Bench Mark Research Articles

Homestead Vegetable Production: A Means Of Livelihood and Nutritional Security for Resource Poor Households in Bangladesh

Justifiable, nutritious and safe food productions are main challenges for food safety which reduce starvation, meets dietary needs and food preferences for a healthy life. Home gardens can play a significant role in providing better food supply and diversity of food. Studies on niche-based homestead gardening were carried out at FSRD site Atia, Tangail under On-Farm Research Division of Bangladesh Agricultural Research Institute during 2018-19 and 2019-20 to utilize the homestead resources for producing vegetables and fruits and to enhance nutritional security for the farm families. A total of 12 households were selected from marginal (0.021–0.20 ha), small (0.21–1.0 ha) and medium (1.0- 3.0) farmer groups and seven production niches were intervened for year-round production following the Palima model. Results revealed that homestead area could be capable of harvesting sufficient and diversified vegetables round the year by utilizing all possible homestead nieches. After intervention, the number of vegetables was produced by medium farmers (630 kg/year) followed by small (510 kg/year) and marginal (408 kg/year) farmers. Yearly vegetable requirements of farmers were largely met by homestead garden with a supply between 30-58 kg/head/year compared with bench mark level of 5-12 kg/head/year. Results suggested that farmers consumed lion share of their products that could meet up nutrition. Utilization of farm resources available in the farm that increased nutritional security, income and improved livelihoods as well. The up scaling of the production model based on ecosystem in different poverty-stricken regions of Bangladesh is recommended to attain food security and lessening malnutrition.
 Bangladesh J. Agril. Res. 47(1): 51-68, March 2022

Extreme Event Statistics in Dst, SYM‐H, and SMR Geomagnetic Indices

AbstractExtreme space weather events are rare, and quantifying their likelihood is challenging, often relying on geomagnetic indices obtained from ground‐based magnetometer observations that span multiple solar cycles. The Dst index ring‐current monitor, derived from an hourly average over four low‐latitude stations, is a benchmark for extreme space weather events, and has been extensively studied statistically. We apply extreme value theory (EVT) to two geomagnetic ring current indices: SYM‐H (derived from 6 stations) and SMR (derived from up to 120 stations). EVT analysis reveals a divergence between the return level found for Dst, and those for SYM‐H and SMR, that increases non‐linearly with return period. For return periods below 10 years, hourly averaged SYM‐H and SMR have return levels similar to Dst, but at return periods of 50 and 100 years, they respectively exceed that of Dst by about 10% and 15% (SYM‐H) and about 7% and 12% (SMR). One minute resolution SYM‐H and SMR return levels progressively exceed that of Dst; their 5, 10, 50, and 100 year return levels exceed that of Dst by about 10%, 12%, 20% and 25% respectively. Our results indicate that consideration should be given to the differences between the indices if selecting one to use as a bench mark in model validation or resilience planning for the wide range of space weather sensitive systems that underpin our society.

The Initial Process of Dam Construction is Seen from a Topographical Perspective (Bench Mark Coordinates and Control Point Coordinates): Case study of D.I. Bajayu Kab Serdang Bedagai

The research aims to determine the initial process of dam construction is seen from a topographical perspective ( bench mark coordinate and control point coordinates: case study of D.I. Bajayu kab. Serdang Bedagai. The aim and objective of this topographic survey is to collect topographical data from the field in order to produce supporting data in the form of a topographical/situation base map including cross-sectional and longitudinal cross-sectional images along the measurement location. Measurement 20 data of topographi for BM coordinat and CP coordinat, so: measurements are made up to 50 meters from the left and right bank of the river, measurement lengthwise (long section) of ± 8.2 km was carried out from the confluence of the Padang river with the Bah disappeared river to the Bajayu free intake location, measurement benchmark interval for 100 meters straight area and 50 meters turning area,conduct measurements on the linking route/trace from the planned main building to the free intake of D.I Bajayu and the first building for D.I Paya Lombang, measuring 50 meter intervals, the length of the measurement path from the axle of the weir to the Bajayu free intake is 3,600 m following the embankment to the right of the Padang river, the length of the canal trace from the axle of the weir to the building for the first Paya Lombang is 4,600 m following the existing road.

