Miracle-dz/UniFAR-FTUs huggingface dataset:
Developing a multilevel distribuiting crowdsourcing system for aiding and rescuing to overcome widespread crises

Today, the management of different crises in urban areas is among the main challenges of societies due to their scope and limited resources. Using the crowd to solve these problems would be a proper solution. Crowdsourcing, due to a large number of people, the diversity of expertise, superficial dispersion and low cost, has long been considered. However, managing such a volume of people to restore the crisis situation has many problems that modern IT-based techniques in recent years have Facilitates the issue. In this paper, a distributed geospatial system consisting of segments and different users is designed that can be used to manage the crowd to solve the problems of the urban crisis. The system consists of several subsystems and several user groups that operate on the basis of spatial crowdsourcing service. The proposed new service is an atomic, consisting of a guiding section, an operational content, and a control segment. Operational content involves performing a simple activity. Solving complex issues involves the proper combination of simple services. After identifying the crisis environment with system elements, the system design a suitable combination of services for addressing regional issues and then allocate services to appropriate rescuers at the region level. The designed mechanism to allocate and combine services is based on a multidisciplinary agent environment. In order to evaluate, in addition to designing software test scenarios, the system was tested during the Aqala flood of 2019 in Golestan province of Iran. The system accuracy in allocation was as well as its performance when the number of users increased. The system also considerably raised various quality indicators such as rescuer fatigue or mission latency. Furthermore, an innovated crowdsourcing evaluation method also announced the overall system success rate of 44.5 %
Case Report: Accidental exposure to daily long-acting gonadotrophinreleasing hormone analogue administration and pregnancy in an in-vitro fertilization cycle

: A case of successful pregnancy in an in-vitro fertilization cycle, in spite of an accidental exposure to daily long-acting gonadotrophin-releasing hormone analogue administration, is reported. The patient underwent two intracytoplasmic sperm injection cycles with thawed epididymal spermatozoa, in which, due to a pharmacist's mistake, ovarian stimulation was carried out by a combination of long-acting gonadotrophin-releasing hormone agonist (leuprolide depot) and gonadotrophins. A successful singleton pregnancy was achieved after intrauterine embryo transfer with the birth of a healthy boy after 38 weeks. We describe the circumstances and results of this clinical case, as well as reviewing the literature.
ForestHealth, an expert advisory system for assessing foliar and crown health of selected northern hardwoods

Assessment of tree health requires accurate estimates of crown condition and identification of specific biotic and abiotic agents that may affect crowns, stems, or roots. ForestHealth, an expert advisory system written in C language for the Macintosh™ platform, provides a diagnostic module and two training modules. The diagnostic module provides guidance in identifying foliar symptoms and the common insects, diseases, and abiotic disorders found on leaves of: sugar maple (Acersaccharum Marsh.), red maple (Acerrubrum L.), black cherry (Prunusserotina Ehrh.), northern red oak (Quercusrubra L.), and white oak (Quercusalba L.). Graphical user interfaces are central to both training modules. The Foliar Severity routine trains users to categorize injury (percent leaf area) on single leaves using a modified Horsfall–Barratt scale. The Crown Dieback routine displays different types and degrees of crown injury that users must identify and classify. Each crown is unique, generated in "real time" using tree–branch p.
Estrutura horizontal e composição florística de três fragmentos secundários na cidade do Rio de Janeiro - DOI: 10.4025/actascibiolsci.v26i4.1525

Urban forests offer important environmental services for surrounding and respective population. This paper aims at characterizing three forest patches in the city of Rio de Janeiro. To accomplish the task, a phytosociologic survey was carried out using sampling method and units of 10 x 10 meters, where all the individuals with CBH (circumference breast height) equal or larger than 15 centimeters and the same or superior to three meters high were identified and measured. Results have shown significant differences in floristic composition and structure where the families Leguminosae and Moraceae were predominant in the two fragments of larger diversity and Compositae at the one with smaller diversity. Most of the species belong to pioneer succeeding groups, and zoocory was the most important seed-dispersal strategy
The diet of goats, red deer and South American camelids feeding on three contrasting Scottish upland vegetation communities

