Search results for: teaching learning model

Authors: Michael W. Markowitz, Jeffrey Gingerich

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The landscape of higher education in the United States has undergone significant changes in the last 25 years. What was once a domain of competition among prospective students for a limited number of college and university seats has become a marketplace in which institutions vie for the enrollment of educational consumers. A central figure in this paradigm shift has been the Chief Academic Officer (CAO), whose institutional role has also evolved beyond academics to include such disparate responsibilities as strategic planning, fiscal oversight, student recruitment, fundraising and personnel management. This paper explores the scope and impact of this transition by, first, explaining its context: the intersection of key social, economic and political factors in neo-conservative, late 20th Century America that redefined the value and accountability of institutions of higher learning. This context, in turn, is shown to have redefined the role and function of the CAO from a traditional academic leader to one centered on the successful application of corporate principles of organizational and fiscal management. Information gathered from a number of sitting Provosts, Vice-Presidents of Academic Affairs and Deans of Faculty is presented to illustrate the parameters of this change, as well as the extent to which today’s academic officers feel prepared and equipped to fulfill this broader institutional role. The paper concludes with a discussion of the impact of this transition on the American academy and whether it serves as a portend of change to come in higher education systems around the globe.

Keywords: academic administration, higher education, leadership, organizational management

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Authors: Leonard D. Agana, Wendell Ace Dela Cruz, Arjan C. Lingaya, Bonifacio T. Doma Jr.

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The purpose of this paper is to study the predict the fuel performance parameters, which include drivability index (DI), vapor lock index (VLI), and vapor lock potential using distillation curve and Reid vapor pressure (RVP) of dual alcohol-gasoline fuel blends. Distillation curve and Reid vapor pressure were predicted using artificial neural networks (ANN) with macroscopic properties such as boiling points, RVP, and molecular weights as the input layers. The ANN consists of 5 hidden layers and was trained using Bayesian regularization. The training mean square error (MSE) and R-value for the ANN of RVP are 91.4113 and 0.9151, respectively, while the training MSE and R-value for the distillation curve are 33.4867 and 0.9927. Fuel performance analysis of the dual alcohol–gasoline blends indicated that highly volatile gasoline blended with dual alcohols results in non-compliant fuel blends with D4814 standard. Mixtures of low-volatile gasoline and 10% methanol or 10% ethanol can still be blended with up to 10% C3 and C4 alcohols. Intermediate volatile gasoline containing 10% methanol or 10% ethanol can still be blended with C3 and C4 alcohols that have low RVPs, such as 1-propanol, 1-butanol, 2-butanol, and i-butanol. Biography: Graduate School of Chemical, Biological, and Materials Engineering and Sciences, Mapua University, Muralla St., Intramuros, Manila, 1002, Philippines

Keywords: dual alcohol-gasoline blends, distillation curve, machine learning, reid vapor pressure

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Authors: Lalit Kumar, Rashid Al Shidi

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Phoenix dactylifera (date palm) is a major crop in many middle-eastern countries, including Oman. The Dubas bug Ommatissus lybicus is the main pest that affects date palm crops. However not all plantations are infested. It is still uncertain why some plantations get infested while others are not. This research investigated whether tree density and the system of planting (random versus systematic) had any relationship with infestation and levels of infestation. Remote Sensing and Geographic Information Systems were used to determine the density of trees (number of trees per unit area) while infestation levels were determined by manual counting of insects on 40 leaflets from two fronds on each tree, with a total of 20-60 trees in each village. The infestation was recorded as the average number of insects per leaflet. For tree density estimation, WorldView-3 scenes, with eight bands and 2m spatial resolution, were used. The Local maxima method, which depends on locating of the pixel of highest brightness inside a certain exploration window, was used to identify the trees in the image and delineating individual trees. This information was then used to determine whether the plantation was random or systematic. The ordinary least square regression (OLS) was used to test the global correlation between tree density and infestation level and the Geographic Weight Regression (GWR) was used to find the local spatial relationship. The accuracy of detecting trees varied from 83–99% in agricultural lands with systematic planting patterns to 50–70% in natural forest areas. Results revealed that the density of the trees in most of the villages was higher than the recommended planting number (120–125 trees/hectare). For infestation correlations, the GWR model showed a good positive significant relationship between infestation and tree density in the spring season with R² = 0.60 and medium positive significant relationship in the autumn season, with R² = 0.30. In contrast, the OLS model results showed a weaker positive significant relationship in the spring season with R² = 0.02, p < 0.05 and insignificant relationship in the autumn season with R² = 0.01, p > 0.05. The results showed a positive correlation between infestation and tree density, which suggests the infestation severity increased as the density of date palm trees increased. The correlation result showed that the density alone was responsible for about 60% of the increase in the infestation. This information can be used by the relevant authorities to better control infestations as well as to manage their pesticide spraying programs.

