Search results for: subject area modeling.

Authors: A. Vassila, D. Kalogeropoulos, R. Rawashdeh, N. Hall, N. Rahman, M. Fabian, S. Thulasidharan, H. Parwez

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Necrotising scleritis is a severe form of scleritis and poses a significant threat to vision. It can manifest in various systemic autoimmune disorders, systemic vasculitis, or as a consequence of microbial infections. The objective of this study is to present a case of necrotizing scleritis associated with scleroderma, which was further complicated by a secondary Staphylococcus epidermidis infection. This is a retrospective analysis, which examines the medical records of a patient who was hospitalised in the Eye Unit at University Hospital Southampton. A 78-year-old woman presented at the eye casualty department of our unit with a two-week history of progressively worsening pain in her left eye. She received a diagnosis of necrotising scleritis and was admitted to the hospital for further treatment. It was decided to commence a three-day course of intravenous methylprednisolone followed by a tapering regimen of oral steroids. Additionally, a conjunctival swab was taken, and two days later, it revealed the presence of S. epidermidis, indicating a potential secondary infection. Given this finding, she was also prescribed topical (Ofloxacin 0.3% - four times daily) and oral (Ciprofloxacin 750 mg – twice daily) antibiotics. The inflammation and symptoms gradually improved, leading to the patient being scheduled for a scleral graft and applying an amniotic membrane to cover the area of scleral thinning. Rheumatoid arthritis and granulomatosis with polyangiitis are the most commonly identifiable systemic diseases associated with necrotising scleritis. Although association with scleroderma is extremely rare, early identification and treatment are necessary to prevent scleritis-related complications.

Keywords: Scleritis, necrotizing scleritis, scleroderma, autoimmune disease.

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Authors: Pedro Llanos, Diego García

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This paper is addressed to expanding our understanding of the effects of hypoxia training on our bodies to better model its dynamics and leverage some of its implications and effects on human health. Hypoxia training is a recommended practice for military and civilian pilots that allow them to recognize their early hypoxia signs and symptoms, and Scientist Astronaut Candidates (SACs) who underwent hypobaric hypoxia (HH) exposure as part of a training activity for prospective suborbital flight applications. This observational-analytical study describes physiologic responses and symptoms experienced by a SAC group before, during and after HH exposure and proposes a model for assessing predicted versus observed physiological responses. A group of individuals with diverse Science Technology Engineering Mathematics (STEM) backgrounds conducted a hypobaric training session to an altitude up to 22,000 ft (FL220) or 6,705 meters, where heart rate (HR), breathing rate (BR) and core temperature (Tc) were monitored with the use of a chest strap sensor pre and post HH exposure. A pulse oximeter registered levels of saturation of oxygen (SpO₂), number and duration of desaturations during the HH chamber flight. Hypoxia symptoms as described by the SACs during the HH training session were also registered. This data allowed to generate a preliminary predictive model of the oxygen desaturation and O₂ pressure curve for each subject, which consists of a sixth-order polynomial fit during exposure, and a fifth or fourth-order polynomial fit during recovery. Data analysis showed that HR and BR showed no significant differences between pre and post HH exposure in most of the SACs, while Tc measures showed slight but consistent decrement changes. All subjects registered SpO₂ greater than 94% for the majority of their individual HH exposures, but all of them presented at least one clinically significant desaturation (SpO₂ < 85% for more than 5 seconds) and half of the individuals showed SpO₂ below 87% for at least 30% of their HH exposure time. Finally, real time collection of HH symptoms presented temperature somatosensory perceptions (SP) for 65% of individuals, and task-focus issues for 52.5% of individuals as the most common HH indications. 95% of the subjects experienced HH onset symptoms below FL180; all participants achieved full recovery of HH symptoms within 1 minute of donning their O₂ mask. The current HH study performed on this group of individuals suggests a rapid and fully reversible physiologic response after HH exposure as expected and obtained in previous studies. Our data showed consistent results between predicted versus observed SpO₂ curves during HH suggesting a mathematical function that may be used to model HH performance deficiencies. During the HH study, real-time HH symptoms were registered providing evidenced SP and task focusing as the earliest and most common indicators. Finally, an assessment of HH signs of symptoms in a group of heterogeneous, non-pilot individuals showed similar results to previous studies in homogeneous populations of pilots.

Keywords: Altitude sickness, cabin pressure, hypobaric chamber training, symptoms and altitude, slow onset hypoxia.

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Authors: Umm-e- Kalsoom, M. Arshad, Sadia Iqbal, M. Usman, M. Adnan

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The research study evaluated the performance of irrigation system by using special scientific tools like Remote Sensing and GIS technology, so that proper measurements could be taken for the sustainable agriculture and water management. Different performance evaluation parameters had been calculated for the purposed data was gathered from field investigation and different government and private organizations. According to the calculations, organic matter ranges from 0.19% (low value) to 0.76% (high value). In flat irrigation system for wheat yield ranges from 3347.16 to 5260.39 kg/ha, while the total water applied to wheat crop ranges from 252.94 to 279.19 mm and WUE ranges from 13.07 to 18.37 kg/ha/mm. For rice yield ranges from 3347.47 to 5433.07 kg/ha with total water supplied to rice crop ranges from 764.71 to 978.15 mm and WUE ranges from 3.49 to 5.71 kg/ha/mm. Similarly, in raised bed system wheat yield ranges from 4569.13 to 6008.60 kg/ha, total water supplied ranges from 158.87 to 185.09 mm and WUE ranges from 27.20 to 33.54 kg/ha/mm while in rice crop, yield ranges from 5285.04 to 6716.69 kg/ha, total water supplied ranges from 600.72 to 755.06 mm and WUE ranges from 6.41 to 10.05 kg/ha/mm. Almost 51.3% water saving is observed in bed irrigation system as compared to flat system. Less water supplied to beds is more affective as its WUE value is higher than flat system where more water is supplied in both the seasons. Similarly, RWS values show that maximum water deficit while minimum area is getting adequate water supply. Greater yield is recorded in bed system as plant per square meter is more in bed system in comparison of flat system Thus, the integration of GIS tools to regularly compute performance indices could provide irrigation managers with the means for managing efficiently the irrigation system.