1. With changes in the agricultural policy for rural areas in the UK there is increased interest in the development of management protocols for indigenous and sown swards in upland Scotland based on grazing by ruminant species other than sheep and cattle, e.g. goats, red deer and South American camelids. 2. Here we describe the diet composition over two seasons of goats, red deer and South American camelids (guanacos) grazing three vegetation types typical of upland ecosystems in the UK: a sown sward (Lolium perenne-dominated), an indigenous grassland (Nardus stricta-dominated) and a dwarf shrub community (Calluna vulgaris-dominated). 3. On each vegetation type, all three animal species were selective feeders. The composition of the goats' diet was more variable than that of the red deer and guanacos. All three species were more selective when grazing the indigenous communities than when grazing the sown sward. 4. On the Lolium sward, the guanacos avoided clover and other dicotyledonous plants, whilst the goats and red deer consumed green leaf from all plant categories found at or near the sward surface. 5. On the Nardus community, all three species avoided the dominant tussock-grass and selected green lamina of broad-leaved grasses from the species-rich inter-tussock areas. Between-species differences in minor components included an increased contribution of non-grass monocotyledonous plants to the goats' diet in spring, and a higher proportion of grass flowerstem and grass seed/flowerhead in the guanacos' diet in summer. 6. The diets of the three species of animal on the Calluna community were broadly similar. All generally avoided C. vulgaris and strongly selected graminoid species. Consumption of grass was greater in spring than summer. 7. Species differences in diet composition, particularly on indigenous swards dominated by N. stricta and C. vulgaris, might facilitate vegetation management and improve animal output using multispecies grazing systems.
Interval Arithmetic based Adaptive Filtering Technique for Removal of Noise in Audio Signal

Active noise cancellation is one of the fundamental problems in acoustic signal processing. The proposed work focuses on the enhancement of audio signal quality by cancelling the noise using interval analysis (arithmetic). An adaptive filters basically works on the concept of optimal weight calculations which is an optimization problem. This optimization problem can be more effectively solved using interval analysis. Interval analysis gives the boundary of the weight co officiants. Using interval Newton method, the weight co officiants are found. This algorithm is tested for noise cancellation of speech signal. The three adaptive filters algorithm used for comparison with the obtained results are Least Mean Square (LMS), Recursive Mean Square (RMS) filters and Kernel based filters. It is observed that the parameters mean square error is very less. The speed of convergence and signal to noise ratio is improved as compared to kernel methods. But processing time is very high and computational cost is doubled, as interval data includes infimum and supremum values. This algorithm can be used in noise cancelling headphones.
Photoacoustics as a diagnostic tool for probing the physiological status of phytoplankton

In nature, conditions for the growth of phytoplankton rarely support their maximal potential doubling rates. The main rate-limiting factor determining the doubling rates of phytoplankters is photosynthesis. This key process is in turn controlled, and frequently limited, by the available light, by lack of essential nutrients, or by the presence of noxious pollutants. Any decrease in the rates of photosynthesis is associated with a reduction in the efficiency of light utilization in that process. We present here the decreased photosynthetic efficiency of phytoplankton upon depletion of nitrogen, phosphorus, and iron as measured by photoacoustics. Such effects have been documented extensively by other methods, such as fluorescence yield, growth rate, carbon assimilation, and oxygen evolution. However, photoacoustics measures directly the energy efficiency of the photosynthetic process. We determined that efficiency by this method in three phytoplankton species belonging to different taxa. Our results illustr.
Optimizing and Load Balancing for Flash Crowd to Improve Quality of Service in Content Delivery Network

