Search results for: electrochemical performance

Authors: Endalkachew Abebe Kebede, Bojin Bojinov, Andon Vasilev Andonov, Orhan Dengiz

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Remote sensing has a potential application in assessing and monitoring the plants' biophysical properties using the spectral responses of plants and soils within the electromagnetic spectrum. However, only a few reports compare the performance of different remote sensing sensors against in-situ field spectral measurement. The current study assessed the potential applications of open data source satellite images (Sentinel 2 and Landsat 9) in estimating the biophysical properties of the wheat crop on a study farm found in the village of OvchaMogila. A Landsat 9 (30 m resolution) and Sentinel-2 (10 m resolution) satellite images with less than 10% cloud cover have been extracted from the open data sources for the period of December 2021 to April 2022. An Unmanned Aerial Vehicle (UAV) has been used to capture the spectral response of plant leaves. In addition, SpectraVue 710s Leaf Spectrometer was used to measure the spectral response of the crop in April at five different locations within the same field. The ten most common vegetation indices have been selected and calculated based on the reflectance wavelength range of remote sensing tools used. The soil samples have been collected in eight different locations within the farm plot. The different physicochemical properties of the soil (pH, texture, N, P₂O₅, and K₂O) have been analyzed in the laboratory. The finer resolution images from the UAV and the Leaf Spectrometer have been used to validate the satellite images. The performance of different sensors has been compared based on the measured leaf spectral response and the extracted vegetation indices using the five sampling points. A scatter plot with the coefficient of determination (R2) and Root Mean Square Error (RMSE) and the correlation (r) matrix prepared using the corr and heatmap python libraries have been used for comparing the performance of Sentinel 2 and Landsat 9 VIs compared to the drone and SpectraVue 710s spectrophotometer. The soil analysis revealed the study farm plot is slightly alkaline (8.4 to 8.52). The soil texture of the study farm is dominantly Clay and Clay Loam.The vegetation indices (VIs) increased linearly with the growth of the plant. Both the scatter plot and the correlation matrix showed that Sentinel 2 vegetation indices have a relatively better correlation with the vegetation indices of the Buteo dronecompared to the Landsat 9. The Landsat 9 vegetation indices somewhat align better with the leaf spectrometer. Generally, the Sentinel 2 showed a better performance than the Landsat 9. Further study with enough field spectral sampling and repeated UAV imaging is required to improve the quality of the current study.

Keywords: landsat 9, leaf spectrometer, sentinel 2, UAV

Procedia PDF Downloads 107

Authors: Dalhatu, Musa Yusha’u, Shuaibu Sidi Safiyanu, Haliru Musa Hussaini

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This study examined budget and performance of public enterprises in Nasarawa State, Nigeria in a period of 2009-2013. The study utilized secondary sources of data obtained from four selected parastatals’ budget allocation and revenue generation for the period under review. The simple correlation coefficient was used to analyze the extent of the relationship between budget allocation and revenue generation of the parastatals. Findings revealed varying results. There was positive (0.21) and weak correlation between expenditure and revenue of Nasarawa Investment and Property Development Company (NIPDC). However, the study further revealed that there was strong and weak negative relationship in the revenue and expenditure of the following parastatals over the period under review. Viz: Nasarawa State Water Board, -0.27 (weak), Nasarawa State Broadcasting Service, -0.52 (Strong) and Nasarawa State College of Agriculture, -0.36 (weak). The study therefore, recommends that government should increase its investments in NIPDC to enhance efficiency and profitability. It also recommends that government should strengthen its fiscal responsibility, accountability and transparency in public parastatals.

Keywords: budget, public enterprises, revenue, enterprise

Procedia PDF Downloads 260

Authors: J. Lu, H. Li, F. Cole

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This paper proposes a high-frequency rotary transformer (HFRT) for a separately excited synchronous machine (SESM) used in a flywheel energy storage system. The SESM can eliminate and reduce rare earth permanent magnet (REPM) usage and provide a better performance in renewable energy systems. However, the major drawback of such SESM is the necessity of brushes and slip rings to supply the field current, which increases the maintenance cost and operation reliability. To overcome these problems, an HFRT integrated with SiC semiconductor devices can replace brushes and slip rings in the SESM. The proposed HFRT features a high-frequency magnetic ferrite for both the stationary part as the transformer primary and the rotating part as the transformer secondary, as well as an air gap, allowing safe operation at high rotational speeds. Hence, this rotary transformer can enable the adoption of a wound rotor synchronous machine (WRSM). The HFRT, working at over 100kHz operating frequency, exhibits excellent performance of power efficiency and significant size reduction. The experimental validations to support the theoretical findings have been provided.