Keywords: dubas bug, date palm, tree density, infestation levels

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Authors: Shreyansh Singh, Afroz Ahmed

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Sentiment Analysis intends to naturally reveal the hidden mentality that we hold towards an entity. The total of this assumption over a populace addresses sentiment surveying and has various applications. Current text-based sentiment analysis depends on the development of word embeddings and Machine Learning models that take in conclusion from enormous text corpora. Sentiment Analysis from text is presently generally utilized for consumer loyalty appraisal and brand insight investigation. With the expansion of online media, multimodal assessment investigation is set to carry new freedoms with the appearance of integral information streams for improving and going past text-based feeling examination using the new transforms methods. Since supposition can be distinguished through compelling follows it leaves, like facial and vocal presentations, multimodal opinion investigation offers good roads for examining facial and vocal articulations notwithstanding the record or printed content. These methodologies use the Recurrent Neural Networks (RNNs) with the LSTM modes to increase their performance. In this study, we characterize feeling and the issue of multimodal assessment investigation and audit ongoing advancements in multimodal notion examination in various spaces, including spoken surveys, pictures, video websites, human-machine, and human-human connections. Difficulties and chances of this arising field are additionally examined, promoting our theory that multimodal feeling investigation holds critical undiscovered potential.

Keywords: sentiment analysis, RNN, LSTM, word embeddings

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Authors: Xinghui Wu, Chun Yang

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Inertial microfluidics is a competitive fluidic method with applications in separation of particles, cells and bacteria. In contrast to traditional microfluidic devices with low Reynolds number, inertial microfluidics works in the intermediate Re number range which brings about several intriguing inertial effects on particle separation/focusing to meet the throughput requirement in the real-world. Geometric modifications to make channels become irregular shapes can leverage fluid inertia to create complex secondary flow for adjusting the particle equilibrium positions and thus enhance the separation resolution and throughput. Although inertial microfluidics has been extensively studied by experiments, our current understanding of its mechanisms is poor, making it extremely difficult to build rational-design guidelines for the particle focusing locations, especially for irregularly shaped microfluidic channels. Inertial particle microfluidics in irregularly shaped channels were investigated in our group. There are several fundamental issues that require us to address. One of them is about the balance between the inertial lift forces and the secondary drag forces. Also, it is critical to quantitatively describe the dependence of the life forces on particle-particle interactions in irregularly shaped channels, such as a rectangular one. To provide physical insights into the inertial microfluidics in channels of irregular shapes, in this work the immersed boundary-lattice Boltzmann method (IB-LBM) was introduced and validated to explore the transport characteristics and the underlying mechanisms of an inertial focusing single particle in a rectangular microchannel. The transport dynamics of a finitesized particle were investigated over wide ranges of Reynolds number (20 < Re < 500) and particle size. The results show that the inner equilibrium positions are more difficult to occur in the rectangular channel, which can be explained by the secondary flow caused by the presence of a finite-sized particle. Furthermore, force decoupling analysis was utilized to study the effect of each type of lift force on the inertia migration, and a theoretical model for the lateral lift force of a finite-sized particle in the rectangular channel was established. Such theoretical model can be used to provide theoretical guidance for the design and operation of inertial microfluidics.

Keywords: inertial microfluidics, particle focuse, life force, IB-LBM

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Authors: A. Benbouali, H. Saidi, A. Derrouazin, T. Bessaad

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Aerial robotics is a very exciting research field dealing with a variety of subjects, including the attitude control. This paper deals with the control of a four rotor vertical take-off and landing (VTOL) Unmanned Aerial Vehicle. The paper presents a mathematical model based on the approach of Lagrange for the flight control of an autonomous quad-rotor. It also describes the controller architecture which is based on PID regulators. The control method has been simulated in closed loop in different situations. All the calculation stages and the simulation results have been detailed.

Keywords: quad-rotor, lagrange approach, proportional integral derivate (PID) controller, Matlab/Simulink

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Authors: Chidozie C. Nwobi-Okoye, Basil Q. Ochieze, Stanley Okiy

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This research reports on the modeling of age hardening process using adaptive neuro-fuzzy inference system (ANFIS). The age hardening output (Hardness) was predicted using ANFIS. The input parameters were ageing time, temperature and percentage composition of cow horn particles (CHp%). The results show the correlation coefficient (R) of the predicted hardness values versus the measured values was of 0.9985. Subsequently, values outside the experimental data points were predicted. When the temperature was kept constant, and other input parameters were varied, the average relative error of the predicted values was 0.0931%. When the temperature was varied, and other input parameters kept constant, the average relative error of the hardness values predictions was 80%. The results show that ANFIS with coarse experimental data points for learning is not very effective in predicting process outputs in the age hardening operation of A356 alloy/CHp particulate composite. The fine experimental data requirements by ANFIS make it more expensive in modeling and optimization of age hardening operations of A356 alloy/CHp particulate composite.

