Search results for: cloud service models

Authors: Bahram Khan, Anderson Rocha Ramos, Rui R. Paulo, Fernando J. Velez

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With the growing demand for a new blend of applications, the users dependency on the internet is increasing day by day. Mobile internet users are giving more attention to their own experiences, especially in terms of communication reliability, high data rates and service stability on move. This increase in the demand is causing saturation of existing radio frequency bands. To address these challenges, researchers are investigating the best approaches, Carrier Aggregation (CA) is one of the newest innovations, which seems to fulfill the demands of the future spectrum, also CA is one the most important feature for Long Term Evolution - Advanced (LTE-Advanced). For this purpose to get the upcoming International Mobile Telecommunication Advanced (IMT-Advanced) mobile requirements (1 Gb/s peak data rate), the CA scheme is presented by 3GPP, which would sustain a high data rate using widespread frequency bandwidth up to 100 MHz. Technical issues such as aggregation structure, its implementations, deployment scenarios, control signal techniques, and challenges for CA technique in LTE-Advanced, with consideration of backward compatibility, are highlighted in this paper. Also, performance evaluation in macro-cellular scenarios through a simulation approach is presented, which shows the benefits of applying CA, low-complexity multi-band schedulers in service quality, system capacity enhancement and concluded that enhanced multi-band scheduler is less complex than the general multi-band scheduler, which performs better for a cell radius longer than 1800 m (and a PLR threshold of 2%).

Keywords: component carrier, carrier aggregation, LTE-advanced, scheduling

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Authors: Ayman Mutahar Alrassas, Shaoran Ren, Renyuan Ren, Hung Vo Thanh, Mohammed Hail Hakimi, Zhenliang Guan

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The significant effect of CO₂ on global climate and the environment has gained more concern worldwide. Enhance oil recovery (EOR) associated with sequestration of CO₂ particularly into the depleted oil reservoir is considered the viable approach under financial limitations since it improves the oil recovery from the existing oil reservoir and boosts the relation between global-scale of CO₂ capture and geological sequestration. Consequently, practical measurements are required to attain large-scale CO₂ emission reduction. This paper presents an integrated modeling workflow to construct an accurate 3D reservoir geological model to estimate the storage capacity of CO₂ under geological uncertainty in an unconventional oil reservoir of the Paleogene Shahejie Formation (Es1) in the block Nv32, Shenvsi oilfield, China. In this regard, geophysical data, including well logs of twenty-two well locations and seismic data, were combined with geological and engineering data and used to construct a 3D reservoir geological modeling. The geological modeling focused on four tight reservoir units of the Shahejie Formation (Es1-x1, Es1-x2, Es1-x3, and Es1-x4). The validated 3D reservoir models were subsequently used to calculate the theoretical CO₂ storage capacity in the block Nv32, Shenvsi oilfield. Well logs were utilized to predict petrophysical properties such as porosity and permeability, and lithofacies and indicate that the Es1 reservoir units are mainly sandstone, shale, and limestone with a proportion of 38.09%, 32.42%, and 29.49, respectively. Well log-based petrophysical results also show that the Es1 reservoir units generally exhibit 2–36% porosity, 0.017 mD to 974.8 mD permeability, and moderate to good net to gross ratios. These estimated values of porosity, permeability, lithofacies, and net to gross were up-scaled and distributed laterally using Sequential Gaussian Simulation (SGS) and Simulation Sequential Indicator (SIS) methods to generate 3D reservoir geological models. The reservoir geological models show there are lateral heterogeneities of the reservoir properties and lithofacies, and the best reservoir rocks exist in the Es1-x4, Es1-x3, and Es1-x2 units, respectively. In addition, the reservoir volumetric of the Es1 units in block Nv32 was also estimated based on the petrophysical property models and fund to be between 0.554368

Keywords: CO₂ storage capacity, 3D geological model, geological uncertainty, unconventional oil reservoir, block Nv32

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Authors: Shu-Hsi Ho

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The problems of aging and number of widowed peers gradually rise in Taiwan. It is worth to concern the related issues for elderly after the death of a spouse. Hence, this study is to examine the impact of spousal death on the surviving spouse’s self-perceived health and mental health for the elderly in Taiwan. A cross section data design and ordered logistic regression models are applied to investigate whether marriage is associated significantly to self-perceived health and mental health for the widowed older Taiwanese. The results indicate that widowed marriage shows significant negative effects on self-perceived health and mental health regardless of widows or widowers. Among them, widows might be more likely to show worse mental health than widowers. The belief confirms that marriage provides effective sources to promote self-perceived health and mental health, particularly for females. In addition, since the social welfare system is not perfect in Taiwan, the findings also suggest that family and social support reveal strongly association with the self-perceived health and mental health for the widows and widowers elderly.

Keywords: logistic regression models, self-perceived health, widow, widower

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Authors: Sidiqat A. Aderinoye-Abdulwahab, Lateef L. Adefalu, Jubril O. Animashaun

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Pastoralists in Nigeria are situated in dry regions - where water and pasture for livestock are particularly scarce, as well as areas with poor availability of social amenities and infrastructure. This study therefore explored how extension service could be used to reduce the exposure of nomads to effects of seasonality, climate change, and the poor environmental conditions. The study was carried out in Northern guinea Savannah region of Nigeria because pastoralists have settled there in large numbers due to desertification and low rainfall in the arid regions. A multi-stage sampling procedure was used to arrive at the selection of two states (Kwara and Nassarawa) in the region. A total of 63 respondents were randomly chosen using simple random sampling. Focus group discussions and questionnaire were used to gather information while the data was analysed using content analysis. The facilities required by the sampled households are milking machine, cheese making machine, and preservatives to increase the shelf life of cheese. Whilst, the extension service required are demonstration on cheese making, training and seminars on animal husbandry. Additionally, livestock of pastoralists often encroach on farmers’ plots which usually result in pastoralist-farmer conflicts. The study thus recommends diversification of economic activity from livestock to non-livestock related activities as well as creation of grazing routes to reduce pastoralist/farmer conflict.

