Search results for: segmentation preference

Authors: Nicholas Freer

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Rhythmic complexity in progressive metal is a developing area of analysis, particularly the interpretation of hyper-metric time spans as hierarchically significant rhythmic units of compositional organisation (Pieslak 2007, Charupakorn 2012, Capuzzo 2018, Calder 2018, Lucas 2018, Hannan 2020). This paper adds to this developing area by considering the relationships between the concepts of tactus, metric imposition, polymeter and rhythmic parallax in the Meshuggah composition “Do Not Look Down”. By considering an architectonic rhythmic framework within “Do Not Look Down” as the controlling organisation mechanism, an exploration of the interaction between distinct rhythmic layers and the composition’s formal segmentation and harmony (as riffs), reveals a pervasive structural misalignment between these elements. By exhibiting how Meshuggah’s manipulations of rhythmic complexities deliberately blur structural boundaries, creating misalignments in a flat approach to temporal partitioning (Nieto 2014), rhythmic characteristics of Meshuggah and the genre of Djent are exposed.

Keywords: hypermeter, rhythmic parallax, meshuggah, temporal partitioning

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Authors: Cut Maisyarah Karyati, Aries Muslim, Sulardi

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Digital image processing techniques to obtain detailed information from an image have been used in various fields, including in civil engineering, where the use of solid beam profiles in buildings and bridges has often been encountered since the early development of beams. Along with this development, the founded castellated beam profiles began to be more diverse in shape, such as the shape of a hexagon, triangle, pentagon, circle, ellipse and oval that could be a practical solution in optimizing a construction because of its characteristics. The purpose of this research is to create a computer application to edge detect the profile of various shapes of the castella beams hole. The digital image segmentation method has been used to obtain the grayscale images and represented in 2D and 3D formats. This application has been successfully made according to the desired function, which is to provide information on the type of castella beam hole.

Keywords: digital image, image processing, edge detection, grayscale, castella beams

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Authors: Mohammad Shokoohi-Yekta, Hamid Mirebrahim

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A body of research has been devoted to investigating the preferences of computer programmers. These researches used various questionnaires to find out what programming language is most popular among programmers. The problem with such research is that the programmers are usually familiar with only a few languages; therefore, disregarding a number of other languages which might have characteristics that match their preferences more closely. To overcome such a problem, we decided to investigate the preferences of programmers in regards to the characteristics of languages, which help us to discover the languages that include the most characteristics preferred by the users. We conducted a user study to measure the preferences of programmers on different characteristics of programming languages and then tried to compare existing languages in the areas of application, Web and system programming. Overall, the results of our study indicated that the Ruby programming language has the highest preference score in the two areas of application and Web, and C++ has the highest score in the system area. The results of our study can also help programming language designers know the characteristics they should consider when developing new programming languages in order to attract more programmers.

Keywords: object orientation, programming language design, programmers' preferences, characteristic

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Authors: Yixuan Wang, A. C. Y. Wong, J. M. Y. Chiu, S. G. Cheung

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After being released into the ocean, microplastics (MPs) are quickly colonized by microbes. The biofilm that forms on MPs alters their characteristics and perplexes users, including filter-feeders, some of whom choose to eat MPs that have biofilm. It has been proposed that filter feeders like mussels and other bivalves could serve as bioindicators of MP pollution. Mussels are considered selective feeders with particle sorting capability. Two sizes (27-32 µm and 90-106 µm), shapes (microspheres and microfibers), and types (polyethylene, polystyrene and polyester) of MPs were available for the green mussel, Perna viridis, at three concentrations (100 P/ml, 1000 P/ml and 10,000 P/ml). These MPs were incubated in the sea for 0, 3 or 14 days for biofilm development. The presence of the biofilm significantly affected the ingestion of MPs, and the mussels preferred MPs with biofilm, with a higher preference observed for biofilm with a longer incubation period. Additionally, the ingestion rate varied with the interaction between the concentration, size and form of MPs. The findings are discussed in relation to the possibility that mussels serve as MP bioindicators.

