Search results for: information warfare techniques

Authors: Ana Nemsadze

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Contemporary era and society are called postindustrial era and postindustrial society and/or informational era and informational society. Today science intends to define concept of information and comprehend informations role and function in contemporary society. Organization of social environment and governance of public processes on the base of information and tools of communication are main characteristics of informational era. This was defined by technological changes which were accomplished in culture in the second half of twentieth century. Today Georgia as an independent state needs to create an informational discourse of the country and therefore it is very important to study political and social cases which accomplished in the country after collapse of the Soviet Union because they start to define the present and the future of the country. The purpose of this study is to analyze political cases of the latest history of Georgia in terms of culture and information, concretely to elucidate which political cases transformed social life of post Soviet Georgia most of all who accomplished these political cases which visual and verbal messages was each political case spread with. The research is conducted on the base of interview. Participants of the interview are people of various specializations. Their professional activity is related to reflections on culture and theme of visual communication. They are philosophers sociologists a journalist media researcher a politologist a painter. The participants of the interview enumerated political cases and characterized them separately. Every expert thinks that declaration of independence of Georgia is the most important fact among all facts which were implemented in Georgia after collapse of the Soviet Union. The research revealed important social and political cases. Most of the cases are related to independence and territorial integrity of the state. Presidents of Georgia Zviad Gamsakhurdia Eduard Shevardnadze Mikheil Saakashvili Catholocos-Patriarch of All Georgia, the Archbishop of Mtskheta Tbilisi and Metropolitan bishop of Bichvinta and Tskhum Abkhazia Ilia II, businessman Bidzina Ivanishvili assumed dominating roles in cases. Verbal narrative of the cases accomplished during Zviad Gamsakhurdia presidential term expresses national freedom and visual part of cases of the same period expresses ruin of social-political structure. Verbal narrative of the cases accomplished during Eduard Sevardnadze presidential term expresses Free State and stability and reestablishment of Georgias political function in international relations and visual part of cases of the same period describes the most important moment of his presidential term and Eduard Shevardnadzes face appears too. Verbal narrative of the cases accomplished during Mikheil Saakashvilis presidential term expresses social renewal and visual part of cases of the same period describes August war and Mikheil Saakashvilis face appears too. The results of the study also reveal other details of visual verbal narrative of political and social cases of post Soviet Georgia. This gives a chance to start further reflection.

Keywords: culture, narrative, post soviet, visual communication

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Authors: Shaibu Salifu, Ofori Boachie

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Philanthropy is part and parcel of African identity; it is intrinsically embedded in the life of Africans where at any point in time people contribute to philanthropy through giving or receiving. Even though, research on corporate philanthropy has gained attention in the academic space of Ghana, little have been done on the effects of corporate foundation giving on female labour force participation in Ghana. We investigate the effects of corporate foundations giving on female labour force participation in Ghana. We applied convenient and purposive sampling techniques to collect qualitative data from thirty (30) women in Ghana through interviews and open-ended questionnaires. We used Nvivo to carryout analysis on the data and our results indicate that corporate foundation giving has significant effect on female labour force participation in Ghana. In addition, contrary to the feminization U-Shape Hypothesis, evidence suggest that, to a larger extent marriage and fertility (birth) of women positively contribute to the female labour force participation in Ghana. Nevertheless, the study was limited by the number of women who were interviewed, time constraints of women for elaborate discussions on the issues (constructs) of the study and fear of victimization by authorities on most of their responses to the interviews. The findings have implications for all stakeholders of philanthropy: academia, governments, civil society organizations, corporate foundations, women of Ghana and other relevant bodies.

Keywords: corporate philanthropy, corporate foundations, corporate foundation giving, female labour force participation, women, Ghana

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Authors: Alisha Sinha, Laxmi Kant Sharma

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Forest fires are a recurring issue in many parts of the world, including India. These fires can have various causes, including human activities (such as agricultural burning, campfires, or discarded cigarettes) and natural factors (such as lightning). This study presents a comprehensive and advanced methodology for assessing wildfire susceptibility by integrating diverse environmental variables and leveraging cutting-edge machine learning techniques across Rajasthan, India. The primary goal of the study is to utilize Google Earth Engine to compare locations in Sariska National Park, Rajasthan (India), before and after forest fires. High-resolution satellite data were used to assess the amount and types of changes caused by forest fires. The present study meticulously analyzes various environmental variables, i.e., slope orientation, elevation, normalized difference vegetation index (NDVI), drainage density, precipitation, and temperature, to understand landscape characteristics and assess wildfire susceptibility. In addition, a sophisticated random forest regression model is used to predict land surface temperature based on a set of environmental parameters.

