Search results for: diagnostic challenge

Authors: Zabeehullah, Fahim Arif, Yawar Abbas

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Software Defined Network (SDN) is a next genera-tion networking model which simplifies the traditional network complexities and improve the utilization of constrained resources. Currently, most of the SDN based Internet of Things(IoT) environments use traditional network routing strategies which work on the basis of max or min metric value. However, IoT network heterogeneity, dynamic traffic flow and complexity demands intelligent and self-adaptive routing algorithms because traditional routing algorithms lack the self-adaptions, intelligence and efficient utilization of resources. To some extent, SDN, due its flexibility, and centralized control has managed the IoT complexity and heterogeneity but still Software Defined IoT (SDIoT) lacks intelligence. To address this challenge, we proposed a model called Deep Routing Strategy (DRS) which uses Deep Learning algorithm to perform routing in SDIoT intelligently and efficiently. Our model uses real-time traffic for training and learning. Results demonstrate that proposed model has achieved high accuracy and low packet loss rate during path selection. Proposed model has also outperformed benchmark routing algorithm (OSPF). Moreover, proposed model provided encouraging results during high dynamic traffic flow.

Keywords: SDN, IoT, DL, ML, DRS

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Authors: Hamed Zolfaghari, Mojtaba Kord

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Project planners and controllers are frequently faced with the challenge of inadequate software for the preparation of automatic project progress reports based on actual project information updates. They usually make dashboards in Microsoft Excel, which is local and not applicable online. Another shortcoming is that it is not linked to planning software such as Microsoft Project, which lacks the database required for data storage. This study aimed to propose a model for the preparation of reports on automatic online project progress based on actual project information updates by the integration of Primavera P6, SQL database, and Power BI for a construction project. The designed model could be applicable to project planners and controller agents by enabling them to prepare project reports automatically and immediately after updating the project schedule using actual information. To develop the model, the data were entered into P6, and the information was stored on the SQL database. The proposed model could prepare a wide range of reports, such as earned value management, HR reports, and financial, physical, and risk reports automatically on the Power BI application. Furthermore, the reports could be published and shared online.

Keywords: primavera P6, SQL, Power BI, EVM, integration management

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Authors: Naveen Kumar, Shyambihari Prajapati

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Industry 4.0 is the fourth industrial revolution that focuses on interconnectivity of machine to machine, human to machine and human to human via Internet of Things (IoT). Technologies of industry 4.0 facilitate communication between human and machine through IoT and forms Cyber-Physical Production System (CPPS). In CPPS, multiple shop floors sensor data are connected through IoT and displayed through sensor dashboard to the operator. These sensor dashboards have enormous amount of information to be presented which becomes complex for operators to perform monitoring, controlling and interpretation tasks. Designing handheld sensor dashboards for supervision task will become a challenge for the interface designers. This paper reports emerging technologies of industry 4.0, changing context of increasing information complexity in consecutive industrial revolutions and upcoming design challenges for interface designers in context of Industry 4.0. Authors conclude that information complexity of sensor dashboards design has increased with consecutive industrial revolutions and designs of sensor dashboard causes cognitive load on users. Designing such complex dashboards interfaces in Industry 4.0 context will become main challenges for the interface designers.

Keywords: Industry4.0, sensor dashboard design, cyber-physical production system, Interface designer

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Authors: Ma. Gracia Corazon Cayanan, Kai Yuen Cheong, Li Sha

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Training a language model for a minority language has been a challenging task. The lack of available corpora to train and fine-tune state-of-the-art language models is still a challenge in the area of Natural Language Processing (NLP). Moreover, the need for high computational resources and bulk data limit the attainment of this task. In this paper, we presented the following contributions: (1) we introduce and used a translation pair set of Tagalog and English (TL-EN) in pre-training a language model to a minority language resource; (2) we fine-tuned and evaluated top-ranking and pre-trained semantic textual similarity binary task (STSB) models, to both TL-EN and STS dataset pairs. (3) then, we reduced the size of the model to offset the need for high computational resources. Based on our results, the models that were pre-trained to translation pairs and STS pairs can perform well for STSB task. Also, having it reduced to a smaller dimension has no negative effect on the performance but rather has a notable increase on the similarity scores. Moreover, models that were pre-trained to a similar dataset have a tremendous effect on the model’s performance scores.

