Search results for: classification of people

Authors: Phusit Phukamchanoad, Thananya Santithammakul, Suwaree Yordchim, Pennapa Palapin

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This research gathered local wisdom towards career building of people in Kamchanoad Community, Baan Muang sub-district, Baan Dung district, Udon Thani province. Data was collected through in-depth interviews with village headmen, community board, teachers, monks, Kamchanoad forest managers and revered elderly aged over 60 years old. All of these 30 interviewees have resided in Kamchanoad Community for more than 40. Descriptive data analysis result revealed that the most prominent local wisdom of Kamchanoad community is their beliefs and religion. Most people in the community have strongly maintained local tradition, the festival of appeasing Chao Pu Sri Suttho on the middle of the 6th month of Thai lunar calendar which falls on the same day with Vesak Day. 100 percent of the people in this community are Buddhist. They believe that Naga, an entity or being, taking the form of a serpent, named “Sri Suttho” lives in Kamchanoad forest. The local people worship the serpent and ask for blessings. Another local wisdom of this community is Sinh fabric weaving.

Keywords: local wisdoms, careers, Kamchanoad Community, career building

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Authors: İsmail Kavdır, M. Burak Büyükcan, Ferhat Kurtulmuş

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Table olive is a valuable product especially in Mediterranean countries. It is usually consumed after some fermentation process. Defects happened naturally or as a result of an impact while olives are still fresh may become more distinct after processing period. Defected olives are not desired both in table olive and olive oil industries as it will affect the final product quality and reduce market prices considerably. Therefore it is critical to sort table olives before processing or even after processing according to their quality and surface defects. However, doing manual sorting has many drawbacks such as high expenses, subjectivity, tediousness and inconsistency. Quality criterions for green olives were accepted as color and free of mechanical defects, wrinkling, surface blemishes and rotting. In this study, it was aimed to classify fresh table olives using different classifiers and NIR spectroscopy readings and also to compare the classifiers. For this purpose, green (Ayvalik variety) olives were classified based on their surface feature properties such as defect-free, with bruised defect and with fly defect using FT-NIR spectroscopy and classification algorithms such as artificial neural networks, ident and cluster. Bruker multi-purpose analyzer (MPA) FT-NIR spectrometer (Bruker Optik, GmbH, Ettlingen Germany) was used for spectral measurements. The spectrometer was equipped with InGaAs detectors (TE-InGaAs internal for reflectance and RT-InGaAs external for transmittance) and a 20-watt high intensity tungsten–halogen NIR light source. Reflectance measurements were performed with a fiber optic probe (type IN 261) which covered the wavelengths between 780–2500 nm, while transmittance measurements were performed between 800 and 1725 nm. Thirty-two scans were acquired for each reflectance spectrum in about 15.32 s while 128 scans were obtained for transmittance in about 62 s. Resolution was 8 cm⁻¹ for both spectral measurement modes. Instrument control was done using OPUS software (Bruker Optik, GmbH, Ettlingen Germany). Classification applications were performed using three classifiers; Backpropagation Neural Networks, ident and cluster classification algorithms. For these classification applications, Neural Network tool box in Matlab, ident and cluster modules in OPUS software were used. Classifications were performed considering different scenarios; two quality conditions at once (good vs bruised, good vs fly defect) and three quality conditions at once (good, bruised and fly defect). Two spectrometer readings were used in classification applications; reflectance and transmittance. Classification results obtained using artificial neural networks algorithm in discriminating good olives from bruised olives, from olives with fly defect and from the olive group including both bruised and fly defected olives with success rates respectively changing between 97 and 99%, 61 and 94% and between 58.67 and 92%. On the other hand, classification results obtained for discriminating good olives from bruised ones and also for discriminating good olives from fly defected olives using the ident method ranged between 75-97.5% and 32.5-57.5%, respectfully; results obtained for the same classification applications using the cluster method ranged between 52.5-97.5% and between 22.5-57.5%.

Keywords: artificial neural networks, statistical classifiers, NIR spectroscopy, reflectance, transmittance

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Authors: Fawzia Mohammed Idris

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Zakat is an Islamic procedure for wealth distribution as a social protection mechanism for needy people. This study aimed to assess the possibility to expand the share of fund for national health insurance fund from zakat funds allocated for poor people by measuring the reduction of poverty that result from the investing on direct payment to the needy or by covering them in social health insurance. This study used stata regression as a statistical analysis tool and the finding clarified that there is no significant relationship between the poverty rate as the main indicator and, the number of poor people covered by national health insurance on one hand and the number of benefits poor people from the distribution of zakat fund. This study experienced many difficulties regarding the quality and the consistency of the data. The study suggested that a joint mission between national health insurance fund and zakat chamber to conduct study to assess the efficient use of zakat fund allocated to poor people.

