Search results for: warning labels

Authors: Ezinne M. Igwe

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Statements of facts have been made about Nollywood, a segment of the Nigerian film industry that has in recent times become phenomenal due largely to its quantity of production and specific production style. In the face of recent transformations reshaping the industry, matters have been arising which have not been given due academic attention from an industry player perspective. While re-addressing such issues like structure, policy and informality, this study benefits from a new perspective – that of a community member adopting participant observation to research into a familiar culture. With data drawn from an extensive ethnographic study of the industry, this paper examines these matters with an emphasis on structure and the industry’s overall political economy. Drawing from discourses on the new and old Nollywood labels and other current matters arising within the industry such as the MOPICON bill redraft, corporate financing and possibilities of regeneration, this paper examines structure and power struggle within Nollywood. These are championing regenerative processes that bring about formalization, professionalism and the quest for a transnational presence, which have only been superficially evaluated. Focused essentially on Nollywood’s political economy, this study critically analyses the transforming face of an informal industry, the consistent quest for structure, quality and standard, and issues of corporate sponsorship as possible trends of regeneration. It evaluates them as indicators of regeneration, questioning the possibilities of their sustenance in an industry experiencing increased interactions with the formal economy and an influx of young professionals. With findings that make sustained regeneration both certain (due to increased formal economy interaction) and uncertain (due to the dysfunctionality of the society and its political system), it concludes that the transforming face of the industry suggests impending gentrification of the industry.

Keywords: formalisation, MOPICON, Nollywood, structure

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Authors: Nourhan A. Saad, Sara Elgazzar, Gehan Saleh

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The food industry nowadays is becoming customer-oriented and needs faster response time to deal with food incidents. There is a deep need for good traceability systems to help the supply chain (SC) partners to minimize production and distribution of unsafe or poor quality products, which in turn will enhance the food SC performance. The current food labeling systems implemented in developing countries cannot guarantee that food is authentic, safe and of good quality. Therefore, the use of origin labels, mainly the geographical indications (GIs), allows SC partners to define quality standards and defend their products' reputation. According to our knowledge there are no studies discussed the use of GIs in developing countries. This research represents a research schema about the implementation of European quality labeling system in developing countries and its impact on enhancing SC performance. An empirical study was conducted on the Egyptian traditional food sector based on a sample of seven restaurants implementing the Med-diet labeling system. First, in-depth interviews were carried out to analyze the Egyptian traditional food SC. Then, a framework was developed to link the European quality labeling system and SC performance. Finally, a structured survey was conducted based on the applied framework to investigate the impact of Med-diet labeling system on the SC performance. The research provides an applied framework linking Med-diet quality labeling system to SC performance of traditional food sector in developing countries generally and especially in the Egyptian traditional food sector. The framework can be used as a SC performance management tool to increase the effectiveness and efficiency of food industry's SC performance.

Keywords: food supply chain, med-diet labeling system, quality labeling system, supply chain performance

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Authors: Oscar H. Malaco Jr.

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Homosexuality has been adapted as the universal concept that defines the deviations from the heteronormative parameters of society. Sexual orientation and gender identities have been used in a concretely separate manner the same way as the dynamics between man and woman, male and female, gender and sex operate. These terms are all products of human beings’ utilization of language. Language has proven its power to define and determine the status and the categories of the subjects in society. This tool developed by human beings provides a definition of their own specific cultural community and their individual selves that either claim or oppugn their space in the social hierarchy. The label ‘bakla’ is reasoned as an identity which is a reaction to the spectral disposition of gender and sexuality in the Philippine society. To expose the Filipino constitutes of bakla is the major attempt of this study. Through the methods of Sikolohiyang Pilipino (Filipino Psychology), namely Pagtatanung-tanong (asking questions) and Pakikipagkuwentuhan (story-telling), the utterances of the bakla were gathered and analyzed in a rhetorical and ideological manner. Furthermore, the Dramatistic Pentad of Kenneth Burke was adapted as a methodology and also utilized as a perspective of analysis. The results suggest that the bakla as an identity carries the hurdles of class. The performativity of the bakla is proven to be a cycle propelled by their guilt to be identified and recognized as subjects in a society where heteronormative power contests their gender and sexual expressions as relatively aberrational to the binary gender and sexual roles. The labels, hence, are potent structures that control the disposition of the bakla in the society, reflecting an aspect of the disposition of Filipino identities. After all, performing kabaklaan in the Philippine society is interplay between resistance and conformity to the hegemonic dominions as a result of imperial attempts to universalize the concept of homosexuality between and among distant cultural communities.

Keywords: gender identity, sexual orientation, rhetoric, performativity

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Authors: Mohamed Farhat O. Hameed, Yasamin K. A. Alrayk, A. A Shaalan, S. S. A. Obayya

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The surface plasmon resonance (SPR) sensors are widely used due to its high sensitivity with molecular labels free. The commercial SPR sensors depend on the conventional prism-coupled configuration. However, this type of configuration suffers from miniaturization and integration. Therefore, the search for compact, portable and highly sensitive SPR sensors becomes mandatory.In this paper, sensitivity enhancement of a novel photonic crystal fiber biosensoris introduced and studied. The suggested design has microstructure of air holes in the core region surrounded by two large semicircular metallized channels filled with the analyte. The inner surfaces of the two channels are coated by a silver layer followed by a gold layer.The simulation results are obtained using full vectorial finite element methodwith perfect matched layer (PML) boundary conditions. The proposed design depends on bimetallic configuration to enhance the biosensor sensitivity. Additionally, the suggested biosensor can be used for multi-channel/multi-analyte sensing. In this study, the sensor geometrical parameters are studied to maximize the sensitivity for the two polarized modes. The numerical results show that high refractive index sensitivity of 4750 nm/RIU (refractive index unit) and 4300 nm/RIU can be achieved for the quasi (transverse magnetic) TM and quasi (transverse electric) TE modes of the proposed biosensor, respectively. The reportedbiosensor has advantages of integration of microfluidics setup, waveguide and metallic layers into a single structure. As a result, compact biosensor with better integration compared to conventional optical fiber SPR biosensors can be obtained.