The online access has been increasing rapidly with the digitization of information, cheaper Internet service and affordable devices to access the Internet. This entails for not only handling increasing number of web requests but also meeting Quality of Service (QoS) requirements of end-users. Content Delivery Network (CDN) system is used to make better the performance of origin server by storing the popular contents on surrogate servers. The contents are disseminated to the web users through surrogate servers. The performance of CDN system relies on the selection of appropriate surrogate server to satisfy end-users’ requests. The proposed method named Load Balancing using Neighbors and Utility Computing (LBNUC) takes into account requests arrival rate, load on surrogate servers, end-users’ changing demand and capacity of surrogate servers. The aim is efficient utilization of CDN resources to minimize the time required to serve end-users requests and the cost of servicing requests. This method is also effective in handling of flash crowd situation by monitoring request rate. It handles this situation with support from neighbor surrogate servers and arranging additional resources, if required, through utility computing to meet QoS requirement of end-users.
Progress Report: Multiscale Phase Inversion of Anisotropic Data

In this paper, we extend the multiscale phase inversion (MPI) methodology to anisotropic media. The MPI method is developed to avoid the cycle-skipping problem of full waveform inversion (FWI) by temporally integrating the traces several times. The inversion of vp0 with a fixed is initially performed using the multiscale method. Numerical tests on synthetic data demonstrate the feasibility of this method. INTRODUCTION Conventional full waveform inversion (FWI) inverts for a velocity model by using an objective function that minimizes the L2 norm of the residuals between the predicted and the observed traces (Tarantola, 2005; Virieux and Operto, 2009). However, such a misfit function is highly non-linear and the iterations often get stuck in a local minimum. In order to mitigate this problem, a skeletonized representation of the data such as first-arrival traveltimes (Luo and Schuster, 1991a,b; Zhou et al., 1995) can be inverted to obtain the low-to-intermediate wavenumber details of the background velocity model. The misfit function for skeletonized inversion is quasi-linear and enjoys better convergence properties than conventional FWI. The resulting tomograms provide a good starting model for FWI and reduce the likelihood of cycle skipping. However, refraction arrivals only provide the low-intermediate wavenumber information of the shallow part of the model. In order to reach deeper depth, the inversion methods has been extended to reflection waves, such as reflection WT (Ma and Hale, 2013; Shihang et al., 2017) and migration velocity analysis (MVA) (Sava et al., 2005; Sava and Vlad, 2008). However, it is still challenging to invert the velocity distribution with the complex geology such as salt dome. As an alternative, multiscale strategy can also mitigate the cycle skipping problem of FWI (Bunks et al., 1995). Conventional multiscale FWI apply a low-pass filter on the data, so the objective function enjoy less local minimals. The drawback of this method is that sometimes low frequency components are weaker than the high frequency components. To combine the multiscale strategy and skeletonized inversion, Sun and Schuster (1993) develop multiscale phase inversion method, where the recorded data are integrated several times in the time domain to boost the low-frequency components. This method had been successfully applied to crosswell data (Sun and Schuster, 1993) and surface seismic data with isotropic media (Fu et al., 2017). In this paper, we extend the multiscale phase inversion methodology to anisotropic media. After the introduction, the next section of this paper summarizes the theory of this method, and the workflow is in the third section. Numerical tests on synthetic data are shown in the following section and the conclusions are in the last section. THEORY Multiscale phase inversion can be extended to VTI medium by inverting for the anisotropy parameters vp0, and δ using the MPI misfit function,
Computer Software Support to enable Autistic Users to Manipulate Website Design

: - The use of mobile devices for day to day interactions for both professional and personal purposes has exploded in recent years, with most people fully dependent on these devices. As these devices are now cheaper and part of main stream society, some users do not necessarily possess the correct knowledge or mental faculties to interact with these devices correctly. This, in turn, exacerbates limitations within these devices and prevents select users from experiencing the devices content in the same way as others. An example of these limitations would be screen size and the scaling of content to fit such a smaller workspace. As a result, design is a major factor in providing beautiful yet functional spaces, but good functional design layout does not necessarily indicate accessible content. The purpose of this study is to examine Autism and technology, focusing on the effects developers’ design decisions have when interacting with mobile web content.
An Experimental Analysis of Outliers Detection on Static Exaustive Datasets.

