Search results for: person recognition

Authors: Felyppe Blum Goncalves, Juliana Sebastiany

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In line with Brazilian legislation on the inclusion of persons with disabilities in the world of work, known as the 'quota law' (Law 8213/91) and in accordance with the prerogatives of the United Nations Convention on Human Rights of people with disabilities, which was ratified by Brazil through Federal Decree No. 6.949 of August 25, 2009, the SESI National Department, through Working Groups, structured the product Affordable Industry. This methodology aims to prepare the industries for the adequate process of inclusion of people with disabilities, as well as the development of an organizational culture that values and respects human diversity. All industries in Brazil with 100 or more employees must comply with current legislation, but due to the lack of information and guidance on the subject, they end up having difficulties in this process. The methodology brings solutions for companies through the professional qualification of the disabled person, preparation of managers, training of human resources teams and employees. It also advocates the survey of the architectural accessibility of the factory and the identification of the possibilities of inclusion of people with disabilities, through the compatibility between work and job requirements, preserving safety, health, and quality of life.

Keywords: inclusion, app, disability, management

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Authors: Thilini M. Yatanwala

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CCTV (Closed-Circuit-Television) Surveillance System is being used in public places over decades and a large variety of data is being produced every moment. However, most of the CCTV data is stored in isolation without having integrity. As a result, identification of the behavior of suspicious people along with their location has become strenuous. This research was conducted to acquire more accurate and reliable timely information from the CCTV video records. The implemented system can identify human objects in public places based on outfit colors. Inter-process communication technologies were used to implement the CCTV camera network to track people in the premises. The research was conducted in three stages and in the first stage human objects were filtered from other movable objects available in public places. In the second stage people were uniquely identified based on their outfit colors and in the third stage an individual was continuously tracked in the CCTV network. A face detection algorithm was implemented using cascade classifier based on the training model to detect human objects. HAAR feature based two-dimensional convolution operator was introduced to identify features of the human face such as region of eyes, region of nose and bridge of the nose based on darkness and lightness of facial area. In the second stage outfit colors of human objects were analyzed by dividing the area into upper left, upper right, lower left, lower right of the body. Mean color, mod color and standard deviation of each area were extracted as crucial factors to uniquely identify human object using histogram based approach. Color based measurements were written in to XML files and separate directories were maintained to store XML files related to each camera according to time stamp. As the third stage of the approach, inter-process communication techniques were used to implement an acknowledgement based CCTV camera network to continuously track individuals in a network of cameras. Real time analysis of XML files generated in each camera can determine the path of individual to monitor full activity sequence. Higher efficiency was achieved by sending and receiving acknowledgments only among adjacent cameras. Suspicious incidents such as a person staying in a sensitive area for a longer period or a person disappeared from the camera coverage can be detected in this approach. The system was tested for 150 people with the accuracy level of 82%. However, this approach was unable to produce expected results in the presence of group of people wearing similar type of outfits. This approach can be applied to any existing camera network without changing the physical arrangement of CCTV cameras. The study of human identification and suspicious incident detection using outfit color analysis can achieve higher level of accuracy and the project will be continued by integrating motion and gait feature analysis techniques to derive more information from CCTV videos.

Keywords: CCTV surveillance, human detection and identification, image processing, inter-process communication, security, suspicious detection

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Authors: Leah Wilck

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Eyewitness identification is arguably one of the most utilized practices within our legal system; however, exoneration cases indicate that this practice may lead to accuracy and conviction errors. The purpose of this study was to examine the effects of the cross-race effect, the phenomena in which people are able to more easily and accurately identify faces from within their racial category, on the accuracy of eyewitness identification. Participants watched three separate videos of a perpetrator trying to steal a bicycle. In each video, the perpetrator was of a different race and gender. Participants watched a video where the perpetrator was a Black male, a White male, and a White female. Following the completion of watching each video, participants were asked to recall everything they could about the perpetrator they witnessed. The initial results of the study did not find the expected cross-race effect impacted the eyewitness identification accuracy. These surprising results are discussed in terms of cross-race bias and recognition theory as well as applied implications.

Keywords: cross race effect, eyewitness identification, own-race bias, racial profiling

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Authors: S. M. Abdullah Al Mamun

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Human Computer Interaction (HCI) is an excellent area for the researchers to make daily life more simple and fast. Necessary hardware equipments for any BCI are generally expensive and not affordable for most of the people. Emotiv is one of the solutions for this problem, which can provide electroencephalograph (EEG) signal and explain the brain activities. BCI virtual speller was one of the important applications for the people who have lost their hand or speaking ability because of diseases or unexpected accident. In this paper, a matrix speller has been designed for the first time for Bengali speaking people around the world. Bengali is one of the most commonly spoken languages. Among them, a lot of disabled person will be able to express their desire in their mother tongue. This application is also usable for the social networks and daily life communications. For this virtual keyboard, the well-known matrix speller method with column flashing is applied and controlled by single Emokey only. Emokey is a great feature which translates emotional state for application inputs. In this paper, it is presented that the ITR (Information Transfer Rate) were 29.4 bits/min and typing speed achieved up to 7.43 char/per min.