Keywords: arid region, coping strategies, livestock, livelihood

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Authors: Debarag Banerjee, Pooja Singh, Arjun Avadhanam, Saksham Srivastava

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Autonomous conversational agents, i.e., chatbots, are becoming an increasingly common mechanism for enterprises to provide support to customers and partners. In order to rate chatbots, especially ones powered by Generative AI tools like Large Language Models (LLMs), we need to be able to accurately assess their performance. This is where chatbot benchmarking becomes important. In this paper, authors propose the use of a benchmark that they call the E2E (End to End) benchmark and show how the E2E benchmark can be used to evaluate the accuracy and usefulness of the answers provided by chatbots, especially ones powered by LLMs. The authors evaluate an example chatbot at different levels of sophistication based on both our E2E benchmark as well as other available metrics commonly used in the state of the art and observe that the proposed benchmark shows better results compared to others. In addition, while some metrics proved to be unpredictable, the metric associated with the E2E benchmark, which uses cosine similarity, performed well in evaluating chatbots. The performance of our best models shows that there are several benefits of using the cosine similarity score as a metric in the E2E benchmark.

Keywords: chatbot benchmarking, end-to-end (E2E) benchmarking, large language model, user centric evaluation.

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Authors: Ahmed Borg, Elsa Aristodemou, Attia Attia

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Well control involves managing the circulating drilling fluid within the wells and avoiding kicks and blowouts as these can lead to losses in human life and drilling facilities. Current practices for good control incorporate predictions of pressure losses through computational models. Developing a realistic hydraulic model for a good control problem is a very complicated process due to the existence of a complex multiphase region, which usually contains a non-Newtonian drilling fluid and the miscibility of formation gas in drilling fluid. The current approaches assume an inaccurate flow fluid model within the well, which leads to incorrect pressure loss calculations. To overcome this problem, researchers have been considering the more complex two-phase fluid flow models. However, even these more sophisticated two-phase models are unsuitable for applications where pressure dynamics are important, such as in managed pressure drilling. This study aims to develop and implement new fluid flow models that take into consideration the miscibility of fluids as well as their non-Newtonian properties for enabling realistic kick treatment. furthermore, a corresponding numerical solution method is built with an enriched data bank. The research work considers and implements models that take into consideration the effect of two phases in kick treatment for well control in conventional drilling. In this work, a corresponding numerical solution method is built with an enriched data bank. Software STARCCM+ for the computational studies to study the important parameters to describe wellbore multiphase flow, the mass flow rate, volumetric fraction, and velocity of each phase. Results showed that based on the analysis of these simulation studies, a coarser full-scale model of the wellbore, including chemical modeling established. The focus of the investigations was put on the near drill bit section. This inflow area shows certain characteristics that are dominated by the inflow conditions of the gas as well as by the configuration of the mud stream entering the annulus. Without considering the gas solubility effect, the bottom hole pressure could be underestimated by 4.2%, while the bottom hole temperature is overestimated by 3.2%. and without considering the heat transfer effect, the bottom hole pressure could be overestimated by 11.4% under steady flow conditions. Besides, larger reservoir pressure leads to a larger gas fraction in the wellbore. However, reservoir pressure has a minor effect on the steady wellbore temperature. Also as choke pressure increases, less gas will exist in the annulus in the form of free gas.

Keywords: multiphase flow, well- control, STARCCM+, petroleum engineering and gas technology, computational fluid dynamic

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Authors: Shuyuan Lin, Zhaohui Huang, Mizi Fan

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In the majority of previous research into modelling large scale composite floor subjected to fire, the beam-to-column and beam-to-beam connections were assumed to behave either as pinned or rigid for simplicity, and the vertical shear and axial tension failures of the connection were not taken into account. We have recently developed robust two-noded connection models for modeling endplate and partial endplate steel connections under fire conditions. The main objective of this research is to systematically investigate the impact of the connections of protected beams, on the tensile membrane actions of supported floor slabs in which the failures of the connections, such as, axial tension, vertical shear and bending are accounted for. The models developed have very good numerical stability under a static solver condition, and can be used for large scale modelling of composite buildings in fire.

Keywords: fire, steel structure, component-based model, beam-to-column connections

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Authors: Raghad A. Altowairgi

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With the wide spread of social media platforms, young people tend to use them extensively as the first means of communication due to their ease and modernity. But these platforms often create a fertile ground for bullies to practice their aggressive behavior against their victims. Platform usage cannot be reduced, but intelligent mechanisms can be implemented to reduce the abuse. This is where machine learning comes in. Understanding and classifying text can be helpful in order to minimize the act of cyberbullying. Artificial intelligence techniques have expanded to formulate an applied tool to address the phenomenon of cyberbullying. In this research, machine learning models are built to classify text into two classes; cyberbullying and non-cyberbullying. After preprocessing the data in 4 stages; removing characters that do not provide meaningful information to the models, tokenization, removing stop words, and lowering text. BoW and TF-IDF are used as the main features for the five classifiers, which are; logistic regression, Naïve Bayes, Random Forest, XGboost, and Catboost classifiers. Each of them scores 92%, 90%, 92%, 91%, 86% respectively.

Keywords: cyberbullying, machine learning, Bag-of-Words, term frequency-inverse document frequency, natural language processing, Catboost

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Authors: Özgür Bahadir, Meltem Kurtuncu

