Miracle-dz/UniFAR-FTUs huggingface dataset:
A Study on a Psychiatric Nurse's Mannerism Experiences.

The purpose of this study was to identify the mannerism phenomenon, which psychiatric nurses experience in hospitals. Methods: Colaizzi`s phenomenological research methodology was used to illuminate the meaning and nature of the experience inherent for nurses when they provide nursing service. Results: Analysis of the data collected through interaction with the participants showed five theme clusters, as follows: `Losing passion`, `Becoming impassive mien`, `Watching and folding up one`s mind`, `Assimilating into the situation` and `Being aware of change to one`s existing style. ` Conclusion: The results of this study provide a description of the phenomenon of mannerism as described by the participants, and allow for identification of the nature of the meaning of the mannerism experience. Accordingly, the study findings provide psychiatric nurses an opportunity to meditate on the nature of nursing in high-quality nursing service for patients with mental illnesses. Further, medical authorities need to provide the opportunity for nurses to apply nursing intervention therapy as part of nursing service and establish an institutional, administrative system to make it possible for nurses to provide service.
Crime Prediction using Autoregressive Integrated Moving Average (ARIMA) Algorithm

Data mining (DM), as coined with the term Knowledge Discovery in databases, used diverse approaches of DM analysis such as clustering, prediction or forecasting and many more. These are instrumental in extracting important information from the database. Along with DM analytics, big data and predictive analysis are relatively new concepts in criminology. This paper analyzes the index and non-index crimes in the province of Surigao del Norte, Philippines using the crime dataset from years 2013-2017. The prediction of its occurrence for the year 2018-2022 was also provided using ARIMA(1,0,7) model. Results showed that physical injury, homicide, violation of special laws, car napping, reckless imprudence resulting to physical injury, and other non-index crimes has 26%, 25%, 25%, 24%, 24%, and 23% forecasted increase for the year 2018-2022 with the highest occurrence in years 2018, 2018, 2020, 2018, 2020, and 2020 respectively.
A Semantic Web Service Discovery System Based on UDDI and OWL-S

As a popular registry for Web services, UDDI provides a mature mechanism for service registration and search, but it does not support semantic operations on Web services, so its service discovery capability is not satisfactory. OWL-S overcomes UDDI’s shortcomings. Using OWL-S, service advertisements and requests based on capability description could be built in a uniform way, and the semantic matching between them could also be achieved. By means of these two technologies, a system was developed which is compatible with UDDI and supports the publication and discovery of semantic Web services. The matching performed by the system is divided into two parts: prematching and post-matching. The pre-matching is generally performed only in the course of service publication, so the time for service discovery is reduced. Experimental results show that the performance of the system is reliable. Furthermore, the system can produce query results ordered by priority according to the requester’s expectations.
Indoor Localization Improved by Spatial Context—A Survey

Indoor localization is essential for healthcare, security, augmented reality gaming, and many other location-based services. There is currently a wealth of relevant literature on indoor localization. This article focuses on recent advances in indoor localization methods that use spatial context to improve the location estimation. Spatial context in the form of maps and spatial models have been used to improve the localization by constraining location estimates in the navigable parts of indoor environments. Landmarks such as doors and corners, which are also one form of spatial context, have proved useful in assisting indoor localization by correcting the localization error. This survey gives a comprehensive review of state-of-the-art indoor localization methods and localization improvement methods using maps, spatial models, and landmarks.
Effects of Press Parameters on Some Technological Properties of Polystren Composite Plywood

Calismanin amaci: Ah sap kompozit malzemelerin uretiminde kullanilan tutkallarin bircogu formaldehit icerigi nedeniyle insan ve cevre sagligi acisindan bir tehdit unsuru olarak gorulmektedir. Bu nedenle odun kokenli levhalarda ki formaldehit emisyonunun azaltilmasina yonelik etkili metotlarin gelistirilmesi icin bircok calisma yapilmis ve cesitli yontemler denenmistir. Bu calismada polistren kompozit kontrplaklarin bazi teknolojik ozellikleri uzerine pres parametrelerinin etkilerinin arastirilmasi amaclanmistir. Calisma alani: Bu calisma, Trabzon’daki Karadeniz Teknik Universitesi Orman Endustri Muhendisligi Bolumu Pilot tesisinde yapilmistir. Materyal ve Yontem: Polistren kompozit kontrplaklarin uretiminde kavak ( Populus deltoides ) kaplamalar kullanilmistir. Geleneksel kontrplaklarin uretiminde yapistirici olarak UF tutkali kullanilmistir. Polistren kompozit kontrplaklarin uretiminde farkli pres sicakliklari (130, 140, 150 o C) ve pres sureleri (6, 8, 10 dakika) secilmistir. Levhalarin, cekme makaslama direnci TS EN 314-1, egilme direnci ve elastikiyet modulu TS EN 310, ozgul agirliklari TS EN 323 ve denge rutubet miktarlari TS EN 322 standartlarina gore belirlenmistir. Sonuclar: Yapilan deneyler sonucunda genel olarak levhalarin mekanik ozelliklerinin ve yogunluk degerlerinin pres sicakligi ve pres suresinin artmasina bagli olarak artis gosterdigi gorulurken denge rutubet miktarlarinin azaldigi gorulmustur. Arastirma vurgulari: Bu calisma, polistiren atiklarinin kontrplak uretiminde ic mekan kullanimlari icin alternatif bir yapistirma malzemesi olarak kullanilabilecegini ortaya koymustur.
A comparison of flow cytometry and conventional microbiology in the study of biofilms.

