Search results for: team effectiveness

Authors: V. I. Kozyavkin, L. F. Shestopalova, T. B. Voloshyn

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Introduction: Rehabilitation of children with Autism is the issue of the day in psychiatry and neurology. It is attributed to constantly increasing quantity of autistic children - Autistic Spectrum Disorders (ASD) Existing rehabilitation approaches in treatment of children with Autism improve their medico- social and social- psychological adjustment. Experience of treatment for different kinds of Autistic disorders in International Clinic of Rehabilitation (ICR) reveals the necessity of complex intensive approach for healing this malady and wider implementation of a Kozyavkin method for treatment of children with ASD. Methods: 19 children aged from 3 to 14 years were examined. They were diagnosed ‘Autism’ (F84.0) with comorbid neurological pathology (from pyramidal insufficiency to para- and tetraplegia). All patients underwent rehabilitation in ICR during two weeks, where INRS approach was used. INRS included methods like biomechanical correction of the spine, massage, physical therapy, joint mobilization, wax-paraffin applications. They were supplemented by art- therapy, ergotherapy, rhythmical group exercises, computer game therapy, team Olympic games and other methods for improvement of motivation and social integration of the child. Estimation of efficacy was conducted using parent’s questioning and done twice- on the onset of INRS rehabilitation course and two weeks afterward. For efficacy assessment of rehabilitation of autistic children in ICR standardized tool was used, namely Autism Treatment Evaluation Checklist (ATEC). This scale was selected because any rehabilitation approaches for the child with Autism can be assessed using it. Results: Before the onset of INRS treatment mean score according to ATEC scale was 64,75±9,23, it reveals occurrence in examined children severe communication, speech, socialization and behavioral impairments. After the end of the rehabilitation course, the mean score was 56,5±6,7, what indicates positive dynamics in comparison to the onset of rehabilitation. Generally, improvement of psychoemotional state occurred in 90% of cases. Most significant changes occurred in the scope of speech (16,5 before and 14,5 after the treatment), socialization (15.1 before and 12,5 after) and behavior (20,1 before and 17.4 after). Conclusion: As a result of INRS rehabilitation course reduction of autistic symptoms was noted. Particularly improvements in speech were observed (children began to spell out new syllables, words), there was some decrease in signs of destructiveness, quality of contact with the surrounding people improved, new skills of self-service appeared. The prospect of the study is further, according to evidence- based medicine standards, deeper examination of INRS and assessment of its usefulness in treatment for Autism and ASD.

Keywords: intensive neurophysiological rehabilitation system (INRS), international clinic od rehabilitation, ASD, rehabilitation

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Authors: Abdulkabir Abdullahi

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Nigeria has not yet welcomed phonics into its primary schools. In government-owned primary schools teachers are functionally ignorant of the stories of the reading wars amongst international scholars. There are few or no Nigerian-authored phonics textbooks, and there has been no government-owned phonics curriculum either. There are few or no academic journal articles on phonics in the country and there is, in fact, a certain danger of confusion between phonics and phonetics among Nigerian publishers, authors, writers and academics as if Nigerian teachers of English and the educational policy makers of the country were unaware of reading failures/problems amongst Nigerian children, or had never heard of phonics or read of the stories of the reading wars or the annual phonics test in the United Kingdom, the United States of America and other parts of the world. It is on this note that this article reviews and examines, in the style of a qualitative inquiry, the body of arguments on phonics, and explores the effectiveness of phonics teaching, particularly, in a second-language learning contexts. While the merit of the paper is, perhaps, situated in its supreme effort to draw global attention to reading failures/problems in Nigeria and the ways the situation may affect English language learning, international academic relations and the educational future of the country, it leaves any quantitative verification of its claims to interested quantitative researchers in the world.

Keywords: graphemes, phonics, reading, reading wars, reading theories, phonemic awareness

Procedia PDF Downloads 233

Authors: Glenn Auld Knierim

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Automated robotic winding of high-temperature superconductors (HTS) addresses precision, efficiency, and reliability critical to the commercialization of products. Today’s HTS materials are mature and commercially promising but require manufacturing attention. In particular to the exaggerated rectangular cross-section (very thin by very wide), winding precision is critical to address the stress that can crack the fragile ceramic superconductor (SC) layer and destroy the SC properties. Damage potential is highest during peak operations, where winding stress magnifies operational stress. Another challenge is operational parameters such as magnetic field alignment affecting design performance. Winding process performance, including precision, capability for geometric complexity, and efficient repeatability, are required for commercial production of current HTS. Due to winding limitations, current HTS magnets focus on simple pancake configurations. HTS motors, generators, MRI/NMR, fusion, and other projects are awaiting robotic wound solenoid, planar, and spherical magnet configurations. As with conventional power cables, full transposition winding is required for long length alternating current (AC) and pulsed power cables. Robotic production is required for transposition, periodic swapping of cable conductors, and placing into precise positions, which allows power utility required minimized reactance. A full transposition SC cable, in theory, has no transmission length limits for AC and variable transient operation due to no resistance (a problem with conventional cables), negligible reactance (a problem for helical wound HTS cables), and no long length manufacturing issues (a problem with both stamped and twisted stacked HTS cables). The Infinity Physics team is solving manufacturing problems by developing automated manufacturing to produce the first-ever reliable and utility-grade commercial SC cables and magnets. Robotic winding machines combine mechanical and process design, specialized sense and observer, and state-of-the-art optimization and control sequencing to carefully manipulate individual fragile SCs, especially HTS, to shape previously unattainable, complex geometries with electrical geometry equivalent to commercially available conventional conductor devices.