Keywords: health finance, poverty, social health insurance, zakat

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Authors: Anju Batta Sehgal

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Climate change is a major challenge in terms of agriculture, food security and rural livelihood for thousands of people especially the poor in Himachal, which falls in North-Western Himalayas. Agriculture contributes over 45 per cent to net state domestic product. It is the main source of income and employment. Over 93 per cent of population is dependent on agriculture which provides direct employment to 71 percent of its people. Area of operation holding is about 9,79 lakh hectares owned by 9.14 lakh farmers. About 80 per cent area is rain-fed and farmers depend on weather gods for rains. Region is a home of diverse ethnic communities having enormous socio-economic and cultural diversities, gifted with range of farming systems and rich resource wealth, including biodiversity, hot spots and ecosystems sustaining millions of people living in the region. But growing demands of ecosystem goods and services are posing threats to natural resources. Climate change is already making adverse impact on the indigenous people. The rural populace is directly dependent for all its food, shelter and other needs on the climate. Our aim should be to shift the focus to indigenous people as primary actors in terms of global climate change monitoring, adaptations and innovations. Objective of this paper is to identify the climate change related threats and vulnerabilities associated with agriculture as a sector and agriculture as people’s livelihood. Broadly it analyses the connections between the nature and rural consumers the ethnic groups.

Keywords: climate change, agriculture, indigenous people, Himachal Pradesh

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Authors: Charawee Butbumrung

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The purpose of this research were to study the factors influencing savings of people between 30-40 years old in Dusit District, Bangkok Metropolis. The statistic used in data analysis were frequency, mean and standard deviation, t-test, one-way ANOVA and Pearson’s correlation coefficient based on social science statistic program. Result of hypothesis testing showed that married people earning different monthly salary generally saved by depositing into the bank at different level. People of different occupation saved in form of life insurance at different level at statistical significance 0.05. Result of influence testing between saving motivation was found that people saved for use upon sickness or getting older, saved for the children. Worthiness and certainty influenced saving in the same direction at high level while saving motivation in public relation, annual tax reduction, inducement by the others, bonus gift influenced saving in the same direction at moderate level at statistical significance 0.05.

Keywords: Dusit District, factors, saving, Bangkok Metropolis

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Authors: Abdullah Al Farwan, Ya Zhang

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In today’s educational arena, it is critical to understand educational data and be able to evaluate important aspects, particularly data on student achievement. Educational Data Mining (EDM) is a research area that focusing on uncovering patterns and information in data from educational institutions. Teachers, if they are able to predict their students' class performance, can use this information to improve their teaching abilities. It has evolved into valuable knowledge that can be used for a wide range of objectives; for example, a strategic plan can be used to generate high-quality education. Based on previous data, this paper recommends employing data mining techniques to forecast students' final grades. In this study, five data mining methods, Decision Tree, JRip, Naive Bayes, Multi-layer Perceptron, and Random Forest with wrapper feature selection, were used on two datasets relating to Portuguese language and mathematics classes lessons. The results showed the effectiveness of using data mining learning methodologies in predicting student academic success. The classification accuracy achieved with selected algorithms lies in the range of 80-94%. Among all the selected classification algorithms, the lowest accuracy is achieved by the Multi-layer Perceptron algorithm, which is close to 70.45%, and the highest accuracy is achieved by the Random Forest algorithm, which is close to 94.10%. This proposed work can assist educational administrators to identify poor performing students at an early stage and perhaps implement motivational interventions to improve their academic success and prevent educational dropout.

Keywords: classification algorithms, decision tree, feature selection, multi-layer perceptron, Naïve Bayes, random forest, students’ academic performance

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Authors: Uwonkunda Jeanne, J. Godwin Prem Singh, Anjaneyalu Subbiah

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HIV/AIDS is known to affect an individual not only physically but also mentally, socially, and financially. It is a syndrome that builds a vacuum in a person affecting his/her life as a whole.

Keywords: People living with HIV, social dysfunction, stigma, and Social support.

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Authors: S. Kherchaoui, A. Houacine

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This paper presents a facial expression recognition system. It performs identification and classification of the seven basic expressions; happy, surprise, fear, disgust, sadness, anger, and neutral states. It consists of three main parts. The first one is the detection of a face and the corresponding facial features to extract the most expressive portion of the face, followed by a normalization of the region of interest. Then calculus of curvelet coefficients is performed with dimensionality reduction through principal component analysis. The resulting coefficients are combined with two ratios; mouth ratio and face edge ratio to constitute the whole feature vector. The third step is the classification of the emotional state using the SVM method in the feature space.

Keywords: facial expression identification, curvelet coefficient, support vector machine (SVM), recognition system

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Authors: Irene Carter, Roy Hanes, Judy MacDonald

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Considering that disability is universal and people with disabilities are part of all societies; that there is a connection between the disabled individual and the societal; and that it is society and social arrangements that disable people with impairments, contemporary disability discourse emphasizes the social model of disability to counter medical and rehabilitative models of disability. However, the social model does not go far enough in addressing the issues of oppression and inclusion. The authors indicate that the social model does not specifically or adequately denote the oppression of persons with disabilities, which is a central component of progressive social work practice with people with disabilities. The social model of disability does not go far enough in deconstructing disability and offering social workers, as well as people with disabilities a way of moving forward in terms of practice anchored in individual, familial and societal change. The social model of disability is expanded by incorporating principles of anti-oppression social work practice. Although the contextual analysis of the social model of disability is an important component there remains a need for social workers to provide service to individuals and their families, which will be illustrated through anti-oppressive practice (AOP). By applying an anti-oppressive model of practice to the above definitions, the authors not only deconstruct disability paradigms but illustrate how AOP offers a framework for social workers to engage with people with disabilities at the individual, familial and community levels of practice, promoting an emancipatory focus in working with people with disabilities. An anti- social- oppression social work model of disability connects the day-to-day hardships of people with disabilities to the direct consequence of oppression in the form of ableism. AOP theory finds many of its basic concepts within social-oppression theory and the social model of disability. It is often the case that practitioners, including social workers and psychologists, define people with disabilities’ as having or being a problem with the focus placed upon adjustment and coping. A case example will be used to illustrate how an AOP paradigm offers social work a more comprehensive and critical analysis and practice model for social work practice with and for people with disabilities than the traditional medical model, rehabilitative and social model approaches.