A comprehensive study on the application of flow cytometry (FCM) for the analysis of biofilms has been undertaken and the results presented in this thesis have shown that flow cytometry can been successfully used to enumerate, sort and image the bacteria and amoebae in biofilms and water distribution systems as a rapid and sensitive semiautomated technique compared with conventional microbiology.It has been shown that the results of flow cytometric analysis of total Legionella pneumophila cells have a strong statistical correlation with the numbers of Legionella cfu by BCYE plate counting (BCYE PC) methods for biofilms and planktonic phases. There are also strong statistical correlations between flow cytometric analysis and epifluorescent microscopic (EFM) analysis (direct counting) for determination of bacteria, including Legionella, Escherichia coli, Salmonella, Pseudomonas and amoebae, and total and viable cells in pure cultures, water distribution systems and biofilms.The flow cytometric protocols have been set up and optimised for the analysis of environmental microorganisms. The novel fluorescent dyes and immunofluorescence antibodies from the most current commercial dyes also have been screened and the staining protocols have been optimised and adopted for flow cytometric analysis and direct counting by epifluorescent microscopy. The tap water biofilms and river water biofilms were analysed by the flow cytometer and direct counting methods as well as by conventional microbiological methods (plate counting). The bacterial populations in real water distribution systems have been fully investigated and the total, viable bacteria were determined by the above methods.The findings of this work have practical implications with respect to the rapid and automatic detection and predictions of Legionella spp. and the risk assessment from biofilms and water environments.
Development of a complex mathematical model of the state of a channel of multi-antenna radio communication systems

The complex mathematical model of the state of the channel of multi-antenna radio communication systems is developed. The model takes into account: the effect of intentional noise and signal fading, the number of receiving antennas, Doppler effect, correlation coefficient, speed and direction of the receiver and the transmitter, intersymbol interference, phase jitter and inclination of the constellation matrix. Simulation of the state of the channel of multi-antenna radio communication systems is carried out for each individual antenna channel, after which a generalized estimate is formed at the output. The development of the proposed integrated mathematical model is due to the need to improve the accuracy of the description of the channel state of multi-antenna radio communication systems with an acceptable computational complexity. The proposed model allows to improve the accuracy of the description of the state of the channel of multi-antenna radio communication systems by taking into account additional destabilizing factors, thereby increasing the accuracy of the channel state assessment. I would like to note that at the same time there is an increase in the computational complexity at the level of 5-7% due to an increase in the number of evaluated indicators. The mentioned complex mathematical model should be used in radio stations with a programmable architecture to increase their noise immunity by increasing the accuracy of the evaluation of the characteristics of the receiving and transmitting path relative to the state of the channel. The research of the correlation between antennas of multi-antenna radio communication systems was conducted. The results show that in the presence of a line of sight between the receiver and the transmitter, the signal correlation is high and therefore a small increase is expected from the use of several antennas, and in the absence of line of sight conditions, the signal correlation is low
AI for General Strategy Game Playing

This chapter addresses the understudied question of how to create AI that plays strategy games, through building and comparing AI for general strategy game playing. The chapter enumerates a series of common characteristics of such a game. Many strategy games can be played in multiplayer mode, where human players compete with each other for domination. There has been extensive research done on AI for traditional board games. The chapter addresses the problem of general strategy game playing. The Strategy Game Description Language (SGDL) is a model-based approach to develop strategy games. The chapter presents 11 agents that are created based on several different techniques. The MinMax, Monte Carlo tree search (MCTS), potential field (PF), and neuroevolution of augmenting topologies (NEAT) agents were determined to be adequate in various models and map combinations and thus are capable of general game play.
Research-based learning in education studies: Design inquiry using group e-Portfolios based on blogs