Keywords: photonic crystal fibers, gold, silver, surface plasmon, biosensor

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Authors: Danielle Shackley, Yetunde Folajimi

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As more people turn to the internet seeking health-related information, there is more risk of finding false, inaccurate, or dangerous information. Sentiment analysis is a natural language processing technique that assigns polarity scores to text, ranging from positive, neutral, and negative. In this research, we evaluate the weight of a sentiment analysis feature added to fake health news classification models. The dataset consists of existing reliably labeled health article headlines that were supplemented with health information collected about COVID-19 from social media sources. We started with data preprocessing and tested out various vectorization methods such as Count and TFIDF vectorization. We implemented 3 Naive Bayes classifier models, including Bernoulli, Multinomial, and Complement. To test the weight of the sentiment analysis feature on the dataset, we created benchmark Naive Bayes classification models without sentiment analysis, and those same models were reproduced, and the feature was added. We evaluated using the precision and accuracy scores. The Bernoulli initial model performed with 90% precision and 75.2% accuracy, while the model supplemented with sentiment labels performed with 90.4% precision and stayed constant at 75.2% accuracy. Our results show that the addition of sentiment analysis did not improve model precision by a wide margin; while there was no evidence of improvement in accuracy, we had a 1.9% improvement margin of the precision score with the Complement model. Future expansion of this work could include replicating the experiment process and substituting the Naive Bayes for a deep learning neural network model.

Keywords: sentiment analysis, Naive Bayes model, natural language processing, topic analysis, fake health news classification model

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Authors: Fatemeh Babaeian, Nemai Chandra Karmakar

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Chipless RFID system is a wireless system for tracking and identification which use passive tags for encoding data. The advantage of using chipless RFID tag is having a planar tag which is printable on different low-cost materials like paper and plastic. The printed tag can be attached to different items in the labelling level. Since the price of chipless RFID tag can be as low as a fraction of a cent, this technology has the potential to compete with the conventional optical barcode labels. However, due to the passive structure of the tag, data processing of the reflection signal is a crucial challenge. The captured reflected signal from a tag attached to an item consists of different components which are the reflection from the reader antenna, the reflection from the item, the tag structural mode RCS component and the antenna mode RCS of the tag. All these components are summed up in both time and frequency domains. The effect of reflection from the item and the structural mode RCS component can distort/saturate the frequency domain signal and cause difficulties in extracting the desired component which is the antenna mode RCS. Therefore, it is required to study the reflection of the tag in both time and frequency domains to have a better understanding of the nature of the captured chipless RFID signal. The other benefits of this study can be to find an optimised encoding technique in tag design level and to find the best processing algorithm the chipless RFID signal in decoding level. In this paper, the reflection from a typical backscattered chipless RFID tag with six resonances is analysed, and different components of the signal are separated in both time and frequency domains. Moreover, the time domain signal corresponding to each resonator of the tag is studied. The data for this processing was captured from simulation in CST Microwave Studio 2017. The outcome of this study is understanding different components of a measured signal in a chipless RFID system and a discovering a research gap which is a need to find an optimum detection algorithm for tag ID extraction.

Keywords: antenna mode RCS, chipless RFID tag, resonance, structural mode RCS

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Authors: De Castro-Pardo M., Cabello J. M., Martin J. M., Ruiz F.

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In this paper, we propose a new Water Sustainability Indicator based on a Multi-Reference methodology that permits modeling compensation between the analysed criteria and provides a participative approach. The proposed indicator provides results based on 19 variables grouped into 5 dimensions: availability, access, resilience, good governance and economic capacity. The indicator was applied to assess water sustainability in 27 European countries. The results showed that Finland, the Netherlands, Sweden and the United Kingdom obtained the best global results in terms of weak water (compensatory) sustainability. In terms of strong water (non-compensatory) sustainability, no country gained acceptable results in terms of strong sustainability. Climate change and the state of freshwater resources were detected as especially vulnerable in all the analysed countries. The results identified some eastern European countries with low GDP and good performance of availability and cost of water, with bad results in terms of governance and water productivity. These results could jeopardize water sustainability in the event of a potential economic development if these limitations are not addressed. In a context of economic and political instability due to the current armed conflict in nearby countries such as Ukraine, it is especially important to pay attention to these countries, whose good governance indicators could worsen even more. The proposed indicator allowed to the identification of warning signs and could contribute to the improvement in decision-making processes. Moreover, it could improve the monitoring of international water policies.