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The study was designed as quasi-experimental and conducted to determine the effect of music therapy on anxiety, fear and pain management in 6-12-year-old children undergoing surgery. The present study was carried out between 01.01.2016 and 19.08.2016 in BEU. Application and Research Center. The children aged 6 -12 who applied for surgery between the mentioned dates constituted the universe of the study. In the quasi-experimental study that was conducted in the clinics where children received operational treatment, two groups were formed: experimental group (the children who received musical therapy before the surgery) and control group (the children who were administered surveys and the surgery service routines only). Each group consisted of 30 children, and the participants of the study were 60 children in total. Necessary permissions were obtained from the parents of the children hospitalized before the beginning of the implementation. The data was collected through Child Anxiety Sensitivity Index (CASI), “Fear In Medical Treatment Scale”, Face, Legs, Activity, Cry, Consolability Scale (FLACC), Visual Analog Scale (VAS) and Participant Information Form. In the analysis of the data, Kolmogorov-Smirnov distribution scale was used to examine the normality of the distribution along with descriptive statistics methods (Frequency, Percentage, Mean, Standard Deviation). Data was presented in the tables in numbers and percentages. Means were demonstrated along with the standard deviations. The research compared children received; case and control groups include socio-demographic perspective, non-significant difference statistically among similar groups are intertwined. The general level of fear regarding the medical processes before returning to service after the operation and 30 minutes before getting discharged was found to be significantly low in the experimental group compared to control group (p<0.05). No statistically significant difference was found between experimental and control groups in terms of general level of fear regarding the medical processes before the operation, during the operation day and in the recovery room after the operation (p>0.05). Total CASI AD (anxiety sensitivity) levels before the operation, day of the operation and 30 minutes before the discharge for patients in experimental group was found to be significantly higher than the control group (p>0.05). There was no statistically significant difference between the experimental and control groups in the total CASI AD levels for the post-operative recovery room and for returning to the service room after the operation (p>0.05). VAS levels for patients in the experimental group in the post-operative recovery room was significantly higher than the control group (p>0.05). There was no statistically significant difference between the groups in terms of VAS findings in returning to service room after the operation and in 30 minutes before the discharge (p>0.05). As a result of the research; applied children music therapy in the experimental group anxiety, fear, and pain of the scales, their scores average, is lower than the control group children in this situation an increase in the satisfaction of children and parents was observed. In line with this, music therapy preoperative anxiety, fear, and can be used as an effective method of decreasing postoperative pain clinics is suggested.

Keywords: anxiety, children, fear, music therapy, pain

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Authors: T. Aragaw, P. Gari

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In spite of social, political, and economic marginalization, women are still considered as the backbone of Ethiopia, one of the least developed countries in the world. The general purpose of this study was to assess factors that affect participation of women in politics, social and economic decisions at Kelem-Wollega Administrative Zone of Oromia Regional State, Ethiopia. Data used in this paper is mainly primary, and a few secondary data were incorporated. Respondents were selected using a systematic random sampling method and were placed questionnaires containing open-ended and closed-ended. Focus group discussion was also used for the study subjects in two offices. According to the information collected from the KWAZ Development and Social Service Office, a total of 18,473 tax-paying employees are present in the Zone, which is 14% of the total population of the Zone. Among the total number of employees in the Zone, 2,617 have been recruited for this study based on the criteria stated. This showed 1.8% of them were comprised of several churches and religious owned integrated development projects in the KWAZ. The 2,103 (80.34%) study participants responded personally, and they completed and returned the questionnaire to the researchers. The study revealed that in public institutions existed in KWAZ, the majority of women were having an educational status of diploma and lower, practicing lower non-decision making and leadership positions. Conclusion: Major barriers hindering women include: Socio-cultural attitudes, lack of necessary experience, education, the burden of domestic responsibilities, and lack of role models of women leaders in the Zone. Empowerment of women via social organizations, critical involvement of the government, and Affirmative action for women is critical. Further research is needed on the scope and challenges in implementing the strategies.

Keywords: women, affirmative action, leadership, empowerment, Ethiopia

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Authors: Kashifa Khalid, Eesham Fatima

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This study aims to analyze the loss of identity and its impact on one’s life in ‘The Last White Man’ by Mohsin Hamid. The theory of Alienation Effect by Bertolt Brecht has been applied to the text as Hamid offers the readers a unique perspective, alluding to significant themes like identity, race, and death. The aspects of defamiliarization align impeccably with the plot, as existence and the corresponding concept of identity seem to have dissolved into utter chaos. This extends from the unexplained transformation to the way the entire world unravels from its general norm into a dystopian mayhem. The characters, starting with the protagonist Anders, have lost their center. One’s own self transforms into the ‘other,’ and the struggle is to get refamiliarized with one’s own self. Alienation and isolation only rise as the construct of race and identity is taken apart brick by brick, ironically at its own pace as many new realities are blown to bits. The inseparable relationship between identity and grief under the ever-looming cloud of ‘death’ is studied in detail. The theoretical framework and thematic aspects harmonize in accordance with the writing style put forth by Hamid, tying all the loose ends together.

Keywords: alienation, chaos, identity, transformation

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Authors: E. H. Walsh, J. McMahon, M. P. Herring

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Post-primary school-based suicide prevention (PSSP) is a valuable avenue to reduce suicidal behaviours in adolescents. The aims of this meta-analysis and meta-regression were 1) to quantify the effect of PSSP interventions on adolescent suicide ideation (SI) and suicide attempts (SA), and 2) to explore how intervention effects may vary based on important contextual and intervention factors. This study provides further support to the benefits of PSSP by demonstrating lower suicide outcomes in over 30,000 adolescents following PSSP and mental health interventions and tentatively suggests that intervention effectiveness may potentially vary based on intervention factors. The protocol for this study is registered on PROSPERO (ID=CRD42020168883). Population, intervention, comparison, outcomes, and study design (PICOs) defined eligible studies as cluster randomised studies (n=12) containing PSSP and measuring suicide outcomes. Aggregate electronic database EBSCO host, Web of Science, and Cochrane Central Register of Controlled Trials databases were searched. Cochrane bias tools for cluster randomised studies demonstrated that half of the studies were rated as low risk of bias. The Egger’s Regression Test adapted for multi-level modelling indicated that publication bias was not an issue (all ps > .05). Crude and corresponding adjusted pooled log odds ratios (OR) were computed using the Metafor package in R, yielding 12 SA and 19 SI effects. Multi-level random-effects models accounting for dependencies of effects from the same study revealed that in crude models, compared to controls, interventions were significantly associated with 13% (OR=0.87, 95% confidence interval (CI), [0.78,0.96], Q18 =15.41, p=0.63) and 34% (OR=0.66, 95%CI [0.47,0.91], Q10=16.31, p=0.13) lower odds of SI and SA, respectively. Adjusted models showed similar odds reductions of 15% (OR=0.85, 95%CI[0.75,0.95], Q18=10.04, p=0.93) and 28% (OR=0.72, 95%CI[0.59,0.87], Q10=10.46, p=0.49) for SI and SA, respectively. Within-cluster heterogeneity ranged from no heterogeneity to low heterogeneity for SA across crude and adjusted models (0-9%). No heterogeneity was identified for SI across crude and adjusted models (0%). Pre-specified univariate moderator analyses were not significant for SA (all ps < 0.05). Variations in average pooled SA odds reductions across categories of various intervention characteristics were observed (all ps < 0.05), which preliminarily suggests that the effectiveness of interventions may potentially vary across intervention factors. These findings have practical implications for researchers, clinicians, educators, and decision-makers. Further investigation of important logical, theoretical, and empirical moderators on PSSP intervention effectiveness is recommended to establish how and when PSSP interventions best reduce adolescent suicidal behaviour.