Research-based learning (RBL) is an approach that aims to engage students in research activities within their study discipline. Since this method puts the focus on the learner, Web 2.0 tools are considered to provide good support in enhancing collaboration processes, which are necessary in conducting research in real-life situations. The link between RBL and the use of digital technologies in higher education has not yet been extensively empirically explored. Therefore, the main aim of this study, based on a project-based university seminar, was to explore the possibilities of group e-Portfolios based on blogs, within the framework of a concrete form of RBL in education studies, the design-inquiry approach. The study employed mixed methods, consisting of quantitative and qualitative data collected via a student questionnaire, and further qualitative data collected from the group blogs and the students’ final reflections. The results show the possibilities and challenges of using e-Portfolios based on blogs for RBL processes. The article concludes by providing guidelines and recommendations and presents a framework that connects the models used in the study.
The Effect of Lactulose on the Survival of Lactobacillus rhamnosus in the Simulator of the Human Intestinal Microbial Ecosystem (SHIME) and in vivo

The effect of lactulose on the survival of Lactobacillus rhamnosus VTT E-97800 and on the colon microbiota and its metabolic activity was studied using the Simulator of the Human Intestinal Microbial Ecosystem (SHIME) model. L. rhamnosus VTT E-97800 and lactulose together enhanced the production of butyric acid and decreased ammonium concentration in the model. The numbers of Bacteroides were observed to decrease 2.5-2.0 log 10 cfu/ml during the SHIME experiment. In the subsequent in vivo studies the colonisation of the human colon by L. rhamnosus VTT E-97800 could be confirmed using either RAPD or RiboPrinter™ for the strain identification. RAPD showed that 10-60% more L. rhamnosus VTT E-97800 was detected in lactulose subjects compared with controls after strain feeding was discontinued indicating that lactulose might enhance the survival of the strain in the colon.
Justification effectiveness of systemic treatment of breast cancer depending on body mass index

The incidence of breast cancer in the world in general and in Ukraine in particular is growing. In 2015, in Ukraine the incidence reached 70.0 per 100 thousand female populations. According to the Ministry of Health in Ukraine 26% of the female population for 2015 was overweight or obese. Obesitya chronic metabolic character, which is the result of the interaction of the endogenous factors, environmental conditions and lifestyle. Endogenous factors could be considered a violation of the genetic and hormonal balance. The external conditions include irregular rhythm nutrition, use of substandard products. By disorders include sedentary lifestyle lifestyles.
Exploiting behavioral biometrics for user security enhancements

As online business has been very popular in the past decade, the tasks of providing user authentication and verification have become more important than before to protect user sensitive information from malicious hands. The most common approach to user authentication and verification is the use of password. However, the dilemma users facing in traditional passwords becomes more and more evident: users tend to choose easy-to-remember passwords, which are often weak passwords that are easy to crack. Meanwhile, behavioral biometrics have promising potentials in meeting both security and usability demands, since they authenticate users by "who you are", instead of "what you have". In this dissertation, we first develop two such user verification applications based on behavioral biometrics: the first one is via mouse movements, and the second via tapping behaviors on smartphones: then we focus on modeling user web browsing behaviors by Fitts' Law. Specifically, we develop a user verification system by exploiting the uniqueness of people's mouse movements. The key feature of our system lies in using much more fine-grained (point-by-point) angle-based metrics of mouse movements for user verification. These new metrics are relatively unique from person to person and independent of the computing platform. We conduct a series of experiments to show that the proposed system can verify a user in an accurate and timely manner, and induced system overhead is minor. Similar to mouse movements, the tapping behaviors of smartphone users on touchscreen also vary from person to person. We propose a non-intrusive user verification mechanism to substantiate whether an authenticating user is the true owner of the smartphone or an impostor who happens to know the passcode. The effectiveness of the proposed approach is validated through real experiments. To further understand user pointing behaviors, we attempt to stress-test Fitts' law in the "wild", namely, under natural web browsing environments, instead of restricted laboratory settings in previous studies. Our analysis shows that, while the averaged pointing times follow Fitts' law very well, there is considerable deviations from Fitts' law. We observe that, in natural browsing, a fast movement has a different error model from the other two movements. Therefore, a complete profiling on user pointing performance should be done in more details, for example, constructing different error models for slow and fast movements. As future works, we plan to exploit multiple-finger tappings for smartphone user verification, and evaluate user privacy issues in Amazon wish list.
Development of Android Comics media on Thermodynamic Experiment to Map the Science Process Skill for Senior High School

