Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of the Influence of Coordination and Supervision in Right to Cultivate Issuance Service on the Performance of Plantation Companies in Jambi Province

Right to Cultivate (HGU or Hak Guna Usaha ) as a legal capital for a plantation business takes a long time to be issued because getting permits as one of the requirements from various institutions is complicated in-process and expensive. This affects the quality of issuance service and comfort for HGU holders to invest and improve their performance in business activities. This study aims to describe and analyze the coordination between agencies related to the issuance of HGU, internal supervision of agencies related to the issuance of HGU, services of HGU issuance, and the performance of HGU holders in Jambi Province. Methodologically, this research fulfills descriptive, explanatory, and exploratory objectives. The population of the study is 120 plantation companies that have obtained HGU in Jambi Province, and there are 165 respondents. Hypothesis testing uses Structural Equation Modeling (SEM). The results of the study show that the coordination between agencies related to the issuance of HGU and the supervision of related agencies positively and significantly affects the service of HGU issuance and the performance of HGU holder companies in Jambi Province. However, those elements have not conducted as expected. Keywords: Coordination, Supervision, Service, Company’s Performance DOI : 10.7176/JESD/10-22-12 Publication date: November 30 th 2019
REDUCED SWITCHING LOSS AC/DC/AC CONVERTER WITH FEED FORWARD CONTROL

This paper presents a novel simplified pulse width modulation (PWM) strategy for the bidirectional ac/dc single phase converter in a micro grid system. Then, the operation mechanism of the novel simplified PWM is clearly explained. The number of switching’s of the proposed simplified PWM strategy is one fourth that of the conventional unipolar PWM and bipolar PWM. Based on the novel simplified PWM strategy, a feasible feed forward control scheme is developed to achieve better rectifier mode and inverter mode performance compared with the conventional dual loop control scheme. The proposed simplified PWM strategy with the proposed feed forward control scheme has lower total harmonic distortion than the bipolar PWM and higher efficiency than both unipolar and bipolar PWMs. Furthermore, the proposed simplified PWM operated in the inverter mode also has larger available fundamental output voltage vab than both the unipolar and bipolar PWMs.
Machine Learning in the Prediction of Costs forLiver Transplantation

Background and aim: Liver transplant is the most effective therapeutic option for patients with end-stage liver disease. The objective of this study is to develop a predictive model of costs after liver transplantation through machine learning using data obtained from the Nationwide Inpatient Sample Database. Methods: We used the Nationwide Inpatient Sample (NIS) database, evaluating data from patients undergoing a liver transplantation procedure for the years 2011 (model training) and 2012 (model validation). Predictors of the total cost (using cost-to-charge ratios), total charges, and length of stay (LOS) were assessed using a combination of machine learning and tree regression models. Results: A total of 2,274 individual patients met our inclusion criteria, 1,090 patients for the year 2011 and 1,184 for 2012. The most important variables predicting cost and LOS were consistent across all models and included the Charlson and Van Walraven comorbidity scores. The best performing model predicting total cost was Support Vector Machine with Linear Kernel with root mean square error (RMSE) values of 0.561 whereas for LOS was the Principal Component Analysis (RMSE=0.743). When evaluating predictors of total cost and LOS, Van Walraven score >26.5 constituted cost-drivers with an average total cost of 207,041 US dollars whereas scores ranging from 21.5-26.4 were associated with a mean increase in the LOS of 26 days. Conclusion: Patient co-morbidities are major drivers of transplants costs, charges and LOS. Machine learning models allow for cost prediction of individual patients, thus allowing for better healthcare management and policy making.
An Proficient Algorithm for Resource Provisioning in Fog Computing

