Search results for: gender specific data

Authors: Agria Rhamdhan

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WhatsApp as the most popular mobile messaging app has been used as evidence in many criminal cases. As the use of mobile messages generates large amounts of data, forensic investigation faces the challenge of large data problems. The hardest part of finding this important evidence is because current practice utilizes tools and technique that require manual analysis to check all messages. That way, analyze large sets of mobile messaging data will take a lot of time and effort. Our work offers methodologies based on forensic triage to reduce large data to manageable sets resulting easier to do detailed reviews, then show the results through interactive visualization to show important term, entities and relationship through intelligent ranking using Term Frequency-Inverse Document Frequency (TF-IDF) and Latent Dirichlet Allocation (LDA) Model. By implementing this methodology, investigators can improve investigation processing time and result's accuracy.

Keywords: forensics, triage, visualization, WhatsApp

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Authors: Adekunle O. Afolabi, Pekka Toivanen

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The world is expected to experience growth in the number of ageing population, and this will bring about high cost of providing care for these valuable citizens. In addition, many of these live with chronic diseases that come with old age. Providing adequate care in the face of rising costs and dwindling personnel can be challenging. However, advances in technologies and emergence of the Internet of Things are providing a way to address these challenges while improving care giving. This study proposes the integration of recommendation systems into homecare to provide real-time recommendations for effective management of people receiving care at home and those living with chronic diseases. Using the simplified Training Logic Concept, stakeholders and requirements were identified. Specific requirements were gathered from people living with cancer. The solution designed has two components namely home and community, to enhance recommendations sharing for effective care giving. The community component of the design was implemented with the development of a mobile app called Recommendations Sharing Community for Aged and Chronically Ill People (ReSCAP). This component has illustrated the possibility of real-time recommendations, improved recommendations sharing among care receivers and between a physician and care receivers. Full implementation will increase access to health data for better care decision making.

Keywords: recommendation systems, Internet of Things, healthcare, homecare, real-time

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Authors: Jamila Fakchich, Mostafa Jamila Lazaar Elachouri, Lakhder Fakchich, Fatna Ouali, Abd Errazzak Belkacem

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Diabetes is a chronic metabolic disease that has a significant impact on the health, quality of life, and life expectancy of patients as well as the health care system. By its nature diabetes, is a multisystem disease with wide-ranging complication that span nearly all region of the body. This epidemic problem, however, is not unique to the industrialized society, but has also hardly struck the developing countries. In Morocco, as developing country, there is an epidemic rise in diabetes, with ensuing concern about the management and control of this disease; it began a chronic burdensome disease of largely middle-aged and elderly people, with a long course and serious complications often resulting in high death-rate, the treatment of diabetes spent vast amount of resources including medicines, diets, physical training. Treatment of this disease is considered problematic due to the lack of effective and safe drugs capable of inducing sustained clinical, biochemical, and histological cure. In Moroccan society, the phytoremedies are some times the only affordable sources of healthcare, particularly for the people in remote areas. In this paper, we present a synthesis work obtained from the ethnobotanical data reported in different specialized journals. A Synthesis of four published ethnobotanical studies that have been carried out in different region of Morocco by different team seekers during the period from 1997 to 2015. Medicinal plants inventoried by different seekers in four Moroccan’s areas have been regrouped and codified, then, Factorial Analysis (FA) and Principal Components Analysis (PCA) are used to analyse the aggregated data from the four studies and plants are classified according to their frequency of use by population. Our work deals with an attempt to gather information on some traditional uses of medicinal plants from different regions of Morocco, also, it was designed to give a set of medicinal plants commonly used by Moroccan people in the treatment of diabetes; In this paper, we intended to provide a basic knowledge about plant species used by Moroccan society for treatment of diabetes. One of the most interesting aspects of this type of works is to assess the relative cultural importance of medicinal plants for specific illnesses and exploring its usefulness in the context of diabetes.

Keywords: Morocco, medicinal plants, ethnobotanical, diabetes, phytoremedies

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Authors: Mohkammad Nur Cahyadi, Hepi Hapsari Handayani, Agus Budi Raharjo, Ronny Mardianto, Daud Wahyu Imani, Arizal Bawazir, Luki Adi Triawan

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PDAM (local water company) determines customer charges by considering the customer's building or house. Charges determination significantly affects PDAM income and customer costs because the PDAM applies a subsidy policy for customers classified as small households. Periodic updates are needed so that pricing is in line with the target. A thorough customer survey in Surabaya is needed to update customer building data. However, the survey that has been carried out so far has been by deploying officers to conduct one-by-one surveys for each PDAM customer. Surveys with this method require a lot of effort and cost. For this reason, this research offers a technology called moblie mapping, a mapping method that is more efficient in terms of time and cost. The use of this tool is also quite simple, where the device will be installed in the car so that it can record the surrounding buildings while the car is running. Mobile mapping technology generally uses lidar sensors equipped with GNSS, but this technology requires high costs. In overcoming this problem, this research develops low-cost mobile mapping technology using a webcam camera sensor added to the GNSS and IMU sensors. The camera used has specifications of 3MP with a resolution of 720 and a diagonal field of view of 78⁰. The principle of this invention is to integrate four camera sensors, a GNSS webcam, and GPS to acquire photo data, which is equipped with location data (latitude, longitude) and IMU (roll, pitch, yaw). This device is also equipped with a tripod and a vacuum cleaner to attach to the car's roof so it doesn't fall off while running. The output data from this technology will be analyzed with artificial intelligence to reduce similar data (Cosine Similarity) and then classify building types. Data reduction is used to eliminate similar data and maintain the image that displays the complete house so that it can be processed for later classification of buildings. The AI method used is transfer learning by utilizing a trained model named VGG-16. From the analysis of similarity data, it was found that the data reduction reached 50%. Then georeferencing is done using the Google Maps API to get address information according to the coordinates in the data. After that, geographic join is done to link survey data with customer data already owned by PDAM Surya Sembada Surabaya.

