Search results for: flight test data

Authors: Najmeh Hoseini

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Strokerecovery happens through neuroplasticity, which is highly influenced by the environment, including neuro-rehabilitation. Transcranial direct current stimulation (tDCS) may enhance recovery by modulating neuroplasticity. With tDCS, weak direct currents are applied noninvasively to modify excitability in the cortical areas under its electrodes. Combined with functional activities, this may facilitate motor recovery in neurologic disorders such as stroke. The purpose of this case study was to examine the effect of tDCS combined with 30 minutes of traditional physical therapy (PT)on arm function following a stroke. A 29-year-old male with chronic stroke involving the left middle cerebral artery territory went through the treatment protocol. Design The design included 5 weeks of treatment: 1 week of traditional PT, 2 weeks of sham tDCS combined with traditional PT, and 2 weeks of tDCS combined with traditional PT. PT included functional electrical stimulation (FES) of wrist extensors followed by task-specific functional training. Dual hemispheric tDCS with 1 mA intensity was applied on the sensorimotor cortices for the first 20 min of the treatment combined with FES. Assessments before and after each treatment block included Modified Ashworth Scale, ChedokeMcmaster Arm and Hand inventory, Action Research Arm Test (ARAT), and the Box and Blocks Test. Results showed reduced spasticity in elbow and wrist flexors only after tDCS combination weeks (+1 to 0). The patient demonstrated clinically meaningful improvements in gross motor and fine motor control over the duration of the study; however, components of the ARAT that require fine motor control improved the greatest during the experimental block. Average time improvement compared to baseline was26.29 s for tDCS combination weeks, 18.48 s for sham tDCS, and 6.83 for PT standard of care weeks. Combining dual hemispheric tDCS with the standard of care PT demonstrated improvements in hand dexterity greater than PT alone in this patient case.

Keywords: tDCS, stroke, case study, physical therapy

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Authors: Fahd Sabry Esmail, M. Badr Senousy, Mohamed Ragaie

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In recent years, there has been an explosion in the rate of using technology that help discovering the diseases. For example, DNA microarrays allow us for the first time to obtain a "global" view of the cell. It has great potential to provide accurate medical diagnosis, to help in finding the right treatment and cure for many diseases. Various classification algorithms can be applied on such micro-array datasets to devise methods that can predict the occurrence of Leukemia disease. In this study, we compared the classification accuracy and response time among eleven decision tree methods and six rule classifier methods using five performance criteria. The experiment results show that the performance of Random Tree is producing better result. Also it takes lowest time to build model in tree classifier. The classification rules algorithms such as nearest- neighbor-like algorithm (NNge) is the best algorithm due to the high accuracy and it takes lowest time to build model in classification.

Keywords: data mining, classification techniques, decision tree, classification rule, leukemia diseases, microarray data

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Authors: Yasir Ali Soomro

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Companies that demonstrate corporate social responsibilities (CSR) are more likely to withstand any downturn or crises because of the trust built with stakeholders. Many firms are utilizing CSR marketing to improve the interactions with their various stakeholders, mainly the consumers. Most previous research on CSR has focused on the impact of CSR on customer responses and behaviors toward a company. As online food ordering and grocery shopping remains inevitable. This study will investigate structural relationships among consumer positive emotions (CPE) and negative emotions (CNE), Corporate Reputation (CR), Customer Trust (CT), Brand Image (BI), and Brand attitude (BA) on behavioral outcomes such as Online purchase intention (OPI) and Word of mouth (WOM) in retail grocery and food restaurants setting. Hierarchy of Effects Model will be used as theoretical, conceptual framework. The model describes three stages of consumer behavior: (i) cognitive, (ii) affective, and (iii) conative. The study will apply a quantitative method to test the hypotheses; a self-developed questionnaire with non-probability sampling will be utilized to collect data from 500 consumers belonging to generation X, Y, and Z residing in KSA. The study will contribute by providing empirical evidence to support the link between CSR and customer affective and conative experiences in Saudi Arabia. The theoretical contribution of this study will be empirically tested comprehensive model where CPE, CNE, CR, CT, BI, and BA act as mediating variables between the perceived CSR & Online purchase intention (OPI) and Word of mouth (WOM). Further, the study will add more to how the emotional/ psychological process mediates in the CSR literature, especially in the Middle Eastern context. The proposed study will also explain the effect of perceived CSR marketing initiatives directly and indirectly on customer behavioral responses.