Keywords: semantic matching, semantic textual similarity binary task, low resource minority language, fine-tuning, dimension reduction, transformer models

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Authors: Konstanca Nikolajevic, Nicolas Belanger, David Duvivier, Rabie Ben Atitallah, Abdelhakim Artiba

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Finding the optimal 3D path of an aerial vehicle under flight mechanics constraints is a major challenge, especially when the algorithm has to produce real-time results in flight. Kinematics models and Pythagorian Hodograph curves have been widely used in mobile robotics to solve this problematic. The level of difficulty is mainly driven by the number of constraints to be saturated at the same time while minimizing the total length of the path. In this paper, we suggest a pragmatic algorithm capable of saturating at the same time most of dimensioning helicopter 3D trajectories’ constraints like: curvature, curvature derivative, torsion, torsion derivative, climb angle, climb angle derivative, positions. The trajectories generation algorithm is able to generate versatile complex 3D motion primitives feasible by a helicopter with parameterization of the curvature and the climb angle. An upper ”motion primitives’ concatenation” algorithm is presented based. In this article we introduce a new way of designing three-dimensional trajectories based on what we call the ”Dubins gliding symmetry conjecture”. This extremely performing algorithm will be soon integrated to a real-time decisional system dealing with inflight safety issues.

Keywords: robotics, aerial robots, motion primitives, helicopter

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Authors: David Chung

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The development of seventeenth-century French harpsichord music is enigmatic in several respects. Although little is known about the formation of this style before 1650 (we have names of composers, but no surviving music), the style has attained a high degree of refinement and sophistication in the music of the earliest known masters (e.g. Chambonnières, Louis Couperin and D’Anglebert). In fact, how the seventeenth-century musicians acquired the skills of their art remains largely steeped in mystery, as the earliest major treatise on French keyboard pedagogy was not published until 1702 by Saint Lambert. This study fills this lacuna by surveying some twenty recently-rediscovered manuscripts, which offer ample materials for revisiting key issues pertaining to seventeenth-century harpsichord pedagogy. By analyzing the musical contents, the verbal information and explicit notation (such as written-out ornaments and rhythmic effects), this study provides a rich picture of the process of learning at the time, with engaging details of performance nuances often lacking in tutors and treatises. Of even greater significance, that creative skills (such as continuo and ornamentation) were taught alongside fundamental knowledge (solfèges, note values, etc.) at the earliest stage of learning offers fresh challenge for modern pedagogues to rethink how harpsichord pedagogy can be revamped to cater for our own pedagogical and aesthetic needs.

Keywords: French, harpsichord, pedagogy, seventeenth century

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Authors: Babar Sultan, Kiran Sultan, Waseem Khan, Ijaz Mansoor Qureshi

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In this paper, a novel idea for the performance enhancement of secondary network is proposed for Underlay Cognitive Radio Networks (CRNs). In Underlay CRNs, primary users (PUs) impose strict interference constraints on the secondary users (SUs). The proposed scheme is based on Artificial Bee Colony (ABC) optimization for relay selection and power allocation to handle the highlighted primary challenge of Underlay CRNs. ABC is a simple, population-based optimization algorithm which attains global optimum solution by combining local search methods (Employed and Onlooker Bees) and global search methods (Scout Bees). The proposed two-phase relay selection and power allocation algorithm aims to maximize the signal-to-noise ratio (SNR) at the destination while operating in an underlying mode. The proposed algorithm has less computational complexity and its performance is verified through simulation results for a different number of potential relays, different interference threshold levels and different transmit power thresholds for the selected relays.

Keywords: artificial bee colony, underlay spectrum sharing, cognitive radio networks, amplify-and-forward

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Authors: Nadia Pourabbas Tahvildari

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National identity is formed in the process of time and in the community while influenced by the historical events. The country which has a more coherent national and historical identity would be successful as well as strengthening solidarity and social cohesion. Among the international community where the various likes challenge the subject of identity, taking into consideration the components which using identity seems to be very critical. Handicrafts as reflecting the historical and cultural characteristics of the product location can be used as an important component in order to introduce the culture and identity to be evaluated. As one of the most durable crafts for man, handicrafts have played a continuous role in sustaining human culture. Today without the presence of handicrafts, restoration of culture and national identity and religious beliefs of the past clans and people, is not only difficult but is even impossible also. Due to its brilliant historical experience and having rich culture and civilization, Iran has accomplished to the high competence in the field of traditional arts and handicrafts. This article is a scientific approach which by using descriptive – analytic method based on library studies tried to address the issue of handicrafts looking to examine the position of the industry to consolidate the national identity. Studies indicate that Iran as one of the original human habitats in the field of handicrafts has adequate enrichment and in case there will be an appropriate planning and investment away from oil-based industry, it would be beneficent. Furthermore, the quality and variety of handicrafts can be used as an essential yardstick for the consolidation of Iran national identity in the age of globalization.

Keywords: handicrafts, Iran national identity, globalization, cultural heritage

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Authors: Reda Askouri, Mohamed Moussetad, Rhma Adhiri

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Reverse osmosis (RO) is one of the most widely used techniques for seawater desalination. However, the conversion rate of this method is generally limited to 35-45% due to the high-pressure capacity of the membranes. Additionally, the specific energy consumption (SEC) for seawater desalination is high, necessitating energy recovery systems to minimise energy consumption. This study aims to enhance the performance of seawater desalination by combining RO with a vibratory shear-enhanced processing (VSEP) technique. The RO unit in this study comprises two stages, each powered by a hydraulic turbocharger that increases the pressure in both stages. The concentrate from the second stage is then directly processed by VSEP technology. The results demonstrate that the permeate water obtained exhibits high quality and that the conversion rate is significantly increased, reaching high percentages with low SEC. Furthermore, the high concentration of total solids in the concentrate allows for potential exploitation within the environmental protection framework. By valorising the concentrated waste, it’s possible to reduce the environmental impact while increasing the overall efficiency of the desalination process.

