Miracle-dz/UniFAR-FTUs huggingface dataset:
Privacy-Aware MapReduce Based Multi-Party Secure Skyline Computation

Selecting representative objects from a large-scale dataset is an important task for understanding the dataset. Skyline is a popular technique for selecting representative objects from a large dataset. It is obvious that the skyline computation from the collective databases of multiple organizations is more effective than the skyline computed from a database of a single organization. However, due to privacy-awareness, every organization is also concerned about the security and privacy of their data. In this regards, we propose an efficient multi-party secure skyline computation method that computes the skyline on encrypted data and preserves the confidentiality of each party’s database objects. Although several distributed skyline computing methods have been proposed, very few of them consider the data privacy and security issues. However, privacy-preserving multi-party skyline computing techniques are not efficient enough. In our proposed method, we present a secure computation model that is more efficient in comparison with existing privacy-preserving multi-party skyline computation models in terms of computation and communication complexity. In our computation model, we also introduce MapReduce as a distributive, scalable, open-source, cost-effective, and reliable framework to handle multi-party data efficiently.
Cortical generators of normal electroencephalographic waveforms: A literature review

Introduction: EEG is a useful, noninvasive, safe technique to study the electrical activity of brain in various physiological and pathological conditions like alertness, sleep, seizure activity. Normal brain rhythms, the electroencephalogram (EEG) represents the electrical activity of brain as recorded through the metal electrodes applied over scalp. An insight to the possible source of EEG, various rhythms and its activation during certain maneuvers can give a better understanding to its applications. Materials and Methods: Number of electronic database, as well as library resources were searched for related references included in published literature till 2017, using following key words ‘cortical’, ‘electroenchephalogram’,’ EEG’,’ EEG Rhythm’,’ EEG wave’, ‘alpha wave’,’ beta wave’,’ theta wave’,’ delta wave’. Those which were related to our subject were included in the review. Results: Of the total number of studies we have finally included 35 studies from search results. These are mentioned in the references. Conclusion: Beta, Alpha, Theta & Delta are produced from various regions of the brain, including cortical & thalamic networks, hippocampus, reticular networks and so on. The rhythm of EEG can be correlated with the level of activation of the brain, with beta wave being produced during alert state and delta wave being produced during deep sleep. Interventions like hyperventilation and photic stimulation can be used to increase the diagnostic yield of EEG. It has been seen that sex-related differences do exist in the degree of lateralization of hemispheric function. Keywords: Electroencephalogram, Brain waves, Cortex, Thalamus, EEG.
Predicting Programmer Quotient

Computing education necessitates programming skill. But it varies in students. How can we quantify or measure the skill? We are yet to have a standardized measurement system for the programming ability. The concept of Programmer Quotient (PQ), which gives a measure of innate programming ability, attributes a value to one's ability to program, just like Intelligence Quotient (IQ). This would remain the same independent of the programming experience. In this paper, we consider few inherent skills such as Analytical ability, ability to synthesize etc. and try to correlate these skills to one's programming ability. A questionnaire was designed and used to measure the skill in these areas. Then a model was designed from the data collected. It can predict the programming skills of a student from his/her inherent skills, irrespective of the programming language.
Mining Specific Content Search using Clustering Algorithm

Overdue problems in information recovery are diagnosed with records in casual corporations and wealthy media content fabric. inside the ones cases, the substance is associated with multilingual, purchaser created views and substance, adaptability, strength and flexibility to mistakes. The graphical model learns is possibly a hopeful term is to be an difficulty term simply as how likely phrases are to be assembled collectively in an inquiry function, and catches the situations among the two elements. Proposed framework upgraded the past work to live faraway from duplication of comparative internet site on line via way of net page parsing and examination of web web page content material fabric. We suggest a bunching calculation is correctly have an effect on the two wonders to therefore mine the foremost subtopics of questions wherein each subtopic is spoken to via a set containing diverse URLs and key terms.moreover brief and gifted ordering and looking administrations are required, for you to scale advanced substance dissemination and video on interest, in which excellent degree of inquiries and substance related errands are done via customers. to assess the span of a hid database, on instinctive concept is to perform topple checking out.
Semi-autonomous robotic wheelchair controlled with low throughput human- machine interfaces