Keywords: wildfire susceptibility mapping, LST, random forest, GEE, MODIS, climatic parameters

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Authors: Mike R. Bambach

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Increasing awareness of environmental concerns is leading a drive towards more sustainable structural products for the built environment. Natural fibres such as flax, jute and hemp have recently been considered for fibre-resin composites, with a major motivation for their implementation being their notable sustainability attributes. While recent decades have seen substantial interest in the use of such natural fibres in composite materials, much of this research has focused on the materials aspects, including fibre processing techniques, composite fabrication methodologies, matrix materials and their effects on the mechanical properties. The present study experimentally investigates the compression strength of structural channel sections of flax, jute and hemp, with a particular focus on their suitability for residential stud wall applications. The section geometry is optimised for maximum strength via the introduction of complex stiffeners in the webs and flanges. Experimental results on both natural fibre composite channel sections and typical steel and timber residential wall studs are compared. The geometrically optimised natural fibre composite channels are shown to have compression capacities suitable for residential wall stud applications, identifying them as a potentially viable alternative to traditional building materials in such application, and potentially other light structural applications.

Keywords: channel sections, natural fibre composites, residential stud walls, structural composites

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Authors: Gaurav Kumar Sinha

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The volatility of the oil market, influenced by geopolitical, economic, and environmental factors, presents significant challenges for stakeholders in predicting trends and demand. This article explores the application of artificial intelligence (AI) in developing robust forecasting models to anticipate changes in the oil market more accurately. We delve into various AI techniques, including machine learning, deep learning, and time series analysis, that have been adapted to analyze historical data and current market conditions to forecast future trends. The study evaluates the effectiveness of these models in capturing complex patterns and dependencies in market data, which traditional forecasting methods often miss. Additionally, the paper discusses the integration of external variables such as political events, economic policies, and technological advancements that influence oil prices and demand. By leveraging AI, stakeholders can achieve a more nuanced understanding of market dynamics, enabling better strategic planning and risk management. The article concludes with a discussion on the potential of AI-driven models in enhancing the predictive accuracy of oil market forecasts and their implications for global economic planning and strategic resource allocation.

Keywords: AI forecasting, oil market trends, machine learning, deep learning, time series analysis, predictive analytics, economic factors, geopolitical influence, technological advancements, strategic planning

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Authors: Zahzouh Zoubir, Bouzaouit Azzeddine, Gahgah Mounir

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The use of more and more electronic power switches with a nonlinear behavior generates non-sinusoidal currents in distribution networks, which causes damage to domestic and industrial equipment. The multi-level shunt power active filter is subsequently shown to be an adequate solution to the problem raised. Nevertheless, the difficulty of adjusting the active filter DC supply voltage requires another technology to ensure it. In this article, a photovoltaic generator is associated with the DC bus power terminals of the active filter. The proposed system consists of a field of solar panels, three multi-level voltage inverters connected to the power grid and a non-linear load consisting of a six-diode rectifier bridge supplying a resistive-inductive load. Current control techniques of active and reactive power are used to compensate for both harmonic currents and reactive power as well as to inject active solar power into the distribution network. An algorithm of the search method of the maximum power point of type Perturb and observe is applied. Simulation results of the system proposed under the MATLAB/Simulink environment shows that the performance of control commands that reassure the solar power injection in the network, harmonic current compensation and power factor correction.

Keywords: Actif power filter, MPPT, pertub&observe algorithm, PV array, PWM-control

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Authors: L. Bih Ni, D. Norizah Ag Kiflee, T. Choon Keong, R. Talip, S. Singh Bikar Singh, M. Noor Mad Japuni, R. Talin

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The purpose of this study is to determine the effectiveness of video clips to enhance students' achievement and motivation towards learning and facilitating of history. We use narrative literature studies to illustrate the current state of the two art and science in focused areas of inquiry. We used experimental method. The experimental method is a systematic scientific research method in which the researchers manipulate one or more variables to control and measure any changes in other variables. For this purpose, two experimental groups have been designed: one experimental and one groups consisting of 30 lower secondary students. The session is given to the first batch using a computer presentation program that uses video clips to be considered as experimental group, while the second group is assigned as the same class using traditional methods using dialogue and discussion techniques that are considered a control group. Both groups are subject to pre and post-trial in matters that are handled by the class. The findings show that the results of the pre-test analysis did not show statistically significant differences, which in turn proved the equality of the two groups. Meanwhile, post-test analysis results show that there was a statistically significant difference between the experimental group and the control group at an importance level of 0.05 for the benefit of the experimental group.

Keywords: Video clips, Learning and Facilitation, Achievement, Motivation

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Authors: Mukadder Baran, Mustafa Sözbilir

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The purpose of this paper is to investigate the applicabillity of the Context- and Problem-Based Learning (CPBL) in general chemistry course to the subject of “Thermodynamics” but also the influence of CPBL on students’ achievement, retention of knowledge, their interest, attitudes, motivation and problem-solving skills. The study group included 13 freshman students who were selected with the sampling method appropriate to the purpose among those taking the course of General Chemistry within the Program of Medical Laboratory Techniques at Hakkari University. The application was carried out in the Spring Term of the academic year of 2012-2013. As the data collection tool, Lesson Observation form were used. In the light of the observations held, it was revealed that CPBL increased the students’ intragroup and intergroup communication skills as well as their self-confidence and developed their skills in time management, presentation, reporting, and technology use; and that they were able to relate chemistry to daily life. Depending on these findings, it could be suggested that the area of use of CPBL be widened; that seminars related to constructive methods be organized for teachers. In this way, it is believed that students will not be passive in the group any longer. In addition, it was concluded that in order to avoid the negative effects of the socio-cultural structure on the education system, research should be conducted in places where there is socio-cultural obstacles, and appropriate solutions should be suggested and put into practice.