Keywords: brain computer interface, Emotiv EPOC, EEG, virtual keyboard, matrix speller

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Authors: Angel Mabudusha

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The impression created by the high volume of foreign nationals being deported by the South African Home Affairs and the police departments is that all undocumented foreign nationals insist on staying in South Africa and voluntary repatriation is open for every person. However, those foreign nationals whose request for deportation has been rejected are often not reported on especially their everyday survival as undocumented immigrant women and their encounter with the police on the street. As a result, this paper aims at exploring the everyday experiences of these women on the street and on why the number of undocumented immigrant women in this country will remain a challenge to the police department. The research was conducted in two cities in South Africa, namely: Johannesburg and Pretoria where the police, the undocumented immigrant women, the human rights lawyers and NGO officials were interviewed on this matter. Based on the idea that voluntary repatriation is open for every immigrant, this study has found that some women’ request for voluntary repatriation remain a dream that never came true. Furthermore, this article proposes more humanitarian ways of dealing with undocumented immigrant women.

Keywords: repatriation, refugee status, undocumented foreign nationals, humanitarian

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Authors: Mekamı Hayet, Bounoua Nacer, Benabderrahmane Sidahmed, Taleb Ahmed

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Pose estimation is an important task in computer vision. Though the majority of the existing solutions provide good accuracy results, they are often overly complex and computationally expensive. In this perspective, we propose the use of dimensionality reduction techniques to address the problem of facial pose estimation. Firstly, a face image is converted into one-dimensional time series using Hilbert space filling curve, then the approach converts these time series data to a symbolic representation. Furthermore, a distance matrix is calculated between symbolic series of an input learning dataset of images, to generate classifiers of frontal vs. profile face pose. The proposed method is evaluated with three public datasets. Experimental results have shown that our approach is able to achieve a correct classification rate exceeding 97% with K-NN algorithm.

Keywords: machine learning, pattern recognition, facial pose classification, time series

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Authors: Gholamreza Madad

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The role of medical equipment in modern advanced hospitals is irrefutable. Despite limited financial resources, developing countries have taken an uncontrollable manner to the purchase of complex and expensive equipment, although they have not taken good maintenance to keep these huge capitals. In our country, limited studies have indicated that the irregularities exist in the management of medical equipment maintenance. Research method: The research was done as a cross-sectional one, and in this study, a questionnaire was used to collect data in 10 hospitals. After distributing and collecting questionnaires in person, the collected data were analyzed using descriptive statistics and SPSS software. Research findings: According to the obtained results from the four dimensions of the management of medical equipment maintenance, only (maintenance planning) was in a moderate position and other components with a score of less than 50% were at a low level. There was a direct relationship between the total score of maintenance management and guidance points and coordination of medical equipment maintenance, and as well as the age of hospital managers. Discussion and conclusion: In sum, we can say that problems such as lack of skilled staff in medical engineering departments of hospitals, lack of funds and unaware of the authorities of medical engineering units to their duties have caused that the maintenance situation of medical equipment maintenance is in poor condition (near average). The low inexperience of the authorities of the unit has also contributed to this problem.

Keywords: equipment, maintenance, medical equipment, hospitals

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Authors: Mufti Nadimul Quamar Ahmed

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Universal and equitable access to safe and inexpensive water is one of the core goals of UN Sustainable Development (Goal-6). Rainwater harvesting and drinkable water scarcity are also prominent themes in the current literature. However, the lack of readily available drinking water sources is a serious roadblock in achieving this major goal in developing countries, especially in Bangladesh. In this study, we aimed to explore how water collecting activities in Bangladesh's coastal region are influenced by participants’ selected socio-demographic characteristics. We gathered information using a structured questionnaire from 154 people who were chosen at random from two of Bangladesh's most susceptible subdistricts situated in the country's southwest coast. Our results show that majority of the respondents think water fetching is a job for the woman as like their other day-day to household works and it’s not a man's duty. Interestingly, we found that person's age, family structure, monthly income and religion all play important roles in how they see and behave water-gathering techniques. Moreover, the local taboo on women and men's roles in water-gathering is also evident in the studied areas.