Optimize the Location of Embedded Pipes by Using Low-Grade Natural Thermal Energy/Waste Heat for Thermal Activated Façade

The final effect of a thermal activated façade (TAF) wouldn’t only be influenced by the thermal character of the wall, dimensions and distance of the embedded pipes besides flow rate and temperature of the medium, but also by the location of the pipes. The location of the embedded pipes not only affects the final effect of thermoactivated, there is at the same time an obvious correspondence with the temperature of the medium. The simulations and lab investigations have concluded that the optimization the depth of embedded pipes, is necessary in order to use low-grade natural thermal energy/waste heat (LGTE) to achieve TAF. Using the bench mark of the “equivalent thermal resistance” (ER-Value), it is clear that the closer the pipes are located to the outside, the less energy grade is required. However, not all of the LGTE with higher temperature than outdoor air can be used for TAF. The limit of LGTE is the “Invalid Medium Temperature” (IVMT); although there is still a temperature difference between the medium and the outdoor environment, its thermal driving potential is not enough to form an effective heat transfer between the pipe and its surrounding per unit length, so that the medium circulation in the wall hardly contributes to changing the temperature gradient in the wall.

An optimization approach for optimal location & size of DSTATCOM and DG

This manuscript proposes a novel method to decide the optimum location and size of Distribution static compensator (DSTATCOM) and Distribution Generation (DG) are examined. For lessening the loss of power, voltage profile improvement and operation costs of system, the objective function is used under the constraints of equality and inequality. The aim of proposed method is diagnosis the dynamic issues present in the power system under various environments, like healthy conditions and unhealthy conditions. The primary location of both Distribution Generation and Distribution static compensator are detected by using the loss sensitivity factor (LSF). The final optimum location is determined by using Dwarf Mongoose Optimization (DMO) method. The DMO is used to decide the optimum size of Distribution Generation and Distribution static compensator. The aim of the proposed method is an integrated approach of loss sensitivity factor and Dwarf Mongoose Optimization to decide the optimum location and size of Distribution Generation and DSTATCOM for diminishing the loss of power, voltage profile improvement and operation cost. The Distribution Generation and DSTATCOM are simultaneously placed in radial DG. The LSF is used earlier to detect the optimum location of Distribution Generation and Distribution static compensator. The proposed system is performed in MATLAB or Simulink site and the performance of dynamic stability is tested with IEEE standard bench mark systems.

Land Planning and Site Plane Creation, Faculty of Engineering, University of Muhammadiyah Buton

Measurement of land development at the Faculty of Engineering, University of Muhammadiyah Buton is carried out to determine the condition of the land that will be used as a reference for developing, structuring land and planning from the University. Measurement method using the Theodolite tool. With the division of benchmark points (BM) in accordance with the conditions in the development land of the Faculty of Engineering. The measurement results can be used as a reference to carry out development planning appropriately. Processing is carried out in several stages, starting from literature studies, field surveys, data collection, measurement, data processing, to results and conclusions. The measurement process is carried out in several stages ranging from the manufacture and installation of benchmark (BM) benchmarks, BM point determination, site up Theodolite tools and detailed measurements. The results of this service activity are in the form of a development site plane plan image, elevation plan, and 3D view image. The measurement images can be used as a reference in carrying out future development of the land development of the Faculty of Engineering, University of Muhammadiyah Buton.

Developed molecular dynamics method of dissipative particle dynamics for the bench mark numerical simulation of fluid flow inside a rectangular chamber,,

The fluid flow inside the chamber with a moving wall is simulated by developed Dissipative Particle Dynamics (DPD) method which implies the developed molecular dynamics (MD) appraoch. In this benchmark problem, the chamber is filled with a fluid with a certain initial temperature and its cover is moving at a constant speed. One of the most important issues in DPD method, is creating solid walls and then applying related boundary conditions. Hence by freezing several layers of DPD particles, solid walls were created to prevent DPD particles from leaving the area. Then, by applying the boundary condition of parallel reflection, the penetration of fluid particles into the solid wall was prevented, and the no-slip condition was applied to the walls. Next, the effect of parameters such as initial distribution of fluid particles, their initial velocity, geometry of the problem, boundary conditions, Reynolds number and different weighting functions, were investigated. It was showed that increasing Reynolds number to more than 800 in addition to eliminating the incompressibility property caused particles exit from the solution domain and diverge. It is also possible to increase the Schmidt number of DPD fluid by applying a suitable weighting function.