Keywords: automated winding manufacturing, high temperature superconductor, magnet, power cable

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Authors: M. Dimitri, M. Ricci, F. Bigi, M. Romiti, A. Corvi

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Tissue engineering has reached a significant milestone with the integration of 3D printing for the creation of complex bioconstructs equipped with vascular networks, crucial for cell maintenance and growth. This study aims to demonstrate the effectiveness of a portable microperfusion system designed to adapt dynamically to the evolving conditions of cell growth within 3D-printed bioconstructs. The microperfusion system was developed to provide a constant and controlled flow of nutrients and oxygen through the integrated vessels in the bioconstruct, replicating in vivo physiological conditions. Through a series of preliminary experiments, we evaluated the system's ability to maintain a favorable environment for cell proliferation and differentiation. Measurements of cell density and viability were performed to monitor the health and functionality of the tissue over time. Preliminary results indicate that the portable microperfusion system not only supports but optimizes cell growth, effectively adapting to changes in metabolic needs during the bioconstruct maturation process. This research opens perspectives in tissue engineering, demonstrating that a portable microperfusion system can be successfully integrated into 3D-printed bioconstructs, promoting sustainable and uniform cell growth. The implications of this study are far-reaching, with potential applications in regenerative medicine and pharmacological research, providing a platform for the development of functional and complex tissues.

Keywords: biofabrication, microfluidic perfusion system, 4D bioprinting

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Authors: Dong Jiang

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Turnout is the essential equipment on the railway, which also belongs to one of the strongest demanded infrastructural facilities of railway on account of the more seriously frog rail failures. In cooperation with Germany Company (DB Systemtechnik AG), our research team focuses on the quantitative analysis about the frog rails to predict their lifetimes. Moreover, the suggestions for the timely and effective maintenances are made to improve the economy of the frog rails. The lifetime of the frog rail depends strongly on the internal damage of the running surface until the breakages occur. On the basis of Hertzian theory of the contact mechanics, the dynamic loads of the running surface are calculated in form of the contact pressures on the running surface and the equivalent tensile stress inside the running surface. According to material mechanics, the strength of the frog rail is determined quantitatively in form of the Stress-cycle (S-N) curve. Under the interaction between the dynamic loads and the strength, the internal damage of the running surface is calculated by means of the linear damage hypothesis of the Miner’s rule. The emergence of the first Breakage on the running surface is to be defined as the failure criterion that the damage degree equals 1.0. From the microscopic perspective, the running surface of the frog rail is divided into numerous segments for the detailed analysis. The internal damage of the segment grows slowly in the beginning and disproportionately quickly in the end until the emergence of the breakage. From the macroscopic perspective, the internal damage of the running surface develops simply always linear along the lifetime. With this linear growth of the internal damages, the lifetime of the frog rail could be predicted simply through the immediate introduction of the slope of the linearity. However, the superficial abrasion plays an essential role in the results of the internal damages from the both perspectives. The influences of the superficial abrasion on the lifetime are described in form of the abrasion rate. It has two contradictory effects. On the one hand, the insufficient abrasion rate causes the concentration of the damage accumulation on the same position below the running surface to accelerate the rail failure. On the other hand, the excessive abrasion rate advances the disappearance of the head hardened surface of the frog rail to result in the untimely breakage on the surface. Thus, the relationship between the abrasion rate and the lifetime is subdivided into an initial phase of the increased lifetime and a subsequent phase of the more rapid decreasing lifetime with the continuous growth of the abrasion rate. Through the compensation of these two effects, the critical abrasion rate is discussed to reach the optimal lifetime.

Keywords: breakage, critical abrasion rate, frog rail, internal damage, optimal lifetime

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Authors: Amine Ez-Zoubi, Abdellah Farah

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Because of their effectiveness and environmental safety, many essential oils have been investigated as biopesticides. Nevertheless, the encapsulation process is necessary to improve its physical, chemical, and biological properties. Therefore, the purpose of this paper was to study the physicochemical characteristics, and antifungal activity of the Artemisia Herba-Alba essential oil (HAEO) encapsulated in succinic acid modified β-CD (SACD). A yellowish oil was obtained from plant A. Herba-Alba using hydrodistillation and GC-MS was used to identify the chemical composition, in which α-Thujone (65.0%) was the main component in HAEO. The succinic acid has been esterified via the hydroxyl groups in β-CD to produce SACD. In addition, the inclusion complex formation of HAEO and SACD was generated according to the co-precipitation method and was analyzed by several techniques. The antifungal activity in vitro was examined against Botrytis cinerea by direct contact with a potato dextrose agar culture medium. At a 0.1 % concentration, the HAEO in encapsulated form showed higher potential for the control of B. cinerea when compared to the EO in free form (38.34 to 12%). Thus, these results produced evidence that the encapsulation of EOs in SACD can be useful for the development of B.cinerea inhibitors and a promising alternative biopesticide.

