Search results for: call drop probability

Authors: Kelebaone Tsamaase, Rapelang Kemoabe, Japhet Sakala, Edward Rakgati, Ishmael Zibani

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Increasing demand for energy, depletion of non-renewable energy, effects of climate change, the abundance of renewable energy such as solar energy have increased the interest in investing in renewable energies, in particular solar photovoltaic (PV) energy. Solar photovoltaic energy systems as part of clean technology are considered to be environmentally friendly, freely available, offer clean production systems, long term costs benefits as opposed to conventional sources, and are the attractive power source for a wide range of applications in remote areas where there is no easy access to the national grid. To get maximum electrical power, maximum solar power should penetrate the module and be converted accordingly. However, some environmental and other geographical related factors reduce the electrical power. One of them is dust which accumulates on the surface of the module and forming a dust layer and in the process obstructing the solar power from penetrating PV module. This study intends to improve the performance of solar photovoltaic (PV) energy modules by establishing soil accumulation effects correction factor from dust characteristics and properties, and also from dust accumulation and retention pattern on PV module surface. The non-urban dry deposition flux model was adapted to determine monthly and yearly dust accumulation pattern. Consideration was done on prevailing environmental and other geographical conditions. Preliminary results showed that cumulative dust settlement increased during the months of July to October leading to a higher drop in module electrical output power.

Keywords: dust, electrical power output, PV module, soil correction factor

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Authors: Kernou Nassim

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The current study presents a vulnerability and a reliability-mechanical approach that focuses on evaluating the seismic performance of reinforced concrete structures to determine the probability of failure. In this case, the performance function reflecting the non-linear behavior of the structure is modeled by a response surface to establish an analytical relationship between the random variables (strength of concrete and yield strength of steel) and mechanical responses of the structure (inter-floor displacement) obtained by the pushover results of finite element simulations. The push over-analysis is executed by software SAP2000. The results acquired prove that properly designed frames will perform well under seismic loads. It is a comparative study of the behavior of the existing structure before and after reinforcement using the pushover method. The coupling indirect mechanical reliability by response surface avoids prohibitive calculation times. Finally, the results of the proposed approach are compared with Monte Carlo Simulation. The comparative study shows that the structure is more reliable after the introduction of new shear walls.

Keywords: finite element method, surface response, reliability, reliability mechanical coupling, vulnerability

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Authors: Benson Ade Eniola Afere

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Over the years, kernel density estimation has been extensively studied within the context of nonparametric density estimation. The fundamental components of kernel density estimation are the kernel function and the bandwidth. While the mathematical exploration of the kernel component has been relatively limited, its selection and development remain crucial. The Mean Integrated Squared Error (MISE), serving as a measure of discrepancy, provides a robust framework for assessing the effectiveness of any kernel function. A kernel function with a lower MISE is generally considered to perform better than one with a higher MISE. Hence, the primary aim of this article is to create kernels that exhibit significantly reduced MISE when compared to existing classical kernels. Consequently, this article introduces a cluster of hybrid polynomial kernel families. The construction of these proposed kernel functions is carried out heuristically by combining two kernels from the classical polynomial kernel family using probability axioms. We delve into the analysis of error propagation within these kernels. To assess their performance, simulation experiments, and real-life datasets are employed. The obtained results demonstrate that the proposed hybrid kernels surpass their classical kernel counterparts in terms of performance.

Keywords: classical polynomial kernels, cluster of families, global error, hybrid Kernels, Kernel density estimation, Monte Carlo simulation

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Authors: Can Liu, Graham Markowitz, John Balay, Ben Pratt

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Baseline or natural hydrology is commonly employed for hydrologic modeling and quantification of hydrologic alteration due to manmade activities. It can inform planning and policy related efforts for various state and federal water resource agencies to restore natural streamflow flow regimes. A common challenge faced by hydrologists is how to replicate unaltered streamflow conditions, particularly in large watershed settings prone to development and regulation. Three different methods were employed to estimate baseline streamflow conditions for 6 major subbasins the Susquehanna River Basin; those being: 1) incorporation of consumptive water use and reservoir operations back into regulated gaged records; 2) using a map correlation method and flow duration (exceedance probability) regression equations; 3) extending the pre-regulation streamflow records based on the relationship between concurrent streamflows at unregulated and regulated gage locations. Parallel analyses were perform among the three methods and limitations associated with each are presented. Results from these analyses indicate that generating baseline streamflow records at large-scale watersheds remain challenging, even with long-term continuous stream gage records available.