-Detecting Outlier and clustering methodologies are an important branch of data mining, by combining the two technologies can improve the data mining significance. Exhaustive data sets by experimental results ensures that the algorithm will improve the efficiency of outlier detection. The outliers may be instances of error or indicate different behavior. The task of outlier detection primarily focused on identifying such outliers so as to improve the data analysis and then find out only interesting and useful information about unusual events within number of application domains. Finding outliers in a group of patterns is a very well-known issue in the data mining. The principle of outlier detection depend on the threshold value. Threshold is generally provided by user. In proposed approach, two methods cluster based approach and distance based approach are applied individually over static data sets to efficiently find the outlier from the data set. The exhaustive datasets can be downloaded from the UCI machine learning repositories. The experimental results of real exhaustive dataset demonstrate that proposed method takes lesser cost in computation and gives better performance than the traditional methods.
(Optimization of Steel Arch Bridge Utilizing Genetic Algorithm)

원형 강관은 단면 특성상 역학적으로 많은 장점을 가지고 있지만 교량 구조물에의 적용은 그다지 활발하지 않았다. 하지만 최근 가공 및 용접 기술의 발달로 인해 강관의 제작과 접합 이 비교적 용이해짐에 따라 강관 구조물의 채 용이 증가하는 추세이며, 아치교에 대한 적용 이 가장 활발하게 진행되고 있다 [1]. 실제 교 량 설계에 있어서는 구조적 안정성 및 경제성 뿐만 아니라 경관성 그리고 기술적 차별화 등 다양한 인자가 고려되지만, 본 논문에서는 구 조적 안정성을 고려한 아치의 형상 및 단면의 최적화를 수행하고자 한다. 구조물의 최적 설계는 설계될 구조물의 특 성에 따라 설계 변수의 선택이 중요한 요소가 된다. 일반적으로 구조물의 설계는 경제적인 측면에서 규격화된 부재를 사용하는 것이 현실 적으로 타당하다. 규격화된 부재는 대량생산이 가능하여 경제성과 편의성을 가지는 가지는 이 점이 있다. 특히 최근에는 구조물의 대형화에 따라 구조물 설계 시에 설계 변수의 증가가 예 상되며, 이 경우 연속 변수를 사용하여 최적 설계 시에는 많은 어려움이 따른다. 이러한 이 유로 구조물 최적 설계는 경제적인 면을 고려 하여 규격부재를 사용하여 설계하는 것이 바람 직하기에 상용화되고 있는 여러 단면 그리고 아치의 높이를 설계 변수로 두고 최적화 과정 을 수행하였다.
Recent developments in accelerated cheese ripening

Abstract Strategies for accelerating the ripening of cheese have traditionally included the use of enzymes like proteinases, peptidases, and lipases. These approaches have shown that the addition of free enzymes to milk or cheese led to uncontrolled biochemical reactions. Consequently, during recent years, new approaches have been attempted to accelerate the cheese ripening process. The addition of liposome-entrapped enzymes and physically or genetically modified lactic bacteria to cheese milk seem to provide some definite advantages. This article reviews the developments in the last 5 yr in this domain dealing with both traditional and untraditional approaches.
Corporate Governance and Firm Performance a Case Study ofPakistan Oil and Gas Companies Listed in Karachi Stock Exchange

In this study the relationship between four Corporate Governance Mechanisms (board size, chief executive status, annual general meeting and audit committee) and two Firm Performance Measures (return on equity, ROE, and profit margin, PM), of Karachi Stock Exchange listed oil & gas firms is examined for the period 2004 2010. The t-test and Multiple Regression analysis are applied to examine the significance & dependency of the above mentioned variables. By using the panel methodology and OLS as a method of estimation, the results provide an evidence of a significant effect and positive relationship between ROE and board size as well as annual general meeting. But ROE has negative relationship with audit committee and CEO status and both have significant effect on it. The results further expose a positive relationship between PM, board size and annual general meeting and they have no significant effect. The study, however, could not provide a significant effect between PM and audit committee. The CEO status and audit committee have a negative relationship with PM but CEO status has a significant effect. The implication of this is that the board size should be limited to a sizeable limit and that the post of the chief executive should be occupied by different persons.
IDENTIFYING OBJECT IN AN IMAGE AND GENERATING CAPTION FOR GIVEN IMAGE