— Cloud computing means sharing of computing resources throughout any communication network by employing virtualization. Virtualization permits a server to be sliced in virtual machines. Every virtual machine has its own applications/operating system that quickly adjust resource distribution. Cloud computing provides several advantages, one of them is flexible resource distribution. To satisfy the needs of clients, cloud environment should be elastic in nature and can be obtain by effective resource allocation. Resource allocation is the phenomenon of allocating existed resources to clients throughout the internet and plays critical role in Infrastructure-as-a-Service (IaaS) model of cloud computing. Flexible resource allocation is needed to optimize the assignment of resources, reducing the response time and increasing the throughput to enhance the cloud computing performance. Enough solutions have been introduced for cloud computing to enhance the performance but for fog computing still effective solution have to be discovered. Fog computing is the virtualized intermediary layer between cloud and clients. It is a highly virtualized technique which is same as cloud and offer computation, data, storage, and networking facilities between cloud servers and end users. This paper presents an effective algorithm and architecture for resources provisioning in fog computing environment by employing virtualization technology .
Implementation of a Native Regularization Scheme Named As Fantope for Similarity Search

This paper introduces a regularization method to explicitly control the rank of a learned symmetric positive semidefinite distance matrix in distance metric learning. To this end, we propose to incorporate in the objective function a linear regularization term that minimizes the k smallest eigenvalues of the distance matrix. It is equivalent to minimizing the trace of the product of the distance matrix with a matrix in the convex hull of rank-k projection matrices, called a Fantope. Based on this new regularization method, we derive an optimization scheme to efficiently learn the distance matrix. We demonstrate the effectiveness of the method on synthetic and challenging real datasets of face verification and image classification with relative attributes, on which our method outperforms state-of-the-art metric learning algorithms.
Detection of Shadow in Very High Resolution Remote Sensing Images Using Different Feature Extraction Methods

: The shadows are mainly observed because of tall buildings, towers etc. in urban areas. To reduce the shadow effects in very high resolution images Remote Sensing (VHR) for their further applications, shadow detection is necessary. In this project, we have addressed the issue of detection of shadow in VHR Remote Sensing images. The shadow detection and classification is done by using (SVM) support vector machine. Noise and wrong shadow regions are handled by using morphological filtering method. While going for shadow detection, first of all extract the features of an image and for extracting that feature two Techniques are used. This two Techniques for Feature Extraction are: 1) Wavelet Decomposition 2) RGB Technique. The Best Results are coming from RGB Technique.
Measurement Properties of Total Ankle Replacement Outcome Measures

Category: Ankle Arthritis Introduction/Purpose: Researchers and clinicians measuring outcomes following total ankle replacement (TAR) are challenged by the wide range of outcome measures used in the literature without consensus as to which are valid, reliable, and responsive in this population. This review identifies region- or joint-specific outcome measures used for evaluating TAR outcomes and synthesizes evidence for their measurement properties. Methods: A standard search strategy was conducted of electronic databases MEDLINE, EMBASE and CINAHL (to June 2015) to identify foot/ankle measures in use. A best evidence synthesis approach was taken to critically appraise measurement properties [COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN)] of identified measures. The review was restricted to English publications and excluded cross-cultural adaptations. Measurement properties collected from each article were coded for validity, reliability, responsiveness, or interpretability. Psychometric evidence exists for identified measures tested in non-TAR populations, but were not the focus of this review. Results: The search identified five measures to include in the best evidence synthesis, which have undergone psychometric testing in a TAR population (Foot Function Index, Ankle Osteoarthritis Scale, American Orthopaedic Foot and Ankle Society Ankle- Hindfoot Scale, Foot and Ankle Outcome Score, Self-Reported Foot and Ankle Score). Methodological quality of the studies providing psychometric evidence was assessed: (1) Validity—Two good quality studies examining different measures provide moderate evidence supporting construct validity (SEFAS; FFI, AOS, AOFAS *subjective items); (2) Reliability—two good quality studies examining different measures provide moderate evidence supporting internal consistency and test-retest reliability (FFI, AOS, AOFAS*; FAOS, SEFAS); (3) Responsiveness—one fair quality study provides limited evidence for AOFAS*, AOS, FFI; (4) Interpretability—two studies provided interpretability values (AOS, FFI, AOFAS*). Conclusion: This review offers a basis for choosing the most appropriate instrument for evaluating TAR outcomes. Numerous outcome measures were identified with evidence supporting their use in populations with various foot/ankle conditions, but none have strong evidence supporting usage in a TAR population. Outcome measures must have adequate psychometric properties in all patient groups in which they are applied. Evidence supporting or critiquing an instrument should not be based on studies with poor quality methodology, as identified by this review. Further testing in a TAR population would benefit identified measures with emphasis on adequate sample sizes, testing a priori hypotheses, and evaluating their content validity for a TAR population.
Nano Computing: An Introduction

