Search results for: evidence based practice

Authors: Edidiong Ekefre

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The Nigerian civil war was one of the foremost postcolonial conflicts in West Africa that attracted a serious humanitarian problem due to an unprecedented refugee crisis that affected the Biafran region. Due to its geographical location, the Nigerian government used blockades and starvation as a weapon of war against the Biafran. Faced with strong opposition from the Nigerian government, most humanitarian organizations withdrew their support from Biafra, whose death toll was rapidly growing daily due to starvation, malnutrition, and chronic ailment. Thus, the Catholic Church, a major Christian denomination in Biafra, had to see it as its religious obligation to support the humanitarian needs of the Biafrans. Thus, applying oral history methods with archival research, this paper examines the humanitarian activities of the Catholic Church in the Nigerian civil war. It contends that the Catholic Church was a key player in the humanitarian aspect of the Nigerian civil war. The paper concludes that faith-based humanitarian intervention in the Biafran refugee crisis was essential for the survival of the Biafran war-stricken women and children.

Keywords: refugee crisis, humanitarian intervention, Caritas International, blockades, airlifts, starvation

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Authors: Guoliang Fan, Aiping Li, Nan Xie, Liyun Xu, Xuemei Liu

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Mass customization production increases the difficulty of the production line layout planning. The material distribution process for variety of parts is very complex, which greatly increases the cost of material handling and logistics. In response to this problem, this paper presents an approach of production line layout planning based on complexity measurement. Firstly, by analyzing the influencing factors of equipment layout, the complexity model of production line is established by using information entropy theory. Then, the cost of the part logistics is derived considering different variety of parts. Furthermore, the function of optimization including two objectives of the lowest cost, and the least configuration complexity is built. Finally, the validity of the function is verified in a case study. The results show that the proposed approach may find the layout scheme with the lowest logistics cost and the least complexity. Optimized production line layout planning can effectively improve production efficiency and equipment utilization with lowest cost and complexity.

Keywords: production line, layout planning, complexity measurement, optimization, mass customization

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Authors: Sari F. Alkhatib, Chang Je Park, Gyuhong Roh

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The iterative scheme which is used to treat buildup factors for stratified shields is being investigated here using the layer-splitting technique. A simple suggested formalism for the scheme based on the Kalos’ formula is introduced, based on which the implementation of the testing technique is carried out. The second layer in a double-layer shield was split into two equivalent layers and the scheme (with the suggested formalism) was implemented on the new “three-layer” shield configuration. The results of such manipulation on water-lead and water-iron shields combinations are presented here for 1 MeV photons. It was found that splitting the second layer introduces some deviation on the overall buildup factor value. This expected deviation appeared to be higher in the case of low Z layer followed by high Z. However, the overall performance of the iterative scheme showed a great consistency and strong coherence even with the introduced changes. The introduced layer-splitting testing technique shows the capability to be implemented in test the iterative scheme with a wide range of formalisms.

Keywords: buildup factor, iterative scheme, stratified shields, layer-splitting tecnique

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Authors: Shih-Yu Wang, Shun-Wen Hsiao

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In the field of cybersecurity, there exists many vendors giving malware samples classified results, namely naming after the label that contains some important information which is also called AV label. Lots of researchers relay on AV labels for research. Unfortunately, AV labels are too cluttered. They do not have a fixed format and fixed naming rules because the naming results were based on each classifiers' viewpoints. A way to fix the problem is taking a majority vote. However, voting can sometimes create problems of bias. Thus, we create a novel ensemble approach which does not rely on the cacophonous naming result but depend on group identification to aggregate everyone's opinion. To achieve this purpose, we develop an scoring system called Pairwise Consensus Score (PCS) to calculate result similarity. The entire method architecture combine Genetic Algorithm and PCS to find maximum consensus in the group. Experimental results revealed that our method outperformed the majority voting by 10% in term of the score.

Keywords: genetic algorithm, ensemble learning, malware family, malware labeling, AV labels

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Authors: Makamas Kumprou, Pipatana Amatachaya, Sugalya Amatachaya, Thiwabhorn Thaweewannakij, Preeda Arayawichanon

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Many individuals with spinal cord injury (SCI) need an ambulatory assistive device (AAD) to promote their independence and experience of task-specific walking practice. Without a periodic follow-up for their walking progression, however, many individuals may use the same AAD even though up to 66% of them had the potential to progress walking ability. This may distort their optimal ability and increase the possibility of having negative impacts due to the long-lasting used of an AAD. However, these findings were cross-sectionally collected without data confirmation for the benefit or negative impacts of those who changed the types of AAD used. Therefore, this study prospectively assessed the proportion of ambulatory individuals with SCI who were able to progress their walking ability as determined using a type of AAD, and the changes of their functional ability as well as the incidence of falls over 6 months. Twenty-four subjects with SCI who daily walked with an AAD were involved in the study for 2 visits over 6 months. At the first visit (baseline assessments), the subjects were assessed for their spatiotemporal variables (i.e., cadence, step length, stride length, and step symmetry) and walking ability using the 10-meter walk test (10MWT). Then, they were assessed for the possibility of their walking progression as determined using the ability of walking with the least support AAD with no more than contact guarding assist. Those who were capable of changing an AAD were trained for the ability to walk with a new AAD. Thereafter, all subjects were monthly monitored for incidence of fall over 6 months. At the second visit (after 6 months followed-up), subjects were reassessed for their spatiotemporal variables and 10MWT. The findings indicated that, of all 24 subjects, 8 subjects (33.3%) were able to walk with less support AAD than their usual one. The walking cadence, step length symmetry, and walking ability of these subjects improved significantly greater than those who walked with the same AAD (p < 0.05). Among these subjects, one subject (12.5%) reported fell (3 times) during the follow-up period, whereas 5 subjects (31.3%) who walked with the same AAD experienced at least one fall (range 1 – 16 times). The findings indicated that a large proportion of ambulatory individuals with SCI who daily walked with an AAD could progress their walking ability, whereby their walking ability and safety also significantly improved after they walked with an optimal AAD. The findings suggest the need for a periodic follow-up for an appropriate AAD used for these individuals.

