Search results for: clustered patterns

Authors: Iftikhar Hussain Gul, Syeda Aatika

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Nickel ferrite was prepared via wet chemical co-precipitation route. Carbon Nano Fibers (CNFs) were used to prepare NiFe₂O₄/CNFs nanohybrids. Polar solvent (ortho-xylene) was used for the dispersion of CNFs in ferrite matrix. X-ray diffraction patterns confirmed the formation of NiFe₂O₄/CNFs nanohybrids without any impurity peak. FTIR patterns showed two consistent characteristic absorption bands for tetrahedral and octahedral sites, confirming the formation of spinel structure of NiFe₂O₄. Scanning Electron Microscopy (SEM) images confirmed the coating of nickel ferrite nanoparticles on CNFs, which confirms the efficiency of deployed method. The dielectric properties were measured as a function of frequency at room temperature. Pure NiFe₂O₄ showed dielectric constant of 1.79 ×10³ at 100 Hz, which increased massively to 2.92 ×10⁶ at 100 Hz with the addition of 20% by weight of CNFs, proving it to be potential candidate for applications in supercapacitors. The impedance analysis showed a considerable decrease of resistance, reactance and cole-cole plot which confirms the decline of impedance on addition of CNFs. The pure NiFe₂O₄ has highest impedance values of 5.89 ×10⁷ Ohm at 100 Hz while the NiFe₂O₄/CNFs nanohybrid with CNFs (20% by weight) has the lowest impedance values of 4.25×10³ Ohm at 100 Hz, which proves this nanohybrid is useful for high-frequency applications.

Keywords: AC impedance, co-precipitation, nanohybrid, Fourier transform infrared spectroscopy, x-ray diffraction

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Authors: Afshin Moazami, Andrea Schiffauerova

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The objective of this work is to investigate the development and the role of collaboration networks in the creation of knowledge and innovations in the US and Canada, with a special focus on Quebec. In order to create scientific networks, the data on journal articles were extracted from SCOPUS, and the networks were built based on the co-authorship of the journal papers. For innovation networks, the USPTO database was used, and the networks were built on the patent co-inventorship. Various indicators characterizing the evolution of the network structure and the positions of the researchers and inventors in the networks were calculated. The comparison between the United States, Canada, and Quebec was then carried out. The preliminary results show that the nature of scientific collaboration networks differs from the one seen in innovation networks. Scientists work in bigger teams and are mostly interconnected within one giant network component, whereas the innovation network is much more clustered and fragmented, the inventors work more repetitively with the same partners, often in smaller isolated groups. In both Canada and the US, an increasing tendency towards collaboration was observed, and it was found that networks are getting bigger and more centralized with time. Moreover, a declining share of knowledge transfers per scientist was detected, suggesting an increasing specialization of science. The US collaboration networks tend to be more centralized than the Canadian ones. Quebec shares a lot of features with the Canadian network, but some differences were observed, for example, Quebec inventors rely more on the knowledge transmission through intermediaries.

Keywords: Canada, collaboration, innovation network, scientific network, Quebec, United States

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Authors: Berhanu Keno Terfa

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To realize the consequences of urbanization, accurate, and up-to-date representation of the urban landscape patterns is critical for urban planners and policymakers. Thus, the study quantitatively characterized the spatiotemporal composition and configuration of the urban landscape and urban expansion process in Dire Dawa City, Ethiopia, form the year 2006 to 2018. The integrated approaches of various sensors satellite data, Spot (2006) and Sentinel 2 (2018) combined with landscape metrics analysis was employed to explore the pattern, process, and overall growth status in the city. The result showed that the built-up area had increased by 62% between 2006 and 2018, at an average annual increment of 3.6%, while the other land covers were lost significantly due to urban expansion. The highest urban expansion has occurred in the northwest direction, whereas the most fragmented landscape pattern was recorded in the west direction. Overall, the analysis showed that Dire Dawa City experienced accelerated urban expansion with a fragmented and complicated spatiotemporal urban landscape patterns, suggesting a strong tendency towards sprawl over the past 12 years. The findings in the study could help planners and policy developers to insight the historical dynamics of the urban region for sustainable development.

Keywords: zonal metrics, multi-temporal, multi-resolution, urban growth, remote sensing data

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Authors: Yasmine Aridi, Lara Nasreddine, Maya Khalil, Arafat Tfayli, Anas Mugharbel, Farah Naja

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Breast cancer is the most commonly diagnosed cancer site among women worldwide and the second most common cause of cancer mortality. Breast cancer rates differ vastly between geographical areas, countries, and within the same country. In Lebanon, the proportion of breast cancer to all other sites of tumor is 38.2%; these rates are still lower than those observed worldwide, but remain the highest among Arab countries. Studies and evidence based reviews show a strong association between breast cancer development and prognosis and dietary habits, specifically the Mediterranean diet (MD). As such, the aim of this study is to examine dietary patterns and adherence to the MD among a sample of 182 breast cancer female patients in Beirut, Lebanon. Subjects were recruited from two major hospitals; a private medical center and a public hospital. All subjects were administered two questionnaires: socio- demographics and Mediterranean diet adherence. Five Mediterranean scores were calculated: MS, MSDPS, PMDI, PREDIMED and DDS. The mean age of the participants was 53.78 years. The overall adherence to the Mediterranean diet (MD) was low since the sample means of 3 out of the 5 calculated scores were less than the scores’ medians. Given that 4 out of the 5 Mediterranean scores significantly varied between the recruitment sites, women in the private medical center were found to adhere more to the MD. Our results also show that the majority of the sample population’s intakes are exceeding the recommendations for total and saturated fat, while meeting the requirements for fiber, EPA, DHA and Linolenic Acid. Participants in the private medical center were consuming significantly more calories, carbohydrates, fiber, sugar, Lycopene, Calcium, Iron and Folate and less fat. After conducting multivariate linear regression analyses, the following significant results were observed: positive associations between MD (CPMDI, PREDIMED) and monthly income & current state of health, while negative associations between MD (MSDPS, PREDIMED) and age & employment status. Our findings indicated a low overall adherence to the MD and identified factors associated with it; which suggests a need to address dietary habits among BC patients in Lebanon, specifically encouraging them to adhere to their traditional Mediterranean diet.