Keywords: adolescents, contextual factors, post-primary school-based suicide prevention, suicide ideation, suicide attempts

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Authors: Henri Champliaud, Zhengkun Feng, Ngan Van Lê, Javad Gholipour

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In this article, a method is presented to effectively estimate the deformed shape of a thick plate due to line heating. The method uses a fifth order spline interpolation, with up to C3 continuity at specific points to compute the shape of the deformed geometry. First and second order derivatives over a surface are the resulting parameters of a given heating line on a plate. These parameters are determined through experiments and/or finite element simulations. Very accurate kriging models are fitted to real or virtual surfaces to build-up a database of maps. Maps of first and second order derivatives are then applied on numerical plate models to evaluate their evolving shapes through a sequence of heating lines. Adding an optimization process to this approach would allow determining the trajectories of heating lines needed to shape complex geometries, such as Francis turbine blades.

Keywords: deformation, kriging, fifth order spline interpolation, first, second and third order derivatives, C3 continuity, line heating, plate forming, thermal forming

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Authors: Muluegziabher Semagne Mekonnen

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This study was intended to show the irrigation water requirements and evaluation of canal hydraulics steady state conditions to improve on scheme performance of the Meki-Ziway irrigation project. The methodology used was the CROPWAT 8.0 model to estimate the irrigation water requirements of five major crops irrigated in the study area. The results showed that for the whole existing and potential irrigation development area of 2000 ha and 2599 ha, crop water requirements were 3,339,200 and 4,339,090.4 m³, respectively. Hydraulic simulation models are fundamental tools for understanding the hydraulic flow characteristics of irrigation systems. Hydraulic simulation models are fundamental tools for understanding the hydraulic flow characteristics of irrigation systems. In this study Hydraulic Analysis of Irrigation Canals Using HEC-RAS Model was conducted in Meki-Ziway Irrigation Scheme. The HEC-RAS model was tested in terms of error estimation and used to determine canal capacity potential.

Keywords: HEC-RAS, irrigation, hydraulic. canal reach, capacity

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Authors: Sabina Huč, Staffan Svensson, Tomaž Hozjan

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Timber structures may be exposed to various environmental conditions during their service life. Often, the structures have to resist extreme changes in the relative humidity of surrounding air, with simultaneously carrying the loads. Wood material response for this load case is seen as increasing deformation of the timber structure. Relative humidity variations cause moisture changes in timber and consequently shrinkage and swelling of the material. Moisture changes and loads acting together result in mechano-sorptive creep, while sustained load gives viscoelastic creep. In some cases, magnitude of the mechano-sorptive strain can be about five times the elastic strain already at low stress levels. Therefore, analyzing mechano-sorptive creep and its influence on timber structures’ long-term behavior is of high importance. Relatively many one-dimensional rheological models for rheological behavior of wood can be found in literature, while a number of models coupling creep response in each material direction is limited. In this study, mathematical formulation of a coupled two-dimensional mechano-sorptive model and its application to the experimental results are presented. The mechano-sorptive model constitutes of a moisture transport model and a mechanical model. Variation of the moisture content in wood is modelled by multi-Fickian moisture transport model. The model accounts for processes of the bound-water and water-vapor diffusion in wood, that are coupled through sorption hysteresis. Sorption defines a nonlinear relation between moisture content and relative humidity. Multi-Fickian moisture transport model is able to accurately predict unique, non-uniform moisture content field within the timber member over time. Calculated moisture content in timber members is used as an input to the mechanical analysis. In the mechanical analysis, the total strain is assumed to be a sum of the elastic strain, viscoelastic strain, mechano-sorptive strain, and strain due to shrinkage and swelling. Mechano-sorptive response is modelled by so-called spring-dashpot type of a model, that proved to be suitable for describing creep of wood. Mechano-sorptive strain is dependent on change of moisture content. The model includes mechano-sorptive material parameters that have to be calibrated to the experimental results. The calibration is made to the experiments carried out on wooden blocks subjected to uniaxial compressive loaded in tangential direction and varying humidity conditions. The moisture and the mechanical model are implemented in a finite element software. The calibration procedure gives the required, distinctive set of mechano-sorptive material parameters. The analysis shows that mechano-sorptive strain in transverse direction is present, though its magnitude and variation are substantially lower than the mechano-sorptive strain in the direction of loading. The presented mechano-sorptive model enables observing real temporal and spatial distribution of the moisture-induced strains and stresses in timber members. Since the model’s suitability for predicting mechano-sorptive strains is shown and the required material parameters are obtained, a comprehensive advanced analysis of the stress-strain state in timber structures, including connections subjected to constant load and varying humidity is possible.

Keywords: mechanical analysis, mechano-sorptive creep, moisture transport model, timber

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Authors: Inna Kornienko, Svetlana Guryeva, Natalia Danilova, Elena Petersen