Randomized comparative double-blind study assessing the difference between topically applied microbiome supporting skincare versus conventional skincare on the facial microbiome in correlation to biophysical skin parameters.

There are trillions of live bacteria, of around 1000 different species, living in human skin which are considered essential for the balance and barrier function of the skin. The gut microbiome has been a subject of extensive research and evidence shows that the gut flora is affected by preservatives and processed foods. In conventional skincare, preservatives are used, and this raises the question of how it affects the skin flora and its balance. A randomized double-blind study on 14 healthy volunteers ages 23-45 years old were advised to use microbiome-supporting (MS) products on one cheek and benchmark (BM) products on the other cheek daily for 3 weeks. To investigate how the skin was affected, the skin microbiome was analysed using 16 S rRNA sequencing and biophysical parameters were assessed using an Antera 3D camera. Measurements were performed before and after the 3 weeks of using the products. The use of MS products for 3 weeks significantly increased the total number of reads mapped to unique bacterial species (p< 0.05) and the number of different unique species (p< 0.05). In addition, the use of MS products significantly reduced redness (p< 0.05) and improved skin texture (p< 0.01). The use of BM products showed no significant difference in any of the parameters except improved skin texture (p< 0.05). Additionally, the MS side showed a significantly improved diversity (p< 0.05) compared with the BM side. The four major phyla found were, similarly to previous findings by others, Actinobacteria, Firmicutes, Proteobacteria and Bacteroidetes. Some of the most prevalent species were Cutibacterium acnes, Staphylococcus epidermidis and Pseudonomas aeruginosa. The findings of this study showed significant improvements in the microbiome and biophysical parameters within 3 weeks of using MS skincare alone, while BM skincare only gave significantly improved skin roughness. Importantly, the MS side gave a significantly improved bacterial Shannon diversity (p < 0.05) compared with the BM side. Regarding the biophysical parameters, the MS skincare gave significant improvements in several parameters compared with baseline. However, they were not yet significant when compared to using BM skincare and therefore a larger study population will be needed. Importantly, this is the first study to investigate how preservatives affect the facial microbiome in vivo and has raised a need for further investigation. These results together with further studies can lead to innovations within the cosmetic industry that promote healthier skin.

Predicting rheumatoid arthritis from the biomarkers of clinical trials using improved harmony search optimization with adaptive neuro-fuzzy inference system

Rheumatoid Arthritis (RA) is a chronic autoimmune disease whose symptoms are hard to determine due to the overlapping indications of the condition with other illnesses such as dengue, malaria, etc. As the symptoms of RA disease are similar to inflammatory diseases, general physicians (GPs) find it difficult to detect the disease earlier. A computer aided framework is proposed in this study to assist and support the GPs to diagnose RA better. In this work Improved Harmony Search Optimization (IHSO) approach is proposed to select the significant feature subset of RA and Adaptive Neuro-Fuzzy Inference System (ANFIS) is used as a classification model. The performance of the proposed IHSO-ANFIS model is examined with metrics such as Balanced Accuracy (Bacc), Area under Curve (AUC), Sensitivity (Sen), Specificity (Spec), and Matthew’s Correlation Coefficient (MCC) using 10-Fold cross-validation. Additionally, the results of the IHSO-ANFIS are compared with HSO-ANFIS, ANFIS without any feature selection and standard bench mark datasets. IHSO-ANFIS attained 87.05% Bacc, 89.95% AUC and 0.6586 MCC on the RA dataset. From the results it is clear that IHSO-ANFIS could assist general physicians to diagnose RA earlier and pave the way for timely treatment.