Keywords: Adherence, Breast cancer, Dietary patterns, Mediterranean diet, Nutrition

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Authors: Zehai Yu, Hui Zhu, Linglong Lin, Huawei Liang, Biao Yu, Weixin Huang

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With the development of intelligent vehicle systems, a high-precision road map is increasingly needed in many aspects. The automatic lane lines extraction and modeling are the most essential steps for the generation of a precise lane-level road map. In this paper, an automatic lane-level road map generation system is proposed. To extract the road markings on the ground, the multi-region Otsu thresholding method is applied, which calculates the intensity value of laser data that maximizes the variance between background and road markings. The extracted road marking points are then projected to the raster image and clustered using a two-stage clustering algorithm. Lane lines are subsequently recognized from these clusters by the shape features of their minimum bounding rectangle. To ensure the storage efficiency of the map, the lane lines are approximated to cubic polynomial curves using a Bayesian estimation approach. The proposed lane-level road map generation system has been tested on urban and expressway conditions in Hefei, China. The experimental results on the datasets show that our method can achieve excellent extraction and clustering effect, and the fitted lines can reach a high position accuracy with an error of less than 10 cm.

Keywords: curve fitting, lane-level road map, line recognition, multi-thresholding, two-stage clustering

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Authors: Adel H.El-Afandy, Abd Alrahman Embaby, Mona A. El Harairey

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Abu Marw area is located in the southeastern part of the Eastern Desert, about 150km south east of Aswan. Abu Marw area is mainly covered by late Proterozoic igneous and metamorphic rocks. These basement rocks are nonconformably overlain by late Cretaceous Nubian sandstones in the western and northern parts of the areas. Abu Marw granitoid batholiths comprises a co-magmatic calc alkaline I type peraluminous suite of rocks ranging in composition from tonalite, granodiorite, monzogranite, syenogranite to alkali feldspar granite. The studied tonalite and granodiorite samples have ΣREE lower than the average REE values (250ppm) of granitic rocks, while the monzogranite, syenogranite and alkali feldspar granite samples have ΣREE above the average REE values of granitic rocks. Chondrite-normalized REE patterns of the considered granites display a gull-wing shape, characterized by large to moderately fractionated patterns and high LREE relative to the MREE and HREE contents. Furthermore, the studied rocks have a steadily decreasing Eu/Eu* values from the tonalite to the alkali feldspar granite with simultaneous increase in the ΣREE contents. The average U contents in different granitic rocks.

Keywords: granite, rare earth element, radioactivity, Abu Marw, south eastern desert

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Authors: Dona Shaini Abhilasha Nanayakkara, Kurugamage Jude Pravinda Gregory Perera

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E-commerce platforms have revolutionized the shopping experience, offering convenient ways for consumers to make purchases. To improve interactions with customers and optimize marketing strategies, it is essential for businesses to understand user behavior, preferences, and needs on these platforms. This paper focuses on recommending businesses to customize interactions with users based on their behavioral patterns, leveraging data-driven analysis and machine learning techniques. Businesses can improve engagement and boost the adoption of e-commerce platforms by aligning behavioral patterns with user goals of usability and satisfaction. We propose TheAnalyzer, a clustering-based system designed to enhance business productivity by analyzing user-profiles and improving human-computer interaction. The Analyzer seamlessly integrates with business applications, collecting relevant data points based on users' natural interactions without additional burdens such as questionnaires or surveys. It defines five key user analytics as features for its dataset, which are easily captured through users' interactions with e-commerce platforms. This research presents a study demonstrating the successful distinction of users into specific groups based on the five key analytics considered by TheAnalyzer. With the assistance of domain experts, customized business rules can be attached to each group, enabling The Analyzer to influence business applications and provide an enhanced personalized user experience. The outcomes are evaluated quantitatively and qualitatively, demonstrating that utilizing TheAnalyzer’s capabilities can optimize business outcomes, enhance customer satisfaction, and drive sustainable growth. The findings of this research contribute to the advancement of personalized interactions in e-commerce platforms. By leveraging user behavioral patterns and analyzing both new and existing users, businesses can effectively tailor their interactions to improve customer satisfaction, loyalty and ultimately drive sales.