Keywords: mobile mapping, GNSS, IMU, similarity, classification

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Authors: Maria Magdy Danial Riad

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Background: In the United Kingdom (UK), pharmacists' roles have expanded considerably in recent decades to encompass clinical practice through more direct patient care. However, dispensing and compounding remain core activities for pharmacists. A lack of marketed preparations for species-specific animal use results in veterinary pharmacy practice compounding, retaining its prominence. Current participation by pharmacists to support this sphere of practice would appear to be minimal. Objectives: This study was undertaken to determine the opinions and views toward the practice of veterinary pharmacy by a cross-sectional group of pharmacists. Methods: Research data were collected via a self-administered survey questionnaire distributed at the 2012 annual conference of the Royal Pharmaceutical Society. Sampling was purposive, with a random distribution of the questionnaire to pharmacists during the conference sessions. Key findings: Interaction by pharmacists with veterinary pharmacies is currently minimal, primarily due to a lack of knowledge of veterinary medicines. Respondents revealed a lack of veterinary pharmacy courses during their undergraduate studies. This has led to situations where some veterinary prescriptions are dispensed without adequate checks being performed by the pharmacist. Pharmacists, on occasion, do not dispense veterinary prescriptions presented to them due to insufficient knowledge of veterinary medicines and/or a lack of consultable reference sources. The effect on practice is that pharmacists do not always participate as fully as would seem logical. Conclusions: Pharmacists' participation in veterinary pharmacy is limited by a lack of knowledge of veterinary medicines, mostly resulting from inadequate tuition on veterinary pharmacy during their initial education.

Keywords: veterinary pharmacy, veterinary medicines, pharmacy education, pharmacists continuing professional development

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Authors: Abraham Motlhabane

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This research analysed the written views of science education students regarding the teaching of laboratory work using the online mode. The research adopted the qualitative methodology. The qualitative research was aimed at investigating small and distinct groups normally regarded as a single-site study. Qualitative research was used to describe and analyze the phenomena from the student’s perspective. This means the research began with assumptions of the world view that use theoretical lenses of research problems inquiring into the meaning of individual students. The research was conducted with three groups of students studying for Postgraduate Certificate in Education, Bachelor of Education and honors Bachelor of Education respectively. In each of the study programmes, the science education module is compulsory. Five science education students from each study programme were purposively selected to participate in this research. Therefore, 15 students participated in the research. In order to analysis the data, the data were first printed and hard copies were used in the analysis. The data was read several times and key concepts and ideas were highlighted. Themes and patterns were identified to describe the data. Coding as a process of organising and sorting data was used. The findings of the study are very diverse; some students are in favour of online laboratory whereas other students argue that science can only be learnt through hands-on experimentation.

Keywords: online learning, laboratory work, views, perceptions

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Authors: Y. Bai, M. Bodlak, V. Frolov, S. Huber, V. Jary, I. Konorov, D. Levit, J. Novy, D. Steffen, O. Subrt, M. Virius

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Modern experiments in high energy physics impose great demands on the reliability, the efficiency, and the data rate of Data Acquisition Systems (DAQ). This contribution focuses on the development and deployment of the new communication library DIALOG for the intelligent, FPGA-based Data Acquisition System (iFDAQ) of the COMPASS experiment at CERN. The iFDAQ utilizing a hardware event builder is designed to be able to readout data at the maximum rate of the experiment. The DIALOG library is a communication system both for distributed and mixed environments, it provides a network transparent inter-process communication layer. Using the high-performance and modern C++ framework Qt and its Qt Network API, the DIALOG library presents an alternative to the previously used DIM library. The DIALOG library was fully incorporated to all processes in the iFDAQ during the run 2016. From the software point of view, it might be considered as a significant improvement of iFDAQ in comparison with the previous run. To extend the possibilities of debugging, the online monitoring of communication among processes via DIALOG GUI is a desirable feature. In the paper, we present the DIALOG library from several insights and discuss it in a detailed way. Moreover, the efficiency measurement and comparison with the DIM library with respect to the iFDAQ requirements is provided.

Keywords: data acquisition system, DIALOG library, DIM library, FPGA, Qt framework, TCP/IP

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Authors: J. K. Alhassan, S. A. Lawal

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This work is on decision tree-based classification for the disbursement of scholarship. Tree-based data mining classification technique is used in other to determine the generic rule to be used to disburse the scholarship. The system based on the defined rules from the tree is able to determine the class (status) to which an applicant shall belong whether Granted or Not Granted. The applicants that fall to the class of granted denote a successful acquirement of scholarship while those in not granted class are unsuccessful in the scheme. An algorithm that can be used to classify the applicants based on the rules from tree-based classification was also developed. The tree-based classification is adopted because of its efficiency, effectiveness, and easy to comprehend features. The system was tested with the data of National Information Technology Development Agency (NITDA) Abuja, a Parastatal of Federal Ministry of Communication Technology that is mandated to develop and regulate information technology in Nigeria. The system was found working according to the specification. It is therefore recommended for all scholarship disbursement organizations.