For a wide range of people with limited upperand lower-body mobility, interaction with robots remains a challenging problem. Due to various health conditions, they are often unable to use standard joystick interface, most of wheelchairs are equipped with. To accommodate this audience, a number of alternative human-machine interfaces have been designed, such as single switch, sip-and-puff, brain-computer interfaces. They are known as low throughput interfaces referring to the amount of information that an operator can pass into the machine. Using them to control a wheelchair poses a number of challenges. This thesis makes several contributions towards the design of robotic wheelchairs controlled via low throughput human-machine interfaces: (1) To improve wheelchair motion control, an adaptive controller with online parameter estimation is developed for a differentially driven wheelchair. (2) Steering control scheme is designed that provides a unified framework integrating different types of low throughput human-machine interfaces with an obstacle avoidance mechanism. (3) A novel approach to the design of control systems with low throughput human-machine interfaces has been proposed. Based on the approach, position control scheme for a holonomic robot that aims to probabilistically minimize time to destination is developed and tested in simulation. The scheme is adopted for a real differentially driven wheelchair. In contrast to other methods, the proposed scheme allows to use prior information about the user habits, but does not restrict navigation to a set of pre-defined points, and parallelizes the inference and motion reducing the navigation time. (4) To enable the real time operation of the position control, a high-performance algorithm for single-source any-angle path planning on a grid has been developed. By abandoning the graph model and introducing discrete geometric primitives to represent the propagating wave front, we were able to design a planning algorithm that uses only integer addition and bit shifting. Experiments revealed a significant performance advantage. Several modifications, including optimal and multithreaded implementations, are also presented. Dissertation Supervisor: Dr. Taşkın Padır Title: Associate Professor Electrical and Computer Engineering Northeastern University
Comparative Study between Radiofrequency Ablation Combined with either Percutaneous Ethanol Injection or Percutaneous Acetic Acid Injection in the Management of Hepatocellular Carcinoma.

Background and study aim: Radio-frequency ablation (RFA) has attracted the greatest interest because of its effectiveness and safety. However, complete tumor necrosis rate with RFA for tumors larger than 5 cm is less favorable. Acetic acid, which has the ability to penetrate cells with the property of extracting collagen and dissolving lipids, has a stronger killing effect on hepatocytes than ethanol. The aim of this study was to compare two percutaneous combined therapies, RFA plus percutaneous ethanol injection (PEI) and RFA plus percutaneous acetic acid injection (PAI) in hepatocellular carcinoma (HCC) treatment in patients having single focal lesions more than five and up to seven cm in diameter. Patients and Methods: The patients were selected according to the triphasic CT scanning characteristics of HCC. They were randomly allocated into 2 groups: GI included 30 patients who were candidates for 1 setting of RFA then PEI in the same setting. GII included 30 patients ;they were ablated by 1 setting of RFA with 2 overlaps to decrease the size of the remaining unablated areas, then PAI in the same setting. Results: Evaluation of the response one month later using triphasic CT showed significant better responses in GII compared to GI (83.3% vs 60%) with P value <0.05. The response 3 months later was not changed significantly compared to the response after one month of the procedure (56.7% in GI and 80% in GII) Conclusion: Ablation of inoperable large HCC 5.1-7cm can be done with combined techniques. RFA plus acetic acid was compared to RFA plus ethyl alcohol. Complete ablation was superior when acetic acid was used.
Efficient Adaptive Subarrays in Millimeter-Wave MIMO Systems With Hybrid RF/Baseband Precoding/Combining Design