Keywords: data clustering, data standardization, dimensionality reduction, human computer interaction, user profiling

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Authors: C. Zimmermann, E. Lackner, M. Ebner

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Massive Open Online Courses (MOOCs) are increasingly popular learning hubs that are boasting considerable participant numbers, innovative technical features, and a multitude of instructional resources. Still, there is a high level of evidence showing that almost all MOOCs suffer from a declining frequency of participant activity and fairly low completion rates. In this paper, we would like to share the lessons learned in implementing several design patterns that have been suggested in order to foster participant activity. Our conclusions are based on experiences with the ‘Dr. Internet’ MOOC, which was created as an xMOOC to raise awareness for a more critical approach to online health information: participants had to diagnose medical case studies. There is a growing body of recommendations (based on Learning Analytics results from earlier xMOOCs) as to how the decline in participant activity can be alleviated. One promising focus in this regard is instructional design patterns, since they have a tremendous influence on the learner’s motivation, which in turn is a crucial trigger of learning processes. Since Medieval Age storytelling, micro-learning units and specific comprehensible, narrative structures were chosen to animate the audience to follow narration. Hence, MOOC participants are not likely to abandon a course or information channel when their curiosity is kept at a continuously high level. Critical aspects that warrant consideration in this regard include shorter course duration, a narrative structure with suspense peaks (according to the ‘storytelling’ approach), and a course schedule that is diversified and stimulating, yet easy to follow. All of these criteria have been observed within the design of the Dr. Internet MOOC: 1) the standard eight week course duration was shortened down to six weeks, 2) all six case studies had a special quiz format and a corresponding resolution video which was made available in the subsequent week, 3) two out of six case studies were split up in serial video sequences to be presented over the span of two weeks, and 4) the videos were generally scheduled in a less predictable sequence. However, the statistical results from the first run of the MOOC do not indicate any strong influences on the retention rate, so we conclude with some suggestions as to why this might be and what aspects need further consideration.

Keywords: case study, Dr. internet, experience, MOOCs, design patterns

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Authors: Ylva Fältholm, Cathrine Norberg

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One of the major threats identified to successful future mining is that women do not find the industry attractive. Many attempts have been made, for example in Sweden and Australia, to create organizational structures and mining communities attractive to both genders. Despite such initiatives, many mining areas are developing into gender-segregated fly-in/fly out communities dominated by men with both social and economic consequences. One of the challenges facing many mining companies is thus to break traditional gender patterns and structures. To do this increased knowledge about gender in the context of mining is needed. Since language both constitutes and reproduces knowledge, increased knowledge can be gained through an exploration and description of the mining discourse from a gender perspective. The aim of this study is to explore what conceptual ideas are activated in connection to the physical/geographical mining area and to work within the mining industry. We use a combination of critical discourse analysis implying close reading of selected texts, such as policy documents, interview materials, applications and research and innovation agendas, and analyses of linguistic patterns found in large language corpora covering millions of words of contemporary language production. The quantitative corpus data serves as a point of departure for the qualitative analysis of the texts, that is, suggests what patterns to explore further. The study shows that despite technological and organizational development, one of the most persistent discourses about mining is the conception of dangerous and unfriendly areas infused with traditional notions of masculinity ideals and manual hard work. Although some of the texts analyzed highlight gender issues, and describe gender-equalizing initiatives, such as wage-mapping systems, female networks and recruitment efforts for women executives, and thereby render the discourse less straightforward, it is shown that these texts are not unambiguous examples of a counter-discourse. They rather illustrate that discourses are not stable but include opposing discourses, in dialogue with each other. For example, many texts highlight why and how women are important to mining, at the same time as they suggest that gender and diversity are all about women: why mining is a problem for them, how they should be, and what they should do to fit in. Drawing on a constitutive view of discourse, knowledge about such conflicting perceptions of women is a prerequisite for succeeding in attracting women to the mining industry and thereby contributing to the development of future mining.

Keywords: discourse, corpus linguistics, gender, mining

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Authors: Edilene Mercedes Mauer Machado, Carolina Hadassa Marques Karoly, Amanda Britz, Claudineia Brazil

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The El Niño phenomenon, characterized by the anomalous warming of surface waters in the Equatorial Pacific Ocean, can influence weather patterns in various parts of the world, including the occurrence of extreme events such as droughts or heavy rainfall. Studies have suggested a relationship between El Niño and an increase in the incidence of dengue in certain areas. During El Niño periods, there can be changes in climatic conditions, such as increased temperatures and reduced rainfall in certain tropical and subtropical regions. These conditions can favor the reproduction of the Aedes aegypti mosquito, the vector for dengue transmission. Research aims to investigate how climate events like El Niño and La Niña can influence the incidence and transmission of dengue. The results have shown that, on average, there was a significant increase in dengue cases during La Niña years compared to years of climatic neutrality, contradicting the findings of Hopp et al. (2015). The study also highlighted that regions affected by El Niño exhibited greater variability in dengue incidence. However, it is important to emphasize that the effects of El Niño on dengue transmission can vary depending on the region and local factors, such as socioeconomic context and implemented control measures, as described by Johansson et al. (2009). Not all areas affected by El Niño will necessarily experience an increase in dengue incidence, and the interaction between climate and disease transmission is complex.

Keywords: anomalous warming, climatic patterns, dengue incidence, extreme events

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Authors: Guinevere Servis

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This paper hypothesizes that withdrawal from positive self-awareness, and the increase of counterfactual-thinking and self-handicapping can help provide ample justification for an individual before, during and/or after committing a crime. The understanding of who someone is, one’s perspective on the world, and why they think the way they do is key to therapy in preventing recidivism. Developing habits to escape self-awareness, by using self-handicapping and counterfactual ideologies, may provide the necessary thinking patterns to decide disobeying the law is a worthy act to pursue. An increase in self-awareness is hypothesized to decrease the likelihood of recidivism, and ways of thinking that withdraw from self awareness can increase the likelihood of it. Especially for those who have been disadvantaged in life and disobeyed the law, self-handicapping and counterfactual thinking can also help to justify one's wrongdoing. The understanding of how a criminal views their disadvantages in the world, and one’s thinking patterns are hypothesized to help one better understand the entire scope on why a crime was committed and thus reduce the likelihood of recidivism. Utilizing therapy for prisoners to increase self-awareness of both thought and action can lead to a healthy, happier life and reduce the likelihood of reoffending. By discussing the terms associated with self-awareness theory and other psychological topics such as self-handicapping, counterfactual thinking, this paper argues the actions towards increasing positive self-awareness can help decrease likelihood of recidivism. Adversely, hypothesizing that increasing the ways of thinking that withdraw one from self-awareness, through counterfactual thinking and self-handicapping, can inherently increase the likelihood of recidivism. Evaluating these findings to further understand the needed changes in correctional institutions is fundamental to reducing crime, benefiting the criminal, the victim(s) and their family, and the state.