Keywords: Field survey, Relative Water Supply (RWS), Remote sensing maps, Water Use Efficiency (WUE).

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Authors: Mohammad Hasan Raouf, Ahmad Rouhani, Mohammad Abedini, Ebrahim Rasooli Anarmarzi

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In this paper the application of a hierarchical fuzzy system (HFS) based on MPSS and SVC in multi-machine environment is studied. Also the effect of communication lines active power variance signal between two ΔP_Tie-line regions, as one of the inputs of hierarchical fuzzy multi-input PSS and SVC (HFMPSS & SVC), on the increase of low frequency oscillation damping is examined. In the MPSS, to have better efficiency an auxiliary signal of reactive power deviation (ΔQ) is added with ΔP+ Δω input type PSS. The number of rules grows exponentially with the number of variables in a classic fuzzy system. To reduce the number of rules the HFS consists of a number of low-dimensional fuzzy systems in a hierarchical structure. Phasor model of SVC is described and used in this paper. The performances of MPSS and ΔP_Tie-line based HFMPSS and also the proposed method in damping inter-area mode of oscillation are examined in response to disturbances. The efficiency of the proposed model is examined by simulating a four-machine power system. Results show that the proposed method is performing satisfactorily within the whole range of disturbances and reduces the cost of system.

Keywords: Communication lines active power variance signal, Hierarchical fuzzy system (HFS), Multi-input power system stabilizer (MPSS), Static VAR compensator (SVC).

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Authors: Ofelia A. Damag

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The study was focused on the development and assessment of the illustrated language activities of the 1996 Edition of the Portage Guide to Early Education. It determined the extent of appropriateness, applicability, time efficiency and aesthetics of the illustrated language activities to be used as instructional material not only by teachers, but parents and caregivers as well. The eclectic research design was applied in this study using qualitative and quantitative methods. To determine the applicability and time efficiency of the study, a try out was done. Since the eclectic research design was used, it made use of a researcher-made survey questionnaire and focus group discussion. Analysis of the data was done through weighted mean and ANOVA. The respondents of the study were representatives of Special Education (SPED) teachers, caregivers and parents of a special-needs child, particularly with difficulties in learning basic language skills. The results of the study show that a large number of respondents are SPED teachers and caregivers and are mostly college graduates. Many of them have earned units towards Master’s studies. Moreover, a majority of the respondents have not attended seminars or in-service training in early intervention for them to be more competent in the area of specialization. It is concluded that the illustrated language activities under review in this study are appropriate, applicable, time efficient and aesthetic for use as a tool in teaching. The recommendations are focused on the advocacy for SPED teachers, caregivers and parents of special-needs children to be more consistent in the implementation of the new instructional materials as an aid in an intervention program.

Keywords: Illustrated language activities, inclusion, portage guide to early education, special educational needs.

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Authors: Hidefumi Kawakatsu, Dong Li, Kosuke Kato

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In Japan, meat-type chickens are mainly classified into three categories: (1) Broilers, (2) Branded chickens, and (3) Jidori (Free-range local traditional pedigree chickens). The Jidori chickens are certified by the Japanese Ministry of Agriculture, whilst, for the Branded chickens, there is no regulation with respect to their breed (genotype) or methods for rearing them. It is, therefore, relatively easy for poultry farmers to introduce Branded than Jidori chickens. The Branded chickens are normally fed a low-calorie diet with ingredients such as herbs, which lengthens their breeding period (compared with that of the Broilers) and increases their market value. In the field of inventory management, fast-growing animals such as broilers are categorised as ameliorating items. To the best of our knowledge, there are no previous studies that have explicitly considered smaller sized poultry farmers with limited breeding areas. This study develops an inventory model for a small sized poultry farmer that produces both the Broilers (Product 1) and the Branded chickens (Product 2) with different amelioration rates. The poultry farmer’s total profit per unit of time is formulated as a function of selling prices by using a price-dependent demand function. The existence of a unique optimal selling price for each product, which maximises the total profit, established. It has also been confirmed through numerical examples that, when the breeding area is fixed, the total profit could increase if the poultry farmer reduced the product quantity of Product 1 to introduce Product 2.

Keywords: Amelioration, deterioration, small sized poultry farmers, optimal price.

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Authors: Yun-na Wu, Zhen Wang

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Due to the economic downturn and the deterioration of the living environment, the development of residential buildings as high energy consuming building is gradually changing from “extensive” to green building in China. So, the evaluation system of green building is continuously improved, but the current evaluation work has the following problems: (1) There are differences in the cost of the actual investment and the purchasing power of residents, also construction target of green residential building is single and lacks multi-objective performance development. (2) Green building evaluation lacks regional characteristics and cannot reflect the different regional residents demand. (3) In the process of determining the criteria weight, the experts’ judgment matrix is difficult to meet the requirement of consistency. Therefore, to solve those problems, questionnaires which are about the green residential building for Ningxia area are distributed, and the results of questionnaires can feedback the purchasing power of residents and the acceptance of the green building cost. Secondly, combined with the geographical features of Ningxia minority areas, the evaluation criteria system of green residential building is constructed. Finally, using the improved group AHP method and the grey clustering method, the criteria weight is determined, and a real case is evaluated, which is located in Xing Qing district, Ningxia. A conclusion can be obtained that the professional evaluation for this project and good social recognition is basically the same.

