Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification of Maize Lodging Extents Using Deep Learning Algorithms by UAV-Based RGB and Multispectral Images

Lodging depresses the grain yield and quality of maize crop. Previous machine learning methods are used to classify crop lodging extents through visual interpretation and sensitive features extraction manually, which are cost-intensive, subjective and inefficient. The analysis on the accuracy of subdivision categories is insufficient for multi-grade crop lodging. In this study, a classification method of maize lodging extents was proposed based on deep learning algorithms and unmanned aerial vehicle (UAV) RGB and multispectral images. The characteristic variation of three lodging extents in RGB and multispectral images were analyzed. The VGG-16, Inception-V3 and ResNet-50 algorithms were trained and compared depending on classification accuracy and Kappa coefficient. The results showed that the more severe the lodging, the higher the intensity value and spectral reflectance of RGB and multispectral image. The reflectance variation in red edge band were more evident than that in visible band with different lodging extents. The classification performance using multispectral images was better than that of RGB images in various lodging extents. The test accuracies of three deep learning algorithms in non-lodging based on RGB images were high, i.e., over 90%, but the classification performance between moderate lodging and severe lodging needed to be improved. The test accuracy of ResNet-50 was 96.32% with Kappa coefficients of 0.9551 by using multispectral images, which was superior to VGG-16 and Inception-V3, and the accuracies of ResNet-50 on each lodging subdivision category all reached 96%. The ResNet-50 algorithm of deep learning combined with multispectral images can realize accurate lodging classification to promote post-stress field management and production assessment.
Personalized Algorithm Generation: A Case Study in Learning ODE Integrators

We study the learning of numerical algorithms for scientific computing, which combines mathematically driven, handcrafted design of general algorithm structure with a data-driven adaptation to specific classes of tasks. This represents a departure from the classical approaches in numerical analysis, which typically do not feature such learning-based adaptations. As a case study, we develop a machine learning approach that automatically learns effective solvers for initial value problems in the form of ordinary differential equations (ODEs), based on the Runge-Kutta (RK) integrator architecture. We show that we can learn high-order integrators for targeted families of differential equations without the need for computing integrator coefficients by hand. Moreover, we demonstrate that in certain cases we can obtain superior performance to classical RK methods. This can be attributed to certain properties of the ODE families being identified and exploited by the approach. Overall, this work demonstrates an effective learning-based approach to the design of algorithms for the numerical solution of differential equations. This can be readily extended to other numerical tasks.
PENGARUH KUALITAS WEBSITE DAN PROMOSI PENJUALAN TERHADAP MINAT BELI DI BUKALAPAK.COM

Website masih menjadi pilihan utama bagi pelaku bisnis di era digital ini. Kualitas website yang baik akan secara langsung memberikan pengaruh bagi jalannya suatu bisnis. Terdapat berbagai macam jenis Website salah satunya adalah marketplace sebagai tempat bertransaksi antara penjual dan pembeli. Berkembangnya suatu marketplace dipengaruhi dengan banyaknya kunjungan dari calon konsumen. Ada banyak faktor pendukung yang dapat meningkatkan kunjungan di suatu marketplace salah satunya dengan promosi penjualan. Dengan adanya Website dan promosi penjualan ini akan menimbulkan minat beli kepada konsumen. Penelitian ini menggunakan pendekatan kuantitatif deskriptif sejumlah 100 responden yang dengan metode purposive sampling. Data dikumpulkan menggunakan metode observasi, wawancara, dokumentasi dan kuisioner yang dianalisis dengan analisis deskriptif kuantitatif menggunakan Analisa Linier Berganda. Hasil penelitian menunjukkan bahwa 1) terdapat pengaruh secara positif signifikan Kualitas website terhadap Minat Beli, 2) terdapat pengaruh secara positif signifikan Promosi Penjualan terhadap Minat Beli dan 3) terdapat pengaruh secara positif signifikan Pengaruh Kualitas website dan Promosi Penjualan terhadap Minat Beli. Berdasarkan Uji Beta menunjukan bahwa Kualitas website mempunyai pengaruh terbesar dibandingkan Promosi Penjualan, maka dari itu penulis menyarankan untuk meningkatkan Kualitas website di Bukalapak untuk meningkatkan Minat Beli di Bukalapak.com
The Demographical Prevalence of Malaria in Pregnant Women in Oshimili South Local Government Area of Delta State, Nigeria