Keywords: water fetching, socio-demographic characteristic, coastal region, Bangladesh, SDG

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Authors: Samina Khalid, Shamila Nasreen

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Dimensionality reduction as a preprocessing step to machine learning is effective in removing irrelevant and redundant data, increasing learning accuracy, and improving result comprehensibility. However, the recent increase of dimensionality of data poses a severe challenge to many existing feature selection and feature extraction methods with respect to efficiency and effectiveness. In the field of machine learning and pattern recognition, dimensionality reduction is important area, where many approaches have been proposed. In this paper, some widely used feature selection and feature extraction techniques have analyzed with the purpose of how effectively these techniques can be used to achieve high performance of learning algorithms that ultimately improves predictive accuracy of classifier. An endeavor to analyze dimensionality reduction techniques briefly with the purpose to investigate strengths and weaknesses of some widely used dimensionality reduction methods is presented.

Keywords: age related macular degeneration, feature selection feature subset selection feature extraction/transformation, FSA’s, relief, correlation based method, PCA, ICA

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Authors: Jhansi Rani Boda, G. Sunitha

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Worldwide, the financial markets are influenced by several factors such as the changes in economic and political processes that occur in the country and the globe, information diffusion and approachability and so on. Yet, the foremost important factor is the investor’s reaction and perception. For an individual investor, decision-making process can be perceived as a continuous process that has significant impact of their psychology while making investment decisions. Behavioral finance relies on research of human and social recognition and emotional tolerance studies to identify and understand the investment decisions. This article aims to report the research of individual investor’s financial behavior in a historical perspective. This article uncovers the investor’s psychology in investment decision making focusing on the investor’s rationality with an explanation of psychological and emotional factors that affect investing. The results of the study are revealed by means of Graphical visualization.

Keywords: behavioral finance, psychology, investor’s behavior, psychological and emotional factors

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Authors: Hui Li, Xueying Zhao, Ke Ma, Yu Cao, Fan Yang, Qingwen Xu, Wenbin Liu

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Soil can often link a person or item to a crime scene, which makes it a valuable evidence in forensic casework. Several techniques have been utilized in forensic soil discrimination in previous studies. Because soil contains a vast number of microbiomes, the analyse of soil microbiomes is expected to be a potential way to characterise soil evidence. In this study, we applied massively parallel sequencing (MPS) to soil bacterial profiling on the Ion Torrent Personal Genome Machine (PGM). Soils from different regions were collected repeatedly. V-region 3 and 4 of Bacterial 16S rRNA gene were detected by MPS. Operational taxonomic units (OTU, 97%) were used to analyse soil bacteria. Several bioinformatics methods (PCoA, NMDS, Metastats, LEfse, and Heatmap) were applied in bacterial profiles. Our results demonstrate that MPS can provide a more detailed picture of the soil microbiomes and the composition of soil bacterial components from different region was individualistic. In conclusion, the utility of soil bacterial profiling via MPS of the 16S rRNA gene has potential value in characterising soil evidences and associating them with their place of origin, which can play an important role in forensic science in the future.

Keywords: bacterial profiling, forensic, massively parallel sequencing, soil evidence

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Authors: Olawale Johnson

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The cry and agitation for the creation of equal opportunities is one of the major reasons behind the social menace countries of the world experience. As the poor, continue to demand for the dividends of economic growth, countries of the world are in a state of dilemma because, despite impressive growth figures, the poor are still far below the empowerment line. However, evidence from the Asian Tigers has proven that with the adoption and efficient utilization of information technology, a growth miracle is not far-fetched. With the mind-boggling pace of technological innovation, the need to ensure that the innovative products are all connected has become vital. Technologies that did not exist a few years ago have become vital equipment used to underlie every aspect of our economy from medicine to banking to sports. The need to connect things sensors, actuators and smart systems with the aim of ensuring person-to-object, object-to-object communications has promoted the need of internet of things. As developing countries struggle with delivering inclusiveness, the Internet of Everything is perceived to be the miracle that will deliver this in no time. This paper examines how the Asian Tigers have been able to promote inclusive growth through the Internet of Everything.

Keywords: inclusive growth, internet of everything, innovation, embedded systems and smart technologies

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Authors: Francesco Morgan Bono, Simone Cinquemani

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This research aims to enhance bridge monitoring by employing innovative techniques that incorporate exogenous factors into the modeling of sensor signals, thereby improving long-term predictability beyond traditional static methods. Using real datasets from two different bridges equipped with Linear Variable Displacement Transducer (LVDT) sensors, the study investigates the fundamental principles governing sensor behavior for more precise long-term forecasts. Additionally, the research evaluates performance on noisy and synthetically damaged data, proposing a residual-based alarm system to detect anomalies in the bridge. In summary, this novel approach combines advanced modeling, exogenous factors, and anomaly detection to extend prediction horizons and improve preemptive damage recognition, significantly advancing structural health monitoring practices.