Keywords: marine miroplastics, biofilm, bioindicator, green mussel perna viridis

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Authors: Dalwinder Singh, Amandeep Verma, Manpreet Kaur, Birmohan Singh

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The detection of pre-cancerous changes using a Pap smear test of cervical cell is the important step for the early diagnosis of cervical cancer. The Pap smear test consists of a sample of human cells taken from the cervix which are analysed to detect cancerous and pre-cancerous stage of the given subject. The manual analysis of these cells is labor intensive and time consuming process which relies on expert cytotechnologist. In this paper, a computer assisted system for the automated analysis of the cervical cells has been proposed. We propose a morphology based approach to the nucleus detection and segmentation of the cytoplasmic region of the given single or multiple overlapped cell. Further, various texture and region based features are calculated from these cells to classify these into normal and abnormal cell. Experimental results on public available dataset show that our system has achieved satisfactory success rate.

Keywords: cervical cancer, cervical tissue, mathematical morphology, texture features

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Authors: Parham Bakhtiari

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Musical compositions are typically examined from various perspectives, with a focus on elements such as melody, harmony, and rhythm. This study provides a comprehensive analysis of tempo indications, segmentations, and musical ideas in Wolfgang Amadeus Mozart's piano sonatas, highlighting the intricate relationship between these elements and their contribution to the overall interpretative landscape of his works. Through a detailed examination of select sonatas, the research categorizes tempo markings and explores their implications for performance practice, emphasizing how Mozart's choices reflect his compositional intentions and the stylistic conventions of the Classical era. Additionally, the segmentation of musical phrases is analyzed to reveal patterns of thematic development and transition, demonstrating how Mozart employs structural techniques to enhance expressive depth. By synthesizing these aspects, the paper aims to offer insights into the complexities of Mozart's musical language, encouraging a deeper appreciation of his sonatas both in scholarly discourse and practical performance.

Keywords: music, Mozart, piano, tempo, sonata

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Authors: Helene Martin, Solmaz Boroomandi Barati, Jean-Charles Pinoli, Stephane Valette, Yann Gavet

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In the present work we developed an image processing algorithm to measure water droplets characteristics during dropwise condensation on pillared surfaces. The main problem in this process is the similarity between shape and size of water droplets and the pillars. The developed method divides droplets into four main groups based on their size and applies the corresponding algorithm to segment each group. These algorithms generate binary images of droplets based on both their geometrical and intensity properties. The information related to droplets evolution during time including mean radius and drops number per unit area are then extracted from the binary images. The developed image processing algorithm is verified using manual detection and applied to two different sets of images corresponding to two kinds of pillared surfaces.

Keywords: dropwise condensation, textured surface, image processing, watershed

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Authors: Chiu-Pin Wei

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This research aims to explore the impact of music preferences on the emotional well-being of military academy students, recognizing the potential long-term implications for their high-stress careers post-graduation. Given the significance of positive emotion regulation in military personnel, this study focuses on understanding the types of music preferred by military cadets and analyzing how these preferences correlate with their emotional states. The study employs a quantitative approach, utilizing the Music Category Scale and Mood Scale to collect data. Statistical tools, such as Statistical Product and Service Solutions (SPSS), are employed for inferential analysis, including t-tests for emotional responses to instrumental and vocal music, one-way variance analysis for different demographic factors (grades, genders, and music listening frequencies), and Pearson's correlation to examine the relationship between music preferences and moods of military students.

Keywords: music preference, emotional regulation, military academic students, SPASS

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Authors: Asmit Neupane, Narayan Prasad Gautam, Prabin Bhusal