Keywords: chemistry, education, science, context-based learning

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Authors: W. Thongkham, K. Sinthiptharakoon, K. Tantisantisom, A. Klamchuen, P. Khanchaitit, K. Jiramitmongkon, C. Lertsatitthanakorn, M. Liangruksa

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Due to demands of sustainable energy, thermoelectricity converting waste heat into electrical energy has become one of the intensive fields of worldwide research. However, such harvesting technology has shown low device performance in the temperature range below 150℃. In this work, a hybrid nanowire of inorganic bismuth telluride (Bi₂Te₃) and organic poly(3,4-ethylenedioxythiophene):polystyrenesulfonate (PEDOT:PSS) synthesized using a simple in-situ one-pot synthesis, enhancing efficiency of the nanowire-incorporated PEDOT:PSS-based thermoelectric converter is highlighted. Since the improvement is ascribed to the increased electrical conductivity of the thermoelectric host material, the individual hybrid nanowires are investigated using voltage-dependent conductive atomic force microscopy (CAFM) and spectroscopy (CAFS) considering that the electrical transport measurement can be performed either on insulating or conducting areas of the sample. Correlated with detailed chemical information on the crystalline structure and compositional profile of the nanowire core-shell structure, an electrical transporting pathway through the nanowire and the corresponding electronic-band structure have been determined, in which the native oxide layer on the Bi₂Te₃ surface is not considered, and charge conduction on the topological surface states of Bi₂Te₃ is suggested. Analyzing the core-shell nanowire synthesized using the conventional mixing of as-prepared Bi₂Te₃ nanowire with PEDOT:PSS for comparison, the oxide-removal effect of the in-situ encapsulating polymeric layer is further supported. The finding not only provides a structural information for mechanistic determination of the thermoelectricity, but it also encourages new approach toward more appropriate encapsulation and consequently higher efficiency of the nanowire-based thermoelectric generation.

Keywords: electrical transport measurement, hybrid Bi₂Te₃-PEDOT:PSS nanowire, nanoencapsulation, thermoelectricity, topological insulator

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Authors: Bassem Saleh, Hussam Nusair, Nariman Al Zubadi, Shams Al Shloul, Usama Saleh

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The nursing round system (NRS) means checking patients on an hourly basis during the A (0700–2200 h) shift and once every 2 h during the B (2200–0700 h) by the assigned nursing staff. The overall goal of this prospective study is to implement an NRS in a major rehabilitation centre—Sultan Bin Abdulaziz Humanitarian City—in the Riyadh area of the Kingdom of Saudi Arabia. The purposes of this study are to measure the effect of the NRS on: (i) the use of patient call light; (ii) the number of incidences of patients’ fall; (iii) the number of incidences of hospital-acquired bed sores; and (iv) the level of patients’ satisfaction. All patients hospitalized in the male stroke unit will be involved in this study. For the period of 8 weeks (17 December 2009–17 February 2010) All Nursing staff on the unit will record each call light and the patient’s need. Implementation of the NRS would start on 18 February 2010 and last for 8 weeks, until 18 April 2010. Data collected throughout this period will be compared with data collected during the 8 weeks period immediately preceding the implementation of the NRS (17 December 2009–17 February 2010) in order to measure the impact of the call light use. The following information were collected on all subjects involved in the study: (i) the Demographic Information Form; (ii) authors’ developed NRS Audit Form; (iii) Patient Call Light Audit Form; (iv) Patient Fall Audit Record; (v) Hospital-Acquired Bed Sores Audit Form; and (vi) hospital developed Patient Satisfaction Records. The findings suggested that a significant reduction on the use of call bell (P < 0.001), a significant reduction of fall incidence (P < 0.01) while pressure ulcer reduced by 50% before and after the implementation of NRS. In addition, the implementation of NRS increased patient satisfaction by 7/5 (P < 0.05).

Keywords: call light, patient-care management, patient safety, patient satisfaction, rounds

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Authors: Ebipatei Victoria Tunyan, T. A. Cao, Cheol Young Ock

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Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.

