Search results for: classification rule

Authors: Xiaohua Zhu, Lingling Ma, Yongguang Zhao

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Leaf Area Index (LAI) is a key structural characteristic of crops and plays a significant role in precision agricultural management and farmland ecosystem modeling. However, LAI retrieved from different resolution data contain a scaling bias due to the spatial heterogeneity and model non-linearity, that is, there is scale effect during multi-scale LAI estimate. In this article, a typical farmland in semi-arid regions of Chinese Inner Mongolia is taken as the study area, based on the combination of PROSPECT model and SAIL model, a multiple dimensional Look-Up-Table (LUT) is generated for multiple crops LAI estimation from unmanned aerial vehicle (UAV) hyperspectral data. Based on Taylor expansion method and computational geometry model, a scale transfer model considering both difference between inter- and intra-class is constructed for scale effect analysis of LAI inversion over inhomogeneous surface. The results indicate that, (1) the LUT method based on classification and parameter sensitive analysis is useful for LAI retrieval of corn, potato, sunflower and melon on the typical farmland, with correlation coefficient R2 of 0.82 and root mean square error RMSE of 0.43m2/m-2. (2) The scale effect of LAI is becoming obvious with the decrease of image resolution, and maximum scale bias is more than 45%. (3) The scale effect of inter-classes is higher than that of intra-class, which can be corrected efficiently by the scale transfer model established based Taylor expansion and Computational geometry. After corrected, the maximum scale bias can be reduced to 1.2%.

Keywords: leaf area index (LAI), scale effect, UAV-based hyperspectral data, look-up-table (LUT), remote sensing

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Authors: M. Yosra, A. Mohamed, T. Sami

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Over the past few years, mobile communication technologies have seen significant evolution. This fact promoted the implementation of many systems in a multi-technological setting. From one system to another, the Quality of Service (QoS) provided to mobile consumers gets better. The growing number of normalized standards extends the available services for each consumer, moreover, most of the available radio frequencies have already been allocated, such as 3G, Wifi, Wimax, and LTE. A study by the Federal Communications Commission (FCC) found that certain frequency bands are partially occupied in particular locations and times. So, the idea of Cognitive Radio (CR) is to share the spectrum between a primary user (PU) and a secondary user (SU). The main objective of this spectrum management is to achieve a maximum rate of exploitation of the radio spectrum. In general, the CR can greatly improve the quality of service (QoS) and improve the reliability of the link. The problem will reside in the possibility of proposing a technique to improve the reliability of the wireless link by using the CR with some routing protocols. However, users declared that the links were unreliable and that it was an incompatibility with QoS. In our case, we choose the QoS parameter "bandwidth" to perform a supervised classification. In this paper, we propose a comparative study between some routing protocols, taking into account the variation of different technologies on the existing spectral bandwidth like 3G, WIFI, WIMAX, and LTE. Due to the simulation results, we observe that LTE has significantly higher availability bandwidth compared with other technologies. The performance of the OLSR protocol is better than other on-demand routing protocols (DSR, AODV and DSDV), in LTE technology because of the proper receiving of packets, less packet drop and the throughput. Numerous simulations of routing protocols have been made using simulators such as NS3.

Keywords: cognitive radio, multi technology, network simulator (NS3), routing protocol

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Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

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The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

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Authors: Leila M. Carvalho, Maria Erica S. Oliveira, Arnoud C. Neto, Elza I. Ida, Massami Shimokomaki, Marta S. Madruga

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The quality of broiler breast meat is changing as a result of the continuing emphasis on genetic selection for a more efficient meat production. Breast meat has been classified as PSE (pale, soft, exudative), DFD (dark, firm, dry) and normal color meat, and recently a third group has emerged: the so-called PFN (pale, firm, non-exudative) meat. This classification was based on pH, color and functional properties. The aim of this work was to confirm the existence of PFN and PSE meat by biochemical characterization and functional properties. Twenty four hours of refrigerated fillet, Pectoralis major, m. samples (n= 838) were taken from Cobb flocks 42-48 days old, obtained in Northeastern Brazil tropical region, the Northeastern, considered to have only dry and wet seasons. Color (L*), pH, water holding capacity (WHC), values were evaluated and compared with PSE group samples. These samples were classified as Normal (465.8), PSE meat (L*≥53; pH<5.8) and PFN (L*≥53; pH>5.8). The occurrence of control meat, PSE and PFN was 69.09%, 11.10% and 19.81%, respectively. Samples from PFN presented 4.0-5.0% higher WHC in relation to PSE meat and similar to control group. These results are explained by the fact that PSE meat syndrome occurs because of higher protein denaturation as the consequence of a simultaneous lower pH values under warm carcass sooner after slaughtering impairing the myofibril proteins functional properties. Conversely, PFN samples follow normal glycolysis rate maintaining the normal proteins activities. In conclusion, the results reported herein confirm the existence of this emerging broiler meat group with similar properties as control group and it should be considered as normal breast meat group.

Keywords: broiler breast meat, funcional properties, PFN, PSE

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Authors: Rita Bagheri, Javed Ahmed, Humayra Bashir, M. Irfan Qureshi

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Agriculture lands suffer from a combination of stresses such as salinity and metal contamination including cadmium at the same time. Under such condition of multiple stresses, plant may exhibit unique responses different from the stress occurring individually. Thus, it would be interesting to investigate that how plant respond to combined stress at level of antioxidants and proteome expression, and identifying the proteins which are involved in imparting stress tolerance. With an approach of comparative proteomics and antioxidant analysis, present study investigates the response of Spinacia oleracea to salt (NaCl), cadmium (Cd), and their combination (NaCl+Cd) stress. Two-dimensional gel electrophoresis was used for resolving leaf proteome, and proteins of interest were identified using PDQuest software. A number of proteins expressed differentially, those indicated towards their roles in imparting stress tolerance, were digested by trypsin and analyzed on mass spectrometer for peptide mass fingerprinting (PMF). Data signals were then matched with protein databases using MASCOT. Results show that NaCl, Cd and both together (NaCl+Cd) induce oxidative stress which was highest in combined stress of Cd+NaCl. Correspondingly, the activities of enzymatic antioxidants viz., SOD, APX, GR and CAT, and non-enzymatic antioxidants had highest changes under combined stress compares to single stress over their respective controls. Among the identified proteins, several interesting proteins were identified that may be have role in Spinacia oleracia tolerance in individual and combinatorial stress of salt and cadmium. The functional classification of identified proteins indicates the importance and necessity of keeping higher ratio of defence and disease responsive proteins.