Keywords: Evaluation, green residential building, grey clustering method, group AHP.

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Authors: Dinesh Acharya U., N. V. Subba Reddy, Krishnamoorthi Makkithaya

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The recognition of handwritten numeral is an important area of research for its applications in post office, banks and other organizations. This paper presents automatic recognition of handwritten Kannada numerals based on structural features. Five different types of features, namely, profile based 10-segment string, water reservoir; vertical and horizontal strokes, end points and average boundary length from the minimal bounding box are used in the recognition of numeral. The effect of each feature and their combination in the numeral classification is analyzed using nearest neighbor classifiers. It is common to combine multiple categories of features into a single feature vector for the classification. Instead, separate classifiers can be used to classify based on each visual feature individually and the final classification can be obtained based on the combination of separate base classification results. One popular approach is to combine the classifier results into a feature vector and leaving the decision to next level classifier. This method is extended to extract a better information, possibility distribution, from the base classifiers in resolving the conflicts among the classification results. Here, we use fuzzy k Nearest Neighbor (fuzzy k-NN) as base classifier for individual feature sets, the results of which together forms the feature vector for the final k Nearest Neighbor (k-NN) classifier. Testing is done, using different features, individually and in combination, on a database containing 1600 samples of different numerals and the results are compared with the results of different existing methods.

Keywords: Fuzzy k Nearest Neighbor, Multiple Classifiers, Numeral Recognition, Structural features.

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Authors: Olumide Simeon Ogunnusi, Shukor Abd Razak, Michael Kolade Adu

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Inter-agent communication manager facilitates communication among mobile agents via message passing mechanism. Until now, all Foundation for Intelligent Physical Agents (FIPA) compliant agent systems are capable of exchanging messages following the standard format of sending and receiving messages. Previous works tend to secure messages to be exchanged among a community of collaborative agents commissioned to perform specific tasks using cryptosystems. However, the approach is characterized by computational complexity due to the encryption and decryption processes required at the two ends. The proposed approach to secure agent communication allows only agents that are created by the host agent server to communicate via the agent communication channel provided by the host agent platform. These agents are assumed to be harmless. Therefore, to secure communication of legitimate agents from intrusion by external agents, a 2-phase policy enforcement system was developed. The first phase constrains the external agent to run only on the network server while the second phase confines the activities of the external agent to its execution environment. To implement the proposed policy, a controller agent was charged with the task of screening any external agent entering the local area network and preventing it from migrating to the agent execution host where the legitimate agents are running. On arrival of the external agent at the host network server, an introspector agent was charged to monitor and restrain its activities. This approach secures legitimate agent communication from Man-in-the Middle and Replay attacks.

Keywords: Agent communication, introspective agent, isolation of agent, policy enforcement system.

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Authors: Ilham Benali, Nasser Hajji, Nawfal Acha

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Given the fact that the pharmaceutical industry is a commonly studied sector in the context of innovation, the majority of innovation research is devoted to the developed markets known by high research and development (R&D) assets and intensive innovation. In contrast, in developing countries where R&D assets are very low, there is relatively little research to mention in the area of pharmaceutical sector innovation, characterized mainly by two principal elements which are the presence of foreign-owned firms and licensed manufacturing agreements between local firms and multinationals. With the scarcity of research in this field, this paper attempts to study the effect of these two elements on the firms’ innovation tendencies. Other traditional factors that influence innovation, which are the age and the size of the firm, the R&D activities and the market structure, revealed in the literature review, will be included in the study in order to try to make this work more exhaustive. The study starts by examining innovation tendency in pharmaceutical firms located in developing countries before analyzing the effect of foreign-owned firms and licensed manufacturing agreements between local firms and multinationals on technological, organizational and marketing innovation. Based on the related work and on the theoretical framework developed, there is a probability that foreign-owned firms and licensed manufacturing agreements between local firms and multinationals have a negative influence on technological innovation. The opposite effect is possible in the case of organizational and marketing innovation.

Keywords: Developing countries, foreign owned firms, innovation, licensed manufacturing agreements, pharmaceutical industry.

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Authors: N. Muthukumaran, R. Ravi

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The Simulation based VLSI Implementation of FELICS (Fast Efficient Lossless Image Compression System) Algorithm is proposed to provide the lossless image compression and is implemented in simulation oriented VLSI (Very Large Scale Integrated). To analysis the performance of Lossless image compression and to reduce the image without losing image quality and then implemented in VLSI based FELICS algorithm. In FELICS algorithm, which consists of simplified adjusted binary code for Image compression and these compression image is converted in pixel and then implemented in VLSI domain. This parameter is used to achieve high processing speed and minimize the area and power. The simplified adjusted binary code reduces the number of arithmetic operation and achieved high processing speed. The color difference preprocessing is also proposed to improve coding efficiency with simple arithmetic operation. Although VLSI based FELICS Algorithm provides effective solution for hardware architecture design for regular pipelining data flow parallelism with four stages. With two level parallelisms, consecutive pixels can be classified into even and odd samples and the individual hardware engine is dedicated for each one. This method can be further enhanced by multilevel parallelisms.