Keywords: subjective bias detection, machine learning, BERT–BiLSTM–Attention, text classification, natural language processing

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Authors: Khalid M. Kheiralla, Georgios Boutsis, Mohammed Y. Abdelgalil, Mohammed A. Ali, Nuha E. Mohamed

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The present study focus on integrated geoelectrical surveys carried out in the mineralization zone in Erkowit region, Eastern Sudan to determine the extensions of the potential ore deposits on the topographically high hilly area and under the cover of alluvium along the nearby wadi and to locate other occurrences if any. The magnetic method (MAG) and the electrical resistivity tomography (ERT) were employed for the survey. Eleven traverses were aligned approximately at right angles to the general strike of the rock formations. The disseminated sulfides are located on the alteration shear zone which is composed of granitic and dioritic highly ferruginated rock occupying the southwestern and central parts of the area, this was confirmed using thin and polished sections mineralogical analysis. The magnetic data indicates low magnetic values for wadi sedimentary deposits in its southern part of the area, and high anomalies which are suspected as gossans due to magnetite formed during wall rock alteration consequent to mineralization. The significant ERT images define low resistivity zone as traced as sheared zones which may associated with the main loci of ore deposition. By itself, no geophysical anomaly can simply be correlated with lithology, instead, magnetic and ERT anomalies raised due to variations in some specific physical properties of rocks which were extremely useful in mineral exploration.

Keywords: ERT, magnetic, mineralization, Red Sea, Sudan

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Authors: Neriman Ozada, Ebrahim Karamian, Amirsalar Khandan, Sina Ghafoorpoor Yazdi

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Natural hydroxyapatite, NHA, coatings on the surface of 316 L stainless steel implants has been widely employed in order to achieve better osteoconductivity. For coating, the plasma spraying method is generally used because they ensure adhesion between the coating and the 316 L stainless steel (SS) surface. Some compounds such as zircon (ZrSiO4) is employed as an additive in an attempt to improve HA’s mechanical properties such as wear resistance and hardness. In this study wear resistance has been carried out in different chemical compositions of coating. Therefore, nanocomposites based on NHA containing of 0 wt.%, 5 wt.%, 10 wt.%, and 15 wt.% of zircon were used as a coating on the SS implants. The samples consisted of NHA, derived from calf heated at 850 °C for 3 h. The composite mixture was coated on SS by plasma spray method. The results were estimated using the scanning electron microscopy (SEM), X-ray diffraction (XRD) techniques were utilized to characterize the shape and size of NHA powder. Disc wear test and Vickers hardness were utilized to characterize the coated nanocomposite samples. The prepared NHA powder had nano-scale morphological structure with the mean crystallite size of 30-50 nm in diameter. The wear resistance are almost 320, 380, 415, and 395 m/g and hardness are approximately 376, 391, 420, 410 VHN in ceramic composite materials containing ZrSiO4. The results have been shown that the best wear resistance and hardness occurred in the sample coated by NHA/ZrSiO4 containing of 10 wt.% of zircon.

Keywords: zircon, 316 L stainless steel, wear resistance, orthopedic applications, plasma spray

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Authors: Qisheng Hu, Jianglei Han, Yue Yang, My Hoa Ha

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When a company is considering purchasing software for commercial use, contract risk assessment is critical to identify risks to mitigate the potential adverse business impact, e.g., security, financial and regulatory risks. Contract risk assessment requires reviewers with specialized knowledge and time to evaluate the legal documents manually. Specifically, validating contracts for a software vendor requires the following steps: manual screening, interpreting legal documents, and extracting risk-prone segments. To automate the process, we proposed a framework to assist legal contract document risk identification, leveraging pre-trained deep learning models and natural language processing techniques. Given a set of pre-defined risk evaluation problems, our framework utilizes the pre-trained transformer-based models for question-answering to identify risk-prone sections in a contract. Furthermore, the question-answering model encodes the concatenated question-contract text and predicts the start and end position for clause extraction. Due to the limited labelled dataset for training, we leveraged transfer learning by fine-tuning the models with the CUAD dataset to enhance the model. On a dataset comprising 287 contract documents and 2000 labelled samples, our best model achieved an F1 score of 0.687.

Keywords: contract risk assessment, NLP, transfer learning, question answering

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Authors: Javad Rahimipour Anaraki, Saeed Samet, Mahdi Eftekhari, Chang Wook Ahn

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Feature selection and attribute reduction are crucial problems, and widely used techniques in the field of machine learning, data mining and pattern recognition to overcome the well-known phenomenon of the Curse of Dimensionality. This paper presents a feature selection method that efficiently carries out attribute reduction, thereby selecting the most informative features of a dataset. It consists of two components: 1) a measure for feature subset evaluation, and 2) a search strategy. For the evaluation measure, we have employed the fuzzy-rough dependency degree (FRFDD) of the lower approximation-based fuzzy-rough feature selection (L-FRFS) due to its effectiveness in feature selection. As for the search strategy, a modified version of a binary shuffled frog leaping algorithm is proposed (B-SFLA). The proposed feature selection method is obtained by hybridizing the B-SFLA with the FRDD. Nine classifiers have been employed to compare the proposed approach with several existing methods over twenty two datasets, including nine high dimensional and large ones, from the UCI repository. The experimental results demonstrate that the B-SFLA approach significantly outperforms other metaheuristic methods in terms of the number of selected features and the classification accuracy.