Keywords: structural health monitoring, dynamic models, sindy, railway bridges

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Authors: Utit Sungkharat

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Purpose: To investigate an invented tradition of Thai Buddhists and Thai Muslims for peace. Methods: The data for this qualitative research were collected from related documents and research reports, field data, and in-depth interviews with Buddhist and Muslim religious leaders and people in the community. Results: The results of the research revealed that Thai Buddhists and Thai Muslims in Tamod Community in the Southern part of Thailand who have lived in the same community and shared the same history of the community jointly invented the Songkran tradition holding on to the reason that they have lived in the same community founded by the same person. The reason for inventing this tradition is that Songkran is a tradition for paying respect to ancestors who passed away and people in Tamod have the same ancestor even though they believe in different religions. Therefore, paying respect to the ancestors can be performed together by people of the two religions. The invented tradition has not only united them and empowered them to drive their community to development but also brought peace and happiness to this community.

Keywords: invented tradition, Thai Buddhists, Thai Muslims, peace

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Authors: Najm Alotaibi

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Human motion capture has become one of the major area of interest in the field of computer vision. Some of the major application areas that have been rapidly evolving include the advanced human interfaces, virtual reality and security/surveillance systems. This study provides a brief overview of the techniques and applications used for the markerless human motion capture, which deals with analyzing the human motion in the form of mathematical formulations. The major contribution of this research is that it classifies the computer vision based techniques of human motion capture based on the taxonomy, and then breaks its down into four systematically different categories of tracking, initialization, pose estimation and recognition. The detailed descriptions and the relationships descriptions are given for the techniques of tracking and pose estimation. The subcategories of each process are further described. Various hypotheses have been used by the researchers in this domain are surveyed and the evolution of these techniques have been explained. It has been concluded in the survey that most researchers have focused on using the mathematical body models for the markerless motion capture.

Keywords: human motion capture, computer vision, vision-based, tracking

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Authors: Elena Valeryevna Pozhidaeva

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This linguistic case study is based on an interaction between the social position and foodways. In every culture there is a social hierarchical system in which there can be means to express and to identify the social status of a person. Food serves as a class indicator. The British being a verbal nation use the words as a preferred medium for signalling and recognising the social status. The linguistic analysis reflects a symbolic hierarchy determined by social groups in the UK. The linguistic class indicators of a British hierarchical system are detectable directly – in speech acts. They are articulated in every aspect of a national identity’s life from preferences of the food and the choice to call it to the names of the meals. The linguistic class indicators can as well be detected indirectly – through symbolic meaning or via the choice of the mealtime, its class (e.g the classes of tea or marmalade), the place to buy food (the class of the supermarket) and consume it (the places for eating out and the frequency of such practices). Under analysis of this study are not only food items and their names but also such categories as cutlery as a class indicator and the act of eating together as a practice of social significance and a class indicator. Current social changes and economic developments are considered and their influence on the class indicators appearance and transformation.

Keywords: linguistic, class, social indicator, English, food class

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Authors: Ho-Won Jung, Donghun Lee, Hyung-Jin Kim

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Predictive analytics (data analysis) uses a subset of measurements (the features, predictor, or independent variable) to predict another measurement (the outcome, target, or dependent variable) on a single person or unit. It applies empirical methods in statistics, operations research, and machine learning to predict the future, or otherwise unknown events or outcome on a single or person or unit, based on patterns in data. Most analyses of metabolic syndrome are not predictive analytics but statistical explanatory studies that build a proposed model (theory building) and then validate metabolic syndrome predictors hypothesized (theory testing). A proposed theoretical model forms with causal hypotheses that specify how and why certain empirical phenomena occur. Predictive analytics and explanatory modeling have their own territories in analysis. However, predictive analytics can perform vital roles in explanatory studies, i.e., scientific activities such as theory building, theory testing, and relevance assessment. In the context, this study is to demonstrate how to use our predictive analytics to support theory building (i.e., hypothesis generation). For the purpose, this study utilized a big data predictive analytics platform TM based on a co-occurrence graph. The co-occurrence graph is depicted with nodes (e.g., items in a basket) and arcs (direct connections between two nodes), where items in a basket are fully connected. A cluster is a collection of fully connected items, where the specific group of items has co-occurred in several rows in a data set. Clusters can be ranked using importance metrics, such as node size (number of items), frequency, surprise (observed frequency vs. expected), among others. The size of a graph can be represented by the numbers of nodes and arcs. Since the size of a co-occurrence graph does not depend directly on the number of observations (transactions), huge amounts of transactions can be represented and processed efficiently. For a demonstration, a total of 13,254 metabolic syndrome training data is plugged into the analytics platform to generate rules (potential hypotheses). Each observation includes 31 predictors, for example, associated with sociodemographic, habits, and activities. Some are intentionally included to get predictive analytics insights on variable selection such as cancer examination, house type, and vaccination. The platform automatically generates plausible hypotheses (rules) without statistical modeling. Then the rules are validated with an external testing dataset including 4,090 observations. Results as a kind of inductive reasoning show potential hypotheses extracted as a set of association rules. Most statistical models generate just one estimated equation. On the other hand, a set of rules (many estimated equations from a statistical perspective) in this study may imply heterogeneity in a population (i.e., different subpopulations with unique features are aggregated). Next step of theory development, i.e., theory testing, statistically tests whether a proposed theoretical model is a plausible explanation of a phenomenon interested in. If hypotheses generated are tested statistically with several thousand observations, most of the variables will become significant as the p-values approach zero. Thus, theory validation needs statistical methods utilizing a part of observations such as bootstrap resampling with an appropriate sample size.