ASSESSEMENT OF RESIDENTIAL HOUSING INFRASTRUCTURE AND AFFORDABILITY ALONG IDAH ROAD, ANYIGBA, KOGI STATE

The study carried out an Assessment of `Residential Housing Infrastructure and Affordability along Idah Road, Anyigba, Kogi State. The objectives of the study were to identify the type of residential infrastructure, examine the characteristics of the residential housing infrastructure and to assess the affordability of the residential housing infrastructure in the study area. The study used systematic sampling techniques to administer 384 questionnaires. Frequency distribution tables and percentages were used to analyze the data. The study reveals that majority of the residential housing infrastructure 22.9% is room and palour. Also, the residential housing characteristics indicates that majority of residential housing infrastructure nature of floor furnishing is ceramic marble tile 79.4%, nature of walling material is normal bricks 69.2% and nature of roofing material is corrugated metal zinc sheets 63.0%. Furthermore, the study shows that majority of respondents 35.2% pay rents of #81,000 - # 100,000. Likewise, about 84.1% spent above 30% bench mark for housing affordability. Equally, majority of the respondents 48.6% agreed that the residential housing infrastructure is moderate and the general condition of the residential housing infrastructure in the study area is fair with 51.2%. The study recommends that they should be general upgrading of the residential housing infrastructure and that civil servant need to get other stream of income in other to be able to pay their rents as at when due.

Health Risk Assessment of PAHs from Wheat (Tritcum specie) Bambara Nut (Vigna subterranea) and Pigeon Peas (Cajanus cajanifolia) Consumed in Nigeria

Polycyclic aromatic hydrocarbons, PAHs are carcinogenic and genotoxic in nature and have been of worldwide concern. This study aimed at determining the PAH contamination levels in types of wheat (Tritcum specie), bambara groundnut (Vigna subterranea) and pigeon peas (Cajanus cajanifolia) commonly consumed in the eastern part of Nigeria and assess the health risk associated with their consumption. The grain samples were analyzed of sixteen priority PAHs using gas chromatography coupled with flame ionization detector, GC-FID after extraction by sonication. Estimation of daily intakes were carried out using adult male and female consumers while margin of exposure was used to assess the health risk applying bench mark dose levels for the indicators-BaP, PAH2, PAH4 and PAH8. The sixteen PAHs were detected in all the analyzed grains. The ∑16 PAHs concentrations (× 10¯²µg/kg) detected ranged from 25.004±20.553 in white pigeon peas to 36.493±20.305 in red pigeon peas. The eight probable carcinogenic PAHs (∑PAH8) detected ranged from 10.913±4.295 to 17.444±7.023 also in white and red pigeon peas respectively. From the estimation of daily intake calculated, the total dietary exposure of male (41.42 µg/kg bw/day) was less than that of female (48.24 µg/kg bw/day) implying that adult female are more exposed. The MOE for adult male individual ranged from 49,893 in pure white bambara groundnut to 392,943 in pigeon peas. While for adult female individual, the values of MOE ranged from 48,110 in bambara groundnut to 336,770 in pigeon peas. The values of margin of MOE obtained for all the indicators were much higher than 10000 which according to EFSA indicate low concern for human health and considered low priority for risk management actions. The PAHs values detected were all below 1.0 µg/kg which is the permissible limit established by EFSA. Based on these facts, these grains are safe for consumption.

Extended state observer based current-constrained controller for a PMSM system in presence of disturbances: Design, analysis and experiments

Considering overcurrent and total disturbances, i.e. measurement noise, parameter uncertainties, external load torque disturbance etc., a composite current-constrained control method based on non-cascade single-loop speed regulation control structure is adopted for permanent magnet synchronous motor system (PMSMs). First, a tracking state space model is proposed to transfer the matched and mismatched disturbances into a uniform matched disturbance. Second, a third-order extended state observer (ESO) is developed to satisfactorily attenuate the effect of the total disturbances with their estimation values via feedforward compensation, since a tracking differentiator (TD) is designed to arrange the transition process for the reference input signal to balance the contradiction between overshoot and quick response. Third, a composite ESO-based current-constrained controller with a penalty mechanism of q-axis current, constructed by a special nonlinear gain, is designed to deal with the overcurrent of the PMSMs speed regulation. In addition, a finite time bounded stability theory is introduced to analyze the proposed closed-loop speed regulation system. A bench mark experimental set-up based on NI CompactRIO 9045 and LabVIEW for a PMSMs is designed to verify and compare the performances of the proposed composite controller against conventional PID controller. Finally, the simulation and experiment results demonstrate the effectiveness and superiority of the proposed controller.