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Drug toxicity often goes undetected until clinical trials, the most expensive and dangerous phase of drug development. Both human cell culture and animal studies have limitations that cannot be overcome by improvements in drug testing protocols. Tissue engineering is an emerging alternative approach to creating models of human malignant tumors for experimental oncology, personalized medicine, and drug discovery studies. This new generation of bioengineered tumors provides an opportunity to control and explore the role of every component of the model system including cell populations, supportive scaffolds, and signaling molecules. An area that could greatly benefit from these models is cancer research. Recent advances in tissue engineering demonstrated that decellularized tissue is an excellent scaffold for tissue engineering. Decellularization of donor organs such as heart, liver, and lung can provide an acellular, naturally occurring three-dimensional biologic scaffold material that can then be seeded with selected cell populations. Preliminary studies in animal models have provided encouraging results for the proof of concept. Decellularized Organs preserve organ microenvironment, which is critical for cancer metastasis. Utilizing 3D tumor models results greater proximity of cell culture morphological characteristics in a model to its in vivo counterpart, allows more accurate simulation of the processes within a functioning tumor and its pathogenesis. 3D models allow study of migration processes and cell proliferation with higher reliability as well. Moreover, cancer cells in a 3D model bear closer resemblance to living conditions in terms of gene expression, cell surface receptor expression, and signaling. 2D cell monolayers do not provide the geometrical and mechanical cues of tissues in vivo and are, therefore, not suitable to accurately predict the responses of living organisms. 3D models can provide several levels of complexity from simple monocultures of cancer cell lines in liquid environment comprised of oxygen and nutrient gradients and cell-cell interaction to more advanced models, which include co-culturing with other cell types, such as endothelial and immune cells. Following this reasoning, spheroids cultivated from one or multiple patient-derived cell lines can be utilized to seed the matrix rather than monolayer cells. This approach furthers the progress towards personalized medicine. As an initial step to create a new ex vivo tissue engineered model of a cancer tumor, optimized protocols have been designed to obtain organ-specific acellular matrices and evaluate their potential as tissue engineered scaffolds for cultures of normal and tumor cells. Decellularized biomatrix was prepared from animals’ kidneys, urethra, lungs, heart, and liver by two decellularization methods: perfusion in a bioreactor system and immersion-agitation on an orbital shaker with the use of various detergents (SDS, Triton X-100) in different concentrations and freezing. Acellular scaffolds and tissue engineered constructs have been characterized and compared using morphological methods. Models using decellularized matrix have certain advantages, such as maintaining native extracellular matrix properties and biomimetic microenvironment for cancer cells; compatibility with multiple cell types for cell culture and drug screening; utilization to culture patient-derived cells in vitro to evaluate different anticancer therapeutics for developing personalized medicines.

Keywords: 3D models, decellularization, drug discovery, drug toxicity, scaffolds, spheroids, tissue engineering

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Authors: Obaid Algahtani

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An interval may be defined as a convex combination as follows: I=[a,b]={x_α=(1-α)a+αb: α∈[0,1]}. Consequently, we may adopt interval operations by applying the scalar operation point-wise to the corresponding interval points: I ∙J={x_α∙y_α ∶ αϵ[0,1],x_α ϵI ,y_α ϵJ}, With the usual restriction 0∉J if ∙ = ÷. These operations are associative: I+( J+K)=(I+J)+ K, I*( J*K)=( I*J )* K. These two properties, which are missing in the usual interval operations, will enable the extension of the usual linear system concepts to the interval setting in a seamless manner. The arithmetic introduced here avoids such vague terms as ”interval extension”, ”inclusion function”, determinants which we encounter in the engineering literature that deal with interval linear systems. On the other hand, these definitions were motivated by our attempt to arrive at a definition of interval random variables and investigate the corresponding statistical properties. We feel that they are the natural ones to handle interval systems. We will enable the extension of many results from usual state space models to interval state space models. The interval state space model we will consider here is one of the form X_((t+1) )=AX_t+ W_t, Y_t=HX_t+ V_t, t≥0, where A∈ 〖IR〗^(k×k), H ∈ 〖IR〗^(p×k) are interval matrices and 〖W 〗_t ∈ 〖IR〗^k,V_t ∈〖IR〗^p are zero – mean Gaussian white-noise interval processes. This feeling is reassured by the numerical results we obtained in a simulation examples.

Keywords: interval analysis, interval matrices, state space model, Kalman Filter

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Authors: Christina Wainikka, Besrat Tesfaye

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Several of the countries in the Baltic Sea region are ranked high in international innovations rankings, such as the Global Innovation Index and European Innovation Scoreboard. There are however some concerns in the performance of different countries. For example, there is a widely spread notion about “The Swedish Paradox”. Sweden is ranked high due to investments in R&D and patent activity, but the outcome is not as high as could be expected. SMEs in Sweden are also below EU average when it comes to registering intellectual property rights such as patents and trademarks. This study is concentrating on the protection of utility model. This intellectual property right does not exist in Sweden, but in for example Finland and Germany. The utility model protection is sometimes referred to as a “patent light” since it is easier to obtain than the patent protection but at the same time does cover technical solutions. In examining statistics on patent activities and activities in registering utility models it is clear that utility model protection is scarcely used in the countries that have the protection. In Germany 10 577 applications were made in 2021. In Finland there were 259 applications made in 2021. This can be compared with patent applications that were 58 568 in Germany in 2021 and 1 662 in Finland in 2021. In Sweden there has never been a protection for utility models. The only protection for technical solutions is patents and business secrets. The threshold for obtaining a patent is high, due to the legal requirements and the costs. The patent protection is there for often not chosen by SMEs in Sweden. This study examines whether the protection of utility models in other countries in the Baltic region provide SMEs in these countries with better options to protect their innovations. The legal methodology is comparative law. In order to study the effects of the legal differences statistics are examined and interviews done with SMEs from different industries.

Keywords: baltic sea region, comparative law, SME, utility model

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Authors: T. Gayen

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Although, there are several software reliability models existing today there does not exist any versatile model even today which can be used for the reliability assessment of software. Complex software has a large number of states (unlike the hardware) so it becomes practically difficult to completely test the software. Irrespective of the amount of testing one does, sometimes it becomes extremely difficult to assure that the final software product is fault free. The Black Box Software Reliability models are found be quite uncertain for the reliability assessment of various systems. As mission critical applications need to be highly reliable and since it is not always possible to ensure the development of highly reliable system. Hence, in order to achieve fault-free operation of software one develops some mechanism to handle faults remaining in the system even after the development. Although, several such techniques are currently in use to achieve fault tolerance, yet these mechanisms may not always be very suitable for various systems. Hence, this discussion is focused on analyzing the issues and challenges faced with the existing techniques for reliability assessment and fault tolerance of various software systems.