Keywords: baseline hydrology, streamflow gage, subbasin, regression

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Authors: Muhammad Noor Hossain

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The biography of the father of the nation is the path of national life. It is natural that the ideals of the father will be reflected in his nation. In the interest of themselves, it is necessary to keep the father of the nation above controversy as well as necessary to research various aspects of his life. In that light, various aspects of Sheikh Mujibur Rahman's (1920-1975 AD) life are being researched at home and abroad. He is the father of Bengali nation, the architect of Bangladesh's independence, the best Bengali of a thousand years, and a beacon of thought and consciousness of the nation. It is unfortunate but true that there are still doubts among the nation about his religious thought. There are many political and historical reasons behind this. Many consider him to be anti-Islamic. Before independence of Bangladesh, Pakistanis called him Islamophobic, accused India's broker and hero of partitioning Islamic Republic of Pakistan. He was also accused of secularism as the post-independence constitution of Bangladesh adopted secularism as one of its fundamental principles. Many called him a communist due to the inclusion of socialism in the constitution. On the other hand, some intellectuals did not hesitate to call him sectarian after seeing his devotion to religion. As the architect of freedom and the father of the nation, his religious thought should be clear. In the interest of national unity and solidarity, it is necessary to verify the truth of the charges against him and come to a decision. The article was written with the aim of clarifying his religious thought and removing doubts about them. This is an endeavor to review the charges of communalism, secularism, and socialism practiced by him. It is written in the historical and analytical method. The major findings are that he is not communist in the meaning of atheist, nor communalist in the meaning of fundamentalist. He is not socialist or secularist in the meaning of anti-religion. He is a moderate Muslim and devoted to righteousness.

Keywords: Sheikh Mujubur Rahman, religious thought, secularism, socialism, communalism, Constitution of Bangladesh of 1972

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Authors: Genesis F. Dela Cruz, Liza C. Costa

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The study is concerned with the Risk factors of dropping out among Grade VII students for SY 2012-2013. A total of 87 Grade VII Students-At-Risk-of-Dropping Out (SARDOs) were involved in this study. The descriptive survey method was used in this study. A 50-item questionnaire was used in data gathering. Expert validation was done to determine the validity and reliability of the instrument. The study used Chi Square, Kruskal Wallis Test and Mann Whitney Test in the statistical treatment of data. The study revealed that the respondents are within the standard age limit for Grade VII students in the Philippines which is 13 years old. Males more than females usually becomes SARDOs. SARDOs come from low economic status and complete families contrary to the common belief that they came from single-parent families. The study also showed that parent’s involvement in educating their children on family-related factors contributed to the very good perception on the family related factors. Based on age, there are no significant differences in their perception of the four major recognized risk factors for dropping out among all ages. There are no significant differences in their perception of the family, individual and community related factors for dropping out based on sex. However, females have a more favorable perception when it comes to school related factors. No significant differences in their perception of dropping out were also noted when they are classified according to distance of school from home. The respondents do not differ in their perception on family, individual and community related factors when they are classified according to type of family. When surveyed regarding the respondents’ reason for being absent, it was found out that laziness and being late are the two major reasons. Respondents also perceived remedial and tutorial classes as school-initiated intervention measure to prevent school disengagement or dropping out.

Keywords: drop-out, guidance and counseling, school initiated intervention, students at risk of dropping out

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Authors: E. Akpinar, A. Erol, M.F. Cakir

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Precast reinforced concrete (RC) structures are excellent alternatives for construction world all over the globe, thanks to their rapid erection phase, ease mounting process, better quality and reasonable prices. Such structures are rather popular for industrial buildings. For the sake of economic importance of such industrial buildings as well as significance of safety, like every other type of structures, performance assessment and structural risk analysis are important. Fragility curves are powerful tools for damage projection and assessment for any sort of building as well as precast structures. In this study, a comparative review of current knowledge on fragility analysis of industrial precast RC structures were presented and findings in previous studies were compiled. Effects of different structural variables, parameters and building geometries as well as soil conditions on fragility analysis of precast structures are reviewed. It was aimed to briefly present the information in the literature about the procedure of damage probability prediction including fragility curves for such industrial facilities. It is found that determination of the aforementioned structural parameters as well as selecting analysis procedure are critically important for damage prediction of industrial precast RC structures using fragility curves.

Keywords: damage prediction, fragility curve, industrial buildings, precast reinforced concrete structures

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Authors: Hatem Mrad, Mohamed Bouazara, Fouad Erchiqui

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Fatigue, is considered as one of the main cause of mechanical properties degradation of mechanical parts. Probability and reliability methods are appropriate for fatigue analysis using uncertainties that exist in fatigue material or process parameters. Current work deals with the study of the effect of the number and counting Rainflow cycle on fatigue lifetime (cumulative damage) of an upper arm of the vehicle suspension system. The major part of the fatigue damage induced in suspension arm is caused by two main classes of parameters. The first is related to the materials properties and the second is the road excitation or the applied force of the passenger’s number. Therefore, Young's modulus and road excitation are selected as input parameters to conduct repetitive simulations by Monte Carlo (MC) algorithm. Latin hypercube sampling method is used to generate these parameters. Response surface method is established according to fatigue lifetime of each combination of input parameters according to strain-life method. A PYTHON script was developed to automatize finite element simulations of the upper arm according to a design of experiments.