Keywords: binary shuffled frog leaping algorithm, feature selection, fuzzy-rough set, minimal reduct

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Authors: Benniche Omar

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We are concerned with abstract fully nonlinear differential equations having the form y’(t)=Ay(t)+f(t,y(t)) where A is an m—dissipative operator (possibly multi—valued) defined on a subset D(A) of a Banach space X with values in X and f is a given function defined on I×X with values in X. We consider a graph K in I×X. We recall that K is said to be viable with respect to the above abstract differential equation if for each initial data in K there exists at least one trajectory starting from that initial data and remaining in K at least for a short time. The viability problem has been studied by many authors by using various techniques and frames. If K is closed, it is shown that a tangency condition, which is mainly linked to the dynamic, is crucial for viability. In the case when X is infinite dimensional, compactness and convexity assumptions are needed. In this paper, we are concerned with the notion of near viability for a given graph K with respect to y’(t)=Ay(t)+f(t,y(t)). Roughly speaking, the graph K is said to be near viable with respect to y’(t)=Ay(t)+f(t,y(t)), if for each initial data in K there exists at least one trajectory remaining arbitrary close to K at least for short time. It is interesting to note that the near viability is equivalent to an appropriate tangency condition under mild assumptions on the dynamic. Adding natural convexity and compactness assumptions on the dynamic, we may recover the (exact) viability. Here we investigate near viability for a graph K in I×X with respect to y’(t)=Ay(t)+f(t,y(t)) where A and f are as above. We emphasis that the t—dependence on the perturbation f leads us to introduce a new tangency concept. In the base of a tangency conditions expressed in terms of that tangency concept, we formulate criteria for K to be near viable with respect to y’(t)=Ay(t)+f(t,y(t)). As application, an abstract null—controllability theorem is given.

Keywords: abstract differential equation, graph, tangency condition, viability

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Authors: Ejaz Ashraf, Raheel Babar, Muhammad Yaseen, Hafiz Khurram Shurjeel, Nosheen Fatima

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Main purpose of this study was to assess adoption level of farmers for quinoa cultivation after they had been taught through training and visit extension approach. At this time of the 21^st century, population structure, climate change, food requirements and eating habits of people are changing rapidly. In this scenario, farmers must play their key role in sustainable crop development and production through adoption of new crops that may also be helpful to overcome the issue of food insecurity as well as reducing poverty in rural areas. Its cultivation in Pakistan is at the early stages and there is a need to raise awareness among farmers to grow quinoa crops. In the middle of the 2015, a training and visit extension approach was used to raise awareness and convince farmers to grow quinoa in the area. During training and visit extension program, 80 farmers were randomly selected for the training of quinoa cultivation. Later on, these farmers trained 60 more farmers living into their neighborhood. After six months, a survey was conducted with all 140 farmers to assess the impact of the training and visit program on adoption level of respondents for the quinoa crop. The survey instrument was developed with the help of literature review and other experts of the crop. Validity and reliability of the instrument were checked before complete data collection. The data were analyzed by using SPSS. Multiple regression analysis was used for interpretation of the results from the survey, which indicated that factors like information/ training, change in agronomic and plant protection practices play a key role in the adoption of quinoa cultivation by respondents. In addition, the model explains more than 50% of variation in the adoption level of respondents. It is concluded that farmers need timely information for improved knowledge of agronomic and plant protection practices to adopt cultivation of the quinoa crop in the area.

Keywords: farmers, quinoa, adoption, contact, training and visit

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Authors: Hummad Ch. Umar

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Most of the developing economies, including Pakistan, are confronted with high level of external debt which is adversely affecting their economic performance. The hypothesis of debt overhang is often used to assess the negative relationship between foreign debt and the economic growth of the indebted country. As first objective of the present study, this hypothesis is tested by using Pooled OLS (POLS), Generalized Method of Moment (GMM), Random Effect (RE), and Fixed effect (FE) techniques. As second objective, the study uses the concept of debt Laffer Curve to determine the eligibility condition of the indebted countries for the relief programs. According to this approach, countries lying on the right side of the Laffer Curve are stated to be trapped in the strong debt overhang making them unable to come out of the vicious circle of low growth and high foreign debt. The empirical analysis confirms that only two countries out of twenty two completely fulfill the conditions of being eligible for the debt relief. All other countries continue to face debt burden of different magnitudes. The study further confirms that the debt relief alone is not sufficient for overcoming the debt problem. Instead, sound economic policies and conducive investment decisions are required to lay the foundations of long-term growth and development. Debt relief should be the option for only those countries that meet a minimum measurable criterion of good governance, economic freedom, and consistency of policies.