Keywords: anti-oppressive practice, disability, people with disabilities, social model of disability

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Authors: Mbah Fidelix Njong, Sabi Emile Forkwa

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Social cognition is an aspect of social psychology that focuses on how people process, store and apply information about others and social situations. It lay emphasis on how cognitive processes play in our social interactions. In this article, we try to show how culture can influence our ways of thinking about others, how we feel and interact with the world around us. Social cognitive processes involve perceiving people and how we learn about the people around us. It concerns the mental processes of remembering, thinking and attending to other people with different cultural backgrounds and how we attend to certain information about the world. Especially in an educational setting, students’ learning processes are most often than not influenced by their cultural background. We can also talk of social schemas. That’s people’s mental representation of social patterns and norms. This involves information about the societal role and the expectations of individuals within a group. These cognitive processes can also be influence by culture. There are important cultural differences in social cognition. In any social situation, two individuals may have different interpretations. Each person brings in a unique background of experiences, knowledge, social influence, feelings and cultural variations. Cultural differences can also affect how people interpret social situations. The same social behavior in one cultural setting might have completely different meaning and interpretation if observed or applied in another culture. However, as people interpret behaviors and bring out meaning from the interpretations, they act based on their beliefs about situations they are confronted with. This helps to reinforce and reproduce the cultural norms that influence their social cognition.

Keywords: social cognition, social schema, cultural influence, psychology

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Authors: Kemal Polat

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In this paper, an attribute weighting method called fuzzy C-means clustering based attribute weighting (FCMAW) for classification of Diabetes disease dataset has been used. The aims of this study are to reduce the variance within attributes of diabetes dataset and to improve the classification accuracy of classifier algorithm transforming from non-linear separable datasets to linearly separable datasets. Pima Indians Diabetes dataset has two classes including normal subjects (500 instances) and diabetes subjects (268 instances). Fuzzy C-means clustering is an improved version of K-means clustering method and is one of most used clustering methods in data mining and machine learning applications. In this study, as the first stage, fuzzy C-means clustering process has been used for finding the centers of attributes in Pima Indians diabetes dataset and then weighted the dataset according to the ratios of the means of attributes to centers of theirs. Secondly, after weighting process, the classifier algorithms including support vector machine (SVM) and k-NN (k- nearest neighbor) classifiers have been used for classifying weighted Pima Indians diabetes dataset. Experimental results show that the proposed attribute weighting method (FCMAW) has obtained very promising results in the classification of Pima Indians diabetes dataset.

Keywords: fuzzy C-means clustering, fuzzy C-means clustering based attribute weighting, Pima Indians diabetes, SVM

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Authors: Lulu Wang, Yongjun Xu, Xiaoyang Qiao

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The Forbidden City is well known for being full of Chinese cultural and historical relics. However, the Masters in the Forbidden City, a documentary film, doesn’t just dwell on the stories of the past. Instead, it focuses on ordinary people—the restorers of the relics and antiquities, which has caught the sight of Chinese audiences. From this popular documentary film, a new way can be considered, that is to show the relics, antiquities and painting with a character of modern humanities by films and TV programs. Of course, it can’t just like a simple explanation from tour guides in museums. It should be a perfect combination of scenes, heritages, stories, storytellers and background music. All we want to do is trying to dig up the humanity behind the heritages and then create a virtual scene for the audience to have emotional resonance from the humanity. It is believed that there are two problems. One is that compared with the entertainment shows, why people prefer to see the boring restoration work. The other is that what the interaction is between those history documentary films, the heritages, the audiences and collective memory. This paper mainly used the methods of text analysis and data analysis. The audiences’ comment texts were collected from all kinds of popular video sites. Through analyzing those texts, there was a word cloud chart about people preferring to use what kind of words to comment the film. Then the usage rate of all comments words was calculated. After that, there was a Radar Chart to show the rank results. Eventually, each of them was given an emotional value classification according their comment tone and content. Based on the above analysis results, an interaction model among the audience, history films/TV programs and the collective memory can be summarized. According to the word cloud chart, people prefer to use such words to comment, including moving, history, love, family, celebrity, tone... From those emotional words, we can see Chinese audience felt so proud and shared the sense of Collective Identity, so they leave such comments: To our great motherland! Chinese traditional culture is really profound! It is found that in the construction of collective memory symbology, the films formed an imaginary system by organizing a ‘personalized audience’. The audience is not just a recipient of information, but a participant of the documentary films and a cooperator of collective memory. At the same time, it is believed that the traditional background music, the spectacular present scenes and the tone of the storytellers/hosts are also important, so it is suggested that the museums could try to cooperate with the producers of movie and TV program to create a vivid scene for the people. Maybe it’s a more artistic way for heritages to be open to all the world.