Keywords: Spinacia oleracea, Cd, salinity, proteomics, antioxidants, combinatorial stress

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Authors: Gurjeet Singh, Harinder Singh

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In this paper, we present "The Language of Science in Higher Education: Related Questions and Discussions". Linguists have written and researched in depth the role of language in science. On this basis, it is clear that language is not just a medium or vehicle for communicating knowledge and ideas. Nor are there mere signs of language knowledge and conversion of ideas into code. In the process of reading and writing, everyone thinks deeply and struggles to understand concepts and make sense. Linguistics play an important role in achieving concepts. In the context of such linguistic diversity, there is no straightforward and simple answer to the question of which language should be the language of advanced science and technology. Many important topics related to this issue are as follows: Involvement in practical or Deep theoretical issues. Languages for the study of science and other subjects. Language issues of science to be considered separate from the development of science, capitalism, colonial history, the worldview of the common man. The democratization of science and technology education in India is possible only by providing maximum reading/resource material in regional languages. The scientific research should be increase to chances of understanding the subject. Multilingual instead or monolingual. As far as deepening the understanding of the subject is concerned, we can shed light on it based on two or three experiences. An attempt was made to make the famous sociological journal Economic and Political Weekly Hindi almost three decades ago. There were many obstacles in this work. The original articles written in Hindi were not found, and the papers and articles of the English Journal were translated into Hindi, and a journal called Sancha was taken out. Equally important is the democratization of knowledge and the deepening of understanding of the subject. However, the question is that if higher education in science is in Hindi or other languages, then it would be a problem to get job. In fact, since independence, English has been dominant in almost every field except literature. There are historical reasons for this, which cannot be reversed. As mentioned above, due to colonial rule, even before independence, English was established as a language of communication, the language of power/status, the language of higher education, the language of administration, and the language of scholarly discourse. After independence, attempts to make Hindi or Hindustani the national language in India were unsuccessful. Given this history and current reality, higher education should be multilingual or at least bilingual. Translation limits should also be increased for those who choose the material for translation. Writing in regional languages on science, making knowledge of various international languages available in Indian languages, etc., is equally important for all to have opportunities to learn English.

Keywords: language, linguistics, literature, culture, ethnography, punjabi, gurmukhi, higher education

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Authors: Naima Jannat, Ariful Islam, Sharafat Hossain

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Due to the involvement of the large target volume, Craniospinal Irradiation makes it challenging to achieve a uniform dose, and it requires different isocenters. This isocentric junction needs to shift after every five fractions to overcome the possibility of hot and cold spots. This study aims to evaluate the Planning Target Volume coverage & sparing Organ at Risk between two techniques and shows that the Field Alignment Technique does not need replanning and resetting. Planning method for Craniospinal Irradiation by Eclipse treatment planning system Field Alignment and Extended Source to Surface Distance technique was developed where 36 Gy in 20 Fraction at the rate of 1.8 Gy was prescribed. The patient was immobilized in the prone position. In the Field Alignment technique, the plan consists of half beam blocked parallel opposed cranium and a single posterior cervicospine field was developed by sharing the same isocenter, which obviates divergence matching. Further, a single field was created to treat the remaining lumbosacral spine. Matching between the inferior diverging edge of the cervicospine field and the superior diverging edge of a lumbosacral field, the field alignment option was used, which automatically matches the field edge divergence as per the field alignment rule in Eclipse Treatment Planning System where the couch was set to 2700. In the Extended Source to Surface Distance technique, two parallel opposed fields were created for the cranium, and a single posterior cervicospine field was created where the Source to Surface Distance was from 120-140 cm. Dose Volume Histograms were obtained for each organ contoured and for each technique used. In all, the patient’s maximum dose to Planning Target Volume is higher for the Extended Source to Surface Distance technique to Field Alignment technique. The dose to all surrounding structures was increased with the use of a single Extended Source to Surface Distance when compared to the Field Alignment technique. The average mean dose to Eye, Brain Steam, Kidney, Oesophagus, Heart, Liver, Lung, and Ovaries were respectively (58% & 60 %), (103% & 98%), (13% & 15%), (10% & 63%), (12% & 16%), (33% & 30%), (14% & 18%), (69% & 61%) for Field Alignment and Extended Source to Surface Distance technique. However, the clinical target volume at the spine junction site received a less homogeneous dose with the Field Alignment technique as compared to Extended Source to Surface Distance. We conclude that, although the use of a single field Extended Source to Surface Distance delivered a more homogenous, but its maximum dose is higher than the Field Alignment technique. Also, a huge advantage of the Field Alignment technique for Craniospinal Irradiation is that it doesn’t need replanning and resetting up of patients after every five fractions and 95% prescribed dose was received by more than 95% of the Planning Target Volume in all the plane with the acceptable hot spot.

Keywords: craniospinalirradiation, cranium, cervicospine, immobilize, lumbosacral spine

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Authors: Sanghamitra Roy

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In recent times, India has experienced the phenomenal rise in the number of registered vehicles and vehicular trips, particularly intra-city trips in most of its urban areas. The increase in vehicle ownership and use have increased parking demand immensely and accommodating the same is now a matter of big concern. Most cities do not have adequate off-street parking facilities thus forcing people to park on the streets. This has resulted in decreased carrying capacity, decreased traffic speed, increased congestion, and increased environmental problems. While integrated multi-modal transportation system is the answer to such problems, parking issues will continue to exist. In Kolkata, only 6.4% land is devoted for roads. The consequences of this huge crunch in road spaces coupled with increased parking demand are severe particularly in the CBD and major commercial areas, making the role of off-street parking facilities in Kolkata even more critical. To meaningfully address parking issues, it is important to identify the factors that influence parking demand so that it can be assessed and comprehensive parking policies and plans for the city can be formulated. This paper aims at identifying the factors that contribute towards parking demand for offices in Kolkata and their degree of correlation with parking demand. The study is limited to home-to-work trips located within Kolkata Municipal Corporation (KMC) where parking related issues are most pronounced. The data for the study is collected through personal interviews, questionnaires and direct observations from offices across the wards of KMC. SPSS is used for classification of the data and analyses of the same. The findings of this study will help in re-assessment of the parking requirements specified in The Kolkata Municipal Corporation Building Rules as a step towards alleviating parking related issues in the city.

