Miracle-dz/UniFAR-FTUs huggingface dataset:
Barcode-Based Vehicle Parking Monitoring System

: The world today is full of innovations. Every year, people can see and discover different inventions such as in gadgets, machines, electronics, and many others which are timely in this generation which makes these inventions to become life easier. Technology is mostly used by people every day in school, work and offices. Through this, the authors established a paper which applied a technology for parking of vehicles. Vehicles are used to go to school, works, malls, and every place people want to go. Parking a car has always been a problem to the people, especially in the crowded cities. Sometimes it is not always safe to just leave your vehicle in the parking lot because there are people who can use a tool to steal a vehicle, and the monitoring guard will not recognize if he is the real owner. With these problems, the researchers came up with an idea, which is to develop a system entitled ―Barcode-based Vehicle Parking Monitoring System‖. The main purpose of the system is to secure, organize and monitor the parking space in a parking area. The researchers developed the system based from the conceptual framework and system architecture established after determining the problems in the existing problem. The researchers used alpha, beta, and acceptance testing in order to test the functionality of the system. The functionalities of the system were conducted that serves as a testing process. During the pilot test, the respondents rated the system into ―strongly agree‖ description in terms of its functionality, reliability and usability which confirmed that the system accomplished its objectives.
Review Of Network Intrusion Detection Systems

: Intrusion detection system performs a vital role in the security of the computer systems from cyber attacks. Among the IDS, the network intrusion detection system is another type, which is used to protect computer networks from unauthorised access and data theft from intruders. However, current approaches are not feasible and sustainable when used in modern networks because human interaction is increasing its level and detection accuracy is going down by its level. In this paper we have reviewed some of the existing approaches used in NIDS, machine learning methods, Genetic Programming, Fuzzy Inference System and honeypot technology. These methods have achieved accuracy between 62.89% to 88.35%. Existing systems have few flaws like processing delays in large scale networks, high cost for data collection. In the future we will propose better approach to counter these flaws.
Architectural Typology of Mamasa Traditional Graves, West Sulawesi, Indonesia

Mamasa is one of the ethnic groups in West Sulawesi, which has a very unique culture, and the implementation of that culture is seen in the form of traditional architecture in the form of a house as a place to live, as well as other activities such as a traditional grave. This study determines the typology of traditional grave architecture in Mamasa, West Sulawesi, one of the traditional architectural products with high cultural value. This is a qualitative research with data collected through interviews, field observations, and documentation. The qualitative data analysis comprises of collection, presentation, reduction, and drawing conclusions. The results showed that the typology of traditional grave architecture in Mamasa emerged from the ancestral belief in Aluk Mappurondo, which consisted of 5 types, including a) Bangka-Bangka, b) Tedong-tedong, c) Ropi, d) Batutu or alang-alang, and e) Lokko'. The contribution of this research is to introduce one of the traditional architectural products that has high cultural value, as an object of research for scientists interested in traditional architecture or in the field of anthropology, and at the same time contribute in the field of tourism, as a cultural attraction that attracts both local tourists and foreign tourists, for the sake of increasing the country's foreign exchange in the field of Tourism.
Morphology Based Inpainting For Removal Of Markers In Medical Images

: The art of restoring the missing pixels or eliminating the unwanted pixels in an image using an appropriate algorithm is called Inpainting. Inpainting is used in wide range of image processing applications. Processing of medical images requires inpainting to remove markers made by the radiologists. The paper proposes a fast and efficient technique to solve Dirichlet boundary value problem using discrete Laplacian and morphological operations in order to remove the unwanted marking present on the medical images that can complicate further processing. Experimentations were done on 165 medical images and the performance is evaluated. The results enhance a simple and promising way for automatic disease diagnosis interpretation.
Direct Optimization of the Latent Representation for Fast Conditional Generation

Gradient-based optimization of images has been proved to be a promising approach to generating state-of-the-art class-conditional images with crisp details and coherent overall structure. However, the optimization process is considerable more expensive than most class-conditional image generation techniques as the optimization needs to go through both the inference and the image generation networks. We present an alternative approach that eliminates the necessity to back-propagate through the composite architecture. In this way, we have turned the big-optimization problem into the optimization of a simple classiﬁer from a low dimensional vector, which is additionally independent of the dimension of the image.
Improved GNSS-R bi-static altimetry and independent digital elevation models of Greenland and Antarctica from TechDemoSat-1