Keywords: classification, data mining, decision tree, scholarship

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Authors: Mariam Azam, Sajjad Ur Rahman, Mukarram Bashir, Muhammad Tahir, Seemal Javaid, Jawad, Aoun Muhammad, Muhammad Zohaib, Hannan Khan

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Products of microbial origin are of great importance as they have proved their value in healthcare and nutrition, use of these microbial metabolites acquired from partially fermented soya hulls and wheat bran along with Saccharomyces cerevisiae (DL-22 S/N) substantiates to be a great source for an increase in the total milk production and quality yield.1×109 CFU/ml cells of Saccharomyces cerevisiae (DL-22 S/N) were further grown under in-vivo conditions for the assessment of quality milk production. Two groups with twelve cows, each having the same physical characteristics (Group A and Group B), were under study, Group A was daily fed with 12gm of biological metabolites and 22% protein-pelleted feed. On the other hand, the animals of Group B were provided with no metabolites in their feed. In thirty days of trial, improvement in the overall health, body score, milk protein, milk fat, yield, incidence rate of mastitis, ash, and solid not fat (SNF) was observed. The collected data showed that the average quality milk production was elevated up to 0.45 liter/h/d. However, a reduction in the milk fats up to 0.45% and uplift in the SNF value up to 0.53% of cow milk was also observed. At the same time, the incidence rate of mastitis recorded for the animals under trial was reduced to half, and improved non specific immunity was reported.

Keywords: microbial metabolites, post-biotics, animal supplements, animal nutrition, proteins, animal production, fermentation

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Authors: Sandra Figueiredo, Margarida Alves Martins, Carlos Silva, Cristina Simões

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This study integrates a larger research empirical project that examines second language (SL) learners’ profiles and valid procedures to perform complete and diagnostic assessment in schools. 102 learners of Portuguese as a SL aged 7 and 17 years speakers of distinct home languages were assessed in several linguistic tasks. In this article, we focused on writing performance in the specific task of narrative essay composition. The written outputs were measured using the score in six components adapted from an English SL assessment context (Alberta Education): linguistic vocabulary, grammar, syntax, strategy, socio-linguistic, and discourse. The writing processes and strategies in Portuguese language used by different immigrant students were analysed to determine features and diversity of deficits on authentic texts performed by SL writers. Differentiated performance was based on the diversity of the following variables: grades, previous schooling, home language, instruction in first language, and exposure to Portuguese as Second Language. Indo-Aryan languages speakers showed low writing scores compared to their peers and the type of language and respective cognitive mapping (such as Mandarin and Arabic) was the predictor, not linguistic distance. Home language instruction should also be prominently considered in further research to understand specificities of cognitive academic profile in a Romance languages learning context. Additionally, this study also examined the teachers representations that will be here addressed to understand educational implications of second language teaching in psychological distress of different minorities in schools of specific host countries.

Keywords: home language, immigrant students, Portuguese language, second language, writing assessment

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Authors: Bharatendra Rai

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Predictive data analysis and modeling involving machine learning techniques become challenging in presence of too many explanatory variables or features. Presence of too many features in machine learning is known to not only cause algorithms to slow down, but they can also lead to decrease in model prediction accuracy. This study involves housing dataset with 79 quantitative and qualitative features that describe various aspects people consider while buying a new house. Boruta algorithm that supports feature selection using a wrapper approach build around random forest is used in this study. This feature selection process leads to 49 confirmed features which are then used for developing predictive random forest models. The study also explores five different data partitioning ratios and their impact on model accuracy are captured using coefficient of determination (r-square) and root mean square error (rsme).

Keywords: housing data, feature selection, random forest, Boruta algorithm, root mean square error

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Authors: M. M. Ali, Ahmed Al- Ani, Derek Eamus, Daniel K. Y. Tan

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In this glasshouse study, we developed the new image-based non-destructive technique for detecting leaf P status of different crops such as cotton, tomato and lettuce. Plants were allowed to grow on nutrient media containing different P concentrations, i.e. 0%, 50% and 100% of recommended P concentration (P0 = no P, L; P1 = 2.5 mL 10 L-1 of P and P2 = 5 mL 10 L-1 of P as NaH2PO4). After 10 weeks of growth, plants were harvested and data on leaf P contents were collected using the standard destructive laboratory method and at the same time leaf images were collected by a handheld crop image sensor. We calculated leaf area, leaf perimeter and RGB (red, green and blue) values of these images. This data was further used in the linear discriminant analysis (LDA) to estimate leaf P contents, which successfully classified these plants on the basis of leaf P contents. The data indicated that P deficiency in crop plants can be predicted using the image and morphological data. Our proposed non-destructive imaging method is precise in estimating P requirements of different crop species.

