Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey on Brain Tumor Diagnosis and Edema Detection Based on Machine Learning

Early brain tumor diagnosis has a significant role in reducing the risk of disease, as well as led to get better treatment results. Usually, magnetic resonance imaging (MRI) images are evaluated manually through visual inspection, which is difficult, time-consuming and often erroneous;this process is performed by radiologists or clinical experts, and its accuracy depends on their experience. Recently, computer-aided diagnosis (CAD) becomes very essential to overcome these limitations. This paper provides a comprehensive assessment of the existing techniques and methodologies for automated detection of brain tumor coupled with oedema detection methods utilisation, with an emphasis on machine learning models. Moreover, this paper provides an analysis of the integrated procedure that pertains to the retrieval of brain pictures by identifying particular data sets in the procedure to recognise the stipulated attributes.
Descriptive Naming & Summarization of large text using Topic Model-A Survey

Due to the plethora of documents containing large scale of text that are available on web it sometimes gets difficult to go through each document to get the clear picture of what the text is depicting. In this paper, we are analyzing several techniques to evaluate Topic Model. A Topic Model is a very popular approach for representing and smoothing the content of documents. Here we will focus on uncovering the thematic structure of a corpus of document that will help in document classification and for compact document topic representation. We have gone through some of the famous topic model such as-Latent Semantic Indexing (LSI),Probabilistic Latent Semantic Indexing (PLSI),Latent Dirichlet Allocation (LDA),Pachinko Allocation Model (PAM) where we encounter few issues such as Topic models are not proper for some SNS such as micro blogging and supervise learning techniques are designed for one-labeled corpus-i. e. they are limiting the document to a single label.
Social media data crowdsourcing as a new stream for environmental planning & monitoring: A review

This research focused on social media applications that had been used by large-scale users. Data might be in the form of text, image, video, each with its own data processing complexity. In this study, the researchers had performed a systematic review of literature on the development and usage of crowdsourcing data collection in recent days, with a range of techniques/methods/approaches to present meaningful data results/conclusions for environmental management. From the collected references, it is found that most papers discuss the monitoring and planning the environment through the use of social media data. An in-depth review of the literature was performed on the state-of-the-art environmental monitoring and planning and the general architecture of the data crowdsourcing system. Finally, based on the literature review, the challenge of data crowdsourcing for environmental monitoring and planning is identified and addressed.
Temperature Effect on Main Girder of Strengthened Dongming Huanghe River Highway Bridge in Service

The main girder of Dongming Huanghe River Highway Bridge was the first prestressed concrete (PC) continuous box girder bridge strengthened by a cable-stayed system in China. In order to study the temperature effect of the main girder structure of Dongming Huanghe River Highway Bridge after reinforcement, based on the measured data of middle span deflection, key section strain and typical crack width, the curve equations of strain and temperature of main girder were obtained by the regression analysis method. The results show that the annual strain value of main girder changed with the acquisition time in a sinusoidal function, and was linearly related to the temperature. The variation of mid-span deflection decreased gradually from side span to middle span, and varied dynamically with temperature in the whole girder, which also has obvious correlation with temperature. The crack width fluctuated up and down in a certain numerical range, which belonged to respiratory cracks and had equally correlation with temperature.
Sensorless Starting Control of Brushless Synchronous Machine (BSM) For Aircraft

In this paper, the sensorless starting control of brushless AC synchronous machine (BSM) for aircraft is studied. Low speed sensorless control technology is the key to accomplish full speed sensorless control. After injected the high frequency voltage with the three-phase AC excitation, the initial rotor position as the response is shown in this paper. On that basis, the sensorless control from starting to low-speed operation is accomplished. The performance of the starting control system is researched using MATLAB simulation software and the feasibility of the proposed scheme is demonstrated by simulation results.
The study of natural biofilm formation and microbial community structure for recirculating aquaculture system

Biofilter is the core unit of the recirculating aquaculture system(RAS), which is mainly to achieve in situ purification and restoration of water pollutants by enriching microorganisms on biofilters to form biofilms. To explore the changes and metabolic characteristics of microbial communities in the process of biofilm formation in the RAS under low-temperature environment, the 16S rRNA high-throughput sequencing was applied to analyze differences of the microbial composition and structural characteristics in the biofilm initiation group (I) and biofilm formation group(B), and the PICRUSt functional gene prediction method was used to predict the metabolic functions. Results of microbial diversity showed that the OTUs numbers, Shannon index and richness index increased significantly after bio-film formation(p<0.05). The Pcoa results indicated that the microbial community composition in group B was quite different compared with the group I. After the biofilm formation, the phylum Proteobacteria, Bacteroidota, Fusobacteriota, Patescibacteria and Verrucomicrobiota were the main dominant bacteria on the biofilter. The denitrifying bacteria, such as Comamonadaceae and Rhodobacteraceae as the dominant bacteria in group B. Meanwhile, the activities of bio-film microorganisms in metabolic aspects of Carbohydrate Metabolism, Energy Metabolism, Lipid Metabolism, Amino Acid Metabolism of Terpenoids and Polyketides and Enzyme Families were obviously enhanced(p <0.05).
Performance Optimization on GPGPU & Multicore CPU Using Roofline Model