This paper concentrates on the computationally efficient sub-connected mapping strategies from radio frequency (RF) chains to antennas in millimeter wave (mmWave) massive multiple input multiple output (MIMO) systems with hybrid RF/baseband precoding/combining design. Such an adaptive subarray architecture offers a tradeoff between hardware complexity and spectral efficiency in massive MIMO networks at mmWave frequencies. Three proposed low-complexity dynamically connected structures comprise the Manhattan metric (MM) with/without overlapping, contiguous subarray correlation (CSC), and equally neighboring correlation design techniques. On the basis of the achievable sum-rate (ASR) maximization, the proposed adaptive RF chain-antenna planning methodologies are used to reconfigure effectively RF-chain associated subarrays. Remarkably, both the nonoverlapped MM and the CSC dynamically connected configurations possess excellent advantages of ASR performance and computational complexity simultaneously at a fixed hardware requirement in terms of phase shifters. Finally, simulation results demonstrate that the proposed adaptive partially connected networks are capable of accomplishing an ASR capacity approaching the fully digital and fully connected design with an alleviated demand on both computation and hardware complexities. Furthermore, with the same amount of phase shifters, all the proposed dynamically constructed subarrays outperform the partially connected but fixed architectures.
Big Data Empowered Self Organized Networks

Mobile networks are generating a huge amount of data in the form of network measurements as well as network control and management interactions, and 5G is expected to make it even bigger. In this paper, we discuss the different approaches according to which this information could be leveraged using a Big Data approach. In particular, we focus on Big Data Empowered Self Organized Networks, discussing its most peculiar traits, its potential, and the relevant related work, as well as analysing several cases of its possible application. Finally, we report the results of a case study targeting network-wide Dropped Call/Bad QoS minimization, with the aim of answering the question of how big is the big data to be dealt with according to the proposed approach.
Product twistor spaces and Weyl geometry

Motivated by generalized geometry (a la Hitchin), we discuss the integrability conditions for four natural almost complex structures on the product bundle ${\mathcal Z}\times {\mathcal Z}\to M$, where ${\mathcal Z}$ is the twistor space of a Riemannian 4-manifold $M$ endowed with a metric connection $D$ with skew-symmetric torsion. These structures are defined by means of the connection $D$ and four (Kahler) complex structures on the fibres of this bundle. Their integrability conditions are interpreted in terms of Weyl geometry and this is used to supply examples satisfying the conditions.
Hot corrosion Type II of FeCr‐based model alloys for boiler and heat exchanger applications

The hot corrosion Type II of the alloys FeCr20, FeCr20Ni10, FeCr20Ni20, and FeCr20Co10 is investigated at 700°C in air + 0.5% SO2 with deposits consisting of Na2SO4 and a eutectic mixture of Na2SO4 and MgSO4 for 24, 100, and 300 h. The alloying elements nickel and cobalt have a positive influence when tests are conducted using a MgSO4‐Na2SO4 deposit. In this case, they reduce the metal loss and increase the time to the propagation stage. In contrast, when the alloys are exposed with a Na2SO4 deposit, these alloying elements increase the metal loss and allow for the transition to the propagation stage because they can form molten phases with the Na2SO4. During the incubation stage an oxide scale forms on the FeCr20 alloy, which is thicker than the one formed during exposure without a deposit, and iron oxides are observed, which precipitate in the deposit. The propagation stage occurs by a dissolution and precipitation mechanism forming localized pitting attack. Iron is the main species that dissolves and precipitates, while chromium remains mainly as an oxide beneath the initial surface. The additional elements are found in the pit and in the salt deposit.
Biochemical characterization of Momordica charantia (leaf and fruit) and effect of soluble extract on MCF-7 breast cancer cell lines