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Indian pangolin, locally called as ‘Salak’, ‘Sal machha’, ‘Pakho machha’, is a globally endangered species, nationally categorized as a critically endangered species, protected under the National Parks and Wildlife Conservation (NPWC) Act 1973 and appended in Appendix I of CITES. Indian pangolins occur in the tropical areas of Terai region and Chure foothills of eastern Nepal, and India, Bangladesh, Pakistan, and Sri Lanka. They utilize a wide range of habitats, including primary and secondary tropical forest, limestone forest, bamboo forest, grassland, and agricultural lands. So, in regard to this fact, this research is aimed to provide detailed information regarding the current distribution pattern, status, habitat preference, prevailing threats and attitude of local people towards species conservation in Madhesh Province, Nepal. The study was conducted in four CFs, two from Bara district and two from Dhanusha district. The study area comprised of Churia range and foothills with tropical and sub-tropical vegetation. A total of 24 transects were established, each of 500*50 m2, where indirect signs of Indian pangolin, including active/old burrows, pugmarks and scratches, were found. Altogether 93 burrows were found, where only 20 were active burrows. Similarly, a vegetation survey and social survey was also conducted. The data was analyzed using Stata 16 and SPSS software. Distance from settlement, ground cover, aspect, presence/absence of ants/termites and human disturbance were the important habitat parameters having statistically significant relationship with the distribution of Indian pangolin in the area. The species was found to prefer an elevation of 360 to 540m, 0-15º slope, red soil, North-east aspect, moderate crown and ground cover, without fire and rocks, vicinity of water, roads, settlement, Sal dominated forest and minimum disturbed by human activities. Similarly, the attitude of local people towards Indian pangolin conservation was found to be significantly different with respect to age, sex and education level. The study concludes that majority of active burrows were found in Churia hills, which indicates that Indian pangolin population is gradually moving uphill towards higher elevation as hilly area supports better prey availability and also less human disturbance. Further studies are required to investigate microhabitat preferences, seasonal variability and impacts of climate change on the distribution, habitat and prey availability of Indian pangolin for the sustainable conservation of this species.

Keywords: conservation, IUCN red list, local participation, small mammal, status, threats

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Authors: Mi Ju Choi

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This study investigated the perception of gaming tourists toward Macau and developed a typology of gaming tourists. The 1,497 responses from tourists in Macau were collected through convenience sampling method. The dimensions of multi-culture, convenience, economy, gaming, and unsafety, were subsequently extracted as the factors of perception of gaming tourists in Macau. Cluster analysis was performed using the delineated factors (perception of tourists on Macau). Four heterogonous groups were generated, namely, gaming lovers (n = 467, 31.2%), exotic lovers (n = 509, 34.0%), reasonable budget seekers (n = 269, 18.0%), and convenience seekers (n = 252, 16.8%). Further analysis was performed to investigate any difference in gaming behavior and tourist activities. The findings are expected to contribute to the efforts of destination marketing organizations (DMOs) in establishing effective business strategies, provide a profile of gaming tourists in certain market segments, and assist DMOs and casino managers in establishing more effective marketing strategies for target markets.

Keywords: destination image, gaming tourists, Macau, segmentation

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Authors: Renuka Mahadevan, Sharon Chang

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This exploratory study is based on potential cruisers’ monetary valuation of cruise attributes. Using choice experiment, monetary trade-offs between four different cruise attributes are examined with Australians as a case study. We found 50% of the sample valued variety of onboard cruise activities the least while 30% were willing to pay A$87 for cruise-organised activities per day, and the remaining 20% regarded an ocean view to be most valuable at A$125. Latent class modelling was then applied and results revealed that potential cruisers’ valuation of the attributes can be used to segment the market into adventurers, budget conscious and comfort lovers. Evidence showed that socio demographics are not as insightful as lifestyle preferences in developing cruise packages and pricing that would appeal to potential cruisers. Marketing also needs to counter the mindset of potential cruisers’ belief that cruises are often costly and that cruising can be done later in life.

Keywords: latent class modelling, choice experiment, potential cruisers, market segmentation, willingness to pay

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Authors: Lien Fa Lin, Yung Ming Li, Hsin Chen Hsieh

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The rise of smartphones brings new concept So-Lo-Mo (social-local-mobile) in mobile commerce area in recent years. However, current So-Lo-Mo services only focus on individual users but not a group of users, and the development of group commerce is not enough to satisfy the demand of real-time group buying and less to think about the social relationship between customers. In this research, we integrate mobile intelligence with group commerce and consider customers' preference, real-time context, and social influence as components in the mechanism. With the support of this mechanism, customers are able to gather near customers with the same potential purchase willingness through mobile devices when he/she wants to purchase products or services to have a real-time group-buying. By matching the demand and supply of mobile group-buying market, this research improves the business value of mobile commerce and group commerce further.