The roofline model introduced in this paper to evaluate the best optimized platform for training the neural network that used to recognize handwritten digits under multicore CPU and general-purpose GPU (GPGPU) as hardware environment. The pattern parallel training technique for MNIST dataset is applied. The parallel network training of MNIST using different data layout of multicore CPU and GPGPU is presented. Different bottlenecks have been explained by applying the roofline model. The most suitable platform is selected according to layouts and constrains either for memory or computation bounds. The computational intensity of all rooflines is moved toward right, then the performance is increased. As a result of optimization, and with the diversity of the available data size, core number, operational strength, the most suitable hardware platform is selected.
Research on the Ability of Regional New Energy Consumption Based on the Coupling Coefficients of Time-series

In this study, a method for the investigation of the available capacity of new energy based on the time-series coupling coefficients of the combination of regional wind power, photovoltaic and load was proposed, with the aim of getting an in depth understanding of the regional new energy consumption capacity, and a more accurate amount on the regional potential installation capacity. The typical scenario of new energy high output in the area was determined based on the historical measured power and load data, and the time-series coupling coefficients of the combination of wind power, photovoltaic and load in the area were summarized. The regional new energy consumption capacity and the potential installation capacity for the next three years were quantitatively calculated based on the time-series coupling coefficients. The accuracy and reliability of this method compared with traditional methods were analyzed.
Application of autonomous navigation in robotics

In recent years, the robot industry has made great progress, and has been widely used in automobile manufacturing, machining, transportation agriculture, medical treatment, food and other aspects. The autonomous navigation is a key technology in the development of robot intelligence. Therefore, this paper extensively investigates the applications of autonomous navigation technology in the transfer robot, the medical robot and the agricultural robot. And we analyze and summarize the developments and applications of autonomous navigation related basic technologies, such as autonomous positioning technology, sports planning technology and 5 g communication technology. Finally, the future development prospect of robot technology and the autonomous navigation technology is given.
Development of distance learning devices based on the elicit, confront, identify, resolve, reinforce (ECIRR) model on Newton’s law material

The Outbreak COVID 19 that struck all parts of the country made the government implement several policies to stop the spread of the epidemic, including learning activities carried out at home with online systems or distance learning. This study aims to develop teaching materials based on the ECIRR learning model in distance learning which is being applied by all schools due to the pandemic that is sweeping across the globe. The learning model applied has five steps, namely Elicit, Confront, Identify, Resolve, Reinforce. This type of research is R n D (research and development) research with the ADDIE research model with five steps, namely analysis, design, development, implementation, and evaluation. In this study only at the stagefourth, namely implementation. The material in this study, namely Newton’s Law material held at SMKN 53 Jakarta. This is done because based on the results of the analysis of the needs of students at SMK 53 Jakarta, 53% of students feel they don’t understand Newton’s Law concept properly. The results of the study this, namely the results of the analysis of the validation of material experts obtained an average percentage of 81% in the very high category, the results of the analysis of learning experts obtained an average percentage of 83% with a very high category, the results of the analysis of the media expert obtained a percentage of 96% with a very high, the results of the teacher validation analysis obtained an average percentage of 84% with a very high category.
Running head: MARKETS’ VERDICT ON F1 SPONSORSHIP

The globalization of media content has encouraged the growth of cross-cultural promotional channels; yet empirical evaluations of advertising strategies at an international level are sparse. This paper advances research in this emerging area by analyzing the global financial markets’ valuation of commercial sponsorships in Formula One (F1) motor racing. While previous research indicates U.S. markets approve of similar promotional investments, the results of this international event study demonstrate the market value of firms entering into F1 sponsorships decline upon announcement. The level of investment and nationality congruence of the sponsorship appear to enhance the probability for negative returns in shareholder value.
An Automatic Recognition Method of Fruits and Vegetables Based on Depthwise Separable Convolution Neural Network

Traditional fruit and vegetable classification is mostly based on manual operation, which is inefficient. Deep convolution neural network shows excellent performance in feature learning and expression. In this paper, an automatic recognition system of fruits and vegetables based on deep convolution neural network is designed. By using depthwise separable convolution instead of the traditional standard convolution, a neural network is constructed with less parameters, which is suitable for equipment with limited resources. A small data set including 12 kinds of common fruits and 8 kinds of common vegetables is established for training and testing through network download and physical shooting. The experimental results show that the recognition accuracy reaches 95.67%.
The effect of application of compost and frass from Black Soldier Fly Larvae (Hermetia illucens L.) on growth of Pakchoi (Brassica rapa L.)