Keywords: fatigue, monte carlo, rainflow cycle, response surface, suspension system

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Authors: M. Mojaddam, M. Araei, T. Saki Nejad, M. Soltani Howyzeh

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In order to study the effect of different levels of triple super phosphate chemical fertilizer and biological phosphate fertilizer (fertile 2) on some morphological traits of corn this research was carried out in Ahvaz in 2002 as a factorial experiment in randomized complete block design with 4 replications.) The experiment included two factors: first, biological phosphate fertilizer (fertile 2) at three levels of 0, 100, 200 g/ha; second, triple super phosphate chemical fertilizer at three levels of 0, 60, 90 kg/ha of pure phosphorus (P2O5). The obtained results indicated that fertilizer treatments had a significant effect on some morphological traits at 1% probability level. In this regard, P2B2 treatment (100 g/ha biological phosphate fertilizer (fertile 2) and 60 kg/ha triple super phosphate fertilizer) had the greatest plan height, stem diameter, number of leaves and ear length. It seems that in Ahvaz weather conditions, decrease of consumption of triple superphosphate chemical fertilizer to less than a half along with the consumption of biological phosphate fertilizer (fertile 2) is highly important in order to achieve optimal results. Therefore, it can be concluded that biological fertilizers can be used as a suitable substitute for some of the chemical fertilizers in sustainable agricultural systems.

Keywords: biological phosphate fertilizer (fertile 2), triple super phosphate, corn, morphological traits

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Authors: Sandhya Baskaran, Hari Kumar Nagabushanam

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Sarcasm sentiment recognition is an area of natural language processing that is being probed into in the recent times. Even with the advancements in NLP, typical translations of words, sentences in its context fail to provide the exact information on a sentiment or emotion of a user. For example, if something bad happens, the statement ‘That's just what I need, great! Terrific!’ is expressed in a sarcastic tone which could be misread as a positive sign by any text-based analyzer. In this paper, we are presenting a unique real time ‘word with its tone’ spotting technique which would provide the sentiment analysis for a tone or pitch of a voice in combination with the words being expressed. This hybrid approach increases the probability for identification of special sentiment like sarcasm much closer to the real world than by mining text or speech individually. The system uses a tone analyzer such as YIN-FFT which extracts pitch segment-wise that would be used in parallel with a speech recognition system. The clustered data is classified for sentiments and sarcasm score for each of it determined. Our Simulations demonstrates the improvement in f-measure of around 12% compared to existing detection techniques with increased precision and recall.

Keywords: sarcasm recognition, tone-word spotting, natural language processing, pitch analyzer

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Authors: Pegah Ebrahimi, Farshad Oveissi, Iman Manavi-Tehrani, Sina Naficy, David F. Fletcher, Fariba Dehghani, David S. Winlaw

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Despite advances in modern surgery, congenital heart disease remains a medical challenge and a major cause of infant mortality. Cardiovascular prostheses are routinely used in surgical procedures to address congenital malformations, for example establishing a pathway from the right ventricle to the pulmonary arteries in pulmonary valvar atresia. Current off-the-shelf options including human and adult products have limited biocompatibility and durability, and their fixed size necessitates multiple subsequent operations to upsize the conduit to match with patients’ growth over their lifetime. Non-physiological blood flow is another major problem, reducing the longevity of these prostheses. These limitations call for better designs that take into account the hemodynamical and anatomical characteristics of different patients. We have integrated tissue engineering techniques with modern medical imaging and image processing tools along with mathematical modeling to optimize the design of cardiovascular grafts in a patient-specific manner. Computational Fluid Dynamics (CFD) analysis is done according to models constructed from each individual patient’s data. This allows for improved geometrical design and achieving better hemodynamic performance. Tissue engineering strives to provide a material that grows with the patient and mimic the durability and elasticity of the native tissue. Simulations also give insight on the performance of the tissues produced in our lab and reduce the need for costly and time-consuming methods of evaluation of the grafts. We are also developing a methodology for the fabrication of the optimized designs.

Keywords: computational fluid dynamics, cardiovascular grafts, design optimization, tissue engineering

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Authors: Alvaro Ramírez, Martín Muñoz-Morales, Ester López- Fernández, Javier Llanos, C. Ania

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Carbon blacks are value-added materials typically produced through the incomplete combustion or thermal decomposition of hydrocarbons. Traditionally, they have been used as catalysts in many different applications, but in the last decade, their potential in green chemistry has gained significant attention. Among them, the electrochemical production of H₂O₂ has attracted interest because of their properties as high oxidant capacity or their industrial interest as a bleaching agent. Carbon blacks are commonly used in this application in a catalytic ink that is drop-casted on supporting electrodes and acts as catalysts for the electrochemical production of H₂O₂ through oxygen reduction reaction (ORR). However, the different structural and electrochemical behaviors of each type of carbon black influence their applications. In this line, the term ‘carbon black’, has to be considered as a generic name that does not guarantee any physicochemical properties if any further description is mentioned. In fact, different specific surface area (SSA), surface functional groups, porous structure, and electro catalysts effect seem very important for electrochemical applications, and considerable differences were found during the analysis of four types of carbon blacks. Thus, the aim of this work is to evaluate the influence of SSA, porous structure, oxygen functional groups, and structural defects to differentiate among these carbon blacks (e.g. Vulcan XC72, Superior Graphite Co, Printex XE2, and Prolabo) for H₂O₂ production via ORR, using carbon paper as electrode support with improved selectivity and efficiency. Results indicate that the number and size of pores, along with surface functional groups, are key parameters that significantly affect the overall process efficiency.