Keywords: brushes and slip rings, flywheel energy storage, high frequency rotary transformer, separately excited synchronous machine

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

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

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

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Authors: Cherifi Mehdi, Lahdir Mourad, Ameur Soltane

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Image compression is used to reduce the number of bits required to represent an image. The Meteosat Second Generation satellite (MSG) allows the acquisition of 12 image files every 15 minutes. Which results a large databases sizes. The transform selected in the images compression should contribute to reduce the data representing the images. The Radon transform retrieves the Radon points that represent the sum of the pixels in a given angle for each direction. Linear predictive coding (LPC) with filtering provides a good decorrelation of Radon points using a Predictor constitute by the Symmetric Nearest Neighbor filter (SNN) coefficients, which result losses during decompression. Finally, Run Length Coding (RLC) gives us a high and fixed compression ratio regardless of the input image. In this paper, a novel image compression method based on the Radon transform and linear predictive coding (LPC) for MSG images is proposed. MSG image compression based on the Radon transform and the LPC provides a good compromise between compression and quality of reconstruction. A comparison of our method with other whose two based on DCT and one on DWT bi-orthogonal filtering is evaluated to show the power of the Radon transform in its resistibility against the quantization noise and to evaluate the performance of our method. Evaluation criteria like PSNR and the compression ratio allows showing the efficiency of our method of compression.

Keywords: image compression, radon transform, linear predictive coding (LPC), run lengthcoding (RLC), meteosat second generation (MSG)

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

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

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

Procedia PDF Downloads 581

Authors: Souad Romdhane, Lotfi Belkacem

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When referring to actuarial analysis of lifetime, only models accounting for observable risk factors have been developed. Within this context, Cox proportional hazards model (CPH model) is commonly used to assess the effects of observable covariates as gender, age, smoking habits, on the hazard rates. These covariates may fail to fully account for the true lifetime interval. This may be due to the existence of another random variable (frailty) that is still being ignored. The aim of this paper is to examine the shared frailty issue in the Cox proportional hazard model by including two different parametric forms of frailty into the hazard function. Four estimated methods are used to fit them. The performance of the parameter estimates is assessed and compared between the classical Cox model and these frailty models through a real-life data set from the Quebec Pension Plan and then using a more general simulation study. This performance is investigated in terms of the bias of point estimates and their empirical standard errors in both fixed and random effect parts. Both the simulation and the real dataset studies showed differences between classical Cox model and shared frailty model.

Keywords: life insurance-pension plan, survival analysis, risk factors, cox proportional hazards model, multivariate failure-time data, shared frailty, simulations study

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Authors: A. M. Wahab, E. Rustighi

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Elastomeric dielectric material has recently become a new alternative for actuator technology. The characteristics of dielectric elastomers placed between two electrodes to withstand large strain when electrodes are charged has attracted the attention of many researcher to study this material for actuator technology. Thus, in the past few years Danfoss Ventures A/S has established their own dielectric electro-active polymer (DEAP), which was called PolyPower. The main objective of this work was to investigate the dynamic characteristics for vibration control of a PolyPower actuator folded in ‘pull’ configuration. A range of experiments was carried out on the folded actuator including passive (without electrical load) and active (with electrical load) testing. For both categories static and dynamic testing have been done to determine the behavior of folded DEAP actuator. Voltage-Strain experiments show that the DEAP folded actuator is a non-linear system. It is also shown that the voltage supplied has no effect on the natural frequency. Finally, varying AC voltage with different amplitude and frequency shows the parameters that influence the performance of DEAP folded actuator. As a result, the actuator performance dominated by the frequency dependence of the elastic response and was less influenced by dielectric properties.

Keywords: dielectric electro-active polymer, pull actuator, static, dynamic, electromechanical

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Authors: Sunbul Jassim Hamodi, Muna Khalid Khudayer, Firas Muzahem Hussein

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The experiment was conducted to study the effect of supplement sources of Phytase enzyme (bacterial, fungal, enzymes mixture) using levels (250, 500, 750) FTY/ kg feed to diets compared with control on the performance for one thousand fifty broiler chicks (Ross 308) from 1day old with initial weight 39.78 gm till 42 days. The study involved 10 treatments, three replicates per treatment (35 chicks/replicate). Treatments were as follows: T1: control diet (without any addition). T2: added bacterial phytase enzyme 250FTY/ kg feed. T3: added bacterial phytase enzyme 500FTY/ kg feed. T4: added bacterial phytase enzyme 750FTY/ kg feed. T5: added fungal phytase enzyme 250FTY/ kg feed. T6: added fungal phytase enzyme 500FTY/ kg feed. T7: added fungal phytase enzyme 750FTY/ kg feed. T8 added enzymes mixture 250U/ kg feed. T9: added enzymes mixture 500U/ kg feed. T10: added enzymes mixture 750U/ kg feed. The results revealed that supplementing 750 U from enzymes mixture to broiler diet increased significantly (p <0.05) body weight compared with (250 FTY bacterial phytase/Kgfeed), (750 FTY bacterial phytase/Kg feed), (750FTY fungal phytase/Kgfeed) at 6 weeks, also supplemented different sources and levels from phytase enzyme improved a cumulative weight gain for (500 FTY bacterial phytase/Kgfeed), (250FTY fungal phytase/Kgfeed), (500FTY fungal phytase/Kgfeed), (250 Uenzymes mixture/Kgfeed), (500 Uenzymes mixture/Kgfeed) and (750 U enzymes mixture/Kgfeed) treatments compared with (750 FTY fungal phytase/Kgfeed)treatment, about accumulative feed consumption (500 FTY fungal phytase/Kgfeed) and (250 Uenzymes mixture/Kgfeed) increased significantly compared with control group and (750FTY fungal phytase/Kgfeed) during 1-6 weeks. There were significantly improved in cumulative feed conversion for (500U enzymes mixture/Kgfeed) compared with the worse feed conversion ratio that recorded in (250 FTY bacterial phytase/Kgfeed). No significant differences between treatments in internal organs relative weights, carcass cuts, dressing percentage and production index. Mortality was increased in (750FTY fungal phytase/Kgfeed) compared with other treatments.