Keywords: corporate social responsibility, corporate reputation, consumer emotions, loyalty, online purchase intention, word-of-mouth, structural equation modeling

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Authors: Chitresh Prasad, Arvind Ramesh, Aditya Virkar, Karan Dholkaria, Vinayak Malhotra

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Solid Propellant Rocket is a rocket that utilises a combination of a solid Oxidizer and a solid Fuel. Success in Solid Rocket Motor design and development depends significantly on knowledge of burning rate behaviour of the selected solid propellant under all motor operating conditions and design limit conditions. Most Solid Motor Rockets consist of the Main Engine, along with multiple Boosters that provide an additional thrust to the space-bound vehicle. Though widely used, they have been eclipsed by Liquid Propellant Rockets, because of their better performance characteristics. The addition of a catalyst such as Iron Oxide, on the other hand, can drastically enhance the performance of a Solid Rocket. This scientific investigation tries to emulate the working of a Solid Rocket using Sparklers and Energized Candles, with a central Energized Candle acting as the Main Engine and surrounding Sparklers acting as the Booster. The Energized Candle is made of Paraffin Wax, with Magnesium filings embedded in it’s wick. The Sparkler is made up of 45% Barium Nitrate, 35% Iron, 9% Aluminium, 10% Dextrin and the remaining composition consists of Boric Acid. The Magnesium in the Energized Candle, and the combination of Iron and Aluminium in the Sparkler, act as catalysts and enhance the burn rates of both materials. This combustion of Metallized Propellants has an influence over the regression rate of the subject candle. The experimental parameters explored here are Separation Distance, Systematically varying Configuration and Layout Symmetry. The major performance parameter under observation is the Regression Rate of the Energized Candle. The rate of regression is significantly affected by the orientation and configuration of the sparklers, which usually act as heat sources for the energized candle. The Overall Efficiency of any engine is factorised by the thermal and propulsive efficiencies. Numerous efforts have been made to improve one or the other. This investigation focuses on the Orientation of Rocket Motor Design to maximize their Overall Efficiency. The primary objective is to analyse the Flame Spread Rate variations of the energized candle, which resembles the solid rocket propellant used in the first stage of rocket operation thereby affecting the Specific Impulse values in a Rocket, which in turn have a deciding impact on their Time of Flight. Another objective of this research venture is to determine the effectiveness of the key controlling parameters explored. This investigation also emulates the exhaust gas interactions of the Solid Rocket through concurrent ignition of the Energized Candle and Sparklers, and their behaviour is analysed. Modern space programmes intend to explore the universe outside our solar system. To accomplish these goals, it is necessary to design a launch vehicle which is capable of providing incessant propulsion along with better efficiency for vast durations. The main motivation of this study is to enhance Rocket performance and their Overall Efficiency through better designing and optimization techniques, which will play a crucial role in this human conquest for knowledge.

Keywords: design modifications, improving overall efficiency, metallized combustion, regression rate variations

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Authors: Peris Wanjiku

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The objective of this paper is to describe the development and implications of a national nursing workforce analytical system in Kenya. Findings: Creating a national electronic nursing workforce analytical system provides more reliable information on nurses ‘national demographics, migration patterns, and workforce capacity and efficiency. Data analysis is most useful for human resources for health (HRH) planning when workforce capacity data can be linked to worksite staffing requirements. As a result of establishing this database, the Kenya Ministry of Health has improved its capability to assess its nursing workforce and document important workforce trends, such as out-migration. Current data identify the United States as the leading recipient country of Kenyan nurses. The overwhelming majority of Kenyan nurses who decide to out-migrate are amongst Kenya’s most qualified. Conclusions: The Kenya nursing database is a first step toward facilitating evidence-based decision-making in HRH. This database is unique to developing countries in sub-Saharan Africa. Establishing an electronic workforce database requires long-term investment and sustained support by national and global stakeholders.

Keywords: analytical, information, health, migration

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Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay

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Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.

Keywords: retail stores, faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition

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Authors: Cornelia-Eugenia Munteanu

