending it to the AC (Acid Flare), by utilizing the existing pipe 6” and connected to off gas compressor KO (Knock-Out ) Drums . This option is simple to operate, flexible, environment-friendly solution as long-term solution, lower in capital expenditure and increase the company's profitability. The feasibility of this proposal is supported by dynamic simulations. The simulations suggest the possibility of operating two out of the three off-gas compressors and LPG (Liquefied petroleum gas) as a liquid phase, is foreseen to be carried over and gathered at the bottom level of the KO (Knock-Out) Drum.

Keywords: thermal incinerator, off-gas compressors, environment, knock-out drums, acid flare

Procedia PDF Downloads 61

Authors: Ng Ziyi Zoe, Yow Wei Quin

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Humor plays a pivotal role in our interaction with people. According to the age-related positivity effect, older adults (OA) demonstrate more positive emotions and are better able to modulate negative emotional states than younger adults (YA), suggesting an increase in humor appreciation with age. However, different types of humor might show different patterns of change in appreciation with age (e.g., incongruity-resolution humor, aggressive humor, self-vs.-other-deprecating humor). Thus, we aim to explore age-related effects in the perception of different types of humor in a single study, including the impact of local slang in humor appreciation. Twenty OA aged 60-and-above and 24 YA aged 13-20 were watched four short videos (i.e., benign, violent, satire+local slang, and others-deprecating humor) and rated how funny the videos were (from a scale of 1-not funny-at-all to 5-very funny). Participants were also asked to rank the videos in the order of most- to least-entertaining. Repeated measures of ANOVA found significant main effects of age, F(3,39)=12,88, p < .001, where OA gave higher ratings than YA (M=3.20 vs. 2.63), and humor type, F(3,123)=19.66, p < .001. Post-hoc analyses revealed a significant linear contrast where benign and violent humor had the lowest ratings while others-deprecating humor had the highest ratings. No significant interaction effect was found. The distribution of ranking ratings also differed between OA and YA (e.g., preferred satire+local slang and others-deprecating humor vs. overwhelmingly preferred other-deprecating humor, respectively). Overall, OA displayed a greater appreciation across various types of humor than YA. Humor perception will be discussed in the larger context of cognitive, societal, and cultural implications.

Keywords: humor, older adults, perception, age differences

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Authors: Felix Boehnisch, Alexander Lutz

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Based on the number of users and the amount of content posted daily, Facebook is considered the largest social network in the world. This content includes images or text posts from companies but also private persons, which are also commented on by other users. However, it can sometimes be difficult for companies to keep track of all the posts and the reactions to them, especially when there are several posts a day that contain hundreds to thousands of comments. To facilitate this, the following paper deals with the possible applications of sentiment analysis to social media comments in order to be able to support the work in social media marketing. In a first step, post comments were divided into positive and negative by a subjective rating, then the same comments were checked for their polarity value by the two german python libraries TextBlobDE and SentiWS and also grouped into positive, negative, or even neutral. As a control, the subjective classifications were compared with the machine-generated ones by a confusion matrix, and relevant quality criteria were determined. The accuracy of both libraries was not really meaningful, with 60% to 66%. However, many words or sentences were not evaluated at all, so there seems to be room for optimization to possibly get more accurate results. In future studies, the use of these specific German libraries can be optimized to gain better insights by either applying them to stricter cleaned data or by adding a sentiment value to emojis, which have been removed from the comments in advance, as they are not contained in the libraries.

Keywords: Facebook, German libraries, polarity, sentiment analysis, social media comments

Procedia PDF Downloads 185

Authors: Soofiyan Atar, Adil Shaikh, Sahil Rajpurkar, Pragnesh Bhalala, Aniket Desai, Irfan Siddavatam

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Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Keywords: model-based reinforcement learning, gait stability, supervised learning, pneumatic quadruped