Keywords: external debt, debt burden, debt overhang, debt laffer curve, debt relief, investment decisions

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Authors: Molla Tadesse Lakew

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This study was intended to identify the factors influencing the use of mobile phones in vegetable marketing in Fogera district. The use of mobile phones in vegetable marketing and factors influencing mobile phone use were specific objectives of the study. Three kebeles from the Fogera district were selected purposively based on their vegetable production potential. A simple random sampling technique (lottery method) was used to select 153 vegetable producer farmers. Interview schedule and key informants interviews were used to collect primary data. For analyzing the data, descriptive statistics like frequency and percentage, two independent t-tests, and chi-square were used. Furthermore, econometric analysis (binary logistic model) was used to assess the factors influencing mobile phone use for vegetable market information. Contingency coefficient and variance inflation factor were used to check multicollinearity problems between the independent variables. Of 153 respondents, 82 (61.72%) were mobile phone users, while 71 (38.28 %) were mobile phone nonusers. Moreover, the main use of mobile phones in vegetable marketing includes communicating at a distance to save time and minimizing transport costs, getting vegetable marketing price information, identifying markets and buyers to sell the vegetable, deciding when to sell the vegetable, negotiating with buyers for better vegetable prices and for searching of the fast market to avoid from losing of product through perishing. The model result indicated that the level of education, size of land, income, access to credit, and age were significant variables affecting the use of mobile phones in vegetable marketing. It could be recommended to encourage adult education or give training for farmers on how to operate mobile phones and create awareness for the elderly rural farmers as they are able to use the mobile phone for their vegetable marketing. Moreover, farmers should be aware that mobile phones are very important for those who own very small land to get maximum returns from their production. Lastly, providing access to credit and improving and diversifying income sources for the farmers to have mobile phones were recommended to improve the livelihood of farmers.

Keywords: mobile phone, farmers, vegetable marketing, Fogera District

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Authors: Signe Svensson, Remy Rey, Anna-Lisa Osvalder, Henrik Artman, Lars Nordström

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The electric power system is undergoing significant changes. Thereby, the operation and control are becoming partly modified, more multifaceted and automated, and thereby supplementary operator skills might be required. This paper discusses developing operational challenges in future power system control rooms, posed by the evolving landscape of sustainable power systems, driven in turn by the shift towards electrification and renewable energy sources. A literature review followed by interviews and a comparison to other related domains with similar characteristics, a descriptive analysis was performed from a human factors perspective. Analysis is meant to identify trends, relationships, and challenges. A power control domain taxonomy includes a temporal domain (planning and real-time operation) and three operational domains within the power system (generation, switching and balancing). Within each operational domain, there are different control actions, either in the planning stage or in the real-time operation, that affect the overall operation of the power system. In addition to the temporal dimension, the control domains are divided in space between a multitude of different actors distributed across many different locations. A control room is a central location where different types of information are monitored and controlled, alarms are responded to, and deviations are handled by the control room operators. The operators’ competencies, teamwork skills, team shift patterns as well as control system designs are all important factors in ensuring efficient and safe electricity grid management. As the power system evolves with sustainable energy technologies, challenges are found. Questions are raised regarding whether the operators’ tacit knowledge, experience and operation skills of today are sufficient to make constructive decisions to solve modified and new control tasks, especially during disturbed operations or abnormalities. Which new skills need to be developed in planning and real-time operation to provide efficient generation and delivery of energy through the system? How should the user interfaces be developed to assist operators in processing the increasing amount of information? Are some skills at risk of being lost when the systems change? How should the physical environment and collaborations between different stakeholders within and outside the control room develop to support operator control? To conclude, the system change will provide many benefits related to electrification and renewable energy sources, but it is important to address the operators’ challenges with increasing complexity. The control tasks will be modified, and additional operator skills are needed to perform efficient and safe operations. Also, the whole human-technology-organization system needs to be considered, including the physical environment, the technical aids and the information systems, the operators’ physical and mental well-being, as well as the social and organizational systems.

Keywords: operator, process control, energy system, sustainability, future control room, skill

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Authors: Anne N. Heirman, Lisette van der Molen, Richard Dirven, Gyorgi B. Halmos, Michiel W.M. van den Brekel

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Background: Due to the rising incidence of oropharyngeal squamous cell cancer (OPSCC), many patients are challenged with choosing between transoral(robotic) surgery and radiotherapy, with equal survival and oncological outcomes. Also, functional outcomes are of little difference over the years. With this study, the wants and needs of patients and caregivers are identified to develop a comprehensible patient decision aid (PDA). Methods: The development of this PDA is based on the International Patient Decision Aid Standards criteria. In phase 1, relevant literature was reviewed and compared to current counseling papers. We interviewed ten post-treatment patients and ten doctors from four head and neck centers in the Netherlands, which were transcribed verbatim and analyzed. With these results, the first draft of the PDA was developed. Phase 2 beholds testing the first draft for comprehensibility and usability. Phase 3 beholds testing for feasibility. After this phase, the final version of the PDA was developed. Results: All doctors and patients agreed a PDA was needed. Phase 1 showed that 50% of patients felt well-informed after standard care and 35% missed information about treatment possibilities. Side effects and functional outcomes were rated as the most important for decision-making. With this information, the first version was developed. Doctors and patients stated (phase 2) that they were satisfied with the comprehensibility and usability, but there was too much text. The PDA underwent text reduction revisions and got more graphics. After revisions, all doctors found the PDA feasible and would contribute to regular counseling. Patients were satisfied with the results and wished they would have seen it before their treatment. Conclusion: Decision-making for OPSCC should focus on differences in side-effects and functional outcomes. Patients and doctors found the PDA to be of great value. Future research will explore the benefits of the PDA in clinical practice.