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The goal of this paper is to present the diagnostic contribution that the screening instrument, Mini-Mental State Examination-2: Expanded Version (MMSE-2:EV), brings in detecting the cognitive impairment or in monitoring the progress of degenerative disorders. The diagnostic signification is underlined by the interpretation of the MMSE-2:EV scores, resulted from the test application to patients with mild and major neurocognitive disorders. The original MMSE is one of the most widely used screening tools for detecting the cognitive impairment, in clinical settings, but also in the field of neurocognitive research. Now, the practitioners and researchers are turning their attention to the MMSE-2. To enhance its clinical utility, the new instrument was enriched and reorganized in three versions (MMSE-2:BV, MMSE-2:SV and MMSE-2:EV), each with two forms: blue and red. The MMSE-2 was adapted and used successfully in Romania since 2013. The cases were selected from current practice, in order to cover vast and significant neurocognitive pathology: mild cognitive impairment, Alzheimer’s disease, vascular dementia, mixed dementia, Parkinson’s disease, conversion of the mild cognitive impairment into Alzheimer’s disease. The MMSE-2:EV version was used: it was applied one month after the initial assessment, three months after the first reevaluation and then every six months, alternating the blue and red forms. Correlated with age and educational level, the raw scores were converted in T scores and then, with the mean and the standard deviation, the z scores were calculated. The differences of raw scores between the evaluations were analyzed from the point of view of statistic signification, in order to establish the progression in time of the disease. The results indicated that the psycho-diagnostic approach for the evaluation of the cognitive impairment with MMSE-2:EV is safe and the application interval is optimal. The alternation of the forms prevents the learning phenomenon. The diagnostic accuracy and efficient therapeutic conduct derive from the usage of the national test norms. In clinical settings with a large flux of patients, the application of the MMSE-2:EV is a safe and fast psycho-diagnostic solution. The clinicians can draw objective decisions and for the patients: it doesn’t take too much time and energy, it doesn’t bother them and it doesn’t force them to travel frequently.

Keywords: MMSE-2, dementia, cognitive impairment, neuropsychology

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Authors: Mohaammad Ahmadpanah, Amineh Akhondi, Mohammad Haghighi, Ali Ghaleiha, Leila Jahangard, Elham Salari

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Background: Working memory includes the capability to keep and manipulate information in a short period of time. This capability is the basis of complicated judgments and has been attended to as the specific and constant character of individuals. Children with attention deficit and hyperactivity are among the people suffering from deficiency in the active memory, and this deficiency has been attributed to the problem of frontal lobe. This study utilizes a new approach with suitable tasks and methods for training active memory and assessment of the effects of the trainings. Participants: The children participating in this study were of 7-15 year age, who were diagnosed by the psychiatrist and psychologist as hyperactive and attention deficit based on DSM-IV criteria. The intervention group was consisted of 8 boys and 6 girls with the average age of 11 years and standard deviation of 2, and the control group was consisted of 2 girls and 5 boys with an average age of 11.4 and standard deviation of 3. Three children in the test group and two in the control group were under medicinal therapy. Results: Working memory training meaningfully improved the performance in not-trained areas as visual-spatial working memory as well as the performance in Raven progressive tests which are a perfect example of non-verbal, complicated reasoning tasks. In addition, motional activities – measured based on the number of head movements during computerized measuring program – was meaningfully reduced in the medication group. The results of the second test showed that training similar exercise to teenagers and adults results in the improvement of cognition functions, as in hyperactive people. Discussion: The results of this study showed that the performance of working memory is improved through training, and these trainings are extended and generalized in other areas of cognition functions not receiving any training. Trainings resulted in the improvement of performance in the tasks related to prefrontal. They had also a positive and meaningful impact on the moving activities of hyperactive children.

Keywords: attention deficit hyperactivity disorder, working memory, non-medical treatment, children

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Authors: Lynndee Kemmet

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The U.S. military plays an increasing role in supporting political stability efforts, and this includes efforts to prevent the food insecurity that can trigger political and social instability. This paper presents a model that assists military commanders in identifying variables that impact food production and distribution in their areas of operation (AO), in identifying connections between variables and in assessing the impacts of those variables on food production and distribution. Through use of the model, military units can better target their data collection efforts and can categorize and analyze data within the data categorization framework most widely-used by military forces—PMESII-PT (Political, Military, Economic, Infrastructure, Information, Physical Environment and Time). The model provides flexibility of analysis in that commanders can target analysis to be highly focused on a specific PMESII-PT domain or variable or conduct analysis across multiple PMESII-PT domains. The model is also designed to assist commanders in mapping food systems in their AOs and then identifying components of those systems that must be strengthened or protected.

Keywords: food security, food system model, political stability, US Military

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Authors: Vani Singhal, Jitendra Parmar, Satyendra Singh Chouhan

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Unseen class discovery has now become an important part of a machine-learning algorithm to judge new classes. Unseen classes are the classes on which the machine learning model is not trained on. With the advancement in technology and AI replacing humans, the amount of data has increased to the next level. So while implementing a model on real-world examples, we come across unseen new classes. Our aim is to find the number of unseen classes by using a hierarchical-based active learning algorithm. The algorithm is based on hierarchical clustering as well as active sampling. The number of clusters that we will get in the end will give the number of unseen classes. The total clusters will also contain some clusters that have unseen classes. Instead of first discovering unseen classes and then finding their number, we directly calculated the number by applying the algorithm. The dataset used is for intent classification. The target data is the intent of the corresponding query. We conclude that when the machine learning model will encounter real-world data, it will automatically find the number of unseen classes. In the future, our next work would be to label these unseen classes correctly.