Keywords: specific energy consumption, vibratory shear enhanced process, environmental challenge, water recovery

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Authors: Aftab Khan, Ashfaq Khan

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The research paper focuses on an interesting challenge faced in Blind Image Deblurring (BID). It relates to the estimation of arbitrarily shaped or non-parametric Point Spread Functions (PSFs) of motion blur caused by camera handshake. These PSFs exhibit much more complex shapes than their parametric counterparts and deblurring in this case requires intricate ways to estimate the blur and effectively remove it. This research work introduces a novel blind deblurring scheme visualized for deblurring images corrupted by arbitrarily shaped PSFs. It is based on Genetic Algorithm (GA) and utilises the Blind/Reference-less Image Spatial QUality Evaluator (BRISQUE) measure as the fitness function for arbitrarily shaped PSF estimation. The proposed BID scheme has been compared with other single image motion deblurring schemes as benchmark. Validation has been carried out on various blurred images. Results of both benchmark and real images are presented. Non-reference image quality measures were used to quantify the deblurring results. For benchmark images, the proposed BID scheme using BRISQUE converges in close vicinity of the original blurring functions.

Keywords: blind deconvolution, blind image deblurring, genetic algorithm, image restoration, image quality measures

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Authors: Umar Hayatu Sidik

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The natural gas vehicle represents a cost-competitive, lower-emission alternative to the gasoline-fuelled vehicle. The immediate challenge that confronts natural gas is increasing its energy density. This paper addresses the question of energy density by reviewing the storage technologies for natural gas with improved adsorbent. Technical comparisons are made between storage systems containing adsorbent and conventional compressed natural gas based on the associated amount of moles contained with Compressed Natural Gas (CNG) and Adsorbed Natural Gas (ANG). We also compare gas storage in different cylinder types (1, 2, 3 and 4) based on weight factor and storage capacity. For the storage tank system, we discussed the concept of carbon adsorbents, when used in CNG tanks, offer a means of increasing onboard fuel storage and, thereby, increase the driving range of the vehicle. It confirms that the density of the stored gas in ANG is higher than that of compressed natural gas (CNG) operated at the same pressure. The obtained experimental data were correlated using linear regression analysis with common adsorption kinetic (Pseudo-first order and Pseudo-second order) and isotherm models (Sip and Toth). The pseudo-second-order kinetics describe the best fitness with a correlation coefficient of 9945 at 35 bar. For adsorption isotherms, the Sip model shows better fitness with the regression coefficient (R2) of 0.9982 and with the lowest RSMD value of 0.0148. The findings revealed the potential of adsorbent in natural gas storage applications.

Keywords: natural gas, adsorbent, compressed natural gas, adsorption

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Authors: Rawa Delshada, Sanaa G. Hamab, Rastee D. Koyeec

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Eighty patients with suspected ischemic heart disease were enrolled in the present study. They were classified into two groups: patients with positive exercise stress test results (n=40) and control group with negative exercise stress test results (n=40). Serum concentration of troponin I, Heart-type Fatty Acid Binding Protein (H-FABP) and Ischemia Modified Albumin (IMA) were measured one hour after performing stress test. Enzyme Linked Immunosorbent Assay was used to measure both troponin I, H-FABP levels, while IMA levels were measured by albumin cobalt binding test. There was no statistically significant difference in the mean concentration of troponin I between two groups (0.75±0.55ng/ml) for patients with positive test result vs. (0.71±0.55ng/ml) for negative test result group with P>0.05. Contrary to our expectation, mean IMA level was slightly higher among control group (70.88±39.76U/ml) compared to (62.7±51.9U/ml) in positive test result group, but still with no statistically significant difference (P>0.05). Median H-FABP level was also higher among negative exercise stress testing group compared the positive one (2ng/ml vs. 1.9ng/ml respectively), but failed to reach statistically significant difference (P>0.05). When quartiles model used to explore the possible association between each study biomarkers with the others; serum H-FABP level was lowest (1.7ng/ml) in highest quartile of IMA and lowest H-FABP (1.8ng/ml) in highest quartile of troponin I but with no statistically significant association (P>0.05). Myocardial ischemia, more likely occurred after exercise stress test, is not capable of causing troponin I release. Furthermore, an increase in H-FABP and IMA levels after stress test are not reflecting myocardial ischemia. Moreover, the combination of troponin I, H-FABP and IMA after measuring their post exercise levels does not improve the diagnostic utility of exercise stress test enormously.