Keywords: black box, fault tolerance, failure, software reliability

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Authors: Freda Sinclair

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The purpose of this paper is to examine the impact of IPV on the family and how to best provide services for this population who suffer in silence from PTSD, medical and mental health issues and living in fear of their partner who is causing them harm. Although this is a societal issue, those in the underserved communities face even greater implications due to lack of education, language barriers, housing and financial insecurity, and overall fear of systems that seem to punish and re-traumatize them when seeking help. This paper examines the systems that treat the underserved and fail them due to their lack of knowledge, implicit biases, and failure to provide adequate time and patience to observe and provide what the family needs when they come to service providers seeking assistance and support. The methodology used examines a qualitative and quantitative study of homeless women and their families seeking safe shelter away from their partners who are causing harm. The study examines ways in which they became known to the system by way of medical, mental health, substance abuse or child welfare authorities. Found that due to the myriad of families facing countless needs, research has found that using trained therapists along with promising practice and/or evidence-based practice models best supports the needs of the families while addressing their trauma and meeting their concrete needs. The implications are that we need more trained clinicians who are sympathetic to this population and are willing to maintain up to date information to help them best serve their community and provide the best possible care. The findings give insight into how this study can be examined on a broader scale and give policy implications of how to serve best all people who are exposed to IPV, trauma, and PTSD and feel as if they are overlooked by society. There are greater implications for needed research to better support all people who live in fear of the people who harm them and best practice, support and outreach that can give best practice care to those who are in need at the most vulnerable times of their lives.

Keywords: trauma, PTSD, IPV, EBP

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Authors: Dmitriy Babenko, Sergey Yegorov, Ilya Korshukov, Aidana Sultanbekova, Valentina Barkhanskaya, Tatiana Bashirova, Yerzhan Zhunusov, Yevgeniya Li, Viktoriya Parakhina, Svetlana Kolesnichenko, Yeldar Baiken, Aruzhan Pralieva, Zhibek Zhumadilova, Matthew S. Miller, Gonzalo H. Hortelano, Anar Turmuhambetova, Antonella E. Chesca, Irina Kadyrova

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Introduction: The rapidly evolving COVID-19 pandemic, along with the re-emergence of pathogens causing acute respiratory infections (ARI), has necessitated the development of novel diagnostic tools to differentiate various causes of ARI. MALDI-MS, due to its wide usage and affordability, has been proposed as a potential instrument for diagnosing SARS-CoV-2 versus non-SARS-CoV-2 ARI. The aim of this study was to investigate the potential of MALDI-MS in conjunction with a machine learning model to accurately distinguish between symptomatic infections caused by SARS-CoV-2 and non-SARS-CoV-2 during both the early and later phases of the pandemic. Furthermore, this study aimed to analyze mass spectrometry (MS) data obtained from nasal swabs of healthy individuals. Methods: We gathered mass spectra from 252 samples, comprising 108 SARS-CoV-2-positive samples obtained in 2020 (Covid 2020), 7 SARS-CoV- 2-positive samples obtained in 2023 (Covid 2023), 71 samples from symptomatic individuals without SARS-CoV-2 (Control non-Covid ARVI), and 66 samples from healthy individuals (Control healthy). All the samples were subjected to RT-PCR testing. For data analysis, we employed the caret R package to train and test seven machine-learning algorithms: C5.0, KNN, NB, RF, SVM-L, SVM-R, and XGBoost. We conducted a training process using a five-fold (outer) nested repeated (five times) ten-fold (inner) cross-validation with a randomized stratified splitting approach. Results: In this study, we utilized the Covid 2020 dataset as a case group and the non-Covid ARVI dataset as a control group to train and test various machine learning (ML) models. Among these models, XGBoost and SVM-R demonstrated the highest performance, with accuracy values of 0.97 [0.93, 0.97] and 0.95 [0.95; 0.97], specificity values of 0.86 [0.71; 0.93] and 0.86 [0.79; 0.87], and sensitivity values of 0.984 [0.984; 1.000] and 1.000 [0.968; 1.000], respectively. When examining the Covid 2023 dataset, the Naive Bayes model achieved the highest classification accuracy of 43%, while XGBoost and SVM-R achieved accuracies of 14%. For the healthy control dataset, the accuracy of the models ranged from 0.27 [0.24; 0.32] for k-nearest neighbors to 0.44 [0.41; 0.45] for the Support Vector Machine with a radial basis function kernel. Conclusion: Therefore, ML models trained on MALDI MS of nasopharyngeal swabs obtained from patients with Covid during the initial phase of the pandemic, as well as symptomatic non-Covid individuals, showed excellent classification performance, which aligns with the results of previous studies. However, when applied to swabs from healthy individuals and a limited sample of patients with Covid in the late phase of the pandemic, ML models exhibited lower classification accuracy.

Keywords: SARS-CoV-2, MALDI-TOF MS, ML models, nasopharyngeal swabs, classification

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Authors: Marina Fomina

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The paper focuses on the category of semantic subject within the framework of a functional approach to linguistics. The semantic subject is related to similar notions such as the grammatical subject and the bearer of predicative feature. It is the multifaceted nature of the category of subject that 1) triggers a number of issues that, syntax-wise, remain to be dealt with (cf. semantic vs. syntactic functions / sentence parts vs. parts of speech issues, etc.); 2) results in a variety of approaches to the category of subject, such as formal grammatical, semantic/syntactic (functional), communicative approaches, etc. Many linguists consider the prototypical approach to the category of subject to be the most instrumental as it reveals the integrity of denotative and linguistic components of the conceptual category. This approach relates to subject as a source of non-passive predicative feature, an element of subject-predicate-object situation that can take on a variety of semantic roles, cf.: 1) an agent (He carefully surveyed the valley stretching before him), 2) an experiencer (I feel very bitter about this), 3) a recipient (I received this book as a gift), 4) a causee (The plane broke into three pieces), 5) a patient (This stove cleans easily), etc. It is believed that the variety of roles stems from the radial (prototypical) structure of the category with some members more central than others. Translation-wise, the most “treacherous” subject types are the peripheral ones. The paper 1) features a peripheral status of spatial impersonal sentence models such as U menia v ukhe zvenit (lit. I-Gen. in ear buzzes) within the category of semantic subject, 2) makes a structural and semantic analysis of the models, 3) focuses on their Russian-English translation patterns, 4) reveals non-prototypical features of subjects in the English equivalents.