Keywords: building rules, office spaces, parking demand, urbanization

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Authors: Thewodros K. Geberemariam

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The rapid physical expansion of urbanization coupled with aging infrastructure presents a unique decision and management challenges for many big city municipalities. Cities must therefore upgrade and maintain the existing aging urban drainage infrastructure systems to keep up with the demands. Given the overall contribution of assets to municipal revenue and the importance of infrastructure to the success of a livable city, many municipalities are currently looking for a robust and smart urban drainage infrastructure asset management solution that combines management, financial, engineering and technical practices. This robust decision-making shall rely on sound, complete, current and relevant data that enables asset valuation, impairment testing, lifecycle modeling, and forecasting across the multiple asset portfolios. On this paper, predictive computational intelligence (CI) and multi-class machine learning (ML) coupled with online, offline, and historical record data that are collected from an array of multi-parameter sensors are used for the extraction of different operational and non-conforming patterns hidden in structured and unstructured data to determine and produce actionable insight on the current and future states of the network. This paper aims to improve the strategic decision-making process by identifying all possible alternatives; evaluate the risk of each alternative, and choose the alternative most likely to attain the required goal in a cost-effective manner using historical and near real-time urban drainage infrastructure data for urban drainage infrastructures assets that have previously not benefited from computational intelligence and machine learning advancements.

Keywords: computational intelligence, machine learning, urban drainage infrastructure, machine learning, classification, prediction, asset management space

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Authors: Chi-Ching Lee, Po-Jung Huang, Kuo-Yang Huang, Petrus Tang

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Background: Recent advances in high-throughput research technologies such as new-generation sequencing and multi-dimensional liquid chromatography makes it possible to dissect the complete transcriptome and proteome in a single run for the first time. However, it is almost impossible for many laboratories to handle and analysis these “BIG” data without the support from a bioinformatics team. We aimed to provide a web-based analysis platform for users with only limited knowledge on bio-computing to study the functional genomics and proteomics. Method: We use NCI-60 as an example dataset to demonstrate the power of the web-based analysis platform and data delivering system: C-eXpress takes a simple text file that contain the standard NCBI gene or protein ID and expression levels (rpkm or fold) as input file to generate a distribution map of gene/protein expression levels in a heatmap diagram organized by color gradients. The diagram is hyper-linked to a dynamic html table that allows the users to filter the datasets based on various gene features. A dynamic summary chart is generated automatically after each filtering process. Results: We implemented an integrated database that contain pre-defined annotations such as gene/protein properties (ID, name, length, MW, pI); pathways based on KEGG and GO biological process; subcellular localization based on GO cellular component; functional classification based on GO molecular function, kinase, peptidase and transporter. Multiple ways of sorting of column and rows is also provided for comparative analysis and visualization of multiple samples.

Keywords: cancer, visualization, database, functional annotation

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Authors: Andreas Aceranti, Simonetta Vernocchi, Marco Colorato, Massimo Briamo, Giovanni Abalsamo

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Most of the benefits of sport come from related physical activity, however, there are secondary psychological positive effects. There are also obvious disadvantages, high tensions related to failure, injuries, eating disorders and burnout. Depressive symptoms and illnesses related to anxiety or stress can be preventable or even simply alleviated through regular activity and exercise. It has been shown that the practice of a sport brings physical benefits, but can also have psychological and spiritual benefits. Reduced performance in male individuals has been linked to sexual activity before competitions in the past. The long-standing debate about the impact of sexual activity on sports performance has been controversial in the mainstream media in recent decades. This salacious topic has generated extensive discussion, although its high-quality data has been limited. Literature has, so far, mainly included subjective assessments from surveys. However, such surveys can be skewed as these assessments are based on individual beliefs, perceptions, and memory. There has been a long discussion over the years but even there objective data has been lacking. One reason behind coaches' bans on sexual activity before sporting events may be the belief that abstinence increases frustration, which in turn is shifted into aggressive behavior toward competitors. However, this assumption is not always valid. In fact, depriving an athlete of a normal activity can cause feelings of guilt and loss of concentration. Sexual activity during training can promote relaxation and positively influence performance. The author concludes that, although there is a need for scientific research in this area, it seems that sexual intercourse does not decrease performance unless it is accompanied by late night socialization, loss of sleep or drinking. Although the effects of sexual engagement on aerobic and strength athletic performance have not been definitively established, most research seems to rule out a direct impact. In order to analyze, as much as possible without bias, whether sexual activity significantly affects an athletic performance or not, we sampled 5 amateur athletes, between 22 and 25 years old and all male. The study was based on the timing of 4 running races of 5 champions. We asked participants to respect guidelines to avoid sexual activity (sex or masturbation) 12 hours before 2 of the 4 competitions, and to practice before the remaining 2 races.In doing so, we were able to compare and analyze the impact of activity and abstinence on performance results. We have come to the conclusion that sexual behavior on athletic performance needs to be better understood, more randomized trials and high-quality controls are strongly needed but available information suggests that sexual activity the day before a race has no negative effects on performance.