Keywords: explanatory modeling, metabolic syndrome, predictive analytics, theory building

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Authors: Esha Thakkar, Ina Liu, Kalynn Hosea, Shana Katz, Katie Marks, Sarah Hall, Cat Liu, Suzanne Harris

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Purpose: Inequities in mental healthcare accessibility are cited as an international public health concern by the World Health Organization (WHO) and National Alliance on Mental Illness (NAMI). These disparities are further exacerbated in racial and ethnic minority groups and are especially concerning in health professional training settings such as Doctor of Pharmacy (PharmD) programs and postgraduate residency training where mental illness rates are high. The purpose of the study was to determine baseline access to culturally sensitive mental healthcare and how to improve such access and communication for racially and ethnically minoritized pharmacy students and residents at one school of pharmacy and a partnering academic medical center in the United States. Methods: This IRB-exempt study included 60-minute focus groups conducted in person or online from November 2021 to February 2022. Eligible participants included PharmD students in their first (P1), second (P2), third (P3), or fourth year (P4) or pharmacy residents completing a postgraduate year 1 (PGY1) or PGY2 who identify as Black, Indigenous, or Person of Color (BIPOC). There were four core theme questions asked during the focus groups to lead the discussion, specifically on the core themes of personal barriers, identities, areas that are working well, and areas for improvement. Participant responses were transcribed and analyzed using an open coding system with two individual reviews, followed by collaborative and intentional discussion and, as needed, an external audit of the coding by a third research team member to reach a consensus on themes. Results: This study enrolled 26 participants, with eight P1, five P2, seven P3, two P4, and four resident participants. Within the four core themes of barriers, identities, areas working well, and areas for improvement, emerging subthemes included: lack of time, access to resources, and stigma under barriers; lack of representation, cultural and family stigma, and gender identities for identity barriers; supportive faculty, sense of community and culture supporting paid time off for areas going well; and wellness days, reduced workload and diversity of the workforce in areas of improvement. Subthemes sometimes varied within a core theme depending on the participant year. Conclusions: There is a gap in the literature in addressing barriers and disparities in mental health access for pharmacy trainees who identify as BIPOC. We identified key findings in regards to barriers, identities, areas going well and areas for improvement that can inform the School and the Residency Program in two priority initiatives of well-being and diversity equity and inclusion in creating actionable recommendations for trainees, program directors, and employers of our institutions, and also has the potential to provide insight for other organizations about the structures influencing access to culturally sensitive care in BIPOC trainees. These findings can inform organizations on how to continue building on communication with those who identify as BIPOC and improve access to care.

Keywords: mental health, disparities, minorities, wellbeing, identity, communication, barriers

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Authors: Gizelle K. Vianna, Gustavo S. Oliveira, Gabriel V. Cunha

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The use of decision support systems in agriculture may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. In our work, we designed and implemented a decision support system for small tomatoes producers. This work investigates ways to recognize the late blight disease from the analysis of digital images of tomatoes, using a pair of multilayer perceptron neural networks. The networks outputs are used to generate repainted tomato images in which the injuries on the plant are highlighted, and to calculate the damage level of each plant. Those levels are then used to construct a situation map of a farm where a cellular automata simulates the outbreak evolution over the fields. The simulator can test different pesticides actions, helping in the decision on when to start the spraying and in the analysis of losses and gains of each choice of action.