Keywords: carbon blacks, oxygen reduction reaction, hydrogen peroxide, porosity, surface functional groups

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Authors: Festus M. Epetimehin

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This study was conducted to identify the effect of National Directorate of Employment (NDE) training on the profit of Agricultural-Small and Medium Enterprises (SMEs) and to evaluate the factors that influenced farmers' participation in NDE training, as well as the type and frequency of training farmers and other agro-allied entrepreneurs in Nigeria. Using a multi-stage sampling procedure, a total of 384 respondents were sampled, including 192 beneficiaries and 192 non-beneficiaries in Oyo and Lagos States, respectively. Data were analysed using Binary Logit regression and Propensity Score Matching techniques. According to the binary logit analysis, respondents’ gender, availability to extension services, and the location of respondent’s operation were determinant factors influencing NDE training enrolment. All identified factors are related to the probability of respondents’ involvement in a positive way. Propensity score matching revealed that Agricultural-SMEs who participated in the NDE program boosted their profit by N341,072.18. The positive outcome of the effect implies that NDE training enhances Agri-SME performance in Nigeria. The study concluded that greater funding should be provided for the NDE for performance-enhancing training of the Agri-SMEs.

Keywords: PSM, binary logit model, Agri-SME

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Authors: Fahad Y. Al-dawish

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The current trend by a large number of organizations and individuals to use cloud computing. Many consider it a significant shift in the field of computing. Cloud computing are distributed and parallel systems consisting of a collection of interconnected physical and virtual machines. With increasing request and profit of cloud computing infrastructure, diverse computing processes can be executed on cloud environment. Many organizations and individuals around the world depend on the cloud computing environments infrastructure to carry their applications, platform, and infrastructure. One of the major and essential issues in this environment related to allocating incoming tasks to suitable virtual machine (cloud task scheduling). Cloud task scheduling is classified as optimization problem, and there are several meta-heuristic algorithms have been anticipated to solve and optimize this problem. Good task scheduler should execute its scheduling technique on altering environment and the types of incoming task set. In this research project a cloud task scheduling methodology based on ant colony optimization ACO algorithm, we call it ACO-TS Ant Colony Optimization for Task Scheduling has been proposed and compared with different scheduling algorithms (Random, First Come First Serve FCFS, and Fastest Processor to the Largest Task First FPLTF). Ant Colony Optimization (ACO) is random optimization search method that will be used for assigning incoming tasks to available virtual machines VMs. The main role of proposed algorithm is to minimizing the makespan of certain tasks set and maximizing resource utilization by balance the load among virtual machines. The proposed scheduling algorithm was evaluated by using Cloudsim toolkit framework. Finally after analyzing and evaluating the performance of experimental results we find that the proposed algorithm ACO-TS perform better than Random, FCFS, and FPLTF algorithms in each of the makespaan and resource utilization.

Keywords: cloud Task scheduling, ant colony optimization (ACO), cloudsim, cloud computing

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Authors: Guangyuan Zhao, Nan Huang, Xuesong Han, Xu Huang

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In order to solve the problem of sample dilution in the traditional particle filter algorithm and achieve accurate state estimation in a nonlinear system, a particle filter method based on an improved artificial bee colony (ABC) algorithm was proposed. The algorithm simulated the process of bee foraging and optimization and made the high likelihood region of the backward probability of particles moving to improve the rationality of particle distribution. The opposition-based learning (OBL) strategy is introduced to optimize the initial population of the artificial bee colony algorithm. The convergence factor is introduced into the neighborhood search strategy to limit the search range and improve the convergence speed. Finally, the crossover and mutation operations of the genetic algorithm are introduced into the search mechanism of the following bee, which makes the algorithm jump out of the local extreme value quickly and continue to search the global extreme value to improve its optimization ability. The simulation results show that the improved method can improve the estimation accuracy of particle filters, ensure the diversity of particles, and improve the rationality of particle distribution.

Keywords: particle filter, impoverishment, state estimation, artificial bee colony algorithm

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Authors: Prakash Thapa, Gye Choon Park, Sung Gi Kwon, Jin Lee

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The generation of electric power from a proton exchange membrane (PEM) fuel cell is influenced by temperature, pressure, humidity, flow rate of reactant gaseous and partial flooding of membrane electrode assembly (MEA). Among these factors, temperature and cathode flooding are the most affecting parameters on the performance of fuel cell. This paper describes the detail design and effect of these parameters on PEM fuel cell. Performance of all parameters was monitored, analyzed and controlled by using 5KWatt PEM fuel cell. In the real-time data communication for remote monitoring and control of PEM fuel cell, a normalized least mean square algorithm in cognitive radio environment is used. By the use of this method, probability of energy signal detection will be maximum which solved the frequency shortage problem. So the monitoring system hanging out and slow speed problem will be solved. Also from the control unit, all parameters are controlled as per the system requirement. As a result, PEM fuel cell generates maximum electricity with better performance.