Keywords: sex, masturbation, male performance, soccer

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Authors: C. M. Williams, R. English, P. King, I. M. Brown

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Introduction: Pseudoangiomatous Stromal Hyperplasia (PASH) is a benign fibrous proliferation of breast stroma affecting predominantly premenopausal women with no significant increased risk of breast cancer. Informal recommendations for management have continued to evolve over recent years from surgical excision to observation, although there are no specific national guidelines. This study assesses the safety of a non-surgical approach to PASH management by review of cases at a single centre. Methods: Retrospective case series review (January 2011 – August 2016) was conducted on consecutive PASH cases. Diagnostic classification (clinical, radiological and histological), management outcomes, and breast cancer incidence were recorded. Results: 43 patients were followed up for median of 25 months (3-64) with 75% symptomatic at presentation. 12% of cases (n=5) had a radiological score (BIRADS MMG or US) ≥ 4 of which 3 were confirmed malignant. One further malignancy was detected and proven radiologically occult and contralateral. No patients were diagnosed with a malignancy during follow-up. Treatment evolved from 67% surgical in 2011 to 33% in 2016. Conclusions: The management of PASH has transitioned in line with other published experience. The preliminary findings suggest this appears safe with no evidence of missed malignancies; however, longer follow up is required to confirm long-term safety. Recommendations: PASH with suspicious radiological findings ( ≥ U4/R4) warrants multidisciplinary discussion for excision. In the absence of histological or radiological suspicion of malignancy, PASH can be safely managed without surgery.

Keywords: benign breast disease, conservative management, malignancy, pseudoangiomatous stromal hyperplasia, surgical excision

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Authors: Wei Wen Yang, Emily Chia Yu Su

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Dengue fever is a mosquito-borne tropical infectious disease caused by the dengue virus. After infection, symptoms usually start from three to fourteen days. Dengue virus may cause a high fever and at least two of the following symptoms, severe headache, severe eye pain, joint pains, muscle or bone pain, vomiting, feature skin rash, and mild bleeding manifestation. In addition, recovery will take at least two to seven days. Dengue fever has rapidly spread in tropical and subtropical areas in recent years. Several phenomena around the world such as global warming, urbanization, and international travel are the main reasons in boosting the spread of dengue. In Taiwan, epidemics occur annually, especially during summer and fall seasons. On the other side, Singapore government also has announced the amounts number of dengue cases spreading in Singapore. As the serious epidemic of dengue fever outbreaks in Taiwan and Singapore, countries around the Asia-Pacific region are becoming high risks of susceptible to the outbreaks and local hub of spreading the virus. To improve public safety and public health issues, firstly, we are going to use Microsoft Excel and SAS EG to do data preprocessing. Secondly, using support vector machines and decision trees builds predict model, and analyzes the infectious cases between Taiwan and Singapore. By comparing different factors causing vector mosquito from model classification and regression, we can find similar spreading patterns where the disease occurred most frequently. The result can provide sufficient information to predict the future dengue infection outbreaks and control the diffusion of dengue fever among countries.

Keywords: dengue fever, Taiwan, Singapore, Aedes aegypti

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Authors: Shamsulhaq Amin

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Drought can arise from several hydrometeorological phenomena that result in insufficient precipitation, soil moisture, and surface and groundwater flow, leading to conditions that are considerably drier than the usual water content or availability. Drought is often assessed using indices that are associated with meteorological, agricultural, and hydrological phenomena. In order to effectively handle drought disasters, it is essential to accurately determine the kind, intensity, and extent of the drought using drought characterization. This information is critical for managing the drought before, during, and after the rehabilitation process. Over a hundred drought assessments have been created in literature to evaluate drought disasters, encompassing a range of factors and variables. Some models utilise solely hydrometeorological drivers, while others employ remote sensing technology, and some incorporate a combination of both. Comprehending the entire notion of drought and taking into account drought indices along with their calculation processes are crucial for researchers in this discipline. Examining several drought metrics in different studies requires additional time and concentration. Hence, it is crucial to conduct a thorough examination of approaches used in drought indices in order to identify the most straightforward approach to avoid any discrepancies in numerous scientific studies. In case of practical application in real-world, categorizing indices relative to their usage in meteorological, agricultural, and hydrological phenomena might help researchers maximize their efficiency. Users have the ability to explore different indexes at the same time, allowing them to compare the convenience of use and evaluate the benefits and drawbacks of each. Moreover, certain indices exhibit interdependence, which enhances comprehension of their connections and assists in making informed decisions about their suitability in various scenarios. This study provides a comprehensive assessment of various drought indices, analysing their types and computation methodologies in a detailed and systematic manner.

Keywords: drought classification, drought severity, drought indices, agricultur, hydrological

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Authors: Brindha Senthil Kumar, Payel Chakraborty, Senthil Kumar Nachimuthu, Arindam Maitra, Prem Nath

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Gastric cancer is predominantly caused by demographic and diet factors as compared to other cancer types. The aim of the study is to predict Early Gastric Cancer (ECG) from diet and lifestyle factors using supervised machine learning algorithms. For this study, 160 healthy individual and 80 cases were selected who had been followed for 3 years (2016-2019), at Civil Hospital, Aizawl, Mizoram. A dataset containing 11 features that are core risk factors for the gastric cancer were extracted. Supervised machine algorithms: Logistic Regression, Naive Bayes, Support Vector Machine (SVM), Multilayer perceptron, and Random Forest were used to analyze the dataset using Python Jupyter Notebook Version 3. The obtained classified results had been evaluated using metrics parameters: minimum_false_positives, brier_score, accuracy, precision, recall, F1_score, and Receiver Operating Characteristics (ROC) curve. Data analysis results showed Naive Bayes - 88, 0.11; Random Forest - 83, 0.16; SVM - 77, 0.22; Logistic Regression - 75, 0.25 and Multilayer perceptron - 72, 0.27 with respect to accuracy and brier_score in percent. Naive Bayes algorithm out performs with very low false positive rates as well as brier_score and good accuracy. Naive Bayes algorithm classification results in predicting ECG showed very satisfactory results using only diet cum lifestyle factors which will be very helpful for the physicians to educate the patients and public, thereby mortality of gastric cancer can be reduced/avoided with this knowledge mining work.