Keywords: group formation, group commerce, mobile commerce, So-Lo-Mo, social influence

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Authors: Kazuko Sakamoto

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It is difficult to explain the factor of design preference only in culture or a geographical environment. It is necessary to turn one's eyes also to the factor in an individual. The purpose of this research is to clarify design potential which is inherent in consumers. Design potential is the consciousness and interpretation to an individual design. That is, it catches quantitatively the preparatory state which faces design. For example, a mobile phone differs in designs, such as a color and a form, by the country or the area. It is considered because a regional consumer taste exists. The root is design potential. This consists of design participation, design knowledge, and design sensitivity. Having focused this time is by design sensitivity, and international comparison of the Netherlands, Bangladesh, China, and Japan was performed. As a result, very interesting finding has been derived. For example, although Bangladesh caught the similarity of goods by the color, other three nations were caught in the form. Moreover, although the Netherlands, Bangladesh, and China liked symmetry, only Japan liked asymmetry. This shows that history and a cultural background have had big influence to the design.

Keywords: design-potential, cultural difference, form characteristic, product development

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Authors: Armita Ghobadi, Samantha Emerson, Seyda Ozcaliskan

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Being a bilingual involves mastery of both speech and gesture patterns in a second language (L2). We know from earlier work in first language (L1) production contexts that speech and co-speech gesture form a tightly integrated system: co-speech gesture mirrors the patterns observed in speech, suggesting an online effect of language on nonverbal representation of events in gesture during the act of speaking (i.e., “thinking for speaking”). Relatively less is known about the online effect of language on gesture in bilinguals speaking structurally different languages. The few existing studies—mostly with small sample sizes—suggests inconclusive findings: some show greater achievement of L2 patterns in gesture with more advanced L2 speech production, while others show preferences for L1 gesture patterns even in advanced bilinguals. In this study, we focus on advanced bilingual speakers of two structurally different languages (Spanish L1 with English L2) in comparison to L1 English speakers. We ask whether bilingual speakers will follow target L2 patterns not only in speech but also in gesture, or alternatively, follow L2 patterns in speech but resort to L1 patterns in gesture. We examined this question by studying speech and gestures produced by 23 advanced adult Spanish (L1)-English (L2) bilinguals (Mage=22; SD=7) and 23 monolingual English speakers (Mage=20; SD=2). Participants were shown 16 animated motion event scenes that included distinct manner and path components (e.g., "run over the bridge"). We recorded and transcribed all participant responses for speech and segmented it into sentence units that included at least one motion verb and its associated arguments. We also coded all gestures that accompanied each sentence unit. We focused on motion event descriptions as it shows strong crosslinguistic differences in the packaging of motion elements in speech and co-speech gesture in first language production contexts. English speakers synthesize manner and path into a single clause or gesture (he runs over the bridge; running fingers forward), while Spanish speakers express each component separately (manner-only: el corre=he is running; circle arms next to body conveying running; path-only: el cruza el puente=he crosses the bridge; trace finger forward conveying trajectory). We tallied all responses by group and packaging type, separately for speech and co-speech gesture. Our preliminary results (n=4/group) showed that productions in English L1 and Spanish L1 differed, with greater preference for conflated packaging in L1 English and separated packaging in L1 Spanish—a pattern that was also largely evident in co-speech gesture. Bilinguals’ production in L2 English, however, followed the patterns of the target language in speech—with greater preference for conflated packaging—but not in gesture. Bilinguals used separated and conflated strategies in gesture in roughly similar rates in their L2 English, showing an effect of both L1 and L2 on co-speech gesture. Our results suggest that online production of L2 language has more limited effects on L2 gestures and that mastery of native-like patterns in L2 gesture might take longer than native-like L2 speech patterns.

