Search results for: pose normalization

Authors: Thu Le Thi Bao

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Industrial parks have both active roles in promoting economic development and source of appearance of boarding houses and slums in the adjacent area, lacking infrastructure, causing many social evils. The context of the recent pandemic and climate change on a global scale pose issues that need to be resolved for sustainable development. Ho Chi Minh City aims to develop housing for migrant workers to stabilize human resources and, at the same time, solve problems of social evils caused by poor living conditions. The paper focuses on the content of renovating existing industrial parks and worker accommodation in Ho Chi Minh City to propose appropriate models, contributing to the goal of urban embellishment and solutions for industrial parks to adapt to abnormal impact conditions such as pandemics, climate change, crises.

Keywords: industrial park, social housing, accommodation, distribution center

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Authors: Rahil Saeedi

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The imbalance in truck parking supply and demand can create important safety issues for truck drivers and the public. Research has shown that breaks at specific intervals can increase drivers’ alertness by reducing the monotony of the task. However, if fatigued truck drivers are unable to find a safe parking spot for rest, they may continue to drive or choose to park at remote and insecure areas or undesignated locations. All of these situations pose serious safety and security risks to truck drivers and other roadway users. This study uses 5-year truck crash data in Ohio to develop and test a framework for identifying crashes that happen as a result of imbalances in truck parking supply and demand. The societal impacts of these crashes are then interpreted as monetary values, calculated using the costs associated with various crash severity levels.

Keywords: truck parking, road safety, crash data, geofencing, driver fatigue, undesignated parking

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Authors: A. Kavya Sri, K. Sai Vineela, R. Vanitha, S. Rohith

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Large pieces of ice that break from the glaciers are known as icebergs. The threat that icebergs pose to navigation, production of offshore oil and gas services, and underwater pipelines makes their detection crucial. In this project, an automated iceberg tracking method using deep learning techniques and satellite images of icebergs is to be developed. With a temporal resolution of 12 days and a spatial resolution of 20 m, Sentinel-1 (SAR) images can be used to track iceberg drift over the Southern Ocean. In contrast to multispectral images, SAR images are used for analysis in meteorological conditions. This project develops a web-based graphical user interface to detect and track icebergs using sentinel-1 images. To track the movement of the icebergs by using temporal images based on their latitude and longitude values and by comparing the center and area of all detected icebergs. Testing the accuracy is done by precision and recall measures.

Keywords: synthetic aperture radar (SAR), icebergs, deep learning, spatial resolution, temporal resolution

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Authors: Sheldon McCall, Miao Yu, Liyun Gong, Shigang Yue, Stefanos Kollias

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Falls are a significant health concern for older adults globally, and prompt identification is critical to providing necessary healthcare support. Our study proposes a new fall detection method using computer vision based on modern deep learning techniques. Our approach involves training a trans- former model on a large 2D pose dataset for general action recognition, followed by transfer learning. Specifically, we freeze the first few layers of the trained transformer model and train only the last two layers for fall detection. Our experimental results demonstrate that our proposed method outperforms both classical machine learning and deep learning approaches in fall/non-fall classification. Overall, our study suggests that our proposed methodology could be a valuable tool for identifying falls.

Keywords: healthcare, fall detection, transformer, transfer learning

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Authors: Bamidele Samson Alobalorun, Ifedotun Roseline Idowu

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Biometrics technologies apply the human body parts for their unique and reliable identification based on physiological traits. The iris recognition system is a biometric–based method for identification. The human iris has some discriminating characteristics which provide efficiency to the method. In order to achieve this efficiency, there is a need for feature extraction of the distinct features from the human iris in order to generate accurate authentication of persons. In this study, an approach for an iris recognition system using 2D Gabor for feature extraction is applied to iris templates. The 2D Gabor filter formulated the patterns that were used for training and equally sent to the hamming distance matching technique for recognition. A comparison of results is presented using two iris image subjects of different matching indices of 1,2,3,4,5 filter based on the CASIA iris image database. By comparing the two subject results, the actual computational time of the developed models, which is measured in terms of training and average testing time in processing the hamming distance classifier, is found with best recognition accuracy of 96.11% after capturing the iris localization or segmentation using the Daughman’s Integro-differential, the normalization is confined to the Daugman’s rubber sheet model.