Keywords: bearer of predicative feature, grammatical subject, impersonal sentence model, semantic subject

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Authors: Lucia Perez, Maria Gaton y Santa Palella

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Starting from the etymology of the word culture, the Latin term ‘colere’, whose meaning is to cultivate, we understand that the society that cultivates its knowledge is laying the foundations for new possibilities. In this sense, art and fashion contain the same attributes: concept, aesthetic principles, and refined techniques. Both play a crucial role, communication, and this implies a sense of community, relationship with tradition, and innovation. This is the mirror in which to contemplate, but also the space that helps to grow. This is the framework where our object of study opens up: the anthropological management or the mission management model applied to fashion exhibitions in museums and cultural institutions. For this purpose, a bibliographic review has been carried out with its subsequent analysis, a case study of three successful exhibitions: ‘Christian Dior: designer of dreams’, ‘Balenciaga and the Spanish painting’, and ‘China: Through the Looking Glass’. The methodology has been completed with interviews focused on the curators. Amongst the results obtained, it is worth highlighting the fundamental role of transcendent leadership, which, in addition to being results-oriented, must align the motivations of the collaborators with the mission. The anthropological management model conceives management as a service, and it is oriented to the interests of the staff and the public, in short, of the person; this is what enables the objectives of effectiveness, efficiency, and social value to be achieved; dimensions, all necessary for the proper development of the mission of the exhibitions. Fashion, understood as art, is at the service of culture, and therefore of the human being, which defines a transcendent mission. We conclude that the profile of an anthropological management model applied to fashion exhibitions in museums is the ideal one to achieve the purpose of these institutions.

Keywords: art, culture, fashion, anthropological model, fashion exhibitions

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Authors: Matan Cohen, Maxim Shoshany

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Climatic, topographic and geological diversity, together with frequent disturbance and recovery cycles, produce highly complex spatial patterns of trees, shrubs, dwarf shrubs and bare ground patches. Assessment of spatial and temporal variations of these life-forms patterns under climate change is of high ecological priority. Here we report on one of the first attempts to discriminate between images of three Mediterranean life-forms patterns at three densities. The development of an extensive database of orthophoto images representing these 9 pattern categories was instrumental for training and testing pre-trained and newly-trained DL models utilizing DenseNet architecture. Both models demonstrated the advantages of using Deep Learning approaches over existing spectral and spatial (pattern or texture) algorithmic methods in differentiation 9 life-form spatial mixtures categories.

Keywords: texture classification, deep learning, desert fringe ecosystems, climate change

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Authors: Rutej R. Mehta, Michael A. Chappell

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Introduction: Arterial spin labelling (ASL) is an increasingly popular perfusion MRI technique, in which arterial blood water is magnetically labelled in the neck before flowing into the brain, providing a non-invasive measure of cerebral blood flow (CBF). The accuracy of ASL CBF measurements, however, is hampered by dispersion effects; the distortion of the ASL labelled bolus during its transit through the vasculature. In spite of this, the current recommended implementation of ASL – the white paper (Alsop et al., MRM, 73.1 (2015): 102-116) – does not account for dispersion, which leads to the introduction of errors in CBF. Given that the transport time from the labelling region to the tissue – the arterial transit time (ATT) – depends on the region of the brain and the condition of the patient, it is likely that these errors will also vary with the ATT. In this study, various dispersion models are assessed in comparison with the white paper (WP) formula for CBF quantification, enabling the errors introduced by the WP to be quantified. Additionally, this study examines the relationship between the errors associated with the WP and the ATT – and how this is influenced by dispersion. Methods: Data were simulated using the standard model for pseudo-continuous ASL, along with various dispersion models, and then quantified using the formula in the WP. The ATT was varied from 0.5s-1.3s, and the errors associated with noise artefacts were computed in order to define the concept of significant error. The instantaneous slope of the error was also computed as an indicator of the sensitivity of the error with fluctuations in ATT. Finally, a regression analysis was performed to obtain the mean error against ATT. Results: An error of 20.9% was found to be comparable to that introduced by typical measurement noise. The WP formula was shown to introduce errors exceeding 20.9% for ATTs beyond 1.25s even when dispersion effects were ignored. Using a Gaussian dispersion model, a mean error of 16% was introduced by using the WP, and a dispersion threshold of σ=0.6 was determined, beyond which the error was found to increase considerably with ATT. The mean error ranged from 44.5% to 73.5% when other physiologically plausible dispersion models were implemented, and the instantaneous slope varied from 35 to 75 as dispersion levels were varied. Conclusion: It has been shown that the WP quantification formula holds only within an ATT window of 0.5 to 1.25s, and that this window gets narrower as dispersion occurs. Provided that the dispersion levels fall below the threshold evaluated in this study, however, the WP can measure CBF with reasonable accuracy if dispersion is correctly modelled by the Gaussian model. However, substantial errors were observed with other common models for dispersion with dispersion levels similar to those that have been observed in literature.

Keywords: arterial spin labelling, dispersion, MRI, perfusion

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Authors: Lluís Bermúdez, Isabel Morillo

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Road safety involves carrying out a determined and explicit policy to reduce accidents. In the city of Barcelona, through the Local Road Safety Plan 2013-2018, in line with the framework that has been established at the European and state level, a series of preventive, corrective and technical measures are specified, with the priority objective of reducing the number of serious injuries and fatalities. In this work, based on the data from the accidents managed by the local police during the period 2010-2019, an analysis is carried out to verify whether the measures established in the Plan to reduce the accident rate have had an effect or not and to what extent. The analysis focuses on the type of accident and the type of vehicles involved. Different count regression models have been fitted, from which it can be deduced that the number of serious and fatal victims of the accidents that have occurred in the city of Barcelona has been reduced as the measures approved by the authorities.