Abstract. Improved digital elevation models (DEMs) of the Antarctic and Greenland ice sheets are presented, which have been derived from Global Navigation Satellite Systems-Reflectometry (GNSS-R). This builds on a previous study (Cartwright et al., 2018) using GNSS-R to derive an Antarctic DEM but uses improved processing and an additional 13 months of measurements, totalling 46 months of data from the UK TechDemoSat-1 satellite. A median bias of under 10 m and root-mean-square errors (RMSEs) of under 53 m for the Antarctic and 166 m for Greenland are obtained, as compared to existing DEMs. The results represent, compared to the earlier study, a halving of the median bias to 9 m, an improvement in coverage of 18 %, and a 4 times higher spatial resolution (now gridded at 25 km). In addition, these are the first published satellite altimetry measurements of the region surrounding the South Pole. Comparisons south of 88∘ S yield RMSEs of less than 33 m when compared to NASA's Operation IceBridge measurements. Differences between DEMs are explored, the limitations of the technique are noted, and the future potential of GNSS-R for glacial ice studies is discussed.
Microcontroller Based Liquefied Petroleum Gas (LPG) Detector And Controller

In today‟s busy lifestyle, we heard the news related to accidents due to LPG leakage. Now a days everyone is busy with their works. Everyone go to office for job purpose far away from the house. In such cases, if there is leakage of gas at home, no-one is there to pay attention and accidents take place. As well as in case of senior citizens, they may lost their smell sensation and if there is leakage of gas, accidents may occur. The rate of accidents due to leakage of gas is 52 per day in India. From the literature survey, it has been found that, many LPG leakage detectors are available in the market . The working principle of the device is based on sensing the leakage using LPG sensor . The gas sensors will sense the leakage of the gas and then signal send to the microcontroller. The audio as well as video alert is given to the user for taking the appropriate controlling action. It has been also found that there is no device available in the market which detects the LPG gas and also controls its leakage by its own. On the same note, this project is aimed at designing and developing an Innovative “LPG leakage detector and controller”. For detecting the LPG leakage, gas sensor is used which sends signal to the micro-controller to operate the controlling circuit. The controller itself makes the supply of LPG OFF by its own, thus in turn provides safety though the home is locked. The main functions covered while developing the device are, to detect the leakage of LPG on a regular basis, to alert about any hazards that may occur due to LPG leakage by audio and video facility, to implementing controlling actions for LPG leakage, to stop the accidents related with gas leakage and to provide safety. The proposed LPG leakage detector is very useful for today‟s very busy schedule where there is no one at home for the whole day. It has following advantages,
Automatic Plastic Waste Segregation And Sorting Using Deep Learning Model

: In urban areas, solid waste is produced high in percentage. In waste management, segregation of recyclable wastes is a major role. Till now, human intervention is needed to manually segregate these waste materials. This proposed paper describes a system to collect different types of plastic bottles and to perform classification and sorting of the bottles. To identify the plastic bottles instead of using sensors, image processing using machine learning algorithm is proposed in this paper. First step is acquisition of plastic bottle Images and features are extracted by using SURF algorithm. Then the features of bottles are given to the conventional neural network classifier for classification and identified for type of bottle class. The proposed design provides accurate identification of bottle and effective recycling in low cost. This system will ensure effective automated waste management and will speed up the process of segregation without any human intervention.
Comparison of SSD and Faster R-CNN Algorithms to Detect the Airports with Data Set Which Obtained From Unmanned Aerial Vehicles and Satellite Images

Gunumuzde goruntu isleme calismalarinda bircok fakli sektorde, ozellikle saglik, uretim ve askeri alanlarda, dogrudan insan yasantisinda cesitli amaclarla kullanilmaya baslanmistir. Derin ogrenme algoritmalarinin gelismesi ve bilgisayarli gorude kullanilmaya baslanmasi ozellikle askeri alandaki kritik hedef, onemli konum ve stratejik bolge tespiti gibi calismalara hiz kazandirmistir. Bu calismada Airport olarak adlandirilan havaalanlarinin, ucak inis pistleri uzerinden tespiti gerceklestirilmistir. Hem orta ve yuksek irtifali insaniz hava araclarindan hem de uydu goruntuleri kullanilarak egitim, test ve degerlendirme veri setleri olusturulmustur. Tespit yapilmasi surecinde SSD-Single Shot Multibox algoritmasi ve Faster R-CNN algoritmasi yeniden egitilerek kullanilmistir. Her iki algoritmanin sonuclari dogruluk orani, duyarlilik, ozgulluk, yanlis pozitif orani, yanlis negatif orani, dogru tahmin orani, F puani, hata orani, sonuc ve egitim suresi gibi degerlendirme kriterleri kapsaminda degerlendirilmistir. Degerlendirme veri seti uzerinde; SSD mimarisi ile %76,61 dogruluk oraniyla, Faster R-CNN mimarisinde ise %99,52 dogruluk orani ile goruntu tespit sonucu elde edilmistir. Soz konusu calisma ile iki mimariden hangisinin insansiz hava araclari ve uydu goruntulerinde kritik bolge tespitinde ne derece basarili oldugu ortaya cikarilmistir.
A Design Review