Keywords: walking device, walker, crutches, cane, rehabilitation

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Authors: Mercia I. Van Der Walt, Suzan Sayegh, Izzeldin E. L. J. Ibrahim, Mohamed G. Al-Kuwari, Manaf Kamil

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Background: Increased physical activity is associated with improvements in health conditions. Walking is recognized as an easy form of physical activity and a strategy used in health promotion. Step into Health (SIH), a national community program, was established in Qatar to support physical activity promotion through the monitoring of step counts. This study aims to assess the physical activity levels of the adult population in Qatar through a pedometer-based community program over a three-year-period. Methodology: This cross-sectional longitudinal study was conducted between from January 2013 and December 2015 based on daily step counts. A total of 15,947 adults (8,551 males and 7,396 females), from different nationalities enrolled in the program and aged 18 to 64, are included. The program involves free distribution of pedometers to members who voluntarily choose to register. It is also supported by a self-monitoring online account and linked to a web-database. All members are informed about the 10,000 steps/day target and automated emails as well as text messages are sent as reminders to upload data. Daily step counts were measured through the Omron HJ-324U pedometer (Omron Healthcare Co., Ltd., Japan). Analyses are done on the data extracted from the web-database. Results: Daily average step count for the overall community increased from 4,830 steps/day (2013) to 6,124 steps /day (2015). This increase was also observed within the three age categories (18–30), (31-45) and (>45) years. Average steps per day were found to be more among males compared with females in each of the aforementioned age groups. Moreover, males and females in the age group (>45 years) show the highest average step count with 7,010 steps/day and 5,564 steps/day respectively. The 21% increase in overall step count throughout the study period is associated with well-resourced program and ongoing impact in smaller communities such as workplaces and universities, a step in the right direction. However, the average step count of 6,124 steps/day in the third year is still classified as the low active category. Although the program showed an increase step count we found, 33% of the study population are low active, 35 % are sedentary with only 32% being active. Conclusion: This study indicates that the pedometer-based intervention was effective in increasing the daily physical activity of participants. However, alternative approaches need to be incorporated within the program to educate and encourage the community to meet the physical activity recommendations in relation to step count.

Keywords: pedometer, physical activity, Qatar, step count

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Authors: László Schmidt

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Technological and digital innovation is constantly and dynamically evolving, which poses an enormous challenge to both lawmaking and law enforcement. To legislation because artificial intelligence permeates many areas of people’s daily lives that the legislator must regulate. it can see how challenging it is to regulate e.g. self-driving cars/taxis/camions etc. Not to mention cryptocurrencies and Chat GPT, the use of which also requires legislative intervention. Artificial intelligence also poses an extraordinary challenge to law enforcement. In criminal cases, police and prosecutors can make great use of AI in investigations, e.g. in forensics, DNA samples, reconstruction, identification, etc. But it can also be of great help in the detection of crimes committed in cyberspace. In the case of cybercrime, on the one hand, it can be viewed as a new type of crime that can only be committed with the help of information systems, and that has a specific protected legal object, such as an information system or data. On the other hand, it also includes traditional crimes that are much easier to commit with the help of new tools. According to Hungarian Criminal Code section 375 (1), any person who, for unlawful financial gain, introduces data into an information system, or alters or deletes data processed therein, or renders data inaccessible, or otherwise interferes with the functioning of the information system, and thereby causes damage, is guilty of a felony punishable by imprisonment not exceeding three years. The Covid-19 coronavirus epidemic has had a significant impact on our lives and our daily lives. It was no different in the world of crime. With people staying at home for months, schools, restaurants, theatres, cinemas closed, and no travel, criminals have had to change their ways. Criminals were committing crimes online in even greater numbers than before. These crimes were very diverse, ranging from false fundraising, the collection and misuse of personal data, extortion to fraud on various online marketplaces. The most vulnerable age groups (minors and elderly) could be made more aware and prevented from becoming victims of this type of crime through targeted programmes. The aim of the study is to show the Hungarian judicial practice in relation to cybercrime and possible preventive solutions.

Keywords: cybercrime, COVID-19, Hungary, criminal law

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Authors: Noureddine Seddari, Mohamed Belaoued, Salah Bougueroua

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The modeling of complex systems is generally based on the decomposition of their components into sub-systems easier to handle. This division has to be made in a methodical way. In this paper, we introduce an industrial control system modeling and simulation based on the Multi-Agent System (MAS) methodology AALAADIN and more particularly the underlying conceptual model Agent/Group/Role (AGR). Indeed, in this division using AGR model, the overall system is decomposed into sub-systems in order to improve the understanding of regulation and control systems, and to simplify the implementation of the obtained agents and their groups, which are implemented using the Multi-Agents Development KIT (MAD-KIT) platform. This approach appears to us to be the most appropriate for modeling of this type of systems because, due to the use of MAS, it is possible to model real systems in which very complex behaviors emerge from relatively simple and local interactions between many different individuals, therefore a MAS is well adapted to describe a system from the standpoint of the activity of its components, that is to say when the behavior of the individuals is complex (difficult to describe with equations). The main aim of this approach is the take advantage of the performance, the scalability and the robustness that are intuitively provided by MAS.