Keywords: audience, heritages, history movies, TV programs

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Authors: Hisham Arab Alkabeya, A. M. Hughes, J. Adams

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Background: People with Rheumatoid Arthritis (RA) continue to experience problems with hand function despite new drug advances and targeted medical treatment. Consequently, it is important to identify the factors that influence the impact of RA disease on hand function. This systematic review identified observational studies that reported factors that influenced the impact of RA on hand function. Methods: MEDLINE, EMBASE, CINAL, AMED, PsychINFO, and Web of Science database were searched from January 1990 up to March 2017. Full-text articles published in English that described factors related to hand functional disability in people with RA were selected following predetermined inclusion and exclusion criteria. Pertinent data were thoroughly extracted and documented using a pre-designed data extraction form by the lead author, and cross-checked by the review team for completion and accuracy. Factors related to hand function were classified under the domains of the International Classification of Functioning, Disability, and Health (ICF) framework and health-related factors. Three reviewers independently assessed the methodological quality of the included articles using the quality of cross-sectional studies (AXIS) tool. Factors related to hand function that was investigated in two or more studies were explored using a best-evidence synthesis. Results: Twenty articles form 19 studies met the inclusion criteria from 1,271 citations; all presented cross-sectional data (five high quality and 15 low quality studies), resulting in at best limited evidence in the best-evidence synthesis. For the factors classified under the ICF domains, the best-evidence synthesis indicates that there was a range of body structure and function factors that were related with hand functional disability. However, key factors were hand strength, disease activity, and pain intensity. Low functional status (physical, emotional and social) level was found to be related with limited hand function. For personal factors, there is limited evidence that gender is not related with hand function; whereas, conflicting evidence was found regarding the relationship between age and hand function. In the domain of environmental factors, there was limited evidence that work activity was not related with hand function. Regarding health-related factors, there was limited evidence that the level of the rheumatoid factor (RF) was not related to hand function. Finally, conflicting evidence was found regarding the relationship between hand function and disease duration and general health status. Conclusion: Studies focused on body structure and function factors, highlighting a lack of investigation into personal and environmental factors when considering the impact of RA on hand function. The level of evidence which exists was limited, but identified that modifiable factors such as grip or pinch strength, disease activity and pain are the most influential factors on hand function in people with RA. The review findings suggest that important personal and environmental factors that impact on hand function in people with RA are not yet considered or reported in clinical research. Well-designed longitudinal, preferably cohort, studies are now needed to better understand the causality between personal and environmental factors and hand functional disability in people with RA.

Keywords: factors, hand function, rheumatoid arthritis, systematic review

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Authors: Naghmeh Moradpoor Sheykhkanloo

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Structured Query Language Injection (SQLI) attack is a code injection technique in which malicious SQL statements are inserted into a given SQL database by simply using a web browser. Losing data, disclosing confidential information or even changing the value of data are the severe damages that SQLI attack can cause on a given database. SQLI attack has also been rated as the number-one attack among top ten web application threats on Open Web Application Security Project (OWASP). OWASP is an open community dedicated to enabling organisations to consider, develop, obtain, function, and preserve applications that can be trusted. In this paper, we propose an effective pattern recognition neural network model for detection and classification of SQLI attacks. The proposed model is built from three main elements of: a Uniform Resource Locator (URL) generator in order to generate thousands of malicious and benign URLs, a URL classifier in order to: 1) classify each generated URL to either a benign URL or a malicious URL and 2) classify the malicious URLs into different SQLI attack categories, and an NN model in order to: 1) detect either a given URL is a malicious URL or a benign URL and 2) identify the type of SQLI attack for each malicious URL. The model is first trained and then evaluated by employing thousands of benign and malicious URLs. The results of the experiments are presented in order to demonstrate the effectiveness of the proposed approach.

Keywords: neural networks, pattern recognition, SQL injection attacks, SQL injection attack classification, SQL injection attack detection

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Authors: Zineb Emrane

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This abstract addresses the issue of radicalization of young people in a context with background of radicalization, in North of Morocco, 5 terrorist of Madrid's Attacts on 11th March, were coming from this context. It were developed a study pilot that describing young people perception about the main causes that lead and motivate for radicalization. Whenever we talk about this topic, we obtain information from studies and investigations by specialists in field, but we don’t give voice to the protagonists who in many cases are victims, specifically, young people at social risk because of social factors. Extremist radicalization is an expanding phenomenon, that affect young people, in north of Morocco. They live in a context with radical background and at risk of social exclusion, their social, economic and familiar needs make them vulnerable. The extremist groups take advantage of this vulnerability to involve them in a process of radicalization, offering them an alternative environment where they can found all they are looking for. This study pilot approaches the main causes that lead and motivates young people to become radicals, analyzing their context with emphasis on influencing factors, and bearing in mind the analysis of young people about how the radical background affect them and their opinion this phenomenon. The pilot study was carried out through the following actions: - Group dynamics with young people to analyze the process of violent radicalization of young people. -A participatory workshop with members of organizations that work directly with young people at risk of radicalization. -Interviews with institutional managers -Participant observation. The implementation of actions has led to the conclusion that young people define violent radicalization as a sequential process, depending on the stage, it can be deconstructed. Young people recognize that they stop feeling belonging to their family, school and neighborhood when they see behavior contrary to what they consider good and evil. The emotional rupture and the search for references outside their circle, push them to sympathize with groups that have an extremist ideology and that offer them what they need. The radicalization is a process with different stages, the main causes and the factors which lead young people to use extremist violence are related their low level of belonging feeling to their context, and lack of critical thinking about important issues. The young people are in a vulnerable stage, searching their identity, a space in which they can be accepted, and when they don't find it they are easily manipulated and susceptible to being attracted by extremist groups.

