Miracle-dz/UniFAR-FTUs huggingface dataset:
Polar sea ice characteristics determined from the ENVISAT RA2 altimeter

The ground tracks of ENVISAT satellite cover the high latitude area that of 81.4° over north and south hemispheres, which provides a special approach to monitor sea ice using the RA-2 radar altimeter onboard the ENVISAT satellite. In this paper, we developed a method using the backscatter coefficients 0  measured by RA-2 to detect the monthly changes of sea ice extent and surface properties over Arctic and Antarctic oceans. Based on the difference of scattering characteristics over the sea water and sea ice surface, we demonstrate that setting the RA-2 sigma0 to 13db as a threshold can separate the sea ice from sea water efficiently. Except in the summer of each hemisphere, the sea ice boundaries derived from the RA-2 altimeter and from the radiometer data by NSIDC are closely consistent. Due to the lack of measurements over central areas of Arctic, we estimated the sea ice extent of Antarctic zones only. The result of extents shows that the altimeter gives higher values in summer (southern hemisphere) compared to the radiometer, which is related to the excellent capacity of altimeter to monitor the dispersed thin ice. In cold seasons with high sea ice concentration, the disagreements of sea ice extent are very low as the mean difference is just 0.17Mkm. Differences of polar ice properties, including surface moisture and roughness, were also studied, and result shows that the sea ice surface is dryer and rougher in Arctic than in Antarctic in the cold season. [Lin Zhu, Lei Yang, Dong-xu Zhou, Xing-hua Zhou, Qiu-hua Tang. Polar sea ice characteristics determined from the ENVISAT RA-2 altimeter. Nat Sci 2014;12(8):40-47]. (ISSN: 1545-0740). http://www.sciencepub. net/nature. 7
Histological Effects of Carotenoid On Carbon Tetrachloride Induced Hepatotoxicity In Adult Wistar Rats

This work focuses primarily on the effects of carotenoid on carbon tetrachloride induced hepatotoxicity in adult wistar rats. Twenty four wistar rats weighing between 100-200g were used. The rats were divided into four groups of six animals each. The groups were designated as A, B, C, and D. group A served as the control and received 0.35ml of distilled water. Group B received 0.41ml of carotenoid, group C received 0.41ml of carbon tetrachloride and group D received 0.41ml of carotenoid + 0.41ml of carbon tetrachloride. The drugs were administered orally once in a day using intubation method for a period of 21 days. Twenty four hours after the last administration, the animals were anaesthetized under chloroform vapor and dissected. Liver tissues were removed, weighed and trimmed down to a size of 3mm×3mm tick and fixed in zenkers fluid for four hours for histological studies. The relative liver weight for group c were significantly higher (p<0.001) than the control. The values for group B and D increased significantly relative to the control. Histological analysis revealed distortions of liver tissues in group C when compared with the control. The result revealed that antioxidant property of carotenoid exhibited a liver protective effect against carbon tetrachloride induced hepatotoxicity.
The Impact Of Social Computing Tools In Multi-National Student Project

— The rapid growth of social computing (SC) is changing the way of knowledge exchange and communication in more connected form. The educational institutions are forced to support the digital learning styles of young generation students who seamlessly integrate social network in their daily life. The modern economy insists the need of virtual team and virtual projects s as the organizations look for better talents across boundaries. In this research, the students are assigned with short term project development where the team members are compulsorily distributed from different geographic location and are communicating each other through SC tools. The collaborative learning opportunity enhanced the students towards team work, better communication skills and also helps in mapping cognitive skills with foreign qualification. The study focus on how Web 2.0 social tools blended in project development for the distributed team.
A Survey on Various Ontology Matching Systems

: Due to the abundant growth of the semantic web massive amount of heterogeneous data’s are growing enormously. This problem of heterogeneity among the web resources can be resolved using various ontology matching techniques and systems. Ontology matching is a great way of solving the heterogeneity and interoperability issues among the web data’s that use different but related ontologies. Ontology matching creates a sharable semantic space for the ontologies to access and associate the similar elements across different ontologies. In this paper various existing ontology matching techniques, its limitations and future works are discussed and a brief comparison of all the ontology matching systems is tabulated and presented.
Knowledge Management in the Light of Organizational Factors

The purpose of this paper is to find out the relationship between knowledge management and organizational factors that are organization culture, human resource practices and leadership in an organization. Cross-sectional and quantitative tactic is used in this study. Questionnaires are used to gather the respondent’s views. Kendall tau-b rank correlation coefficient, one-way ANOVA and linear regression are used for testing hypothesis and conceptual model. The results of the analysis show that individual variables (organizational culture, human resource practices and leadership) significantly affect the dependent variable (knowledge management).
A Study on Different Image Retrieval Techniques in Image Processing