Keywords: complex systems, modeling and simulation, industrial control system, MAS, AALAADIN, AGR, MAD-KIT

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Authors: Jantakan Jullawateelert, Korakod Haonoo, Sutipong Sananseang, Sarun Torpaiboon, Thanunthon Bowornsakulwong, Lalintip Hocharoen

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Process scale-up is essential for the biological process to increase production capacity from bench-scale bioreactors to either pilot or commercial production. Scale-up based on constant volumetric oxygen mass transfer coefficient (KLa) is mostly used as a scale-up factor since oxygen supply is one of the key limiting factors for cell growth. However, to estimate KLa of culture vessels operated with different conditions are time-consuming since it is considerably influenced by a lot of factors. To overcome the issue, this study aimed to establish correlation equations of KLa and operating parameters in 0.5 L and 5 L bioreactor employed with pitched-blade impeller and gas sparger. Temperature, gas flow rate, agitation speed, and impeller position were selected as process parameters and equations were created using response surface methodology (RSM) based on central composite design (CCD). In addition, the effects of these parameters on KLa were also investigated. Based on RSM, second-order polynomial models for 0.5 L and 5 L bioreactor were obtained with an acceptable determination coefficient (R²) as 0.9736 and 0.9190, respectively. These models were validated, and experimental values showed differences less than 10% from the predicted values. Moreover, RSM revealed that gas flow rate is the most significant parameter while temperature and agitation speed were also found to greatly affect the KLa in both bioreactors. Nevertheless, impeller position was shown to influence KLa in only 5L system. To sum up, these modeled correlations can be used to accurately predict KLa within the specified range of process parameters of two different sizes of bioreactors for further scale-up application.

Keywords: response surface methodology, scale-up, stirred-tank bioreactor, volumetric oxygen mass transfer coefficient

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Authors: Nor Zila Abd Hamid, Mohd Salmi M. Noorani

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This study is focused on the development of prediction models of the Ozone concentration time series. Prediction model is built based on chaotic approach. Firstly, the chaotic nature of the time series is detected by means of phase space plot and the Cao method. Then, the prediction model is built and the local linear approximation method is used for the forecasting purposes. Traditional prediction of autoregressive linear model is also built. Moreover, an improvement in local linear approximation method is also performed. Prediction models are applied to the hourly ozone time series observed at the benchmark station in Malaysia. Comparison of all models through the calculation of mean absolute error, root mean squared error and correlation coefficient shows that the one with improved prediction method is the best. Thus, chaotic approach is a good approach to be used to develop a prediction model for the Ozone concentration time series.

Keywords: chaotic approach, phase space, Cao method, local linear approximation method

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Authors: Sunghae Jun

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Technology management (TM) is important issue in a company improving the competitiveness. Among many activities of TM, technology analysis (TA) is important factor, because most decisions for management of technology are decided by the results of TA. TA is to analyze the developed results of target technology using statistics or Delphi. TA based on Delphi is depended on the experts’ domain knowledge, in comparison, TA by statistics and machine learning algorithms use objective data such as patent or paper instead of the experts’ knowledge. Many quantitative TA methods based on statistics and machine learning have been studied, and these have been used for technology forecasting, technological innovation, and management of technology. They applied diverse computing tools and many analytical methods case by case. It is not easy to select the suitable software and statistical method for given TA work. So, in this paper, we propose a methodology for quantitative TA using statistical computing software called R and data science to construct a general framework of TA. From the result of case study, we also show how our methodology is applied to real field. This research contributes to R&D planning and technology valuation in TM areas.

Keywords: technology management, R system, R data science, statistics, machine learning

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Authors: Asmir Gogic, Aljo Mujcic, Sandra Ibric, Nermin Suljanovic

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Ubiquity of natural disasters during last few decades have risen serious questions towards the prediction of such events and human safety. Every disaster regardless its proportion has a precursor which is manifested as a disruption of some environmental parameter such as temperature, humidity, pressure, vibrations and etc. In order to anticipate and monitor those changes, in this paper we propose an overall system for disaster prediction and monitoring, based on wireless sensor network (WSN). Furthermore, we introduce a modified and simplified WSN routing protocol built on the top of the trickle routing algorithm. Routing algorithm was deployed using the bluetooth low energy protocol in order to achieve low power consumption. Performance of the WSN network was analyzed using a real life system implementation. Estimates of the WSN parameters such as battery life time, network size and packet delay are determined. Based on the performance of the WSN network, proposed system can be utilized for disaster monitoring and prediction due to its low power profile and mesh routing feature.

Keywords: bluetooth low energy, disaster prediction, mesh routing protocols, wireless sensor networks

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Authors: Gerardo Casal, Miguel E. Vázquez-Méndez

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The clothoid (also known as Cornu spiral or Euler spiral) is a curve that is characterized because its curvature is proportional to its length. This property makes that it would be widely used as transition curve for designing the layout of roads and railway tracks. In this work, from the geometrical property characterizing the clothoid, its parametric equations are obtained and two algorithms to compute it are compared. The first (classical), is widely used in Surveying Schools and it is based on the use of explicit formulas obtained from Taylor expansions of sine and cosine functions. The second one (alternative) is a very simple algorithm, based on the numerical solution of the initial value problems giving the clothoid parameterization. Both methods are compared in some typical surveying problems. The alternative method does not use complex formulas and so it is conceptually very simple and easy to apply. It gives good results, even if the classical method goes wrong (if the quotient between length and radius of curvature is high), needs no subsequent translations nor rotations and, consequently, it seems an efficient tool for designing the layout of roads and railway tracks.