Keywords: active sampling, hierarchical clustering, open world learning, unseen class discovery

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Authors: Y. Mehdipour, S. Ebrahimi, A. Jahanpour, F. Seyedzaei, B. Sabayan, A. Karimi, H. Amirifard

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Ischemic stroke is one of the common reasons for disability and mortality. The fourth leading cause of death in the world and the third in some other sources. Only 1/3 of the patients with ischemic stroke fully recover, 1/3 of them end in permanent disability and 1/3 face death. Thus, the use of predictive models to predict stroke has a vital role in reducing the complications and costs related to this disease. Thus, the aim of this study was to specify the effective factors and predict ischemic stroke with the help of DM methods. The present study was a descriptive-analytic study. The population was 213 cases from among patients referring to Ali ibn Abi Talib (AS) Hospital in Zahedan. Data collection tool was a checklist with the validity and reliability confirmed. This study used DM algorithms of decision tree for modeling. Data analysis was performed using SPSS-19 and SPSS Modeler 14.2. The results of the comparison of algorithms showed that CHAID algorithm with 95.7% accuracy has the best performance. Moreover, based on the model created, factors such as anemia, diabetes mellitus, hyperlipidemia, transient ischemic attacks, coronary artery disease, and atherosclerosis are the most effective factors in stroke. Decision tree algorithms, especially CHAID algorithm, have acceptable precision and predictive ability to determine the factors affecting ischemic stroke. Thus, by creating predictive models through this algorithm, will play a significant role in decreasing the mortality and disability caused by ischemic stroke.

Keywords: data mining, ischemic stroke, decision tree, Bayesian network

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Authors: Qiang Bu

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This paper compares the explanatory power of sentiment level and sentiment shock. The preliminary test results show that sentiment shock plays a more significant role in explaining stocks returns, including the raw return and abnormal return. We also find that sentiment shock beta has a higher statistical significance than sentiment beta. These finding sheds new light on the relationship between investor sentiment and stock returns.

Keywords: sentiment level, sentiment shock, explanatory power, abnormal stock return, beta

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Authors: K. A. Adepoju, O. I. Shittu, A. U. Chukwu

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In this paper, a new four-parameter generalized version of the Fisher Snedecor distribution called Beta- F distribution is introduced. The comprehensive account of the statistical properties of the new distributions was considered. Formal expressions for the cumulative density function, moments, moment generating function and maximum likelihood estimation, as well as its Fisher information, were obtained. The flexibility of this distribution as well as its robustness using cancer remission time data was demonstrated. The new distribution can be used in most applications where the assumption underlying the use of other lifetime distributions is violated.

Keywords: fisher-snedecor distribution, beta-f distribution, outlier, maximum likelihood method

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Authors: Irfan U. Din

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The growing presence and operational capacity of Islamic State aka Daesh, which emerged in Pak-Afghan region in 2015, poses a serious threat to the already fragile state of the security situation in the region. This paper will shed light on the current state of IS-K network in the Pak-Afghan region and will explain how its presence and operational capacity in the northern and central Afghanistan has increased despite intensive military operations against the group in Nangarhar province – the stronghold of IS-K. It will also explore the role of Pakistani Taliban in the emergence and expansion of IS-K in the region and will unveil the security implication of growing nexus of IS-K and transnational organized groups for the region in Post NATO withdrawal scenario. The study will be qualitative and will rely on secondary and primary data to explore the topic. For secondary data existing literature on the topic will be extensively reviewed while for primary data in-depth interviews will be conducted with subject experts, Taliban commanders, and field researchers.

Keywords: Islamic State of Khorasan (IS-K), North Atlantic Treaty Organization (NATO), Pak-Afghan Region, Transnational Organized Crime (TNOC)

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Authors: A. Bertašienė

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Energy harvesting from any structure makes a challenge. Different structure of air/wind flows in industrial, environmental and residential applications emerge the real flow investigation in detail. Many of the application fields are hardly achievable to the detailed description due to the lack of up-to-date statistical data analysis. In situ measurements aim crucial investments thus the simulation methods come to implement structural analysis of the flows. Different configurations of testing environment give an overview how important is the simple structure of field in limited area on efficiency of the system operation and the energy output. Several configurations of modeled working sections in air flow test facility was implemented in CFD ANSYS environment to compare experimentally and numerically air flow development stages and forms that make effects on efficiency of devices and processes. Effective form and amount of these flows under different geometry cases define the manner of instruments/devices that measure fluid flow parameters for effective operation of any system and emission flows to define. Different fluid flow regimes were examined to show the impact of fluctuations on the development of the whole volume of the flow in specific environment. The obtained results rise the discussion on how these simulated flow fields are similar to real application ones. Experimental results have some discrepancies from simulation ones due to the models implemented to fluid flow analysis in initial stage, not developed one and due to the difficulties of models to cover transitional regimes. Recommendations are essential for energy harvesting systems in both, indoor and outdoor cases. Further investigations aim to be shifted to experimental analysis of flow under laboratory conditions using state-of-the-art techniques as flow visualization tool and later on to in situ situations that is complicated, cost and time consuming study.