Pot experiment was conducted to observe the effect of frass (insect feces) from Black Soldier Fly larvae (BSFL) as soil amendments at different application rates in comparation with other organic fertilizers on Pakchoi (Brassica rapa L). The experimental design was completely random with seven treatments, namely compost, compost+LOB (liquid organic biofertilizer), 5%, 10%, and 15% BSF frass, chemical fertilizer (NPK, equivalent to 10 kg/ha), and soil as a control. After 35 days planting, the result showed that Pakchoi cultivated with compost+LOB, compost, and BSF frass produced the highest biomass compared to control and NPK treatment significantly. The highest total plant weight was achieved in the treatment of Compost+LOB (24.4 gr), followed by 10% BSF frass (23.3 gr), compost (21.8 gr), 15% BSF frass (20.7 gr), 5% BSF frass (19,8 gr), NPK (1.3 gr ) and control soil (0.9 gr). While the chlorophyll content was not significantly different between all treatments, the application of BSF frass tended to be higher but with curly leaf symptoms than other treatments. The population of P solubilizing bacteria and the activity of PME-ase enzyme in soil were also higher in the treatment of compost, compost+LOB, and BSF frass compared to control and NPK treatment.
The Important Role of Gravel and Rocky Beach as A Natural Stable Form of Shore Defense in Southern Garut, West Java

Tectonic processes and high energy waves, tidal phases, generally formed the coasts of southern Java. The grain size of the beach is generally gravel, and large stones. Some pristine beaches consist of pebbly, rocky, sandy beaches or a mixture of sand, gravel, and rocks / boulders. Steep gravel beaches are always associated with coastal erosion. On the other hand, a beach with pebbles and boulders can be a stable natural defense. This location is a preservation of various fossil markers of sea level change and also as a habitat for marine life. A study on geomorphology and sediment types was carried out around the coast of Pameungpeuk, South West Java in May 2016. The purpose of this study was to demonstrate the importance of gravel beaches as natural protection in maintaining stability of coastal habitats and as a barrier from high waves. On the other hand, sandy beaches are highly susceptible to erosion. Exposure to gravel and boulders in front of the beach can act as a barrier to erosion from the beating of waves. Pameumpeuk beach and its surroundings are also a habitat for lobsters because many rock structures are found with holes and their position behind the rock barrier as natural protection.
Extension and validation of a revised Cassie-Baxter model for tailor-made surface topography design and controlled wettability

Predicting wettability accurately across various materials, surface topographies and wetting liquids is undeniably of paramount importance as it sets the foundations for technological developments related to improved life quality, energy saving and economization of resources, thereby reducing the environmental impact for recycling and reuse. In this work, we extend and validate our recently published wetting model, constituting a refinement of the original Cassie-Baxter model after consideration of realistic curved liquid-air interfaces. Our model enabled more meaningful contact angle predictions, while it captured the experimentally observed trends between contact angle and surface roughness. Here, the formalism of our wetting model is further extended to 3D surface topographies, whereas the validity of our model, in its entirety, is evaluated. To this end, a total of thirty-two experimentally engineered surfaces of various materials exhibiting single- and multilevel hierarchical topographies of increasing complexity were utilized. Our model predictions were consistently in remarkable agreement with experimental data (deviations of 3%–6%) and, in most cases, within statistical inaccuracies of the experimental measurements. Direct comparison between experiments and modeling results corroborated that surface topographies featuring re-entrant geometries promoted enhanced liquid-repellency, whereas hierarchical multilevel surface topographies enabled even more pronounced nonwetting behaviors. For the sinusoidal topography, consideration of a second superimposing topography level almost doubled the observed water contact angles, whereas addition of a third level brought about an extra 12.5% increase in water contact angle.
The application of unmanned aerial vehicle photogrammetry for building maintenance (case study : national education museum, universitas pendidikan indonesia)

The use of UAV photogrammetry for three-dimensional modeling continues to be developed to produce models with high accuracy which are then used for documentation, maintenance, and development of the object being modeled. In this research a three-dimensional modeling of the National Education Museum, Universitas Pendidikan Indonesia is one of the landmarks of the Indonesian Education University campus. At the acquisition stage, taking photographs with two flight paths, namely circular grid and vertical grid so as to produce photos with oblique orientation and upright parallel to the face of the building. At the processing stage, scaling is done using field dimension data inputted on the model to produce a model that has dimensions that resemble actual conditions. From the processing results, we get a three-dimensional model that has the shape and texture in accorandce with the original conditions, but there is a large distortion in the glass object. In addition to the accuracy test analysis, there is an RMSe value of 0.278 meters in the comparison of the sizes in the model with the actual conditions
Evidence of residential area of whale sharks in Saleh Bay, West Nusa Tenggara