— With the popularity of the network and development of multimedia technology, the traditional information retrieval techniques do not meet the users’ demand. Recently, the content-based image retrieval has become the hot topic and the techniques of content-based image retrieval have been achieved great development. In this paper, the basic components of content-based image retrieval system are introduced. Image retrieval methods based on color, texture, shape and semantic image are discussed, analyzed and compared. The semantic-based image retrieval is a better way to solve the “semantic gap” problem, so the semantic-based image retrieval method is stressed in this paper. Other related techniques such as relevance feedback and performance evaluation also discussed. In the end of paper the problems and challenges are proposed. In
Early Indian Metallurgy by Paul T Craddock

The topic of the volume “Early Indian Metallurgy the production of Lead, Silver and Zinc through Three Millennia in North West India”, just published by Archetype Publications in London, discusses archeological data and analytic results, collected in several decades of research in three zinc, lead and silver mines in India. The author of the volume is Paul T Craddock, former Head of Metallurgy in the Department of Scientific Research of the British Museum in London, a well-known scholar that in the past published several important books on topics regarding the field of ancient metallurgy.
Inpainting with Refinement of Vicinity Patches using alpha trim filter for Heritage Sites

Image processing and computer vision have been active areas of research and used in different applications. Few researchers have attempted the use of image processing techniques in the digital preservation of heritage sites. Heritage sites across the world are important sources of knowledge which introduce us to our cultural history, depicting the evolution of humankind. Digital reconstruction of ruined historic monuments and heritage sites can help in visualizing how these may have existed in the past. Also, such a process requires no physical alteration to the existing monuments. Inpainting is the process of restoring image contents imperceptibly. The contribution of this paper is patch based inpainting technique with standard deviation used as a parameter to find the pixel of highest priority. In the search strategy v vicinity patches in the neighborhood of the destination patch with center pixel of v belonging to the boundary of destination patch is used. The vicinity patches are searched merely by looking at the known and unknown pixels of the destination patch. Experimental results carried on a set of 90 images in comparison with standard techniques show improved performance.
Advantage of resistance genetic parameters from several pepaya F1 results (Carica papaya L.) to mealybug pest (Paracoccus marginatus) using choice test method

Papaya is a popular and economically important fruit tree of tropical and subtropical country. This study aims to obtain information on the genetic parameters and the best level of resistance of papaya plants to mealybug pests (Paracoccus marginatus) using the choice test method.This study used a Completely Randomized Design with eleven genotypes as a treatment and repeated three times. Observations carried out included variables (plant height, leaf number, petiol length, stem diameter, leaf area index and dry weight), and resistance variables (intensity of attack, number of ovisaks). The results showed that: The intensity of the fourth week of attack after infestation of mealybug pests on choice test found that the genotypes were resistant to testing were USK7, USK1, and USK1xUSK7; heritability values with high category on choice test were found in the character of plant height, petiol length, dry weight and leaf area index; there is a significant correlation on all the characters of plant growth on the intensity of the attack with the highest value of the character of dry weight with the intensity of the attack on the test with a value of -0.58. * Corresponding Author: Siti Hafsah  sitihafsah@unsyiah.ac. id International Journal of Biosciences | IJB | ISSN: 2220-6655 (Print), 2222-5234 (Online) http://www.innspub. net Vol. 14, No. 3, p. 1-6, 2019
BER Analysis of Wavelet Based OFDM and SC-FDMA for 4 th Generation LTE Using Various Modulation Techniques

: 4 th generation long term evolution(LTE) usesorthogonal frequency division multiplexing (OFDM) and single carrier frequency division multiplexing (SC-FDMA). OFDM contains multiple carriers and it provides higher spectral efficiency compared to frequency division multiplexing (FDM). Use of Wavelets provides good orthogonally and there is no need of cyclic prefixing thus the spectrum efficiency increases. Thus Wavelet based OFDM improves the Bit error Rate(BER) performance.Recent research has shown that the Single Carrier Frequency Division Multiple Access (SC-FDMA) is an attractive technology for uplink broadband wireless communications, because it does not have the problems of Orthogonal Frequency Division Multiple Access (OFDMA) such as the large Peak-to-Average Power Ratio (PAPR). In this paper, an efficient transceiver scheme for the SC-FDMA system, using the wavelet transforms is proposed. In the proposed scheme, the Fast Fourier Transform (FFT) and its inverse (IFFT) are replaced by the Discrete Wavelet Transform (DWT) and its inverse (IDWT). Wavelet filter banks at the transmitter and the receiver have the ability to reduce distortion in the reconstructed signals, while retaining all the significant features present in the signals. The performance of the proposed scheme is investigated with different wireless channels. Simulation results show that the proposed scheme provides better performance, when compared to the wavelet based OFDM, while the complexity of the system is slightly increased. In this paper, BER performance of DWT based OFDM and DWT based SC-FDMA are compared using different modulation techniques such as QPSK,16-QAM,64-QAM.
Extracting User Search Goals by Conceptually Related Feedback Sessions