Automatically generating the textual description for an image from an artificial system is known as image captioning. It uses each tongue process and computer vision to get the captions. It is a challenging artificial problem since it requires computer vision to understand the content of the image and a language model from the field of natural language processing to turn the understandings of the image into words. Many techniques proposed to solve this problem. Current approaches or techniques mainly focus on generating captions that are general about image contents.Describing images at a human level and applicable in real life environments is a challenging issue. In this paper, we would implement a neural network based method for image captioning and make it generate the captions for images at a human level by using image captioning, well grounded by the elements of images
Adaptive Security Framework for the Blockchain on IOT

Current blockchain technologies lack adapt- ability required to accommodate incoming heterogeneous devices as nodes in the Blockchain network. This inability becomes more pronounced when it comes to blockchains for Internet of Things (IOT) due to varied capabilities and heterogeneity of constituent devices in IOT network. Specifically, security solutions which are used by Blockchain in IoT domain lack support for adapting with different network resources, ranging from low power devices to high end servers. This paper presents an adaptive security framework for blockchain based IOT architectures. The security framework consists of a dynamic resource computation algorithm based on which the network adapts to the existing resources and decides which security services to offer
Changes in prognostic factors for patients with hepatocellular carcinoma underwent transarterial chemoembolization with the transition of the time: Child-Pugh class, Albumin-Bilirubin grade, and then

Division of Gastroenterology, Department of Medicine, Kurume University School of Medicine, Kurume, Japan; Department of Gastroenterology and Hepatology, Yokokura Hospital, Miyama, Japan Correspondence to: Takumi Kawaguchi, MD, PhD. Division of Gastroenterology, Department of Medicine, Kurume University School of Medicine, Kurume, Japan. Email: takumi@med.kurume-u.ac. jp. Provenance and Peer Review: This article was commissioned by the editorial office, Annals of Translational Medicine. The article did not undergo external peer review. Comment on: Zhao S, Zhang T, Li H, et al. Comparison of albumin-bilirubin grade versus Child-Pugh score in predicting the outcome of transarterial chemoembolization for hepatocellular carcinoma using time-dependent ROC. Ann Transl Med 2020;8:538.
Efficient Ultra-Elastic Resource Provisioning through Hyper-Converged Cloud Infrastructure using Hybrid Machine Learning Techniques.

Ultra-flexibility is future asset provisioning method so as to deftly meet the clients' prerequisite in powerful way. Be that as it may, more components are required for execution improvement, for example, CPU and the capacity. It is trying to decide a reasonable edge to effectively scale the assets up or down. In this paper, we propose an efficient resource provisioning using hybrid machine learning techniques (ERP-HML) that emphasis on mutually advance the vitality utilization of servers and system. Here, the proposed asset provisioning is utilized for ultraversatile cloud benefits in hyper-joined cloud framework. In a Hyper-converged Infrastructure the resources such as CPU, storage and Network will be virtualized and software-defined as pools to meet the current demand. The principal commitment is to present an artificial plant optimization algorithm to improve the administration inertness and lessening over-provisioning of flexible cloud administrations. The subsequent commitment is to delineate a deep Q neural network (DQNN) for anticipating the server's preparing load. At that point, an improved hunting search (IHS) calculation is use to register the quantity of assets that must be provisioned dependent on the anticipated burden. The principle target of proposed ERP-HML strategy is precisely foresee the handling heap of a conveyed server and gauge the proper number of assets that must be provisioned to decrease vitality utilization. At last, the presentation of the proposed ERPHML strategy is contrast and the current condition ofcraftsmanship strategies as far as energy consumption, infrastructure costs and QoS.