Saleh Bay is one of the locations where whale sharks (Rhincodon typus) occurrence observed in Indonesia and can be found all year round. Whale sharks broadly distributed throughout tropical and sub-tropical waters of the world’s oceans. Immature male is less than 7 m long, while female is less than 10 m, mostly tend to coastal habitat related. Result of research by Conservation International presented at International Whale Shark Conference in Australia in 2019, Whale Sharks in Saleh Bay had home movement patterns. This study aims to prove that Saleh Bay is the residential area of the whale shark. This study was conducted from November 2019 to January 2020. The Photo-ID data obtained were compared with CI’s Saleh Bay Whale Shark ID Catalog data which last update on April 2020. Surface temperature was measured directly in the range of 29-320C, data for chlorophyll-a were taken from marine.copernicus. eu and bathymetry from cmap.ihms. us then interpolated using QGIS 3.10 software. From this study period, 24 Photo-IDs were obtained from 39 whale sharks, which identified as 23 males, 1 female, and 6 were new individuals from June 2019 to April 2020. The size of the whale sharks recorded in this study ranged from 2,5 to 7 m with 4,86 m in average, and considered as juveniles.
Retraction Retraction: Analysis and Prediction of Epilepsy Using Heart Rate by Application of Ensemble Learning and Linear Regression

In the existing methods the epilepsy was analysed using the PPG, EEG, ECG. The output obtained from the two different signals were analysed and found that the signal obtained while using ECG wearable sensor was more accurate and reliable when compared to the result obtained while using PPG. The main drawback while using EEG signal is the placement of wet scalp electrodes. Hence heart rate is used to analyse epilepsy in the proposed methodin order to obtain accurate and reliable result. In this method analysing the heart rate signal of the patient and epilepsy death rate prediction are two main goals of the project. The biomedical sensors and wearable sensors currently available in the market was studied. Sensors like EEG, ECG, PPG characteristics, and their working were studied completely. In this paper, we have not used any biomedical sensors or wearable sensors. For the heart rate signal, the dataset from the "fitbase" website was collected. Heart rate data collection per minute average heartbeat of the person. heart rate signal data length was 12,000 But only 90 samples were used for ensemble averaging. Not only the heart rate of the signal the epilepsy was also focussed. The epilepsy death rate data from the Statista. Epilepsy data contains year and death for future prediction; a linear regression algorithm was used.
Modeling of nutrient retention ecosystem services in oil palm plantations in Sei Jentikar sub-watershed using ISPO policy approach

Indonesia already has regulations on oil palm plantations that try to maintain good ecosystem services. The regulations are contained in ISPO. However, this regulation has not been fully implemented in oil palm plantations in Sei Jentikar sub-watershed. In this paper, we identify land cover and model N and P nutrient retention in oil palm plantations in the current condition and when ISPO is applied in Sei Jentikar sub-watershed. The method used was land cover identification using supervised classification and rivers using DEMNAS assisted by Google Earth Pro and modeling using the InVEST device. The identification results show the existing condition of oil palm plantation land covering an area of 16 962.99 ha. Meanwhile, when ISPO is applied in the oil palm plantation, the area that cannot be planted is 956.43 ha. This area has a predicted yield of around 2 226.41 tonnes/ha/year. Nutrient retention modeling results in N and P nutrient exports in existing conditions which will increase when approaching the river. Meanwhile, when scenario 2 is implemented, the export of nutrients will decrease in the buffer river. This shows scenario 2 can maintain ecosystem services nutrient retention, but will result in a reduction of value from oil palm production.
Overview of Obstacle Avoidance Algorithms for UAV Environment Awareness

In complex indoor and outdoor environment, obstacle avoidance of UAV (Unmanned Aerial Vehicles) is a challenging problem. In order to realize the obstacle detection, autonomous positioning and trajectory planning of UAV flight mission in large outdoor scene, there are three main technical problems: Firstly, UAV needs to have the ability to quickly detect a variety of obstacles in outdoor scene. Secondly, in order to realize the autonomous navigation of UAV, it needs to establish the coordinates of obstacles in three-dimensional space. Thirdly, based on the above two conditions, UAV can independently plan flight path to avoid obstacles. This paper mainly introduces the use of RGB-D camera, lidar, monocular camera and binocular camera in UAV obstacle avoidance, and compares them from the sensor types, advantages disadvantages and application range. Secondly, the path planning strategy of UAV is discussed, and the existing problems and current research results of UAV trajectory planning strategy are described. Finally, it is pointed out that real-time computing, multi-sensor fusion and integrated obstacle avoidance between multi aircraft should be the research direction of autonomous obstacle avoidance navigation for UAV in the future.