Keywords: crime, self-awareness theory, correctional institutions, self-regulate, counterfactual thinking, recidivism

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Authors: Xiuguo Zhao, He Li, Alireza Yazdani, Xiaoning Zheng, Xinxi Xu

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Wound infected poses a serious threat to the surgery on the patient during the process of surgery. Understanding the bacteria-carrying particles (BCPs) transportation and deposition in the open surgical wound model play essential role in protecting wound against being infected. Therefore BCPs transportation and deposition in the surgical wound model were investigated using force-coupling method (FCM) based computational fluid dynamics. The BCPs deposition in the wound was strongly associated with BCPs diameter and concentration. The results showed that the rise on the BCPs deposition was increasing not only with the increase of BCPs diameters but also with the increase of the BCPs concentration. BCPs deposition morphology was impacted by the combination of size distribution, airflow patterns and model geometry. The deposition morphology exhibited the characteristic with BCPs deposition on the sidewall in wound model and no BCPs deposition on the bottom of the wound model mainly because the airflow movement in one direction from up to down and then side created by laminar system constructing airflow patterns and then made BCPs hard deposit in the bottom of the wound model due to wound geometry limit. It was also observed that inertial impact becomes a main mechanism of the BCPs deposition. This work may contribute to next study in BCPs deposition limit, as well as wound infected estimation in surgical-site infections.

Keywords: BCPs deposition, computational fluid dynamics, force-coupling method (FCM), numerical simulation, open surgical wound model

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Authors: Fortaki Tarek, S. Bedra

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In this paper, the effects of both uniaxial anisotropy in the substrate and high Tc superconducting patch on the resonant frequency, half-power bandwidth, and radiation patterns are investigated using an electric field integral equation and the spectral domain Green’s function. The analysis has been based on a full electromagnetic wave model with London’s equations and the Gorter-Casimir two-fluid model has been improved to investigate the resonant and radiation characteristics of high Tc superconducting rectangular microstrip patch in the case where the patch is printed on electric-magnetic uniaxially anisotropic substrate materials. The stationary phase technique has been used for computing the radiation electric field. The obtained results demonstrate a considerable improvement in the half-power bandwidth, of the rectangular microstrip patch, by using a superconductor patch instead of a perfect conductor one. Further results show that high Tc superconducting rectangular microstrip patch on the uniaxial substrate with properly selected electric and magnetic anisotropy ratios is more advantageous than the one on the isotropic substrate by exhibiting wider bandwidth and radiation characteristic. This behavior agrees with that discovered experimentally for superconducting patches on isotropic substrates. The calculated results have been compared with measured one available in the literature and excellent agreement has been found.

Keywords: high Tc superconducting microstrip patch, electric-magnetic anisotropic substrate, Galerkin method, surface complex impedance with boundary conditions, radiation patterns

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Authors: Hlabishi Peter Ntloana

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This paper aims to present the effectiveness of the Spatial Planning and Land Use Management Act, 2013, in addressing key spatial challenges in Fetakgomo Tubatse Local Municipality, mainly focusing on Apel nodal point. Spatial Planning and Land Use Management Act, 2013, popularly known as SPLUMA, aimed at addressing emerging and existing spatial planning and land use management challenges in South Africa. There are critical key spatial challenges that are continuously encountered in Apel Nodal Point, which include dispersed rural settlement mainly in a communal settlement. The spatial patterns and rural settlements development patterns are a challenge, and such results in uncoordinated human settlements. The objective of this research paper is to analyze the spatial planning of Apel nodal points and determine the effectiveness of the SPLUMA policy. Key Informant interviews were conducted with 20 participants, and also the municipal Spatial Development Framework was considered to explore more challenges and proposed recommendations. The results divulged that there is a huge gap in addressing spatial planning, mainly in rural areas, and correlation with the findings of the Municipal Spatial Development framework. In conclusion, spatial planning remains a critical dilemma in most rural settlements, and there must be programmes and strategies to balance the effectiveness of spatial planning in urban and rural settlements.

Keywords: land use management, rural settlement, spatial development framework, spatial planning

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Authors: Alok S Chauhan, Sridhar S., Pradyumna R.

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In the process of precision investment casting of turbine hollow blade/vane components, a part of the dimensional deviations observed in the castings can be attributed to the wax pattern. In the process of injection moulding of wax to produce patterns, heated wax shrinks in size during cooling in the die, leading to a reduction in the dimensions of the pattern. Also, flow and thermal induced residual stresses result in shrinkage & warpage of the component after removal from the die, further adding to the deviations. Injection moulding parameters such as wax temperature, flow rate, packing pressure, etc. affect the flow and thermal behavior of the component and hence are directly responsible for the dimensional deviations. There is a need to precisely determine and control these deviations in order to achieve stringent dimensional accuracies imposed on these castings by aerospace standards. Simulation based approaches provide a platform to predict these dimensional deviations without resorting to elaborate experimentation. In the present paper, Moldex3D simulation package has been utilized to analyze the effect of variations in injection temperature, packing pressure and cooling time on the shrinkage behavior of a stepped pattern. Two types of waxes with different rheological properties have been included in the study to gauge the effect of change in wax on the dimensional deviations. A full factorial design of experiments has been configured with these parameters and results of analysis of variance have been presented.