Study on the Application of Non-Plastering Technology of BM Lightweight Aggregate Interlocking Block

Benchmark (BM) lightweight aggregate interlocking block has the characteristics of energy saving, no plastering, convenient construction, etc., which can be used for internal infilled walls at all parts (240 mm thick block can also be used for external infilled walls). The U-shaped bricks are used in building ring beams, structural columns and lintel formwork. It eases the formwork construction process, saves energy consumption, shortens the construction period, and reduces the materials used, achieving the purpose of ensuring a high-quality building at minimum construction cost. Taking the practical project as an example, this paper studies the performance and characteristics of BM light aggregate interlocking block, and introduces the key construction technologies, aiming to provide relevant reference for the application of BM light aggregate interlocking block in practical projects.

Land use land cover change in and around Chebera Churchura National Park, Southwestern Ethiopia: implications for management effectiveness

BackgroundLand use-land cover change (LULCC) resulting from anthropogenic activities has been one of the major causes of loss of biodiversity globally. Thus, understanding the dynamics of such LULCC, especially within protected areas, is important to assess their past-present management effectiveness, identify the driving forces and assist future implementation of mitigation measures. The objectives of this study, based on satellite images analysis, were to examine and describe patterns of LULCC within and in the buffer zone area of Chebera Churchura National Park, SW Ethiopia, at five points in time (1985, 1991, 2000, 2010, and 2020); and to examine management effectiveness of the park authority in slowing down the rate of LULCCs after the establishment of the park.ResultsResults showed that different land cover types exhibited varying patterns of change over the last 35 years. However, major differences were detected between the park area boundary and its buffer zone area after establishment of the park. From the year 1991 to 2000 (before the establishment), grassland declined by 52.9% (120.55km2) and 58.9% (151.9km2) within the park boundary and its buffer zone, respectively. After the establishment, grassland continued to decline only in the buffer zone. Similarly, agricultural land declined by 13.2% (2.7 km2) within the park but expanded by 5.4% (3.1 km2) in the buffer zone prior to park establishment. However, after establishment of the park, agricultural land in the buffer zone increased by 99.4% (99.7 km2). Grassland and wooded grassland had the opposite trend within the park area before vs after the establishment of the park.ConclusionsResults of the present study showed that striking differences in the rates of LULCCs within the park area and its buffer zone after establishment of the park, with the implication that the management is effective in slowing down LULCC relative to that in the buffer zone areas. In sum, this study would serve as a showcase on cost-effective means to assess human impacts on biodiversity in protected areas due to policy changes. Findings of the study would serve as a bench mark to evaluate future management effectives of the park authority.

Computing Models to Predict the Compressive Strength of Engineered Cementitious Composites (ECC) at Various Mix Proportions

Concrete has relatively high compressive strength (resists breaking when squeezed) but significantly lower tensile strength (vulnerable to breaking when pulled apart). The compressive strength is typically controlled by the ratio of water-to-cement when forming the concrete, and tensile strength is increased by additives, typically steel, to create reinforced concrete. In other words, we can say concrete is made up of sand (which is a fine aggregate), ballast (which is a coarse aggregate), cement (which can be referred to as a binder), and water (which is an additive). Highly ductile material engineered cementitious composites (ECC) were developed to address these issues by spreading short polymer fibers randomly throughout a cement-based matrix. It has a high tensile strain capacity of more than 3%, hundreds of times more than conventional concrete. On the other hand, among the other examined qualities, compressive strength (CS) is a critical property. Consequently, developing reliable models to predict an ECC’s compressive strength is crucial for cost, time, and energy savings. It also includes instructions for planning construction projects and calculating the optimal time to remove the formwork. The artificial neural network (ANN), nonlinear model (NLR), linear relationship model (LR), multi-logistic model (MLR), and M5P-tree model were all proposed as alternative models to estimate the CS of ECC mixtures created by fly ash in this research (M5P). To create the models, a large amount of data were gathered and evaluated, totaling roughly 205 mixes. Various mixture proportions, fiber length, diameter, and curing durations were explored as input variables. To test the effectiveness of the suggested models, several statistical evaluations, including determination coefficient (R2), Mean Absolute Error (MAE), Scatter Index (SI), Root Mean Squared Error (RMSE), and Objective (OBJ) value, were utilized. Based on the statistical evaluations, the ANN model performed better in forecasting the CS of ECC mixes incorporating fly ash than other models. This model’s RMSE, MAE, OBJ, and R2 values were 4.55 MPa, 3.46 MPa, 4.39 MPa, and 0.98, respectively. A large database presented in this investigation can be used as the bench mark for future mixture proportions of the ECC. Moreover, the sensitivity analysis showed the contribution of each mixture ingredient on the CS of ECC.