Keywords: cardiac biomarkers, ischemic heart disease, troponin I, ischemia modified albumin, heart-type fatty acid binding protein, exercise stress testing

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Authors: Sabah Mohammed, Jinan Fiaidhi, Darien Sawyer

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Data integration of health through connected services can save lives in the event of a medical emergency or provide efficient and effective interventions for the benefit of the patients through the integration of bedside and bench side clinical research. Such integration will support all wind of change in healthcare by being predictive, pre-emptive, personalized, problem-oriented and participatory. Prototyping a healthcare system that enables data integration has been a big challenge for healthcare for a long time. However, an innovative solution started to emerge by focusing on problem lists where everything can connect the problem list forming a growing graph. This notion was introduced by Dr. Lawrence Weed in early 70’s, but the enabling technologies weren’t mature enough to provide a successful implementation prototype. In this article, we are describing our efforts in prototyping Dr. Lawrence Weed's problem-oriented medical record (POMR) and his patient case schema (SOAP) to shape a prototype for connected health. For this, we are using the TypeGraphQL API and our enterprise-based QL4POMR to describe a Web-Based gateway for healthcare services connectivity. Our prototype has reported success in connecting to the HL7 FHIR medical record and the OpenTarget biomedical repositories.

Keywords: connected health, problem-oriented healthcare record, SOAP, QL4POMR, typegraphQL

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Authors: Irena Alperyte

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Since the regaining of the Independence, the Lithuanian state has been confronting an increasingly dramatic challenge because of the lack of funding sources dedicated to the film industries. During the Soviet times, Lithuanian film was under a total supervision of the Soviet functioners. This means that the responsibility of the state to make movies was of a monopolist character. The filmmakers’ community of the newly independent state needed to learn how to develop their fundraising skills, co-production and marketing techniques. Currently, Lithuanian film is experiencing a new phase concerning its funding: it is exploring the possibilities of motivating the public to invest in entertainment via crowd funding and crowd sourcing techniques and making these activities an alternative way of funding films. The paper aims at the exploration of the existing film financing practices in Lithuania and abroad and provides recommendations on how to improve the alternative Lithuanian film financing strategy via employing new possibilities, such as crowd funding and other alternative marketing tools. Objectives: 1) To examine the theories on creative industries and possibilities for their application. 2) To analyze the current situation in the film industry Lithuania. 3) To analyze the statistical data on movie theater visitors in Lithuania. 4) To discuss alternative options for film financing system. 5) To look through the alternative funding strategies tailored for Lithuanian film industry. 6) To propose recommendations for alternative funding strategies in Lithuanian film fundraising.

Keywords: creative industries, film, funding, fun theory

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Authors: Hossam El-Sayed Emam

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As an essential issue for life, water while it’s important for all living organisms. However, the world is dangerously facing the serious problem for the deficiency of the sources of drinking water. Within the aquatic systems, there are various gases, microbes, and other toxic ingredients (chemical compounds and heavy metals) occurred owing to the draining of agricultural and industrial wastewater, resulting in water pollution. On the other hand, fuel (gaseous, liquid, or in solid phase) is one of the extensively consumable energy sources, and owing to its origin from fossil, it contains some sulfur-, nitrogen- and oxygen-based compounds that cause serious problems (toxicity, catalyst poisoning, corrosion, and gum formation andcarcinogenic effects), to be ascribed as undesirable pollutants.MOFs as porous coordinating polymers are superiorly exploited in the adsorption and separationof contaminants for wastewater treatment and fuel purification. The inclusion of highly adsorbent materials like MOFs to be immobilized within cellulosic materialscould be investigated as a new challenge for the separation of contaminants with high efficiency and opportunity for recyclability. Therefore, the current approach ascribes the exploitation of different MOFsimmobilized within cellulose (powder, films, and fabrics)for applications in environmental. Herein, using cellulose containing MOFs in dye removal (degradation and adsorption), pharmaceutical intermediates removal, and fuel purification were summarized.

Keywords: cellulose, MOFs, dye removal, pharmaceutical intermediates, fuel purification

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Authors: S. A. Che Osmi, W. M. F. Wan Ishak, H. Kim, M. A. Azman, M. A. Ramli

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River is one of important water sources for many activities including industrial and domestic usage such as daily usage, transportation, power supply and recreational activities. However, increasing activities in a river has grown the sources of pollutant enters the water bodies, and degraded the water quality of the river. It becomes a challenge to develop an effective river management to ensure the water sources of the river are well managed and regulated. In Malaysia, several approaches for river management have been implemented such as Integrated River Basin Management (IRBM) program for coordinating the management of resources in a natural environment based on river basin to ensure their sustainability lead by Department of Drainage and Irrigation (DID), Malaysia. Nowadays, Total Maximum Daily Load (TMDL) is one of the best approaches for river management in Malaysia. TMDL implementation is regulated and implemented in the United States. A study on the development of TMDL in Malacca River has been carried out by doing water quality monitoring, the development of water quality model by using Environmental Fluid Dynamic Codes (EFDC), and TMDL implementation plan. The implementation of TMDL will help the stakeholders and regulators to control and improve the water quality of the river. It is one of the good approaches for river management in Malaysia.