Keywords: proton exchange membrane (PEM) fuel cell, pressure, temperature and humidity sensor (PTH), efficiency curve, cognitive radio network (CRN)

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Authors: Hadia Abdel Aziz, Raghda El Ebrashi

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Business models are shaped by their design space or the environment they are designed to be implemented in. The rapidly changing economic, technological, political, regulatory and market external environment severely affects business logic. This is particularly true for social enterprises whose core mission is to transform their environments, and thus, their whole business logic revolves around the interchange between the enterprise and the environment. The context in which social business operates imposes different business design constraints while at the same time, open up new design opportunities. It is also affected to a great extent by the impact that successful enterprises generate; a continuous loop of interaction that needs to be managed through a dynamic capability in order to generate a lasting powerful impact. This conceptual research synthesizes and analyzes literature on social enterprise, social enterprise business models, business model innovation, business model design, and the open system view theory to propose a new business model design process for social enterprises that takes into account the critical role of environmental factors. This process would help the social enterprise develop a dynamic capability that ensures the alignment of its business model to its environmental context, thus, maximizing its probability of success.

Keywords: social enterprise, business model, business model design, business model environment

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Authors: Meron Zenaselase Rata, Euridice Leyequien Abarca

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The production of major crops in Northern Ethiopia, especially the Tigray Region, is at subsistence level due to drought, erratic rainfall, and poor soil fertility. Since cactus pear is a drought-resistant plant, it is considered as a lifesaver fruit and a strategy for poverty reduction in a drought-affected area of the region. Despite its contribution to household income and food security in the area, the cactus pear sub-sector is experiencing many constraints with limited attention given to its post-harvest loss management. Therefore, this research was carried out to identify opportunities for reducing post-harvest losses and recommend possible strategies to reduce post-harvest losses, thereby improving production and smallholder’s income. Both probability and non-probability sampling techniques were employed to collect the data. Ganta Afeshum district was selected from Eastern Tigray, and two peasant associations (Buket and Golea) were also selected from the district purposively for being potential in cactus pear production. Simple random sampling techniques were employed to survey 30 households from each of the two peasant associations, and a semi-structured questionnaire was used as a tool for data collection. Moreover, in this research 2 collectors, 2 wholesalers, 1 processor, 3 retailers, 2 consumers were interviewed; and two focus group discussion was also done with 14 key farmers using semi-structured checklist; and key informant interview with governmental and non-governmental organizations were interviewed to gather more information about the cactus pear production, post-harvest losses, the strategies used to reduce the post-harvest losses and suggestions to improve the post-harvest management. To enter and analyze the quantitative data, SPSS version 20 was used, whereas MS-word were used to transcribe the qualitative data. The data were presented using frequency and descriptive tables and graphs. The data analysis was also done using a chain map, correlations, stakeholder matrix, and gross margin. Mean comparisons like ANOVA and t-test between variables were used. The analysis result shows that the present cactus pear value chain involves main actors and supporters. However, there is inadequate information flow and informal market linkages among actors in the cactus pear value chain. The farmer's gross margin is higher when they sell to the processor than sell to collectors. The significant postharvest loss in the cactus pear value chain is at the producer level, followed by wholesalers and retailers. The maximum and minimum volume of post-harvest losses at the producer level is 4212 and 240 kgs per season. The post-harvest loss was caused by limited farmers skill on-farm management and harvesting, low market price, limited market information, absence of producer organization, poor post-harvest handling, absence of cold storage, absence of collection centers, poor infrastructure, inadequate credit access, using traditional transportation system, absence of quality control, illegal traders, inadequate research and extension services and using inappropriate packaging material. Therefore, some of the recommendations were providing adequate practical training, forming producer organizations, and constructing collection centers.

Keywords: cactus pear, post-harvest losses, profit margin, value-chain

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Authors: Hamidou Diallo, Marianne Guille

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This paper identifies leading triggers of deficient episodes in terms of GDP growth based on a sample of countries at different stages of development over 1994-2017. Using logit models, we build early warning systems (EWS), and our results show important differences between developing countries (DCs) and advanced economies (AEs). For AEs, the main predictors of the probability of entering in a GDP growth deficient episode are the deterioration of external imbalances and the vulnerability of fiscal position while DCs face different challenges that need to be considered. The key indicators for them are first, the low ability to pay their debts, and second, their belonging or not to a common currency area. We also build homogeneous pools of countries inside AEs and DCs. The evolution of the proportion of AE countries in the riskiest pool is marked first, by three distinct peaks just after the high-tech bubble burst, the global financial crisis, and the European sovereign debt crisis, and second by a very low minimum level in 2006 and 2007. In contrast, the situation of DCs is characterized first by the relative stability of this proportion and then by an upward trend from 2006, that can be explained by a more unfavorable socio-political environment leading to shortcomings in the fiscal consolidation.