Keywords: Image compression, Pixel, Compression Ratio, Adjusted Binary code, Golumb Rice code, High Definition display, VLSI Implementation.

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Authors: PoiSim Khiew, MuiYen Ho, ThianKhoonTan, WeeSiong Chiu, Roslinda Shamsudin, Muhammad Azmi Abd-Hamid, ChinHua Chia

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In the present work, we have developed a symmetric electrochemical capacitor based on the nanostructured iron oxide (Fe3O4)-activated carbon (AC) nanocomposite materials. The physical properties of the nanocomposites were characterized by Scanning Electron Microscopy (SEM) and Brunauer-Emmett-Teller (BET) analysis. The electrochemical performances of the composite electrode in 1.0 M Na2SO3 and 1.0 M Na2SO4 aqueous solutions were evaluated using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The composite electrode with 4 wt% of iron oxide nanomaterials exhibits the highest capacitance of 86 F/g. The experimental results clearly indicate that the incorporation of iron oxide nanomaterials at low concentration to the composite can improve the capacitive performance, mainly attributed to the contribution of the pseudocapacitance charge storage mechanism and the enhancement on the effective surface area of the electrode. Nevertheless, there is an optimum threshold on the amount of iron oxide that needs to be incorporated into the composite system. When this optimum threshold is exceeded, the capacitive performance of the electrode starts to deteriorate, as a result of the undesired particle aggregation, which is clearly indicated in the SEM analysis. The electrochemical performance of the composite electrode is found to be superior when Na2SO3 is used as the electrolyte, if compared to the Na2SO4 solution. It is believed that Fe3O4 nanoparticles can provide favourable surface adsorption sites for sulphite (SO3 2-) anions which act as catalysts for subsequent redox and intercalation reactions.

Keywords: Metal oxide nanomaterials, Electrochemical Capacitor, Double Layer Capacitance, Pseduocapacitance

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Authors: N. H. Othman, N. Udin, M. Ishak, L. H. Shah

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This study focuses on the effect of pin taper tool ratio on friction stir welding of magnesium alloy AZ31. Two pieces of AZ31 alloy with thickness of 6 mm were friction stir welded by using the conventional milling machine. The shoulder diameter used in this experiment is fixed at 18 mm. The taper pin ratio used are varied at 6:6, 6:5, 6:4, 6:3, 6:2 and 6:1. The rotational speeds that were used in this study were 500 rpm, 1000 rpm and 1500 rpm, respectively. The welding speeds used are 150 mm/min, 200 mm/min and 250 mm/min. Microstructure observation of welded area was studied by using optical microscope. Equiaxed grains were observed at the TMAZ and stir zone indicating fully plastic deformation. Tool pin diameter ratio 6/1 causes low heat input to the material because of small contact surface between tool surface and stirred materials compared to other tool pin diameter ratio. The grain size of stir zone increased with increasing of ratio of rotational speed to transverse speed due to higher heat input. It is observed that worm hole is produced when excessive heat input is applied. To evaluate the mechanical properties of this specimen, tensile test was used in this study. Welded specimens using taper pin ratio 6:1 shows higher tensile strength compared to other taper pin ratio up to 204 MPa. Moreover, specimens using taper pin ratio 6:1 showed better tensile strength with 500 rpm of rotational speed and 150mm/min welding speed.

Keywords: Friction stir welding, magnesium AZ31, cylindrical taper tool, taper pin ratio.

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Authors: Ashok Kumar, Vinod Kumar

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Wireless Sensor Networks (WSNs) are used to monitor/observe vast inaccessible regions through deployment of large number of sensor nodes in the sensing area. For majority of WSN applications, the collected data needs to be combined with geographic information of its origin to make it useful for the user; information received from remote Sensor Nodes (SNs) that are several hops away from base station/sink is meaningless without knowledge of its source. In addition to this, location information of SNs can also be used to propose/develop new network protocols for WSNs to improve their energy efficiency and lifetime. In this paper, range free localization protocols for WSNs have been proposed. The proposed protocols are based on weighted centroid localization technique, where the edge weights of SNs are decided by utilizing fuzzy logic inference for received signal strength and link quality between the nodes. The fuzzification is carried out using (i) Mamdani, (ii) Sugeno, and (iii) Combined Mamdani Sugeno fuzzy logic inference. Simulation results demonstrate that proposed protocols provide better accuracy in node localization compared to conventional centroid based localization protocols despite presence of unintentional radio frequency interference from radio frequency (RF) sources operating in same frequency band.

Keywords: localization, range free, received signal strength, link quality indicator, Mamdani fuzzy logic inference, Sugeno fuzzy logic inference.

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Authors: Mohammad A. Khasawneh

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Asphalt concrete pavements gradually lose their skid resistance causing safety problems especially under wet conditions and high driving speeds. In order to enact the actual field polishing and wearing process of asphalt pavement surfaces in a laboratory setting, several laboratory-scale accelerated polishing devices were developed by different agencies. To mimic the actual process, friction and texture measuring devices are needed to quantify surface deterioration at different polishing intervals that reflect different stages of the pavement life. The test could still be considered lengthy and to some extent labor-intensive. Therefore, there is a need to come up with another method that can assist in investigating the bituminous pavement surface characteristics in a practical and time-efficient test procedure.

The purpose of this paper is to utilize a well-developed image analysis technique to characterize asphalt pavement surfaces without the need to use conventional friction and texture measuring devices in an attempt to shorten and simplify the polishing procedure in the lab.