Keywords: exclusion, radicalization, vulnerability, youth

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Authors: Katsumi Hirata

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Certain systems can function well only if they recognize the sound environment as humans do. In this research, we focus on sound classification by adopting a convolutional neural network and aim to develop a method that automatically classifies various environmental sounds. Although the neural network is a powerful technique, the performance depends on the type of input data. Therefore, we propose an approach via a slice bispectrogram, which is a third-order spectrogram and is a slice version of the amplitude for the short-time bispectrum. This paper explains the slice bispectrogram and discusses the effectiveness of the derived method by evaluating the experimental results using the ESC‑50 sound dataset. As a result, the proposed scheme gives high accuracy and stability. Furthermore, some relationship between the accuracy and non-Gaussianity of sound signals was confirmed.

Keywords: environmental sound, bispectrum, spectrogram, slice bispectrogram, convolutional neural network

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Authors: Auliya Adzillatin Uzhma, Ismu Rini Dwi Ari, I. Nyoman Suluh Wijaya

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Corporate Social Responsibility (CSR) programme in Pantai Harapan Jaya village is cultivation of mangrove and fishery capital distribution, to achieve the goal the CSR programme needed participation from the society in it. Moeliono in Fahrudin (2011) mentioned that participation from society is based by intrinsic reason from inside people it self and extrinsic reason from the other who related to him or from connection with other people. The fundamental connection who caused more boundaries from action which the organization can do called the social structure. The purpose of this research is to know the form of public participation and the density of the villager and people who is participated in CSR programme. This research use Social Network Analysis method by knew the Rate of Participation and Density. The result of the research is people who is involved in the programme is lived in Dusun Pondok Dua and they work in fisheries field. Rate of Participation is 11,61 and that means people involved in 11 or 12 activites of CSR Programme. The rate of participation of CSR Programme is categorized as high rate participation. The density value from the participant is 0.516 it’s mean that 51.6% of the people that participated is involved in the same step of CSR programme.

Keywords: community participation, social network analysis, corporate social responsibility, urban and regional studies

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Authors: Bencherif Kada

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In the forest management practice, landscape and Mediterranean forest are never posed as linked objects. But sustainable forestry requires the valorization of the forest landscape, and this aim involves assessing the spatial distribution of biodiversity by mapping forest landscaped units and subunits and by monitoring the environmental trends. This contribution aims to highlight, through object-oriented classifications, the landscaped biodiversity of the National Park of Tlemcen (Algeria). The methodology used is based on ground data and on the basic processing units of object-oriented classification, that are segments, so-called image-objects, representing a relatively homogenous units on the ground. The classification of Landsat Enhanced Thematic Mapper plus (ETM+) imagery is performed on image objects and not on pixels. Advantages of object-oriented classification are to make full use of meaningful statistic and texture calculation, uncorrelated shape information (e.g., length-to-width ratio, direction, and area of an object, etc.), and topological features (neighbor, super-object, etc.), and the close relation between real-world objects and image objects. The results show that per object classification using the k-nearest neighbor’s method is more efficient than per pixel one. It permits to simplify of the content of the image while preserving spectrally and spatially homogeneous types of land covers such as Aleppo pine stands, cork oak groves, mixed groves of cork oak, holm oak, and zen oak, mixed groves of holm oak and thuja, water plan, dense and open shrub-lands of oaks, vegetable crops or orchard, herbaceous plants, and bare soils. Texture attributes seem to provide no useful information, while spatial attributes of shape and compactness seem to be performant for all the dominant features, such as pure stands of Aleppo pine and/or cork oak and bare soils. Landscaped sub-units are individualized while conserving the spatial information. Continuously dominant dense stands over a large area were formed into a single class, such as dense, fragmented stands with clear stands. Low shrublands formations and high wooded shrublands are well individualized but with some confusion with enclaves for the former. Overall, a visual evaluation of the classification shows that the classification reflects the actual spatial state of the study area at the landscape level.

Keywords: forest, oaks, remote sensing, diversity, shrublands

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Authors: Bruno T. Gomes, José A. Menezes, Giordano Cabral

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With the popularity of smartphones, mobile apps emerge to meet the diverse needs, however the resources at the disposal are limited, either by the hardware, due to the low computing power, or the software, that does not have the same robustness of desktop environment. For example, in automatic audio classification (AC) tasks, musical information retrieval (MIR) subarea, is required a fast processing and a good success rate. However the mobile platform has limited computing power and the best AC tools are only available for desktop. To solve these problems the fast classifier suits, to mobile environments, the most widespread MIR technologies, seeking a balance in terms of speed and robustness. At the end we found that it is possible to enjoy the best of MIR for mobile environments. This paper presents the results obtained and the difficulties encountered.