Keywords: Artemisia Herba-Alba essential oil, succinic acid modified β-cyclodextrin, inclusion complex, co-precipitation, Botrytis cinerea, direct contact

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Authors: Yooseo Pang, Jongwoong Choi, Yong Cho, Yongchae Jeong

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Climate crisis, such as environmental problems related to energy supply, is getting emerged issues, so the use of renewable energy is essentially required to solve these problems, which are mainly managed by the Paris Agreement, the international treaty on climate change. The government of the Republic of Korea announced that the key long-term goal for a low-carbon strategy is “Carbon neutrality by 2050”. It is focused on the role of the internet data centers (IDC) in which large amounts of data, such as artificial intelligence (AI) and big data as an impact of the 4th industrial revolution, are managed. The demand for the cooling system market for IDC was about 9 billion US dollars in 2020, and 15.6% growth a year is expected in Korea. It is important to control the temperature in IDC with an efficient air conditioning system, so hydrothermal energy is one of the best options for saving energy in the cooling system. In order to save energy and optimize the operating conditions, it has been considered to apply ‘the dam deep water air conditioning system. Deep water at a specific level from the dam can supply constant water temperature year-round. It will be tested & analyzed the amount of energy saving with a pilot plant that has 100RT cooling capacity. Also, a target of this project is 1.2 PUE (Power Usage Effectiveness) which is the key parameter to check the efficiency of the cooling system.

Keywords: hydrothermal energy, HVAC, internet data center, free-cooling

Procedia PDF Downloads 81

Authors: Lisa Bennett, Cynthia Walters, Cynthia Argani, Andy Satin, Geeta Sood, Kerri Huber, Lisa Grubb, Woodrow Noble, Melissa Eichelberger, Darlene Zinalabedini, Eric Ausby, Jeffrey Snyder, Kevin Kirchoff

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Background: Surgical site infections (SSIs) within the obstetric population pose a variety of complications, creating clinical and personal challenges for the new mother and her neonate during the postpartum period. Our journey to achieve compliance with the SSI core measure for cesarean sections revealed many opportunities to improve these outcomes. Objective: Achieve and sustain core measure compliance keeping surgical site infection rates below the national benchmark pooled mean of 1.8% in post-operative patients, who delivered via cesarean section at the Johns Hopkins Bayview Medical Center. Methods: A root cause analysis was performed and revealed several environmental, pharmacologic, and clinical practice opportunities for improvement. A multidisciplinary approach led by the OB Safety Nurse, OB Medical Director, and Infectious Disease Department resulted in the implementation of fourteen interventions over a twenty-month period. Interventions included: post-operative dressing changes, standardizing operating room attire, broadening pre-operative antibiotics, initiating vaginal preps, improving operating room terminal cleaning, testing air quality, and re-educating scrub technicians on technique. Results: Prior to the implementation of our interventions, the SSI quarterly rate in Obstetrics peaked at 6.10%. Although no single intervention resulted in dramatic improvement, after implementation of all fourteen interventions, the quarterly SSI rate has subsequently ranged from to 0.0% to 2.70%. Significance: Taking an introspective look at current practices can reveal opportunities for improvement which previously were not considered. Collectively the benefit of these interventions has shown a significant decrease in surgical site infection rates. The impact of this quality improvement project highlights the synergy created when members of the multidisciplinary team work in collaboration to improve patient safety, and achieve a high quality of care.

Keywords: cesarean section, surgical site infection, collaboration and teamwork, patient safety, quality improvement

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Authors: S. Assylbekova, D. Zolotareva, A. Dauletbakov, Ye. Belyankova, S. Bayazit, A. Basharimova, A. Zazybin, A. Isimberlenova, A. Kakimova, M. Aydemir, A. Kairullinova

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Transfer hydrogenation (TH) is a key process in organic chemistry, especially in pharmaceutical and agrochemical synthesis, offering a safer and more sustainable approach compared to traditional methods. This work is devoted to the synthesis and use of ruthenium catalysts containing phosphinite ligands in TH reactions. Ruthenium complexes are particularly noteworthy for their effectiveness in asymmetric TH. Their stability and adaptability to different reaction environments make them ideal for both laboratory-scale and industrial applications. Phosphinite ligands (P(OR)R'2) are used in the synthesis of complexes to improve their properties. These ligands are known for their ability to finely tune the electronic and steric properties of metal centers. The electron-donating nature of the phosphorus atom, combined with the variability in the R and R' groups, allows for significant customization of the catalyst's properties. The purpose and difference of the work is to study the incorporation of a hydrophilic ionic liquid into the composition of a phosphinite ligand, which will then be converted into a catalyst. The technique involves the synthesis of a phosphinite ligand with an ionic liquid at room temperature under an inert atmosphere and then a ruthenium complex. Next, the TH reactions of acetophenone and its derivatives are carried out using the resulting catalyst. The conversion of ketone to alcohol is analyzed using a gas chromatograph. This study contributes to the understanding of the influence of catalyst physico-chemical properties on transfer hydrogenation results.

Keywords: transfer hydrogenation, ruthenium, catalysts, phosphinite ligands

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Authors: Muhammad Mazhar, Yong Zhu, Likang Qin

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Foods contain endogenous components known as dietary fibers, which are classified into soluble and insoluble forms. Dietary fibers are resistant to gut digestive enzymes, modulating anaerobic intestinal microbiota (AIM) and fabricating short-chain fatty acids (SCFAs). Acetate, butyrate, and propionate dominate in the gut, and different pathways, including Wood-Ljungdahl and acrylate pathways, generate these SCFAs. In pancreatic dysfunction, the release of insulin/glucagon is impaired, which leads to hyperglycemia. SCFAs enhance insulin sensitivity or secretion, beta-cell functions, leptin release, mitochondrial functions, and intestinal gluconeogenesis in human organs, which positively affect type 2 diabetes (T2D). Research models presented that SCFAs either enhance the release of peptide YY (PYY) and glucagon-like peptide-1 (GLP-1) from L-cells (entero-endocrine) or promote the release of leptin hormone satiation in adipose tissues through G-protein receptors, i.e., GPR-41/GPR-43. Dietary fibers are the components of foods that influence AIM and produce SCFAs, which may be offering beneficial effects on T2D. This review addresses the effectiveness of SCFAs in modulating gut AIM in the fermentation of dietary fiber and their worth against T2D.