Keywords: water sustainability, composite indicators, compensatory approach, sustainability European policies

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Authors: Subhan Ahmad, Pradeep Bhargava, Ajay Chourasia

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Shear failure in reinforced concrete beams without shear reinforcement leads to loss of property and life since a very little or no warning occurs before failure as in case of flexural failure. Shear strength of reinforced concrete beams decreases as its depth increases. This phenomenon is generally called as the size effect. In this paper, a comparative analysis is performed to estimate the performance of shear strength models in capturing the size effect of reinforced concrete beams made with conventional concrete, self-compacting concrete, and recycled aggregate concrete. Four shear strength models that account for the size effect in shear are selected from the literature and applied on the datasets of slender reinforced concrete beams. Beams prepared with conventional concrete, self-compacting concrete, and recycled aggregate concrete are considered for the analysis. Results showed that all the four models captured the size effect in shear effectively and produced conservative estimates of the shear strength for beams made with normal strength conventional concrete. These models yielded unconservative estimates for high strength conventional concrete beams with larger effective depths ( > 450 mm). Model of Bazant and Kim (1984) captured the size effect precisely and produced conservative estimates of shear strength of self-compacting concrete beams at all the effective depths. Also, shear strength models considered in this study produced unconservative estimates of shear strength for recycled aggregate concrete beams at all effective depths.

Keywords: reinforced concrete beams; shear strength; prediction models; size effect

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Authors: Yun Wang, Ruoyu Wang, Tuo Chen, Guangxiu Liu, Guodong Chen, Wei Zhang

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Tuberculosis (TB) is a major public health problem in China. China has the world's second largest tuberculosis epidemic (after India). Xinjiang almost has the highest annual attendance rate of TB in China, and the province is also famous because of its severe dust storms. The epidemic timing starts in February and ends in July, and the dust storm mainly distribute throughout the spring and early summer, which strongly indicate a close linkage between causative agent of TB and dust storm events. However, mechanisms responsible for the observed patterns are still not clearly indentified. By comparing the information on cases of TB from Centers for Disease Control of China annual reports with dust storm atmosphere datasets, we constructed the relationship between the large scale annual occurrence of TB in Xinjiang, a Northwest province of China, and dust storm occurrence. Regional atmospheric indexes of dust storm based on surface wind speed show a clear link between population dynamics of the disease and the climate disaster: the onset of epidemics and the dust storm defined by the atmospheric index share the same mean year. This study is the first that provides a clear demonstration of connections that exist between TB epidemics and dust storm events in China. The development of this study will undoubtedly help early warning for tuberculosis epidemic onset in China and help nationwide and international public health institutions and policy makers to better control TB disease in Norwest China.

Keywords: dust storm, tuberculosis, Xinjiang province, epidemic

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Authors: Vaishali Joshi, Pallav Joshi

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Environment concern has become an important topic and continues to acquire more popularity in the coming scenario. We all are exposed to messages daily, which encourage us to involve in green behavior. Factors such as Global Warming, Climate change are creating a big buzz amongst the people. Realizing this, many firms/companies are adopting the bright way of making profit along with creating a brand image, by going green. These firms/companies persuade consumers to use purchase eco-friendly products for the benefit of the environment and the society. In such scenario, it becomes very essential for such firms/companies to approach the customers in a better way. In other words, we can say that marketing approach plays a crucial role for such firm/companies. Hence in this research study, we have tried to create a marketing approach for the firms/companies for selling the eco-friendly apparels. We have studied the hypothetical apparel brand who has taken a green initiative of making their products eco-friendly. We have named this hypothetical brand as “Go-Green”. By taking this hypothetical brand we have studied about how this brand can achieve better marketing approach. In particular, we have studied the four types of print advertisements of this brand as follows :(i) print advertisement showing only eco-friendly apparel (ii) print advertisement showing eco-friendly apparel labeled with eco-label (iii) print advertisement showing eco-friendly apparel along with information about the benefit of the featured apparel and (iv) print advertisement showing eco-friendly apparel with both eco-label and information about the benefit of the featured apparel. The conclusion of this research suggest that respondents more positively evaluate the print advertisement of eco-friendly apparel labeled with eco-labels and information about the benefit of the featured apparel, compared by other three print advertisement. Moreover, in this research study, we have studied environment knowledge, as the moderating factor affecting the consumer green purchase behavior.

Keywords: eco-friendly apparel, print advertisement, eco-label, environment knowledge

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Authors: Feisal Khudher Mahmood, Abdul Samad Rahman Sultan

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Iraq had been a diverse society with races, cultures and religions that peacefully coexistence. The phenomenon of internal displacement occurred after April 2003, because of political instability as will as the deterioration of the political and security situation as a result of United States of America occupation. Biggest internal displacement have occurred (and keep happening) since 10th of June 2014 due to rise of Islamic State of Iraq and Syria (ISIS) and it’s occupation of one third of country territories. This crisis effected directly 3,275,000 people and reflected negatively on the social fabric of Iraq community and led to waves of sectorial violence that swept the country. Internal displaced communities are vulnerable, especially under non functional and weak government, that led to lose of essential human rights and dignity. Using Geographic Information System (GIS) and Geospatial Techniques, two types of internal displacement have been found; voluntary and forced. Both types of displacement are highly influenced by location, race and religion. The main challenge for Iraqi government and NGOs will be after defeating ISIS. Helping the displaced to resettle within their community and to re-establish the coexistence. By spatial-statical analysis hot spots of future conflicts among displaced community have been highlighted. This will help the government to tackle future conflicts before they occur. Also, it will be the base for social conflict early warning system.