Keywords: audio classification, audio extraction, environment mobile, musical information retrieval

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Authors: Helena Macedo, Larissa Tomaz, Levi Guimarães, Luís Cerqueira-Pinto, José Dinis-Carvalho

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In the context of retail logistics, the pursuit of operational efficiency and cost optimization involves a rigorous distinction between value-added and non-value-added activities. In today's competitive market, optimizing efficiency and reducing operational costs are paramount for retail businesses. This research paper focuses on the development of a classification model adapted to the retail sector, specifically examining internal logistics processes. Based on a comprehensive analysis conducted in a retail supermarket located in the north of Portugal, which covered various aspects of internal retail logistics, this study questions the concept of value and the definition of wastes traditionally applied in a manufacturing context and proposes a new way to assess activities in the context of internal logistics. This study combines quantitative data analysis with qualitative evaluations. The proposed classification model offers a systematic approach to categorize operations within the retail logistics chain, providing actionable insights for decision-makers to streamline processes, enhance productivity, and allocate resources more effectively. This model contributes not only to academic discourse but also serves as a practical tool for retail businesses, aiding in the enhancement of their internal logistics dynamics.

Keywords: lean retail, lean logisitcs, retail logistics, value-added and non-value-added

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Authors: Laheeb M. Ibrahim, Ibrahim A. Salih

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Biometrics is a technology that has been widely used in many official and commercial identification applications. The increased concerns in security during recent years (especially during the last decades) have essentially resulted in more attention being given to biometric-based verification techniques. Here, a novel fusion approach of palmprint, dental traits has been suggested. These traits which are authentication techniques have been employed in a range of biometric applications that can identify any postmortem PM person and antemortem AM. Besides improving the accuracy, the fusion of biometrics has several advantages such as increasing, deterring spoofing activities and reducing enrolment failure. In this paper, a first unimodel biometric system has been made by using (palmprint and dental) traits, for each one classification applying an artificial neural network and a hybrid technique that combines swarm intelligence and neural network together, then attempt has been made to combine palmprint and dental biometrics. Principally, the fusion of palmprint and dental biometrics and their potential application has been explored as biometric identifiers. To address this issue, investigations have been carried out about the relative performance of several statistical data fusion techniques for integrating the information in both unimodal and multimodal biometrics. Also the results of the multimodal approach have been compared with each one of these two traits authentication approaches. This paper studies the features and decision fusion levels in multimodal biometrics. To determine the accuracy of GAR to parallel system decision-fusion including (AND, OR, Majority fating) has been used. The backpropagation method has been used for classification and has come out with result (92%, 99%, 97%) respectively for GAR, while the GAR) for this algorithm using hybrid technique for classification (95%, 99%, 98%) respectively. To determine the accuracy of the multibiometric system for feature level fusion has been used, while the same preceding methods have been used for classification. The results have been (98%, 99%) respectively while to determine the GAR of feature level different methods have been used and have come out with (98%).

Keywords: back propagation neural network BP ANN, multibiometric system, parallel system decision-fusion, practical swarm intelligent PSO

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Authors: Ashiraliyev SHavkat

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Relevance of the topic: Diabetes mellitus in overweight people development and absence of treatment measures. Objective: to give patients the correct instructions on proper nutrition, to organize a network of preventive and therapeutic measures. Materials and methods: Multidisciplinary Tashkent Medical Academy. As a result of objective observations in patients who applied to the clinic, 28 11 overweight patients had to type 2 diabetes. Diabetesmellituswasdiagnosed. Results: 11.5 mmol / L on an empty stomach in the morning. EDT yes. Pathogenesis: fat content in the diet of patients with diabetes mellitus. Carbohydrate foods make up 60%. Eating disorders and physical inactivity As a result, the accumulation of glucose in the form of fat increases, and this is constantly in the blood, which led to an increase in the number of fatty acids. Clinic: Frequent fasting in 11 patients (hypothalamus). Associated with glucose deficiency), drinking 8-9 liters of water per day of blood in 7 people Systolic pressure 150 diastolic pressures 100. Sensation of ants in 3 people and poor eyesight in 5 people. Conclusion: Explain to patients that nutritional guidelines should be followed. Assign active movement in accordance with the energy entering the body.

Keywords: mellitus, diabetes, pathogenesis, clinic

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Authors: Dorota Kobus-Ostrowska

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Work for everyone, especially for person with disability is a condition in independence; it secures basic needs and develops manual and intellectual capabilities. The work is a source of income, and it builds and strengthens of self-esteem and competence. The purpose of this article is to identify work as an important factor in everyone’s life, despite Polish disabled persons rarely having the chance to undertake a job. In order to achieve this purpose, two methods were used: comparative and qualitative. The theoretical part of this article is based on studies of a wide range of Polish and foreign literature devoted to the issue of the occupational development of people with disabilities. The article was also enriched with the institutional and legal analysis types of support for people with disabilities in Poland. Currently, a Polish person with disability who wants to enter or return to the labor market is under a special protection. Those entities employing workers with disabilities may obtain a subsidy for the salary of a person with disabilities. Unfortunately, people with disability in Poland rarely participate in the workforce. The factors that contribute to this include the difficulty in obtaining work, the uncertainty of keeping it, and the low salary offered. Despite that domestic and foreign literature highlight the important role of disabled people as a workforce, very few people with disability in Poland are economically active.