Keywords: dietary fibers, intestinal microbiota, short-chain fatty acids, fermentation, type 2 diabetes

Procedia PDF Downloads 73

Authors: Hui Fang Huang Su, Jia Borror

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This study compared two interventions for teaching math to preschool-aged students with autism spectrum disorder (ASD). The first is considered the business as usual (BAU) intervention, which uses the Strategies for Teaching Based on Autism Research (STAR) curriculum and discrete trial teaching as the instructional methodology. The second is the Math is Not Difficult (Project MIND) activity-embedded, naturalistic intervention. These interventions were randomly assigned to four preschool students with ASD classrooms and implemented over three months for Project Mind. We used measurement gained during the same three months for the STAR intervention. In addition, we used A quasi-experimental, pre-test/post-test design to compare the effectiveness of these two interventions in building mathematical knowledge and skills. The pre-post measures include three standardized instruments: the Test of Early Math Ability-3, the Problem Solving and Calculation subtests of the Woodcock-Johnson Test of Achievement IV, and the Bracken Test of Basic Concepts-3 Receptive. The STAR curriculum-based assessment is administered to all Baudhuin students three times per year, and we used the results in this study. We anticipated that implementing these two approaches would improve the mathematical knowledge and skills of children with ASD. Still, it is crucial to see whether a behavioral or naturalistic teaching approach leads to more significant results.

Keywords: early learning, autism, math for pre-schoolers, special education, teaching strategies

Procedia PDF Downloads 165

Authors: Bowei Yuan, Shi Li, Liuyang Song, Huaqing Wang, Lingli Cui

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Convolutional neural networks (CNN) have received extensive attention in the field of fault diagnosis. Many fault diagnosis methods use CNN for fault type identification. However, when the amount of raw data collected by sensors is massive, the neural network needs to perform a time-consuming classification task. In this paper, a mechanical fault diagnosis method based on vibration signal down-sampling and the improved one-dimensional convolutional neural network is proposed. Through the robust principal component analysis, the low-rank feature matrix of a large amount of raw data can be separated, and then down-sampling is realized to reduce the subsequent calculation amount. In the improved one-dimensional CNN, a smaller convolution kernel is used to reduce the number of parameters and computational complexity, and regularization is introduced before the fully connected layer to prevent overfitting. In addition, the multi-connected layers can better generalize classification results without cumbersome parameter adjustments. The effectiveness of the method is verified by monitoring the signal of the centrifugal pump test bench, and the average test accuracy is above 98%. When compared with the traditional deep belief network (DBN) and support vector machine (SVM) methods, this method has better performance.

Keywords: fault diagnosis, vibration signal down-sampling, 1D-CNN

Procedia PDF Downloads 131

Authors: S. Valarmathi, P. B. Harathi, R. Sridhar, S. Balasubramanian

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Machine learning tools in medical diagnosis is increasing due to the improved effectiveness of classification and recognition systems to help medical experts in diagnosing breast cancer. In this study, ID3 chooses the splitting attribute with the highest gain in information, where gain is defined as the difference between before the split versus after the split. It is applied for age, location, taluk, stage, year, period, martial status, treatment, heredity, sex, and habitat against Very Serious (VS), Very Serious Moderate (VSM), Serious (S) and Not Serious (NS) to calculate the gain of information. The ranked histogram gives the gain of each field for the breast cancer data. The doctors use TNM staging which will decide the risk level of the breast cancer and play an important decision making field in fuzzy logic for perception based measurement. Spatial risk area (taluk) of the breast cancer is calculated. Result clearly states that Coimbatore (North and South) was found to be risk region to the breast cancer than other areas at 20% criteria. Weighted value of taluk was compared with criterion value and integrated with Map Object to visualize the results. ID3 algorithm shows the high breast cancer risk regions in the study area. The study has outlined, discussed and resolved the algorithms, techniques / methods adopted through soft computing methodology like ID3 algorithm for prognostic decision making in the seriousness of the breast cancer.

Keywords: ID3 algorithm, breast cancer, fuzzy logic, MATLAB

Procedia PDF Downloads 519

Authors: Bolin Hua

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In city governance, various data are involved, including city component data, demographic data, housing data and all kinds of business data. These data reflects different aspects of people, events and activities. Data generated from various systems are different in form and data source are different because they may come from different sectors. In order to reflect one or several facets of an event or rule, data from multiple sources need fusion together. Data from different sources using different ways of collection raised several issues which need to be resolved. Problem of data fusion include data update and synchronization, data exchange and sharing, file parsing and entry, duplicate data and its comparison, resource catalogue construction. Governments adopt statistical analysis, time series analysis, extrapolation, monitoring analysis, value mining, scenario prediction in order to achieve pattern discovery, law verification, root cause analysis and public opinion monitoring. The result of Multi-source data fusion is to form a uniform central database, which includes people data, location data, object data, and institution data, business data and space data. We need to use meta data to be referred to and read when application needs to access, manipulate and display the data. A uniform meta data management ensures effectiveness and consistency of data in the process of data exchange, data modeling, data cleansing, data loading, data storing, data analysis, data search and data delivery.