Keywords: EFDC, river management, TMDL, water quality modelling

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Authors: Bandar Alahmadi, Manohar Mareboyana, Lethia Jackson

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Today, there are many applications that are using computer vision models, such as face recognition, image classification, and object detection. The accuracy of these models is very important for the performance of these applications. One challenge that facing the computer vision models is the adversarial examples attack. In computer vision, the adversarial example is an image that is intentionally designed to cause the machine learning model to misclassify it. One of very well-known method that is used to attack the Convolution Neural Network (CNN) is Fast Gradient Sign Method (FGSM). The goal of this method is to find the perturbation that can fool the CNN using the gradient of the cost function of CNN. In this paper, we introduce a novel model that can attack Regional-Convolution Neural Network (R-CNN) that use FGSM. We first extract the regions that are detected by R-CNN, and then we resize these regions into the size of regular images. Then, we find the best perturbation of the regions that can fool CNN using FGSM. Next, we add the resulted perturbation to the attacked region to get a new region image that looks similar to the original image to human eyes. Finally, we placed the regions back to the original image and test the R-CNN with the attacked images. Our model could drop the accuracy of the R-CNN when we tested with Pascal VOC 2012 dataset.

Keywords: adversarial examples, attack, computer vision, image processing

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Authors: Faiza Abdul Latip

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One of the ultimate goals of any nation is to produce competitive manpower and this includes Philippines. Inclination in the field of Mathematics has a significant role in achieving this goal. However, Mathematics, as considered by most people, is the most difficult subject matter along with its topics to learn. This could be manifested from the low performance of students in national and international assessments. Educators have been widely using learning style models in identifying the way students learn. Moreover, it could be the frontline in knowing the difficulties held by each learner in a particular topic specifically concepts pertaining to fractions. However, as what many educators observed, students show difficulties in doing mathematical tasks and in great degree in dealing with fractions most specifically in the district of Datu Odin Sinsuat, Maguindanao. This study focused on the Datu Odin Sinsuat district grade six pupils’ learning styles along with their achievements and difficulties in learning concepts on fractions. Five hundred thirty-two pupils from ten different public elementary schools of the Datu Odin Sinsuat districts were purposively used as the respondents of the study. A descriptive research using the survey method was employed in this study. Quantitative analysis on the pupils’ learning styles on the Kolb’s Learning Style Inventory (KLSI) and scores on the mathematics diagnostic test on fraction concepts were made using this method. The simple frequency and percentage counts were used to analyze the pupils’ learning styles and their achievements on fractions. To determine the pupils’ difficulties in fractions, the index of difficulty on every item was determined. Lastly, the Kruskal-Wallis Test was used in determining the significant difference in the pupils’ achievements on fractions classified by their learning styles. This test was set at 0.05 level of significance. The minimum H-Value of 7.82 was used to determine the significance of the test. The results revealed that the pupils of Datu Odin Sinsuat districts learn fractions in varied ways as they are of different learning styles. However, their achievements in fractions are low regardless of their learning styles. Difficulties in learning fractions were found most in the area of Estimation, Comparing/Ordering, and Division Interpretation of Fractions. Most of the pupils find it very difficult to use fraction as a measure, compare or arrange series of fractions and use the concept of fraction as a quotient.

Keywords: difficulties in fraction, fraction, Kolb's model, learning styles

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Authors: Shuofeng Yuan, Bojian Zheng

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Assembly of the heterotrimeric polymerase complex of influenza virus from the individual subunits PB1, PA, and PB2 is a prerequisite for viral replication, in which the interaction between the N-terminal of PB1 (PB1N) and the C terminal of PA (PAC) may be a desired target for antiviral development. In this study, we first compared the feasibility of high throughput screening by enzyme-linked immunosorbent assay (ELISA) and fluorescence polarization (FP) assay. Among the two, ELISA was demonstrated to own broader dynamic range so that it was used for screening inhibitors, which blocked PA and PB1 interaction. Several binding inhibitors of PAC-PB1N were identified and subsequently tested for the antiviral efficacy. Apparently, 3-(2-chlorophenyl)-6-ethyl-7-methyl[1,2,4]triazolo[4,3-a]pyrimidin-5-ol, designated ANA-1, was found to be a strong inhibitor of PAC-PB1N interaction and act as a potent antiviral agent against the infections of multiple subtypes of influenza A virus, including H1N1, H3N2, H5N1, H7N7, H7N9 and H9N2 subtypes, in cell cultures. Intranasal administration of ANA-1 protected mice from lethal challenge and reduced lung viral loads in H1N1 virus infected BALB/c mice. Docking analyses predicted that ANA-1 bound to an allosteric site of PAC, which would cause conformational changes thereby disrupting the PAC-PB1N interaction. Overall, our study has identified a novel compound with potential to be developed as an anti-influenza drug.