Keywords: Daugman rubber sheet, feature extraction, Hamming distance, iris recognition system, 2D Gabor wavelet transform

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Authors: Ismahafezi Ismail, Mohd Shahrizal Sunar

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The motion of a realistic 3D humanoid character is very important especially for the industries developing computer animations and games. However, this type of motion is seen with a very complex dimensional data as well as body position, orientation, and joint rotation. Integrated Style Motion Editor (ISME), on the other hand, is a method used to alter the 3D humanoid motion capture data utilised in computer animation and games development. Therefore, this study was carried out with the purpose of demonstrating a method that is able to manipulate and deform different motion styles by integrating Key Pose Deformation Technique and Trajectory Control Technique. This motion editing method allows the user to generate new motions from the original motion capture data using a simple interface control. Unlike the previous method, our method produces a realistic humanoid motion style in real time.

Keywords: computer animation, humanoid motion, motion capture, motion editing

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Authors: Plessen Mogens Graf

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Within the context of multivariate time series segmentation, this paper proposes a method inspired by a posteriori optimal trading. After a normalization step, time series are treated channelwise as surrogate stock prices that can be traded optimally a posteriori in a virtual portfolio holding either stock or cash. Linear transaction costs are interpreted as hyperparameters for noise filtering. Trading signals, as well as trading signals obtained on the reversed time series, are used for unsupervised channelwise labeling before a consensus over all channels is reached that determines the final segmentation time instants. The method is model-free such that no model prescriptions for segments are made. Benefits of proposed approach include simplicity, computational efficiency, and adaptability to a wide range of different shapes of time series. Performance is demonstrated on synthetic and real-world data, including a large-scale dataset comprising a multivariate time series of dimension 1000 and length 2709. Proposed method is compared to a popular model-based bottom-up approach fitting piecewise affine models and to a recent model-based top-down approach fitting Gaussian models and found to be consistently faster while producing more intuitive results in the sense of segmenting time series at peaks and valleys.

Keywords: time series segmentation, model-free, trading-inspired, multivariate data

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Authors: Mustapha Kamel Mihoubi, Reda Madi

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The problem of natural disasters in general and flooding in particular is a topic which marks a memorable action in the world and specifically in cities and large urban areas. Torrential floods and faster flows pose a major problem in urban area. Indeed, a better management of risks of floods becomes a growing necessity that must mobilize technical and scientific means to curb the adverse consequences of this phenomenon, especially in the Saharan cities in arid climate. The aim of this study is to deploy a basic calculation approach based on a hydrologic and hydraulic quantification for locating the black spots in urban areas generated by the flooding and to locate the areas that are vulnerable to flooding. The principle of flooding method is applied to the city of Ghardaia to identify vulnerable areas to inundation and to establish maps management and prevention against the risks of flooding.

Keywords: Alea, Beni Mzab, cartography, HEC-RAS, inundation, torrential, vulnerability, wadi

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Authors: Svetlana Ignatjeva, Jelena Slesareva

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The aim of the study is development and adaptation of the method to analyze and quantify the indicators characterizing the relationship between a company and its employees. Diagnostics of such indicators is one of the most complex and actual issues in psychology of labour. The offered method is based on the questionnaire; its indicators reflect cognitive, affective and connotative components of socio-psychological attitude of employees to be as efficient as possible in their professional activities. This approach allows measure not only the selected factors but also such parameters as cognitive and behavioural dissonances. Adaptation of the questionnaire includes factor structure analysis and suitability analysis of phenomena indicators measured in terms of internal consistency of individual factors. Structural validity of the questionnaire was tested by exploratory factor analysis. Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Factor analysis allows reduce dimension of the phenomena moving from the indicators to aggregative indexes and latent variables. Aggregative indexes are obtained as the sum of relevant indicators followed by standardization. The coefficient Cronbach's Alpha was used to assess the reliability-consistency of the questionnaire items. The two-step cluster analysis in the space of allocated factors allows classify employees according to their attitude to work in the company. The results of psychometric testing indicate possibility of using the developed technique for the analysis of employees’ attitude towards their work in companies and development of recommendations on their optimization.