Nanocomputing refers to computing devices built from nanoscale components. It is an emerging technology that is at the early stage of its development. An exciting anticipation of nanocomputing is the smaller system size it will provide and the ability to construct systems that use many orders of magnitude more components than in the past. This paper provides a brief introduction to nanocomputing.
Leishmania amazonensis em cão com quadro clínico de leishmaniose visceral no Estado do Paraná, Brasil - relato de caso Leishmania amazonensis in dog with clinical diagnosis of visceral leishmaniasis in Paraná State, Brazil - a case report

Leishmaniasis are antropozoonoses involving various species of Leishmania and hosts, with variable clinical presentations and considered of great importance to public health. This article describes a case of canine leishmaniasis caused by Leishmania amazonensis, from the town of Cambe, Parana state, Brazil. This state is considered endemic for American cutaneous leishmaniasis (ACL) in humans, but this is the first report in a dog in the region, caused by L. amazonensis. The taxonomic characterization of Leishmania was performed by multilocus enzyme electrophoresis technique (MLEE). Clinical signs were similar to those observed in visceral leishmaniasis as polyarthritis and progressive weight loss. It is concluded that the related polyarthritis when related to leishmaniasis, cannot be considered a clinical sign associated only with L. chagasi in view of the L. amazonensis also has this as one of its presentations. The LTA becomes a differential diagnosis of polyarthritis in dogs.
Single-Phase Seven-Level Grid-Connected Inverter for Photovoltaic System

† In this paper proposes a single-phase seven-level inverter for grid-connected photovoltaic systems, with a novel pulse width-modulated (PWM) control scheme. Three reference signals that are identical to each other with an offset that is equivalent to the amplitude of the triangular carrier signal were used to generate the PWM signals. The inverter is capable of producing seven levels of output-voltage levels ( V dc , 2 V dc / 3 , V dc / 3 , 0 (cid:15)(cid:237)9 dc (cid:15)(cid:237) 2 V dc / 3 (cid:15)(cid:237)9 dc / 3) from the dc supply voltage. The photovoltaic (PV) energy is presented as one of the most promising source of clean energy, and so a good way for greenhouse gas emissions mitigation and reduce the fossil fuel dependence. Within it, the photovoltaic energy has caused a huge interest in the electronic converters, and the need to improve their efficiency and reducing their cost. With this work I present a solution for a module scale grid-connected single-phase inverter. The solution consists in a two-stage inverter insolated with a grid line transformer. To the boost control it is implemented a Maximum Power Point Tracking algorithm that can optimize the power extraction from the PV source and for the inverter it is used a sliding mode hysteretic control.
Lichen Planus In A Three Year Old-A Case Report

Introduction: Lichen planus is a very common chronic inflammatory mucocutaneous disorder and the etiopathology of this disease remains obscure. Lichen planus is usually seen to occur commonly in the middle aged and postmenopausal females where as a few cases have been reported in children in the past ten years. Case report: This is a case report of the youngest child patient reported in the outpatient clinic of the Department of Oral Medicine and Radiology in Government Dental College, Kozhikode. The chief complaint was burning sensation on intake of food for a period of two months. The child presented with Lichen planus involving the oral cavity, skin and nails. There was no scalp and genital involvement. The child was treated with topical steroids and symptomatic relief was present. There were no new lesions on the follow up visits. Conclusion: The classic picture of presentation of both adult and childhood. Lichen planus more or less remains the same. The prognosis and the treatment outcome of childhood lichen planus is better when compared to the adult.
3D Visualization and Spatial Data Mining for Analysis of LULC Images