Keywords: disabled person, employer, rehabilitation, work

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Authors: Bencherif Kada

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In forest management practice, landscape and Mediterranean forest are never posed as linked objects. But sustainable forestry requires the valorization of the forest landscape and this aim involves assessing the spatial distribution of biodiversity by mapping forest landscaped units and subunits and by monitoring the environmental trends. This contribution aims to highlight, through object-oriented classifications, the landscaped biodiversity of the National Park of Tlemcen (Algeria). The methodology used is based on ground data and on the basic processing units of object-oriented classification that are segments, so-called image-objects, representing a relatively homogenous units on the ground. The classification of Landsat Enhanced Thematic Mapper plus (ETM+) imagery is performed on image objects, and not on pixels. Advantages of object-oriented classification are to make full use of meaningful statistic and texture calculation, uncorrelated shape information (e.g., length-to-width ratio, direction and area of an object, etc.) and topological features (neighbor, super-object, etc.), and the close relation between real-world objects and image objects. The results show that per object classification using the k-nearest neighbor’s method is more efficient than per pixel one. It permits to simplify the content of the image while preserving spectrally and spatially homogeneous types of land covers such as Aleppo pine stands, cork oak groves, mixed groves of cork oak, holm oak and zen oak, mixed groves of holm oak and thuja, water plan, dense and open shrub-lands of oaks, vegetable crops or orchard, herbaceous plants and bare soils. Texture attributes seem to provide no useful information while spatial attributes of shape, compactness seem to be performant for all the dominant features, such as pure stands of Aleppo pine and/or cork oak and bare soils. Landscaped sub-units are individualized while conserving the spatial information. Continuously dominant dense stands over a large area were formed into a single class, such as dense, fragmented stands with clear stands. Low shrublands formations and high wooded shrublands are well individualized but with some confusion with enclaves for the former. Overall, a visual evaluation of the classification shows that the classification reflects the actual spatial state of the study area at the landscape level.

Keywords: forest, oaks, remote sensing, biodiversity, shrublands

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Authors: Krishna Prasad Regmi, Jun-Bo Tu, Cheng-Qun Hou, Li-Feng Li

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Maxillofacial trauma in a pediatric group of patients is particularly challenging, as these patients have significant differences from adults as far as the facial skeleton is concerned. Mandibular condylar fractures are common presentations to hospitals across the globe and remain the most important cause of temporomandibular joint (TMJ) ankylosis. The etiology and epidemiology of pediatric trauma involving the diacapitular condylar fractures (DFs) have been reported in a large series of patients. Nevertheless, little is known about treatment protocols for DFs in children. Accordingly, the treatment modalities for the management of pediatric fractures also differ. We suggest following the PDA and intracapsular ABC classification of condylar fracture to increase the overall postoperative satisfaction level that bypasses the change of subjective feelings of patients’ from preoperative to the postoperative condition. At the same time, use of 3-D technology and surgical navigation may also increase treatment accuracy.

Keywords: maxillofacial trauma, diacapitular fracture, condylar fracture, PDA classification

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Authors: Ali Kirkbas

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R peaks in an electrocardiogram (ECG) are signs of cardiac activity in individuals that reveal valuable information about cardiac abnormalities, which can lead to mortalities in some cases. This paper examines the problem of detecting R-peaks in ECG signals, which is a two-class pattern classification problem in fact. To handle this problem with a reliable high accuracy, we propose to use the common vector approach which is a successful machine learning algorithm. The dataset used in the proposed method is obtained from MIT-BIH, which is publicly available. The results are compared with the other popular methods under the performance metrics. The obtained results show that the proposed method shows good performance than that of the other. methods compared in the meaning of diagnosis accuracy and simplicity which can be operated on wearable devices.

Keywords: ECG, R-peak classification, common vector approach, machine learning

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Authors: Marina Yurievna Aleksandrova

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Research of the Holocaust retains value not only for history but also for sociology and psychology. One of the most important fields of study is how people were coping during and after this traumatic event. The aim of this paper is to identify the main contexts of the topic of love and to determine which contexts are more characteristic for different groups of victims of the Holocaust (gender, nationality, age). In this research, transcripts of interviews with Holocaust victims that were collected during 1946 for the "Voices of the Holocaust" project were used as data. Main contexts were analyzed with methods of network analysis and latent semantic analysis and classified by gender, age, and nationality with random forest. The results show that love is articulated and described significantly differently for male and female informants, nationality is shown results with lower values of quality metrics, as well as the age.

Keywords: Holocaust, latent semantic analysis, network analysis, text-mining, random forest

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Authors: Marielcio Lacerda, Angelo Paulino, Elcio Shiguemori, Alvaro Damiao, Lamartine Guimaraes, Camila Anjos