Keywords: Early Gastric cancer, Machine Learning, Diet, Lifestyle Characteristics

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Authors: Aldrin Avergas, Quennie Mariel Peñaranda, Niña Karen San Miguel, Alexis Katrina Agustin, Peralta Xusha Mae, Maria Luisa Sison

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The research is entitled “The Relationship of Socioeconomic Status and Levels of Delinquency among Senior High School Students with Secured Attachment to their Mothers”. The researchers had explored the relationship between socioeconomic status and delinquent tendencies among grade 11 students. The objective of the research is to discover if delinquent behavior will have a relationship with the current socio-economic status of an adolescent student having a warm relationship with their mothers. The researchers utilized three questionnaires that would measure the three variables of the study, namely: (1) 1SEC 2012: The New Philippines Socioeconomic Classification System was used to show the current socioeconomic status of the respondents, (2) Self-Reported Delinquency – Problem Behavior Frequency Scale was utilized to determine the individual's frequency in engaging to delinquent behavior, and (3) Inventory of Parent and Peer Attachment Revised (IPPA-R) was used to determine the attachment style of the respondents. The researchers utilized a quantitative research design, specifically correlation research. The study concluded that there is no significant relationship between socioeconomic status and academic delinquency despite the fact that these participants had secured attachment to their mother hence this research implies that delinquency is not just a problem for students belonging in the lower socio-economic status and that even having a warm and close relationship with their mothers is not sufficient enough for these students to completely be free from engaging in delinquent acts. There must be other factors (such as peer pressure, emotional quotient, self-esteem or etc.) that are might be contributing to delinquent behaviors.

Keywords: adolescents, delinquency, high school students, secured attachment style, socioeconomic status

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Authors: Atour Taghipour

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In the real world each manufacturing company is an independent business unit. These business units are linked to each other through upstream and downstream linkages. The management of these linkages is called coordination which, could be considered as a difficult engineering task. The degree of difficulty of coordination depends on the type and the nature of information exchanged between partners as well as the structure of relationship from mutual to the network structure. The literature of manufacturing systems comprises a wide range of varieties of methods and approaches of coordination. In fact, two main streams of research can be distinguished: central coordination versus decentralized coordination. In the centralized systems a high degree of information exchanges is required. The high degree of information exchanges sometimes leads to difficulties when independent members do not want to share information. In order to address these difficulties, decentralized approaches of coordination of operations planning decisions based on some minimal information sharing have been proposed in many academic disciplines. This paper first proposes a framework of analysis in order to analyze the proposed approaches in the literature, based on this framework which includes the similarities between approaches we categorize the existing approaches. This classification can be used as a research map for future researches. The result of our paper highlights several opportunities for future research. First, it is proposed to develop more dynamic and stochastic mechanisms of planning coordination of manufacturing units. Second, in order to exploit the complementarities of approaches proposed by diverse science discipline, we propose to integrate the techniques of coordination. Finally, based on our approach we proposed to develop coordination standards to guaranty both the complementarity of these approaches as well as the freedom of companies to adopt any planning tools.

Keywords: network coordination, manufacturing, operations planning, supply chain

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Authors: Ethan James

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Over one billion people worldwide suffer from some level of vision loss or blindness as a result of progressive retinal diseases. Many patients, particularly in developing areas, are incorrectly diagnosed or undiagnosed whatsoever due to unconventional diagnostic tools and screening methods. Artificial intelligence (AI) based on deep learning (DL) convolutional neural networks (CNN) have recently gained a high interest in ophthalmology for its computer-imaging diagnosis, disease prognosis, and risk assessment. Optical coherence tomography (OCT) is a popular imaging technique used to capture high-resolution cross-sections of retinas. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography, and visual fields, achieving robust classification performance in the detection of various retinal diseases including macular degeneration, diabetic retinopathy, and retinitis pigmentosa. However, there is no complete diagnostic model to analyze these retinal images that provide a diagnostic accuracy above 90%. Thus, the purpose of this project was to develop an AI model that utilizes machine learning techniques to automatically diagnose specific retinal diseases from OCT scans. The algorithm consists of neural network architecture that was trained from a dataset of over 20,000 real-world OCT images to train the robust model to utilize residual neural networks with cyclic pooling. This DL model can ultimately aid ophthalmologists in diagnosing patients with these retinal diseases more quickly and more accurately, therefore facilitating earlier treatment, which results in improved post-treatment outcomes.

Keywords: artificial intelligence, deep learning, imaging, medical devices, ophthalmic devices, ophthalmology, retina

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Authors: Mohammad Saber Eslamlou

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Morphology of Islamic cities has been extensively studied by researchers of Islamic cities and different theories could be found about it. In this regard, there exist much difference in method of analysis, classification, recognition, confrontation and comparative method of urban morphology. The present paper aims to examine the previous methods, approaches and insights and that how Dr. Giulia Annalinda Neglia dealt with the analysis of morphology of Islamic cities. Neglia is assistant professor in University of Bari, Italy (UNIBA) who has published numerous papers and books on Islamic cities. I introduce her works in the field of morphology of Islamic cities. And then, her thoughts, insights and research methodologies are presented and analyzed in critical perspective. This is a qualitative research on her written works, which have been classified in three major categories. The first category consists mainly of her works on morphology and physical shape of Islamic cities. The results of her works’ review suggest that she has used Moratoria typology in investigating morphology of Islamic cities. Moreover, overall structure of the cities under investigation is often described linear; however, she’s against to define a single framework for the recognition of morphology in Islamic cities. She states that ‘to understand the physical complexity and irregularities in Islamic cities, it is necessary to study the urban fabric by typology method, focusing on transformation processes of the buildings’ form and their surrounding open spaces’ and she believes that fabric of each region in the city follows from the principles of an specific period or urban pattern, in particular, Hellenistic and Roman structures. Furthermore, she believes that it is impossible to understand the morphology of a city without taking into account the obvious and hidden developments associated with it, because form of building and their surrounding open spaces are written history of the city.