The present study is an attempt made to create a new tool for the analysis of Land Use Land Cover (LUCL) images in 3D visualization. This study mainly uses spatial data mining techniques on high resolution LULC satellite imagery. Visualization of feature space allows exploration of patterns in the image data and insight into the classification process and related uncertainty. Visual Data Mining provides added value to image classifications as the user can be involved in the classification process providing increased confidence in and understanding of the results. In this study, we present a prototype of image segmentation, K-Means clustering and 3D visualization tool for visual data mining (VDM) of LUCL satellite imagery into volume visualization. This volume based representation divides feature space into spheres or voxels. The visualization tool is showcased in a classification study of high-resolution LULC imagery of Latur district (Maharashtra state, India) is used as sample data.
INTRUSION DETECTION SYSTEM: CLASSIFICATION, TECHNIQUES AND DATASETS TO IMPLEMENT

– With the escalation of the internet, Security of network traffic is becoming a major problem of computer network system. As time is passing the number of attacks on the network are increasing. Such attacks on network are nothing but the Intrusions. Intrusion detection system has been used for detecting intrusion and to protect the data and network from attacks. Data mining techniques are used to monitor and analyze large amount of network data & classify these network data into anomalous and normal data. Since data comes from various sources, network traffic is large. Data mining techniques such as classification and clustering are applied to build Intrusion detection system. This paper presents the classification of IDS, different Data mining techniques and datasets for the effective detection of pattern for both malicious and normal activities in network, which helps to develop secure information system. Also it provides a brief study of various datasets that are useful for an intrusion detection system.
IN VITRO SHOOT MULTIPLICATION FROM SHOOT TIP AND NODAL EXPLANTS OF Rauvolfia serpentina (L.) Benth. ex. Kurz, AN ENDANGERED MEDICINAL PLANT

Presence of pharmaceutically important alkaloids in various parts of the plant body made Rauvolfia serpentina an overexploited one and led to its inclusion in Red Data Book of India as an endangered species. Conventional propagation is beset with problems like poor seed viability, low seed germination rate and delayed rooting of cuttings. In vitro clonal propagation may therefore be beneficial for the production of elite plants and subsequent germplasm conservation. Multiple shoots were obtained from shoot tip and nodal explants of Rauvolfia serpentina on MS media supplemented with different concentrations of BAP. Maximum number of shoots was obtained from shoot tip and nodal explants at 13. 32μM BAP. Shoot multiplication and their development was better on MS medium supplemented with 8. 87μM BAP and 2. 85μM IAA for shoot tip explants and 8. 87μM BAP with 5. 71μM IAA for nodal explants. In vitro regenerated shoots were rooted in half strength MS medium fortified with 7. 38μM IBA. The regenerated plantlets were acclimatized and successfully transferred to field condition.
Survey on Driver’s Drowsiness Detection System

There is much attentional impairment while driving that affect driver’s reaction. Among which driving while drowsy is one of the major causes behind road accidents, and exposes the driver to a much higher crash risk compared to driving while alert. Therefore, the use of an assistive system that monitor a driver’s level of vigilance and alert the driver in case of drowsiness can be significant in the prevention of accidents. This paper introduces a new approach towards detection of driver's drowsiness based on yawning measurement and head movement. This involves several steps including the real time detection and tracking of driver’s face, detection and tracking of the mouth contour, the detection of yawning based on measuring both the rate and the amount of changes in the mouth contour area and head movement tracking. Test results demonstrate that the proposed system can efficiently measure the aforementioned parameters and detect driver’s drowsiness.
Dual Input Dual Output Converter for Renewable Energy Applications