Keywords: artificial neural networks, cellular automata, decision support system, pattern recognition

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Authors: Rebecca Laycock

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Many Urban Agriculture (UA) initiatives, including community/allotment gardens, Community Supported Agriculture, and community/social farms, depend on volunteers. However, initiatives supported or run by volunteers are often faced with a high turnover of labour as a result of the involvement of episodic volunteers (a term describing ad hoc, one-time, and seasonal volunteers), leading to challenges with maintaining project continuity and retaining skills/knowledge within the initiative. This is a notable challenge given that food growing is a knowledge intensive activity where the fruits of labour appear months or sometimes years after investment. Participatory Action Research (PAR) is increasingly advocated for in the field of UA as a solution-oriented approach to research, providing concrete results in addition to advancing theory. PAR is a cyclical methodological approach involving researchers and stakeholders collaboratively 'identifying' and 'theorising' an issue, 'planning' an action to address said issue, 'taking action', and 'reflecting' on the process. Through iterative cycles and prolonged engagement, the theory is developed and actions become better tailored to the issue. The demand for PAR in UA research means that understanding how to use PAR with episodic volunteers is of critical importance. The aim of this paper is to explore (1) the challenges of doing PAR in UA initiatives with episodic volunteers, and (2) how PAR can be harnessed to advance sustainable development of UA through theoretically-informed action. A 2.5 year qualitative PAR study on three English case study student-led food growing initiatives took place between 2014 and 2016. University UA initiatives were chosen as exemplars because most of their volunteers were episodic. Data were collected through 13 interviews, 6 workshops, and a research diary. The results were thematically analysed through eclectic coding using Computer-Assisted Qualitative Data Analysis Software (NVivo). It was found that the challenges of doing PAR with transient participants were (1) a superficial understanding of issues by volunteers because of short term engagement, resulting in difficulties ‘identifying’/‘theorising’ issues to research; (2) difficulties implementing ‘actions’ given those involved in the ‘planning’ phase often left by the ‘action’ phase; (3) a lack of capacity of participants to engage in research given the ongoing challenge of maintaining participation; and (4) that the introduction of the researcher acted as an ‘intervention’. The involvement of a long-term stakeholder (the researcher) changed the group dynamics, prompted critical reflections that had not previously taken place, and improved continuity. This posed challenges for providing a genuine understanding the episodic volunteering PAR initiatives, and also challenged the notion of what constitutes an ‘intervention’ or ‘action’ in PAR. It is recommended that researchers working with episodic volunteers using PAR should (1) adopt a first-person approach by inquiring into the researcher’s own experience to enable depth in theoretical analysis to manage the potentially superficial understandings by short-term participants; and (2) establish safety mechanisms to address the potential for the research to impose artificial project continuity and knowledge retention that will end when the research does. Through these means, we can more effectively use PAR to conduct solution-oriented research about UA.

Keywords: community garden, continuity, first-person research, higher education, knowledge retention, project management, transience, university

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Authors: Randa Boukhris, Alima Damak, Dorra Sellami

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Fingervein biometric authentication is one of the most popular and accurate technologies. However, low cost embedded solution is still an open problem. In this paper, a real-time implementation of fingervein recognition process embedded in Raspberry-Pi has been proposed. The use of Raspberry-Pi reduces overall system cost and size while allowing an easy user interface. Implementation of a target technology has guided to opt some specific parallel and simple processing algorithms. In the proposed system, we use four structural directional kernel elements for filtering finger vein images. Then, a Top-Hat and Bottom-Hat kernel filters are used to enhance the visibility and the appearance of venous images. For feature extraction step, a simple Local Directional Code (LDC) descriptor is applied. The proposed system presents an Error Equal Rate (EER) and Identification Rate (IR), respectively, equal to 0.02 and 98%. Furthermore, experimental results show that real-time operations have good performance.

Keywords: biometric, Bottom-Hat, Fingervein, LDC, Rasberry-Pi, ROI, Top-Hat

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Authors: Kuribachew Gizaw Tohiye, Monica Garfield

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Personal knowledge management is the aspect of knowledge management that relates to the way in which individuals organize and manage their own set of knowledge. While in that respect, there has been research in this area for the past 25 years, it is at present necessary to speculate upon what research has been done and what we have discovered about this arena of knowledge management. In contrast to organizational knowledge management, which focuses on a firm’s profitability and competitiveness, personal knowledge management (PKM) is concerned with the person’s self-effectiveness, competence and success. People are concerned in managing their knowledge in order to become more efficient in a variety of personal and organizational interests. This study presents a systematic review of PKM studies. Articles with PKM concepts are reviewed with the objective of clearly defining PKM, identifying the benefits of PKM, classifying the tools that enable PKM and finding the research gaps to indicate future research directions in the area. Consequently, we have developed a definition of PKM and identified the benefits of PKM, including an understanding of who seeks PKM and for what. Tools enabling PKM are identified and classified under three categories Web 1.0, 2.0 and 3.0 and finally the research gap and future directions are suggested. Research which facilitates collaboration by using semantic technologies is suggested to be studied further to improve PKM effectiveness.