Keywords: adaptive neuro-fuzzy inference system (ANFIS), age hardening, aluminum alloy, metal matrix composite

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Authors: Supakorn Tantisriyanurak, Hussaya Maneesuwan, Thanyalak Chaisuwan, Sujitra Wongkasemjit

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TUD-1 is a siliceous mesoporous material with a three-dimensional amorphous structure of random, interconnecting pores, large pore size, high surface area (400-1000 m2/g), hydrothermal stability, and tunable porosity. However, the significant disadvantage of the mesoporous silicates is few catalytic active sites. In this work, a series of bimetallic Fe and Ti incorporated into TUD-1 framework is successfully synthesized by sol–gel method. The synthesized Fe,Ti-TUD-1 is characterized by various techniques. To study the catalytic activity of Fe, Ti–TUD-1, phenol hydroxylation was selected as a model reaction. The amounts of residual phenol and oxidation products were determined by high performance liquid chromatography coupled with UV-detector (HPLC-UV).

Keywords: iron, phenol hydroxylation, titanium, TUD-1

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Authors: Hiba Naccache, Rima Hleiss

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Additive manufacturing AM or 3D printing is one of the pillars of Industry 4.0. Compared to traditional manufacturing, AM provides a prototype before production in order to optimize the design and avoid the stock market and uses strictly necessary material which can be recyclable, for the benefit of leaning towards local production, saving money, time and resources. Different types of AM exist and it has a broad range of applications across several industries like aerospace, automotive, medicine, education and else. The Laser Powder Bed Fusion (LPBF) is a metal AM technique that uses a laser to liquefy metal powder, layer by layer, to build a three-dimensional (3D) object. In industry 4.0 and aligned with the numbers 9 (Industry, Innovation and Infrastructure) and 12 (Responsible Production and Consumption) of the Sustainable Development Goals of the UNESCO 2030 Agenda, the AM’s manufacturers committed to minimizing the environmental impact by being sustainable in every production. The LPBF has several environmental advantages, like reduced waste production, lower energy consumption, and greater flexibility in creating components with lightweight and complex geometries. However, LPBF also have environmental drawbacks, like energy consumption, gas consumption and emissions. It is critical to recognize the environmental impacts of LPBF in order to mitigate them. To increase awareness and promote sustainable practices regarding LPBF, the researchers use the Elaboration Likelihood Model (ELM) theory where people from multiple universities in France and Qatar process information in two ways: peripherally and centrally. The peripheral campaigns use superficial cues to get attention, and the central campaigns provide clear and concise information. The authors created a seminar including a video showing LPBF production and a website with educational resources. The data is collected using questionnaire to test attitude about the public awareness before and after the seminar. The results reflected a great shift on the awareness toward LPBF and its impact on the environment. With no presence of similar research, to our best knowledge, this study will add to the literature on the sustainability of the LPBF production technique.

Keywords: additive manufacturing, laser powder bed fusion, elaboration likelihood model theory, sustainable development goals, education-awareness, France, Qatar, specific energy consumption, environmental impact, lightweight components

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Authors: Hajara Abdulkarim Aliyu, Abdulbasid Ismail Isa

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This research paper studies electrohydraulic system for its role in position and motion control system and develops as mathematical model describing the behaviour of the system. The research further proposes Fuzzy logic and conventional PID controllers in order to achieve both accurate positioning of the payload and overall improvement of the system performance. The simulation result shows Fuzzy logic controller has a superior tracking performance and high disturbance rejection efficiency for its shorter settling time, less overshoot, smaller values of integral of absolute and deviation errors over the conventional PID controller at all the testing conditions.

Keywords: electrohydraulic, fuzzy logic, modelling, NZ-PID

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Authors: Emma Groenewald

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In 1994, numerous policies of a democratic dispensation envisage social justice and the transformation of the South Africa society. The drive for transformation and social justice resulted in an increasing number of university students from diverse backgrounds, which in turn, lead to the establishment of Sol Plaatje University (SPU) in 2014. A re-curriculated B. Ed. programme at SPU aims to equip students with knowledge and skills to realise the aim of social justice and to enhance the transformation of the South African society. The aim of this study is to explore the experiences and perceptions of students at a diverse university campus on a curriculum that aims to promote social justice. Four education modules, with the assumption that it reflects social justice content, were selected. Four students, representative of different ethnic and language groupings found at the SPU, were chosen as participants. Data were generated by the participants through four reflective exercises on each of the modules, spread over a period of four years. The module aims, linked with the narratives of the participants' perceptions and experiences of each module, provided an overview of the enacted curriculum. A qualitative research design with an interpretivist approach informed by Vygotsky's theory of learning was used. The participants' experiences of the four modules were analysed, and their views were interpreted. The students' narratives shed light on the strengths and weaknesses of how the B.Ed. Curriculum works towards social justice and revealed student's perceptions of otherness. From the narratives it became apparent that module did promote a social justice orientation in prospective teachers trained at a university.