Keywords: bilingualism, cross-linguistic variation, gesture, second language acquisition, thinking for speaking hypothesis

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Authors: Mousa Bani Baker, Raed Abendeh, Zaidoon Abu Salem, Hesham Ahmad

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This research paper was commissioned to discuss the Jordanian marble, which is a non-foliated metamorphic rock composed of recrystallized carbonate minerals, most commonly calcite or dolomite. Geologists use the term "marble" to refer to metamorphosed limestone; however, stonemasons use the term more broadly to encompass unmetamorphised limestone. Marble is commonly used for sculpture and as a building material. The marble has many uses; one of them is using the white marble that has been prized for its use in sculptures since classical times. This preference has to do with its softness, relative isotropy and homogeneity, and a relative resistance to shattering. Another use of it is the construction marble which is “a stone which is composed of calcite, dolomite or serpentine which is capable of taking a polish” Marble Institute of America. This report focuses most about the marble in Jordan and its properties: rock definition, physical properties, the marble occurrences in Jordan, types of Jordanian marble and their prices and test done on this marble.

Keywords: marble, metamorphic, non-foliated, compressive strength, recrystallized, Moh’s hardness, abrasion, absorption, modulus of rupture, porosity

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Authors: Suparman

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Piecewise linear regression models are very flexible models for modeling the data. If the piecewise linear regression models are matched against the data, then the parameters are generally not known. This paper studies the problem of parameter estimation of piecewise linear regression models. The method used to estimate the parameters of picewise linear regression models is Bayesian method. But the Bayes estimator can not be found analytically. To overcome these problems, the reversible jump MCMC algorithm is proposed. Reversible jump MCMC algorithm generates the Markov chain converges to the limit distribution of the posterior distribution of the parameters of picewise linear regression models. The resulting Markov chain is used to calculate the Bayes estimator for the parameters of picewise linear regression models.

Keywords: regression, piecewise, Bayesian, reversible Jump MCMC

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Authors: Zaid Jamal Saeed Almahmoud

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Smart Grid is the vision of the future power system that combines advanced monitoring and communication technologies to provide energy in a smart, efficient, and user-friendly manner. This proposal considers a demand response model in the Smart Grid based on utility maximization. Given a set of consumers with conflicting preferences in terms of consumption and a utility company that aims to minimize the peak demand and match demand to supply, we study the problem of aggregating these preferences while modelling the problem as a game. We also investigate whether an equilibrium can be reached to maximize the social benefit. Based on such equilibrium, we propose a dynamic pricing heuristic that computes the equilibrium and sets the prices accordingly. The developed approach was analysed theoretically and evaluated experimentally using real appliances data. The results show that our proposed approach achieves a substantial reduction in the overall energy consumption.

Keywords: heuristics, smart grid, aggregation, mechanism design, equilibrium

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Authors: Zhongzhen Luo, Saeid Habibi, Martin v. Mohrenschildt

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Self-driving vehicle require a high level of situational awareness in order to maneuver safely when driving in real world condition. This paper presents a LiDAR based real time perception system that is able to process sensor raw data for multiple target detection and tracking in dynamic environment. The proposed algorithm is nonparametric and deterministic that is no assumptions and priori knowledge are needed from the input data and no initializations are required. Additionally, the proposed method is working on the three-dimensional data directly generated by LiDAR while not scarifying the rich information contained in the domain of 3D. Moreover, a fast and efficient for real time clustering algorithm is applied based on a radially bounded nearest neighbor (RBNN). Hungarian algorithm procedure and adaptive Kalman filtering are used for data association and tracking algorithm. The proposed algorithm is able to run in real time with average run time of 70ms per frame.