Promising findings showed the possibility of using image analysis in lieu of the labor-sensitive-variable-in-nature friction and texture measurements. It was found that the exposed aggregate surface area of asphalt specimens made from limestone and gravel aggregates produced solid evidence of the validity of this method in describing asphalt pavement surfaces. Image analysis results correlated well with the British Pendulum Numbers (BPN), Polish Values (PV) and Mean Texture Depth (MTD) values.

Keywords: Friction, Image Analysis, Polishing, Statistical Analysis, Texture.

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Authors: B. Elshafei, X. Mao

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The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Keywords: Data fusion, Gaussian process regression, signal denoise, temporal extrapolation.

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Authors: Musarrat Jabeen

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Thoughtful intelligence offers a sustainable position to enhance the influence of decision-makers. Thoughtful Intelligence implies the understanding to realize the impact of one’s thoughts, words and actions on the survival, dignity and development of the individuals, groups and nations. Thoughtful intelligence has received minimal consideration in the area of Decision Support Systems, with an end goal to evaluate the quantity of knowledge and its viability. This pattern degraded the imbibed contribution of thoughtful intelligence required for sustainable decision making. Given the concern, this paper concentrates on the question: How to present a model of Thoughtful Decision Support System (TDSS)? The aim of this paper is to appreciate the concepts of thoughtful intelligence and insinuate a Decision Support System based on thoughtful intelligence. Thoughtful intelligence includes three dynamic competencies: i) Realization about long term impacts of decisions that are made in a specific time and space, ii) A great sense of taking actions, iii) Intense interconnectivity with people and nature and; seven associate competencies, of Righteousness, Purposefulness, Understanding, Contemplation, Sincerity, Mindfulness, and Nurturing. The study utilizes two methods: Focused group discussion to count prevailing Decision Support Systems; 70% results of focus group discussions found six decision support systems and the positive inexistence of thoughtful intelligence among decision support systems regarding sustainable decision making. Delphi focused on defining thoughtful intelligence to model (TDSS). 65% results helped to conceptualize (definition and description) of thoughtful intelligence. TDSS is offered here as an addition in the decision making literature. The clients are top leaders.

Keywords: Thoughtful intelligence, Sustainable decision making, Thoughtful decision support system.

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Authors: Yuki Irie, Shota Ogawa, Hitomi Kosugi, Hiromitsu Shinozaki

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Dropout rates in higher educational institutions pose significant challenges for both students and institutions, with poor mental health (MH) emerging as a key risk factor. Healthcare college students, including medical students, are particularly vulnerable to MH issues due to the demanding academic schedules they face. Poor mental health (MH) would be considered as a key risk factor for dropout from higher educational institutions that pose significant challenges for both students and institutions. And, inadequate food access (FA) has been related to poor MH. Given that targeted students may experience multiple risk factors for poor MH and vulnerable FA, the study aims to clarify the relationship between MH and FA to enhance student well-being. A cross-sectional design was used to explore the association between MH status and FA among 421 students (147 male, 274 female). Participants completed two questionnaires assessing MH and FA during winter 2022. The mean MH score was 6.7 ± 4.6, with higher scores indicating worse MH (max. score 27). While year-round FA showed no significant association with MH, FA during winter was significantly associated with MH (p = 0.01). Although car ownership did not directly impact MH, it was significantly associated with FA (p < 0.01), thus indirectly influencing MH. Our findings underscore the importance of FA in promoting MH, particularly during winter. Adopting a lifestyle that facilitates easier FA may be beneficial for MH, given its indirect association with MH outcomes. These insights emphasize the significance of addressing FA-related challenges to enhance student’s mental well-being.

Keywords: Mental health, food access, co-medical students, lifestyle.

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Authors: D. Goustouridis, A. Sideris, I. Sdrolias, G. Loizos, N.-Alexander Tatlas, S. M. Potirakis

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Both daily and long-term management of a heavy-duty vehicles and construction machinery fleet is an extremely complicated and hard to solve issue. This is mainly due to the diversity of the fleet vehicles – machinery, which concerns not only the vehicle types, but also their age/efficiency, as well as the fleet volume, which is often of the order of hundreds or even thousands of vehicles/machineries. In the present paper we present “InteligentLogger”, a holistic heavy-duty fleet management system covering a wide range of diverse fleet vehicles. This is based on specifically designed hardware and software for the automated vehicle health status and operational cost monitoring, for smart maintenance. InteligentLogger is characterized by high adaptability that permits to be tailored to practically any heavy-duty vehicle/machinery (of different technologies -modern or legacy- and of dissimilar uses). Contrary to conventional logistic systems, which are characterized by raised operational costs and often errors, InteligentLogger provides a cost-effective and reliable integrated solution for the e-management and e-maintenance of the fleet members. The InteligentLogger system offers the following unique features that guarantee successful heavy-duty vehicles/machineries fleet management: (a) Recording and storage of operating data of motorized construction machinery, in a reliable way and in real time, using specifically designed Internet of Things (IoT) sensor nodes that communicate through the available network infrastructures, e.g., 3G/LTE; (b) Use on any machine, regardless of its age, in a universal way; (c) Flexibility and complete customization both in terms of data collection, integration with 3rd party systems, as well as in terms of processing and drawing conclusions; (d) Validation, error reporting & correction, as well as update of the system’s database; (e) Artificial intelligence (AI) software, for processing information in real time, identifying out-of-normal behavior and generating alerts; (f) A MicroStrategy based enterprise BI, for modeling information and producing reports, dashboards, and alerts focusing on vehicles– machinery optimal usage, as well as maintenance and scraping policies; (g) Modular structure that allows low implementation costs in the basic fully functional version, but offers scalability without requiring a complete system upgrade.