Keywords: student diversity, social justice, transformation, teacher education

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Authors: Remzi Saltoglu, Nazmia Humaira, Gokhan Inalhan

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During aircraft maintenance scheduling, operator calculates the budget of the maintenance. Usually, this calculation includes only the costs that are directly related to the maintenance process such as cost of labor, material, and equipment. In some cases, overhead cost is also included. However, in some of those, downtime cost is neglected claiming that grounding is a natural fact of maintenance; therefore, it is not considered as part of the analytical decision-making process. Based on the normalized data, we introduce downtime cost with its monetary value and add its seasonal character. We envision that the rest of the model, which works together with the downtime cost, could be checked with the real life cases, through the review of MRO cost and airline spending in the particular and scheduled maintenance events.

Keywords: aircraft maintenance, downtime, downtime cost, maintenance cost

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Authors: Ihab Elaff

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Simulating the heart’s electrical stimulation is essential in modeling and evaluating the electrophysiology behavior of the heart. For achieving that, there are two structures in concern: the ventricles’ Myocardium, and the ventricles’ Conduction Network. Ventricles’ Myocardium has been modeled as anisotropic material from Diffusion Tensor Imaging (DTI) scan, and the Conduction Network has been extracted from DTI as a case-based structure based on the biological properties of the heart tissues and the working methodology of the Magnetic Resonance Imaging (MRI) scanner. Results of the produced activation were much similar to real measurements of the reference model that was presented in the literature.

Keywords: diffusion tensor, DTI, heart, conduction network, excitation propagation

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Authors: I. Ioannou, I. M. Gitman

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This study focused on the contribution of micro-mechanical parameters on the macro-mechanical response of short fiber composites, namely polypropylene matrix reinforced by glass fibers. In the framework of this paper, an attention has been given to the glass fibers length, as micromechanical parameter influences the overall macroscopic material’s behavior. Three dimensional numerical models were developed and analyzed through the concept of a Representative Volume Element (RVE). Results of the RVE-based approach were compared with analytical Halpin-Tsai’s model.

Keywords: effective properties, homogenization, representative volume element, short fiber reinforced composites

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Authors: Dr. Dionysis Panos Dpt. Communication, Internet Studies Cyprus University of Technology

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The widespread use of New Media and particularly Social Media, through fixed or mobile devices, has changed in a staggering way our perception about what is “intimate" and "safe" and what is not, in interpersonal communication and social relationships. The distribution of self and identity-related information in communication now evolves under new and different conditions and contexts. Consequently, this new framework forces us to rethink processes and mechanisms, such as what "exposure" means in interpersonal communication contexts, how the distinction between the "private" and the "public" nature of information is being negotiated online, how the "audiences" we interact with are understood and constructed. Drawing from an interdisciplinary perspective that combines sociology, communication psychology, media theory, new media and social networks research, as well as from the empirical findings of a longitudinal comparative research, this work proposes an integrative model for comprehending mechanisms of personal information management in interpersonal communication, which can be applied to both types of online (Computer-Mediated) and offline (Face-To-Face) communication. The presentation is based on conclusions drawn from a longitudinal qualitative research study with 458 new media users from 24 countries for almost over a decade. Some of these main conclusions include: (1) There is a clear and evidenced shift in users’ perception about the degree of "security" and "familiarity" of the Web, between the pre- and the post- Web 2.0 era. The role of Social Media in this shift was catalytic. (2) Basic Web 2.0 applications changed dramatically the nature of the Internet itself, transforming it from a place reserved for “elite users / technical knowledge keepers" into a place of "open sociability” for anyone. (3) Web 2.0 and Social Media brought about a significant change in the concept of “audience” we address in interpersonal communication. The previous "general and unknown audience" of personal home pages, converted into an "individual & personal" audience chosen by the user under various criteria. (4) The way we negotiate the nature of 'private' and 'public' of the Personal Information, has changed in a fundamental way. (5) The different features of the mediated environment of online communication and the critical changes occurred since the Web 2.0 advance, lead to the need of reconsideration and updating the theoretical models and analysis tools we use in our effort to comprehend the mechanisms of interpersonal communication and personal information management. Therefore, is proposed here a new model for understanding the way interpersonal communication evolves, based on a revision of social penetration theory.