Keywords: involved in the organization, loyalty, organizations, method

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Authors: H. Aljabli

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The research on the presence of heavy metals and bromate in drinking water is of significant scientific importance. These substances have the potential to pose risks to public health and are subject to regulatory limits outlined by the National Primary Drinking Water Regulations. Through a comprehensive analysis that includes the compilation of existing data and the collection of new data via water sampling in residential areas of Kuwait, you aim to generate maps that depict the spatial distribution of these substances. Moreover, your investigation will involve the utilization of GRAPHER software to explore correlations among different chemical parameters. By employing rigorous scientific methodologies, your research will provide valuable insights for the Ministry of Electricity and Water and the Ministry of Health. These insights can inform evidence-based decision-making, facilitate the implementation of corrective measures, and support strategic planning for future infrastructure activities.

Keywords: heavy metals, bromate, ozonation, GIS

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Authors: Hayder Shanbara, Felicite Ruddock, William Atherton, Ali Al-Rifaie

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In highways construction, Hot Mix Asphalt (HMA) is used predominantly as a paving material from many years. Around 90 percent of the world road network is laid by flexible pavements. However, there are some restrictions on paving hot mix asphalt such as immoderate greenhouse gas emission, rainy season difficulties, fuel and energy consumption and cost. Therefore, Cold Bitumen Emulsion Mixture (CBEM) is considered an alternative mix to the HMA. CBEM is the popular type of Cold Mix Asphalt (CMA). It is unheated emulsion, aggregate and filler mixtures, which can be prepared and mixed at ambient temperature. This research presents a simple and more practicable design procedure of CBEM and discusses limitations of this design. CBEM is a mixture of bitumen emulsion and aggregates that mixed and produced at ambient temperature. It is relatively easy to produce, but the design procedure that provided by Asphalt Institute (Manual Series 14 (1989)) pose some issues in its practical application.

Keywords: cold bitumen, emulsion mixture, design procedure, pavement

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Authors: Francesco Arese Visconti

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The purpose of this paper is to question the methodological challenges that practice-based research on recent Italian migrants in Switzerland can pose. The entire development of the work has moved from the theorization to the production and back in a continuous exchange which is at the base of failures and successful results. The theoretical background leads to reflect on practical solutions to produce photographic portraits in the attempt to depict the cultural identity of a specific population. Thus, a series of key points of this challenging, visual, and intimate journey are discussed and developed. While analyzing, in the first stance, the psychological challenges resulting from the encounter of the photographer, the sitter, and the spectator, the challenges of the representation of a group of people with individual photographic portraits will secondly be highlighted. The paper underlines how previous work can be precursory of subsequent research and why the inclusion of the landscape versus maintaining a neutral background has links with paintings from the Italian Renaissance.

Keywords: photography, migration, Italians, Switzerland

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Authors: Alex S. Talan

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The introduction of scientific terms for esports can directly affect the quality of the training process. This is a critically important scientific task since esports is a rapidly developing global sport that has only recently begun to receive scientific and methodological consideration. In this report, we evaluate esports from a biomechanical perspective. First, we examine the relationship between physical performance and esports gaming techniques, with consideration toward engineering more effective physical and in-game training methodologies for amateur and professional esports competitors. In addition, we advocate that applying biomechanical research methodologies has the added potential to improve physical performance and endurance in esports athletes. With the budding attention on the esports enterprise globally, scientific research into esports would benefit from standardizing terminologies and methodological approaches that are specifically tailored to assess esports training efficacy to enhance individual and team performance within the esports community.