Procedia PDF Downloads 319

Authors: Ibrahim Suliman Hanaish

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Disaggregation daily rainfall using stochastic models formulated based on multivariate approach (MuDRain) is discussed in this paper. Seven rain gauge stations are considered in this study for different distances from the referred station starting from 4 km to 160 km in Peninsular Malaysia. The hourly rainfall data used are covered the period from 1973 to 2008 and July and November months are considered as an example of dry and wet periods. The cross-correlation among the rain gauges is considered for the available hourly rainfall information at the neighboring stations or not. This paper discussed the applicability of the MuDRain model for disaggregation daily rainfall to hourly rainfall for both sources of cross-correlation. The goodness of fit of the model was based on the reproduction of fitting statistics like the means, variances, coefficients of skewness, lag zero cross-correlation of coefficients and the lag one auto correlation of coefficients. It is found the correlation coefficients based on extracted correlations that was based on daily are slightly higher than correlations based on available hourly rainfall especially for neighboring stations not more than 28 km. The results showed also the MuDRain model did not reproduce statistics very well. In addition, a bad reproduction of the actual hyetographs comparing to the synthetic hourly rainfall data. Mean while, it is showed a good fit between the distribution function of the historical and synthetic hourly rainfall. These discrepancies are unavoidable because of the lowest cross correlation of hourly rainfall. The overall performance indicated that the MuDRain model would not be appropriate choice for disaggregation daily rainfall.

Keywords: rainfall disaggregation, multivariate disaggregation rainfall model, correlation, stochastic model

Procedia PDF Downloads 523

Authors: Ari Istiany, Guspri Devi Artanti, M. Si

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Based on the results Riskesdas, it is known that breastfeeding awareness about the importance of exclusive breastfeeding is still low at only 15.3 %. These conditions resulted in a very infant at risk for infectious diseases, such as diarrhea and acute respiratory infection. Therefore, the aim of this study to evaluate the video development about exclusive breastfeeding as a nutrition education media for posyandu cadre. This research used development methods for making the video about exclusive breastfeeding. The study was conducted in urban areas Rawamangun, East Jakarta. Respondents of this study were 1 media experts from the Department of Educational Technology - UNJ, 2 subject matter experts from Department of Home Economics - UNJ and 20 posyandu cadres to assess the quality of the video. Aspects assessed include the legibility of text, image display quality, color composition, clarity of sound, music appropriateness, duration, suitability of the material and language. Data were analyzed descriptively likes frequency distribution table, the average value, and deviation standard. The result of this study showed that the average score assessment according to media experts, subject matter experts, and posyandu cadres respectively was 3.43 ± 0.51 (good), 4.37 ± 0.52 (very good) and 3.6 ± 0.73 (good). The conclusion is on exclusive breastfeeding video as feasible as a media for nutrition education. While suggestions for the improvement of visual media is multiply illustrations, add material about the correct way of breastfeeding and healthy baby pictures.

Keywords: exclusive breastfeeding, posyandu cadre, video, nutrition education

Procedia PDF Downloads 415

Authors: Mazita Mohd Diah, Anton V. Dolzhenko, Tin Wui Wong

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Nanoparticles, being small with a large specific surface area, increase solubility, enhance bioavailability, improve controlled release and enable precision targeting of the entrapped compounds. In this study, chitosan as polymeric permeation enhancer was conjugated to a polar pro-drug, carboxymethyl-5-fluorouracil (CMFU) to increase the skin drug permeation. Chitosan-CMFU conjugate was synthesized using chemical conjugation process through succinate linker. It was then transformed into nanoparticles via spray drying method. The conjugation was elucidated using Fourier Transform Infrared and Proton Nuclear Magnetic Resonance techniques. The nanoparticle size, size distribution, zeta potential, drug content, skin permeation and retention profiles were characterized. The conjugation was denoted using 1H NMR by new peaks at signal δ = 4.184 ppm (singlet, 2H for CH2) and 7.676-7.688 ppm (doublet, 1H for C6) attributed to CMFU in chitosan-CMFU NMR spectrum. The nanoparticles had profiles of particle size: 93.97 ±35.11 nm, polydispersity index: 0.40 ± 0.14, zeta potential: +18.25 ±2.95 mV and drug content: 6.20 ± 1.98 % w/w. Almost 80 % w/w CMFU in the form of nanoparticles permeated through the skin in 24 hours and close to 50 % w/w permeation occurred in first 1-2 hours. Without conjugation to chitosan and nanoparticulation, less than 40 % w/w CMFU permeated through the skin in 24 hours. The skin drug retention likewise was higher with chitosan-CMFU nanoparticles (15.34 ± 5.82 % w/w) than CMFU (2.24 ± 0.57 % w/w). CMFU, through conjugation with chitosan permeation enhancer and processed in nanogeometry, had its skin permeation and retention degree promoted.

Keywords: carboxymethyl-5-fluorouracil, chitosan, conjugate, skin permeation, skin retention

Procedia PDF Downloads 368