Keywords: new media, interpersonal communication, social penetration theory, communication exposure, private information, public information

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Authors: Noor Ayuni Che Zakaria, Takashi Komeda, Cheng Yee Low, Kaoru Inoue, Fazah Akhtar Hanapiah

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Previous studies have shown that there are arguments regarding the reliability and validity of the Ashworth and Modified Ashworth Scale towards evaluating patients diagnosed with upper limb disorders. These evaluations depended on the raters’ experiences. This initiated us to develop an upper limb disorder part-task trainer that is able to simulate consistent upper limb disorders, such as spasticity and rigidity signs, based on the Modified Ashworth Scale to improve the variability occurring between raters and intra-raters themselves. By providing consistent signs, novice therapists would be able to increase training frequency and exposure towards various levels of signs. A total of 22 physiotherapists and occupational therapists participated in the study. The majority of the therapists agreed that with current therapy education, they still face problems with inter-raters and intra-raters variability (strongly agree 54%; n = 12/22, agree 27%; n = 6/22) in evaluating patients’ conditions. The therapists strongly agreed (72%; n = 16/22) that therapy trainees needed to increase their frequency of training; therefore believe that our initiative to develop an upper limb disorder training tool will help in improving the clinical education field (strongly agree and agree 63%; n = 14/22).

Keywords: upper limb disorder, clinical education tool, inter/intra-raters variability, spasticity, modified Ashworth scale

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Authors: Lingge Tan, Hongpeng Xu, Jieun Yang, Maarten Hornikx

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Acoustic diffusers are important components in enhancing the quality of room acoustics. This paper provides a type of modular diffuser based on the Sierpinski Triangle of the plane and combines it with fractal theory to expand the effective frequency range. In numerical calculations and full-scale model experiments, the effect of fractal design elements on normal-incidence diffusion coefficients is examined. It is demonstrated the reasonable times of iteration of modules is three, and the coverage density is 58.4% in the design frequency from 125Hz to 4kHz.

Keywords: acoustic diffuser, fractal, Sierpinski-triangle, diffusion coefficient

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Authors: Temesgen Sidamo, Prakruti S. Rao, Eleni Akllilu, Workineh Shibeshi, Yumi Park, Yong-Soon Cho, Jae-Gook Shin, Scott K. Heysell, Stellah G. Mpagama, Ephrem Engidawork

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The fluoroquinolones (FQs) are used off-label for the treatment of multidrug-resistant tuberculosis (MDR-TB), and for evaluation in shortening the duration of drug-susceptible TB in recently prioritized regimens. Within the class, levofloxacin (LFX) and moxifloxacin (MXF) play a substantial role in ensuring success in treatment outcomes. However, sub-therapeutic plasma concentrations of either LFX or MXF may drive unfavorable treatment outcomes. To the best of our knowledge, the pharmacokinetics of LFX and MXF in Ethiopian patients with MDR-TB have not yet been investigated. Therefore, the aim of this study was to develop a population pharmacokinetic (PopPK) model of levofloxacin (LFX) and moxifloxacin (MXF) and assess the percent probability of target attainment (PTA) as defined by the ratio of the area under the plasma concentration-time curve over 24-h (AUC0-24) and the in vitro minimum inhibitory concentration (MIC) (AUC0-24/MIC) in Ethiopian MDR-TB patients. Steady-state plasma was collected from 39 MDR-TB patients enrolled in the programmatic treatment course and the drug concentrations were determined using optimized liquid chromatography-tandem mass spectrometry. In addition, the in vitro MIC of the patients' pretreatment clinical isolates was determined. PopPK and simulations were run at various doses, and PK parameters were estimated. The effect of covariates on the PK parameters and the PTA for maximum mycobacterial kill and resistance prevention was also investigated. LFX and MXF both fit in a one-compartment model with adjustments. The apparent volume of distribution (V) and clearance (CL) of LFX were influenced by serum creatinine (Scr), whereas the absorption constant (Ka) and V of MXF were influenced by Scr and BMI, respectively. The PTA for LFX maximal mycobacterial kill at the critical MIC of 0.5 mg/L was 29%, 62%, and 95% with the simulated 750 mg, 1000 mg, and 1500 mg doses, respectively, whereas the PTA for resistance prevention at 1500 mg was only 4.8%, with none of the lower doses achieving this target. At the critical MIC of 0.25 mg/L, there was no difference in the PTA (94.4%) for maximum bacterial kill among the simulated doses of MXF (600 mg, 800 mg, and 1000 mg), but the PTA for resistance prevention improved proportionately with dose. Standard LFX and MXF doses may not provide adequate drug exposure. LFX PopPK is more predictable for maximum mycobacterial kill, whereas MXF's resistance prevention target increases with dose. Scr and BMI are likely to be important covariates in dose optimization or therapeutic drug monitoring (TDM) studies in Ethiopian patients.