Keywords: fluid flow, initial region, tube coefficient, distinct shape

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Authors: Gregor Kosec

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Simple and robust numerical approach for solving flow problems is presented, where involved physical fields are represented through the local approximation functions, i.e., the considered field is approximated over a local support domain. The approximation functions are then used to evaluate the partial differential operators. The type of approximation, the size of support domain, and the type and number of basis function can be general. The solution procedure is formulated completely through local computational operations. Besides local numerical method also the pressure velocity is performed locally with retaining the correct temporal transient. The complete locality of the introduced numerical scheme has several beneficial effects. One of the most attractive is the simplicity since it could be understood as a generalized Finite Differences Method, however, much more powerful. Presented methodology offers many possibilities for treating challenging cases, e.g. nodal adaptivity to address regions with sharp discontinuities or p-adaptivity to treat obscure anomalies in physical field. The stability versus computation complexity and accuracy can be regulated by changing number of support nodes, etc. All these features can be controlled on the fly during the simulation. The presented methodology is relatively simple to understand and implement, which makes it potentially powerful tool for engineering simulations. Besides simplicity and straightforward implementation, there are many opportunities to fully exploit modern computer architectures through different parallel computing strategies. The performance of the method is presented on the lid driven cavity problem, backward facing step problem, de Vahl Davis natural convection test, extended also to low Prandtl fluid and Darcy porous flow. Results are presented in terms of velocity profiles, convergence plots, and stability analyses. Results of all cases are also compared against published data.

Keywords: fluid flow, meshless, low Pr problem, natural convection

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Authors: Dusanee Suwankhong, Pranee Liamputtong

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Mothers living with HIV tend to experience stigma and discrimination which has an impact on their psychological and social well-being and their human rights. This paper explores the lived experience of Thai mothers with HIV in their family. In-depth interviewing and drawing methods were employed to gain a deep understanding on the experience of 30 HIV-positive mothers in the southern community of Thailand. The data was analyzed using thematic analysis method. We found that the majority of HIV-positive mothers learned about their HIV status through blood test services during their antenatal care, but some decided to visit a doctor when their partner became chronically frail and showed some signs indicating HIV/AIDS. Learning about their HIV gave them a great shock, and they could not believe that they were infected with HIV/AIDS. They feared that their illness would be disclosed and hence attempted to keep their HIV secret. This was due to the fact that people in their community would blame and labeled them as a ‘disgusting person’. Besides, they would be separated from social contacts and networks, their individual rights would be disregarded, and their potential roles would be restricted. Although participants suggested that people had more positive view on HIV-infected person nowadays, all still wanted to keep it secret because of fear of stigma and discrimination. Thai health care has provided various kinds of support programs, but many mothers chose not to participate due to the fear of disclosure. However, the women attempted to seek some strategies to live a life which would be more acceptable by the community. We conclude that HIV is still seen as a stigmatised disease in rural community of southern Thailand. Local health care providers and relevant sectors in the locality should create suitable programs to enhance self-worth among those HIV-positive mothers because this could increase a quality of life of this vulnerable mothers. Providing sufficient and appropriate supports for better emotional wellbeing is an essential role of health professionals so that the feeling of isolation among these women could be eliminated and positive social justice can be achieved.

Keywords: HIV-positive mothers, lived experience, southern Thailand, stigma and discrimination

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Authors: Thiago M. R Dias, Gray F. Moita

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The analysis of scientific collaboration networks has contributed significantly to improving the understanding of how does the process of collaboration between researchers and also to understand how the evolution of scientific production of researchers or research groups occurs. However, the identification of collaborations in large scientific databases is not a trivial task given the high computational cost of the methods commonly used. This paper proposes a method for identifying collaboration in large data base of curriculum researchers. The proposed method has low computational cost with satisfactory results, proving to be an interesting alternative for the modeling and characterization of large scientific collaboration networks.