Keywords: city, Islamic city, Giulia Annalinda Neglia, morphology

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Authors: Nicola G. G. Cecca

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In Italian IPSSEOAs, high schools that give a vocational education to students that will work in the field of Enogastronomy and Hotel Management, the course of Food Science allows the students to start and see food as a mixture of substances that they will transform during their profession. These substances are characterized not only by a chemical composition but also by a molecular structure that makes them nutritionally active. But the increasing number of new products proposed by Food Industry, the modern techniques of production and transformation, the innovative preparations required by customers have made many information reported in the most wide spread Food Science textbooks not up-to-date or too poor for the people who will work in catering sector. Often Authors offer information aged to Bohr’s Atomic Model and to the ‘Octet Rule’ proposed by G.N. Lewis to describe the Chemical Bond, without giving any reference to new as Orbital Atomic Model and Molecular Orbital Theory that, in the meantime, start to be old themselves. Furthermore, this antiquated information precludes an easy understanding of a wide range of properties of nutritive substances and many reactions in which the food constituents are involved. In this paper, our attention is pointed out to use GEOMAG™ to represent the dynamics with which the chemical bond is formed during the synthesis of the molecules. GEOMAG™ is a toy, produced by the Swiss Company Geomagword S.A., pointed to stimulate in children, aged between 6-10 years, their fantasy and their handling ability and constituted by metallic spheres and metallic magnetic bars coated by coloured plastic materials. The simulation carried out with GEOMAG™ is based on the similitude existing between the Coulomb’s force and the magnetic attraction’s force and in particular between the formulae with which they are calculated. The electrostatic force (F in Newton) that allows the formation of the chemical bond can be calculated by mean Fc = kc q1 q2/d2 where: q1 e q2 are the charge of particles [in Coulomb], d is the distance between the particles [in meters] and kc is the Coulomb’s constant. It is surprising to observe that the attraction’s force (Fm) acting between the magnetic extremities of GEOMAG™ used to simulate the chemical bond can be calculated in the same way by using the formula Fm = km m1 m2/d2 where: m1 e m2 represent the strength of the poles [A•m], d is the distance between the particles [m], km = μ/4π in which μ is the magnetic permeability of medium [N•A-2]. The magnetic attraction can be tested by students by trying to keep the magnetic elements of GEOMAG™ separate by hands or trying to measure by mean an appropriate dynamometric system. Furthermore, by using a dynamometric system to measure the magnetic attraction between the GEOMAG™ elements is possible draw a graphic F=f(d) to verify that the curve obtained during the simulation is very similar to that one hypnotized, around the 1920’s by Linus Pauling to describe the formation of H2+ in according with Molecular Orbital Theory.

Keywords: chemical bond, molecular orbital theory, magnetic attraction force, GEOMAG™

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Authors: Qingsong Xiong, Cheng Yuan, Qingzhao Kong, Haibei Xiong

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Deep-learning-driven approaches based on vibration responses have attracted larger attention in rapid structural condition assessment while obtaining sufficient measured training data with corresponding labels is relevantly costly and even inaccessible in practical engineering. This study proposes an integrated label propagation network for structural condition assessment, which is able to diffuse the labels from continuously-generating measurements by intact structure to those of missing labels of damage scenarios. The integrated network is embedded with damage-sensitive features extraction by deep autoencoder and pseudo-labels propagation by optimized fuzzy clustering, the architecture and mechanism which are elaborated. With a sophisticated network design and specified strategies for improving performance, the present network achieves to extends the superiority of self-supervised representation learning, unsupervised fuzzy clustering and supervised classification algorithms into an integration aiming at assessing damage conditions. Both numerical simulations and full-scale laboratory shaking table tests of a two-story building structure were conducted to validate its capability of detecting post-earthquake damage. The identifying accuracy of a present network was 0.95 in numerical validations and an average 0.86 in laboratory case studies, respectively. It should be noted that the whole training procedure of all involved models in the network stringently doesn’t rely upon any labeled data of damage scenarios but only several samples of intact structure, which indicates a significant superiority in model adaptability and feasible applicability in practice.

Keywords: autoencoder, condition assessment, fuzzy clustering, label propagation

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Authors: Ayu Dwi Hardiyanti, Bernardus Anggit Winahyu, I. Gusti Agung Ayu Sugita Sari, Lestari Sutra Simamora, I. Wayan Warmada

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The Penosogan Formation sandstone, that has Middle Miosen age, has been deemed as a reservoir potential based on sample data from sandstone outcrop in Kebakalan and Kedawung villages, Karangsambung sub-district, Kebumen Regency, Central Java. This research employs the following analytical methods; petrography, X-ray diffraction (XRD), and porosity test. Based on the presence of micritic sandstone, muddy micrite, and muddy sandstone, the Penosogan Formation sandstone has a fine-coarse granular size and middle-to-fine sorting. The composition of the sandstone is mostly made up of plagioclase, skeletal grain, and traces of micrite. The percentage of clay minerals based on petrographic analysis is 10% and appears to envelop grain, resulting enveloping grain which reduces the porosity of rocks. The porosity types as follows: interparticle, vuggy, channel, and shelter, with an equant form of cement. Moreover, the diagenesis process involves compaction, cementation, authigenic mineral growth, and dissolving due to feldspar alteration. The maturity of the reservoir can be seen through the X-ray diffraction analysis results, using ethylene glycol solution for clay minerals fraction transformed from smectite–illite. Porosity test analysis showed that the Penosogan Formation sandstones has a porosity value of 22% based on the Koeseomadinata classification, 1980. That shows high maturity is very influential for the quality of reservoirs sandstone of the Penosogan Formation.

Keywords: sandstone reservoir, Penosogan Formation, smectite, XRD

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Authors: S. Abdi Goudazri, R. Ziaie Moayed, A. Nazeri

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Loose soils normally are of weak bearing capacity due to their structural nature. Being exposed to heavy traffic loads, they would fail in most cases. To tackle the aforementioned issue, geotechnical engineers have come up with different approaches; one of which is making use of geosynthetic-reinforced soil-aggregate systems. As these polymeric reinforcements have highlighted economic and environmentally-friendly features, they have become widespread in practice during the last decades. The present research investigates the efficiency of four different types of these reinforcements in increasing the bearing capacity of two-layered soil sections using a series California Bearing Ratio (CBR) test. The studied sections are comprised of a 10 cm-thick layer of no. 161 Firouzkooh sand (weak subgrade) and a 10 cm-thick layer of compacted aggregate materials (base course) classified as SP and GW according to the United Soil Classification System (USCS), respectively. The aggregate layer was compacted to the relative density (Dr) of 95% at the optimum water content (Wopt) of 6.5%. The applied reinforcements were including two kinds of geocomposites (type A and B), a geotextile, and a geogrid that were embedded at the interface of the lower and the upper layers of the soil-aggregate system. As the standard CBR mold was not appropriate in height for this study, the mold used for soaked CBR tests were utilized. To make a comparison between the results of stress-settlement behavior in the studied specimens, CBR values pertinent to the penetrations of 2.5 mm and 5 mm were considered. The obtained results demonstrated 21% and 24.5% increments in the amount of CBR value in the presence of geocomposite type A and geogrid, respectively. On the other hand, the effect of both geotextile and geocomposite type B on CBR values was generally insignificant in this research.