Keywords: cybersport, esports, biomechanics, sports technique, training standards, dental occlusion, sports engineering, sitting pose

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Authors: Dongwon Lee, Sunmyeng Kim

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Underwater acoustic networks (UANs) have become a very active research area in recent years. Compared with wireless networks, UANs are characterized by the limited bandwidth, long propagation delay and high channel dynamic in acoustic modems, which pose challenges to the design of medium access control (MAC) protocol. The characteristics severely affect network performance. In this paper, we study a MS-MAC (Multi-Sender MAC) protocol in order to improve network performance. The proposed protocol exploits temporal reuse by learning the propagation delays to neighboring nodes. A source node locally calculates the transmission schedules of its neighboring nodes and itself based on the propagation delays to avoid collisions. Performance evaluation is conducted using simulation, and confirms that the proposed protocol significantly outperforms the previous protocol in terms of throughput.

Keywords: acoustic channel, MAC, temporal reuse, UAN

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Authors: Abdelhadi Nadjer

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The structure of the text to the systemic school -(glossématique-Helmslev). At the beginning of the note we have a cursory look around the concepts of general linguistics The science that studies scientific study of human language based on the description and preview the facts away from the trend of education than we gave a detailed overview the founder of systemic school and most important customers and more methods and curriculum theory and analysis they extend to all humanities, practical action each offset by a theoretical and the procedure can be analyzed through the elements that pose as another method we talked to its links with other language schools where they are based on the sharp criticism of the language before and deflected into consideration for the field of language and its erection has outside or language network and its participation in the actions (non-linguistic) and after that we started our Valglosamatik analytical structure of the text is ejected text terminal or all of the words to was put for expression. This text Negotiable divided into types in turn are divided into classes and class should not be carrying a contradiction and be inclusive. It is on the same materials as described relationships that combine language and seeks to describe their relations and identified.

Keywords: text, language schools, linguistics, human language

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Authors: Jennie Long, Marjorie Bock

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Although the professional literature related to Autism Spectrum Disorder (ASD) has focused on successful interventions and strategies, there is a lack of documentation regarding which of these methods and supports are most foundational and essential for classroom use. Specifically, literature does not define the core foundational interventions and strategies that would be elemental for educators to use with students with an ASD diagnosis. From the increase in prevalence of autism spectrum disorders, to the challenge students with ASD pose in classrooms, to the requirement to implement evidence-based practice, rises an enormous challenge in the field of education. Foundational interventions should be in place the first day the student enters the classroom. The nine interventions are foundational in nature and because of the dramatic increase in prevalence there is currently a need for classroom programs to provide the foundation of basic educational skills as well as the specialty skills specific to the area of ASD utilizing the most current research. This article presents nine evidence-based intervention categories for implementation with students on the spectrum.

Keywords: autism spectrum disorder, classroom, evidence-based, foundational

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Authors: Liu Wei-Hsien, Chuang Hsiao-Li, Huang Yen-Te, Wu Chien-Chen, Chou Geng-Ting, Tsai Ying-Chieh

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Intestinal microflora play an important role in communication along the gut-brain axis. Probiotics, defined as live bacteria or bacterial products, confer a significant health benefit to the host. Here we administered Lactobacillus plantarum PS128 (PS128) to the germ-free (GF) mouse to investigate the impact of the gut-brain axis on emotional behavior. Administration of live PS128 significantly increased the total distance traveled in the open field test; it decreased the time spent in the closed arm and increased the time spent and total entries into the open arm in the elevated plus maze. In contrast, heat-killed PS128 caused no significant changes in the GF mice. Treatment with live PS128 significantly increased levels of both serotonin and dopamine in the striatum, but not in the prefrontal cortex or hippocampus. However, live PS128 did not alter pro- or anti-inflammatory cytokine production by mitogen-stimulated splenocytes. The above data indicate that the normalization of emotional behavior correlated with monoamine neurotransmission, but not with immune activity. Our findings suggest that daily intake of the probiotic PS128 could ameliorate neuropsychiatric disorders such as anxiety and excessive psychological stress.