Keywords: wax patterns, investment casting, pattern die/mould, wax injection, Moldex3D simulation

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Authors: Yan-Lin Liu, Cheng-Ting Shih, Jay Wu

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Tablet devices have been introduced into the medical environment in recent years. The performance of display can be varied based on the use of different hardware specifications and types of display technologies. Therefore, the differences between tablet devices and medical diagnostic LCDs have to be verified to ensure that image quality is not jeopardized for clinical diagnosis in a picture archiving and communication system (PACS). In this study, a set of randomized object test patterns (ROTPs) were developed, which included randomly located spheres in abdominal CT images. Five radiologists were asked to independently review the CT images on different generations of iPads and a diagnostic monochrome medical LCD monitor. Receiver operating characteristic (ROC) analysis was performed by using a five-point rating scale, and the average area under curve (AUC) and average reading time (ART) were calculated. The AUC values for the second generation iPad, iPad mini, iPad Air, and monochrome medical monitor were 0.712, 0.717, 0.725, and 0.740, respectively. The differences between iPads were not significant. The ARTs were 177 min and 127 min for iPad mini and medical LCD monitor, respectively. A significant difference appeared (p = 0.04). The results show that the iPads were slightly inferior to the monochrome medical LCD monitor. However, tablet devices possess advantages in portability and versatility, which can improve the convenience of rapid diagnosis and teleradiology. With advances in display technology, the applicability of tablet devices and mobile devices may be more diversified in PACS.

Keywords: tablet devices, PACS, receiver operating characteristic, LCD monitor

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Authors: Zeinab Jafari A., Ali Sharifnezhad B., Mohammad Razi C., Mohammad Haghpanahi D., Arash Maghsoudi

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Background and Objective: Sports-related rupture of the anterior cruciate ligament (ACL) and following injuries have been associated with various disorders, such as long-lasting changes in muscle activation patterns in athletes, which might last after ACL reconstruction (ACLR). The rupture of the ACL might result in abnormal patterns of movement execution, extending the treatment period and delaying athletes’ return to sports (RTS). As ACL injury is especially prevalent among athletes, the lengthy treatment process and athletes’ absence from sports are of great concern to athletes and coaches. Thus, estimating safe time of RTS is of crucial importance. Therefore, using a deep neural network (DNN) to classify the health levels of ACL in injured athletes, this study aimed to estimate the safe time for athletes to return to competitions. Methods: Ten athletes with ACLR and fourteen healthy controls participated in this study. Three health levels of ACL were defined: healthy, six-month post-ACLR surgery and nine-month post-ACLR surgery. Athletes with ACLR were tested six and nine months after the ACLR surgery. During the course of this study, surface electromyography (sEMG) signals were recorded from five knee muscles, namely Rectus Femoris (RF), Vastus Lateralis (VL), Vastus Medialis (VM), Biceps Femoris (BF), Semitendinosus (ST), during single-leg drop landing (SLDL) and forward hopping (SLFH) tasks. The Pseudo-Wigner-Ville distribution (PWVD) was used to produce three-dimensional (3-D) images of the energy distribution patterns of sEMG signals. Then, these 3-D images were converted to two-dimensional (2-D) images implementing the heat mapping technique, which were then fed to a deep convolutional neural network (DCNN). Results: In this study, we estimated the safe time of RTS by designing a DCNN classifier with an accuracy of 90 %, which could classify ACL into three health levels. Discussion: The findings of this study demonstrate the potential of the DCNN classification technique using sEMG signals in estimating RTS time, which will assist in evaluating the recovery process of ACLR in athletes.

Keywords: anterior cruciate ligament reconstruction, return to sports, surface electromyography, deep convolutional neural network

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Authors: S. Roy, R. Rekha, K. Sriram, G. Subhadra, R. Johana

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Cardiovascular disease remains a leading cause of death in most industrialized countries. Many chemical drugs are available in the market which targets different receptor proteins related to cardiovascular diseases. Of late the traditional herbal drugs are safer when compared to chemical drugs because of its side effects. However, many herbal remedies used in treating cardiovascular diseases have not undergone scientific assessment to prove its pharmacological activities. There are many natural compounds, nature derived and Natural product mimic compounds are available which are in the market as approved drug. In the most of the cases drug activity at the molecular level are not known. Here we have categorized those compounds with our experimental compounds in different classes based on the structural similarity and physicochemical properties, using a tool, Chemmine and has attempted to understand the mechanism of the action of a experimental compound, which are clustered with Simvastatin, Lovastatin, Mevastatin and Pravastatin. Target protein molecule for Simvastatin, Lovastatin, Mevastatin and Pravastatin is HMG-CoA reductase, so we concluded that the experimental compound may be able to bind to the same target. Molecular docking and atomic interaction studies with simvastatin and our experimental compound were compared. A pharmacophore modeling was done based on the experimental compound and HMG-CoA reductase inhibitor.