Keywords: geosynthetics, geogrid, geotextile, CBR test, increasing bearing capacity

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Authors: Parul Johri, Mala Trivedi

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Major Intrinsic proteins (MIPs), actively involved in the passive transport of small polar molecules across the membranes of almost all living organisms. MIPs that specifically transport water molecules are named aquaporins (AQPs). The permeability of membranes is actively controlled by the regulation of the amount of different MIPs present but also in some cases by phosphorylation and dephosphorylation of the channel. Based on sequence similarity, MIPs have been classified into many categories. All of the proteins are made up of the 20 amino acids, the only difference is there in their orientations. Again all the 20 amino acids are made up of the basic five elements namely: carbon, hydrogen, oxygen, sulphur and nitrogen. These elements are responsible for giving the amino acids the properties of hydrophilicity/hydrophobicity which play an important role in protein interactions. The hydrophobic amino acids characteristically have greater number of carbon atoms as carbon is the main element which contributes to hydrophobic interactions in proteins. It is observed that the carbon level of proteins in different species is different. In the present work, we have taken a sample set of 150 aquaporins proteins from Uniprot database and a dynamic programming code was written to calculate the carbon percentage for each sequence. This carbon percentage was further used to barcode the aqauporins of animals and plants. The protein taken from Oryza sativa, Zea mays and Arabidopsis thaliana preferred to have carbon percentage of 31.8 to 35, whereas on the other hand sequences taken from Mus musculus, Saccharomyces cerevisiae, Homo sapiens, Bos Taurus, and Rattus norvegicus preferred to have carbon percentage of 31 to 33.7. This clearly demarks the carbon range in the aquaporin proteins from plant and animal origin. Hence the atom level analysis of protein sequences can provide us with better results as compared to the residue level comparison.

Keywords: aquaporins, carbon, dynamic prgramming, MIPs

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Authors: Silvija Šiljeg, Ivan Marić, Ante Šiljeg

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The accessibility of urban green spaces (UGS) is an integral element in the quality of life. Due to rapid urbanization, UGS studies have become a key element in urban planning. The potential benefits of space for its inhabitants are frequently analysed. A functional transport network system and the optimal spatial distribution of urban green surfaces are the prerequisites for maintaining the environmental equilibrium of the urban landscape. An accessibility analysis was conducted as part of the Urban Green Belts Project (UGB). The development of a GIS database for Zadar was the first step in generating the UGS accessibility indicator. Data were collected using the supervised classification method of multispectral LANDSAT images and manual vectorization of digital orthophoto images (DOF). An analysis of UGS accessibility according to the ANGst standard was conducted in the first phase of research. The accessibility indicator was generated on the basis of seven objective measurements, which included average UGS surface per capita and accessibility according to six functional levels of green surfaces. The generated indicator was compared with subjective measurements obtained by conducting a survey (718 respondents) within statistical units. The collected data reflected individual assessments and subjective evaluations of UGS accessibility. This study highlighted the importance of using objective and subjective measures in the process of understanding the accessibility of urban green surfaces. It may be concluded that when evaluating UGS accessibility, residents emphasize the immediate residential environment, ignoring higher UGS functional levels. It was also concluded that large areas of UGS within a city do not necessarily generate similar satisfaction with accessibility. The heterogeneity of output results may serve as guidelines for the further development of a functional UGS city network.

Keywords: urban green spaces (UGS), accessibility indicator, subjective and objective measurements, Zadar

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Authors: Vinay Kumar, M. Kishor, Sathyanarayana Rao Ts

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Background: Growth of elderly people in the general population in recent years is termed as ‘greying of the world’ where there is a shift from high mortality & fertility to low mortality and fertility, resulting in an increased proportion of older people as seen in India. Improved health care promises longevity but socio-economic factors like poverty, joint families and poor services pose a psychological threat. Epidemiological data regarding the prevalence of mental disorders in geriatric population with physical illness is required for proper health planning. Methods: Sixty consecutive elderly patients aged 60 years or above of both sexes, reporting with physical illness to general outpatient registration counter of JSS Medical College and Hospital, Mysore, India, were considered for the Study. With informed consent, they were screened with General Health Questionnaire (GHQ-12) and were further evaluated for diagnosing mental disorders according to WHO International Classification of Diseases (ICD-10) criteria. Results: Mental disorders were detected in 48.3%, predominantly depressive disorders, nicotine dependence, generalized anxiety disorder, alcohol dependence and least was dementia. Most common physical illness was cardiovascular disease followed by metabolic, respiratory and other diseases. Depressive disorders, substance dependence and dementia were more associated with cardiovascular disease compared to metabolic disease and respiratory diseases were more associated with nicotine dependence. Conclusions: Depression and Substance use disorders among elderly population is of concern, which needs to be further studied with larger population. Psychiatric morbidity will adversely have an impact on physical illness which needs proper assessment and management. This will enhance our understanding and prioritize our planning for future.