Keywords: currency area, early warning system, external imbalances, fiscal vulnerability, GDP growth, public debt

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Authors: Merve Aydin, Mağfiret Kara Kaşikçi

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Aim: To determine the perceptions of inpatients about care at Farabi Hospital in KTU. Material and Method: This research was conducted by using the universe known examples of formulas and probability selected by sampling method with 277 chosen patients in the hospital at least 14 days in other internal and surgical clinics except for pediatric, psychiatry, and intensive care unit services between January-March 2014 in KTU Farabi Hospital. The data was collected through the forms of nursing care perception scale of patients and defining characteristics of patients. In the evaluation of data, percentage, mean, Mann Whitney U, Student t and Kurskall Wallis tests were applied. Results: The average point the patients got in nursing care perception scale is 62.64±10.08’dir. 48.7 % of patients regard nursing care well and 36.8 % of them regard it very well. 19 % of the patients regard nursing care badly. When the age, sex, occupation, marital status, educational background, residential place, income level, hospitalization period, hospitalization clinic and having a hospital attendant were compared with nursing care perception average point, the difference among point averages was not found meaningful statistically (p > 0.05). The average point of nursing care perception was found greater in those having chronic disease (p < 0.05). Conclusion: The perception point of patients about nursing care is above the average according to the average of the lowest and highest points. The great majority of patients regard nursing care well or very well.

Keywords: hospital, patient, perception of nursing care, nursing care

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Authors: J. J. Vargas, N. Prieto, L. A. Toro

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Control charts are commonly used to monitor processes involving either variable or attribute of quality characteristics and determining the control limits as a critical task for quality engineers to improve the processes. Nonetheless, in some applications it is necessary to include an estimation of efficiency. In this paper, the ability to define the efficiency of an industrial process was added to a control chart by means of incorporating a data envelopment analysis (DEA) approach. In depth, a Bayesian estimation was performed to calculate the posterior probability distribution of parameters as means and variance and covariance matrix. This technique allows to analyse the data set without the need of using the hypothetical large sample implied in the problem and to be treated as an approximation to the finite sample distribution. A rejection simulation method was carried out to generate random variables from the parameter functions. Each resulting vector was used by stochastic DEA model during several cycles for establishing the distribution of each efficiency measures for each DMU (decision making units). A control limit was calculated with model obtained and if a condition of a low level efficiency of DMU is presented, system efficiency is out of control. In the efficiency calculated a global optimum was reached, which ensures model reliability.

Keywords: data envelopment analysis, DEA, Multivariate control chart, rejection simulation method

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Authors: Seongwon Im, Jimin Kim, Kyeongcheol Kim, Dong-Hoon Kim

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Cattle manure (CM) produced from farmhas been utilized to soils for increasing crop production owing to high nutrients content and effective microorganisms. Some cities with the concentrated activity of livestock industry have suffered from environmental problems, such as odorous gas emissions and soil and water pollution, caused by excessive use of compost. As an alternative option, the anaerobic digestion (AD) process can be utilized, which can reduce the volume of organic waste but also produce energy. According to Korea-Ministry of Trade, Industry, and Energy (KMTIE), the energy potential of CM via biogas production was estimated to be 0.8 million TOE per year, which is higher than that of other organic wastes. However, limited energy is recovered since useful organic matter, capable of converting to biogas, may be degraded during the long storage period (1-6 months).In this study, the effect of storage period on biogas potential of CM was investigated. Compared to fresh CM (VS 14±1 g/L, COD 205±5 g/L, TKN 7.4±0.8 g/L, NH4+-N 1.5±0.1), old CM has higher organic (35-37%) and nitrogen content (50-100%) due to the drying process during storage. After stabilization period, biogas potential of 0.09 L CH4/g VS was obtained in R1 (old CM supplement) at HRT of 150-100 d, and it was decreased further to 0.06 L CH4/g VS at HRT of 80 d. The drop of pH and organic acids accumulation were not observed during the whole operation of R1. Ammonia stripping and pretreatment of CM were found to be not effective to increase CH4 yield. On the other hand, a sudden increase of biogas potential to 0.19-0.22 L CH4/g VS was achieved in R2 after changing feedstock to fresh CM. The expected reason for the low biogas potential of old CM might be related with the composition of organic matters in CM. Easily biodegradable organic matters in the fresh CM were contained in high concentration, butthey were removed by microorganisms during storing CM in a farm, resulting low biogas yield. This study implies that fresh storage is important to make AD process applicable for CM.

Keywords: storage period, cattle manure, biogas potential, microbial analysis

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Authors: Judith Stein, Elfriede Friedmann

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The injection of a drug into the vitreous body for the treatment of retinal diseases like wet aged-related macular degeneration (AMD) is the most common medical intervention worldwide. We develop mathematical models for drug transport in the vitreous body of a human eye to analyse the impact of different rheological models of the vitreous on drug distribution. In addition to the convection diffusion equation characterizing the drug spreading, we use porous media modeling for the healthy vitreous with a dense collagen network and include the steady permeating flow of the aqueous humor described by Darcy's law driven by a pressure drop. Additionally, the vitreous body in a healthy human eye behaves like a viscoelastic gel through the collagen fibers suspended in the network of hyaluronic acid and acts as a drug depot for the treatment of retinal diseases. In a completely liquefied vitreous, we couple the drug diffusion with the classical Navier-Stokes flow equations. We prove the global existence and uniqueness of the weak solution of the developed initial-boundary value problem describing the drug distribution in the healthy vitreous considering the permeating aqueous humor flow in the realistic three-dimensional setting. In particular, for the drug diffusion equation, results from the literature are extended from homogeneous Dirichlet boundary conditions to our mixed boundary conditions that describe the eye with the Galerkin's method using Cauchy-Schwarz inequality and trace theorem. Because there is only a small effective drug concentration range and higher concentrations may be toxic, the ability to model the drug transport could improve the therapy by considering patient individual differences and give a better understanding of the physiological and pathological processes in the vitreous.