Keywords: dopamine, hypothalamic-pituitary-adrenal axis, intestinal microflora, serotonin

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Authors: Settana M. Abdulh, Naila A. Sadalla, Yaseen H. Taha, Howaida Elshoush

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Side channel attacks are based on side channel information, which is information that is leaked from encryption systems. This includes timing information, power consumption as well as electromagnetic or even sound leaking which can exploited by an attacker. Implementing side channel attacks are possible if and only if an attacker has access to a cryptosystem. In this case, the attacker can exploit bad implementation in software or hardware which is not controlled by encryption implementer. Thus, he/she will represent a real threat to the security system. Several countermeasures have been proposed to eliminate side channel information vulnerability.Cache timing attack is a special type of side channel attack. Here, timing information is collected and analyzed by an attacker to guess sensitive information such as encryption key or plaintext. This paper reviews the technique applied in this attack and surveys the countermeasures against it, evaluating the feasibility and usability of each. Based on this evaluation, finally we pose several recommendations about using these countermeasures.

Keywords: AES algorithm, side channel attack, cache timing attack, cache timing countermeasure

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Authors: Jingjie Li, Wenjie Hu

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Phraseological units in academic English texts have been a central focus in recent corpus linguistic research. A wide variety of phraseological units have been explored, including collocations, chunks, lexical bundles, patterns, semantic sequences, etc. This paper describes a special category of clause-level phraseological units, namely, Characteristic Sentence Stems (CSSs), with a view to describing their defining criteria and extraction method. CSSs are contiguous lexico-grammatical sequences which contain a subject-predicate structure and which are frame expressions characteristic of academic writing. The extraction of CSSs consists of six steps: Part-of-speech tagging, n-gram segmentation, structure identification, significance of occurrence calculation, text range calculation, and overlapping sequence reduction. Significance of occurrence calculation is the crux of this study. It includes the computing of both the internal association and the boundary independence of a CSS and tests the occurring significance of the CSS from both inside and outside perspectives. A new normalization algorithm is also introduced into the calculation of LocalMaxs for reducing overlapping sequences. It is argued that many sentence stems are so recurrent in academic texts that the most typical of them have become the habitual ways of making meaning in academic writing. Therefore, studies of CSSs could have potential implications and reference value for academic discourse analysis, English for Academic Purposes (EAP) teaching and writing.

Keywords: characteristic sentence stem, extraction method, phraseological unit, the statistical measure

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Authors: Halefom Kidane

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This study aims to assess the wind resource potential and characterize the urban area wind patterns in Hawassa City, Ethiopia. The estimation and characterization of wind resources are crucial for sustainable urban planning, renewable energy development, and climate change mitigation strategies. A secondary data collection method was used to carry out the study. The collected data at 2 meters was analyzed statistically and extrapolated to the standard heights of 10-meter and 30-meter heights using the power law equation. The standard deviation method was used to calculate the value of scale and shape factors. From the analysis presented, the maximum and minimum mean daily wind speed at 2 meters in 2016 was 1.33 m/s and 0.05 m/s in 2017, 1.67 m/s and 0.14 m/s in 2018, 1.61m and 0.07 m/s, respectively. The maximum monthly average wind speed of Hawassa City in 2016 at 2 meters was noticed in the month of December, which is around 0.78 m/s, while in 2017, the maximum wind speed was recorded in the month of January with a wind speed magnitude of 0.80 m/s and in 2018 June was maximum speed which is 0.76 m/s. On the other hand, October was the month with the minimum mean wind speed in all years, with a value of 0.47 m/s in 2016,0.47 in 2017 and 0.34 in 2018. The annual mean wind speed was 0.61 m/s in 2016,0.64, m/s in 2017 and 0.57 m/s in 2018 at a height of 2 meters. From extrapolation, the annual mean wind speeds for the years 2016,2017 and 2018 at 10 heights were 1.17 m/s,1.22 m/s, and 1.11 m/s, and at the height of 30 meters, were 3.34m/s,3.78 m/s, and 3.01 m/s respectively/Thus, the site consists mainly primarily classes-I of wind speed even at the extrapolated heights.