Keywords: head-and-neck oncology, oropharyngeal cancer, patient decision aid, development, shared decision making

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Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

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There has been a need in recent years to predict student academic achievement prior to graduation. This is to assist them in improving their grades, especially for those who have struggled in the past. The purpose of this research is to use supervised learning techniques to create a model that predicts student academic progress. Many scholars have developed models that predict student academic achievement based on characteristics including smoking, demography, culture, social media, parent educational background, parent finances, and family background, to mention a few. This element, as well as the model used, could have misclassified the kids in terms of their academic achievement. As a prerequisite to predicting if the student will perform well in the future on related courses, this model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester. With a 96.7 percent accuracy, the model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost. This model is offered as a desktop application with user-friendly interfaces for forecasting student academic progress for both teachers and students. As a result, both students and professors are encouraged to use this technique to predict outcomes better.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

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Authors: Jumanah S. Alawfi

Abstract:

Polycystic ovary syndrome (PCOS) is a common endocrinopathy among females in their reproductive years. The incidence cases are nearly 1.55 million among females across the globe, with 0.43 million associated disability-adjusted life-years (DALYs). This syndrome is associated with intricate mechanisms typically characterized by insulin resistance (IR), infertility, overweight and/or obesity. Lifestyle interventions are often prescribed as an adjective treatment. Nonetheless, obesity is a complex disease that encompasses multiple dimensions, such as excessive energy intake and genetics. The melanocortin 4 receptor mutation (MC4R) is an important mediator in appetite. There is emerging evidence that suggests its role in the Body Mass Index (BMI) among PCOS subjects, which poses the question of obesity and/or overweight among the PCOS patients who carry the MC4R variants may be caused by overconsumption. Thereby, using other satiety techniques may be beneficial as a part of personalized nutrition. Therefore, the aim of the current mini-review is to discuss the effect of the vegan low glycemic diet on reducing appetite among PCOS patients. The review shows that there is a gap in the knowledge of the effect of the vegan diet on PCOS patients who carry MC4R variants which need further research.

Keywords: polycystic ovarian syndrome (PCOS), Appetite, Melanocortin 4 Receptor Mutation (MC4R)., Obesity

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Authors: Hakeem Ade Omokayode Idowu

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The extent of the role played by human capabilities developments as well as knowledge management on employees’ performance in the nuclear energy sector of Nigeria remains unclear. This is in view of the important role which human resource capabilities could play in the desire to generate energy using nuclear resources. This study appraised the extent of human resource capabilities available in the nuclear energy sector of Nigeria. It further examined the relationship between knowledge management and employees’ performance in the nuclear energy sector. The study adopted a descriptive research design with a population that comprised all the 1736 members of staff of the selected centres, institutes, and the headquarters of the Nigeria Atomic Energy Commission (NAEC), Nigerian Nuclear Regulatory Authority (NNRA), and Energy Commission of Nigeria (ECN) and a sample size of 332 employees was selected using purposive and convenience sampling techniques. Data collected were subjected to analysis using frequency counts and simple regression. The results showed that majority of the employees perceived that they have to a high extent of availability of knowledge (118, 35.5%), credibility (134, 40.4%), alignment (130, 39.2%), performance (126, 38%) and innovation (138, 41.6%) The result of the hypothesis tested indicated that knowledge management has a positive and significant effect on employees’ performance (Beta weight = 0.336, R2 =0.113, F-value = 41.959, p-value = 0.000< 0.05). The study concluded that human resource capabilities and knowledge management could enhance employee performance within the nuclear energy sector of Nigeria.

Keywords: human resource capabilities, knowledge management, employees productivity, national development

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Authors: H. M. Mohammad, A. Martin, N. Brown, N. Hodson, P. Hill, E. Roberts

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Graphite intercalation compound (GIC) has been demonstrated to be a useful, low capacity and rapid adsorbent for the removal of organic micropollutants from water. The high electrical conductivity and low capacity of the material lends itself to electrochemical regeneration. Following electrochemical regeneration, equilibrium loading under similar conditions is reported to exceed that achieved by the fresh adsorbent. This behavior is reported in terms of the regeneration efficiency being greater than 100%. In this work, surface analysis techniques are employed to investigate the material in three states: ‘Fresh’, ‘Loaded’ and ‘Regenerated’. ‘Fresh’ GIC is shown to exhibit a hydrogen and oxygen rich surface layer approximately 150 nm thick. ‘Loaded’ GIC shows a similar but slightly thicker surface layer (approximately 370 nm thick) and significant enhancement in the hydrogen and oxygen abundance extending beyond 600 nm from the surface. 'Regenerated’ GIC shows an oxygen rich layer, slightly thicker than the fresh case at approximately 220 nm while showing a very much lower hydrogen enrichment at the surface. Results demonstrate that while the electrochemical regeneration effectively removes the phenol model pollutant, it also oxidizes the exposed carbon surface. These results may have a significant impact on the estimation of adsorbent life.