This study evaluated the prevalence of malaria in pregnant women attending antenatal clinics in Delta state. Thick-film microscopy was used to detect parasitaemia while polymerase chain reaction (PCR) was employed to confirm positivity. Statistical method used were Chi square, Paired Sample T test and Pearson Correlation test at 5% level using SPSS version 23.0. Out of three hundred and fifty (350) HIV-negative and asymptomatic pregnant women examined at first antenatal registration, one hundred and twenty-two (122) were found positive for malaria parasite. The percentage prevalence of malaria positive cases recorded using microscopy was 34.86% (122/350) while PCR confirmed the positivity of 84% (21/25) for both positive and negative samples derived from microscopy. Prevalence of malaria in relation to age, gravidity, and educational qualification were statistically significant while prevalence in relation to occupation, the hospital they attended were not statistically significant. Participants within the age group of 15-19(66.6%), primigravidae (42.6%), primary education (100%) and traders/businessmen had the highest prevalence of malaria. It is therefore recommended that malaria test should be one of the routine tests compulsorily done on pregnant women to avoid complications and public awareness campaign programs on preventive measures against malaria should be regularly conducted to make the journey to eradication of malaria from Nigeria an easier one.
A moving window-based spatial assessment method for dynamic urban growth simulations

Abstract This study proposes a spatial evaluation method for urban growth simulation based on moving windows, where the metrics measured within each window are considered to be those of the central cell. We also applied the generalized additive model to identify the quantitative relationship between the urban growth drivers and the spatial assessment metrics. A case study in Jiaxing city shows that the single-number overall accuracies (OAs) are above 94% and the figure-of-merits (FOMs) are above 27% in both 2010 and 2015. Most regions of the study area yield very high OAs and low FOMs while the regions around the administration centres yield low OAs and high FOMs. The spatial method can well indicate the model’s effects on the urban simulations in different regions. The spatial assessment can report the assessment metrics of each cell to produce assessment maps as well as quantify the relationship between drivers and assessment metrics.
Utilization of Straw Resources May Affect the Speciation of Cd and Its Solubility in Cd-Contaminated Paddy Soil

Rice-wheat rotation has long been the most typical cropping system along the mid-lower reaches of the Yangtse River in China, and the full amount returning of wheat straw before rice season is widely practiced in the rotation system. However, massive incorporation of fresh wheat straw may activate Cd in the soil solid phase and cause more labile Cd entering soil solution in Cd-contaminated soil during the flooded rice season. An incubation experiment was conducted under flooded conditions to investigate the solubility and speciation of Cd and its variation and driving factors with an ongoing decomposition phase in simulated Cd-contaminated paddy soil treated with wheat straw addition. The results indicated that wheat straw addition enhanced Cd solubility, and soluble Cd concentration increased with the ongoing decomposition phase. The observed significant positive correlation (r = 0.648, p < 0.01, n = 77) between soluble Cd concentration and DOC content in soil leachate was gradually strengthened with ongoing decomposition. Wheat straw addition decreased the exchangeable fraction of Cd and increased the residual fraction during the first 5 days of decomposition, while the exchangeable Cd increased and the residual Cd decreased after 10 days of decomposition. The exchangeable Cd increased and the residual Cd decreased gradually with ongoing decomposition. Correlation analysis showed that the exchangeable and residual fractions were sensitive to DOC content. Nitrogen fertilizer input further activated Cd by promoting wheat straw decomposition. In summary, wheat straw addition would activate Cd by increasing Cd solubility and promoting the translation from immobile fraction to labile fraction in Cd-contaminated paddy soil under flooded conditions.
A Survey of Artificial General Intelligence Projects for Ethics, Risk, and Policy

Artificial general intelligence (AGI) is AI that can reason across a wide range of domains. It has long been considered the “grand dream” or “holy grail” of AI. It also poses major issues of ethics, risk, and policy due to its potential to transform society: if AGI is built, it could either help solve the world’s problems or cause major catastrophe, possibly even human extinction. This paper presents the first-ever survey of active AGI R&D projects in terms of ethics, risk, and policy. A thorough search identifies 45 projects of diverse sizes, nationalities, ethical goals, and other attributes. Most projects are either academic or corporate. The academic projects tend to express goals of advancing knowledge and are less likely to be active on AGI safety issues. The corporate projects tend to express goals of benefiting humanity and are more likely to be active on safety. Most projects are based in the US, and almost all are in either the US or a US ally, including all of the larger projects. This geographic concentration could simplify policymaking, though most projects publish open-source code, enabling contributions from anywhere in the world. These and other findings of the survey offer an empirical basis for the study of AGI R&D and a guide for policy and other action.
Data-Based Assembly Patterns for Overall Equipment Effectiveness at Semi-Automatic Assembly Lines

In industrial practice, production planning is a key factor for manufacturers and suppliers. The entire planning process spans from the appearance of the customer demand to the fulfillment of the demand. Operational execution is based on pre-planned production processes and operations using properly allocated resources. The accurate planning of assembly operations within production is an extremely complex process in terms of efficiency. Predicting stochastically variable efficiencies is difficult due to the ever-changing manufacturing conditions. This paper defines typical assembly process situations for a semi-automatic assembly line and examines their consequence for the Overall Equipment Effectiveness (OEE). Firstly, a literature review demonstrates the scientific relevance. Secondly, the classification of patterns based on assembly process description parameters is described taking into account the positive and negative effects on the OEE. In addition, the assembly patterns and their characteristics are illustrated through a real automotive example.
Distributed control reconfiguration of nonlinear interconnected systems in the presence of actuator faults