Keywords: transition curves, railroad and highway engineering, Runge-Kutta methods

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Authors: Wanqing You, Kai Qian, Ying Qian

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The concepts of Cloud Computing provide users with infrastructure, platform and software as service, which make those services more accessible for people via Internet. To better analysis the performance of Cloud Computing provisioning policies as well as resources allocation strategies, a toolkit named CloudSim proposed. With CloudSim, the Cloud Computing environment can be easily constructed by modelling and simulating cloud computing components, such as datacenter, host, and virtual machine. A good scheduling strategy is the key to achieve the load balancing among different machines as well as to improve the utilization of basic resources. Recently, the existing scheduling algorithms may work well in some presumptive cases in a single machine; however they are unable to make the best decision for the unforeseen future. In real world scenario, there would be numbers of tasks as well as several virtual machines working in parallel. Based on the concepts of multi-queue, this paper presents a new scheduling algorithm to schedule tasks with CloudSim by taking into account several parameters, the machines’ capacity, the priority of tasks and the history log.

Keywords: hierarchical queue, load balancing, CloudSim, information technology

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Authors: Yanwen Li, Shuguo Xie

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In electromagnetic imaging, because of the diffraction limited system, the pixel values could change slowly near the edge of the image targets and they also change with the location in the same target. Using traditional digital image segmentation methods to segment electromagnetic gradient images could result in lots of errors because of this change in pixel values. To address this issue, this paper proposes a novel image segmentation and extraction algorithm based on Mean-Shift and dictionary learning. Firstly, the preliminary segmentation results from adaptive bandwidth Mean-Shift algorithm are expanded, merged and extracted. Then the overlap rate of the extracted image block is detected before determining a segmentation region with a single complete target. Last, the gradient edge of the extracted targets is recovered and reconstructed by using a dictionary-learning algorithm, while the final segmentation results are obtained which are very close to the gradient target in the original image. Both the experimental results and the simulated results show that the segmentation results are very accurate. The Dice coefficients are improved by 70% to 80% compared with the Mean-Shift only method.

Keywords: gradient image, segmentation and extract, mean-shift algorithm, dictionary iearning

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Authors: Mohamad Ammar Ayass, Natalya Griko, Victor Pashkov, Wanying Cao, Kevin Zhu, Jin Zhang, Lina Abi Mosleh

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Respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent for coronavirus disease 2019 (COVID-19). Early evidence pointed at the angiotensin-converting enzyme 2 (ACE-2) expressed on the epithelial cells of the lung as the main entry point of SARS-CoV-2 into the cells. The viral entry is mediated by the binding of the Receptor Binding Domain (RBD) of the spike protein that is expressed on the surface of the virus to the ACE-2 receptor. As the number of SARS-CoV-2 variants continues to increase, mutations arising in the RBD of SARS-CoV-2 may lead to the ineffectiveness of RBD targeted neutralizing antibodies. To address this limitation, the objective of this study is to develop a combination of aptamers that target different regions of the RBD, preventing the binding of the spike protein to ACE-2 receptor and subsequent viral entry and replication. A safe and innovative biomedical tool was developed to inhibit viral infection and reduce the harms of COVID-19. In the present study, DNA aptamers were developed against a recombinant trimer S protein using the Systematic Evolution of Ligands by Exponential enrichment (SELEX). Negative selection was introduced at round number 7 to select for aptamers that bind specifically to the RBD domain. A series of 9 aptamers (ADI2010, ADI2011, ADI201L, ADI203L, ADI205L, ADIR68, ADIR74, ADIR80, ADIR83) were selected and characterized with high binding affinity and specificity to the RBD of the spike protein. Aptamers (ADI25, ADI2009, ADI203L) were able to bind and pull down endogenous spike protein expressed on the surface of SARS-CoV-2 virus in COVID-19 positive patient samples and determined by liquid chromatography- tandem mass spectrometry analysis (LC-MS/MS). LC-MS/MS data confirmed that aptamers can bind to the RBD of the spike protein. Furthermore, results indicated that the combination of the 9 best aptamers inhibited the binding of the purified trimer spike protein to the ACE-2 receptor found on the surface of Vero E6 cells. In the same experiment, the combined aptamers displayed a better neutralizing effect than antibodies. The data suggests that the selected aptamers could be used in therapy to neutralize the effect of the SARS-CoV-2 virus by inhibiting the interaction between the RBD and ACE-2 receptor, preventing viral entry into target cells and therefore blocking viral replication.