Keywords: influenza, antiviral, viral polymerase, compounds

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Authors: Patricia Portugal Marques de Carvalho Lourenço

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Mental Health, mental illnesses, and suicide are old topics made young. While broadly addressed on a global scale to various extents and degrees, mental health, mental disorders, and suicide remain to a large extent a, taboo in a number of societies such as the Chinese. The country’s report on mental health was scrutinized for an in-depth understanding of the prevalence of mental disorders domestically, emphasizing depression, which is more accentuated in rural settings than urban, affecting a significant number of students, retired individuals and that unemployed country-wise. Depression in China is linked to anxiety in younger years, both decreasing as the population grows in age. Mental health, mental disorders and suicide remain for the most part, “forgotten”, despite statistically significant and the media’s yet small efforts in educating the population about the terms i.e. through online/television dramas that approach the topics, trying to demystify them. Whereas crucial to openly address mental health, mental disorders, and suicide, the issues remain an ongoing challenge in China, where series draw light into a reality the media and the population do not broadly converse about. The media in general and the entertainment media, in particular, have a vital role in helping China acknowledge mental health, mental disorders and suicide, albeit having a long way to go in assisting the Chinese population in dealing with the health of their inner minds.

Keywords: mental health, mental disorders, suicide, media, China, Chinese entertainment

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Authors: Osman Yildiz

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As it is predicted 2559 years before there is nothing permanent except change. In our turbulent World, Organizations will always be faced with the challenge of determining the path that will always keep them on balance en route that will bring success. That means from top to bottom, every organisation is exposed to fight to stay afloat and compete while they face the continuous prospect of change in an increasingly competitive and globalized World. Otherwise, they would fail to realize their goals and targets, and ultimately would disappear. But the organizations that will celebrate success five or ten years from now will be the winners of the fight by having recognizing that planning the change was only the first step in the journey and put sufficient efforts into the task of leading change. Increasingly unpredictable and competitive organizational environments have put pressure on leaders across all industries to better manage the change. The key of establishing effective change and transformation in organisations lies on the steps taken before the change happens depending to the quality of the human sources; readiness for change, acknowledgement by management, prepared leaders, motivated employees, overcoming the resistance to change and ultimately adapting change into the organization. Due to these factors, leaders managing the organisational development can ensure organizations and employees to meet new performance targets, motivation and skills rapidly and effectively. Finally, this article will provide some tools for leaders, and discuss how to catch organisational development and manage the innovations in effective ways.

Keywords: managing the change, organizational change, human factor, leaders, globalization, organisational development

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Authors: Angelyn Del Mundo

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Bullying cases are a proliferating issue that schools need to address. This calls for a challenge in providing effective measures to reduce bullying. The study aimed to determine which among the socio-emotional aspects of adolescent males could predict bullying. The respondents of the study were the grades 10 and 11 level and the selection of the respondents was based on the names listed by the teachers and guidance counselors through the Student Nomination Questionnaire. The Bullying Survey Questionnaire Checklist was answered by the respondents to be able to identify their most observed bullying behavior. On the other hand, the level of their mental ability was measured through the use of Otis-Lennon School Ability Test, while their socio-emotional aspects was is classified into 2 contexts: emotional intelligence and personality traits which were determined with the use of Bar-On Emotional Quotient Inventory: Youth Version (BarOn EQ-i:YV) and the Five-Factor Personality Inventory-Children (FFPI-C). Results indicated that majority of the respondents have average level of mental ability and socio-emotional aspects. However, many students have low to markedly low level interpersonal scale. Furthermore, general mood and emotional regulation were found as predictors of bullying behaviors. These findings became the basis for a proposed bullying intervention program.

Keywords: bullying, emotional intelligence, mental ability, personality traits

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Authors: Rudolf Egger

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This paper explores the relationships between the basic learning processes of leading trade union workers and their methods for coping with the changes in the life-courses of societies today. It will discuss the fragile discourse on lifelong learning in trade unions and the “production of self-techniques” to get in touch with the new economic forms. On the basis of an empirical project, different processes of the socialization of leading trade union workers will be analysed to discover the consequences of the lifelong learning discourse. The results show what competences they need to develop for the “wider benefits of negotiations”. The main challenge remains to make visible how deeply intertwined trade union learning and education are with development in an ongoing dynamic economic process, rather than a quick-fix injection of skills and information. There is a complex relationship existing between the three ‘partners’, work, learning and society forming. The author suggests that contemporary trade unions could be trendsetters who make their own learning agendas by drawing less on formal education and more on informal and non-formal learning contexts. This is in parallel with growing political and scientific consciousness of the need to arrive at new educational/vocational policies and practices.