Keywords: lidar, segmentation, clustering, tracking

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Authors: Madushani Rodrigo, Banuka Athuraliya

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In today's world of medical diagnosis and prediction, machine learning stands out as a strong tool, transforming old ways of caring for health. This study analyzes the use of machine learning in the specialized domain of sports medicine, with a focus on the timely and accurate detection of bone fractures in cricket athletes. Failure to identify bone fractures in real time can result in malunion or non-union conditions. To ensure proper treatment and enhance the bone healing process, accurately identifying fracture locations and types is necessary. When interpreting X-ray images, it relies on the expertise and experience of medical professionals in the identification process. Sometimes, radiographic images are of low quality, leading to potential issues. Therefore, it is necessary to have a proper approach to accurately localize and classify fractures in real time. The research has revealed that the optimal approach needs to address the stated problem and employ appropriate radiographic image processing techniques and object detection algorithms. These algorithms should effectively localize and accurately classify all types of fractures with high precision and in a timely manner. In order to overcome the challenges of misidentifying fractures, a distinct model for fracture localization and classification has been implemented. The research also incorporates radiographic image enhancement and preprocessing techniques to overcome the limitations posed by low-quality images. A classification ensemble model has been implemented using ResNet18 and VGG16. In parallel, a fracture segmentation model has been implemented using the enhanced U-Net architecture. Combining the results of these two implemented models, the FracXpert system can accurately localize exact fracture locations along with fracture types from the available 12 different types of fracture patterns, which include avulsion, comminuted, compressed, dislocation, greenstick, hairline, impacted, intraarticular, longitudinal, oblique, pathological, and spiral. This system will generate a confidence score level indicating the degree of confidence in the predicted result. Using ResNet18 and VGG16 architectures, the implemented fracture segmentation model, based on the U-Net architecture, achieved a high accuracy level of 99.94%, demonstrating its precision in identifying fracture locations. Simultaneously, the classification ensemble model achieved an accuracy of 81.0%, showcasing its ability to categorize various fracture patterns, which is instrumental in the fracture treatment process. In conclusion, FracXpert has become a promising ML application in sports medicine, demonstrating its potential to revolutionize fracture detection processes. By leveraging the power of ML algorithms, this study contributes to the advancement of diagnostic capabilities in cricket athlete healthcare, ensuring timely and accurate identification of bone fractures for the best treatment outcomes.

Keywords: multiclass classification, object detection, ResNet18, U-Net, VGG16

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Authors: Marcos Bosques-Perez, Walter Izquierdo, Harold Martin, Liangdon Deng, Josue Rodriguez, Thony Yan, Mercedes Cabrerizo, Armando Barreto, Naphtali Rishe, Malek Adjouadi

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Aerial imagery is a powerful tool when it comes to analyzing temporal changes in ecosystems and extracting valuable information from the observed scene. It allows us to identify and assess various elements such as objects, structures, textures, waterways, and shadows. To extract meaningful information, multispectral cameras capture data across different wavelength bands of the electromagnetic spectrum. In this study, the collected multispectral aerial images were subjected to principal component analysis (PCA) to identify independent and uncorrelated components or features that extend beyond the visible spectrum captured in standard RGB images. The results demonstrate that these principal components contain unique characteristics specific to certain wavebands, enabling effective object identification and image segmentation.

Keywords: big data, image processing, multispectral, principal component analysis

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Authors: P. Chonsin, N. Neelapaichit, N. Piaseu

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This household survey aimed to describe food behaviors and nutritional status of households in suburb nearby Bangkok, Thailand. Through convenience sampling, sample included 187 food providers from 125 households in three communities. Data were collected by structured interview and nutritional assessment. Results revealed that majority of the sample were female (68.4 %), aged between 18 to 91 years. The households selected raw foods concerning quality as the first priority (46.5%), cooking for their family members as 91.2%, using seasonings as 71.2%. The most favorite tastes were sweet (19.8%), salty (20.3%), and fatty (1.6%). Food related health problems were hypertension (40.1%), diabetes (26.7%), and dyslipidemia (19.3%). Approximately half of the overall samples (55.1%) and the sample with hypertension (84.5%) had excessive body mass index (BMI). Moreover, one-fourth of the sample with hypertension (25.3%) had salty food preference. Results suggest approaches to promote behavioral modification for sodium reduction particularly in food providers of households with hypertension and excessive BMI.