Keywords: multi-source data fusion, urban comprehensive management, information fusion, government data

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Authors: W. E. Igwegbe, B. C. Okoro, J. C. Osuagwu

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The study was aimed at assessing the effectiveness of reducing the concentrations of heavy metals in waste water using Pawpaw (Carica papaya) wood as a bio-sorbent. The heavy metals considered include; zinc, cadmium, lead, copper, iron, selenium, nickel, and manganese. The physiochemical properties of carica papaya stem were studied. The experimental sample was obtained from a felled trunk of matured pawpaw tree. Waste water for experimental use was prepared by dissolving soil samples collected from a dump site at Owerri, Imo state in water. The concentration of each metal remaining in solution as residual metal after bio-sorption was determined using Atomic absorption Spectrometer. The effects of ph, contact time and initial heavy metal concentration were studied in a batch reactor. The results of Spectrometer test showed that there were different functional groups detected in the carica papaya stem biomass. Optimum bio-sorption occurred at pH 5.9 with 5g/100ml solution of bio-sorbent. The results of the study showed that the treated wastewater is fit for irrigation purpose based on Canada wastewater quality guideline for the protection of Agricultural standard. This approach thus provides a cost effective and environmentally friendly option for treating waste water.

Keywords: biomass, bio-sorption, Carica papaya, heavy metal, wastewater

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Authors: Eiman Kattan

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This study aims to evaluate the impact of classifying labelled remote sensing images conventional neural network (CNN) architecture, i.e., AlexNet on different land cover scenarios based on two remotely sensed datasets from different point of views such as the computational time and performance. Thus, a set of experiments were conducted to specify the effectiveness of the selected convolutional neural network using two implementing approaches, named fully trained and fine-tuned. For validation purposes, two remote sensing datasets, AID, and RSSCN7 which are publicly available and have different land covers features were used in the experiments. These datasets have a wide diversity of input data, number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in training, validation, and testing. As a result, the fully trained approach has achieved a trivial result for both of the two data sets, AID and RSSCN7 by 73.346% and 71.857% within 24 min, 1 sec and 8 min, 3 sec respectively. However, dramatic improvement of the classification performance using the fine-tuning approach has been recorded by 92.5% and 91% respectively within 24min, 44 secs and 8 min 41 sec respectively. The represented conclusion opens the opportunities for a better classification performance in various applications such as agriculture and crops remote sensing.

Keywords: conventional neural network, remote sensing, land cover, land use

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Authors: S. El Hasini, M. El Azzouzi, M. De Nobili, K. Azim, A. Zouahri

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Soil salinization is one of the most severe environmental hazards which threaten sustainable agriculture in arid and semi-arid regions, including Morocco. In this regard the application of organic matter to saline soil has confirmed its effectiveness. The present study was aimed to examine the effect of humic acid which represent, among others, the important component of organic matter that contributes to reduce soil salinity. In fact, different composts taken from Agadir (Morocco), with different C/N ratio, were tested. After extraction and purification of humic acid, the interaction with Na2CO3 was carried out. The reduction of salinity is calculated as a value expressed in mg Na2CO3 equivalent/g HA. The results showed that humic acid had generally a significant effect on salinity. In that respect, the hypothesis proposed that carboxylic groups of humic acid create bonds with excess sodium in the soil to form a coherent complex which descends by leaching operation. The comparison between composts was based on C/N ratio, it showed that the compost with the lower ratio C/N had the most important effect on salinity reduction, whereas the compost with higher C/N ratio was less effective. The study is attended also to evaluate the quality of each compost by determining the humification index, we noticed that the compost which have the lowest C/N (20) ratio was relatively less stable, where a greater predominance of the humified substances, when the compost with C/N ratio is 35 exhibited higher stability.

Keywords: compost, humic acid, organic matter, salinity

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Authors: Sai Hung Cheung, Zhe Shao

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Recent earthquake-induced tsunamis in Padang, 2004 and Tohoku, 2011 brought huge losses of lives and properties. Maintaining vertical evacuation systems is the most crucial strategy to effectively reduce casualty during the tsunami event. Thus, it is of our great interest to quantify the risk to structural dynamic systems due to earthquake-induced tsunamis. Despite continuous advancement in computational simulation of the tsunami and wave-structure interaction modeling, it still remains computationally challenging to evaluate the reliability (or its complement failure probability) of a structural dynamic system when uncertainties related to the system and its modeling are taken into account. The failure of the structure in a tsunami-wave-structural system is defined as any response quantities of the system exceeding specified thresholds during the time when the structure is subjected to dynamic wave impact due to earthquake-induced tsunamis. In this paper, an approach based on a novel integration of the Subset Simulation algorithm and a recently proposed moving least squares response surface approach for stochastic sampling is proposed. The effectiveness of the proposed approach is discussed by comparing its results with those obtained from the Subset Simulation algorithm without using the response surface approach.