Keywords: internal displacement, Iraq, ISIS, human security, human rights, GIS, spatial-statical analysis

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Authors: J. P. Panda, K. Sasmal, H. V. Warrior

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Eddy viscosity models in turbulence modeling can be mainly classified as linear and nonlinear models. Linear formulations are simple and require less computational resources but have the disadvantage that they cannot predict actual flow pattern in complex geophysical flows where streamline curvature and swirling motion are predominant. A constitutive equation of Reynolds stress anisotropy is adopted for the formulation of eddy viscosity including all the possible higher order terms quadratic in the mean velocity gradients, and a simplified model is developed for actual oceanic flows where only the vertical velocity gradients are important. The new model is incorporated into the one dimensional General Ocean Turbulence Model (GOTM). Two realistic oceanic test cases (OWS Papa and FLEX' 76) have been investigated. The new model predictions match well with the observational data and are better in comparison to the predictions of the two equation k-epsilon model. The proposed model can be easily incorporated in the three dimensional Princeton Ocean Model (POM) to simulate a wide range of oceanic processes. Practically, this model can be implemented in the coastal regions where trasverse shear induces higher vorticity, and for prediction of flow in estuaries and lakes, where depth is comparatively less. The model predictions of marine turbulence and other related data (e.g. Sea surface temperature, Surface heat flux and vertical temperature profile) can be utilized in short term ocean and climate forecasting and warning systems.

Keywords: Eddy viscosity, turbulence modeling, GOTM, CFD

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Authors: Masek A., Diakowska K., Zaborski M.

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Polymeric materials have found their use almost in every branch of industry worldwide. Most of them constitute so-called “petropolymers" obtained from crude oil. However literature information sounds a warning that its global sources are running out. Thus, it seems that one should search for polymeric materials from renewable raw materials belonging to the group of green polymers. Therefore on account of environmental protection and the issue of sustainable technologies, nowadays greater and greater achievements have been observed in the field of green technology using engineering sciences to develop composite materials. The main aim of this study was to research what is the influence of biofillers on the properties. We used biofillers like : cellulose with different length of fiber, cellulose UFC100, silica and montmorillonite. In our research, we reported on biodegradable composites exhibitingspecificity properties by melt blending of polylactide (PLA), one of the commercially available biodegradable material, and epoxidized natural rubber (ENR) containing 50 mol.%epoxy group. Blending hydrophilic natural polymers and aliphatic polyesters is of significant interest, since it could lead to the development of a new range of biodegradable polymeric materials. We research the degradation of composites on the basis epoxidized natural rubber and poly(lactide). The addition of biofillers caused far-reaching degradation processes. The greatest resistance to biodegradation showed a montmorillonite-based mixtures, the smallest inflated cellulose fibers of varying length.The final aim in the present study is to use ENR and poly(lactide) to design composite from renewable resources with controlled degradation.

Keywords: renewable resources, biopolymer, degradation, polylactide

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Authors: Nadhifah A. Nugraha, Dida D. Damayanti, Widia Juliani

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Airplanes manufacturing is growing along with the increasing demand from consumers. The helicopter's tail called Tailboom is a product of the helicopter division at XYZ Corp, where the Tailboom assembly line is a pull system. Based on observations of existing conditions that occur at XYZ Corp, production is still unable to meet the demands of consumers; lead time occurs greater than the plan agreed upon by the consumers. In the assembly process, each work station experiences a lack of parts and components needed to assemble components. This happens because of the delay in getting the required part information, and there is no warning about the availability of parts needed, it makes some parts unavailable in assembly warehouse. The lack of parts and components from the previous work station causes the assembly process to stop, and the assembly line also stops at the next station. In its completion, the production time was late and not on the schedule. In resolving these problems, the controlling process is needed, which is controlling the assembly line to get all components and subassembly in the right amount and at the right time. This study applies one of Just In Time tools, namely Kanban and automation, should be added as efficiently and effectively communication line becomes electronic Kanban. The problem can be solved by reducing non-value added time, such as waiting time and idle time. The proposed results of controlling the assembly line of Tailboom result in a smooth assembly line without waiting, reduced lead time, and achieving production time according to the schedule agreed with the consumers.

Keywords: kanban, e-Kanban, lead time, pull system

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Authors: Abdurrahman Arslanyilmaz, Salman Al Matouq, Durmus V. Doner

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Level 3 autonomous vehicles are able to take full responsibility over the control of the vehicle unless a system boundary is reached or a system failure occurs, in which case, the driver is expected to take-over the control of the vehicle. While this happens, the driver is often not aware of the traffic situation or is engaged in a secondary task. Factors affecting the duration and quality of take-overs in these situations have included secondary task type and nature, traffic density, take-over request (TOR) time, and TOR warning type and modality. However, to the best of the authors’ knowledge, no prior study examined time buffer for TORs when a system failure occurs immediately before intersections. The first objective of this study is to investigate the effect of time buffer (3 and 7 seconds) on the duration and quality of take-overs when a system failure occurs just prior to intersections. In addition, eye-tracking has become one of the most popular methods to report what individuals view, in what order, for how long, and how often, and it has been utilized in driving simulations with various objectives. However, to the extent of authors’ knowledge, none has compared drivers’ eye gaze behavior in the two different time buffers in order to examine drivers’ attention and comprehension of salient information. The second objective is to understand the driver’s attentional focus on comprehension of salient traffic-related information presented on different parts of the dashboard and on the roads.