Keywords: extraction, data integration, information retrieval, scientific collaboration

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Authors: Koutsopoulou Ioanna, Gkintoni Evgenia, Halkiopoulos Constantinos, Antonopoulou Hera

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Recent advances in Internet Computer Technology (ICT) and the ever-increasing use of technological equipment amongst adolescents and young adults along with unattended access to the internet and social media and uncontrolled use of smart phones and PCs have caused social problems like sexting to emerge. The main purpose of the present article is first to present an analytic theoretical framework of sexting as a recent social phenomenon based on studies that have been conducted the last decade or so; and second to investigate Greek students’ and also social network users, sexting perceptions and to record how often social media users exchange sexual messages and to retrace demographic variables predictors. Data from 1,000 students were collected and analyzed and all statistical analysis was done by the software package WEKA. The results indicate among others, that the use of data mining methods is an important tool to draw conclusions that could affect decision and policy making especially in the field and related social topics of educational psychology. To sum up, sexting lurks many risks for adolescents and young adults students in Greece and needs to be better addressed in relevance to the stakeholders as well as society in general. Furthermore, policy makers, legislation makers and authorities will have to take action to protect minors. Prevention strategies based on Greek cultural specificities are being proposed. This social problem has raised concerns in recent years and will most likely escalate concerns in global communities in the future.

Keywords: educational ethics, sexting, Greek sexters, sex education, data mining

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Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

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Quantitative structure-retention relationship (QSRR) analysis was used to predict the chromatographic behavior of s-triazine derivatives by using theoretical descriptors computed from the chemical structure. Fundamental basis of the reported investigation is to relate molecular topological descriptors with chromatographic behavior of s-triazine derivatives obtained by reversed-phase (RP) thin layer chromatography (TLC) on silica gel impregnated with paraffin oil and applied ethanol-water (φ = 0.5-0.8; v/v). Retention parameter (RM0) of 14 investigated s-triazine derivatives was used as dependent variable while simple connectivity index different orders were used as independent variables. The best QSRR model for predicting RM0 value was obtained with simple third order connectivity index (3χ) in the second-degree polynomial equation. Numerical values of the correlation coefficient (r=0.915), Fisher's value (F=28.34) and root mean square error (RMSE = 0.36) indicate that model is statistically significant. In order to test the predictive power of the QSRR model leave-one-out cross-validation technique has been applied. The parameters of the internal cross-validation analysis (r2CV=0.79, r2adj=0.81, PRESS=1.89) reflect the high predictive ability of the generated model and it confirms that can be used to predict RM0 value. Multivariate classification technique, hierarchical cluster analysis (HCA), has been applied in order to group molecules according to their molecular connectivity indices. HCA is a descriptive statistical method and it is the most frequently used for important area of data processing such is classification. The HCA performed on simple molecular connectivity indices obtained from the 2D structure of investigated s-triazine compounds resulted in two main clusters in which compounds molecules were grouped according to the number of atoms in the molecule. This is in agreement with the fact that these descriptors were calculated on the basis of the number of atoms in the molecule of the investigated s-triazine derivatives.

Keywords: s-triazines, QSRR, chemometrics, chromatography, molecular descriptors

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Authors: Yang Yang, Lu Xin

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The study of extant musical sites can provide a side-by-side picture of historical ethnomusicological information. In their data collection on Chinese opera houses, researchers found that one Ming Dynasty opera house reached a width of nearly 18 meters, while all opera houses of the same period and after it was far from such a width, being significantly smaller than 18 meters. The historical transient fluctuations in the data dimension of width that caused Chinese theatres to fluctuate in the absence of construction scale constraints have piqued the interest of researchers as to why there is data variation in width. What factors have contributed to the lack of further expansion in the width of theatres? To address this question, this study used a comparative approach to conduct a venue experiment between this theater stage and another theater stage for non-heritage opera performances, collecting the subjective perceptions of performers and audiences at different theater stages, as well as combining BK Connect platform software to measure data such as echo and delay. From the subjective and objective results, it is inferred that the Chinese ancients discovered and understood the acoustical phenomenon of the Haas effect by exploring the effect of stage width on musical performance and appreciation of listening states during the Ming Dynasty and utilized this discovery to serve music in subsequent stage construction. This discovery marked a node of evolution in Chinese architectural acoustics technology driven by musical demands. It is also instructive to note that, in contrast to many of the world's "unsuccessful civilizations," China can use a combination of heritage and intangible cultural research to chart a clear, demand-driven course for the evolution of human music technology, and that the findings of such research will complete the course of human exploration of music acoustics. The findings of such research will complete the journey of human exploration of music acoustics, and this practical experience can be applied to the exploration and understanding of other musical heritage base data.

Keywords: Haas effect, musical acoustics, history of acoustical technology, Chinese opera stage, structure

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Authors: Annisa D. Febryandini

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Annexation is a typical construction that commonly used in Arabic language. The use of the construction appears in Arabic speech such as the speech of Thariq bin Ziyad. The speech as one of the most famous speeches in the history of Islam uses many annexations. This qualitative research paper uses the secondary data by library method. Based on the data, this paper concludes that the speech has two basic structures with some variations and has some grammatical relationship. Different from the other researches that identify the speech in sociology field, the speech in this paper will be analyzed in linguistic field to take a look at the structure of its annexation as well as the grammatical relationship.