Keywords: response surface model, subset simulation, structural reliability, Tsunami risk

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Authors: Heri Suryoatmojo, Adi Kurniawan, Feby A. Pamuji, Nursalim, Syaffaruddin, Herbert Innah

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Photovoltaic (PV) system hybrid with diesel system is utilized widely for electrification in remote area. PV output power fluctuates due to uncertainty condition of temperature and sun irradiance. When the penetration of PV power is large, the reliability of the power utility will be disturbed and seriously impact the unstable frequency of system. Therefore, designing a robust frequency controller in PV-diesel hybrid power system is very important. This paper proposes new method of frequency control application in hybrid PV-diesel system based on artificial neural network (ANN). This method can minimize the frequency deviation without smoothing PV output power that controlled by maximum power point tracking (MPPT) method. The neural network algorithm controller considers average irradiance, change of irradiance and frequency deviation. In order the show the effectiveness of proposed algorithm, the addition of battery as energy storage system is also presented. To validate the proposed method, the results of proposed system are compared with the results of similar system using MPPT only. The simulation results show that the proposed method able to suppress frequency deviation smaller compared to the results of system using MPPT only.

Keywords: energy storage system, frequency deviation, hybrid power generation, neural network algorithm

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Authors: Taghreed Al-Khalid, Muftah El-Naas

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As an economical and environmentally friendly technology, biological treatment has been shown to be one of the most promising approaches for the removal of numerous types of organic water pollutants such as Chlorophenols, which are hazardous pollutants commonly encountered in wastewater generated by the petroleum and petrochemical industries. This study aimed at evaluating the performance of a spouted bed bioreactor (SBBR) for aerobic biodegradation of 2, 4 dichlorophenol (DCP) by a commercial strain of Pseudomonas putida immobilized in polyvinyl alcohol (PVA) gel particles. The SBBR is characterized by systematic intense mixing, resulting in improvement of the biodegradation rates through reducing the mass transfer limitations. The reactor was evaluated in both batch and continuous mode in order to evaluate its hydrodynamics in terms of stability and response to shock loads. The SBBR was able to maintain a stable operation and recovered quickly to its normal operating mode once the shock load had been removed. In comparison to a packed bed reactor bioreactor, the SBBR proved to be more efficient and more stable, achieving a removal percentage and throughput of 80% and 1414 g/m3day, respectively. In addition, the biodegradation of chlorophenols was mathematically modeled using a dynamic modeling approach in order to assess reaction and mass transfer limitations. The results confirmed the effectiveness of the use of the PVA immobilization technique for the biodegradation of phenols.

Keywords: biodegradation, 2, 4 dichlorophenol, immobilization, polyvinyl alcohol (PVA) gel

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Authors: Ganesh B. Shinde, Vijaya B. Musande

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Cotton crop identification based on the timely information has significant advantage to the different implications of food, economic and environment. Due to the significant advantages, the accurate detection of cotton crop regions using supervised learning procedure is challenging problem in remote sensing. Here, classifiers on the direct image are played a major role but the results are not much satisfactorily. In order to further improve the effectiveness, variety of vegetation indices are proposed in the literature. But, recently, the major challenge is to find the better vegetation indices for the cotton crop identification through the proposed methodology. Accordingly, fuzzy c-means clustering is combined with neural network algorithm, trained by Levenberg-Marquardt for cotton crop classification. To experiment the proposed method, five LISS-III satellite images was taken and the experimentation was done with six vegetation indices such as Simple Ratio, Normalized Difference Vegetation Index, Enhanced Vegetation Index, Green Atmospherically Resistant Vegetation Index, Wide-Dynamic Range Vegetation Index, Green Chlorophyll Index. Along with these indices, Green Leaf Area Index is also considered for investigation. From the research outcome, Green Atmospherically Resistant Vegetation Index outperformed with all other indices by reaching the average accuracy value of 95.21%.

Keywords: Fuzzy C-Means clustering (FCM), neural network, Levenberg-Marquardt (LM) algorithm, vegetation indices

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Authors: Fuyuan Ma, Ying Wang, Xin Wang

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Social networks have become breeding grounds for the rapid spread of rumors and malicious information, posing threats to societal stability and causing significant public harm. Existing research focuses on simulating the spread of information and its impact on users through propagation dynamics and applies methods such as greedy approximation strategies to approximate the optimal control solution at the global scale. However, the greedy strategy at the global scale may fall into locally optimal solutions, and the approximate simulation of information spread may accumulate more errors. Therefore, we propose a multi-scale control model for network group behavior, introducing individual and group scales on top of the greedy strategy’s global scale. At the individual scale, we calculate the propagation influence of nodes based on their structural attributes to alleviate the issue of local optimality. At the group scale, we conduct precise propagation simulations to avoid introducing cumulative errors from approximate calculations without increasing computational costs. Experimental results on three real-world datasets demonstrate the effectiveness of our proposed multi-scale model in controlling network group behavior.

Keywords: influence blocking maximization, competitive linear threshold model, social networks, network group behavior

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Authors: Rajeev Kumar, Harishankar Kumar

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Fragmented data silos within enterprises impede the extraction of meaningful insights and hinder efficiency in tasks such as product development, client understanding, and meeting preparation. To address this, we propose a system-agnostic framework that leverages large language models (LLMs) to unify diverse data sources into a cohesive, user-centered knowledge graph. By automating entity extraction, relationship inference, and semantic enrichment, the framework maps interactions, behaviors, and data around the user, enabling intelligent querying and reasoning across various data types, including emails, calendars, chats, documents, and logs. Its domain adaptability supports applications in contextual search, task prioritization, expertise identification, and personalized recommendations, all rooted in user-centric insights. Experimental results demonstrate its effectiveness in generating actionable insights, enhancing workflows such as trip planning, meeting preparation, and daily task management. This work advances the integration of knowledge graphs and LLMs, bridging the gap between fragmented data systems and intelligent, unified enterprise solutions focused on user interactions.