Keywords: autonomous vehicles, driving simulation, eye gaze, attention, comprehension, take-over duration, take-over quality, time buffer

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Authors: Mariam Ismail, Kazeem Rufai, Jeremiah Balogun

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A study was conducted to apply fuzzy logic to the development of a monitoring model for child pornography based on associated risk factors, which can be used by forensic experts or integrated into forensic systems for the early detection of child pornographic activities. A number of methods were adopted in the study, which includes an extensive review of related works was done in order to identify the factors that are associated with child pornography following which they were validated by an expert sex psychologist and guidance counselor, and relevant data was collected. Fuzzy membership functions were used to fuzzify the associated variables identified alongside the risk of the occurrence of child pornography based on the inference rules that were provided by the experts consulted, and the fuzzy logic expert system was simulated using the Fuzzy Logic Toolbox available in the MATLAB Software Release 2016. The results of the study showed that there were 4 categories of risk factors required for assessing the risk of a suspect committing child pornography offenses. The results of the study showed that 2 and 3 triangular membership functions were used to formulate the risk factors based on the 2 and 3 number of labels assigned, respectively. The results of the study showed that 5 fuzzy logic models were formulated such that the first 4 was used to assess the impact of each category on child pornography while the last one takes the 4 outputs from the 4 fuzzy logic models as inputs required for assessing the risk of child pornography. The following conclusion was made; there were factors that were related to personal traits, social traits, history of child pornography crimes, and self-regulatory deficiency traits by the suspects required for the assessment of the risk of child pornography crimes committed by a suspect. Using the values of the identified risk factors selected for this study, the risk of child pornography can be easily assessed from their values in order to determine the likelihood of a suspect perpetuating the crime.

Keywords: fuzzy, membership functions, pornography, risk factors

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Authors: Paria Soleimani, Arezoo Neshati

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Myocardial infarction is one of the leading causes of ‎death in the world. Some of these deaths occur even before the patient ‎reaches the hospital. Myocardial infarction occurs as a result of ‎impaired blood supply. Because the most of these deaths are due to ‎coronary artery disease, hence the awareness of the warning signs of a ‎heart attack is essential. Some heart attacks are sudden and intense, but ‎most of them start slowly, with mild pain or discomfort, then early ‎detection and successful treatment of these symptoms is vital to save ‎them. Therefore, importance and usefulness of a system designing to ‎assist physicians in the early diagnosis of the acute heart attacks is ‎obvious.‎ The purpose of this study is to determine how well a predictive ‎model would perform based on the only patient-reportable clinical ‎history factors, without using diagnostic tests or physical exams. This ‎type of the prediction model might have application outside of the ‎hospital setting to give accurate advice to patients to influence them to ‎seek care in appropriate situations. For this purpose, the data were ‎collected on 711 heart patients in Iran hospitals. 28 attributes of clinical ‎factors can be reported by patients; were studied. Three logistic ‎regression models were made on the basis of the 28 features to predict ‎the risk of heart attacks. The best logistic regression model in terms of ‎performance had a C-index of 0.955 and with an accuracy of 94.9%. ‎The variables, severe chest pain, back pain, cold sweats, shortness of ‎breath, nausea, and vomiting were selected as the main features.‎

Keywords: Coronary heart disease, Acute heart attacks, Prediction, Logistic ‎regression‎

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Authors: Ayse Cobanoglu

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Working memory can be defined as a workspace that holds and regulates active information in mind. This study investigates individual changes in children's working memory from kindergarten to first grade. The main purpose of the study is whether parental discipline methods and child impulsive/overactive behaviors affect children's working memory initial status and growth rate, controlling for gender, minority status, and socioeconomic status (SES). A linear growth curve model with the first four waves of the Early Childhood Longitudinal Study-Kindergarten Cohort of 2011 (ECLS-K:2011) is performed to analyze the individual growth of children's working memory longitudinally (N=3915). Results revealed that there is a significant variation among students' initial status in the kindergarten fall semester as well as the growth rate during the first two years of schooling. While minority status, SES, and children's overactive/impulsive behaviors influenced children's initial status, only SES and minority status were significantly associated with the growth rate of working memory. For parental discipline methods, such as giving a warning and ignoring the child's negative behavior, are also negatively associated with initial working memory scores. Following that, students' working memory growth rate is examined, and students with lower SES as well as minorities showed a faster growth pattern during the first two years of schooling. However, the findings of parental disciplinary methods on working memory growth rates were mixed. It can be concluded that schooling helps low-SES minority students to develop their working memory.

Keywords: growth curve modeling, impulsive/overactive behaviors, parenting, working memory

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Authors: M. McHugh, D. Lillis

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Mobile applications are being used to perform a wide variety of tasks in day-to-day life, ranging from checking email to controlling your home heating. Application developers have recognized the potential to transform a smart device into a medical device, by using a mobile medical application i.e. a mobile phone or a tablet. When initially conceived these mobile medical applications performed basic functions e.g. BMI calculator, accessing reference material etc.; however, increasing complexity offers clinicians and patients a range of functionality. As this complexity and functionality increases, so too does the potential risk associated with using such an application. Examples include any applications that provide the ability to inflate and deflate blood pressure cuffs, as well as applications that use patient-specific parameters and calculate dosage or create a dosage plan for radiation therapy. If an unapproved mobile medical application is marketed by a medical device organization, then they face significant penalties such as receiving an FDA warning letter to cease the prohibited activity, fines and possibility of facing a criminal conviction. Regulatory bodies have finalized guidance intended for mobile application developers to establish if their applications are subject to regulatory scrutiny. However, regulatory controls appear contradictory with the approaches taken by mobile application developers who generally work with short development cycles and very little documentation and as such, there is the potential to stifle further improvements due to these regulations. The research presented as part of this paper details how by adopting development techniques, such as agile software development, mobile medical application developers can meet regulatory requirements whilst still fostering innovation.