Keywords: annexation, Thariq bin Ziyad, grammatical relationship, Arabic syntax

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Authors: Matěj Kuc

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This paper compares different types of profitability measures of cooperative banks from two developed regions: the European Union and the United States of America together with Canada. We created balanced dataset of more than 200 cooperative banks covering 2011-2016 period. We made series of tests and run Random Effects estimation on panel data. We found that American and Canadian cooperatives are more profitable in terms of return on assets (ROA) and return on equity (ROE). There is no significant difference in net interest margin (NIM). Our results show that the North American cooperative banks accommodated better to the current market environment.

Keywords: cooperative banking, panel data, profitability measures, random effects

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Authors: Mallikarjuna Rao Yamarthy, Subramanyam Makam Venkata, Satya Prasad Kodati

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The main objective of the proposed work is to reduce the overall network traffic incurred by mobility management, packet delivery cost and to increase the resource utilization. The proposed algorithm, An Efficient Resource Management Algorithm (ERMA) for mobility management in wireless mesh networks, relies on pointer based mobility management scheme. Whenever a mesh client moves from one mesh router to another, the pointer is set up dynamically between the previous mesh router and current mesh router based on the distance constraints. The algorithm evaluated for signaling cost, data delivery cost and total communication cost performance metrics. The proposed algorithm is demonstrated for both internet sessions and intranet sessions. The proposed algorithm yields significantly better performance in terms of signaling cost, data delivery cost, and total communication cost.

Keywords: data delivery cost, mobility management, pointer forwarding, resource management, wireless mesh networks

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Authors: Milenko Košutić, Jelena Filipović, Zvonko Nježić

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Extrusion technology is thermal processing that is applied to improve the nutritional, hygienic, and physical-chemical characteristics of the raw material. Overall, the extrusion process is an efficient method for the production of a wide range of food products. It combines heat, pressure, and shear to transform raw materials into finished goods with desired textures, shapes, and nutritional profiles. The extruded products’ quality is remarkably dependent upon feed material composition, barrel temperature profile, feed moisture content, screw speed, and other extrusion system parameters. Given consumer expectations for snack foods, a high expansion index and low bulk density, in addition to crunchy texture and uniform microstructure, are desired. This paper investigates the effects of simultaneous different types of corn (white corn, yellow corn, red corn, and black corn) addition and different screw speed (350, 500, 650 rpm) on the physical, technological, and functional properties of flakes products. Black corn flour and screw speed at 350 rpm positively influenced physical, technological characteristics, mineral composition, and antioxidant properties of flake products with the best total score analysis of 0,59. Overall, the combination of Tukey's HSD test and PCA enables a comprehensive analysis of the observed corn products, allowing researchers to identify them. This research aims to analyze the influence of different types of corn flour (white corn, yellow corn, red corn, and black corn) on the nutritive and sensory properties of the product (quality, texture, and color), as well as the acceptance of the new product by consumers on the territory of Novi Sad. The presented data point that investigated corn flakes from black corn flour at 350 rpm is a product with good physical-technological and functional properties due to a higher level of antioxidant activity.

Keywords: corn types, flakes product, nutritive quality, acceptability

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Authors: T. Garlan, I. Gabelotaud, S. Lucas, E. Marchès

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Production of a global sedimentological seabed map has been initiated in 1995 to provide the necessary tool for searches of aircraft and boats lost at sea, to give sedimentary information for nautical charts, and to provide input data for acoustic propagation modelling. This original approach had already been initiated one century ago when the French hydrographic service and the University of Nancy had produced maps of the distribution of marine sediments of the French coasts and then sediment maps of the continental shelves of Europe and North America. The current map of the sediment of oceans presented was initiated with a UNESCO's general map of the deep ocean floor. This map was adapted using a unique sediment classification to present all types of sediments: from beaches to the deep seabed and from glacial deposits to tropical sediments. In order to allow good visualization and to be adapted to the different applications, only the granularity of sediments is represented. The published seabed maps are studied, if they present an interest, the nature of the seabed is extracted from them, the sediment classification is transcribed and the resulted map is integrated in the world map. Data come also from interpretations of Multibeam Echo Sounder (MES) imagery of large hydrographic surveys of deep-ocean. These allow a very high-quality mapping of areas that until then were represented as homogeneous. The third and principal source of data comes from the integration of regional maps produced specifically for this project. These regional maps are carried out using all the bathymetric and sedimentary data of a region. This step makes it possible to produce a regional synthesis map, with the realization of generalizations in the case of over-precise data. 86 regional maps of the Atlantic Ocean, the Mediterranean Sea, and the Indian Ocean have been produced and integrated into the world sedimentary map. This work is permanent and permits a digital version every two years, with the integration of some new maps. This article describes the choices made in terms of sediment classification, the scale of source data and the zonation of the variability of the quality. This map is the final step in a system comprising the Shom Sedimentary Database, enriched by more than one million punctual and surface items of data, and four series of coastal seabed maps at 1:10,000, 1:50,000, 1:200,000 and 1:1,000,000. This step by step approach makes it possible to take into account the progresses in knowledge made in the field of seabed characterization during the last decades. Thus, the arrival of new classification systems for seafloor has improved the recent seabed maps, and the compilation of these new maps with those previously published allows a gradual enrichment of the world sedimentary map. But there is still a lot of work to enhance some regions, which are still based on data acquired more than half a century ago.