Keywords: image-based techniques, leaf area, leaf P contents, linear discriminant analysis

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Authors: Lukumba Phiri, Simon Tembo, Kumbuso Joshua Nyoni

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In Zambia recent initiatives by various power operators like ZESCO, CEC, and consumers like the mines to upgrade power systems into smart grids target an even tighter integration with information technologies to enable the integration of renewable energy sources, local and bulk generation, and demand response. Thus, for the reliable operation of smart grids, its information infrastructure must be secure and reliable in the face of both failures and cyberattacks. Due to the nature of the systems, ICS/SCADA cybersecurity and governance face additional challenges compared to the corporate networks, and critical systems may be left exposed. There exist control frameworks internationally such as the NIST framework, however, there are generic and do not meet the domain-specific needs of the SCADA systems. Zambia is also lagging in cybersecurity awareness and adoption, therefore there is a concern about securing ICS controlling key infrastructure critical to the Zambian economy as there are few known facts about the true posture. In this paper, we introduce a stochastic Edged-based Anomaly Detection for SCADA systems (SEADS) framework for threat modeling and risk assessment. SEADS enables the calculation of steady-steady probabilities that are further applied to establish metrics like system availability, maintainability, and reliability.

Keywords: anomaly, availability, detection, edge, maintainability, reliability, stochastic

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Authors: Ming Ze Kao

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Static magnetic fields (SMF) are widely used in several medical applications, especially in diagnosis of tumors. However, biological effects of the SMFs on modulating cell physiology through the Lorentz force, which is highly frequency and magnitude dependent, remain to be elucidated. Specific patterns from SMFs of static MF, delivered by means of Halbach array magnets with a gradient increment of 6.857mT/mm from center to border, were found to have profound inhibitory effect on the growth rate of human cell line derived from Nasopharyngeal carcinoma patients. The SMFs, which were shown to be noncontact, selectively impact rapid dividing cells while quiescent cells stay intact. The phenomenon acts in two modes: the arrest of cell proliferation in the G2/M phase and destruction of cell mitosis in cell division. First mode is manifested by impacting the proper formation of mitotic spindle, whereas the second results in disintegration of the cancer cell. Both modes are demonstrated when SMF was applied for 24 hours to cancer cells, the results revealed that metaphase arrest during mitosis due to activation of DNA damage response (DDR), resulting in high expression of ATM-NBS1-CHEK signaling pathways and higher G2/M phase ratio compared with control group. Here, experimental data suggest that the SMFs cause activation of cell cycle checkpoints, which implies the MFs as a potential therapeutic modality as a sensitizer for radiotherapy or chemotherapy.

Keywords: static magnetic field, DNA damage response, Halbach array, magnetic therapy

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Authors: N. F. Mikhailova, M. E. Fattakhova, M. A. Mironova, E. V. Vyacheslavova

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For the mental and social adaptation of the deaf and hard-of-hearing people, cultural and social aspects - the formation of identity (acculturation) and educational conditions – are highly significant. We studied 137 deaf and hard-of-hearing students in different educational situations. We used these methods: Big Five (Costa & McCrae, 1997), TRF (Becker, 1989), WCQ (Lazarus & Folkman, 1988), self-esteem, and coping strategies (Jambor & Elliott, 2005), self-stigma scale (Mikhailov, 2008). Type of self-identification of students depended on the degree of deafness, type of education, method of communication in the family: large hearing loss, education in schools for deaf, and gesture communication increased the likelihood of a 'deaf' acculturation. Less hearing loss, inclusive education in public school or school for the hearing-impaired, mixed communication in the family contributed to the formation of 'hearing' acculturation. The choice of specific coping depended on the degree of deafness: a large hearing loss increased coping 'withdrawal into the deaf world' and decreased 'bicultural skills' coping. People with mild hearing loss tended to cover-up it. In the context of ongoing discussion, we researched personality characteristics in deaf and hard on-hearing students, coping and other deafness associated factors depending on their acculturation type. Students who identified themselves with the 'hearing world' had a high self-esteem, a higher level of extraversion, self-awareness, personal resources, willingness to cooperate, better psychological health, emotional stability, higher ability to empathy, a greater satiety of life with feelings and sense and high sense of self-worth. They also actively used strategies, problem-solving, acceptance of responsibility, positive revaluation. Student who limited themselves within the culture of deaf people had more severe hearing loss and accordingly had more communication barriers. Lack of use or seldom use of coping strategies by these students point at decreased level of stress in their life. Their self-esteem have not been challenged in the specific social environment of the students with the same severity of defect, and thus this environment provided sense of comfort (we can assume that from the high scores on psychological health, personality resources, and emotional stability). Students with bicultural acculturation had higher level of psychological resources - they used Positive Reappraisal coping more often and had a higher level of psychological health. Lack of belonging to certain culture (marginality) leads to personality disintegration, social and psychological disadaptation: deaf and hard-of-hearing students with marginal identification had a lower self-estimation level, worse psychological health and personal resources, lower level of extroversion, self-confidence and life satisfaction. They, in fact, become 'risk group' (many of them dropped out of universities, divorced, and one even ended up in the ranks of ISIS). All these data argue the importance of cultural 'anchor' for people with hearing deprivation. Supported by the RFBR No 19-013-00406.