Technological development influences smartphone addiction. Low academic achievement has a negative influence on school life. Comics include media that are often used in everyday life and as entertainment facilities. Comics are not only functioned as entertainment tools, but are also used in education. Physics laboratories are still minimally utilized by physics teachers in schools, so students’ science process skills are still lacking. The purpose of this study was to measure science process skills using Android-based physics comics on thermodynamic practicums. Development models used, namely R & D of Borg and Gall. Learning is done in the form of practicum on thermodynamic material. Android media use is used to measure science process skills. Physics learning innovation is applied in the XI science class of one of the senior high schools in Sleman, Yogyakarta, Indonesia. Data obtained from observation sheets of science process skills from modelling and implementation classes are very good; good; and enough. The results revealed that the application of Android comic media on thermodynamic experiment could map the science process skills of senior high school.
Foundations for a Game Theoretic Framework for Agile Acquisition

This article evaluates the applicability of game theory within the government acquisition community to provide strategies that move potential vendors into a preferred negotiation point and expedite the decision-making process in acquisition. The research focuses on the application of utility models in support of a game theoretic foundation to provide a means to illuminate better contracting tradeoffs for the government.
Remarks on the age of Dominican amber

Amber from the Dominican Republic is famous for the high quality, frequency, and diversity of organic fossils found as inclusions in this mineral (Grimaldi, 1996; Poinar & Poinar, 1999). However, its geological age of origin remains a continuing source of controversy. Over the years a wide variety of age estimates have been made for occurrences of Dominican amber, ranging from Cretaceous (Brouwer & Brouwer, 1982) to Late Eocene (Lambert et al., 1985) to pre-Lower Miocene (Baroni-Urbani & Saunders, 1982). Some authors have also favored a spread of ages that covers much of the Cenozoic (e.g., 40 or 45 Ma to 15 Ma; Poinar & Poinar, 1999). Iturralde-Vinent & MacPhee (1996) attempted to resolve discrepancies in age assignments by taking a multi-pronged analytical approach which yielded a best-fit estimate of mid-Miocene age (20–15 Ma). This estimate has been widely accepted and additionally corroborated by new studies (Iturralde-Vinent, 2001; Ortega-Ariza et al., 2015). However, Braga et al. (2012) have challenged the assessment of Iturralde-Vinent & MacPhee (1996) by arguing for a Pliocene–early Pleistocene date for the amber-bearing Yanigua Formation. Here we address the sources of disagreement and suggest a solution.
MODEL FOR EFFICIENT ALLOCATION OF NETWORK FUNCTIONS IN HYBRID ENVIRONMENT

Background. To ensure the required quality of experience and optimal use of network operator's resources in the current conditions telecommunication operator can deploy services using the concept of Network Functions Virtualization (NFV), that has fundamental differences from traditional dedicated hardware. To achieve the expected benefits of NFV, physical resources must be used effectively. This requires effective algorithms to determine onto which physical resources network functions are allocated. Objective. The aim of the paper is to improve the efficiency of mobile network through optimal resource allocation in hybrid data center environment. Methods. Analysis of all known publications devoted to virtualization of network functions of mobile network has shown the modeling approach to resource allocation and also has shown the absence of decisions on important issues of this process (performance of functional blocks, heterogeneous environment). Results. An analytical approach to model and investigate the resource allocation of network functions on a telecommunication operator’s network is proposed. Conclusions. To model the resource allocation for virtualized network functions a technique of virtual network embedding can be used, while changing the constraints in which you can get the results for a variety of deployment scenarios. In such way, adding a number of constraints to the classical formulation of the problem, we can take into account the performance of the network functions and heterogeneity (hybridity) of the deployment environment.
Breast cancer detection in histopathological images using convolutional neural networks

Breast cancer is one of the biggest causes of death among women around the world. Diagnosing this disease early can offer better treatment to the patient. Intelligent systems have been used for the detection of diseases using images. In this work a convolutional neural network was used for the detection of breast cancer in histopathological images through Keras library and TensorFlow framework. Models were created for 4 datasets with different magnifying factors (40x, 100x, 200x and 400x). Using k-fold cross-validation, it was found that there was a better result for the set of 400x images with 98.44% accuracy in the training data. The set of 200x images obtained a better result for recall and f1-score.
Statistical Digital Signal Processing And Modeling

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