Keywords: knowledge graph, entity extraction, relation extraction, LLM, activity graph, enterprise intelligence

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Authors: Nur Mohammad Ali, Md. Shafiqul Alam, Jayanta Bhusan Deb, Nowrin Sharmin

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The past ten years have seen significant expansion in the aviation sector, which during the previous five years has steadily pushed emerging countries closer to economic independence. It is crucial to accurately forecast the potential demand for air travel to make long-term financial plans. To forecast market demand for low-cost passenger carriers, this study suggests working with low-cost airlines, airports, consultancies, and governmental institutions' strategic planning divisions. The study aims to develop an artificial intelligence-based methods, notably fuzzy inference systems (FIS), to determine the most accurate forecasting technique for domestic low-cost carrier demand in Bangladesh. To give end users real-world applications, the study includes nine variables, two sub-FIS, and one final Mamdani Fuzzy Inference System utilizing a graphical user interface (GUI) made with the app designer tool. The evaluation criteria used in this inquiry included mean square error (MSE), accuracy, precision, sensitivity, and specificity. The effectiveness of the developed air passenger demand prediction FIS is assessed using 240 data sets, and the accuracy, precision, sensitivity, specificity, and MSE values are 90.83%, 91.09%, 90.77%, and 2.09%, respectively.

Keywords: aviation industry, fuzzy inference system, membership function, graphical user interference

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Authors: Azzeddine Atibi, Sara Atibi, Salim Ahmed, Khadija El Kabab

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In an educational context where innovation holds a predominant position, political discourses and pedagogical practices are increasingly oriented toward this concept. Innovation has become a benchmark value, gradually replacing the notion of progress. This term is omnipresent in discussions among policymakers, administrators, and academic researchers. The pressure to innovate impacts all levels of education, influencing institutional and educational policies, training objectives, and teachers' pedagogical practices. Higher education and continuing education sectors are not exempt from this trend. These sectors are compelled to transform to attract and retain an audience whose behaviors and expectations have significantly evolved. Indeed, the employability of young graduates has become a crucial issue, prompting us to question the effectiveness of various pedagogical methods in meeting this criterion. In this article, we propose to thoroughly examine the relationship between pedagogical methods employed in different fields of higher education and the acquisition of interpersonal skills, or "soft skills". Our aim is to determine to what extent these methods contribute to better-preparing students for the professional world. We will analyze how innovative pedagogical approaches can enhance the acquisition of soft skills, which are essential for the professional success of young graduates.

Keywords: educational context, innovation, higher education, soft skills, pedagogical practices, pedagogical approaches

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Authors: YingWei Tan, XueFeng Ding

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Attention-based voice activity detection models have gained significant attention in recent years due to their fast training speed and ability to capture a wide contextual range. The inclusion of multi-head style and position embedding in the attention architecture are crucial. Having multiple attention heads allows for differential focus on different parts of the sequence, while position embedding provides guidance for modeling dependencies between elements at various positions in the input sequence. In this work, we propose an approach by considering each head as a node, enabling the application of graph neural networks (GNN) to identify correlations among the different nodes. In addition, we adopt an implementation named rotary position embedding (RoPE), which encodes absolute positional information into the input sequence by a rotation matrix, and naturally incorporates explicit relative position information into a self-attention module. We evaluate the effectiveness of our method on a synthetic dataset, and the results demonstrate its superiority over the baseline CRNN in scenarios with low signal-to-noise ratio and noise, while also exhibiting robustness across different noise types. In summary, our proposed framework effectively combines the strengths of CNN and RNN (LSTM), and further enhances detection performance through the integration of graph neural networks and rotary position embedding.

Keywords: voice activity detection, CRNN, graph neural networks, rotary position embedding

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Authors: David Lynch, Jake Madden

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There exists a body of literature that reports on the many benefits of partnerships between universities and schools, especially in terms of teaching improvement and school reform. This is because such partnerships can build significant teaching capital, by deepening and expanding the skillsets and mindsets needed to create the connections that support ongoing and embedded teacher professional development and career goals. At the same time, this literature is critical of such initiatives when the partnership outcomes are short- term or one-sided, misaligned to fundamental problems, and not expressly focused on building the desired teaching capabilities. In response to this situation, research conducted by Professor David Lynch and his TeachLab research team, has begun to shed light on the strengths and limitations of school/university partnerships, via the identification of key conceptual elements that appear to act as critical partnership success factors. These elements are theorised as an inter-play between professional knowledge acquisition, readiness, talent management and organisational structure. However, knowledge of how these elements are established, and how they manifest within the school and its teaching workforce as an overall system, remains incomplete. Therefore, research designed to more clearly delineate these elements in relation to their impact on school/university partnerships is thus required. It is within this context that this paper reports on the development and testing of a Professional Learning (PL) model for schools and their teachers that incorporates school-university research partnering within a systematic, whole-of-school PL strategy that is underpinned and structured by a micro-credentialing (MC) regime. MC involves learning a narrow-focused certificate (a micro-credential) in a specific topic area (e.g., 'How to Differentiate Instruction for English as a second language Students') and embedded in the teacher’s day-to-day teaching work. The use of MC is viewed as important to the efficacy and sustainability of teacher PL because it (1) provides an evidence-based framework for teacher learning, (2) has the ability to promote teacher social capital and (3) engender lifelong learning in keeping professional skills current in an embedded and seamless to work manner. The associated research is centred on a primary school in Australia (P-6) that acted as an arena to co-develop, test/investigate and report on outcomes for teacher PL that uses MC to support a whole-of-school partnership with a university.