Keywords: acculturation, coping, deafness, marginality

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Authors: Rushiraj Heshi, Smriti Bhandari

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Master Data Management requires creation of Central repository, applying constraints on Repository and designing processes to manage data. Designing of Repository, constraints on repository and business processes is very tedious and time consuming task for large Enterprise. Hence Visual Repository, constraints and Process (Workflow) modeling is the most critical step in Master Data Management.In this paper, we realize a Visual Modeling tool for implementing Repositories, Constraints and Processes based on Eclipse Plugin using GMF/EMF which follows principles of Model Driven Engineering (MDE).

Keywords: EMF, GMF, GEF, repository, constraint, process

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Authors: Radyah Ivan, Khanferyan Roman

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Milk and dairy products are an important component of a balanced diet. Dairy products represent a heterogeneous food group of solid, semi-solid and liquid, fermented or non-fermented foods, each differing in nutrients such as fat and micronutrient content. Deficiency of milk and dairy products contributes a impact on the main health parameters of the various age groups of the population. The goal of this study was to analyze of the frequency of the consumption of milk and various groups of dairy products by students and its association with their body mass index (BMI), body composition and other physiological parameters. 388 full-time students of the Medical Institute of RUDN University (185 male and 203 female, average age was 20.4+2.2 and 21.9+1.7 y.o., respectively) took part in the cross-sectional study. Anthropometric measurements, estimation of BMI and body composition were analyzed by bioelectrical impedance analysis. The frequency of consumption of the milk and various groups of dairy products was studied using a modified questionnaire on the frequency of consumption of products. Due to the questionnaire data on the frequency of consumption of the diary products, it have been demonstrated that only 11% of respondents consume milk daily, 5% - cottage cheese, 4% and 1% - fermented natural and with fillers milk products, respectively, hard cheese -4%. The study demonstrated that about 16% of the respondents did not consume milk at all over the past month, about one third - cottage cheese, 22% - natural sour-milk products and 18% - sour-milk products with various fillers. hard cheeses and pickled cheeses didn’t consume 9% and 26% of respondents, respectively. We demonstrated the gender differences in the characteristics of consumer preferences were revealed. Thus female students are less likely to use cream, sour cream, soft cheese, milk comparing to male students. Among female students the prevalence of persons with overweight was higher (25%) than among male students (19%). A modest inverse relationship was demonstrated between daily milk intake, BMI, body composition parameters and diary products consumption (r=-0.61 and r=-0.65). The study showed daily insufficient milk and dairy products consumption by students and due to this it have been demonstrated the relationship between the low and rare consumption of diary products and main parameters of indicators of physical activity and health indicators.

Keywords: frequency of consumption, milk, dairy products, physical development, nutrition, body mass index.

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Authors: Thu Thuy Pham, Thi Chau Loan Tran, Van Duy Nguyen

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Marine fungi play an important role in the marine ecosystems. Marine fungi also supply biomass and metabolic products of industrial value. Currently, the biodiversity of marine fungi along the coastal areas of Vietnam has not yet been studied fully. The objective of this study is to assess the spatial and temporal diversity of planktonic fungi from the coastal waters of Nha Trang Bay and Van Phong Bay in Central Vietnam using culture-dependent and independent approach. Using culture-dependent approach, filamentous fungi and yeasts were isolated on selective media and then classified by phenotype and genotype based on the sequencing of ITS (internal transcribed spacers) regions of rDNA with two primer pairs (ITS1F_KYO2 and ITS4; NS1 and NS8). Using culture-independent approach, environmental DNA samples were isolated and amplified using fungal-specific ITS primer pairs. A total of over 160 strains were isolated from 10 seawater sampling stations at 50 cm depth. They were classified into diverse genera and species of both yeast and mold. At least 5 strains could be potentially novel species. Our results also revealed that planktonic fungi were molecularly diverse with hundreds of phylotypes recovered across these two bays. The results of the study provide data about the distribution and taxonomy of mycoplankton in this area, thereby allowing assessment of their positive role in the biogeochemical cycle of coastal ecosystems and the development of new bioactive compounds for industrial applications.

Keywords: biodiversity, ITS, marine fungi, Nha Trang Bay, Van Phong Bay

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Authors: Gifty Kumadey, Albert Tchey Agbenyegah