Keywords: molecular docking, physicochemical properties, pharmacophore modeling structural similarity, pravastatin

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Authors: Hamdi Sana, Emna Bouazizi, Sami Faiz

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In recent years, there is a huge increase in the use of spatio-temporal applications where data and queries are continuously moving. As a result, the need to process real-time spatio-temporal data seems clear and real-time stream data management becomes a hot topic. Sliding window model and frequent itemset mining over dynamic data are the most important problems in the context of data mining. Thus, sliding window model for frequent itemset mining is a widely used model for data stream mining due to its emphasis on recent data and its bounded memory requirement. These methods use the traditional transaction-based sliding window model where the window size is based on a fixed number of transactions. Actually, this model supposes that all transactions have a constant rate which is not suited for real-time applications. And the use of this model in such applications endangers their performance. Based on these observations, this paper relaxes the notion of window size and proposes the use of a timestamp-based sliding window model. In our proposed frequent itemset mining algorithm, support conditions are used to differentiate frequents and infrequent patterns. Thereafter, a tree is developed to incrementally maintain the essential information. We evaluate our contribution. The preliminary results are quite promising.

Keywords: real-time spatial big data, frequent itemset, transaction-based sliding window model, timestamp-based sliding window model, weighted frequent patterns, tree, stream query

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Authors: Tsvetomira Braynova, Miglena Simonska

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The article presents the results of research on phonological processes in three and four-year-old children. For the purpose of the study, an author's test was developed and conducted among 120 children. The study included three areas of research - at the level of words (96 words), at the level of sentence repetition (10 sentences) and at the level of generating own speech from a picture (15 pictures). The test also gives us additional information about the articulation errors of the assessed children. The main purpose of the icing is to analyze all phonological processes that occur at this age in Bulgarian children and to identify which are typical and atypical for this age. The results show that the most common phonology errors that children make are: sound substitution, an elision of sound, metathesis of sound, elision of a syllable, and elision of consonants clustered in a syllable. All examined children were identified with the articulatory disorder from type bilabial lambdacism. Measuring the correlation between the average length of repeated speech and the average length of generated speech, the analysis proves that the more words a child can repeat in part “repeated speech,” the more words they can be expected to generate in part “generating sentence.” The results of this study show that the task of naming a word provides sufficient and representative information to assess the child's phonology.

Keywords: assessment, phonology, articulation, speech-language development

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Authors: Velly Kapadia, Reenu Singh

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This report identifies the long-term driving forces behind urbanization and the impact of compact living on both society and the home and proposes a concept to create smarter and more sustainable homes. Compact living has been trending across India as a sustainable housing solution, and the reality is that India is currently facing a housing shortage in urban areas of around 10 million units. With the rising demand for housing, urban land prices have been rising and the cost of homes. The paper explores how and why the interior design of the homes can be improved to relieve the housing demand in an environmentally, socially and economically sustainable manner. A questionnaire survey was conducted to determine living patterns, area requirements, ecological footprints, energy consumption, purchasing patterns, and various pro-environmental behaviors of people who downsize to compact homes. Quantitative research explores sustainable material choices, durability, functionality, cost, and reusability of furniture. Besides addressing the need for smart and sustainable designed compact homes, a conceptual model is proposed, including options of ideal schematic layouts for homes in urban areas. In the conclusions, suggestions to improve space planning and suitable interior entities have been made to support the fact that compact homes are an eminently practical and sensible solution for the urban citizen.

Keywords: compact living, housing shortage, lifestyle, sustainable interior design

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Authors: M. Nadeem, Y. K. Chang, C. Diallo, U. Venkatadri, P. Havard, T. Nguyen-Quang

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Uniform distribution of agro-chemicals is highly important because there is a significant loss of agro-chemicals, for example from pesticide, during spraying due to non-uniformity of droplet and off-target drift. Improving the efficiency of spray pattern for different cropping systems would reduce energy, costs and to minimize environmental pollution. In this paper, we examine the water jet patterns in order to study the performance and uniformity of water distribution during the spraying process. We present a method to quantify the water amount from a sprayer jet by using the Particle Image Velocimetry (PIV) system. The results of the study will be used to optimize sprayer or nozzles design for chemical application. For this study, ten sets of images were acquired by using the following PIV system settings: double frame mode, trigger rate is 4 Hz, and time between pulsed signals is 500 µs. Each set of images contained different numbers of double-framed images: 10, 20, 30, 40, 50, 60, 70, 80, 90 and 100 at eight different pressures 25, 50, 75, 100, 125, 150, 175 and 200 kPa. The PIV images obtained were analysed using custom-made image processing software for droplets and volume calculations. The results showed good agreement of both manual and PIV measurements and suggested that the PIV technique coupled with image processing can be used for a precise quantification of flow through nozzles. The results also revealed that the method of measuring fluid flow through PIV is reliable and accurate for sprayer patterns.

Keywords: image processing, PIV, quantifying the water volume from nozzle, spraying pattern

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Authors: Amira, A. Goma, U. E. Mahrous

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Welfare may be considered to be a subjective experience; it has a biological function that is related to the fitness and survival of the animal accordingly, researches have suggested that welfare is compromised when the animal's evolutionary fitness is reduced. This study was carried out to explain the effect of some managerial stressors as handling and restraint on behavioral patterns and biochemical parameters of rats. A total of 24 (12 males and 12 females) Sprague-Dawley rats (12 months and 150-180g) were allotted into 3 groups, handled group (4 male and 4 female), restrained group (4 male and 4 female) and control group (4 males and 4 females). The obtained results revealed that time spent feeding, drinking frequency, movement and cage exploration increased significantly in handled rats than other groups, while lying time and licking increased significantly in restrained rats than handled and controls. Moreover, social behavior decreased in both stressed groups than control. Triglycerides were significantly increased in handled rats than other groups, while total lipid, total protein and globulin significantly increased in both treated groups than control. Corticosterone increased in restrained and handled rats than control ones. Moreover, there was an increment in packed cell volume significantly in restrained rats than others. These deducted that if we want to study the effect of stress on animal welfare it is necessary to study the effect of such stressors on animal’s behavior and physiological responses.