Keywords: phytase, phytic acid, broiler, productive performance

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Authors: Mingwei Yi, Liujie Guo, Zongjun Pan, Xiang Lin, Xiaoming Yi

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With the rapid expansion of road construction mileage in China, the scale of road maintenance needs has concurrently escalated. As the service life of roads extends, the design of pavement repair and maintenance emerges as a crucial component in preserving the excellent performance of the pavement. The remaining service life of asphalt pavement structure is a vital parameter in the lifecycle maintenance design of asphalt pavements. Based on an analysis of pavement structural integrity, this study introduces a characterization and assessment of the remaining life of existing asphalt pavement structures. It proposes indicators such as the transverse crack spacing and the length of longitudinal cracks. The transverse crack spacing decreases with an increase in maintenance intervals and with the extended use of semi-rigid base layer structures, although this trend becomes less pronounced after maintenance intervals exceed 4 years. The length of longitudinal cracks increases with longer maintenance intervals, but this trend weakens after five years. This system can support the enhancement of standardization and scientific design in highway maintenance decision-making processes.

Keywords: structural integrity, highways, pavement evaluation, asphalt concrete pavement

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Authors: Y. Lu, L. Liu, J. Guo

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Monolayer graphene and dichaclogenide semiconductor materials attract extensive research interest for potential nanoelectronics applications. The ultimate scaling limit of double gate MoS2 Field-Effect-Transistors (FETs) with a monolayer thin body is examined and compared with ultra-thin-body Si FETs by using self-consistent quantum transport simulation in the presence of phonon scattering. Modelling of phonon scattering, quantum mechanical effects, and self-consistent electrostatics allows us to accurately assess the performance potential of monolayer MoS2 FETs. The results revealed that monolayer MoS2 FETs show 52% smaller Drain Induced Barrier Lowering (DIBL) and 13% Smaller Sub-Threshold Swing (SS) than 3 nm-thick-body Si FETs at a channel length of 10 nm with the same gating. With a requirement of SS<100mV/dec, the scaling limit of monolayer MoS2 FETs is assessed to be 5 nm, comparing with 8nm of the ultra-thin-body Si counterparts due to the monolayer thin body and higher effective mass which reduces direct source-to-drain tunnelling. By comparing with the ITRS target for high performance logic devices of 2023; double gate monolayer MoS2 FETs can fulfil the ITRS requirements.

Keywords: nanotransistors, monolayer 2D materials, quantum transport, scaling limit

Procedia PDF Downloads 235

Authors: Claudia Popescu, Adriana Mihaela Soaita

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Within the EU accession process, Romania, as well as other CEE countries, have embarked on the post-1990 urbanization wave aiming to reduce the gaps between ‘older’ and ‘new’ EU member states. While post-socialist urban transitions have been extensively scrutinized, little is known about the developing trajectories of these new towns across the CEE region. To start addressing this knowledge gap, we wish to bring to the fore one of the most humble expressions of urbanism, that of the small, new towns of Romania. Despite rural-to-urban reclassification, urbanization levels have remained persistently low over the last three decades. In this context, it is timely and legitimate to ask about the prospects of new towns for a ‘successful’ socioeconomic performance within the urban network and avoidance of precarity and marginalization and adequate measure of place performance within the urban/settlement network and understanding the drivers that trigger towns’ socioeconomic performances. To answer these, we create a socioeconomic index of the place in order to compare the profile of the 60 new towns with large cities, old small towns and rural. We conceive ‘successful’ and ‘precarious’ performance in terms of a locality’s index value being above or below all small towns’ index average. Second, we performed logistic regression to interrogate the relevance of some key structural factors to the new towns’ socioeconomic performance (i.e. population size, urban history, regional location, connectivity and political determination of their local governments). Related to the first research question, our findings highlight the precarity of place as a long-standing condition of living and working in the new towns of Romania, particularly evident through our cross-comparative analysis across key category along the rural-urban continuum. We have substantiated the socioeconomic condition of precarity in rural places, with the new towns still maintaining features of ‘rurality’ rather than ‘urbanity’ - except a few successful satellites of economically striving large cities, particularly the country capital of Bucharest, which benefited from spillover effects. Related to our second research question, we found that the new towns of Romania have significantly higher odds of being characterized by precarity as a socioeconomic condition than all other small towns and urban places, but less so compared to the even more marginalized rural areas. Many new towns contain resource-dependent rural communities with a poor response to the context of change. Therefore, issues pertaining to local capacity building to adapt to the new urban environment should be addressed by the spatial planning policy. Our approach allowed us to bring to the fore the idea of precarity as a condition of whole localities. Thinking of precarity of place is important as it brings the whole institutional and political apparatus of spatial planning, urban and regional, into conversation with other causative or substantive axes of precarity developed in the literature. We recommend future research on the new towns in Romania and elsewhere.