Keywords: food behavior, nutrition status, household, suburb

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Authors: Samiah Alammari, Nassim Ammour

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When providing a massive number of tasks successively to a deep learning process, a good performance of the model requires preserving the previous tasks data to retrain the model for each upcoming classification. Otherwise, the model performs poorly due to the catastrophic forgetting phenomenon. To overcome this shortcoming, we developed a successful continual learning deep model for remote sensing hyperspectral image regions classification. The proposed neural network architecture encapsulates two trainable subnetworks. The first module adapts its weights by minimizing the discrimination error between the land-cover classes during the new task learning, and the second module tries to learn how to replicate the data of the previous tasks by discovering the latent data structure of the new task dataset. We conduct experiments on HSI dataset Indian Pines. The results confirm the capability of the proposed method.

Keywords: continual learning, data reconstruction, remote sensing, hyperspectral image segmentation

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Authors: Ali Mithad Emre

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In military aviation, the use of flight simulators has proliferated recently in order to train fifth generation fighter pilots. With these simulators, pilots can carry out real-time flights resulting in seeing their faults and can perform emergency drills prior to real flights. Since we cannot risk losing the aircraft and the pilot himself/herself in the flight training process, flight simulators are of great importance to adapt the fighter pilots competently to real flights aboard the fifth generation aircraft. The real flights are impossible to simulate thoroughly on the ground. To some extent, the fixed-based simulators may assist the pilot to steer aircraft technically and visually but flight simulators can’t trick the pilot’s vestibular, sensory, and perceptual systems without motion platforms. This paper discusses the benefits of motion simulators for fifth generation fighter pilots’ training in preference to the fixed-based counterparts by analyzing their pros and cons.

Keywords: military, pilot, sickness, simulator

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Authors: Gelila Tamyalew, Asres Abitie

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Community Pharmacists (CPs) have a significant part in consumer choice in the rational use of LMPPs. The opinion of pharmacists regarding branded and generic medications can offer a perception of the potential obstacles that might have to be overcome to advance generic medicine utilization. Many factors affect CPs' attitudes negatively toward LMPPs. Therefore, the current study assessed factors that can affect CPs' attitudes toward LMPPs. In the regression analysis of variables, three variables were associated with CPs' attitudes toward LMPPs. These are; maximum educational status, professional status, and year of experience in community pharmacy practice. Moreover, lack of belief in LMPPs, substitution agreement with the prescriber, cost-effectiveness of LMPPs, and consumer preference/demand were the most influencing reasons for the selection of LMPPs. In conclusion, the attitude of CPs seems suboptimal that requires an intervention to optimize LMPP utilization.

Keywords: locally manufactured pharmaceutical products, attitude, community pharmacist, Ethiopia

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Authors: Cesar Hernández, Diego Giral, Ingrid Páez

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This article proposes a hybrid algorithm for spectrum allocation in cognitive radio networks based on the algorithms Analytical Hierarchical Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to improve the performance of the spectrum mobility of secondary users in cognitive radio networks. To calculate the level of performance of the proposed algorithm a comparative analysis between the proposed AHP-TOPSIS, Grey Relational Analysis (GRA) and Multiplicative Exponent Weighting (MEW) algorithm is performed. Four evaluation metrics is used. These metrics are the accumulative average of failed handoffs, the accumulative average of handoffs performed, the accumulative average of transmission bandwidth, and the accumulative average of the transmission delay. The results of the comparison show that AHP-TOPSIS Algorithm provides 2.4 times better performance compared to a GRA Algorithm and, 1.5 times better than the MEW Algorithm.

Keywords: cognitive radio, decision making, hybrid algorithm, spectrum handoff, wireless networks

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Authors: Hao-Hsi Tseng, Hsin-Yun Lee

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The Most Advantageous Tender (MAT) has been criticized for its susceptibility to dictatorial situations and for its processing of same score, same rank issues. This study applies the four criteria from Arrow's Impossibility Theorem to construct a mechanism for revealing illegitimate scores in scoring methods. While commonly be used to improve on problems resulting from extreme scores, ranking methods hide significant defects, adversely affecting selection fairness. To address these shortcomings, this study relies mainly on the overall evaluated score method, using standardized scores plus normal cumulative distribution function conversion to calculate the evaluation of vender preference. This allows for free score evaluations, which reduces the influence of dictatorial behavior and avoiding same score, same rank issues. Large-scale simulations confirm that this method outperforms currently used methods using the Impossibility Theorem.