Date of publication: 24 September 2018 microgrid currently under construction in Venice, Italy, is part of a plant for testing quasi-zero-emission processes. It has a 400-V ac bus and works islanded and connected. It includes three renewable-source generators and five energy storage (ES) systems (ESSs), based on lithium (Li), lead (Pb), sodium (Na), vanadium, and hydrogen. The hierarchical control uses a master system (Li battery) and slave systems. An energy management system (EMS) with a supervisory-control-and-data-acquisition-like architecture controls the microgrid, providing such features as anti-islanding, lowvoltage ride through, and black start. The EMS performs acquisition, processing, and storage of the data produced by power network analyzers. An advanced human interface ensures flexible operation management and A Real Multitechnology Microgrid in Venice A Design Review
The good and bad sides of exosomes: pre-metastatic niche formation, cancer biomarker and therapy carriers

Exosomes, nanovesicles of endocytic origin, are secreted by most cell types; cancer cells representing no exception. Exosomes facilitate intercellular communication as they deliver diverse proteins, mRNA, miRNA and lipids. In this review, we discuss how exosomes represent one of the main risks associated with cancer but also one of the most promising new tools to fight it. Exosomes appear to function as signalling molecules between the tumour microenvironment, i.e., the complex of both cancer and stromal cells, and the rest of the body. Cancerderived exosomes have been shown to drive the initiation and progression of metastasis, by transporting their cargoes to target tissues. In this respect, exosomes are implicated in cancer progression, dissemination and therapy resistance. However, exosomes are also emerging as a key tool in precision medicine, pivotal for cancer liquid biopsy in early diagnosis and for assessing when there is a recurrence. Profiling exosomal cancer-derived nucleic acids by ultrasensitive next-generation sequencing along with mapping the protein profile utilizing highthroughput proteomics will allow earlier cancer detection, therapeutic stratification and monitoring of response to therapy. Exosomes are also a promising new tool for cancer immunotherapy. Clinically utilizing exosomes for these applications in cancer diagnosis and therapeutics will be the next challenge.
Prioritising Server Bugs via Inter-process Concolic Testing

Existing approaches to automated white-box testing usually consider the client side and the server side of a web application in isolation from each other. Such testers thus lack a whole-program perspective on the web application under test. However, such a perspective may provide multiple benefits. For one, it would allow the tester to automatically discover which server side errors can actually be triggered by an end-user accessing the application via the client interface, and which can only be triggered in hypothetical scenarios. This allows for a classification between high-priority errors, which are reachable by exercising a particular client, and low-priority errors, which are not accessible via the tested client or which are only hypothetical. This classification would allow developers to prioritise correcting those errors that might be encountered by users and postpone correcting other errors that are less easily reachable. Another benefit to this holistic application perspective is that it allows the automated tester to construct practical, step-by-step scenarios for triggering server side errors from the end-users' perspective. We therefore propose an inter-process testing approach to automated white-box testing of web applications, in contrast to the existing intra-process approaches. In this new approach, the tester observes the execution of the client as well as the server process and tracks the application's input across their boundaries. This enables the tester to observe how automatically-generated user input shapes the client's interactions with the server, and how it affects the behaviour of the server itself. We explore the idea of inter-process testing via StackFul, a novel concolic tester which operates on full-stack JavaScript web applications, where both the client side and the server side are JavaScript processes that communicate via asynchronous messages -- as enabled by e.g., the WebSocket or this http URL-libraries. We find that StackFul correctly classifies the majority of server errors. We therefore deem this novel inter-process approach worth investigating further.
Dynamics of root biomass in two eastern Tennessee old-field communities. [Andropogar and Festuca grass communities]

Andropogon and Festuca grass communities were sampled periodically for 1 year to determine root biomass and net root production. Extracted roots were dried, weighed and ashed with all weight values reported as organic matter. Estimated production rates for root biomass ranged from 0.55 to 1.31 g/m/sup 2/ per day for te Andropogon community and 1.38 to 4.02 g/m/sup 2/ per day for the Festuca community. Root biomass increased from 446 to 633 g/m/sup 2/ in the Andropogon community and from 278 to 794 g/m/sup 2/ in the Festuca community during the study period. Eighty-five percent of the root biomass in the Festuca community was in the top 30 cm of the soil as compared to 98 percent in the Andropogon community. Increase in root biomass below 20 cm was small in both communities. The mean root-shoot ratio of the Festuca community (1.40) was nearly twice the mean for the Andropogon community (0.78). (auth)
Oncolytic Virotherapy in Glioma Tumors