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(i) Overview and research goal(s): This study aims to address research gaps in the Ghanaian pharmaceutical industry by examining the impact of environmental supply chain management (ESCM) practices on environmental and operational performance. Previous studies have provided inconclusive evidence on the relationship between ESCM practices and environmental and operational performance. The research aims to provide a clearer understanding of the impact of ESCM practices on environmental and operational performance in the context of the Ghanaian pharmaceutical industry. Limited research has been conducted on ESCM practices in developing countries, particularly in Africa. The study aims to bridge this gap by examining the drivers and barriers specific to the pharmaceutical industry in Ghana. The research aims to analyze the impact of ESCM practices on the achievement of Sustainable Development Goals (SDGs) in the Ghanaian pharmaceutical industry, focusing on SDGs 3, 12, 13, and 17. It also explores the potential for partnerships and collaborations to advance ESCM practices in the pharmaceutical industry. The research hypotheses suggest that pressure from stakeholder positively influences the adoption of ESCM practices in the Ghanaian pharmaceutical industry. By addressing these goals, the study aims to contribute to sustainable development initiatives and offer practical recommendations to enhance ESCM A practices in the industry. (ii) Research methods and data: This study uses a quantitative research design to examine the drivers and barriers to environmental supply chain management in the pharmaceutical industry in Accra.The sample size is approximately 150 employees, with senior and middle-level managers from pharmaceutical industry of Ghana. A purposive sampling technique is used to select participants with relevant knowledge and experience in environmental supply chain management. Data will be collected using a structured questionnaire using Likert scale responses. Descriptive statistics will be used to analyze the data and provide insights into current practices and their impact on environmental and operational performance. (iii) Preliminary results and conclusions: Main contributions: Identifying drivers/barriers to ESCM in Ghana's pharmaceutical industry, evaluating current ESCM practices, examining impact on performance, providing practical insights, contributing to knowledge on ESCM in Ghanaian context. The research contributes to SDGs 3, 9, and 12 by promoting sustainable practices and responsible consumption in the industry. The study found that government rules and regulations are the most critical drivers for ESCM adoption, with senior managers playing a significant role. However, employee and competitor pressures have a lesser impact. The industry has made progress in implementing certain ESCM practices, but there is room for improvement in areas like green distribution and reverse logistics. The study emphasizes the importance of government support, management engagement, and comprehensive implementation of ESCM practices in the industry. Future research should focus on overcoming barriers and challenges to effective ESCM implementation.

Keywords: environmental supply chain, sustainable development goal, ghana pharmaceutical industry, government regulations

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Authors: Amirreza Fazely Hamedani, Muzzamil Aziz, Philipp Wieder, Ramin Yahyapour

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Software-defined networking in recent years came into the sight of so many network designers as a successor to the traditional networking. Unlike traditional networks where control and data planes engage together within a single device in the network infrastructure such as switches and routers, the two planes are kept separated in software-defined networks (SDNs). All critical decisions about packet routing are made on the network controller, and the data level devices forward the packets based on these decisions. This type of network is vulnerable to DDoS attacks, degrading the overall functioning and performance of the network by continuously injecting the fake flows into it. This increases substantial burden on the controller side, and the result ultimately leads to the inaccessibility of the controller and the lack of network service to the legitimate users. Thus, the protection of this novel network architecture against denial of service attacks is essential. In the world of cybersecurity, attacks and new threats emerge every day. It is essential to have tools capable of managing and analyzing all this new information to detect possible attacks in real-time. These tools should provide a comprehensive solution to automatically detect, predict and prevent abnormalities in the network. Big data encompasses a wide range of studies, but it mainly refers to the massive amounts of structured and unstructured data that organizations deal with on a regular basis. On the other hand, it regards not only the volume of the data; but also that how data-driven information can be used to enhance decision-making processes, security, and the overall efficiency of a business. This paper presents an intelligent big data framework as a solution to handle illegitimate traffic burden on the SDN network created by the numerous DDoS attacks. The framework entails an efficient defence and monitoring mechanism against DDoS attacks by employing the state of the art machine learning techniques.

Keywords: apache spark, apache kafka, big data, DDoS attack, machine learning, SDN network

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Authors: Rahmad Wisnu Wardana, Eakachai Warinsiriruk, Sutep Joy-A-Ka

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Selecting the most suitable welding process usually depends on experiences or common application in similar companies. However, this approach generally ignores many criteria that can be affecting the suitable welding process selection. Therefore, knowledge automation through knowledge-based systems will significantly improve the decision-making process. The aims of this research propose integrated data envelopment analysis (DEA) and fuzzy credibility constrained programming approach for identifying the best welding process for stainless steel storage tank in the food and beverage industry. The proposed approach uses fuzzy concept and credibility measure to deal with uncertain data from experts' judgment. Furthermore, 12 parameters are used to determine the most appropriate welding processes among six competitive welding processes.

Keywords: welding process selection, data envelopment analysis, fuzzy credibility constrained programming, storage tank

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Authors: Kayode Balogun, Femi Ayoola

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Crime is at alarming rate in this part of world and there are many factors that are contributing to this antisocietal behaviour both among the youths and old. In this work, principal component analysis (PCA) was used as a tool to reduce the dimensionality and to really know those variables that were crime prone in the study region. Data were collected on twenty-eight crime variables from National Bureau of Statistics (NBS) databank for a period of fifteen years, while retaining as much of the information as possible. We use PCA in this study to know the number of major variables and contributors to the crime in the Southwest Nigeria. The results of our analysis revealed that there were eight principal variables have been retained using the Scree plot and Loading plot which implies an eight-equation solution will be appropriate for the data. The eight components explained 93.81% of the total variation in the data set. We also found that the highest and commonly committed crimes in the Southwestern Nigeria were: Assault, Grievous Harm and Wounding, theft/stealing, burglary, house breaking, false pretence, unlawful arms possession and breach of public peace.