Keywords: artificial neural networks, forecasting, min-max normalization, wind speed

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Authors: Zaman Jawahar, Anne Rouve-Khiev, Elizabeth Hoban, Joanne Williams

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Ensuring access to timely obstetric care is essential to prevent maternal deaths. Geographical barriers pose significant challenges for women accessing quality reproductive and maternal health services in rural Cambodia. This policy brief affirms the need to address the issue of transportation and cost (direct and indirect) as critical barriers to accessing reproductive and maternal health (RMH) services in four provinces in Northeast Cambodia (Kratie, Ratanak Kiri, Mondul Kiri, Stung Treng). A systemic search of the literature identified 1,116 articles, and only ten articles from low-and-middle-income countries met the inclusion criteria. The ten articles reported on transportation and cost related to accessing RMH services. In addition, research findings from Partnering to Save Lives (PSL) studies in the four provinces were included in the analysis. Thematic data analysis using the information in the ten articles and PSL research findings was conducted, and the findings are presented in this paper. The key findings are the critical barriers to accessing RMH services in the four provinces because women experience: 1) difficulties finding affordable transportation; 2) lack of available and accessible transportation; 3) greater distance and traveling time to services; 4) poor geographical terrain and; 5) higher opportunity costs. Distance and poverty pose a double burden for the women accessing RMH services making a facility-based delivery less feasible compared to home delivery. Furthermore, indirect and hidden costs associated with institutional delivery may have an impact on women’s decision to seek RMH care. Existing health financing schemes in Cambodia such as the Health Equity Fund (HEF) and the Voucher Scheme contributed to the solution but have also shown some limitations. These schemes contribute to improving access to RMH services for the poorest group, but the barrier of transportation costs remains. In conclusion, initiatives that are proven to be effective in the Cambodian context should continue or be expanded in conjunction with the HEF, and special consideration should be given to communities living in geographically remote regions and difficult to access areas. The following strategies are recommended: 1) maintain and further strengthen transportation support in the HEF scheme; 2) expand community-based initiatives such as Community Managed Health Equity Funds and Village Saving Loans Associations; 3) establish maternity waiting homes; and 4) include antenatal and postnatal care in the provision of integrated outreach services. This policy brief can be used to inform key policymakers and provide evidence that can assist them to develop strategies to increase poor women’s access to RMH services in low-income settings, taking into consideration the geographic distance and other indirect costs associated with a facility-based delivery.

Keywords: access, barriers, northeast Cambodia, reproductive and maternal health service, transportation and cost

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Authors: Chenxi Zhang, Weizhong Qian, Fei Wei

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Gas solids multiphase flow is common in many engineering and environmental applications. Turbulence and multiphase flows are two of the most challenging topics in fluid mechanics, and when combined they pose a formidable challenge, even in the dilute dispersed regime. Dimensionless numbers are important in mechanics because their constancy can imply dynamic similarity between systems, despite possible differences in medium or scale. In the fluid mechanics literature, the Strouhal number is usually associated with the dimensionless shedding frequency of a von Karman wake; here we introduce this dimensionless number to investigate bubbling in gas solids fluidization. St=fA/U, which divides stroke frequency (f) and amplitude (A) by forward speed (U). The bubble behavior in a large two-dimensional bubbling fluidized bed (500mm×30mm×6000mm) is investigated. Our result indicates that propulsive efficiency is high and energy dissipation is low over a narrow range of St and usually within the interval 0.2Keywords: bubbles, Strouhal number, two-phase flow, energy dissipation

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Authors: Sohail Yasin, Massimo Curti, Nemeshwaree Behary, Giorgio Rovero

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It is well-known that the presence of discarded textile products in municipal landfills poses environmental problems due to leaching of chemical products from the textile to the environment. Incineration of such textiles is considered to be an efficient way to produce energy and reduce environmental impacts of textile materials at their end-of life stage. However, the presence of flame retardant products on textiles would decrease the energy yield and emit toxic gases during incineration stage. While some non-durable flame retardants can be removed by wet treatments (e.g. washing), these substances pollute water and pose concerns towards environmental health. Our study shows that infrared radiation can be used efficiently to degrade flame retardant products on the textiles. This method is finalized to minimize the decrease in energy yield during the incineration or gasification processes of flame retardant cotton fabrics.