Keywords: politics of fantasy, precarity of place, urbanization, Romania

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Authors: Mohammad Besharatloo

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Intrusion detection is an important research topic in network security because of increasing growth in the use of computer network services. Intrusion detection is done with the aim of detecting the unauthorized use or abuse in the networks and systems by the intruders. Therefore, the intrusion detection system is an efficient tool to control the user's access through some predefined regulations. Since, the data used in intrusion detection system has high dimension, a proper representation is required to show the basis structure of this data. Therefore, it is necessary to eliminate the redundant features to create the best representation subset. In the proposed method, a hybrid model of differential evolution and firefly algorithms was employed to choose the best subset of properties. In addition, decision tree and support vector machine (SVM) are adopted to determine the quality of the selected properties. In the first, the sorted population is divided into two sub-populations. These optimization algorithms were implemented on these sub-populations, respectively. Then, these sub-populations are merged to create next repetition population. The performance evaluation of the proposed method is done based on KDD Cup99. The simulation results show that the proposed method has better performance than the other methods in this context.

Keywords: intrusion detection system, differential evolution, firefly algorithm, support vector machine, decision tree

Procedia PDF Downloads 91

Authors: Flora Paganelli

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The radiometric performance of remotely sensed images is important for volcanic monitoring. The Thermal Infrared Sensor (TIRS) on-board Landsat 8 was designed with specific requirements in regard to the noise-equivalent change in temperature (NEΔT) at ≤ 0.4 K at 300 K for the two thermal infrared bands B10 and B11. This study investigated the on-orbit NEΔT of the TIRS two bands from a scene-based method using clear-sky images over the volcanic activity of Kīlauea Volcano and the active East Rift Zone (Hawaii), in order to optimize the use of TIRS data. Results showed that the NEΔTs of the two bands exceeded the design specification by an order of magnitude at 300 K. Both separate bands and split window algorithm were examined to estimate the effect of NEΔT on the land surface temperature (LST) retrieval, and NEΔT contribution to the final LST error. These results were also useful in the current efforts to assess the requirements for volcanology research campaign using the Hyperspectral Infrared Imager (HyspIRI) whose airborne prototype MODIS/ASTER instruments is plan to be flown by NASA as a single campaign to the Hawaiian Islands in support of volcanology and coastal area monitoring in 2016.

Keywords: landsat 8, radiometric performance, thermal infrared sensor (TIRS), volcanology

Procedia PDF Downloads 241

Authors: Vilma Sasyte, Vilma Viliene, Asta Raceviciute-Stupeliene, Agila Dauksiene, Romas Gruzauskas, Virginijus Slausgalvis, Jamal Al-Saifi

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The aim of the present study was to investigate the effect of butyrate, acids, medium-chain fatty acids and plant extract mixture on performance, blood and gastrointestinal tract characteristics of laying hens’. For the period of 8 weeks, 24 Hisex Brown laying hens were randomly assigned to 2 dietary treatments: 1) control wheat-corn-soybean meal based diet (Control group), 2) control diet supplemented with the mixture of butyrate, acids, medium chain fatty acids and plant extract (Lumance®) at the level of 1.5 g/kg of feed (Experimental group). Hens were fed with a crumbled diet at 125 g per day. Housing and feeding conditions were the same for all groups and met the requirements of growth for laying hens of Hisex Brown strain. In the blood serum total protein, bilirubin, cholesterol, DTL- and MTL- cholesterol, triglycerides, glucose, GGT, GOT, GPT, alkaline phosphatase, alpha amylase, contents of c-reactive protein, uric acid, and lipase were analyzed. Development of intestines and internal organs (intestinal length, intestinal weight, the weight of glandular and muscular stomach, pancreas, heart, and liver) were determined. The concentration of short chain fatty acids in caecal content was measured using the method of HPLC. The results of the present study showed that 1.5 g/kg supplementation of feed additive affected egg production and feed conversion ratio for the production of 1 kg of egg mass. Dietary supplementation of analyzed additive in the diets increased the concentration of triglycerides, GOT, alkaline phosphatase and decreased uric acid content compared with the control group (P<0.05). No significant difference for others blood indices in comparison to the control was observed. The addition of feed additives in laying hens’ diets increased intestinal weight by 11% and liver weight by 14% compared with the control group (P<0.05). The short chain fatty acids (propionic, acetic and butyric acids) in the caecum of laying hens in experimental groups decreased compared with the control group. The supplementation of the mixture of butyrate, acids, medium-chain fatty acids and plant extract at the level of 1.5 g/kg in the laying hens’ diets had the effect on the performance, some gastrointestinal tract function and blood parameters of laying hens.