Abstract. Ansari AA, Singh J, Aminuddin M. 2019. Biochemical characterization of Momordica charantia (leaf and fruit) and effect of soluble extract on MCF-7 breast cancer cell lines. Cell Biol Dev 3: 1-5. Cancer is a serious worldwide problem targeted by various treatments, including traditional medicinal plants. One known medicinal plant is bitter gourd (Momordica charantia), which has been investigated for its anti-cancerous properties. This study was carried out to explore the biochemical analysis of different components of M. charantia (leaf and fruit) and the effect of alcoholic extract of M. charantia to investigate their potential effect on MCF-7 breast cancer cell line in comparison to cisplatin, a commercial anti-cancer drug. The different components (leaf and fruit) were separated, dried, and converted to powdered form. MCF-7 (human mammary primary epithelial cancer cells) breast cancer cell line was treated with different concentrations (8 - 800 µg/mL) of the soluble extract and cisplatin (all dissolved in DMSO and diluted in the incubating medium) for 48 hours. Initial time course experiments established that maximal cell death occurred between 24-48 hours. Cell viability (cell death) was measured using an established method. The results have shown that with the MCF-7 cell line, the extract at a high concentration (800 µg/mL) was more effective in killing the cancer cells when compared to cisplatin. The present results have clearly shown that the soluble ethanol extract of M. charantia, especially at high doses, can be used effectively to treat breast cancer.
A Microcontroller-based Intelligent System for Real-time Flood Alerting

The development of efficient flood alerting systems became more demanding in the last years. In this paper it is presented the first version of a prototype intelligent system for flood forecasting and real-time alerting. The system is implemented by using a microcontroller from the ARM family, Marvell 88F6281, and has a user interface realized under the Free UnixBSD operating system. Also, a knowledge base is integrated in the system. The real-time alert is sent to the decision making factors via a communication channel (such as, the internet, a mobile phone, or radio communication). Some experimental results obtained so far are also discussed in the paper.
DEEP LEARNING BASED PERSON BIOMETRIC IDENTIFICATION

The article is about the biometric person identification using Deep Learning methods. The issues related to the preprocessong of the signal, the extracting of biometric features and classification are considered. The implementation of the LSTM Deep Learning model, which is a kind of Recurrent neural network, is discussed. Factors affecting the accuracy of biometric identification are being studied
A Commit Strategy for Distributed Real-Time Transaction

Ramamritham gives three common types of constraints for the execution his-tory of concurrent transactions. This paper extends the constraints and gives the fourth type ofconstraint. Then the weak commit dependency and abort dependency between transactions, be-cause of data access conflicts, are analyzed. Based on the analysis, an optimistic commit protocol2LC (two-Level Commit) is proposed, which is specially designed for the distributed real-time do-main. It allows transactions to optimistically access the locked data in a controlled manner, which reduces the data inaccessibility and priority inversion inherent and undesirable in distributed real-time database systems. Furthermore, if the prepared transaction is aborted, the transactions in itsweak commit dependency set will execute as normal according to 2LC. Extensive simulation ex-periments have been performed to compare the performance of 2LC with that of the base protocol,the permits reading of modified prepared-data for timeliness (PROMPT) and the deadline-drivenconflict resolution (DDCR). The simulation results show that 2LC is effective in reducing the num-ber of missed transaction deadlines. Furthermore, it is easy to be incorporated with the existing concurrency control protocols.
THE EXPERIENTIAL LEARNING CYCLE IN VISUAL DESIGN

Experiential Learning Cycle has been applied to the Layout and Graphics Design in Computer Course provided by the Faculty of Communication and Media Studies to the students studying at the Public Relations and Advertising Department. It is hoped that by applying the Experiential Learning Cycle, the creativity and problem solving strategies of the students will be further improved. For the present study, the reactions of the students of the Layout and Graphics Design in Computer Course to adopting Experiential Learning Cycle have been explored.
Real-time Face Tracking