Keywords: degradation, flame retardant, infrared radiation, cotton, incineration

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Authors: Omar Elharrouss, Youssef Hmamouche, Assia Kamal Idrissi, Btissam El Khamlichi, Amal El Fallah-Seghrouchni

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Edge detection is represented as one of the most challenging tasks in computer vision, due to the complexity of detecting the edges or boundaries in real-world images that contains objects of different types and scales like trees, building as well as various backgrounds. Edge detection is represented also as a key task for many computer vision applications. Using a set of backbones as well as attention modules, deep-learning-based methods improved the detection of edges compared with the traditional methods like Sobel and Canny. However, images of complex scenes still represent a challenge for these methods. Also, the detected edges using the existing approaches suffer from non-refined results while the image output contains many erroneous edges. To overcome this, n this paper, by using the mechanism of residual learning, a refined edge detection network is proposed (RED-Net). By maintaining the high resolution of edges during the training process, and conserving the resolution of the edge image during the network stage, we make the pooling outputs at each stage connected with the output of the previous layer. Also, after each layer, we use an affined batch normalization layer as an erosion operation for the homogeneous region in the image. The proposed methods are evaluated using the most challenging datasets including BSDS500, NYUD, and Multicue. The obtained results outperform the designed edge detection networks in terms of performance metrics and quality of output images.

Keywords: edge detection, convolutional neural networks, deep learning, scale-representation, backbone

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Authors: Nibedita Pani, Vishnu Tejani, T. S. Anantha Singh

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Water pollution resulting from discharge of partial/not treated textile wastewater containing high carbon and nitrogen pollutants pose a huge threat to the environment, ecosystem, and human health. It is essential to remove carbon- and nitrogen-based organic pollutants more effectively from industrial wastewater before discharging. The present study focuses on removal of carbon-based pollutant in particular COD (chemical oxygen demand) and nitrogen-based pollutants, in particular, ammoniacal nitrogen by Fenton oxidation process using Fe²⁺ and H₂O₂ as reagents. The study was carried out with high strength wastewater containing initial COD 5632 mg/L and NH⁴⁺-N 1372 mg/L. The major operating condition like pH was varied between 1.0 to 4.0. The maximum degradation was obtained at pH 3.0 taking the molar ratio of Fe²⁺/H₂O₂ as 1:1. At this pH, the removal efficiencies of COD and ammoniacal nitrogen were found to be 77.27% and 74.9%, respectively. The Fenton process can be the best alternative for the simultaneous removal of COD and NH4+-N from industrial wastewater.

Keywords: ammoniacal nitrogen, COD, Fenton oxidation, industrial wastewater

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Authors: Amrita Anil Agashe, Sumant Tapas, Ajay Verma Yogesh Sonavane, Sourabh Yeravar

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Due to advancement in MEMS technology today wireless sensors network has gained a lot of importance. The wide range of its applications includes environmental and habitat monitoring, object localization, target tracking, security surveillance etc. Wireless sensor networks consist of tiny sensor devices called as motes. The constrained computation power, battery power, storage capacity and communication bandwidth of the tiny motes pose challenging problems in the design and deployment of such systems. In this paper, we propose a ubiquitous framework for Real-Time Tracking, Sensing and Management System using IITH motes. Also, we explain the algorithm that we have developed for location management in wireless sensor networks with the aspect of mobility. Our developed framework and algorithm can be used to detect emergency events and safety threats and provides warning signals to handle the emergency.