Keywords: trade union workers, educational leadership, learning societies, social acting

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Authors: M. Shemis, O. Maher, G. Casterou, F. Gauffre

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Hepatitis C virus (HCV) is a major cause of chronic liver disease with a global 170 million chronic carriers at risk of developing liver cirrhosis and/or liver cancer. Egypt reports the highest prevalence of HCV worldwide. Currently, two classes of assays are used in the diagnosis and management of HCV infection. Despite the high sensitivity and specificity of the available diagnostic assays, they are time-consuming, labor-intensive, expensive, and require specialized equipment and highly qualified personal. It is therefore important for clinical and economic terms to develop a low-tech assay for the direct detection of HCV RNA with acceptable sensitivity and specificity, short turnaround time, and cost-effectiveness. Such an assay would be critical to control HCV in developing countries with limited resources and high infection rates, such as Egypt. The unique optical and physical properties of gold nanoparticles (AuNPs) have allowed the use of these nanoparticles in developing simple and rapid colorimetric assays for clinical diagnosis offering higher sensitivity and specificity than current detection techniques. The current research aims to develop a detection assay for HCV RNA using gold nanoparticles (AuNPs). Methods: 200 anti-HCV positive samples and 50 anti-HCV negative plasma samples were collected from Egyptian patients. HCV viral load was quantified using m2000rt (Abbott Molecular Inc., Des Plaines, IL). HCV genotypes were determined using multiplex nested RT- PCR. The assay is based on the aggregation of AuNPs in presence of the target RNA. Aggregation of AuNPs causes a color shift from red to blue. AuNPs were synthesized using citrate reduction method. Different sets of probes within the 5’ UTR conserved region of the HCV genome were designed, grafted on AuNPs and optimized for the efficient detection of HCV RNA. Results: The nano-gold assay could colorimetrically detect HCV RNA down to 125 IU/ml with sensitivity and specificity of 91.1% and 93.8% respectively. The turnaround time of the assay is < 30 min. Conclusions: The assay allows sensitive and rapid detection of HCV RNA and represents an inexpensive and simple point-of-care assay for resource-limited settings.

Keywords: HCV, gold nanoparticles, point of care, viral load

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Authors: Shaherah Jordan, Paula Vandergert

Abstract:

The discussion on public charging infrastructure is usually framed around the ‘chicken-egg’ challenge of consumers feeling reluctant to purchase without the necessary infrastructure and policymakers reluctant to invest in the infrastructure without the demand. However, public charging infrastructure may be more crucial to electric vehicle (EV) adoption than previously thought. Historically, access to residential charging was thought to be a major factor in potential for growth in the EV market as it offered a guaranteed place for a vehicle to be charged. The purpose of this study is to understand how the built environment may encourage uptake of EVs by seeking a correlation between EV ownership and public charging points in an urban and densely populated city such as London. Using a statistical approach with data from the Department for Transport and Zap-Map, a statistically significant correlation was found between the total (slow, fast and rapid) number of public charging points and a number of EV registrations per borough – with the strongest correlation found between EV registrations and rapid chargers. This research does not explicitly prove that there is a cause and effect relationship between public charging points EVs but challenges some of the previous literature which indicates that public charging infrastructure is not as important as home charging. Furthermore, the study provides strong evidence that public charging points play a functional and psychological role in the adoption of EVs and supports the notion that the built environment can influence human behaviour.

Keywords: behaviour change, electric vehicles, public charging infrastructure, transportation

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Authors: Hamidreza Saberkari, Mousa Shamsi, Hossein Ahmadi, Saeed Vaali, , MohammadHossein Sedaaghi

Abstract:

In the recent years, using signal processing tools for accurate identification of the protein coding regions has become a challenge in bioinformatics. Most of the genomic signal processing methods is based on the period-3 characteristics of the nucleoids in DNA strands and consequently, spectral analysis is applied to the numerical sequences of DNA to find the location of periodical components. In this paper, a novel ensemble algorithm for gene selection in DNA sequences has been presented which is based on the combination of Goertzel algorithm and anti-notch filter (ANF). The proposed algorithm has many advantages when compared to other conventional methods. Firstly, it leads to identify the coding protein regions more accurate due to using the Goertzel algorithm which is tuned at the desired frequency. Secondly, faster detection time is achieved. The proposed algorithm is applied on several genes, including genes available in databases BG570 and HMR195 and their results are compared to other methods based on the nucleotide level evaluation criteria. Implementation results show the excellent performance of the proposed algorithm in identifying protein coding regions, specifically in identification of small-scale gene areas.