Keywords: personal knowledge management, knowledge management, organizational knowledge management, systematic review

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Authors: Sergey Ermolin, Olga Ermolin

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A Deep Convolution Neural Network with Triplet Loss is used to identify duplicate images in real-estate advertisements in the presence of image artifacts such as watermarking, cropping, hue/brightness adjustment, and others. The effects of batch normalization, spatial dropout, and various convergence methodologies on the resulting detection accuracy are discussed. For comparative Return-on-Investment study (per industry request), end-2-end performance is benchmarked on both Nvidia Titan GPUs and Intel’s Xeon CPUs. A new real-estate dataset from San Francisco Bay Area is used for this work. Sufficient duplicate detection accuracy is achieved to supplement other database-grounded methods of duplicate removal. The implemented method is used in a Proof-of-Concept project in the real-estate industry.

Keywords: visual recognition, convolutional neural networks, triplet loss, spatial batch normalization with dropout, duplicate removal, advertisement technologies, performance benchmarking

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Authors: Retty Ratnawati, Santi Sri Wulandari, Tulus Sabrina

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Feminine and masculine gender role stress could occur in some work situation. Being manager in health services that is known to be more women’ role in Indonesia, has expected to have feminine stereotype role. In the communities, this has been done in the program kesejahteraan keluarga (welfare family program) since the 1970s, for example through family planning program. The aim of the study was to explore the experience of being a motherhood managerial in health services. Our auto ethnographic study has revealed that motherhood managerial, even though running by a woman, could have some stress conditions whether she has realized or has not. The challenge would occur when the manager did not realize that she needed the eustress. The autonomy concept for a woman to be a manager could be a complex cycle that needs open communication continually and understanding the four elements surround her life. In conclusion, there is a demand to have the eustress when the manager does not realize that she has to be an autonomy person. However, it does not need eustress when the manager understands about how to deal with the complex cycle of being autonomy.

Keywords: motherhood managerial, eustress, feminine gender role stress, masculine gender role stress, autonomy concept in women

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Authors: Daniel Benson, Yundan Gong, Hannah Kirk

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Advancement in national language processing techniques has led to increased data processing speeds, and reduced the need for cumbersome, manual data processing that is often required when processing data from multilateral organizations for specific purposes. As such, using named entity recognition (NER) modeling and the Organisation of Economically Developed Countries (OECD) Creditor Reporting System database, we present the first geotagged dataset of OECD donor Official Development Assistance (ODA) projects on a global, subnational basis. Our resulting data contains 52,086 ODA projects geocoded to subnational locations across 115 countries, worth a combined $87.9bn. This represents the first global, OECD donor ODA project database with geocoded projects. We use this new data to revisit old questions of how ‘well’ donors allocate ODA to the developing world. This understanding is imperative for policymakers seeking to improve ODA effectiveness.

Keywords: international aid, geocoding, subnational data, natural language processing, machine learning

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Authors: Annabelle Nelson

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This literature review documents indigenous storytelling as it functions to help humans face adversity and find emotional strength by aligning with nature. Archetypes in stories can transform the inner world from a Jungian perspective. Joseph Campbell’s hero-heroine cycle depicts the structure of stories to include a call to adventure, tests, helpers, and a return as the transformed person can help him or herself and even help their communities. By showcasing certain character traits, such as bravery or perseverance or humility, stories give maps for humans to face adversity. The main characters or archetypes in stories, as Carl Jung posited, provide a vehicle that can open consciousness if a listener identifies with the character. As documented in the review, this has many benefits. First, it can open consciousness to the collective unconscious for insight and intuitive clarity, as well as healing and release emotional trauma. The resultant spacious quality of consciousness allows the spiritual self to present insights to conscious awareness. Research in applied youth development programs demonstrates the utility of storytelling to prompt healthy choices and transform difficult life experience into success.

Keywords: archetypes, learning, storytelling, transformation

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Authors: Aneta Nitsch-Osuch, Damian Okrucinski, Magdalena Dawgialło, Izabela Gołębiak, Ernest Kuchar

Abstract:

The Hospital Antibiotic Policy (HAP) should be implemented to rationalize the antibiotic use and to decrease the risk of spreading of spreading of resistant bacteria. The aim of our study was to describe the antibiotic consumption patterns at the single oncosurgery ward before and after implementation of the HAP. We conducted a retrospective analysis of the antibiotic use at the Oncosurgery Ward in Warsaw (Poland) in years 2011-2016. Calculations were based on daily defined doses (DDDs), DDDs/100 hospitalizations and DDDs/100 person-days, drug utilization rates (DU 90% and DU 100%) were also analysed. After implementation of the HAP, the total antibiotic consumption increased (365.35 DDD in 2011 vs. 1359,22 DDD in 2016). The significant change was observed in antibiotic consumption patterns: the use of amoxicillin clavulanate and carbapenems or glycopeptides decreased significantly (p < 0,05), while the use of ciprofloxacin and aminoglycosides increased (p < 0,05). The DU100% rate varied from 6 in 2011 to 12 in 2016; while DU 90% rate varied from 2 in 2011 to 3-5 in 2013-2016. Although the implementation of the HAP did not result in the decreased total antibiotic consumption, it provided favorable changes in the antibiotic consumption patterns.