Keywords: coupled PDE systems, drug diffusion, mixed boundary conditions, vitreous body

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Authors: Apoorva Vinod, Archana Mathur, Snehanshu Saha

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Though there exists a plethora of Activation Functions (AFs) used in single and multiple hidden layer Neural Networks (NN), their behavior always raised curiosity, whether used in combination or singly. The popular AFs –Sigmoid, ReLU, and Tanh–have performed prominently well for shallow and deep architectures. Most of the time, AFs are used singly in multi-layered NN, and, to the best of our knowledge, their performance is never studied and analyzed deeply when used in combination. In this manuscript, we experiment with multi-layered NN architecture (both on shallow and deep architectures; Convolutional NN and VGG16) and investigate how well the network responds to using two different AFs (Sigmoid-Tanh, Tanh-ReLU, ReLU-Sigmoid) used alternately against a traditional, single (Sigmoid-Sigmoid, Tanh-Tanh, ReLUReLU) combination. Our results show that using two different AFs, the network achieves better accuracy, substantially lower loss, and faster convergence on 4 computer vision (CV) and 15 Non-CV (NCV) datasets. When using different AFs, not only was the accuracy greater by 6-7%, but we also accomplished convergence twice as fast. We present a case study to investigate the probability of networks suffering vanishing and exploding gradients when using two different AFs. Additionally, we theoretically showed that a composition of two or more AFs satisfies Universal Approximation Theorem (UAT).

Keywords: activation function, universal approximation function, neural networks, convergence

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Authors: Shima Soleimani, Steven Eckels

Abstract:

One area of special importance for surface-level study of heat exchangers is tubes with internal micro-fins (< 0.5 mm tall). Micro-finned surfaces are a kind of extended solid surface in which energy is exchanged with water that acts as the source or sink of energy. Significant performance gains are possible for either shell, tube, or double pipe heat exchangers if the best surfaces are identified. The parametric studies of micro-finned tubes that have appeared in the literature left some key parameters unexplored. Specifically, they ignored three-dimensional (3D) micro-fin configurations, conduction heat transfer in the fins, and conduction in the solid surface below the micro-fins. Thus, this study aimed at implementing a parametric study of 3D micro-finned tubes that considered micro-fin height and discontinuity features. A 3D conductive and convective heat-transfer simulation through coupled solid and periodic fluid domains is applied in a commercial package, ANSYS Fluent 19.1. The simulation is steady-state with turbulent water flow cooling inner wall of a tube with micro-fins. The simulation utilizes a constant and uniform temperature on the tube outer wall. Performance is mapped for 18 different simulation cases, including a smooth tube using a realizable k-ε turbulence model at a Reynolds number of 48,928. Results compared the performance of 3D tubes with results for the similar two-dimensional (2D) one. Results showed that the micro-fin height has greater impact on performance factor than discontinuity features in 3D micro-fin tubes. A transformed 3D micro-fin tube can enhance heat transfer and pressure drop up to 21% and 56% compared to a 2D one, respectfully.

Keywords: three-dimensional micro-finned tube, heat transfer, friction factor, heat exchanger

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Authors: Fergus Wade, Jasmine Makker, Matthew Jankinson, Aminah Qamar, Gemma Morrelli, Shayan Shah

Abstract:

Background: Ambulance offload delays (AODs) affect patient outcomes. At baseline, the average AOD at Princess Royal University Hospital (PRUH) was 41 minutes, in breach of the 15-minute target. Aims: By February 2023, we aimed to reduce: the average AOD to 30 minutes percentage of AOD >30 minutes (PA30) to 25% and >60 minutes (PA60) to 10% Methods: Following a root-cause analysis, we implemented 2 Plan, Do, Study, Act (PDSA) cycles. PDSA-1 ‘Drop-and-run’: ambulances waiting >15 minutes for a handover left the patients in the Emergency Department (ED) and returned to the community. PDSA-2: Booking in the patients before the handover, allowing direct updates to online records, eliminating the need for handwritten notes. Outcome measures: AOD, PA30, and PA60, and process measures: total ambulances and patients in the ED were recorded for 16 weeks. Results: In PDSA-1, all parameters increased slightly despite unvarying ED crowding. In PDSA-2, two shifts in data were seen: initially, a sharp increase in the outcome measures consistent with increased ED crowding, followed by a downward shift when crowding returned to baseline (p<0.01). Within this interval, the AOD reduced to 29.9 minutes, and PA30 and PA60 were 31.2% and 9.2% respectively. Discussion/conclusion: PDSA-1 didn’t result in any significant changes; lack of compliance was a key cause. The initial upward shift in PDSA-2 is likely associated with NHS staff strikes. However, during the second interval, the AOD and the PA60 met our targets of 30 minutes and 10%, respectively, improving patient flow in the ED. This was sustained without further input and if maintained, saves 2 paramedic shifts every 3 days.