Keywords: acids, butyrate, laying hens, MCFA, performance, plant extract, psysiological state

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Authors: Umut Kokbas, Mustafa Nisari

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Immunoglobulins, also known as antibodies, are glycoprotein molecules produced by activated B cells that transform into plasma cells and result in them. Antibodies are critical molecules of the immune response to fight, which help the immune system specifically recognize and destroy antigens such as bacteria, viruses, and toxins. Immunoglobulin classes differ in their biological properties, structures, targets, functions, and distributions. Five major classes of antibodies have been identified in mammals: IgA, IgD, IgE, IgG, and IgM. Evaluation of the immunoglobulin isotype can provide a useful insight into the complex humoral immune response. Evaluation and knowledge of immunoglobulin structure and classes are also important for the selection and preparation of antibodies for immunoassays and other detection applications. The immunoglobulin test measures the level of certain immunoglobulins in the blood. IgA, IgG, and IgM are usually measured together. In this way, they can provide doctors with important information, especially regarding immune deficiency diseases. Hypogammaglobulinemia (HGG) is one of the main groups of primary immunodeficiency disorders. HGG is caused by various defects in B cell lineage or function that result in low levels of immunoglobulins in the bloodstream. This affects the body's immune response, causing a wide range of clinical features, from asymptomatic diseases to severe and recurrent infections, chronic inflammation and autoimmunity Transient infant hypogammaglobulinemia (THGI), IgM deficiency (IgMD), Bruton agammaglobulinemia, IgA deficiency (SIgAD) HGG samples are a few. Most patients can continue their normal lives by taking prophylactic antibiotics. However, patients with severe infections require intravenous immune serum globulin (IVIG) therapy. The IgE level may rise to fight off parasitic infections, as well as a sign that the body is overreacting to allergens. Also, since the immune response can vary with different antigens, measuring specific antibody levels also aids in the interpretation of the immune response after immunization or vaccination. Immune deficiencies usually occur in childhood. In Immunology and Allergy clinics, apart from the classical methods, it will be more useful in terms of diagnosis and follow-up of diseases, if it is fast, reliable and especially in childhood hypogammaglobulinemia, sampling from children with a method that is more convenient and uncomplicated. The antibodies were attached to the electrode surface via the poly hydroxyethyl methacrylamide cysteine nanopolymer. It was used to evaluate the anodic peak results obtained in the electrochemical study. According to the data obtained, immunoglobulin determination can be made with a biosensor. However, in further studies, it will be useful to develop a medical diagnostic kit with biomedical engineering and to increase its sensitivity.

Keywords: biosensor, immunosensor, immunoglobulin, infection

Procedia PDF Downloads 106

Authors: Jessica Lopez Espejel, Mahaman Sanoussi Yahaya Alassan, Walid Dahhane, El Hassane Ettifouri

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Pretrained transformer-based models have shown high performance in natural language generation tasks. However, a new wave of interest has surged: automatic programming language code generation. This task consists of translating natural language instructions to a source code. Despite the fact that well-known pre-trained models on language generation have achieved good performance in learning programming languages, effort is still needed in automatic code generation. In this paper, we introduce JaCoText, a model based on Transformer neural network. It aims to generate java source code from natural language text. JaCoText leverages the advantages of both natural language and code generation models. More specifically, we study some findings from state of the art and use them to (1) initialize our model from powerful pre-trained models, (2) explore additional pretraining on our java dataset, (3) lead experiments combining the unimodal and bimodal data in training, and (4) scale the input and output length during the fine-tuning of the model. Conducted experiments on CONCODE dataset show that JaCoText achieves new state-of-the-art results.

Keywords: java code generation, natural language processing, sequence-to-sequence models, transformer neural networks

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Authors: Young Mun Lee, Seon Ho Kim, Seok Min Choi, JeongJu Kim, Seungyeong Choi, Hyung Hee Cho

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To decrease sulfur oxide in the flue gas from coal power plant, a flue gas de-sulfurization facility is operated. In the reactor, a chemical reaction occurs with a temperature change of the gas so that sulfur oxide is removed and cleaned air is emitted. In this process, temperature change induces a serious problem which is a cold erosion of stack. To solve this problem, the rotary heat exchanger is managed before the stack. In the heat exchanger, a heating element is equipped to increase a heat transfer area. Heat transfer and pressure loss is a big issue to improve a performance. In this research, thermal-fluid characteristics of the heating element are analyzed by computational fluid dynamics. Fouling simulation is also conducted to calculate a performance of heating element. Numerical analysis is performed on the situation where plugging phenomenon has already occurred and existed in the inlet region of the heating element. As the pressure of the rear part of the plugging decreases suddenly and the flow velocity becomes slower, it is found that the flow is gathered from both sides as it develops in the flow direction, and it is confirmed that the pressure difference due to plugging is increased.