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Accurate information about the terrain is extremely important in disaster management activities or conflict. This paper proposes the use of the Unmanned Aircraft Systems (UAS) at the identification of Airdrop Zones (AZs) and Helicopter Landing Zones (HLZs). In this paper we consider the AZs the zones where troops or supplies are dropped by parachute, and HLZs areas where victims can be rescued. The use of digital image processing enables the automatic generation of an orthorectified mosaic and an actual Digital Surface Model (DSM). This methodology allows obtaining this fundamental information to the terrain’s comprehension post-disaster in a short amount of time and with good accuracy. In order to get the identification and classification of AZs and HLZs images from DJI drone, model Phantom 4 have been used. The images were obtained with the knowledge and authorization of the responsible sectors and were duly registered in the control agencies. The flight was performed on May 24, 2017, and approximately 1,300 images were obtained during approximately 1 hour of flight. Afterward, new attributes were generated by Feature Extraction (FE) from the original images. The use of multispectral images and complementary attributes generated independently from them increases the accuracy of classification. The attributes of this work include the Declivity Map and Principal Component Analysis (PCA). For the classification four distinct classes were considered: HLZ 1 – small size (18m x 18m); HLZ 2 – medium size (23m x 23m); HLZ 3 – large size (28m x 28m); AZ (100m x 100m). The Decision Tree method Random Forest (RF) was used in this work. RF is a classification method that uses a large collection of de-correlated decision trees. Different random sets of samples are used as sampled objects. The results of classification from each tree and for each object is called a class vote. The resulting classification is decided by a majority of class votes. In this case, we used 200 trees for the execution of RF in the software WEKA 3.8. The classification result was visualized on QGIS Desktop 2.12.3. Through the methodology used, it was possible to classify in the study area: 6 areas as HLZ 1, 6 areas as HLZ 2, 4 areas as HLZ 3; and 2 areas as AZ. It should be noted that an area classified as AZ covers the classifications of the other classes, and may be used as AZ, HLZ of large size (HLZ3), medium size (HLZ2) and small size helicopters (HLZ1). Likewise, an area classified as HLZ for large rotary wing aircraft (HLZ3) covers the smaller area classifications, and so on. It was concluded that images obtained through small UAV are of great use in calamity situations since they can provide data with high accuracy, with low cost, low risk and ease and agility in obtaining aerial photographs. This allows the generation, in a short time, of information about the features of the terrain in order to serve as an important decision support tool.

Keywords: disaster management, unmanned aircraft systems, helicopter landing zones, airdrop zones, random forest

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Authors: Elizabeth Malebogo Mosepele

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Road transport has become increasingly common in the world; people rely on road networks for transportation purpose on a daily basis. However, environmental impact of roads on surrounding landscapes extends their potential effects even further. This study investigates the impact of road network on natural vegetation. The study will provide baseline knowledge regarding roadside vegetation and would be helpful in future for conservation of biodiversity along the road verges and improvements of road verges. The general hypothesis of this study is that the amount and condition of road side vegetation could be explained by road network conditions. Remote sensing techniques were used to analyze vegetation conditions. Landsat 8 OLI image was used to assess vegetation cover condition. NDVI image was generated and used as a base from which land cover classes were extracted, comprising four categories viz. healthy vegetation, degraded vegetation, bare surface, and water. The classification of the image was achieved using the supervised classification technique. Road networks were digitized from Google Earth. For observed data, transect based quadrats of 50*50 m were conducted next to road segments for vegetation assessment. Vegetation condition was related to road network, with the multinomial logistic regression confirming a significant relationship between vegetation condition and road network. The null hypothesis formulated was that 'there is no variation in vegetation condition as we move away from the road.' Analysis of vegetation condition revealed degraded vegetation within close proximity of a road segment and healthy vegetation as the distance increase away from the road. The Chi Squared value was compared with critical value of 3.84, at the significance level of 0.05 to determine the significance of relationship. Given that the Chi squared value was 395, 5004, the null hypothesis was therefore rejected; there is significant variation in vegetation the distance increases away from the road. The conclusion is that the road network plays an important role in the condition of vegetation.

Keywords: Chi squared, geographic information system, multinomial logistic regression, remote sensing, road side vegetation

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Authors: Erhong Sun, Xuchun Ye

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Technophobia, namely the fear or dislike of modern advanced technologies, plays a central role in age-related digital divides and is considered a new risk factor for older adults, which can affect the daily lives of people through low adherence to digital living. Indeed, there is considerable heterogeneity in the group of older adults who feel technophobia. Therefore, the aim of this study was to identify different technophobia typologies of older people and to examine their associations with the subjective age factor. A sample of 704 retired elderly over the age of 55 was recruited in China. Technophobia and subjective age were assessed with a questionnaire, respectively. Latent profile analysis was used to identify technophobia subgroups, using three dimensions including techno-anxiety, techno-paranoia, and privacy concerns as indicators. The association between the identified technophobia subgroups and subjective age was explored. In summary, four different technophobia typologies were identified among older adults in China. Combined with an investigation of personal background characteristics and subjective age, it draws a more nuanced image of the technophobia phenome among older adults in China. First, not all older adults suffer from technophobia, with about half of the elderly subjects belonging to the profiles of “Low-technophobia” and “Medium-technophobia.” Second, privacy concern plays an important role in the classification of technophobia among older adults. Third, subjective age might be a protective factor for technophobia in older adults. Although the causal direction between identified technophobia typologies and subjective age remains uncertain, our suggests that future interventions should better focus on subjective age by breaking the age stereotype of technology to reduce the negative effect of technophobia on older. Future development of this research will involve extensive investigation of the detailed impact of technophobia in senior populations, measurement of the negative outcomes, as well as formulation of innovative educational and clinical pathways.

Keywords: technophobia, older adults, latent profile analysis, subjective age

Procedia PDF Downloads 75