Keywords: aptamer, ACE-2 receptor, binding inhibitor, COVID-19, spike protein, SARS-CoV-2, treatment

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Authors: José M. Liñeira Del Río, Ramón Rial, Khodor Nasser, María J.G. Guimarey

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The need to develop new lubricants that offer better anti-friction and anti-wear performance in internal combustion vehicles is one of the great challenges of lubrication in the automotive field. The addition of nanoparticles has emerged as a possible solution and, combined with the lubricating power of ionic liquids, may become one of the alternatives to reduce friction losses and wear of the contact surfaces in the conditions to which tribo-pairs are subjected, especially in the contact of the piston rings and the cylinder liner surface. In this study, the improvement in SAE 10W-40 engine oil tribological performance after the addition of magnesium oxide (MgO) nanoadditives and two different phosphonium-based ionic liquids (ILs) was investigated. The nanoparticle characterization was performed by means of transmission electron microscopy (TEM), Fourier-transform infrared spectroscopy (FTIR), Raman spectroscopy, X-ray diffraction (XRD), and scanning electron microscopy (SEM). The tribological properties, friction coefficients and wear parameters of the formulated oil modified with 0.01 wt.% MgO and 1 wt.% ILs compared with the neat 10W-40 oil were performed and analyzed using a ball-on-three-pins tribometer and a 3D optical profilometer, respectively. Further analysis on the worn surface was carried out by Raman spectroscopy and SEM microscopy, illustrating the formation of the protective IL and MgO tribo-films as hybrid additives. In friction tests with sliding steel-steel tribo-pairs, IL3-based hybrid nanolubricant decreased the friction coefficient and wear volume by 7% and 59%, respectively, in comparison with the neat SAE 10W-40, while the one based on IL1 only achieved a reduction of these parameters by 6% and 39%, respectively. Thus, the tribological characterization also revealed that the MgO and IL3 addition has a positive synergy over the commercial lubricant, adequately meeting the requirements for their use in internal combustion engines. In summary, this study has shown that the addition of ionic liquids to MgO nanoparticles can improve the stability and lubrication behavior of MgO nanolubricant and encourages more investigations on using nanoparticle additives with green solvents such as ionic liquids to protect the environment as well as prolong the lifetime of machinery. The improvement in the lubricant properties was attributed to the following wear mechanisms: the formation of a protective tribo-film and the ability of nanoparticles to fill out valleys between asperities, thereby effectively smoothing out the shearing surfaces.

Keywords: lubricant, nanoparticles, phosphonium-based ionic liquids, tribology

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Authors: Amin Salighehdar, Ziwen Ye, Mingzhe Liu, Ionut Florescu, Alan F. Blumberg

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Storm surge is an abnormal water level caused by a storm. Accurate prediction of a storm surge is a challenging problem. Researchers developed various ensemble modeling techniques to combine several individual forecasts to produce an overall presumably better forecast. There exist some simple ensemble modeling techniques in literature. For instance, Model Output Statistics (MOS), and running mean-bias removal are widely used techniques in storm surge prediction domain. However, these methods have some drawbacks. For instance, MOS is based on multiple linear regression and it needs a long period of training data. To overcome the shortcomings of these simple methods, researchers propose some advanced methods. For instance, ENSURF (Ensemble SURge Forecast) is a multi-model application for sea level forecast. This application creates a better forecast of sea level using a combination of several instances of the Bayesian Model Averaging (BMA). An ensemble dressing method is based on identifying best member forecast and using it for prediction. Our contribution in this paper can be summarized as follows. First, we investigate whether the ensemble models perform better than any single forecast. Therefore, we need to identify the single best forecast. We present a methodology based on a simple Bayesian selection method to select the best single forecast. Second, we present several new and simple ways to construct ensemble models. We use correlation and standard deviation as weights in combining different forecast models. Third, we use these ensembles and compare with several existing models in literature to forecast storm surge level. We then investigate whether developing a complex ensemble model is indeed needed. To achieve this goal, we use a simple average (one of the simplest and widely used ensemble model) as benchmark. Predicting the peak level of Surge during a storm as well as the precise time at which this peak level takes place is crucial, thus we develop a statistical platform to compare the performance of various ensemble methods. This statistical analysis is based on root mean square error of the ensemble forecast during the testing period and on the magnitude and timing of the forecasted peak surge compared to the actual time and peak. In this work, we analyze four hurricanes: hurricanes Irene and Lee in 2011, hurricane Sandy in 2012, and hurricane Joaquin in 2015. Since hurricane Irene developed at the end of August 2011 and hurricane Lee started just after Irene at the beginning of September 2011, in this study we consider them as a single contiguous hurricane event. The data set used for this study is generated by the New York Harbor Observing and Prediction System (NYHOPS). We find that even the simplest possible way of creating an ensemble produces results superior to any single forecast. We also show that the ensemble models we propose generally have better performance compared to the simple average ensemble technique.

Keywords: Bayesian learning, ensemble model, statistical analysis, storm surge prediction

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Authors: Beibit Karibayev, Akmaral Imanbayeva, Timur Namazbayev

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Currently, the small spacecraft (SSC) industry is experiencing a big boom in popularity. This is primarily due to ease of use, low cost and mobility. In addition, these programs can be implemented not only at the state level but also at the level of companies, universities and other organizations. For remote sensing of the Earth (ERS), small spacecraft with an orientation system is used. It is important to take into account here that a remote sensing device, for example, a camera for photographing the Earth's surface, must be directed at the Earth's surface. But this, at first glance, the limitation can be turned into an advantage using a patch antenna. This work proposed to use a patch antenna based on a unidirectional fractal in the SSC. The CST Microwave Studio software package was used for simulation and research. Copper (ε = 1.0) was chosen as the emitting element and reflector. The height of the substrate was 1.6 mm, the type of substrate material was FR-4 (ε = 4.3). The simulation was performed in the frequency range of 0 – 6 GHz. As a result of the research, a patch antenna based on fractal geometry was developed for ERS nanosatellites. The capabilities of these antennas are modeled and investigated. A method for calculating and modeling fractal geometry for patch antennas has been developed.