Keywords: heating element, plugging, rotary heat exchanger, thermal fluid characteristics

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Authors: U. Gunal, H. I. Turgut, H. Gurler, S. Kaya

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There are many ever-increasing and newly emerging problems with rapid population growth in the world. With the increase in people's quality of life in our daily life, acoustic comfort has become an important feature in the textile industry. In order to meet all these expectations in people's comfort areas and survive in challenging competitive conditions in the market without compromising the customer product quality expectations of textile manufacturers, it has become a necessity to bring functionality to the products. It is inevitable to research and develop materials and processes that will bring these functionalities to textile products. The noise we encounter almost everywhere in our daily life, in the street, at home and work, is one of the problems which textile industry is working on. It brings with it many health problems, both mentally and physically. Therefore, noise control studies become more of an issue. Besides, materials used in noise control are not sufficient to reduce the effect of the noise level. The fabrics used in acoustic studies in the textile industry do not show sufficient performance according to their weight and high cost. Thus, acoustic textile products can not be used in daily life. In the thesis study, the attributions used in the noise control and building acoustics studies in the literature were analyzed, and the product with the highest damping value that a textile material will have was designed, manufactured, and tested. Optimum values were obtained by using different material samples that may affect the performance of the acoustic material. Acoustic measurement methods should be applied to verify the acoustic performances shown by the parameters and the designed three-dimensional structure at different values. In the measurements made in the study, the device designed for determining the acoustic performance of the material for both the impedance tube according to the relevant standards and the different noise types in the study was used. In addition, sound records of noise types encountered in daily life are taken and applied to the acoustic absorbent fabric with the aid of the device, and the feasibility of the results and the commercial ability of the product are examined. MATLAB numerical computing programming language and libraries were used in the frequency and sound power analyses made in the study.

Keywords: acoustic, egg crate, fabric, textile

Procedia PDF Downloads 108

Authors: E. O. Adeleye

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Field experiments were conducted to investigate the effect of soil tillage techniques and poultry manure application on the soil properties and yam (Dioscorea rotundata) performance in Ondo, southwestern Nigeria for two farming seasons. Five soil tillage techniques, namely ploughing (P), ploughing plus harrowing (PH), manual ridging (MR), manual heaping (MH) and zero-tillage (ZT) each combined with and without poultry manure at the rate of 10 tha-1 were investigated. Data were obtained on soil properties, nutrient uptake, growth and yield of yam. Soil moisture content, bulk density, total porosity and post harvest soil chemical characteristics were significantly (p>0.05) influenced by soil tillage-manure treatments. Addition of poultry manure to the tillage techniques in the study increased soil total porosity, soil moisture content and reduced soil bulk density. Poultry manure improved soil organic matter, total nitrogen, available phosphorous, exchangeable Ca, k, leaf nutrients content of yam, yam growth and tuber yield relative to tillage techniques plots without poultry manure application. It is concluded that the possible deleterious effect of tillage on soil properties, growth and yield of yam on an alfisol in southwestern Nigeria can be reduced by combining tillage with poultry manure.

Keywords: poultry manure, tillage, soil chemical properties, yield

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Authors: P. Geetha, R. S. D. Wahida Banu

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The crowning advances in Silicon based electronic technology have dominated the computation world for the past decades. The captivating performance of Si devices lies in sustainable scaling down of the physical dimensions, by that increasing device density and improved performance. But, the fundamental limitations due to physical, technological, economical, and manufacture features restrict further miniaturization of Si based devices. The pit falls are due to scaling down of the devices such as process variation, short channel effects, high leakage currents, and reliability concerns. To fix the above-said problems, it is needed either to follow a new concept that will manage the current hitches or to support the available concept with different materials. The new concept is to design spintronics, quantum computation or two terminal molecular devices. Otherwise, presently used well known three terminal devices can be modified with different materials that suits to address the scaling down difficulties. The first approach will occupy in the far future since it needs considerable effort; the second path is a bright light towards the travel. Modelling paves way to know not only the current-voltage characteristics but also the performance of new devices. So, it is desirable to model a new device of suitable gate control and project the its abilities towards capability of handling high current, high power, high frequency, short delay, and high velocity with excellent electronic and optical properties. Carbon nanotube became a thriving material to replace silicon in nano devices. A well-planned optimized utilization of the carbon material leads to many more advantages. The unique nature of this organic material allows the recent developments in almost all fields of applications from an automobile industry to medical science, especially in electronics field-on which the automation industry depends. More research works were being done in this area. This paper reviews the carbon nanotube field effect transistor with various gate configurations, number of channel element, CNT wall configurations and different modelling techniques.

Keywords: array of channels, carbon nanotube field effect transistor, double gate transistor, gate wrap around transistor, modelling, multi-walled CNT, single-walled CNT

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Authors: Alina Muradyan, Lina Babayan, Arsen Nanyan, Gohar Galstyan, Vigen Khachatryan

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We present a photometric method for identifying stars, galaxies and quasars in multi-color surveys, which uses a library of ∼> 65000 color templates for comparison with observed objects. The method aims for extracting the information content of object colors in a statistically correct way, and performs a classification as well as a redshift estimation for galaxies and quasars in a unified approach based on the same probability density functions. For the redshift estimation, we employ an advanced version of the Minimum Error Variance estimator which determines the redshift error from the redshift dependent probability density function itself. The method was originally developed for the Calar Alto Deep Imaging Survey (CADIS), but is now used in a wide variety of survey projects. We checked its performance by spectroscopy of CADIS objects, where the method provides high reliability (6 errors among 151 objects with R < 24), especially for the quasar selection, and redshifts accurate within σz ≈ 0.03 for galaxies and σz ≈ 0.1 for quasars. For an optimization of future survey efforts, a few model surveys are compared, which are designed to use the same total amount of telescope time but different sets of broad-band and medium-band filters. Their performance is investigated by Monte-Carlo simulations as well as by analytic evaluation in terms of classification and redshift estimation. If photon noise were the only error source, broad-band surveys and medium-band surveys should perform equally well, as long as they provide the same spectral coverage. In practice, medium-band surveys show superior performance due to their higher tolerance for calibration errors and cosmic variance. Finally, we discuss the relevance of color calibration and derive important conclusions for the issues of library design and choice of filters. The calibration accuracy poses strong constraints on an accurate classification, which are most critical for surveys with few, broad and deeply exposed filters, but less severe for surveys with many, narrow and less deep filters.