Keywords: E-maintenance, predictive maintenance, IoT sensor nodes, cost optimization, artificial intelligence, heavy-duty vehicles.

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Authors: A.L. Seetharam, B.L. Udaya Simha

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The Bangalore City is facing the acute problem of pollution in the atmosphere due to the heavy increase in the traffic and developmental activities in recent years. The present study is an attempt in the direction to assess trend of the ambient air quality status of three stations, viz., AMCO Batteries Factory, Mysore Road, GRAPHITE INDIA FACTORY, KHB Industrial Area, Whitefield and Ananda Rao Circle, Gandhinagar with respect to some of the major criteria pollutants such as Total Suspended particular matter (SPM), Oxides of nitrogen (NOx), and Oxides of sulphur (SO2). The sites are representative of various kinds of growths viz., commercial, residential and industrial, prevailing in Bangalore, which are contributing to air pollution. The concentration of Sulphur Dioxide (SO2) at all locations showed a falling trend due to use of refined petrol and diesel in the recent years. The concentration of Oxides of nitrogen (NOx) showed an increasing trend but was within the permissible limits. The concentration of the Suspended particular matter (SPM) showed the mixed trend. The correlation between model and observed values is found to vary from 0.4 to 0.7 for SO2, 0.45 to 0.65 for NOx and 0.4 to 0.6 for SPM. About 80% of data is observed to fall within the error band of ±50%. Forecast test for the best fit models showed the same trend as actual values in most of the cases. However, the deviation observed in few cases could be attributed to change in quality of petro products, increase in the volume of traffic, introduction of LPG as fuel in many types of automobiles, poor condition of roads, prevailing meteorological conditions, etc.

Keywords: Bangalore, urban air pollution, time series analysis.

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Authors: Vijay Shankar, C.S.P. Ojha, K.S. Hari Prasad

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Maize and Indian mustard are significant crops in semi-arid climate zones of India. Improved water management requires precise scheduling of irrigation, which in turn requires an accurate computation of daily crop evapotranspiration (ETc). Daily crop evapotranspiration comes as a product of reference evapotranspiration (ET0) and the growth stage specific crop coefficients modified for daily variation. The first objective of present study is to develop crop coefficients Kc for Maize and Indian mustard. The estimated values of Kc for maize at the four crop growth stages (initial, development, mid-season, and late season) are 0.55, 1.08, 1.25, and 0.75, respectively, and for Indian mustard the Kc values at the four growth stages are 0.3, 0.6, 1.12, and 0.35, respectively. The second objective of the study is to compute daily crop evapotranspiration from ET0 and crop coefficients. Average daily ETc of maize varied from about 2.5 mm/d in the early growing period to > 6.5 mm/d at mid season. The peak ETc of maize is 8.3 mm/d and it occurred 64 days after sowing at the reproductive growth stage when leaf area index was 4.54. In the case of Indian mustard, average ETc is 1 mm/d at the initial stage, >1.8 mm/d at mid season and achieves a peak value of 2.12 mm/d on 56 days after sowing. Improved schedules of irrigation have been simulated based on daily crop evapo-transpiration and field measured data. Simulation shows a close match between modeled and field moisture status prevalent during crop season.

Keywords: Crop coefficient, Crop evapotranspiration, Field moisture, Irrigation Scheduling

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Authors: Djordjevic J. Sladjana, Djordjevic-Milošević B. Suzana, Milošević M. Slobodan

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The potential of biomass as a renewable energy source leads Serbia to be the top of European countries by the amount of available but unused biomass. Technologies for its use are available and ecologically acceptable. Moreover, they are not expensive high-tech solutions even for the poor investment environment of Serbia, while other options seem to be less achievable. From the other point of view, Serbia has a huge percentage of unused agriculture land. Agricultural production in Serbia languishes: a large share of agricultural land therefore remains untreated, and there is a significant proportion of degraded land. From all the above, biomass intended for energy production is becoming an increasingly important factor in the stabilization of agricultural activities. Orientation towards the growing bioenergy crops versus conventional crop cultivation becomes an interesting option. The aim of this paper is to point out the possibility of growing energy crops in accordance with the conditions and cultural practice in rural areas of Serbia. First of all, the cultivation of energy crops on lower quality land is being discussed, in order to revitalize the rural areas of crops through their inclusion into potential energy sector. Next is the theme of throwing more light on the increase in the area under this competitive agricultural production to correct land use in terms of climate change in Serbia. The goal of this paper is to point out the contribution of the share of biomass in energy production and consumption, and the effect of reducing the negative environmental impact.

Keywords: Agro-energy crops, conditions for plantation, revitalization of rural areas, degraded and unused soils.

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Authors: Srinivasan Chandrasekaran, Thailammai Chithambaram, Shihas A. Khader

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The early-stage damage detection in offshore structures requires continuous structural health monitoring and for the large area the position of sensors will also plays an important role in the efficient damage detection. Determining the dynamic behavior of offshore structures requires dense deployment of sensors. The wired Structural Health Monitoring (SHM) systems are highly expensive and always needs larger installation space to deploy. Wireless sensor networks can enhance the SHM system by deployment of scalable sensor network, which consumes lesser space. This paper presents the results of wireless sensor network based Structural Health Monitoring method applied to a scaled experimental model of offshore structure that underwent wave loading. This method determines the serviceability of the offshore structure which is subjected to various environment loads. Wired and wireless sensors were installed in the model and the response of the scaled BLSRP model under wave loading was recorded. The wireless system discussed in this study is the Raspberry pi board with Arm V6 processor which is programmed to transmit the data acquired by the sensor to the server using Wi-Fi adapter, the data is then hosted in the webpage. The data acquired from the wireless and wired SHM systems were compared and the design of the wireless system is verified.