Keywords: mobility management, motes, multihop, wireless sensor networks

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Authors: Pratishtha Singh

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Gender-based violence (GBV) or gendered violence refers to violence inflicted on a person because of their gender. Majority of men who perpetrate gender-based violence, first do so during their teenage years. Further, the first sexual experience of most girls is coerced. In order to reduce the widespread occurrence of GBV, it is vital to intervene and reach people, especially boys, when their attitudes and beliefs about sexuality and gender are developing. This study aims to understand GBV through an adolescent lens, focusing on their knowledge, attitudes and experiences regarding gendered abuse. This is a cross-sectional, qualitative study. The respondents are Delhi based students in grades 11th and 12th, recruited via snowball sampling. Sixteen in-depth, telephonic interviews were carried out in the month of April, 2020. The data was transcribed verbatim into MS Word and qualitative coding was undertaken in Atlas.ti 8. Twelve out of sixteen respondents admitted experiencing sexual GBV. Out of these, a little more than half of the victims reported it to somebody. Thematic analysis revealed key themes of: (i) Introduction and reinforcement of a patriarchal structure (ii) Violence in teen dating (iii) Acceptability and normalization of violence and (iv) Justice System. Findings reflect a process wherein GBV becomes an intricate part of adolescents’ lives. Participants showed a moderately well-informed understanding of gendered abuse whereas attitudes reflected a complex combination of internalized patriarchy and a desire to bring positive societal reform. The results of this study highlight a need for health promoting, gender-equitable interventions.

Keywords: adolescents, gender, health, violence

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Authors: Marisa Almeida AraúJo

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Artificial intelligence (AI) tools are being used (including in the criminal justice system) and becomingincreasingly popular. The many questions that these (future) super-beings pose the neuralgic center is rooted in the (old) problematic between rationality and morality. For instance, if we follow a Kantian perspective in which morality derives from AI, rationality will also surpass man in ethical and moral standards, questioning the nature of mind, the conscience of self and others, and moral. The recognition of superior intelligence in a non-human being puts us in the contingency of having to recognize a pair in a form of new coexistence and social relationship. Just think of the humanoid robot Sophia, capable of reasoning and conversation (and who has been recognized for Saudi citizenship; a fact that symbolically demonstrates our empathy with the being). Machines having a more intelligent mind, and even, eventually, with higher ethical standards to which, in the alluded categorical imperative, we would have to subject ourselves under penalty of contradiction with the universal Kantian law. Recognizing the complex ethical and legal issues and the significant impact on human rights and democratic functioning itself is the goal of our work.

Keywords: ethics, artificial intelligence, legal rules, principles, philosophy

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Authors: Francky Fouedjio

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Multivariate geostatistical data have become omnipresent in the geosciences and pose substantial analysis challenges. One of them is the grouping of data locations into spatially contiguous clusters so that data locations within the same cluster are more similar while clusters are different from each other, in some sense. Spatially contiguous clusters can significantly improve the interpretation that turns the resulting clusters into meaningful geographical subregions. In this paper, we develop an agglomerative hierarchical clustering approach that takes into account the spatial dependency between observations. It relies on a dissimilarity matrix built from a non-parametric kernel estimator of the spatial dependence structure of data. It integrates existing methods to find the optimal cluster number and to evaluate the contribution of variables to the clustering. The capability of the proposed approach to provide spatially compact, connected and meaningful clusters is assessed using bivariate synthetic dataset and multivariate geochemical dataset. The proposed clustering method gives satisfactory results compared to other similar geostatistical clustering methods.

Keywords: clustering, geostatistics, multivariate data, non-parametric

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Authors: Yonatan Sverdlov, Shimon Ullman

Abstract:

Artificial neural networks encounter a notable challenge known as continual learning, which involves acquiring knowledge of multiple tasks over an extended period. This challenge arises due to the tendency of previously learned weights to be adjusted to suit the objectives of new tasks, resulting in a phenomenon called catastrophic forgetting. Most approaches to this problem seek a balance between maximizing performance on the new tasks and minimizing the forgetting of previous tasks. In contrast, our approach attempts to maximize the performance of the new task, while ensuring zero forgetting. This is accomplished through the introduction of task-specific modulation parameters for each task, and only these parameters are learned for the new task, after a set of initial tasks have been learned. Through comprehensive experimental evaluations, our model demonstrates superior performance in acquiring and retaining novel tasks that pose difficulties for other multi-task models. This emphasizes the efficacy of our approach in preventing catastrophic forgetting while accommodating the acquisition of new tasks.

Keywords: continual learning, life-long learning, neural analogies, adaptive modulation

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