This article proposes a new method of distributed fault‐tolerant control for a class of nonlinear interconnected systems with actuator faults. This method is based on fault‐hiding idea as a reconfiguration control scheme and tries to redesign the control signal according to the dynamics of the faulty subsystem. Based on fault‐hiding principle, after diagnosing actuator faults, control signals are modified by a predesigned dynamic block which is implemented in the closed‐loop control structure with the same nominal controller. Subsystems are considered as nonlinear Lipschitz systems which interact with each other through nonlinear interconnection dynamics. Because of interactions, occurring a fault in one subsystem causes instability in the overall large‐scale system. A distributed control scheme based on solving a new linear matrix inequality is presented to obtain the control inputs so that it can recover stability and performance of the overall system. Simulation results illustrate and verify the effectiveness of the proposed control approach.
On the Morphological Deviation in Additive Manufacturing of Porous Ti6Al4V Scaffold: A Design Consideration

Additively manufactured Ti scaffolds have been used for bone replacement and orthopaedic applications. In these applications, both morphological and mechanical properties are important for their in vivo performance. Additively manufactured Ti6Al4V triply periodic minimal surface (TPMS) scaffolds with diamond and gyroid structures are known to have high stiffness and high osseointegration properties, respectively. However, morphological deviations between the as-designed and as-built types of these scaffolds have not been studied before. In this study, the morphological and mechanical properties of diamond and gyroid scaffolds at macro and microscales were examined. The results demonstrated that the mean printed strut thickness was greater than the designed target value. For diamond scaffolds, the deviation increased from 7.5 μm (2.5% excess) for vertical struts to 105.4 μm (35.1% excess) for horizontal struts. For the gyroid design, the corresponding deviations were larger, ranging from 12.6 μm (4.2% excess) to 198.6 μm (66.2% excess). The mean printed pore size was less than the designed target value. For diamonds, the deviation of the mean pore size from the designed value increased from 33.1 μm (−3.0% excess) for vertical struts to 92.8 μm (−8.4% excess) for horizontal struts. The corresponding deviation for gyroids was larger, ranging from 23.8 μm (−3.0% excess) to 168.7 μm (−21.1% excess). Compressive Young’s modulus of the bulk sample, gyroid and diamond scaffolds was calculated to be 35.8 GPa, 6.81 GPa and 7.59 GPa, respectively, via the global compression method. The corresponding yield strength of the samples was measured to be 1012, 108 and 134 MPa. Average microhardness and Young’s modulus from α and β phases of Ti6Al4V from scaffold struts were calculated to be 4.1 GPa and 131 GPa, respectively. The extracted morphology and mechanical properties in this study could help understand the deviation between the as-design and as-built matrices, which could help develop a design compensation strategy before the fabrication of the scaffolds.
Research on the Influencing Factors of Consumers' Purchase Intention in WeChat Daigou

After the reform and opening up, the scale of overseas daigou in China has gradually expanded, and WeChat platform has become an important trading platform for daigou by virtue of the integration of virtual community and payment functions. As there are many contents involved in the transaction process, there will be a variety of factors that affect whether consumers are willing to purchase on WeChat. Therefore, based on the analysis of four factors on the basis of the theory and technology acceptance model, with the external environment factors, individual consumers, marketing factors and community factors dimensions of four kinds of factors as independent variables, perceived value as intermediary variables, consumers purchase intention as dependent variable, the WeChat act as purchasing agency in the empirical research on the influence factors of consumer purchase intention, and on this basis, Relevant countermeasures and suggestions are put forward for effective marketing of WeChat purchasing agents.
Measuring innovative capability maturity model of trucking companies in Indonesia

Abstract Trucking companies are important part of supply chains, as they connect most of product movements. While a lot of studies have been done to assess supply chain maturity level, very limited studies have been done to specifically address trucking companies. In this study we develop a model and measurement instruments to assess maturity of trucking companies in terms of their innovative capabilities. Innovative capabilities are critical in today's fast technological development such as industry 4.0 and trucking companies have opportunities to use those technologies to play a better role in the supply chain they involve in. We then use the instruments to assess the maturity level of 52 companies that involved in transporting goods using trucks. The results show that the maturity level has a widespread, ranging from the lowest to the highest level, but most of them are in the category of partial maturity to mature. This indicates that most companies have an opportunity to improve their innovative capabilities.
A Potential Treatment Strategy for the Treatment of Diabetic Kidney Disease in Streptozotocin-induced Diabetic Rats: Leptadenia Hastata Extract