Keywords: protein coding regions, period-3, anti-notch filter, Goertzel algorithm

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Authors: Chenyu Huang, Minrong Cui, Hua Fang, Luqing Zhang, Yunlong Yu

Abstract:

The emergence and spread of antibiotic resistance genes (ARGs) have become a pressing issue in global agricultural production. However, understanding how these ARGs spread across different spatial scales, especially when exposed to both pesticides and antibiotics, has remained a challenge. Here, metagenomic assembly and binning methodologies were used to determine the mechanism of ARG propagation within soil-lettuce systems exposed to both fungicides and antibiotics. The results of our study showed that the presence of fungicide and antibiotic stresses had a significant impact on certain bacterial communities. Notably, we observed that ARGs were primarily transferred from the soil to the plant through plasmids. The selective pressure exerted by fungicides and antibiotics contributed to an increase in unique ARGs present on lettuce leaves. Moreover, ARGs located on chromosomes and plasmids followed different transmission patterns. The presence of diverse selective pressures, a result of compound treatments involving antibiotics and fungicides, amplifies this phenomenon. Consequently, there is a higher probability of bacteria developing multi-antibiotic resistance under the combined pressure of fungicides and antibiotics. In summary, our findings highlight that combined fungicide and antibiotic treatments are more likely to drive the acquisition of ARGs within the soil-plant system and may increase the risk of human ingestion.

Keywords: soil-lettuce system, fungicide, antibiotic, ARG, transmission

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Authors: Bipasha Sen, Aditya Agarwal

Abstract:

Multilingual automatic speech recognition (ASR) system is a single entity capable of transcribing multiple languages sharing a common phone space. Performance of such a system is highly dependent on the compatibility of the languages. State of the art speech recognition systems are built using sequential architectures based on recurrent neural networks (RNN) limiting the computational parallelization in training. This poses a significant challenge in terms of time taken to bootstrap and validate the compatibility of multiple languages for building a robust multilingual system. Complex architectural choices based on self-attention networks are made to improve the parallelization thereby reducing the training time. In this work, we propose Reed, a simple system based on 1D convolutions which uses very short context to improve the training time. To improve the performance of our system, we use raw time-domain speech signals directly as input. This enables the convolutional layers to learn feature representations rather than relying on handcrafted features such as MFCC. We report improvement on training and inference times by atleast a factor of 4x and 7.4x respectively with comparable WERs against standard RNN based baseline systems on SpeechOcean's multilingual low resource dataset.

Keywords: convolutional neural networks, language compatibility, low resource languages, multilingual automatic speech recognition

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Authors: Madhumita Sahu, S. S. Tiwary

Abstract:

The Radiotherapy of Carcinoma Lung has always been difficult and a matter of great concern. The significant movement due to fractional motion caused due to non-rhythmic respiratory motion poses a great challenge for the treatment of Lung cancer using Ionizing Radiation. The present study compares the accuracy in the measurement of Target Volume using Slow-CT and 4DCT Imaging in SBRT for Lung Tumor. The experimental samples were extracted from patients with Lung Cancer who underwent SBRT. Slow-CT and 4DCT images were acquired under free breathing for each patient. PTV were delineated on Slow CT images. Similarly, ITV was also delineated on each of the 4DCT volumes. Volumetric and Statistical analysis were performed for each patient by measuring corresponding PTV and ITV volumes. The study showed (1) The Maximum Deviation observed between Slow-CT-based PTV and 4DCT imaging-based ITV is 248.58 cc. (2) The Minimum Deviation observed between Slow-CT-based PTV and 4DCT imaging-based ITV is 5.22 cc. (3) The Mean Deviation observed between Slow-CT-based PTV and 4DCT imaging-based ITV is 63.21 cc. The present study concludes that irradiated volume ITV with 4DCT is less as compared to the PTV with Slow-CT. A better and more precise treatment could be given more accurately with 4DCT Imaging by sparing 63.21 CC of mean body volume.

Keywords: CT imaging, 4DCT imaging, lung cancer, statistical analysis

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Authors: Ayadi Aya, Ghorbel Oussama, M. Obeid Abdulfattah, Abid Mohamed

Abstract:

Nowadays, many wireless sensor networks have been distributed in the real world to collect valuable raw sensed data. The challenge is to extract high-level knowledge from this huge amount of data. However, the identification of outliers can lead to the discovery of useful and meaningful knowledge. In the field of wireless sensor networks, an outlier is defined as a measurement that deviates from the normal behavior of sensed data. Many detection techniques of outliers in WSNs have been extensively studied in the past decade and have focused on classic based algorithms. These techniques identify outlier in the real transaction dataset. This survey aims at providing a structured and comprehensive overview of the existing researches on classification based outlier detection techniques as applicable to WSNs. Thus, we have identified key hypotheses, which are used by these approaches to differentiate between normal and outlier behavior. In addition, this paper tries to provide an easier and a succinct understanding of the classification based techniques. Furthermore, we identified the advantages and disadvantages of different classification based techniques and we presented a comparative guide with useful paradigms for promoting outliers detection research in various WSN applications and suggested further opportunities for future research.

Keywords: bayesian networks, classification-based approaches, KPCA, neural networks, one-class SVM, outlier detection, wireless sensor networks

Procedia PDF Downloads 496