Keywords: population PK, PTA, moxifloxacin, levofloxacin, MDR-TB patients, ethiopia

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Authors: Nassim Ourabia, Malika Ourabia

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A new and efficient method is presented for the analysis of arbitrarily shaped discontinuities. The technique obtains closed form expressions for the equivalent circuits which are used to model these discontinuities. Then it would be easy to handle and to characterize complicated structures like T and Y junctions, truncated junctions, arbitrarily shaped junctions, cascading junctions, and more generally planar multiport junctions. Another advantage of this method is that the edge line concept for arbitrary shape junctions operates with real parameters circuits. The validity of the method was further confirmed by comparing our results for various discontinuities (bend, filters) with those from HFSS as well as from other published sources.

Keywords: CAD analysis, contour integral approach, microwave circuits, s-parameters

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Authors: Margarita Santi Becerra Santiago

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The following document addresses the descriptive analysis under the qualitative approach of resilient leadership that allows us to know the importance of the application of a new leadership model to face the new challenges within the gastronomic companies in Mexico. Likewise, to know the main factors that influence resilient leaders and companies to develop new skills to elaborate strategies that contribute to overcoming adversities and managing change. Adversities in a company always exist and challenge us to move and apply our knowledge to be competitive as well as to strengthen our work team through motivation to achieve efficiency and develop in a good organizational climate.

Keywords: challenges, efficiency, leadership, resilience skills

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Authors: Mina Samizadeh

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In the past few decades, there has been an explosion in the amount of available data produced from various sources with different topics. The availability of this enormous data necessitates us to adopt effective computational tools to explore the data. This leads to an intense growing interest in the research community to develop computational methods focused on processing this text data. A line of study focused on condensing the text so that we are able to get a higher level of understanding in a shorter time. The two important tasks to do this are keyword extraction and text summarization. In keyword extraction, we are interested in finding the key important words from a text. This makes us familiar with the general topic of a text. In text summarization, we are interested in producing a short-length text which includes important information about the document. The TextRank algorithm, an unsupervised learning method that is an extension of the PageRank (algorithm which is the base algorithm of Google search engine for searching pages and ranking them), has shown its efficacy in large-scale text mining, especially for text summarization and keyword extraction. This algorithm can automatically extract the important parts of a text (keywords or sentences) and declare them as a result. However, this algorithm neglects the semantic similarity between the different parts. In this work, we improved the results of the TextRank algorithm by incorporating the semantic similarity between parts of the text. Aside from keyword extraction and text summarization, we develop a topic clustering algorithm based on our framework, which can be used individually or as a part of generating the summary to overcome coverage problems.

Keywords: keyword extraction, n-gram extraction, text summarization, topic clustering, semantic analysis

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Authors: Dean A. McCorkle, Ed W. Hellman, Rebekka M. Dudensing, Dan D. Hanselka

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The motivation for this study centers on the labor- and cost-intensive nature of wine and table grape production in the U.S., and the potential opportunities for precision mechanization using robotics to augment those production tasks that are labor-intensive. The objectives of this study are to evaluate the economic viability of grape production in five U.S. states under current operating conditions, identify common production challenges and tasks that could be augmented with new technology, and quantify a maximum price for new technology that growers would be able to pay. Wine and table grape production is primed for precision mechanization technology as it faces a variety of production and labor issues. Methodology: Using a grower panel process, this project includes the development of a representative wine grape vineyard in five states and a representative table grape vineyard in California. The panels provided production, budget, and financial-related information that are typical for vineyards in their area. Labor costs for various production tasks are of particular interest. Using the data from the representative budget, 10-year projected financial statements have been developed for the representative vineyard and evaluated using a stochastic simulation model approach. Labor costs for selected vineyard production tasks were evaluated for the potential of new precision mechanization technology being developed. These tasks were selected based on a variety of factors, including input from the panel members, and the extent to which the development of new technology was deemed to be feasible. The net present value (NPV) of the labor cost over seven years for each production task was derived. This allowed for the calculation of a maximum price for new technology whereby the NPV of labor costs would equal the NPV of purchasing, owning, and operating new technology. Expected Results: The results from the stochastic model will show the projected financial health of each representative vineyard over the 2015-2024 timeframe. Investigators have developed a preliminary list of production tasks that have the potential for precision mechanization. For each task, the labor requirements, labor costs, and the maximum price for new technology will be presented and discussed. Together, these results will allow technology developers to focus and prioritize their research and development efforts for wine and table grape vineyards, and suggest opportunities to strengthen vineyard profitability and long-term viability using precision mechanization.