Keywords: agile, applications, FDA, medical, mobile, regulations, software engineering, standards

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Authors: Yinglisong, Jingge Chen, Jingxuan Chen, Yan Wang, Hui Huang, Jing Zhnag, Qianqian Zhang, Zhenzhen Zhang, Ji Zhang

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Purpose: The study aims to establish a nomogram prediction model for postpartum hemorrhage (PPH) in vaginal delivery. Patients and Methods: Clinical data were retrospectively collected from vaginal delivery patients admitted to a hospital in Zhengzhou, China, from June 1, 2022 - October 31, 2022. Univariate and multivariate logistic regression were used to filter out independent risk factors. A nomogram model was established for PPH in vaginal delivery based on the risk factors coefficient. Bootstrapping was used for internal validation. To assess discrimination and calibration, receiver operator characteristics (ROC) and calibration curves were generated in the derivation and validation groups. Results: A total of 1340 cases of vaginal delivery were enrolled, with 81 (6.04%) having PPH. Logistic regression indicated that history of uterine surgery, induction of labor, duration of first labor, neonatal weight, WBC value (during the first stage of labor), and cervical lacerations were all independent risk factors of hemorrhage (P <0.05). The area-under-curve (AUC) of ROC curves of the derivation group and the validation group were 0.817 and 0.821, respectively, indicating good discrimination. Two calibration curves showed that nomogram prediction and practical results were highly consistent (P = 0.105, P = 0.113). Conclusion: The developed individualized risk prediction nomogram model can assist midwives in recognizing and diagnosing high-risk groups of PPH and initiating early warning to reduce PPH incidence.

Keywords: vaginal delivery, postpartum hemorrhage, risk factor, nomogram

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Authors: Lian Yang

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Object-oriented programming (OOP) is the dominant programming paradigm in today’s software industry and it has literally enabled average software developers to develop millions of commercial strength software applications in the era of INTERNET revolution over the past three decades. On the other hand, the lack of strict mathematical model and domain constraint features at the language level has long perplexed the computer science academia and OOP engineering community. This situation resulted in inconsistent system qualities and hard-to-understand designs in some OOP projects. The difficulties with regards to fix the current situation are also well known. Although the power of OOP lies in its unbridled flexibility and enormously rich data modeling capability, we argue that the ambiguity and the implicit facade surrounding the conceptual model of a class and an object should be eliminated as much as possible. We listed the five major usage of class and propose to separate them by proposing new language constructs. By using well-established theories of set and FSM, we propose to apply certain simple, generic, and yet effective constraints at OOP language level in an attempt to find a possible solution to the above-mentioned issues regarding OOP. The goal is to make OOP more theoretically sound as well as to aid programmers uncover warning signs of irregularities and domain-specific issues in applications early on the development stage and catch semantic mistakes at runtime, improving correctness verifiability of software programs. On the other hand, the aim of this paper is more practical than theoretical.

Keywords: new language constructs, set theory, FSM theory, user defined value type, function groups, membership qualification attribute (MQA), check-constraint (CC)

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Authors: Suchitra Chnadrashekhar

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Earlier looked as a support function in an organization information technology has now become a critical utility to manage their daily operations. Organizations are processing huge amount of data which was unimaginable few decades before. This has opened the opportunity for IT sector to help industries across domains to handle the data in the most intelligent manner. Presence of IT has been a leverage for the Oil & Gas industry to store, manage and process the data in most efficient way possible thus deriving the economic value in their day-to-day operations. Proper synchronization between Operational data system and Information Technology system is the need of the hour. Predictive analytics supports oil and gas companies by addressing the challenge of critical equipment performance, life cycle, integrity, security, and increase their utilization. Predictive analytics go beyond early warning by providing insights into the roots of problems. To reach their full potential, oil and gas companies need to take a holistic or systems approach towards asset optimization and thus have the functional information at all levels of the organization in order to make the right decisions. This paper discusses how the use of predictive analysis in oil and gas industry is redefining the dynamics of this sector. Also, the paper will be supported by real time data and evaluation of the data for a given oil production asset on an application tool, SAS. The reason for using SAS as an application for our analysis is that SAS provides an analytics-based framework to improve uptimes, performance and availability of crucial assets while reducing the amount of unscheduled maintenance, thus minimizing maintenance-related costs and operation disruptions. With state-of-the-art analytics and reporting, we can predict maintenance problems before they happen and determine root causes in order to update processes for future prevention.

Keywords: hydrocarbon, information technology, SAS, predictive analytics

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Authors: Yunita Ratih Wijayanti, Dwi Rahmawati, Turniningtyas Ayu Rahmawati

Abstract:

Gresik is one of the districts in East Java Province, Indonesia. Gresik Regency has three major rivers, namely Bengawan Solo River, Brantas River, and Lamong River. Lamong River is a tributary of Bengawan Solo River. Flood disasters that occur in Gresik Regency are often caused by the overflow of the Lamong River. The losses caused by the flood were very large and certainly detrimental to the affected people. Therefore, to be able to minimize the impact caused by the flood, it is necessary to take preventive action. However, before taking preventive action, it is necessary to have information regarding potential inundation areas and water levels at various points. For this reason, a flood simulation model is needed. In this study, the simulation was carried out using the Geographic Information System (GIS) method with the help of Global Mapper software. The approach used in this simulation is to use a topographical approach with Digital Elevation Models (DEMs) data. DEMs data have been widely used for various researches to analyze hydrology. The results obtained from this flood simulation are the distribution of flood inundation and water level. The location of the inundation serves to determine the extent of the flooding that occurs by referring to the 50-100 year flood plan, while the water level serves to provide early warning information. Both will be very useful to find out how much loss will be caused in the future due to flooding in Gresik Regency so that the Gresik Regency Regional Disaster Management Agency can take precautions before the flood disaster strikes.