Keywords: handling, restraint, welfare, rat, behavior, physiology

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Authors: Apostolos Lagarias, Anastasia Stratigea

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Coastal urbanization is heavily affecting the Mediterranean, taking the form of linear urban sprawl along the coastal zone. This process is posing extreme pressure on ecosystems, leading to an unsustainable model of growth. The aim of this research is to analyze coastal urbanization patterns in the Mediterranean using High-resolution multi-temporal data provided by the Global Human Settlement Layer (GHSL) database. Methodology involves the estimation of a set of spatial metrics characterizing the density, aggregation/clustering and dispersion of built-up areas. As case study areas, the Spanish Coast and the Adriatic Italian Coast are examined. Coastalization profiles are examined and selected sub-areas massively affected by tourism development and suburbanization trends (Costa Blanca/Murcia, Costa del Sol, Puglia, Emilia-Romagna Coast) are analyzed and compared. Results show that there are considerable differences between the Spanish and the Italian typologies of spatial development, related to the land use structure and planning policies applied in each case. Monitoring and analyzing spatial patterns could inform integrated Mediterranean strategies for coastal areas and redirect spatial/environmental policies towards a more sustainable model of growth

Keywords: coastalization, Mediterranean, multi-temporal, urban sprawl, spatial metrics

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Authors: Angelina A. Tzacheva, Jaishree Ranganathan

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Interest in (STEM) Science Technology Engineering Mathematics education especially Computer Science education has seen a drastic increase across the country. This fuels effort towards recruiting and admitting a diverse population of students. Thus the changing conditions in terms of the student population, diversity and the expected teaching and learning outcomes give the platform for use of Innovative Teaching models and technologies. It is necessary that these methods adapted should also concentrate on raising quality of such innovations and have positive impact on student learning. Light-Weight Team is an Active Learning Pedagogy, which is considered to be low-stake activity and has very little or no direct impact on student grades. Emotion plays a major role in student’s motivation to learning. In this work we use the student feedback data with emotion classification using surveys at a public research institution in the United States. We use Actionable Pattern Discovery method for this purpose. Actionable patterns are patterns that provide suggestions in the form of rules to help the user achieve better outcomes. The proposed method provides meaningful insight in terms of changes that can be incorporated in the Light-Weight team activities, resources utilized in the course. The results suggest how to enhance student emotions to a more positive state, in particular focuses on the emotions ‘Trust’ and ‘Joy’.

Keywords: actionable pattern discovery, education, emotion, data mining

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Authors: S. Abera, T. Gidey, W. Terefe

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Introduction: Testing for HIV is the key entry point to HIV prevention, treatment, and care and support services. Hence, predictive data mining techniques can greatly benefit to analyze and discover new patterns from huge datasets like that of EDHS 2011 data. Objectives: The objective of this study is to build a predictive modeling for HIV testing and identify determinants of HIV testing for adults with age above fourteen years using data mining techniques. Methods: Cross-Industry Standard Process for Data Mining (CRISP-DM) was used to predict the model for HIV testing and explore association rules between HIV testing and the selected attributes among adult Ethiopians. Decision tree, Naïve-Bayes, logistic regression and artificial neural networks of data mining techniques were used to build the predictive models. Results: The target dataset contained 30,625 study participants; of which 16, 515 (53.9%) were women. Nearly two-fifth; 17,719 (58%), have never been tested for HIV while the rest 12,906 (42%) had been tested. Ethiopians with higher wealth index, higher educational level, belonging 20 to 29 years old, having no stigmatizing attitude towards HIV positive person, urban residents, having HIV related knowledge, information about family planning on mass media and knowing a place where to get testing for HIV showed an increased patterns with respect to HIV testing. Conclusion and Recommendation: Public health interventions should consider the identified determinants to promote people to get testing for HIV.

Keywords: data mining, HIV, testing, ethiopia

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Authors: Ashok Sachdeva

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This research paper delves into the application of digital tools, especially Voyant Tools and AntConc version 4.0, for the analysis and interpretation of Seamus Heaney's poems. Scholars and literary aficionados can acquire deeper insights into Heaney's writings by utilising these tools, revealing hidden nuances and improving their knowledge. This paper outlines the methodology used, presents sample analyses and evaluates the merits and limitations of using digital tools in literary analysis. The combination of traditional close reading with digital analysis tools promises to offer new paths for understanding Heaney's vast tapestry of poetry. Seamus Heaney, a Nobel winner known for his vivid poetry, provides a treasure mine of literary discovery. The advent of digital tools gives an exciting opportunity to reveal previously unknown layers of meaning within his works. This paper investigates the use of Voyant Tools and AntConc version 4.0 to analyse and understand Heaney's writings, demonstrating the symbiotic relationship between traditional literary analysis and cutting-edge digital methodologies. Methodology: To demonstrate the efficiency of digital tools in the analysis of Heaney's poetry, a sample of his notable works will be entered into Voyant Tools and AntConc version 4.0. The former provides a graphic representation of word frequency, word clouds, and patterns over numerous poems. The latter, a concordance tool, enables detailed linguistic analysis, revealing patterns, and linguistic subtleties.