Glioma tumors are one of the most devastating cancer types. Glioblastoma is the most advanced stage with the worst prognosis. Current therapies are still unable to provide an effective cure. Recent advances in oncolytic immunotherapy have generated great expectations in the cancer therapy field. The use of oncolytic viruses (OVs) in cancer treatment is one such immune-related therapeutic alternative. OVs have a double oncolytic action by both directly destroying the cancer cells and stimulating a tumor specific immune response to return the ability of tumors to escape the control of the immune system. OVs are one promising alternative to conventional therapies in glioma tumor treatment. Several clinical trials have proven the feasibility of using some viruses to specifically infect tumors, eluding undesired toxic effects in the patient. Here, we revisited the literature to describe the main OVs proposed up to the present moment as therapeutic alternatives in order to destroy glioma cells in vitro and trigger tumor destruction in vivo. Oncolytic viruses were divided with respect to the genome in DNA and RNA viruses. Here, we highlight the results obtained in various clinical trials, which are exploring the use of these agents as an alternative where other approaches provide limited hope.
Preprocedural Use of Povidone-Iodine Mouthwash during Dental Procedures in the COVID-19 Pandemic

1Department of Dental Materials, Islamic International Dental College, Riphah International University, Islamabad, Pakistan 2Department of Prosthodontics and Dental Implantology, College of Dentistry, King Faisal University, Al-Ahsa, Saudi Arabia 3Department of Dental Hospital, College of Dentistry, King Faisal University, Al-Ahsa, Saudi Arabia 4Department of Community Dentistry, University College of Dentistry, The University of Lahore, Lahore, Pakistan Address for correspondence Zohaib Khurshid, MRes, FHEA, MDTFEd, FPFA, BDS, Department of Prosthodontics and Dental Implantology, College of Dentistry, King Faisal University, Al-Ahsa 31982, Saudi Arabia (e-mail: drzohaibkhurshid@gmail.com).
Learning Rich Rankings

Although the foundations of ranking are well established, the ranking literature has primarily been focused on simple, unimodal models, e.g. the Mallows and Plackett-Luce models, that define distributions centered around a single total ordering. Explicit mixture models have provided some tools for modelling multimodal ranking data, though learning such models from data is often difficult. In this work, we contribute a contextual repeated selection (CRS) model that leverages recent advances in choice modeling to bring a natural multimodality and richness to the rankings space. We provide rigorous theoretical guarantees for maximum likelihood estimation under the model through structure-dependent tail risk and expected risk bounds. As a by-product, we also furnish the first tight bounds on the expected risk of maximum likelihood estimators for the multinomial logit (MNL) choice model and the Plackett-Luce (PL) ranking model, as well as the first tail risk bound on the PL ranking model. The CRS model significantly outperforms existing methods for modeling real world ranking data in a variety of settings, from racing to rank choice voting.
Bitcoin Proof of Stake: A Peer-to-Peer Electronic Cash System

Today, Bitcoin core continues utilizing proof of work, a consensus algorithm that is slow, open to 51% attacks, costly to mine, harmful to the environment, and resistant to scalability. There are, however, many innovations unique to Bitcoin that require preservation, such as its 21 million token supply model and proven code-base developed by many of the world’s foremost software engineers and cryptographers.
AAPG HEDBERG CONFERENCE “MICROBIAL CARBONATE RESERVOIR CHARACTERIZATION” JUNE 4-8, 2012 – HOUSTON, TEXAS Controls on High-Frequency Oolite-Microbialite-Coral Reef Sequences, Upper Miocene, SE Spain

In the 1970’s, Esteban and collaborators defined the Terminal Carbonate Complex (TCC) as a distinctive upper Miocene unit distributed around the Mediterranean (Franseen et. al., 1996). The unit consists of oolite, bioclastic units, thrombolite, stromatolites, and some coral reefs, deposited in association with high-amplitude cyclic glacioeustacy and evaporitic drawdown of the Mediterranean (Franseen et. al., 1996). We studied the TCC at two locations in SE Spain, La Molata and Ricardillo (Figure 1). The study areas, approximately 5 km apart, preserve extensive (about 10 km) 3-D outcrop of the TCC associated with different substrate elevations. La Molata was deposited at an intermediate elevation relative to the Miocene sea-level signal, whereas Ricardillo was deposited at a high elevation relative to that signal. At Ricardillo and La Molata, the TCC is composed of oolitic, bioclastic, thrombolitic, stromatolitic and reef facies (Figure 1). Oolite units are important reservoirs for oil and gas throughout the world (e.g. Honda et. al., 1989; Marcal et. al., 1998; Llinas, 2003). Recently discovered reservoirs containing microbial facies of offshore Brazil basins are currently enigmatic but important reservoir systems. The TCC in Spain contains many similar facies to those of the recent discoveries, and exceptional outcrops allow for analysis of controls on 3-D variability.