Keywords: flood hazard, simulation model, potential inundation, global mapper, Gresik Regency

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Authors: V. A. Ritchie

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The loss of life and livelihood experienced after the magnitude 9.3 Sumatra earthquake and tsunami on 26 December 2004 and magnitude 9 earthquake and tsunami in northeastern Japan on 11 March 2011, has raised global awareness and brought tsunami phenomenology, nomenclature, and representation into sharp focus. At the same time, travel and tourism continue to increase, contributing around 1 in 11 jobs worldwide. This increase in tourism is especially true for coastal zones, placing pressure on decision-makers to downplay tsunami risks and at the same time provide adequate tsunami warning so that holidaymakers will feel confident enough to visit places of high tsunami risk. This study investigates how well tsunami preparedness messages are getting through for tourist-based businesses in Hawke’s Bay New Zealand, a region of frequent seismic activity and a high probability of experiencing a nearshore tsunami. The aim of this study is to investigate whether tourists based businesses are well informed about tsunamis, how well they understand that information and to what extent their clients are included in awareness raising and evacuation processes. In high-risk tsunami zones, such as Hawke’s Bay, tourism based businesses face competitive tension between short term business profitability and longer term reputational issues related to preventable loss of life from natural hazards, such as tsunamis. This study will address ways to accommodate culturally and linguistically relevant tourist awareness measures without discouraging tourists or being too costly to implement.

Keywords: tsunami risk and response, travel and tourism, business preparedness, cross cultural knowledge transfer

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Authors: Rajkumar Ghosh

Abstract:

The study presents an overview of the many uses and approaches for estimating out-of-sequence thrust movement in earthquake mitigation. The study investigates how knowing and forecasting thrust movement during seismic occurrences might assist to effective earthquake mitigation measures. The review begins by discussing out-of-sequence thrust movement and its importance in earthquake mitigation strategies. It explores how typical techniques of estimating thrust movement may not capture the full complexity of seismic occurrences and emphasizes the benefits of include out-of-sequence data in the analysis. A thorough review of existing research and studies on out-of-sequence thrust movement estimates for earthquake mitigation. The study demonstrates how to estimate out-of-sequence thrust movement using multiple data sources such as GPS measurements, satellite imagery, and seismic recordings. The study also examines the use of out-of-sequence thrust movement estimates in earthquake mitigation measures. It investigates how precise calculation of thrust movement may help improve structural design, analyse infrastructure risk, and develop early warning systems. The potential advantages of using out-of-sequence data in these applications to improve the efficiency of earthquake mitigation techniques. The difficulties and limits of estimating out-of-sequence thrust movement for earthquake mitigation. It addresses data quality difficulties, modelling uncertainties, and computational complications. To address these obstacles and increase the accuracy and reliability of out-of-sequence thrust movement estimates, the authors recommend topics for additional study and improvement. The study is a helpful resource for seismic monitoring and earthquake risk assessment researchers, engineers, and policymakers, supporting innovations in earthquake mitigation measures based on a better knowledge of thrust movement dynamics.

Keywords: earthquake mitigation, out-of-sequence thrust, satellite imagery, seismic recordings, GPS measurements

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Authors: Najmeh Arabnejad, Mohammad Hossein Yousefi

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The risk of injuring is possible in most sports. These injuries are inevitable in contact sports. Since sports injuries result in financial, physical, physiological and social problems for most athletes and endanger their professional future, studying the happening of sports injuries in sports changes to an important issue. This study can be conducted through different aspects including psychological, pathological, social, managerial, etc. Therefore, the present study was designed and conducted with the aim Survey of Sports Injuries In Ten Sports from 2006 to 2011.This descriptive study was carried out in a documentary form. Thus, data related to sports insurance and sport injuries happened in soccer, volleyball, basketball, handball, badminton, karate, track and field, taekwondo, gymnastics and wrestling was collected from Sports Medical Board of Kerman Province, as the largest province in Iran, and then was analyzed. Data collection method was library one. Furthermore, information related to 210406 insured athletes was analyzed using Descriptive Statistical Indexes in the level mean and SPSS20 Software. The research findings showed that the number of male athletes who injured was higher than female athletes in most sports within various years. Soccer, karate, volleyball, wrestling, handball, taekwondo, gymnastics, basketball, track and field, and badminton had the most injuries, respectively. Moreover, the number of injured athletes and their ratio to insured ones during six years were studied; in general, an increase in ratio of sports injuries was observed. Thus, upward movement of sports injuries in different sports, as the results of this study confirm it, is a warning which results in losing young forces and wasting of sports potential in Iran.