Keywords: net present value, robotic technology, stochastic simulation, wine and table grapes

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Authors: Ella Sèdé Maforikan

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Accurate land cover mapping is essential for effective environmental monitoring and natural resources management. This study focuses on assessing the classification performance of two satellite datasets and evaluating the impact of different input feature combinations on classification accuracy in the Beterou catchment, situated in the northern part of Benin. Landsat-8 and Sentinel-2 images from June 1, 2020, to March 31, 2021, were utilized. Employing the Random Forest (RF) algorithm on Google Earth Engine (GEE), a supervised classification categorized the land into five classes: forest, savannas, cropland, settlement, and water bodies. GEE was chosen due to its high-performance computing capabilities, mitigating computational burdens associated with traditional land cover classification methods. By eliminating the need for individual satellite image downloads and providing access to an extensive archive of remote sensing data, GEE facilitated efficient model training on remote sensing data. The study achieved commendable overall accuracy (OA), ranging from 84% to 85%, even without incorporating spectral indices and terrain metrics into the model. Notably, the inclusion of additional input sources, specifically terrain features like slope and elevation, enhanced classification accuracy. The highest accuracy was achieved with Sentinel-2 (OA = 91%, Kappa = 0.88), slightly surpassing Landsat-8 (OA = 90%, Kappa = 0.87). This underscores the significance of combining diverse input sources for optimal accuracy in land cover mapping. The methodology presented herein not only enables the creation of precise, expeditious land cover maps but also demonstrates the prowess of cloud computing through GEE for large-scale land cover mapping with remarkable accuracy. The study emphasizes the synergy of different input sources to achieve superior accuracy. As a future recommendation, the application of Light Detection and Ranging (LiDAR) technology is proposed to enhance vegetation type differentiation in the Beterou catchment. Additionally, a cross-comparison between Sentinel-2 and Landsat-8 for assessing long-term land cover changes is suggested.

Keywords: land cover mapping, Google Earth Engine, random forest, Beterou catchment

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Authors: Medjram Sofiane, Babahenini Mohamed Chaouki, Mohamed Benali Yamina

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Skin detection is an important task for computer vision systems. A good method for skin detection means a good and successful result of the system. The colour is a good descriptor that allows us to detect skin colour in the images, but because of lightings effects and objects that have a similar colour skin, skin detection becomes difficult. In this paper, we proposed a method using the YCbCr colour space for skin detection and lighting effects elimination, then we use the information of texture to eliminate the false regions detected by the YCbCr colour skin model.

Keywords: skin detection, YCbCr, GLCM, texture, human skin

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Authors: Fouad Berrabeh, Sabir Messalti

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The performances of the photovoltaic systems are very dependent on different conditions, such as solar irradiation, temperature, etc. Therefore, it is very important to provide detailed studies for different cases in order to provide continuously power, so the photovoltaic system must be properly sized. This paper presents the modelling and simulation of the photovoltaic cell using single diode model. I-V characteristics and P-V characteristics are presented and it verified at different conditions (irradiance effect, temperature effect, series resistance effect).

Keywords: photovoltaic cell, BP SX 150 BP solar photovoltaic module, irradiance effect, temperature effect, series resistance effect, I–V characteristics, P–V characteristics

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Authors: Yiming Jin, Yuanhao Gao

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In this paper, using the method of multiple scales, the second sub-harmonic resonance in vortex-induced vibrations (VIV) of a marine pipeline close to the seabed is investigated based on a developed wake oscillator model. The amplitude-frequency equations are also derived. It is found that the oscillation will increase all the time when both discriminants of the amplitude-frequency equations are positive while the oscillation will decay when the discriminants are negative.

Keywords: vortex-induced vibrations, marine pipeline, seabed, sub-harmonic resonance

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Authors: Roberto Machado

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We conducted a systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses methodology, analyzing 2,996 studies and synthesizing 41 of them to explore the evolution of data science and its integration into geography. By employing optimization algorithms, we accelerated the review process, significantly enhancing the efficiency and precision of literature selection. Our findings indicate that data science has developed over five decades, facing challenges such as the diversified integration of data and the need for advanced statistical and computational skills. In geography, the integration of data science underscores the importance of interdisciplinary collaboration and methodological innovation. Techniques like large-scale spatial data analysis and predictive algorithms show promise in natural disaster management and transportation route optimization, enabling faster and more effective responses. These advancements highlight the transformative potential of data science in geography, providing tools and methodologies to address complex spatial problems. The relevance of this study lies in the use of optimization algorithms in systematic reviews and the demonstrated need for deeper integration of data science into geography. Key contributions include identifying specific challenges in combining diverse spatial data and the necessity for advanced computational skills. Examples of connections between these two fields encompass significant improvements in natural disaster management and transportation efficiency, promoting more effective and sustainable environmental solutions with a positive societal impact.