Keywords: digital tools, resonance, assonance, alliteration, creative quotient

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Authors: Shankaran Sitarama

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New Product Development (NPD) is invariably a team effort and involves effective teamwork. NPD team has members from different disciplines coming together and working through the different phases all the way from conceptual design phase till the production and product roll out. Creativity and Innovation are some of the key factors of successful NPD. Team members going through the different phases of NPD interact and work closely yet challenge each other during the design phases to brainstorm on ideas and later converge to work together. These two traits require the teams to have a divergent and a convergent thinking simultaneously. There needs to be a good balance. The team dynamics invariably result in conflicts among team members. While some amount of conflict (ideational conflict) is desirable in NPD teams to be creative as a group, relational conflicts (or discords among members) could be detrimental to teamwork. Team communication truly reflect these tensions and team dynamics. In this research, team communication (emails) between the members of the NPD teams is considered for analysis. The email communication is processed through a semantic analysis algorithm (LSA) to analyze the content of communication and a semantic similarity analysis to arrive at a social network graph that depicts the communication amongst team members based on the content of communication. The amount of communication (content and not frequency of communication) defines the interaction strength between the members. Social network adjacency matrix is thus obtained for the team. Standard social network analysis techniques based on the Adjacency Matrix (AM) and Dichotomized Adjacency Matrix (DAM) based on network density yield network graphs and network metrics like centrality. The social network graphs are then rendered for visual representation using a Metric Multi-Dimensional Scaling (MMDS) algorithm for node placements and arcs connecting the nodes (representing team members) are drawn. The distance of the nodes in the placement represents the tie-strength between the members. Stronger tie-strengths render nodes closer. Overall visual representation of the social network graph provides a clear picture of the team’s interactions. This research reveals four distinct patterns of team interaction that are clearly identifiable in the visual representation of the social network graph and have a clearly defined computational scheme. The four computational patterns of team interaction defined are Central Member Pattern (CMP), Subgroup and Aloof member Pattern (SAP), Isolate Member Pattern (IMP), and Pendant Member Pattern (PMP). Each of these patterns has a team dynamics implication in terms of the conflict level in the team. For instance, Isolate member pattern, clearly points to a near break-down in communication with the member and hence a possible high conflict level, whereas the subgroup or aloof member pattern points to a non-uniform information flow in the team and some moderate level of conflict. These pattern classifications of teams are then compared and correlated to the real level of conflict in the teams as indicated by the team members through an elaborate self-evaluation, team reflection, feedback form and results show a good correlation.

Keywords: team dynamics, team communication, team interactions, social network analysis, sna, new product development, latent semantic analysis, LSA, NPD teams

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Authors: Carolina S. Monteiro, Eugénia Pinto, Miguel A. Faria, Sara C. Cunha

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Rice (Oryza sativa) production plays a vital role in reducing hunger and poverty and assumes particular importance in low-income and developing countries. Rice is a sensitive plant, and production occurs strictly where suitable temperature and water conditions are found. Climatic changes are likely to affect worldwide, and some models have predicted increased temperatures, variations in atmospheric CO₂ concentrations and modification in precipitation patterns. Therefore, the ongoing climatic changes threaten rice production by increasing biotic and abiotic stress factors, and crops will grow in different environmental conditions in the following years. Around the world, the effects will be regional and can be detrimental or advantageous depending on the region. Mediterranean zones have been identified as possible hot spots, where dramatic temperature changes, modifications of CO₂ levels, and rainfall patterns are predicted. The actual estimated atmospheric CO₂ concentration is around 400 ppm, and it is predicted that it can reach up to 1000–1200 ppm, which can lead to a temperature increase of 2–4 °C. Alongside, rainfall patterns are also expected to change, with more extreme wet/dry episodes taking place. As a result, it could increase the migration of pathogens, and a shift in the occurrence of mycotoxins, concerning their types and concentrations, is expected. Mycotoxigenic spoilage fungi can colonize the crops and be present in all rice food chain supplies, especially Penicillium species, mainly resulting in ochratoxin A (OTA) contamination. In this scenario, the objectives of the present study are evaluating the effect of temperature (20 vs. 25 °C), CO₂ (400 vs. 1000 ppm), and water stress (0.93 vs 0.95 water activity) on growth and OTA production by a Penicillium nordicum strain in vitro on rice-based media and when colonizing layers of raw rice. Results demonstrate the effect of temperature, CO₂ and drought on the OTA production in a rice-based environment, thus contributing to the development of mycotoxins predictive models in climate change scenarios. As a result, improving mycotoxins' surveillance and monitoring systems, whose occurrence can be more frequent due to climatic changes, seems relevant and necessary. The development of prediction models for hazard contaminants presents in foods highly sensitive to climatic changes, such as mycotoxins, in the highly probable new agricultural scenarios is of paramount importance.

Keywords: climate changes, ochratoxin A, penicillium, rice

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Authors: Hyojin Lim, Cuong Nguyen Khac, Yeongyu Choi, Ho-Youl Jung

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In this paper, we propose a simple moving object detection, which is based on motion vectors obtained from pyramidal Lucas-Kanade optical flow. The proposed method detects moving objects such as pedestrians, the other vehicles and some obstacles at the front-side of the host vehicle, and it can provide the warning to the driver. Motion vectors are obtained by using pyramidal Lucas-Kanade optical flow, and some outliers are eliminated by comparing the amplitude of each vector with the pre-defined threshold value. The background model is obtained by calculating the mean and the variance of the amplitude of recent motion vectors in the rectangular shaped local region called the cell. The model is applied as the reference to classify motion vectors of moving objects and those of background. Motion vectors are clustered to rectangular regions by using the unsupervised clustering K-means algorithm. Labeling method is applied to label groups which is close to each other, using by distance between each center points of rectangular. Through the simulations tested on four kinds of scenarios such as approaching motorbike, vehicle, and pedestrians to host vehicle, we prove that the proposed is simple but efficient for moving object detection in parking lots.

Keywords: moving object detection, dynamic scene, optical flow, pyramidal optical flow

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