With the increasing fossil fuel exhaustion, environmental pollution and global energy demand, the use of renewable energy based clean and non-pollutant energy sources are gaining more importance. Since these sources are highly intermittent in nature, power electronic interfaces are necessary for their efficient utilization. For stand-alone applications, energy storage devices are required for backup and fast dynamic response.Existing converters for such applications use a common dc-link, which employ multiple converters. A single stage dual input dual output DC-DC converter with energy storage system for standalone applications is proposed in this paper. The first input of the converter is from photovoltaic (PV) cells and the second input is a rechargeable battery. The work is intended to minimize the complexity of the converter during the integration of rechargeable battery to Solar PV systems. The existing converter is modified to provide a regulated output voltage and to clamp the PV cells’ voltage to the maximum power point value to maximize efficiency. When the PV cells harvest more power than the load demand, the surplus energy is used to charge the rechargeable battery. When the PV cells cannot harvest sufficient power, the converter schedules the PV cells and the batterytogetherto power the load . The proposed converter has been modelled and simulated using Simulink in the MATLAB. The simulation results proved that the proposed converter works satisfactorily where the load voltage is regulated in all power flow.
Comparative Analysis of Papain from Different varieties of Papaya Plant Latex

Background: Papain is a proteolytic enzyme that catalyzes the breakdown of a protein. It shows several biological functions in plants and animals. It is used in many industries like food, leather, detergents, meat processing and medical application like blood coagulation, fibrinolysis and digestion process. Aim: The present study focused on evaluation of proteolytic activity from lattices of different variety of papaya such as carica papaya, red lady, arca surya and arca prabath. To study the protein concentration of various papaya lateces. Methods and Materials: Four different varieties of papaya latex were collected from different parts of Karnataka. Papain was isolated from latex. Estimation of protein was done by Lowry’s method. Protease enzyme was assessed by Kunitz method. Protease controlling parameters were studied by assessing Temperature, pH, Time and Substrate concentration. Result: Arka Surya showed good activity followed by Arka Prabhath, Red Lady and Carica Papaya. Conclusion: An innovative aspect of the current study helps to determine the protease activity in the different lateces of plant that could have possible positive effect on local economy. © 2014 Universal Research Publications. All rights reserved
Texture Classification using Local Binary Patterns and Modular PCA

 Abstract — Texture classification is one of the traditional challenges in the field of pattern recognition. In this paper, we propose a technique to classify textures using two very powerful tools: Modular PCA (m-PCA) and Local Binary Patterns (LBP). Being an advanced version of conventional PCA, m-PCA focuses more on various portions of a texture, which results into enhanced recognition and improved robustness. On the other hand, LBP is a well-known texture operator, which has been used for object segmentation. The proposed algorithm combines these two feature extraction approaches into one. We get highly competitive results which prove the effectiveness of the proposed methodology.
IN VITRO EVALUATION OF ANTIMICROBIAL ACTIVITY OF Tecoma stans AND Vitex negundo

Plants with antimicrobial activity can serve as potential medicine with lesser side effects. There were many active compounds still present in many medicinal plants which have yet to be discovered. Only the need is to screen them for their potential antimicrobial property. This study aims to evaluate the antimicrobial activities of two medicinal plants – Tecoma stans and Vitex negundo against Pseudomonas aeruginosa and Aspergillus niger.
Artificial intelligence and machine learning: changing paradigm in diagnostics and imaging

Healthcare industry is currently undergoing a digital transformation, and Artificial Intelligence (AI) is the latest buzzword in the healthcare domain. The accuracy and efficiency of AI-based decisions are already been heard across countries. Moreover, the increasing availability of electronic clinical data can be combined with big data analytics to harness the power of AI applications in healthcare. Like other countries, the Indian healthcare industry has also witnessed the growth of AI-based applications. A review of the literature for data on AI and machine learning was conducted. In this article, we discuss AI, the need for AI in healthcare, and its current status. An overview of AI in the Indian healthcare setting has also been discussed.