Keywords: VO, ArVO, DFBS, FITS, image processing, data analysis

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Authors: Bipasha Sen, Aditya Agarwal

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

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

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Authors: O. J. Osunkeye, P. O. Fakolade, B. E. Olorede

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Broilers productions depend on the provision of adequate and goo quality feed containing all the nutrients, including proteins, carbohydrate, fats, vitamins, minerals and water. All these nutrients have to be provided at a required amount to support maximum productivity and normal physiological functions and demands. Among these nutrients proteins are particularly important, since they are essential for meat and muscle production, optimum growth and health status. Poultry production industry in the developing countries is been threatened because of the over dependency on Soybean meal as one of the key/major conventional protein stuff for feeding livestock. Even the competition between man and livestock for Soybean and other protein sources made the price of this feed stuff to be on the increase. Hence the needs to seek for an alternative feed stuff which is cheap and less competitive. This study showed the blood profile, organ and carcass characteristics and performance of broilers fed with Cowpea Testa Meal (CTM) based diets. Four diets were formulated with Cowpea Testa replacing Soybean at 0%, 15%, 30%, and 50% graded levels. One hundred and twenty day-old unsexed broiler birds were allotted to these four treatments with 3 replicates of 10 birds per replicate. The results showed no significant differences in all the haematological parameters measured (P>0.05), the serum metabolites analysis revealed significant different in Cholesterol (99.8 mg/dl, 112.84 mg/dl, 131.07 mg/dl and 97.66 mg/dl respectively) (P<0.05) among others. There were significant differences within the diets for average daily weight gain, average feed intake and feed to gain ratio. The birds on control (0%) and CTM gained more weight than those fed with 30% and 50% CTM diets. The organs and carcass primal cuts of the broilers expressed significant different for the spleen (0.12 g, 0.09 g, 0.11 g and 0.14 g respectively), lungs (0.97 g, 0.72 g, 0.77 g and 1.01g respectively) and proventriculus (0.96 g, 0.99 g, 0.81 g and 0.85 g respectively) (P<0.05). For the carcass, there were no significant differences (P<0.05) in the breast, thigh, drumstick, wing and neck except for the Back (21.27 g, 21.04 g, 17.71 g, and 17.89 g respectively). In conclusion, CTM inclusion in broiler’s diet could be used as an alternative feed stuff in replacement of Soybean meal up to 15% without any adverse effects as revealed by the blood profile and to increase the growth performance of the birds.

Keywords: physiological functions, cholesterol, blood profiles, CTM and carcass analysis

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Authors: Yung-Jin Weng, Chia-Chi Chang, Chun-Yu Tsai

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This paper is focused on the research of imprinting and replica molding of quasi-grey scale soft mold curved surface microstructure mold. In this paper, a magnetic photocuring forming system is first developed and built independently, then the magnetic curved surface microstructure soft mode is created; moreover, the magnetic performance of the magnetic curved surface at different heights is tested and recorded, and through experimentation and simulation, the magnetic curved surface microstructure soft mold is used in the research of quasi-grey scale soft mold curved surface microstructure imprinting and replica molding. The experimental results show that, under different surface curvatures and voltage control conditions, different quasi-grey scale array microstructures take shape. In addition, this paper conducts research on the imprinting and replica molding of photoresist composite magnetic powder in order to discuss the forming performance of magnetic photoresist, and finally, the experimental result is compared with the simulation to obtain more accurate prediction and results. This research is predicted to provide microstructure component preparation technology with heterogeneity and controllability, and is a kind of valid shaping quasi-grey scale microstructure manufacturing technology method.

Keywords: soft mold, magnetic, microstructure, curved surface

Procedia PDF Downloads 326

Authors: Khalid S. Hashim, Andy Shaw, Rafid Alkhaddar, Montserrat Ortoneda Pedrola

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A flow column has been innovatively used in the design of a new electrocoagulation reactor (ECR1) that will reduce the temperature of water being treated; where the flow columns work as a radiator for the water being treated. In order to investigate the performance of ECR1 and compare it to that of traditional reactors; 600 mL water samples with an initial temperature of 35 0C were pumped continuously through these reactors for 30 min at current density of 1 mA/cm2. The temperature of water being treated was measured at 5 minutes intervals over a 30 minutes period using a thermometer. Additional experiments were commenced to investigate the effects of initial temperature (15-35 0C), water conductivity (0.15 – 1.2 S) and current density (0.5 -3 mA/cm2) on the performance of ECR1. The results obtained demonstrated that the ECR1, at a current density of 1 mA/cm2 and continuous flow model, reduced water temperature from 35 0C to the vicinity of 28 0C during the first 15 minutes and kept the same level till the end of the treatment time. While, the temperature increased from 28.1 to 29.8 0C and from 29.8 to 31.9 0C in the batch and the traditional continuous flow models respectively. In term of initial temperature, ECR1 maintained the temperature of water being treated within the range of 22 to 28 0C without the need for external cooling system even when the initial temperatures varied over a wide range (15 to 35 0C). The influent water conductivity was found to be a significant variable that affect the temperature. The desirable value of water conductivity is 0.6 S. However, it was found that the water temperature increased rapidly with a higher current density.