Keywords: crime rates, data, Southwest Nigeria, principal component analysis, variables

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Authors: Hyun-Woo Cho

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Detection of incipient abnormal events in production processes is important to improve safety and reliability of manufacturing operations and reduce losses caused by failures. The construction of calibration models for predicting faulty conditions is quite essential in making decisions on when to perform preventive maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of process measurement data. The calibration model is used to predict faulty conditions from historical reference data. This approach utilizes variable selection techniques, and the predictive performance of several prediction methods are evaluated using real data. The results shows that the calibration model based on supervised probabilistic model yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: calibration model, monitoring, quality improvement, feature selection

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Authors: Elitza Z. Ambrus, Bjoern Hartig, Ryan McKay

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Individuals’ self-judgments might be malleable and influenced by comparison with a random value. On the one hand, self-judgments reflect our self-image, which is typically considered to be stable in adulthood. Indeed, people also strive hard to maintain a fixed, positive moral image of themselves. On the other hand, research has shown the robustness of the so-called anchoring effect on judgments and decisions. The anchoring effect refers to the influence of a previously considered comparative value (anchor) on a consecutive absolute judgment and reveals that individuals’ estimates of various quantities are flexible and can be influenced by a salient random value. The present study extends the anchoring paradigm to the domain of the self. We also investigate whether participants are more susceptible to self-serving anchors, i.e., anchors that enhance participant’s self-image, especially their moral self-image. In a pre-reregistered study via the online platform Prolific, 249 participants (156 females, 89 males, 3 other and 1 who preferred not to specify their gender; M = 35.88, SD = 13.91) ranked themselves on eight personality characteristics. However, in the anchoring conditions, respondents were asked to first indicate whether they thought they would rank higher or lower than a given anchor value before providing their estimated rank in comparison to 100 other anonymous participants. A high and a low anchor value were employed to differentiate between anchors in a desirable (self-serving) direction and anchors in an undesirable (self-diminishing) direction. In the control treatment, there was no comparison question. Subsequently, participants provided their self-rankings on the eight personality traits with two personal characteristics for each combination of the factors desirable/undesirable and moral/non-moral. We found evidence of an anchoring effect for self-judgments. Moreover, anchoring was more efficient when people were anchored in a self-serving direction: the anchoring effect was enhanced when supporting a more favorable self-view and mitigated (even reversed) when implying a deterioration of the self-image. The self-serving anchoring was more pronounced for moral than for non-moral traits. The data also provided evidence in support of a better-than-average effect in general as well as a magnified better-than-average effect for moral traits. Taken together, these results suggest that self-judgments might not be as stable in adulthood as previously thought. In addition, considerations of constructing and maintaining a positive self-image might interact with the anchoring effect on self-judgments. Potential implications of our results concern the construction and malleability of self-judgments as well as the psychological mechanism shaping anchoring.

Keywords: anchoring, better-than-average effect, self-judgments, self-serving anchoring

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Authors: Farzaneh Badinlou, Reza Kormi-Nouri, Monika Knopf

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Enacted tasks are typically remembered better than when the same task materials are only verbally encoded, a robust finding referred to as the enactment effect. It has been assumed that enactment effect is independent of object presence but the size of enactment effect can be increased by providing objects at study phase in adults. To clarify the issues in children, free recall and cued recall performance of action phrases with or without using real objects were compared in 410 school-aged children from four age groups (8, 10, 12 and 14 years old). In this study, subjects were instructed to learn a series of action phrases under three encoding conditions, participants listened to verbal action phrases (VTs), performed the phrases (SPTs: subject-performed tasks), and observed the experimenter perform the phrases (EPTs: experimenter-performed tasks). Then, free recall and cued recall memory tests were administrated. The results revealed that the real object compared with imaginary objects improved recall performance in SPTs and EPTs, but more so in VTs. It was also found that the object presence was not necessary for the occurrence of the enactment effect but it was changed the size of enactment effect in all age groups. The size of enactment effect was more pronounced for imaginary objects than the real object in both free recall and cued recall memory tests in children. It was discussed that SPTs and EPTs deferentially facilitate item-specific and relation information processing and providing the objects can moderate the processing underlying the encoding conditions.

Keywords: action memory, enactment effect, item-specific processing, object, relational processing, school-aged children

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Authors: Masoud Ghahvechi Pour

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Risk management is a systematic and regular process of identifying, analyzing and responding to risks throughout the project's life cycle in order to achieve the optimal level of elimination, reduction or control of risk. The purpose of project risk management is to increase the probability and effect of positive events and reduce the probability and effect of unpleasant events on the project. Risk management is one of the most fundamental parts of project management, so that unmanaged or untransmitted risks can be one of the primary factors of failure in a project. Effective risk management does not apply to risk regression, which is apparently the cheapest option of the activity. However, the main problem with this option is the economic sensitivity, because what is potentially profitable is by definition risky, and what does not pose a risk is economically interesting and does not bring tangible benefits. Therefore, in relation to the implemented project, effective risk management is finding a "middle ground" in its management, which includes, on the one hand, protection against risk from a negative direction by means of accurate identification and classification of risk, which leads to analysis And it becomes a comprehensive analysis. On the other hand, management using all mathematical and analytical tools should be based on checking the maximum benefits of these decisions. Detailed analysis, taking into account all aspects of the company, including stakeholder analysis, will allow us to add what will become tangible benefits for our project in the future to effective risk management. Identifying the risk of the project is based on the theory that which type of risk may affect the project, and also refers to specific parameters and estimating the probability of their occurrence in the project. These conditions can be divided into three groups: certainty, uncertainty, and risk, which in turn support three types of investment: risk preference, risk neutrality, specific risk deviation, and its measurement. The result of risk identification and project analysis is a list of events that indicate the cause and probability of an event, and a final assessment of its impact on the environment.