Abstract Face detection and recognition has been a widely researched topic due to its high application value in various fields and industries, such as biometrics, image retrieval. Recently face recognition has also been deployed to aid in counter-terrorism by recognizing hardcore criminals and terrorist in the important installations. In this paper, we present an approach to the real-time detection and recognition of human faces, and the tracking of the face. We have also modified the approach to allow for situations when the face cannot be detected, and we will then track the motion under changing background in real-time. Our approach uses the cascade architecture for face detection proposed by Viola and Jones which uses a feature selection algorithm based on AdaBoost. This architecture has been incorporated into the existing OpenCV library. As for face recognition, we will use ARENA, a simple, memory-based algorithm for face recognition. Due to the rapidly changing background during tracking, we will be using a modified background subtraction method which can adapt robustly and detect the motion. A Canon-VCC4 pan/tilt/zoom camera will be employed to track the face and the motion.
Green synthesis of silver nanoparticles and its physico, phytochemical and antimicrobial properties of Cissus quadrangularis and Gymnema sylvestre from South India.

The emerging branch of Bio-Nanotechnology combines biological principles with physical and chemical approaches to produce nano sized particles with specific functions. Silver nanoparticles has been widely studied due to the excellent physicochemical properties, high chemical stability, catalytic activity and antibacterial activity, eco-friendly nature and cost-effectiveness. The main objective of this work is to green synthesis of silver nanoparticles with Cissus quadrangularisand Gymnema sylvestre and to assess their antibacterial properties. The observed results suggested that using C.quadrangularis and G.sylvestre, synthesised silver nanoparticles and exhibited significant antimicrobial properties. The results demonstrate that the Ag-NPs reported in this work are capable of eradicating pathogenic resistant bacteria in an infection in vivo. Obtained results suggest the potential use of Ag-NPs, synthesized by green chemistry methods, as therapeutic agents against infections caused by resistant and non-resistant strains.
Ensemble feature analysis classifier for sentiment analysis using convolutional neural networks

Text mining is the worldwide fast growing domain in research. Sentiment analysis is the one of the sub domain in the text mining to extract the sentiment from the various texts available in the internet and from other sources. Various existing systems are implemented to get the sentiment analysis with the migration of natural language processing algorithms (NLP) and artificial intelligence algorithms.Various issues identified in the text mining with sentiment analysis are solved very rarely. According to the previous research, deep-learning and artificial intelligencebased TSA prediction method that comprises of a stacked auto encoder (SAE) model that is used to learn generic linguistic and text semantic features But the system not reached up to the mark. In this paper, Ensemble Feature Analysis Classifier to incorporate the new domain dimension within the rating and text based sentiment analyzer. Implementation of this proposed prototype validates our claim and highlights our efficiency in supporting multiple dimensions during sentiment analysis.
Technical overview of nuclear microsatellites for Fagus sp., and their utility in F. sylvatica from the central Balkans (Serbia)

ABSTRACT Selectively neutral nuclear microsatellites (SSRs) are available for Fagus sp. , and have been used in F. sylvatica, an ecologically and economically most important European Fagus species. We provide a comprehensive technical overview of available Fagus sp. SSRs (185 loci), carry out meta-analysis of loci used in F. sylvatica (62 loci employed in 62 surveys), and validate a set of 16 loci in 45 individuals of this species from the central Balkans (Serbia). Erroneous usage of marker’s names/authors is rather frequent, and loci successfully used in a number of studies are characterized by other authors by high prevalence of null alleles and even multilocus amplification products. Frequent occurrence of null alleles at FS4-46, used in 26 surveys to date, most likely indicates a failure to record multiple alleles at this locus. Twelve loci are reliable/informative in F. sylvatica from the Balkans (5–18 alleles/locus, HE ranging from 0.523 to 0.850), while four loci are characterized by high prevalence of null alleles (sfc0161 and sfc1063) and multilocus amplification products (FS4-46 and Fagsyl_007038). Our findings are important for future population genetics and studies on adaptation of F. sylvatica to its environment, because the latter rely on both selectively neutral and adaptive markers under selection.