Keywords: antibiotics, hospital, policy, stewardship

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Authors: Yulong Wang, Yuan Yan Tang, Cuiming Zou, Lina Yang

Abstract:

This paper presents a novel sparse representation method for robust pattern classification. Generalized orthogonal matching pursuit (GOMP) is a recently proposed efficient sparse representation technique. However, GOMP adopts the mean square error (MSE) criterion and assign the same weights to all measurements, including both severely and slightly corrupted ones. To reduce the limitation, we propose an information-theoretic GOMP (ITGOMP) method by exploiting the correntropy induced metric. The results show that ITGOMP can adaptively assign small weights on severely contaminated measurements and large weights on clean ones, respectively. An ITGOMP based classifier is further developed for robust pattern classification. The experiments on public real datasets demonstrate the efficacy of the proposed approach.

Keywords: correntropy induced metric, matching pursuit, pattern classification, sparse representation

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Authors: Chander Kant, Arun Kumar

Abstract:

Biometric systems automatically recognize an individual based on his/her physiological and behavioral characteristics. There are also some traits like weight, age, height etc. that may not provide reliable user recognition because of there common and temporary nature. These traits are called soft bio metric traits. Although soft bio metric traits are lack of permanence to uniquely and reliably identify an individual, yet they provide some beneficial evidence about the user identity and may improve the system performance. Here in this paper, we have proposed an approach for integrating the soft bio metrics with fingerprint and face to improve the performance of personal authentication system. In our approach we have proposed a combined architecture of three different sensors to elevate the system performance. The approach includes, soft bio metrics, fingerprint and face traits. We have also proven the efficiency of proposed system regarding FAR (False Acceptance Ratio) and total response time, with the help of MUBI (Multimodal Bio metrics Integration) software.

Keywords: FAR, minutiae point, multimodal bio metrics, primary bio metric, soft bio metric

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Authors: Justyna P. Majewska, Szymon M. Truskolaski

Abstract:

The growing importance of digitalized services in the so-called new economy, including the e-sports industry, can be observed recently. Various demographic or technological changes lead consumers to modify their needs, not regarding the services themselves but the method of their application (attracting customers, forms of payment, new content, etc.). In the case of leisure-related to competitive spectating activities, there is a growing need to participate in events whose content is not sports competitions but computer games challenge – e-sport. The literature in this area so far focuses on determining the number of e-sport fans with elements of a simple statistical description (mainly concerning demographic characteristics such as age, gender, place of residence). Meanwhile, the development of the industry is influenced by a combination of many different, intertwined demographic, personality and psychosocial characteristics of customers, as well as the characteristics of their environment. Therefore, there is a need for a deeper recognition of the determinants of the behavioral patterns upon selecting digitalized services by customers, which, in the absence of available large data sets, can be achieved by using econometric simulations – multi-agent modeling. The cognitive aim of the study is to reveal internal and external determinants of behavioral patterns of customers taking into account various variants of economic development (the pace of digitization and technological development, socio-demographic changes, etc.). In the paper, an agent-based model with heterogeneous agents (characteristics of customers themselves and their environment) was developed, which allowed identifying a three-stage development scenario: i) initial interest, ii) standardization, and iii) full professionalization. The probabilities regarding the transition process were estimated using the Method of Simulated Moments. The estimation of the agent-based model parameters and sensitivity analysis reveals crucial factors that have driven a rising trend in e-sport spectating and, in a wider perspective, the development of digitalized services. Among the psychosocial characteristics of customers, they are the level of familiarization with the rules of games as well as sports disciplines, active and passive participation history and individual perception of challenging activities. Environmental factors include general reception of games, number and level of recognition of community builders and the level of technological development of streaming as well as community building platforms. However, the crucial factor underlying the good predictive power of the model is the level of professionalization. While in the initial interest phase, the entry barriers for new customers are high. They decrease during the phase of standardization and increase again in the phase of full professionalization when new customers perceive participation history inaccessible. In this case, they are prone to switch to new methods of service application – in the case of e-sport vs. sports to new content and more modern methods of its delivery. In a wider context, the findings in the paper support the idea of a life cycle of services regarding methods of their application from “traditional” to digitalized.

Keywords: agent-based modeling, digitalized services, e-sport, spectators motives

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