Keywords: Geriatric, mental disorders, physical illness, psychiatry

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Authors: Wedad Albalawi

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The mathematical inequalities have been the core of mathematical study and used in almost all branches of mathematics as well in various areas of science and engineering. The inequalities by Hardy, Littlewood and Polya were the first significant composition of several science. This work presents fundamental ideas, results and techniques, and it has had much influence on research in various branches of analysis. Since 1934, various inequalities have been produced and studied in the literature. Furthermore, some inequalities have been formulated by some operators; in 1989, weighted Hardy inequalities have been obtained for integration operators. Then, they obtained weighted estimates for Steklov operators that were used in the solution of the Cauchy problem for the wave equation. They were improved upon in 2011 to include the boundedness of integral operators from the weighted Sobolev space to the weighted Lebesgue space. Some inequalities have been demonstrated and improved using the Hardy–Steklov operator. Recently, a lot of integral inequalities have been improved by differential operators. Hardy inequality has been one of the tools that is used to consider integrity solutions of differential equations. Then, dynamic inequalities of Hardy and Coposon have been extended and improved by various integral operators. These inequalities would be interesting to apply in different fields of mathematics (functional spaces, partial differential equations, mathematical modeling). Some inequalities have been appeared involving Copson and Hardy inequalities on time scales to obtain new special version of them. A time scale is an arbitrary nonempty closed subset of the real numbers. Then, the dynamic inequalities on time scales have received a lot of attention in the literature and has become a major field in pure and applied mathematics. There are many applications of dynamic equations on time scales to quantum mechanics, electrical engineering, neural networks, heat transfer, combinatorics, and population dynamics. This study focuses on Hardy and Coposon inequalities, using Steklov operator on time scale in double integrals to obtain special cases of time-scale inequalities of Hardy and Copson on high dimensions. The advantage of this study is that it uses the one-dimensional classical Hardy inequality to obtain higher dimensional on time scale versions that will be applied in the solution of the Cauchy problem for the wave equation. In addition, the obtained inequalities have various applications involving discontinuous domains such as bug populations, phytoremediation of metals, wound healing, maximization problems. The proof can be done by introducing restriction on the operator in several cases. The concepts in time scale version such as time scales calculus will be used that allows to unify and extend many problems from the theories of differential and of difference equations. In addition, using chain rule, and some properties of multiple integrals on time scales, some theorems of Fubini and the inequality of H¨older.

Keywords: time scales, inequality of hardy, inequality of coposon, steklov operator

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Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee

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Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.

Keywords: deep neural models, natural language inference, recognizing textual entailment (RTE), sentence-to-sentence relation

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Authors: Antonio Pratelli, Lorenzo Brocchini, Reginald Roy Souleyrette

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A rotary is a traffic circle intersection where vehicles entering from branches give priority to circulating flow. Vehicles entering the intersection from converging roads move around the central island and weave out of the circle into their desired exiting branch. This creates merging and diverging conflicts among any entry and its successive exit, i.e., a section. Therefore, rotary capacity models are usually based on the weaving of the different movements in any section of the circle, and the maximum rate of flow value is then related to each weaving section of the rotary. Nevertheless, the single-section capacity value does not lead to the typical performance characteristics of the intersection, such as the entry average delay which is directly linked to its level of service. From another point of view, modern roundabout capacity models are based on the limitation of the flow entering from the single entrance due to the amount of flow circulating in front of the entrance itself. Modern roundabouts capacity models generally lead also to a performance evaluation. This paper aims to incorporate a modern roundabout capacity model into an old rotary capacity method to obtain from the latter the single input capacity and ultimately achieve the related performance indicators. Put simply; the main objective is to calculate the average delay of each single roundabout entrance to apply the most common Highway Capacity Manual, or HCM, criteria. The paper is organized as follows: firstly, the rotary and roundabout capacity models are sketched, and it has made a brief introduction to the model combination technique with some practical instances. The successive section is deserved to summarize the TRRL old rotary capacity model and the most recent HCM-7th modern roundabout capacity model. Then, the two models are combined through an iteration-based algorithm, especially set-up and linked to the concept of roundabout total capacity, i.e., the value reached due to a traffic flow pattern leading to the simultaneous congestion of all roundabout entrances. The solution is the average delay for each entrance of the rotary, by which is estimated its respective level of service. In view of further experimental applications, at this research stage, a collection of existing rotary intersections operating with the priority-to-circle rule has already started, both in the US and in Italy. The rotaries have been selected by direct inspection of aerial photos through a map viewer, namely Google Earth. Each instance has been recorded by location, general urban or rural, and its main geometrical patterns. Finally, conclusion remarks are drawn, and a discussion on some further research developments has opened.

Keywords: mixed methods, old rotary and modern roundabout capacity models, total capacity algorithm, level of service estimation

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Authors: Wendu Pang, Yaxin Luo, Junhong Li, Yu Zhao, Danni Cheng, Yufang Rao, Minzi Mao, Ke Qiu, Yijun Dong, Fei Chen, Jun Liu, Jian Zou, Haiyang Wang, Wei Xu, Jianjun Ren

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We aimed to compare the prognostic prediction value of positive lymph node number (PLNN) to the American Joint Committee on Cancer (AJCC) tumor, lymph node, and metastasis (TNM) staging system for patients with hypopharyngeal squamous cell carcinoma (HPSCC). A total of 826 patients with HPSCC from the Surveillance, Epidemiology, and End Results database (2004–2015) were identified and split into two independent cohorts: training (n=461) and validation (n=365). Univariate and multivariate Cox regression analyses were used to evaluate the prognostic effects of PLNN in patients with HPSCC. We further applied six Cox regression models to compare the survival predictive values of the PLNN and AJCC TNM staging system. PLNN showed a significant association with overall survival (OS) and cancer-specific survival (CSS) (P < 0.001) in both univariate and multivariable analyses, and was divided into three groups (PLNN 0, PLNN 1-5, and PLNN>5). In the training cohort, multivariate analysis revealed that the increased PLNN of HPSCC gave rise to significantly poor OS and CSS after adjusting for age, sex, tumor size, and cancer stage; this trend was also verified by the validation cohort. Additionally, the survival model incorporating a composite of PLNN and TNM classification (C-index, 0.705, 0.734) performed better than the PLNN and AJCC TNM models. PLNN can serve as a powerful survival predictor for patients with HPSCC and is a surrogate supplement for cancer staging systems.

Keywords: hypopharyngeal squamous cell carcinoma, positive lymph nodes number, prognosis, prediction models, survival predictive values

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