Keywords: risk, management, knowledge, risk management

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Authors: Rupali Bhardwaj

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Cryptography is the science of using mathematics to encrypt and decrypt data; the data are converted into some other gibberish form, and then the encrypted data are transmitted. The primary purpose of this paper is to provide two levels of security through a two-step process, rather than transmitted the message bits directly, first encrypted it using 2D cellular automata and then scrambled with Arnold Cat Map transformation; it provides an additional layer of protection and reduces the chance of the transmitted message being detected. A comparative analysis on effectiveness of scrambling technique is provided by scrambling degree measurement parameters i.e. Gray Difference Degree (GDD) and Correlation Coefficient.

Keywords: scrambling, cellular automata, Arnold cat map, game of life, gray difference degree, correlation coefficient

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Authors: Naveed Ghani, Samreen Javed

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In today’s heterogeneous network environment, there is a growing demand for distrust clients to jointly execute secure network to prevent from malicious attacks as the defining task of propagating malicious code is to locate new targets to attack. Residual risk is always there no matter what solutions are implemented or whet so ever security methodology or standards being adapted. Security is the first and crucial phase in the field of Computer Science. The main aim of the Computer Security is gathering of information with secure network. No one need wonder what all that malware is trying to do: It's trying to steal money through data theft, bank transfers, stolen passwords, or swiped identities. From there, with the help of our survey we learn about the importance of white listing, antimalware programs, security patches, log files, honey pots, and more used in banks for financial data protection but there’s also a need of implementing the IPV6 tunneling with Crypto data transformation according to the requirements of new technology to prevent the organization from new Malware attacks and crafting of its own messages and sending them to the target. In this paper the writer has given the idea of implementing IPV6 Tunneling Secessions on private data transmission from financial organizations whose secrecy needed to be safeguarded.

Keywords: network worms, malware infection propagating malicious code, virus, security, VPN

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Authors: Vesna Šućur-Janjetović, Andrea Rakanović Radonjić

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Department of Social Work of the Faculty of Political Sciences, University of Banja Luka is the only School of Social Work in the Republic of Srpska (entity of Bosnia and Herzegovina). This Department has been implementing students’ practice as mandatory module since it was established in year 2000. As of 2006, the University of Banja Luka initiated the transformation of the education system in accordance with the Bologna Agreement. The Department of Social Work adopted a new Curriculum that anticipated 120 hours of Students’ practice. After ten years, a new process of changing and improving the Curriculum has been initiated, and research was conducted, in order to meet both the needs of practice and academic standards in the field of social work education. From 2006-2016 students were evaluating their practice experience under the mentor’s supervision. These evaluations were subject to the evaluation process of current Curriculum, including students practice module. Additional research was designed in order to assess the opinions of certified mentors on specific aspects of students’ practice, the needs of practice and possibilities for improving the education for social workers. Special research instruments were designed for the purpose of this research. All mentors were graduated social works working in all fields where social work services are provided (social welfare sector, health, education, non-government sector etc.). The third dimension of the research was a qualitative analysis of curriculums of Schools of Social Work in the region of Southeast Europe. This paper represents the results of the research, conclusions and consequences that led towards the improvement of Students’ practice and Curriculum of the Department of Social Work. The new Model anticipates 300 hours of Students’ practice, divided in three years of study, with different and specific learning outcomes.

Keywords: curriculum, Republic of Srpska, social work education, students’ practice

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Authors: Abdallah Al-ZoubI, Mamoun Dmour

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The spectrum of IoT devices is becoming widely diversified, entering almost all possible fields and finding applications in industry, health, finance, logistics, education, to name a few. The IoT active endpoint sensors and devices exceeded the 12 billion mark in 2021 and are expected to reach 27 billion in 2025, with over $34 billion in total market value. This sheer rise in numbers and use of IoT devices bring with it considerable concerns regarding data storage, analysis, manipulation and protection. IoT Blockchain-based systems have recently been proposed as a decentralized solution for large-scale data storage and protection. COVID-19 has actually accelerated the desire to utilize IoT devices as it impacted both demand and supply and significantly affected several regions due to logistic reasons such as supply chain interruptions, shortage of shipping containers and port congestion. An IoT-blockchain system is proposed to handle big data generated by a distributed network of sensors and controllers in an interactive manner. The system is designed using the Ethereum platform, which utilizes smart contracts, programmed in solidity to execute and manage data generated by IoT sensors and devices. such as Raspberry Pi 4, Rasbpian, and add-on hardware security modules. The proposed system will run a number of applications hosted by a local machine used to validate transactions. It then sends data to the rest of the network through InterPlanetary File System (IPFS) and Ethereum Swarm, forming a closed IoT ecosystem run by blockchain where a number of distributed IoT devices can communicate and interact, thus forming a closed, controlled environment. A prototype has been deployed with three IoT handling units distributed over a wide geographical space in order to examine its feasibility, performance and costs. Initial results indicated that big IoT data retrieval and storage is feasible and interactivity is possible, provided that certain conditions of cost, speed and thorough put are met.

Keywords: IoT devices, blockchain, Ethereum, big data

Procedia PDF Downloads 152