Keywords: ambulance offload, district general hospital, handover, quality improvement

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Authors: Todor Bačkalić, Marinko Maslarić, Milosav Georgijević, Sanja Bojić

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Water transport could be the backbone of the future European combined transport system. The future transport policy in landlocked countries from the Danube Region has to be based on inland waterway transport (IWT). The development of the container transport on inland waterways depends directly on technical-exploitative characteristics of the network of inland waterways. Research of navigational abilities of inland waterways is the basic step in transport planning. The size of the vessel’s draught (T) is the limiting value in project tasks and it depends on the depth of the waterway. Navigation characteristics of rivers have to be determined as precise as possible, especially from the aspect of determination of the possible draught of vessels. This article outlines a rationale, why it is necessary to develop competence about infrastructure risk in water transport. Climate changes are evident and require special attention and global monitoring. Current risk assessment methods for Inland waterway transport just consider some dramatic events. We present a new method for the assessment of risk and vulnerability of inland waterway transport where river depth represents a crucial part. The analysis of water level changes in the lower Danube was done for two significant periods (1965-1979 and 1998-2012).

Keywords: container vessel, draught, probability, the Danube

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Authors: Jinkoo Kim, Minsung Kim

Abstract:

This study develops a hybrid seismic energy dissipation device composed of a viscoelastic damper and a steel slit damper connected in parallel. A cyclic loading test is conducted on a test specimen to validate the seismic performance of the hybrid damper. Then a moment-framed model structure is designed without seismic load so that it is retrofitted with the hybrid dampers. The model structure is transformed into an equivalent simplified system to find out optimum story-wise damper distribution pattern using genetic algorithm. The effectiveness of the hybrid damper is investigated by fragility analysis and the life cycle cost evaluation of the structure with and without the dampers. The analysis results show that the model structure has reduced probability of reaching damage states, especially the complete damage state, after seismic retrofit. The expected damage cost and consequently the life cycle cost of the retrofitted structure turn out to be significantly small compared with those of the original structure. Acknowledgement: This research was supported by the Ministry of Trade, Industry and Energy (MOTIE) and Korea Institute for Advancement of Technology (KIAT) through the International Cooperative R & D program (N043100016).

Keywords: seismic retrofit, slit dampers, friction dampers, hybrid dampers

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Authors: Bhat Geetalaxmi Jairam, D. V. Ashoka

Abstract:

Wireless Sensor Networks are used in many applications to collect sensed data from different sources. Sensed data has to be delivered through sensors wireless interface using multi-hop communication towards the sink. The data collection in wireless sensor networks consumes energy. Energy consumption is the major constraints in WSN .Reducing the energy consumption while increasing the amount of generated data is a great challenge. In this paper, we have implemented two data gathering protocols with multiple mobile sinks/elements to collect data from sensor nodes. First, is Energy-Efficient Data Gathering with Tour Length-Constrained Mobile Elements in Wireless Sensor Networks (EEDG), in which mobile sinks uses vehicle routing protocol to collect data. Second is An Intelligent Agent-based Routing Structure for Mobile Sinks in WSNs (IAR), in which mobile sinks uses prim’s algorithm to collect data. Authors have implemented concepts which are common to both protocols like deployment of mobile sinks, generating visiting schedule, collecting data from the cluster member. Authors have compared the performance of both protocols by taking statistics based on performance parameters like Delay, Packet Drop, Packet Delivery Ratio, Energy Available, Control Overhead. Authors have concluded this paper by proving EEDG is more efficient than IAR protocol but with few limitations which include unaddressed issues likes Redundancy removal, Idle listening, Mobile Sink’s pause/wait state at the node. In future work, we plan to concentrate more on these limitations to avail a new energy efficient protocol which will help in improving the life time of the WSN.

Keywords: aggregation, consumption, data gathering, efficiency

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Authors: Fei Gao, Rodolfo C. Raga Jr.

Abstract:

This research proposal will ascertain the major risk factors for diabetes and to design a predictive model for risk assessment. The project aims to improve diabetes early detection and management by utilizing data science techniques, which may improve patient outcomes and healthcare efficiency. The phase relation values of each attribute were used to analyze and choose the attributes that might influence the examiner's survival probability using Diabetes Health Indicators Dataset from Kaggle’s data as the research data. We compare and evaluate eight machine learning algorithms. Our investigation begins with comprehensive data preprocessing, including feature engineering and dimensionality reduction, aimed at enhancing data quality. The dataset, comprising health indicators and medical data, serves as a foundation for training and testing these algorithms. A rigorous cross-validation process is applied, and we assess their performance using five key metrics like accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC). After analyzing the data characteristics, investigate their impact on the likelihood of diabetes and develop corresponding risk indicators.

Keywords: diabetes, risk factors, predictive model, risk assessment, data science techniques, early detection, data analysis, Kaggle

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