Keywords: antenna, earth remote sensing, fractal, small spacecraft

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Authors: Lazhar Zourgui

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Opuntia species are used as local medicinal interventions for chronic diseases and as food sources, mainly because they possess nutritional properties and biological activities. Opuntia ficus-indica (L.) Mill, commonly known as prickly pear or nopal cactus, is the most economically valuable plant in the Cactaceae family worldwide. It is a tropical or subtropical plant native to tropical and subtropical America, which can grow in arid and semi-arid climates. It belongs to the family of angiosperms dicotyledons Cactaceae of which about 1500 species of cacti are known. The Opuntia plant is distributed throughout the world and has great economic potential. There are differences in the phytochemical composition of Opuntia species between wild and domesticated species and within the same species. It is an interesting source of plant bioactive compounds. Bioactive compounds are compounds with nutritional benefits and are generally classified into phenolic and non-phenolic compounds and pigments. Opuntia species are able to grow in almost all climates, for example, arid, temperate, and tropical climates, and their bioactive compound profiles change depending on the species, cultivar, and climatic conditions. Therefore, there is an opportunity for the discovery of new compounds from different Opuntia cultivars. Health benefits of prickly pear are widely demonstrated: There is ample evidence of the health benefits of consuming prickly pear due to its source of nutrients and vitamins and its antioxidant properties due to its content of bioactive compounds. In addition, prickly pear is used in the treatment of hyperglycemia and high cholesterol levels, and its consumption is linked to a lower incidence of coronary heart disease and certain types of cancer. It may be effective in insulin-independent type 2 diabetes mellitus. Opuntia ficus-Indica seed oil has shown potent antioxidant and prophylactic effects. Industrial applications of these bioactive compounds are increasing. In addition to their application in the pharmaceutical industries, bioactive compounds are used in the food industry for the production of nutraceuticals and new food formulations (juices, drinks, jams, sweeteners). In my lecture, I will review in a comprehensive way the phytochemical, nutritional, and bioactive compound composition of the different aerial and underground parts of Opuntia species. The biological activities and applications of Opuntia compounds are also discussed.

Keywords: medicinal plants, cactus, Opuntia, actives biomolecules, biological activities

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Authors: Marios Papaevripidou, Yvoni Pavlou, Zacharias Zacharia

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Embodied cognition and additional (touch) sensory channel theories indicate that physical manipulation is crucial to learning since it provides, among others, touch sensory input, which is needed for constructing knowledge. Given these theories, the use of Physical Manipulatives (PM) becomes a prerequisite for learning. On the other hand, empirical research on Virtual Manipulatives (VM) (e.g., simulations) learning has provided evidence showing that the use of PM, and thus haptic sensory input, is not always a prerequisite for learning. In order to investigate which means of experimentation, PM or VM, are required for enhancing student science learning at the kindergarten level, an empirical study was conducted that sought to investigate the impact of haptic feedback on the conceptual understanding of pre-school students (n=44, age mean=5,7) in three science domains: beam balance (D1), sinking/floating (D2) and springs (D3). The participants were equally divided in two groups according to the type of manipulatives used (PM: presence of haptic feedback, VM: absence of haptic feedback) during a semi-structured interview for each of the domains. All interviews followed the Predict-Observe-Explain (POE) strategy and consisted of three phases: initial evaluation, experimentation, final evaluation. The data collected through the interviews were analyzed qualitatively (open-coding for identifying students’ ideas in each domain) and quantitatively (use of non-parametric tests). Findings revealed that the haptic feedback enabled students to distinguish heavier to lighter objects when held in hands during experimentation. In D1 the haptic feedback did not differentiate PM and VM students' conceptual understanding of the function of the beam as a mean to compare the mass of objects. In D2 the haptic feedback appeared to have a negative impact on PM students’ learning. Feeling the weight of an object strengthen PM students’ misconception that heavier objects always sink, whereas the scientifically correct idea that the material of an object determines its sinking/floating behavior in the water was found to be significantly higher among the VM students than the PM ones. In D3 the PM students outperformed significantly the VM students with regard to the idea that the heavier an object is the more the spring will expand, indicating that the haptic input experienced by the PM students served as an advantage to their learning. These findings point to the fact that PMs, and thus touch sensory input, might not always be a requirement for science learning and that VMs could be considered, under certain circumstances, as a viable means for experimentation.

Keywords: haptic feedback, physical and virtual manipulatives, pre-school science learning, science experimentation

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Authors: Doni Dermawan

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Hypertension is a disease with a high prevalence in Indonesia. The prevalence of hypertension in Indonesia is based on the Basic Health Research (Riskesdas) in 2013 which amounted to 25.8%. Medicinal plants have been widely used to treat hypertension including roselle (Hibiscus sabdariffa L.) and garlic (Allium sativum L.) by a mechanism as angiotensin converting enzyme (ACE) inhibitor. The purpose of this research is to analyze the in silico (molecular studies) of pharmacological effects and toxicity of roselle (Hibiscus sabdariffa L.) and garlic (Allium sativum L.) as well as a combination of both are used as antihypertensive herbs. The results of study showed that roselle (Hibiscus sabdariffa L.) and garlic (Allium sativum L.) have great potential as antihypertensive herbs based on the affinity and stability of active substances to specific receptor with a much better value than a of antihypertensive drugs (lisinopril). Toxicity values determined by the method of AST, ALT and ALP in which the three values obtained indicate the presence of acute toxic effects that need to be considered in determining the dose of the extract of roselle and garlic as antihypertensives.