Keywords: Condition assessment, damage detection, structural health monitoring, structural response, wireless sensor network.

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Authors: Atiqul Islam, Shamim Akhter, Tumnun E. Mursalin

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Least Development Countries (LDC) like Bangladesh, whose 25% revenue earning is achieved from Textile export, requires producing less defective textile for minimizing production cost and time. Inspection processes done on these industries are mostly manual and time consuming. To reduce error on identifying fabric defects requires more automotive and accurate inspection process. Considering this lacking, this research implements a Textile Defect Recognizer which uses computer vision methodology with the combination of multi-layer neural networks to identify four classifications of textile defects. The recognizer, suitable for LDC countries, identifies the fabric defects within economical cost and produces less error prone inspection system in real time. In order to generate input set for the neural network, primarily the recognizer captures digital fabric images by image acquisition device and converts the RGB images into binary images by restoration process and local threshold techniques. Later, the output of the processed image, the area of the faulty portion, the number of objects of the image and the sharp factor of the image, are feed backed as an input layer to the neural network which uses back propagation algorithm to compute the weighted factors and generates the desired classifications of defects as an output.

Keywords: Computer vision, image acquisition device, machine vision, multi-layer neural networks.

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Authors: A. Knezović

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21st century has transformed the labor market landscape in a way of posing new and different demands on university graduates as well as university lecturers, which means that the knowledge and academic skills students acquire in the course of their studies should be applicable and transferable from the higher education context to their future professional careers. Given the context of the Languages for Specific Purposes (LSP) classroom, the teachers’ objective is not only to teach the language itself, but also to prepare students to use that language as a medium to develop generic skills and competences. These include media and information literacy, critical and creative thinking, problem-solving and analytical skills, effective written and oral communication, as well as collaborative work and social skills, all of which are necessary to make university graduates more competitive in everyday professional environments. On the other hand, due to limitations of time and large numbers of students in classes, the frequently topic-centered syllabus of LSP courses places considerable focus on acquiring the subject matter and specialist vocabulary instead of sufficient development of skills and competences required by students’ prospective employers. This paper intends to explore some of those issues as viewed both by LSP lecturers and by business professionals in their respective surveys. The surveys were conducted among more than 50 LSP lecturers at higher education institutions in Croatia, more than 40 HR professionals and more than 60 university graduates with degrees in economics and/or business working in management positions in mainly large and medium-sized companies in Croatia. Various elements of LSP course content have been taken into consideration in this research, including reading and listening comprehension of specialist texts, acquisition of specialist vocabulary and grammatical structures, as well as presentation and negotiation skills. The ability to hold meetings, conduct business correspondence, write reports, academic texts, case studies and take part in debates were also taken into consideration, as well as informal business communication, business etiquette and core courses delivered in a foreign language. The results of the surveys conducted among LSP lecturers will be analyzed with reference to what extent those elements are included in their courses and how consistently and thoroughly they are evaluated according to their course requirements. Their opinions will be compared to the results of the surveys conducted among professionals from a range of industries in Croatia so as to examine how useful and important they perceive the same elements of the LSP course content in their working environments. Such comparative analysis will thus show to what extent the syllabi of LSP courses meet the demands of the employment market when it comes to the students’ language skills and competences, as well as transferable skills. Finally, the findings will also be compared to the observations based on practical teaching experience and the relevant sources that have been used in this research. In conclusion, the ideas and observations in this paper are merely open-ended questions that do not have conclusive answers, but might prompt LSP lecturers to re-evaluate the content and objectives of their course syllabi.

Keywords: Languages for specific purposes (LSP), language skills, topic-centered syllabus, transferable skills.

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Authors: K. Aravindhan, Trishit Bandyopadhyay, Mahesh Mehendale, Supriya Kumar De

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The inherent iterative nature of product design and development poses significant challenge to reduce the product design and development time (PD). In order to shorten the time to market, organizations have adopted concurrent development where multiple specialized tasks and design activities are carried out in parallel. Iterative nature of work coupled with the overlap of activities can result in unpredictable time to completion and significant rework. Many of the products have missed the time to market window due to unanticipated or rather unplanned iteration and rework. The iterative and often overlapped processes introduce greater amounts of ambiguity in design and development, where the traditional methods and tools of project management provide less value. In this context, identifying critical metrics to understand the iteration probability is an open research area where significant contribution can be made given that iteration has been the key driver of cost and schedule risk in PD projects. Two important questions that the proposed study attempts to address are: Can we predict and identify the number of iterations in a product development flow? Can we provide managerial insights for a better control over iteration? The proposal introduces the concept of decision points and using this concept intends to develop metrics that can provide managerial insights into iteration predictability. By characterizing the product development flow as a network of decision points, the proposed research intends to delve further into iteration probability and attempts to provide more clarity.

Keywords: Decision Points, Iteration, Product Design, Rework.