: This research proposal proposes to enhance search query log analysis by taking into account the conceptual properties of query terms. We first describe a method for extracting a conceptual representation of a search query log and then show how we can use it to relatively extract results with no ambiguity. The concept relation is composed of a set terms frequent together concept relations and of a function to measure the concept distance between terms, which further referred as CTF (concept term frequency). We then sink CTF with feedback sessions, which we build upon click through logs. Further a query terms clustering algorithm that is applied to the log representation to extract user interests.
EPILEPTIC SEIZURE DETECTION: A NONLINEAR APPROACH

Feature extraction and classification of electro-physiological signals is an important issue in development of disease diagnostic expert system (DDES). In this paper we propose a method based upon chaos methodology for EEG signals classification, later on trained by Support Vector Machine. The nonlinear dynamics of original EEGs are quantified in the form of largest Lyapunov exponent (LLE), correlation dimension (CD), capacity dimension (CAD) and were considered for discrimination of various categories of EEG signals. After calculating the above mentioned parameters for signals, we trained the signal by using SVM classifier which shows higher accuracy. So we state that the chaos based parameters will well-being suitable to classify various EEG signals.
Intrusion Detection System Using Deep Learning

Intrusion detection system (IDS) plays a very critical part in identifying threats and monitoring malicious activities in networking system. The system administrators can use IDS to detect unauthorized access by intruders in different organizations. It has become an inevitable element to the security administration of every organization. IDSs can be generally categorized into two categories. The first group focuses on patterns/signatures of network packets/traffic and they identify network intrusions using rule-based matching. The second group uses machine learning (ML) based approaches such as supervised and/or semi-supervised learning and train IDS models on a collection of labeled and/or unlabeled network data. This method has obtained better detection compared to the previous method. This project paper’s scope involves implementing an intrusion detection system using deep learning technology for efficient detection of intrusion and intrusive activities that can cause disruption in the networking system. We use a Feed-forward Neural Network, a deep learning based technique, on KDD99 CUP – a commonly used dataset for network intrusion. In this paper the performance of the proposed system is compared with the existing previous work.
TWO STEP CREDIT RISK ASSESMENT MODEL FOR RETAIL BANK LOAN APPLICATIONS USING DECISION TREE DATA MINING TECHNIQUE

Data mining techniques are becoming very popular nowadays because of the wide availability of huge quantity of data and the need for transforming such data into knowledge. In today’s globalization, core banking model and cut throat competition making banks to struggling to gain a competitive edge over each other. The face to face interaction with customer is no more exists in the modern banking world. Banking systems collect huge amounts of data on day to day basis, be it customer information, transaction details like deposits and withdrawals, loans, risk profiles, credit card details, credit limit and collateral details related information. Thousands of decisions are taken in a bank on daily basis. In recent years the ability to generate, capture and store data has increased enormously. The information contained in this data can be very important. The wide availability of huge amounts of data and the need for transforming such data into knowledge encourage IT industry to use data mining. Lending is the primary business of the banks. Credit Risk Management is one of the most important and critical factor in banking world. Without proper credit risk management banks will face huge losses and lending becomes very tough for the banks. Data mining techniques are greatly used in the banking industry which helps them compete in the market and provide the right product to the right customer with less risk. Credit risks which account for the risk of loss and loan defaults are the major source of risk encountered by banking industry. Data mining techniques like classification and prediction can be applied to overcome this to a great extent. In this paper we introduce an effective prediction model for the bankers that help them predict the credible customers who have applied for loan. Decision Tree Induction Data Mining Algorithm is applied to predict the attributes relevant for credibility. A prototype of the model is described in this paper which can be used by the organizations in making the right decision to approve or reject the loan request of the customers.
Pioneering the Classification in Deep Web Mining