Keywords: sports, sports injuries, survey, Kerman

Procedia PDF Downloads 340

Authors: Sikander Nawaz Khan

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Natural disasters like flood, earthquake, cyclone, volcanic eruption and others are causing immense losses to the property and lives every year. Current status and actual loss information of natural hazards can be determined and also prediction for next probable disasters can be made using different remote sensing and mapping technologies. Global Positioning System (GPS) calculates the exact position of damage. It can also communicate with wireless sensor nodes embedded in potentially dangerous places. GPS provide precise and accurate locations and other related information like speed, track, direction and distance of target object to emergency responders. Remote Sensing facilitates to map damages without having physical contact with target area. Now with the addition of more remote sensing satellites and other advancements, early warning system is used very efficiently. Remote sensing is being used both at local and global scale. High Resolution Satellite Imagery (HRSI), airborne remote sensing and space-borne remote sensing is playing vital role in disaster management. Early on Geographic Information System (GIS) was used to collect, arrange, and map the spatial information but now it has capability to analyze spatial data. This analytical ability of GIS is the main cause of its adaption by different emergency services providers like police and ambulance service. Full potential of these so called 3S technologies cannot be used in alone. Integration of GPS and other remote sensing techniques with GIS has pointed new horizons in modeling of earth science activities. Many remote sensing cases including Asian Ocean Tsunami in 2004, Mount Mangart landslides and Pakistan-India earthquake in 2005 are described in this paper.

Keywords: disaster mitigation, GIS, GPS, remote sensing

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Authors: Iuliana-Erika Köpeczi

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‘Language is no longer regarded as peripheral to our grasp of the world we live in, but as central to it. Words are not mere vocal labels or communicational adjuncts superimposed upon an already given order of things. They are collective products of social interaction, essential instruments through which human beings constitute and articulate their world’, said Roy Harris. If we were to accept the above-mentioned premise, then we surely must accept that discourse, generally, - and political discourse, specifically -, bears a crucial importance to one’s perception of reality. The way in which political rhetoric constructs reality changes the relationship between the voter and his/her view of the world, which, in turn, influences greatly the future trends of political participation. In this context, our inquiry focuses on the role of populist discourses in the post 9/11 political rhetoric, and how this led to the formation, construction and reconstruction of identity within the ‘us’ vs. ‘them’ dichotomy. It is our hypothesis that anti-intellectualistic elements played a significant role in the manner in which identity construction had been carried out on a discursive level. By adopting a comparative approach, we intend to identify the similarities and differences between the use of such anti-intellectualist elements in the United States of America on one hand – within the discourse of Rick Santorum, – and France on the other – with Marine le Pen’s discourse. Our methodological approach uses close textual analysis of primary source material (discourse analysis); historical contextualization of both primary documents and broader socio-political and cultural framework through archival research and secondary sources; as well as interpretation of primary texts through theoretical frameworks (qualitative research). We hope that the output of our endeavor will be useful in better understanding the different correlations that exist between anti-intellectualism and populism and how the interactions between these two elements aids in political identity construction through discourse.

Keywords: anti-intellectualism, discourse theory, France, identity construction, populism, United States of America

Procedia PDF Downloads 255

Authors: Sara Hasani

Abstract:

This research focuses on natural sudden onset disasters characterised as ‘occurring with little or no warning and often cause excessive injuries far surpassing the national response capacities’. Based on the panel analysis of the historic record of 4,252 natural onset disasters between 1980 to 2015, a predictive method was developed to predict the human impact of the disaster (fatality, injured, homeless) with less than 3% of errors. The geographical dispersion of the disasters includes every country where the data were available and cross-examined from various humanitarian sources. The records were then filtered into 4252 records of the disasters where the five predictive variables (disaster type, HDI, DRI, population, and population density) were clearly stated. The procedure was designed based on a combination of pattern recognition techniques and rule-based clustering for prediction and discrimination analysis to validate the results further. The result indicates that there is a relationship between the disaster human impact and the five socio-economic characteristics of the affected country mentioned above. As a result, a framework was put forward, which could predict the disaster’s human impact based on their severity rank in the early hours of disaster strike. The predictions in this model were outlined in two worst and best-case scenarios, which respectively inform the lower range and higher range of the prediction. A necessity to develop the predictive framework can be highlighted by noticing that despite the existing research in literature, a framework for predicting the human impact and estimating the needs at the time of the disaster is yet to be developed. This can further be used to allocate the resources at the response phase of the disaster where the data is scarce.

Keywords: disaster management, natural disaster, pattern recognition, prediction

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Authors: Jixiang Lei, Alexander Fuchs, Franz Pernkopf, Katrin Ellermann

Abstract:

Within the Space@Sea project, funded by the Horizon 2020 program, an island consisting of multiple platforms was designed. The platforms are connected by ropes and fenders. The connection is critical with respect to the safety of the whole system. Therefore, fault detection systems are investigated, which could detect early warning signs for a possible failure in the connection elements. Previously, a model-based method called Extended Kalman Filter was developed to detect the reduction of rope stiffness. This method detected several types of faults reliably, but some types of faults were much more difficult to detect. Furthermore, the model-based method is sensitive to environmental noise. When the wave height is low, a long time is needed to detect a fault and the accuracy is not always satisfactory. In this sense, it is necessary to develop a more accurate and robust technique that can detect all rope faults under a wide range of operational conditions. Inspired by this work on the Space at Sea design, we introduce a fault diagnosis method based on deep neural networks. Our method cannot only detect rope degradation by using the acceleration data from each platform but also estimate the contributions of the specific acceleration sensors using methods from explainable AI. In order to adapt to different operational conditions, the domain adaptation technique DANN is applied. The proposed model can accurately estimate rope degradation under a wide range of environmental conditions and help users understand the relationship between the output and the contributions of each acceleration sensor.

Keywords: fault diagnosis, deep learning, domain adaptation, explainable AI

Procedia PDF Downloads 151