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Authors: S. M. Giripunje, Shikha Jindal

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Zinc sulphide (ZnS) quantum dots (QDs) were synthesized successfully via simple sonochemical method. X-ray diffraction (XRD), scanning electron microscopy (SEM) and high resolution transmission electron microscopy (HRTEM) analysis revealed the average size of QDs of the order of 3.7 nm. The band gap of the QDs was tuned to 5.2 eV by optimizing the synthesis parameters. UV-Vis absorption spectra of ZnS QD confirm the quantum confinement effect. Fourier transform infrared (FTIR) analysis confirmed the formation of single phase ZnS QDs. To fabricate the diode, blend of ZnS QDs and P3HT was prepared and the heterojunction of PEDOT:PSS and the blend was formed by spin coating on indium tin oxide (ITO) coated glass substrate. The diode behaviour of the heterojunction was analysed, wherein the ideality factor was found to be 2.53 with turn on voltage 0.75 V and the barrier height was found to be 1.429 eV. ZnS-Graphene QDs nanocomposite was characterised for the surface morphological study. It was found that the synthesized ZnS QDs appear as quasi spherical particles on the graphene sheets. The average particle size of ZnS-graphene nanocomposite QDs was found to be 8.4 nm. From voltage-current characteristics of ZnS-graphene nanocomposites, it is observed that the conductivity of the composite increases by 10⁴ times the conductivity of ZnS QDs. Thus the addition of graphene QDs in ZnS QDs enhances the mobility of the charge carriers in the composite material. Thus, the graphene QDs, with high specific area for a large interface, high mobility and tunable band gap, show a great potential as an electron-acceptors in photovoltaic devices.

Keywords: Graphene, mobility, nanocomposites, photovoltaics, quantum dots, zinc sulphide.

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Authors: María-Dolores Afonso-Suárez, Nayra Pumar-Carreras, Juan Ruiz-Alzola

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This research addresses the use of an e-Learning creation methodology for learning objects. Throughout the process, indicators are being gathered, to determine if it responds to the main objectives of an engineering discipline. These parameters will also indicate if it is necessary to review the creation cycle and readjust any phase. Within the project developed for this study, apart from the use of structured methods, there has been a central objective: the establishment of a learning atmosphere. A place where all the professionals involved are able to collaborate, plan, solve problems and determine guides to follow in order to develop creative and innovative solutions. It has been outlined as a blended learning program with an assessment plan that proposes face to face lessons, coaching, collaboration, multimedia and web based learning objects as well as support resources. The project has been drawn as a long term task, the pilot teaching actions designed provide the preliminary results object of study. This methodology is been used in the creation of learning content for the African countries of Senegal, Mauritania and Cape Verde. It has been developed within the framework of the MACbioIDi, an Interreg European project for the International cooperation and development. The educational area of this project is focused in the training and advice of professionals of the medicine as well as engineers in the use of applications of medical imaging technology, specifically the 3DSlicer application and the Open Anatomy Browser.

Keywords: Teaching contents engineering, e-learning, blended learning, international cooperation, 3DSlicer, open anatomy browser.

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Authors: Brian H. Marsh

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Nitrogen fertilizer is the most used and often the most mismanaged nutrient input. Nitrogen management has tremendous implications on crop productivity, quality and environmental stewardship. Sufficient nitrogen is needed to optimum yield and quality. Soil and in-season plant tissue testing for nitrogen status are a time consuming and expensive process. Real time sensing of plant nitrogen status can be a useful tool in managing nitrogen inputs. The objectives of this project were to assess the reliability of remotely sensed non-destructive plant nitrogen measurements compared to wet chemistry data from sampled plant tissue, develop in-season nitrogen recommendations based on remotely sensed data for improved nitrogen use efficiency and assess the potential for determining yield and quality from remotely sensed data. Very good correlations were observed between early-season remotely sensed crop nitrogen status and plant nitrogen concentrations and subsequent in-season fertilizer recommendations. The transmittance/absorbance type meters gave the most accurate readings. Early in-season fertilizer recommendation would be to apply 40 kg nitrogen per hectare plus 15 kg nitrogen per hectare for each unit difference measured with the SPAD meter between the crop and reference area or 25 kg plus 13 kg per hectare for each unit difference measured with the CCM 200. Once the crop was sufficiently fertilized meter readings became inconclusive and were of no benefit for determining nitrogen status, silage yield and quality and grain yield and protein.

Keywords: Wheat, nitrogen fertilization, chlorophyll meter.

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Authors: Kanthida Kusonmano, Michael Netzer, Bernhard Pfeifer, Christian Baumgartner, Klaus R. Liedl, Armin Graber

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Availability of high dimensional biological datasets such as from gene expression, proteomic, and metabolic experiments can be leveraged for the diagnosis and prognosis of diseases. Many classification methods in this area have been studied to predict disease states and separate between predefined classes such as patients with a special disease versus healthy controls. However, most of the existing research only focuses on a specific dataset. There is a lack of generic comparison between classifiers, which might provide a guideline for biologists or bioinformaticians to select the proper algorithm for new datasets. In this study, we compare the performance of popular classifiers, which are Support Vector Machine (SVM), Logistic Regression, k-Nearest Neighbor (k-NN), Naive Bayes, Decision Tree, and Random Forest based on mock datasets. We mimic common biological scenarios simulating various proportions of real discriminating biomarkers and different effect sizes thereof. The result shows that SVM performs quite stable and reaches a higher AUC compared to other methods. This may be explained due to the ability of SVM to minimize the probability of error. Moreover, Decision Tree with its good applicability for diagnosis and prognosis shows good performance in our experimental setup. Logistic Regression and Random Forest, however, strongly depend on the ratio of discriminators and perform better when having a higher number of discriminators.

Keywords: Classification, High dimensional data, Machine learning

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