Keywords: teaching improvement, teacher professional learning, talent management, education partnerships, school-university research

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Authors: Yaou Zhang

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Background: Relatively little scholarly attention has been paid to the production of Benjamin Britten’s chamber opera The Turn of the Screw. As one of Britten’s most remarkable operas. The story of the libretto was from Henry James’s novella of the same name. The novella was created in 1898 and one of the primary questions addressed to people in the story is “how real the ghosts are,” which leads the story to a huge ambiguity in readers’ minds. Aims: This research focuses on the experience of seeing the opera on stage over several decades. This study of opera productions over time not only provides insight into how stage performances can alter audience members' perceptions of the opera in the present but also reveals a landscape of shifting aesthetics and receptions. Methods: To examine the hypotheses in interpretation and reception, the qualitative analysis is used to examine the figures of ghosts in different productions across the time from 1954 to 2021 in the UK: by accessing recordings, newspapers, and reviews for the productions that are sourced from online and physical archives. For instance, the field research is conducted on the topic by arranging interviews with the creative team and visiting Opera North in Leeds and Britten-Pears Foundation. The collected data reveals the “hidden identity” in creative teams’ interpretations, social preferences, and rediscover that have previously remained unseen. Results: This research presents an angle of Britten’s Screw by using the third position; it shows how the attention moved from the stage of “do the ghosts really exist” to “traumatised children.” Discussion: Critics and audiences have debated whether the governess hallucinates the ghosts in the opera for decades. While, in recent years, directors of new productions have given themselves the opportunity to go deeper into Britten's musical structure and offer the opera more space to be interpreted, rather than debating if "ghosts actually exist" or "the psychological problems of the governess." One can consider and reflect that the questionable actions of the children are because they are suffering from trauma, whether the trauma comes from the ghosts, the hallucinating governess, or some prior experiences: various interpretations cause one result that children are the recipients of trauma. Arguably, the role of the supernatural is neither simply one of the elements of a ghost story nor simply one of the parts of the ambiguity between the supernatural and the hallucination of the governess; rather, the ghosts and the hallucinating governess can exist at the same time - the combination of the supernatural’s and the governess’s behaviours on stage generates a sharper and more serious angle that draws our attention to the traumatized children.

Keywords: benjamin britten, chamber opera, production, reception, staging, the turn of the screw

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Authors: Luís Pina

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The conservation of marine biodiversity keeps ecosystems in balance and ensures the sustainable use of resources. In this context, technological resources have been used for monitoring marine species to allow biologists to obtain data in real-time. There are different mobile applications developed for data collection for monitoring purposes, but these systems are designed to be utilized only on third-generation (3G) phones or smartphones with Internet access and in rural parts of the developing countries, Internet services and smartphones are scarce. Thus, the objective of this work is to develop a system to monitor marine turtles using Unstructured Supplementary Service Data (USSD), which users can access through basic mobile phones. The system aims to improve the data collection mechanism and enhance the effectiveness of current systems in monitoring sea turtles using any type of mobile device without Internet access. The system will be able to report information related to the biological activities of marine turtles. Also, it will be used as a platform to assist marine conservation entities to receive reports of illegal sales of sea turtles. The system can also be utilized as an educational tool for communities, providing knowledge and allowing the inclusion of communities in the process of monitoring marine turtles. Therefore, this work may contribute with information to decision-making and implementation of contingency plans for marine conservation programs.

Keywords: GSM, marine biology, marine turtles, unstructured supplementary service data (USSD)

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Authors: Wong Seng Yue

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Game dynamics and game mechanics are the two main components that used in gamification to engage and encourage students to learn. The advantages of gamified classroom are engaging students, increasing students interest, preserving students focus and remain a positive behaviour. However, the empirical studies on gamification are still at early stage, especially the effectiveness of various gamification components have not been evaluated. Thus, this study is aimed to conduct a user experience (UX) evaluation on gamified classroom through Prezi, which focused on learning experience, gaming experience, adaptivity, and gameplay experience. This study is a further study extended from the previous exploratory study to explore more on UX of gamified classroom via Prezi by interview. A focus group study, which involves 22 students from a foundation course has been conducted for the study. Besides the empirical data from the previous study, this focus group study has significantly found that 90.9% respondents show their positive perceptions on gaming experience via Prezi. They are interested, feel fresh, good, and highly motivated of the contents of Prezi. 95.5% participants have had a positive learning experience from the gamified classroom via Prezi, which can engage them, made them concentrate on learning and easy to remember what they have learned if compared to the traditional classroom slides. The adaptivity of the gamified classroom also high due to its zooming user interface, narrative, rewards and engagement features. This study has uncovered on how far the impact of gamification components in the classroom, especially UX that implemented in gamified classroom.

Keywords: user experience (UX), gamification, gamified classroom, Prezi

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