Keywords: water temperature, flow column, electrocoagulation

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Authors: Jay Ananth

Abstract:

The drug discovery process currently requires numerous years of clinical testing as well as money just for a single drug to earn FDA approval. For drugs that even make it this far in the process, there is a very slim chance of receiving FDA approval, resulting in detrimental hurdles to drug accessibility. To minimize these inefficiencies, numerous studies have implemented computational methods, although few computational investigations have focused on a crucial feature of drugs: lipophilicity. Lipophilicity is a physical attribute of a compound that measures its solubility in lipids and is a determinant of drug efficacy. This project leverages Artificial Intelligence to predict the impact of a drug’s lipophilicity on its performance by accounting for factors such as binding affinity and toxicity. The model predicted lipophilicity and binding affinity in the validation set with very high R² scores of 0.921 and 0.788, respectively, while also being applicable to a variety of target receptors. The results expressed a strong positive correlation between lipophilicity and both binding affinity and toxicity. The model helps in both drug development and discovery, providing every pharmaceutical company with recommended lipophilicity levels for drug candidates as well as a rapid assessment of early-stage drugs prior to any testing, eliminating significant amounts of time and resources currently restricting drug accessibility.

Keywords: drug discovery, lipophilicity, ligand-receptor interactions, machine learning, drug development

Procedia PDF Downloads 111

Authors: Jinesh Kumar Jain, Faishal Pathan

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The concept of sustainable development and effective environmental regulation has led to the emergence of a new field of study and practise that is the Green Supply Chain Management. GSCM has become a subject of great importance for both the developed and developing countries to achieve the desired and much-awaited goals of the firm within the environmental and sustainable framework. Its merits are comprised of good financial pay off and competitiveness to the firms in a long lasting and sustainable manner. The purpose of the paper is to briefly review the recent literature of the GSCM and also determines the new direction area of this emerging field. A detailed study has helped to enlighten the minute details and develop the research direction of the study. The GSCM has gained popularity with both academic and practitioners. The items for the study were developed based on the extent literature. Here we found that the state of adoption of GSCM practices by Indian Firms was still in its infancy, the awareness of environmental sustainability was quite low among consumers and the regulatory frameworks were also lacking in terms promoting environmental sustainability. The present paper is an attempt to emphasize much attention on the above-mentioned issues and present a conclusive summary to make its use widespread and for reaching.

Keywords: environmental management, environmental performance, financial performance, green supply chain management

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Authors: Zahid Ullah, Atlas Khan

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This abstract focuses on the advancements in mathematical modeling and optimization techniques that play a crucial role in enhancing the efficiency, reliability, and performance of these systems. In this era of rapidly evolving technology, mathematical modeling and optimization offer powerful tools to tackle the complex challenges faced by control, signal processing, and energy systems. This abstract presents the latest research and developments in mathematical methodologies, encompassing areas such as control theory, system identification, signal processing algorithms, and energy optimization. The abstract highlights the interdisciplinary nature of mathematical modeling and optimization, showcasing their applications in a wide range of domains, including power systems, communication networks, industrial automation, and renewable energy. It explores key mathematical techniques, such as linear and nonlinear programming, convex optimization, stochastic modeling, and numerical algorithms, that enable the design, analysis, and optimization of complex control and signal processing systems. Furthermore, the abstract emphasizes the importance of addressing real-world challenges in control, signal processing, and energy systems through innovative mathematical approaches. It discusses the integration of mathematical models with data-driven approaches, machine learning, and artificial intelligence to enhance system performance, adaptability, and decision-making capabilities. The abstract also underscores the significance of bridging the gap between theoretical advancements and practical applications. It recognizes the need for practical implementation of mathematical models and optimization algorithms in real-world systems, considering factors such as scalability, computational efficiency, and robustness. In summary, this abstract showcases the advancements in mathematical modeling and optimization techniques for control, signal processing, and energy systems. It highlights the interdisciplinary nature of these techniques, their applications across various domains, and their potential to address real-world challenges. The abstract emphasizes the importance of practical implementation and integration with emerging technologies to drive innovation and improve the performance of control, signal processing, and energy.

Keywords: mathematical modeling, optimization, control systems, signal processing, energy systems, interdisciplinary applications, system identification, numerical algorithms

Procedia PDF Downloads 112

Authors: Hussin K. Ragb, Vijayan K. Asari

Abstract:

In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.

Keywords: pedestrian detection, phase congruency, local phase, LBP features, CSLBP features, FST descriptor

Procedia PDF Downloads 488