Keywords: Arrow’s impossibility theorem, cumulative normal distribution function, most advantageous tender, scoring method

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Authors: C. Rana, S. K. Jain

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The enormous amount of Web data has challenged its usage in efficient manner in the past few years. As such, a range of techniques are applied to tackle this problem; prominent among them is personalization and recommender system. In fact, these are the tools that assist user in finding relevant information of web. Most of the e-commerce websites are applying such tools in one way or the other. In the past decade, a large number of recommendation algorithms have been proposed to tackle such problems. However, there have not been much research in the evaluation criteria for these algorithms. As such, the traditional accuracy and classification metrics are still used for the evaluation purpose that provides a static view. This paper studies how the evolution of user preference over a period of time can be mapped in a recommender system using a new evaluation methodology that explicitly using time dimension. We have also presented different types of experimental set up that are generally used for recommender system evaluation. Furthermore, an overview of major accuracy metrics and metrics that go beyond the scope of accuracy as researched in the past few years is also discussed in detail.

Keywords: collaborative filtering, data mining, evolutionary, clustering, algorithm, recommender systems

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Authors: Katarzyna Kamińska

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When thinking about custodial arrangements after divorce or separation, there has been a shift from sole custody, particularly maternal preference, to joint physical custody. In many Western countries, an increasing of children with separated parents have joint physical custody, which is believed to be in the best interests of the child, as children can maintain personal relations and direct contact with both parents on a regular basis. The aim of the article is to examine joint physical custody, both from the perspective of the binding legal instruments that are relevant to joint physical custody, the Principles of European Family Law drafted by the CEFL, as well as the international research on this matter. The thesis underlying this paper is that joint physical custody is in itself neither good nor bad, and it depends on how the arrangements are managed by the parents. The paper includes a reflection on joint physical custody in the face of the COVID-19 crisis. The results indicate that in normal circumstances, joint physical custody demands broad communication, and now it times of crisis, we need over-communication about children and plans. Only a very tight and coordinated co-parenting plan make the whole family safer.

Keywords: joint physical custody, co-parenting, child welfare, COVID-19

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Authors: Earl Joy H. Ausa, Lianna Rozl Brosas, Niema T. Floro, Jycyl Joice R. Medina, Nejie A. Millarada

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This study examines the demographic and personality profiles of pre-service teachers at Rizal Technological University, Boni Campus. The participants consisted of 212 pre-service teachers from the College of Education with majors in various subjects. The majority of respondents were female (74.88%), and the average age of participants was 22. Using the NEO PI-R framework, the study assessed the personality traits of pre-service teachers. The results showed that pre-service teachers displayed average levels of neuroticism, extraversion, openness, agreeableness, and conscientiousness. This suggests that they possess a balanced combination of traits that are conducive to effective teaching, such as moderate emotional stability, a balanced preference for social interactions, curiosity, good interpersonal skills, and a strong work ethic. The personality enhancement program could also benefit the pre-service teachers. In conclusion, this study provides valuable insights into the demographic and personality characteristics of pre-service teachers.

Keywords: personality traits, neo PI- R, pre-service teachers, five-factor theory

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Authors: Ali Dulla

Abstract:

This paper introduces a new dataset (and the methodology used to generate it) based on a wide range of historical Arabic documents containing clean data simple and homogeneous-page layouts. The experiments are implemented on printed and handwritten documents obtained respectively from some important libraries such as Qatar Digital Library, the British Library and the Library of Congress. We have gathered and commented on 150 archival document images from different locations and time periods. It is based on different documents from the 17th-19th century. The dataset comprises differing page layouts and degradations that challenge text line segmentation methods. Ground truth is produced using the Aletheia tool by PRImA and stored in an XML representation, in the PAGE (Page Analysis and Ground truth Elements) format. The dataset presented will be easily available to researchers world-wide for research into the obstacles facing various historical Arabic documents such as geometric correction of historical Arabic documents.

Keywords: dataset production, ground truth production, historical documents, arbitrary warping, geometric correction

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