Texture classification with modified rotation invariant local binary pattern and gradient boosting

Since texture is prominent low level feature of an image, most of the image processing and computer vision applications rely on this feature for efficient extraction, retrieval, visualization and classification of the images. Hence, the texture analysis method mainly concentrates on efficient feature extraction and representation of the image. The images captured and analyzed in many of the applications are not in same (or) similar scale, orientation and illumination and also texture has regular, stochastic, periodic, homogeneous (or) inhomogeneous and directional in nature. To address these issues, recent texture analysis method focused on efficient and invariant feature extraction and representation with reduced dimension. Hence this paper proposes a invariant texture descriptor, Locality preserving Rotation Invariant Modified Directional Local Binary Pattern (LRIMDLBP) based on LBP. The classical LBP descriptor is widely used in most of the texture analysis applications due to its simplicity and robustness to illumination changes. However, it does not efficiently capture the discriminative texture information because it uses sign information and ignores the magnitude value of the neighborhood and also suffers from high dimensionality. Hence to improve the performance of LBP, many variants are proposed. Though most of these LBP variants are either geometrical or direction invariant, fails to address the spatial locality and contrast invariance. To address these issues, the proposed LRIMDLBP incorporates spatial locality, contrast and direction information for rotation invariant texture descriptor with reduced dimension. The proposed LRIMDLBP consists of 5 phases: (i) Reference point identification, (ii) Magnitude calculation, (iii) Binary Label computation based on threshold, (iv) Pattern identification in dominant direction and (v) LRIMDLBP code computation. The locality and rotation invariance is achieved by identifying and using reference point in a local neighborhood. The reference point is a dominant pixel whose magnitude is large in the neighborhood excluding center pixel. The spatial locality and rotation invariance is achieved by preserving the weights of LBP dynamically based on the reference point. The proposed method also preserves the direction information of the texture by comparing the magnitude of the pixel in the four dominant directions such as horizontal, vertical, diagonal and anti-diagonal directions. Finally the proposed invariant LRIMDLBP descriptor computes histogram based on decimal pattern value. The proposed LRIMDLBP descriptor results in texture feature with reduced dimension when compared to other LBP variants. The performance of the proposed descriptor is evaluated with large and well known four bench mark texture datasets namely (i) CUReT, (ii) Outex, (iii) KTS-TIPS and (iv) UIUC against three classifiers such as (i). K-Nearest Neighbor (K-NN), (ii). Support Vector Machine (SVM) with Radial Basis Function (RBF) and (iii). Gradient Boosting Classifier (GBC). The intensive experimental result shows that the ensemble based GBC yields superior classification accuracy of 99.38%, 99.43%, 98.67% and 98.82% for the datasets CUReT, Outex, KTH-TIPS and UIUC respectively when compared with other two classifiers and also improves the generalization ability. The proposed LRIMDLBP descriptor achieves approximately 15% more classification accuracy when compared with traditional LBP and also produces 1% to 2.5% more classification accuracy compared with other state of the art LBP variants.

System identification using neuro fuzzy approach for IoT application

The Internet of Things (IoT) has become a popular application in recent years. However, it is the wireless communication mode. In such a scenario, the user would have to send information either nonlinear or dynamic data type in the form of a signal or an image, videos depending on the application. The proposed work is focused on this model identification that tends to nonlinear dynamic system identification for IoT applications. An Autoregressive Moving Average (ARMA) model represents model for IoT application. To verify the model supremacy, an ARMA bench mark system is used. The adaptiveness is proved through variation of weights and can be universally used for the next generation. In the first attempt, the Multilayer Perceptron model (MLP) is considered as the ARMA system and observed. Further, to improve its accuracy, the Adaptive Neuro-Fuzzy system (ANFIS) model is designed for system identification. It is shown in the result section that it identifies better than the MLP as well as traditional system identification techniques.