Keywords: marine sedimentology, seabed map, sediment classification, world ocean

Procedia PDF Downloads 230

Authors: Rui Yin, Haojie Wang, Xun Li

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Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then, the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. We also explore contrastive learning as a method for training domain-adapted dense retrievers and show that it leads to strong performance in various retrieval settings. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data.

Keywords: dense retrieval, query generation, contrastive learning, unsupervised training

Procedia PDF Downloads 94

Authors: Enver Kucukkulahli, Pakize Erdogmus, Kemal Polat

Abstract:

The 2D image segmentation is a significant process in finding a suitable region in medical images such as MRI, PET, CT etc. In this study, we have focused on 2D MRI images for image segmentation process. We have designed a GUI (graphical user interface) written in MATLABTM for 2D MRI images. In this program, there are two different interfaces including data pre-processing and image clustering or segmentation. In the data pre-processing section, there are median filter, average filter, unsharp mask filter, Wiener filter, and custom filter (a filter that is designed by user in MATLAB). As for the image clustering, there are seven different image segmentations for 2D MR images. These image segmentation algorithms are as follows: PSO (particle swarm optimization), GA (genetic algorithm), Lloyds algorithm, k-means, the combination of Lloyds and k-means, mean shift clustering, and finally BBO (Biogeography Based Optimization). To find the suitable cluster number in 2D MRI, we have designed the histogram based cluster estimation method and then applied to these numbers to image segmentation algorithms to cluster an image automatically. Also, we have selected the best hybrid method for each 2D MR images thanks to this GUI software.

Keywords: image segmentation, clustering, GUI, 2D MRI

Procedia PDF Downloads 372

Authors: Manoj Kumar

Abstract:

Routing protocols have a central role in any mobile ad hoc network (MANET). There are many routing protocols that exhibit different performance levels in different scenarios. In this paper, we compare AODV, DSDV, DSR, and ZRP routing protocol in mobile ad hoc networks to determine the best operational conditions for each protocol. We analyze these routing protocols by extensive simulations in OPNET simulator and show how to pause time and the number of nodes affect their performance. In this study, performance is measured in terms of control traffic received, control traffic sent, data traffic received, sent data traffic, throughput, retransmission attempts.

Keywords: AODV, DSDV, DSR, ZRP

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Authors: Neetu Tyagi, Sumit Sharma

Abstract:

The study illustrates the results of an integrated study done on Tangni landslide located on NH-58 at Chamoli, Uttarakhand. Geological, geo-morphological and geotechnical investigations were carried out to understand the mechanism of landslide and to plan further investigation and monitoring. At any rate, the movements were favored by continuous rainfall water infiltration from the zones where the phyllites/slates and Dolomites outcrop. The site investigations were carried out including the monitoring of landslide movements and of the water level fluctuations due to rainfall give us a better understanding of landslide dynamics that have been causing in time soil instability at Tangni landslide site. The Early Warning System (EWS) installed different types of sensors and all sensors were directly connected to data logger and raw data transfer to the Defence Terrain Research Laboratory (DTRL) server room with the help of File Transfer Protocol (FTP). The slip surfaces were found at depths ranging from 8 to 10 m from Geophysical survey and hence sensors were installed to the depth of 15m at various locations of landslide. Rainfall is the main triggering factor of landslide. In this study, the developed model of unsaturated soil slope stability is carried out. The analysis of sensors data available for one year, indicated the sliding surface of landslide at depth between 6 to 12m with total displacement up to 6cm per year recorded at the body of landslide. The aim of this study is to set the threshold and generate early warning. Local peoples already alert towards landslide, if they have any types of warning system.

Keywords: early warning system, file transfer protocol, geo-morphological, geotechnical, landslide

Procedia PDF Downloads 152