Keywords: graphite, adsorbent, electrochemical, regeneration, phenol

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Authors: A. Latif Karimi

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Since 2001, construction works, especially the construction of new homes and residential buildings, witnessed a dramatic boom across Afghanistan. More so, the construction industry and house builders are relied upon as important players in the country’s job market, economy and infrastructural development schemes. However, a lack of innovation, quality assurance mechanism, substandard construction and market dominance by traditional methods push all the parties in house building sector to shift for more advanced construction techniques and mass production technologies to meet the rising demands for proper accommodation. Meanwhile, rapid population growth and urbanization are widening the gap between the demand and supply of new and modern houses in urban areas like Kabul, Herat, etc. This paper investigates about current condition of construction practices in house building projects, the associated challenges, and the outcomes of transition to more reasonable and sustainable building methods. It is obvious, the introduction and use of Modern Methods of Construction (MMC) can help construction industry and house builders in Afghanistan to tackle the challenges and meet the desired standards for modern houses. This paper focuses on prefabrication, a popular MMC that is becoming more common, improving in quality and available in a variety of budgets. It is revealed that this method is the way forward to improving house building practices as it has been proven to reduce construction time, minimize waste and improve environmental performance of construction developments.

Keywords: modern houses, traditional construction, modern methods of construction, prefabrication, sustainable building

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Authors: S. Chabbak

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In a widely globalized world, the influence of audiovisual translation on the culture and identity of audiences is unmistakable. However, in the Arab World, there is a noticeable disproportion between this growing influence and the research carried out in the field. As a matter of fact, the voiced-over documentary is one of the most abundantly translated genres in the Arab World that carries lots of ideological elements which are in many cases rendered by manipulation. However, voiced-over documentaries have hardly received any focused attention from researchers in the Arab World. This paper attempts to scrutinize the process of translation of voiced-over documentaries in the Arab World, from French into Arabic in the present case study, by sub-categorizing the ideological items subject to manipulation, identifying the techniques utilized in their translation and exploring the potential extra-linguistic factors that prompt translation agents to opt for manipulative translation. The investigation is based on a corpus of 94 episodes taken from a series entitled 360° GEO Reports, produced by the French German network ARTE in French, and acquired, translated and aired by Al Jazeera Documentary Channel for Arab audiences. The results yielded 124 cases of manipulation in four sub-categories of ideological items, and the use of 10 different oblique procedures in the process of manipulative translation. The study also revealed that manipulation is in most of the instances dictated by the editorial line of the broadcasting channel, in addition to the religious, geopolitical and socio-cultural peculiarities of the target culture.

Keywords: audiovisual translation, ideological items, manipulation, voiced-over documentaries

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Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi

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Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.

Keywords: breast cancer, diagnosis, machine learning, biomarker classification, neural network

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Authors: Mohammad Yousefikia, Sara Moridpour, Ehsan Mazloumi

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Perceiving track geometry deterioration decisively influences the optimization of track maintenance operations. The effective management of this deterioration and increasingly utilized system with limited financial resources is a significant challenge. This paper provides a review of degradation models relevant for railroad tracks. Furthermore, due to the lack of long term information on the condition development of tram infrastructures, presents the methodology which will be used to derive degradation models from the data of Melbourne tram network.

Keywords: deterioration modeling, asset management, railway, tram

Procedia PDF Downloads 374

Authors: Marie Kristel A. Gabawa

Abstract:

The accessibility of health programs, specifically family planning programs and maternal and child health care (FP/MCH), are generally low in urban poor communities. Moreover, most of FP/MCH programs are directed toward medical terms that are usually not included in ideation of the body of urban poor dwellers. This study aims to explore the beliefs on reproduction that will encompass, but not limited to, beliefs on conception, pregnancy, and maternal and child health care. The site of study will be the 2 barangays of North Bay Boulevard South 1 (NBBS1) and North Bay Boulevard South 2 (NBBS2). These 2 barangays are the nearest residential community within the Navotas Fish Port Complex (NFPC). Data gathered will be analyzed using grounded-theory method of analysis, with the theories of cultural materialism and equity feminism as foundation. Survey questionnaires, key informant interviews, and focus group discussions will be utilized in gathering data. Further, the presentation of data will be recommended to health program initiators and use the data gathered as a tool to customize FP/MCH programs to the perception and beliefs of women residing in NBBS1and NBBS2, and to aid any misinformation for FP/MCH techniques.

Keywords: beliefs on reproduction, fish port community, family planning, maternal and child health care, Navotas

Procedia PDF Downloads 256