Ni/Ni(OH)2-rGO nanocomposites sensor for the detection of long forgotten mycotoxin, xanthomegnin

Xanthomegnin, a known fungal toxin, secondary metabolite, and pigment diffuses from the dermatophytes has gained attention as local virulence factor because of the mutagenicity, toxicity, cytocidal, and immunosuppressive properties. Not only as a dermatophyte in skin related disorders, the production of xanthomegnin is implicated as a powerful diagnostic marker in patients suffering from ocular mycoses. Incidentally also attributed to death in livestock's majorly by exposing themselves to food-borne fungi like Aspergillus and Penicillium. The production of xanthomegnin in dermetophytic species Trichophyton rubrum, found commonly in infected skin and nails. In this study nickel/nickel hydroxide nanoparticles decorated reduced graphene oxide (Ni/Ni(OH)2-rGO) modified glassy carbon electrode has been successfully used for non-enzymatic detection of xanthomegnin. The Ni/Ni(OH)2-rGO composites were synthesized through a simple microwave assisted technique with less harmful reducing agent. The UV-visible spectroscopy (UV-vis), X-ray photoelectron spectroscopy (XPS), Scanning electron microscopy - energy dispersive X-ray spectroscopy (SEM-EDS), and electrochemical investigations demonstrated the robust formation of the sensor. The sensor exhibited improved electrochemical properties with enhanced electrochemical active area and excellent electrochemical behavior towards xanthomegnin detection with a limit of detection of 0.12 μM. The selectivity, stability, and analytical recovery studies proved the potential use of the sensor for the detection of xanthomegnin in real samples. Further, the sensor successfully detected xanthomegnin produced by the Trichophyton rubrum, the most common superficial fungus, accounting for at least 60% of all superficial fungal infections in humans. Validation studies showed satisfiable and quantifiable amount of xanthomegnin in comparison with common bench mark UV-Vis studies meant for fungal mycotoxin detection.

Character recognition of Tibetan Historical document in Uchen font: Dataset and bench mark

. A offline character dataset of Tibetan Historical document in Uchen font, THCU, is presented to facilitate the research of Tibetan Historical document recognition. The dataset THCU includes two subsets: THCU-M and THCU-S. The THCU-M is annotated manually in original document images, including 121214 character samples and 238 character categories. The subset THCU-S is a simulation dataset, and its samples are generated based on the idea of component combination. There are four subsets in THCU-S, in which the numbers of character category are 7238, 2908, 562 and 245 respectively, and the numbers of sample in each category are 5000, 3000, 600 and 600 respectively. We also evaluate THCU dataset using a CNN based model as a baseline performance. The experiment shows that the performance of the model on the real data is greatly improved by adding the generated samples.

Hybridization of Deep Convolutional Neural Network for Underwater Object Detection and Tracking Model

In this present work, underwater object detection and tracking was studied using the efficient Hybridization of Deep Convolutional Neural Network for Underwater Object Detection and Tracking (HDCNN-UODT) model for three bench mark data sets namely UOT32, brackish, and URPC 2020 datasets. The HDCNN-UODT technique primarily employs data augmentation process for increasing the size of the training dataset to improve the detection and average precision. Besides, a hybridization of two Deep Learning (DL) models namely RetinaNet and EfficientNet models was applied as feature extractors. In addition, the bounding box prediction process takes place via support vector regression (SVR) followed by kernel extreme learning machine (KELM) model. The novelty of the present work was demonstrated by the design of SVR based bounding box regression and fusion based feature extractions. The average precision examination (APE), average success rate(ASR) & average frame per second(AFPS) analysis of the HDCNN-UODT model using UOT32 dataset showed better APE (51.27%), ASR (43.19) & AFPS (310.25) over other reported techniques. Additionally, the detection accuracy of the HDCNN-UODT model for brackish and URPC datasets showed improved accuracies for different objects over YOLO v4, T-YOLO v4, and AFFM-YOLO v4 techniques. Moreover, using brackish dataset, HDCNN-UODT model showed highest accuracy of 94.85% for ‘Crab’ object and for URPC dataset, a highest accuracy of 88.34% for ‘Scallop’ object was obtained. Hence based on our outcome, HDCNN-UODT technique might be better suited for the object detection and tracking application.