Background: Kidney disorders are serious outcomes of diabetes, resulting in renal ailments. This study seeks to provide an alternative treatment for the disorder through the use of medicinal plants that offer renal protection and ameliorate the deleterious effect of diabetes. Methods: Thirty rats were divided into six groups of five and hyperglycemia was induced by intraperitoneal injection of 50 mg/kg streptozotocin. The rats with a fasting blood glucose level exceeding 250 mg/dl were selected. The L. hastata leaf extract was administered orally and a daily insulin injection was given intramuscularly into the left thigh for 28 days. Rats were then sacrificed and the urine was collected for urinalysis. The kidneys were harvested and examined histologically. The micrographs obtained were subjected to morphometric analyses to evaluate several parameters. Results: The extract-treated groups showed preservation of the cytoarchitecture of the renal tubules and glomeruli as compared to the diabetic control group, which showed distortion of the glomeruli and atrophied renal tubules. The rats that received the extract showed a significantly increased glomerular perimeters and areas (P<0.01). The cellularity was significantly increased (P<0.001); however, the glomerular basement membranes were significantly thicker in these groups compared to the controls (P<0.001). Both the extract-treated and insulin-treated rats showed reduced urine glucose concentrations. Urobilirubinogen, protein, and ketone levels were elevated in the diabetic controls compared to the extract-treated rats. Conclusion: Administration of the L. hastata extract led to renal protection by preserving the cytoarchitecture of the glomeruli and renal tubules, restoring the kidneys’ function.
Fault detection and diagnosis in asymmetric multilevel inverter using artificial neural network

ABSTRACT The increased component requirement to realise multilevel inverter (MLI) fallout in a higher fault prospect due to power semiconductors. In this scenario, efficient fault detection and diagnosis (FDD) strategies to detect and locate the power semiconductor faults have to be incorporated in addition to the conventional protection systems. Even though a number of FDD methods have been introduced in the symmetrical cascaded H-bridge (CHB) MLIs, very few methods address the FDD in asymmetric CHB-MLIs. In this paper, the gate-open circuit FDD strategy in asymmetric CHB-MLI is presented. Here, a single artificial neural network (ANN) is used to detect and diagnose the fault in both binary and trinary configurations of the asymmetric CHB-MLIs. In this method, features of the output voltage of the MLIs are used as to train the ANN for FDD method. The results prove the validity of the proposed method in detecting and locating the fault in both asymmetric MLI configurations. Finally, the ANN response to the input parameter variation is also analysed to access the performance of the proposed ANN-based FDD strategy.
An SISL dual‐band filtering antenna with parasitic strips for 5G applications

This paper proposes a dual‐band filtering patch antenna with out‐of‐band rejection for 5G applications. The design is based on the substrate integrated suspended line (SISL) platform, which combines a T‐junction power divider, a square driven patch with an I‐slot, and two parasitic strips, fed by slot coupling to achieve the desired performance. The working mechanism of dual‐band operation is explained by analyzing |S11| and electric field distribution. The slot on the G5 layer can generate two different resonance modes in the upper and lower frequency bands, and a radiation null is produced simultaneously. The driven patch and parasitic strips generate additional resonant modes, and two radiation nulls are generated, which improve the frequency selectivity. The realized antenna operates in two frequency bands: 3.38–3.6 and 4.73–5.23 GHz. The peak gain can reach 9.11 and 7.61 dBi in the higher and lower bands, respectively. The excellent performance of this antenna provides one more choice for 5G communication systems.
Analisis Kelayakan Sistem Monitoring dan Kontrol Lampu Menggunakan Web Server Berbasis Raspberry Pi

As technology develops progressively over time, system developers continue to strive to create more efficient monitoring systems. The problem that often happens is the control room and light control is currently not utilize an integrated system based web server. Room control systems still utilize large equipment such as televisions and large computers, so that every problem occurs in the room is difficult to control. From these problems then the purpose of this study to create an efficient control system that utilizes super mini-based Raspberry Pi. To create a system based on Raspberry P microcontroller then required an initial observation to perform the feasibility test on the system to be developed. The feasibility test system is the successful monitoring of the room using CCTV (Closed Circuit Television) equipment and control the lamp automatically by using prototyping method. The CCTV feasibility test is viewed from the resolution while the control of room light control is seen from the success of controlling the life of the lights on the test. Based on the testing concluded that the monitoring of the room using Raspberry Pi-based web server is feasible to use, seen the test results when the light control goes smoothly, because the lights controlled through the webserver managed to live and die. Similarly, when monitoring the room with live CCTV also runs well. And while conducting Room monitoring experiments with Webcam at 800 x 600 resolution there is a lot of variation value of frame rate sometimes up and down. The up and down frame is caused by an unstable network connection.