Keywords: data science, geography, systematic review, optimization algorithms, supervised learning

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Authors: Dana El-Mughayyar, Neil Manson, Erin Bigney, Eden Richardson, Dean Tripp, Edward Abraham

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Use of narcotics to treat pain has increased over the past two decades and is a contributing factor to the current public health crisis. Understanding the pre-operative risks of chronic narcotic use may be aided through investigation of psychological measures. The objective of the reported study is to determine predictors of narcotic use two years post-surgery in a thoracolumbar spine surgery population, including an array of psychological factors. A prospective observational study of 191 consecutively enrolled adult patients having undergone thoracolumbar spine surgery is presented. Baseline measures of interest included the Pain Catastrophizing Scale (PCS), Tampa Scale for Kinesiophobia, Multidimensional Scale for Perceived Social Support (MSPSS), Chronic Pain Acceptance Questionnaire (CPAQ-8), Oswestry Disability Index (ODI), Numeric Rating Scales for back and leg pain (NRS-B/L), SF-12’s Mental Component Summary (MCS), narcotic use and demographic variables. The post-operative measure of interest is narcotic use at 2-year follow-up. Narcotic use is collapsed into binary categories of use and no use. Descriptive statistics are run. Chi Square analysis is used for categorical variables and an ANOVA for continuous variables. Significant variables are built into a hierarchical logistic regression to determine predictors of post-operative narcotic use. Significance is set at α < 0.05. Results: A total of 27.23% of the sample were using narcotics two years after surgery. The regression model included ODI, NRS-Leg, time with condition, chief complaint, pre-operative drug use, gender, MCS, PCS subscale helplessness, and CPAQ subscale pain willingness and was significant χ² (13, N=191)= 54.99; p = .000. The model accounted for 39.6% of the variance in narcotic use and correctly predicted in 79.7% of cases. Psychological variables accounted for 9.6% of the variance over and above the other predictors. Conclusions: Managing chronic narcotic usage is central to the patient’s overall health and quality of life. Psychological factors in the preoperative period are significant predictors of narcotic use 2 years post-operatively. The psychological variables are malleable, potentially allowing surgeons to direct their patients to preventative resources prior to surgery.

Keywords: narcotics, psychological factors, quality of life, spine surgery

Procedia PDF Downloads 144

Authors: Vertika Goswami, Gargi Sharma

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The rapid evolution of fintech has led to the rise of robo-advisor platforms that utilize artificial intelligence (AI) and machine learning to offer personalized investment solutions efficiently and cost-effectively. This research paper conducts a comprehensive sentiment analysis of investor experiences with these platforms, employing natural language processing (NLP) and sentiment classification techniques. The study investigates investor perceptions, engagement, and satisfaction, identifying key drivers of positive sentiment such as clear communication, low fees, consistent returns, and robust security. Conversely, negative sentiment is linked to issues like inconsistent performance, hidden fees, poor customer support, and a lack of transparency. The analysis reveals that addressing these pain points—through improved transparency, enhanced customer service, and ongoing technological advancements—can significantly boost investor trust and satisfaction. This paper contributes valuable insights into the fields of behavioral finance and fintech innovation, offering actionable recommendations for stakeholders, practitioners, and policymakers. Future research should explore the long-term impact of these factors on investor loyalty, the role of emerging technologies, and the effects of ethical investment choices and regulatory compliance on investor sentiment.

Keywords: artificial intelligence in finance, automated investment, financial technology, investor satisfaction, investor sentiment, robo-advisors, sentimental analysis

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Authors: Indhumathi Gopal

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Undergraduate research is well documented in Science, Technology, Engineering, and Mathematics (STEM), neurosciences, and microbiology disciplines, though it is hardly part of a physical fitness & wellness discipline. However, students need experiential learning opportunities, like internships and research assistantships, to get ahead with graduate schools and be gainfully employed. The first step towards this goal is to have students do a simple research project in a semester-long course. The value of research experiences and how to integrate research activity in a physical fitness & wellness course are discussed. The investigator looks into a mini research project, “Awareness of Obesity among College Students” and explains how to guide students through the research process, including journal search, data collection, and basic statistics. Besides, students will be introduced to the statistical package program SPSS 22.0 to assist with data evaluation. The lab component of the combined lecture-physical activity course could include the measurement of student’s weight with respect to their height to obtain body mass index (BMI). Students could categorize themselves in accordance with the World Health Organization’s guidelines. Results obtained after completing the data analysis help students be aware of their own potential health risks associated with overweight and obesity. Overweight and obesity are risk factors for hypertension, hypercholesterolemia, heart disease, stroke, diabetes, and certain types of cancer. It is hoped that this experience will get students interested in scientific studies, gain confidence, think critically, and develop problem-solving and good communication skills.

Keywords: physical fitness, undergraduate research experience, obesity, BMI

Procedia PDF Downloads 81