Keywords: Allium sativum, antihypertensive, Hibiscus sabdariffa, in silico, toxicity

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Authors: Pengfei Meng, Shuangcheng Jia, Qian Li

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We proposed a real-time high-precision semantic segmentation network based on a multi-resolution feature fusion module, the auxiliary feature extracting module, upsampling module, and atrous spatial pyramid pooling (ASPP) module. We designed a feature fusion structure, which is integrated with sufficient features of different resolutions. We also studied the effect of side-branch structure on the network and made discoveries. Based on the discoveries about the side-branch of the network structure, we used a side-branch auxiliary feature extraction layer in the network to improve the effectiveness of the network. We also designed upsampling module, which has better results than the original upsampling module. In addition, we also re-considered the locations and number of atrous spatial pyramid pooling (ASPP) modules and modified the network structure according to the experimental results to further improve the effectiveness of the network. The network presented in this paper takes the backbone network of Bisenetv2 as a basic network, based on which we constructed a network structure on which we made improvements. We named this network deep multiple-resolution bilateral networks for real-time, referred to as DMBR-Net. After experimental testing, our proposed DMBR-Net network achieved 81.2% mIoU at 119FPS on the Cityscapes validation dataset, 80.7% mIoU at 109FPS on the CamVid test dataset, 29.9% mIoU at 78FPS on the COCOStuff test dataset. Compared with all lightweight real-time semantic segmentation networks, our network achieves the highest accuracy at an appropriate speed.

Keywords: multi-resolution feature fusion, atrous convolutional, bilateral networks, pyramid pooling

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Authors: Nji Clement Bang, Rosemary Shafack M., Kum Henry Asei, Yaro Loveline Y

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Scholars perceive learner-centered teaching-learning reform as roles and resources in teacher education (TE) and professional outcome with transformative learning (TL) continuum dimensions. But, teaching-learning reform is fast proliferating amidst debilitating stakeholder systemic dichotomies, resources, commitment, resistance and poor quality outcome that necessitate stronger TE and professional continuums. Scholars keep seeking greater understanding of themes in teaching-learning reform, TE and professional outcome as continuums and how policymakers, student-teachers, teacher trainers and local communities concerned with initial TE can promote continuous holistic quality performance. To sustain the debate continuum and answer the overarching question, we use mixed-methods research-design with diverse literature and 409 sample-data. Onset text, interview and questionnaire analyses reveal debilitating teaching-learning reform in TE continuums that need TL revival. Follow-up focus group discussion and teaching considering TL insights reinforce holistic teaching-learning in TE. Therefore, significant increase in diverse prior-experience articulation1; critical reflection-discourse engagement2; teaching-practice interaction3; complex-activity constrain control4 and formative outcome- reintegration5 reinforce teaching-learning in learning-to-teach role-resource pathways and outcomes. Themes reiterate complex teaching-learning in TE programs that suits TL journeys and student-teachers and students cum teachers, workers/citizens become akin, transformative-learners who evolve personal and collective roles-resources towards holistic-lifelong-learning outcomes. The article could assist debate about quality teaching-learning reform through TL dimensions as TE and professional role-resource continuums.

Keywords: transformative learning perspectives, teacher education, initial teacher education, learner-centered pedagogical reform, life-long learning

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Authors: Maha Atout, Pippa Hemingway, Jane Seymour

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Background: A mixed method systematic review was undertaken in order to explore issues related to the experiences of health care providers and parents in the care of children with palliative care needs. The aims of this systematic review were to identify existing evidence about the experiences of communication in the care of children with palliative care needs, to appraise the research conducted in this area and to identify gaps in the literature in order to recommend for future related studies. Method: A mixed method systematic review of research on the experience of communication in the care of children with palliative care needs, conducted with parents and health professionals was undertaken. The electronic databases of CINAHL, Cochrane, PubMed, OVID, Social Care Online, Web of Science, Scopus, and ProQuest were searched for the period of 2000-2016. Inclusion was limited to studies of communication experience in the care of children with palliative care needs. Result: Thirty-eight studies were found. The studies were conducted in a variety of countries: Uganda, Jordan, USA, UK, Taiwan, Turkey, Ireland, Poland, Brazil, Australia, Switzerland, Sweden, Netherland, Lebanon, Spain, Greece, and China. The current review shows that parents tend to protect their children when they are discussing their illnesses with them, particularly where they have a life-threatening or life-limiting condition. The approach of parents towards the discussion of sensitive issues concerning death with their children is significantly affected by the cultural background of the families. Conservative cultures encourage collusion behaviours which tend to keep children unaware of the incurable nature of the disease. The major communication challenges reported by health professionals are facing difficulties in judging how much information should be given to parents, responding to difficult questions, conflicts with families and inadequate skills to support grieving families. Conclusion: It is probably significant for the future studies to consider the change of parent-child communication experience over time in order to understand how the parents could change their interaction styles with their children according to the different stages of their children’s disease. Moreover, further studies are required to investigate the experience of communication of parents of children with non-malignant life-threatening and life-limiting illnesses.