Keywords: accident reduction, count regression models, road safety, urban traffic

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Authors: Ian O'Loughlin

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Memory networks aim to integrate some of the recent successes in machine learning with a dynamic memory base that can be updated and deployed in artificial reasoning tasks. These models involve training networks to identify, update, and operate over stored elements in a large memory array in order, for example, to ably perform question and answer tasks parsing real-world and simulated discourses. This family of approaches still faces numerous challenges: the performance of these network models in simulated domains remains considerably better than in open, real-world domains, wide-context cues remain elusive in parsing words and sentences, and even moderately complex sentence structures remain problematic. This innovation, employing an array of stored and updatable ‘memory’ elements over which the system operates as it parses text input and develops responses to questions, is a compelling one for at least two reasons: first, it addresses one of the difficulties that standard machine learning techniques face, by providing a way to store a large bank of facts, offering a way forward for the kinds of long-term reasoning that, for example, recurrent neural networks trained on a corpus have difficulty performing. Second, the addition of a stored long-term memory component in artificial reasoning seems psychologically plausible; human reasoning appears replete with invocations of long-term memory, and the stored but dynamic elements in the arrays of memory networks are deeply reminiscent of the way that human memory is readily and often characterized. However, this apparent psychological plausibility is belied by a recent turn in the study of human memory in cognitive science. In recent years, the very notion that there is a stored element which enables remembering, however dynamic or reconstructive it may be, has come under deep suspicion. In the wake of constructive memory studies, amnesia and impairment studies, and studies of implicit memory—as well as following considerations from the cognitive neuroscience of memory and conceptual analyses from the philosophy of mind and cognitive science—researchers are now rejecting storage and retrieval, even in principle, and instead seeking and developing models of human memory wherein plasticity and dynamics are the rule rather than the exception. In these models, storage is entirely avoided by modeling memory using a recurrent neural network designed to fit a preconceived energy function that attains zero values only for desired memory patterns, so that these patterns are the sole stable equilibrium points in the attractor network. So although the array of long-term memory elements in memory networks seem psychologically appropriate for reasoning systems, they may actually be incurring difficulties that are theoretically analogous to those that older, storage-based models of human memory have demonstrated. The kind of emergent stability found in the attractor network models more closely fits our best understanding of human long-term memory than do the memory network arrays, despite appearances to the contrary.

Keywords: artificial reasoning, human memory, machine learning, neural networks

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Authors: Perpetual Nwakaego Ibe

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The Millennium Development Goals (MDGs), were an integrated project formed to eradicate many unnatural situations the citizens of the third world country may found themselves in. The MDGs, to be a sustainable project for the future depends 100% on the actions of governments, multilateral institutions and civil society. This paper first looks at the political views on the MDGs and relates it to the current electoral situations around the country by underlining the drastic changes over the few months. The second part of the paper presents ICT in tertiary institutions as one of the solutions in terms of the success of the MDGs. ICT is vital in all phases of educational process and development of the cloud connectivity is an added advantage of Information and Communication Technology (ICT) for sharing a common data bank for research purposes among UNICEF, RED CROSS, NPS, INEC, NMIC, and WHO. Finally, the paper concludes with areas that needs twigging and recommendations for the tertiary institutions committed to delivering an ambitious set of goals. A combination of observation, and document materials for data gathering was employed as the methodology for carrying out this research.

Keywords: MDG, ICT, data bank, database

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Authors: Abobaker Mohammed Qasem Farhan, Olof M. A. Saif

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The demand for parking spaces in urban areas, particularly in developing countries, has led to a significant issue in the absence of sufficient parking spaces in crowded areas, which results in daily traffic congestion as drivers search for parking. This not only affects the appearance of the city but also has indirect impacts on the economy, society, and environment. In response to these challenges, researchers from various countries have sought technical and intelligent solutions to mitigate the problem through the development of smart parking systems. This paper aims to analyze and design three models of parking lots, with a focus on parking time and security. The study used computer software and Uppaal tools to simulate the models and determine the best among them. The results and suggestions provided in the paper aim to reduce the parking problems and improve the overall efficiency and safety of the parking process. The conclusion of the study highlights the importance of utilizing advanced technology to address the pressing issue of insufficient parking spaces in urban areas.

Keywords: preliminaries, system requirements, timed Au- tomata, Uppaal

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Authors: Carly Nesvat, Dominic Jarrett, Colin Thomson, Wilma Coltart, Thelma Bowers, Jan Thomson

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Introduction: Within Scotland, the Same As You strategy committed to moving people with learning disabilities out of long-stay hospital accommodation into homes in the community. Much of the focus of this movement was on the placement of people within individual homes. In order to achieve this, potentially excessive supports were put in place which created dependence, and carried significant ongoing cost primarily for local authorities. The greater focus on empowerment and community participation which has been evident in more recent learning disability strategy, along with the financial pressures being experienced across the public sector, created an imperative to re-examine that provision, particularly in relation to the use of expensive sleepover supports to individuals, and the potential for this to be appropriately scaled back through the use of telecare. Method: As part of a broader programme of redesigning overnight supports within North Ayrshire, a cluster of individuals living in close proximity were identified, who were in receipt of overnight supports, but who were identified as having the capacity to potentially benefit from their removal. In their place, a responder service was established (an individual staying overnight in a nearby service user’s home), and a variety of telecare solutions were placed within individual’s homes. Active and passive technology was connected to an Alarm Receiving Centre, which would alert the local responder service when necessary. Individuals and their families were prepared for the change, and continued to be informed about progress with the pilot. Results: 4 individuals, 2 of whom shared a tenancy, had their sleepover supports removed as part of the pilot. Extensive data collection in relation to alarm activation was combined with feedback from the 4 individuals, their families, and staff involved in their support. Varying perspectives emerged within the feedback. 3 of the individuals were clearly described as benefitting from the change, and the greater sense of independence it brought, while more concerns were evident in relation to the fourth. Some family members expressed a need for greater preparation in relation to the change and ongoing information provision. Some support staff also expressed a need for more information, to help them understand the new support arrangements for an individual, as well as noting concerns in relation to the outcomes for one participant. Conclusion: Developing a telecare response in relation to a cluster of individuals was facilitated by them all being supported by the same care provider. The number of similar clusters of individuals being identified within North Ayrshire is limited. Developing other solutions such as a response service for redesign will potentially require greater collaboration between different providers of home support, as well as continuing to explore the full range of telecare, including digital options. The pilot has highlighted the need for effective preparatory and ongoing engagement with staff and families, as well as the challenges which can accompany making changes to long-standing packages of support.

Keywords: challenges, change, engagement, telecare

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