Keywords: children with life-threatening or life- limiting illnesses, end of life, experience of communication, healthcare care providers, paediatric palliative care

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Authors: Hossein Kh. Bisheh, Nan Wu

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Advanced composite materials have a great importance in engineering structures due to their high specific modulus and strength and low weight. These materials can be used in design and fabrication of automotive drive shafts to reduce the weight of the structure. Hence, an optimum design of a composite drive shaft satisfying the design criteria, can be an appropriate substitution of metallic drive shafts. The aim of this study is to design and analyze a composite automotive drive shaft with high specific strength and low weight satisfying the design criteria. Tsai-Wu criterion is chosen as the failure criterion. Various designs with different lay-ups and materials are investigated based on the design requirements and finally, an optimum design satisfying the design criteria is chosen based on the weight and cost considerations. The results of this study indicate that if the weight is the main concern, a shaft made of Carbon/Epoxy can be a good option, and if the cost is a more important parameter, a hybrid shaft made of aluminum and Carbon/Epoxy can be considered.

Keywords: Bending natural frequency, Composite drive shaft, Peak torque, Torsional buckling

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Authors: Alec Wells, Aminu Bello Usman, Justin McKeown

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The growing usage of smart speakers raises many privacy and trust concerns compared to other technologies such as smart phones and computers. In this study, a proxy measure of trust is used to gauge users’ opinions on three different technologies based on an empirical study, and to understand which technology most people are most likely to trust. The collected data were analysed using the Kruskal-Wallis H test to determine the statistical differences between the users’ trust level of the three technologies: smart speaker, computer and smart phone. The findings of the study revealed that despite the wide acceptance, ease of use and reputation of smart speakers, people find it difficult to trust smart speakers with their sensitive information via the Direct Voice Input (DVI) and would prefer to use a keyboard or touchscreen offered by computers and smart phones. Findings from this study can inform future work on users’ trust in technology based on perceived ease of use, reputation, perceived credibility and risk of using technologies via DVI.

Keywords: direct voice input, risk, security, technology, trust

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Authors: Mohammad Saberian, Reza Porhoseini, Mohammad Ali Rahgozar

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Peat is a partially carbonized vegetable tissue which is formed in wet conditions by decomposition of various plants, mosses and animal remains. This restricted definition, including only materials which are entirely of vegetative origin, conflicts with several established soil classification systems. Peat soils are usually defined as soils having more than 75 percent organic matter. Due to this composition, the structure of peat soil is highly different from the mineral soils such as silt, clay and sand. Peat has high compressibility, high moisture content, low shear strength and low bearing capacity, so it is considered to be in the category of problematic. Since this kind of soil is generally found in many countries and various zones, except for desert and polar zones, recognizing this soil is inevitably significant. The objective of this paper is to review the classification of peats based on various properties of peat soils such as organic contents, water content, color, odor, and decomposition, scholars offer various classification systems which Von Post classification system is one of the most well-known and efficient system.

Keywords: peat soil, degree of decomposition, organic content, water content, Von Post classification

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Authors: Morteza Taherinezhad, Ahmad Reza Rabbani, Morteza Asemani, Rudy Swennen

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Oil-oil correlation is one of the most important issues in geochemical studies that enables to classify oils genetically. Oil-oil correlation is generally estimated based on non-polar fractions of crude oil (e.g., saturate and aromatic compounds). Despite several advantages, the drawback of using these compounds is their susceptibility of being affected by secondary processes. The polar fraction of crude oil (e.g., asphaltenes) has similar characteristics to kerogen, and this structural similarity is preserved during migration, thermal maturation, biodegradation, and water washing. Therefore, these structural characteristics can be considered as a useful correlation parameter, and it can be concluded that asphaltenes from different reservoirs with the same genetic signatures have a similar origin. Hence in this contribution, an integrated study by using both non-polar and polar fractions of oil was performed to use the merits of both fractions. Therefore, five oil samples from oil fields in the Persian Gulf were studied. Structural characteristics of extracted asphaltenes were investigated by Fourier transform infrared (FTIR) spectroscopy. Graphs based on aliphatic and aromatic compounds (predominant compounds in asphaltenes structure) and sulphoxide and carbonyl functional groups (which are representatives of sulphur and oxygen abundance in asphaltenes) were used for comparison of asphaltenes structures in different samples. Non-polar fractions were analyzed by GC-MS. The study of asphaltenes showed the studied oil samples comprise two oil families with distinct genetic characteristics. The first oil family consists of Salman and Reshadat oil samples, and the second oil family consists of Resalat, Siri E, and Siri D oil samples. To validate our results, biomarker parameters were employed, and this approach completely confirmed previous results. Based on biomarker analyses, both oil families have a marine source rock, whereby marl and carbonate source rocks are the source rock for the first and the second oil family, respectively.

Keywords: biomarker, non-polar fraction, oil-oil correlation, petroleum geochemistry, polar fraction

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Authors: Yuan Zheng

Abstract:

3D model-based vehicle matching provides a new way for vehicle recognition, localization and tracking. Its key is to construct an evaluation function, also called fitness function, to measure the degree of vehicle matching. The existing fitness functions often poorly perform when the clutter and occlusion exist in traffic scenarios. In this paper, we present a practical and efficient fitness function. Unlike the existing evaluation functions, the proposed fitness function is to study the vehicle matching problem from both local and global perspectives, which exploits the pixel gradient information as well as the silhouette information. In view of the discrepancy between 3D vehicle model and real vehicle, a weighting strategy is introduced to differently treat the fitting of the model’s wireframes. Additionally, a normalization operation for the model’s projection is performed to improve the accuracy of the matching. Experimental results on real traffic videos reveal that the proposed fitness function is efficient and robust to the cluttered background and partial occlusion.

Keywords: 3D-2D matching, fitness function, 3D vehicle model, local image gradient, silhouette information

Procedia PDF Downloads 382