The main purpose of this study is to discuss about web mining and its categories. Web mining is used to achieve information from web data. As now a days there are many users on the web which leads to amount of data generated . In this paper, web mining and its types will be discussed to clear the vision towards data on web how it is processed and managed. It comprises of three types: web content mining, web usage mining and web structure mining. This paper will also focus on analyzing the three types and enhancing their features and capabilities. Web mining technologies has played a vital role in discovering knowledge. Web mining has become more interesting now as it has grown fast in a short span of time in the field of research.
An Improved Buck PFC Converter with High Power Factor

In This paper an improved buck power factor correction (PFC) converter topology is proposed in this paper. By adding an aux-iliary switch and two diodes, the dead zones in ac input current of traditional buck PFC converter can be eliminated. An improved constant ON-time control is proposed and utilized in this improved buck PFC converter to force it that operates in critical conduction mode (CRM). In this paper of voltage source and current wave form in by using MATLAB/SIMULINK
A Framework for Utilizing Serious Games and MachineLearning to Classifying Game Play Towards DetectingCognitive Impairments

Objective: This work presents a framework for geriatricians with interests in exploring the opportunities that serious games and machine learning may offer in assisting with diagnoses of cognitive impairment. Mild Cognitive Impairment (MCI) is often a precursor to more serious dementias, and this work focuses on the potential of applying machine learning (ML) approaches to data from serious games to detect MCI. The focus on MCI detection sets the work apart from mobile games marketed as ‘brain training’ to maintain mental acuity. Materials & methods: Our prototypical game is denoted WarCAT. WarCAT captures players’ moves during the game to infer processes of strategy recognition, learning, and maintenance (memory, or conversely, loss). As with any ML endeavor, effectively demonstrating this conjecture requires large datasets, and thus, the objective of this work is to also develop ML methods to generate synthetic data that can plausibly emulate a large population of players. To generate synthetic data, the ML paradigm of Reinforcement Learning (RL) is being applied as it most closely emulates the way humans learn. Subsequently, The ML-based classification of game-play data to identify varying degrees of cognitive impairment. Results: We have developed RL bots that process millions of gameplay training patterns and achieve gameplay results comparable to the best human performance. This baseline allows us to create bots with various levels of training to emulate individuals at various stages of learning, or by extension, various levels of cognitive decline. Conclusion: The work introduces a framework to demonstrate the characteristics and potential that ML offers to cognitive health diagnosis. Specifically, the work demonstrates the RL work and the ML methods to successfully classify different levels of gameplay.
Face and Expression Recognition Techniques: A Review

—in this review paper, we discuss various techniques for face and expression recognition. Finally, we propose a Hidden Markov Model (HMM)-based face recognition system and Principal Component Analysis (PCA) based expression recognition system. The person is identified using 7-state HMM as classifier and Singular Values Decomposition (SVD) coefficients as features for face recognition. Using quantized SVD as feature describing blocks of the image, each face is considered as a numerical sequence that can be easily modeled by HMM.
E Study of IoT: Understanding IoT Architecture, Applications, Issues and Challenges

-The Internet of Things (IoT) is an emerging and challenging field for researchers. IoT is a network of general objects which are embedded with technologies that helps to communicate and interact within themselves and external environment. This in-turn provides intelligence to the objects to make people life comfortable. In this paper we discussed IoT, its architecture, Relationship between wireless sensor networks (WSN) and IoT. Further we explained different applications of IoT, Current IoT tools for users, IoT advantage, disadvantage and challenges. In this paper we also proposed an idea of using IoT in Indian agriculture domain.
Macular Buckle: Indications and Limitations

Progress in ophthalmology, specifically in macular surgery, is accompanied not only by discovering the new surgical technique, but also by renewed interest to old surgical procedures have been described for the treatment of retinal detachment in myopic macular hole and foveoschisis. The macular buckling was described for the first time in 1957 by Charles L. Schepens, the father of modern retinal surgery, using a radially placed polyethylene tube. In 1966 Rosengren B described a silver ring and plomb technique to indent the macula. The ring is attached to the limbus and an arm fixed to the ring has a terminal ball, which was made to indent the macula. In 1974, Theodossiadis used a silastic sponge rod placed between the inferior oblique insertion and the optic nerve. The rod was stretched vertically across the macula by fixing sutures to produce the required indentation. In 1980, Ando introduced the Ando plombe, consists of a T-shaped semirigid silicone rubber rod internally reinforced with titanium wires and an indenting head at one end. Different types of macular buckles have been proposed, but proper alignment of the buckle under the fovea is still a major concern in this technique.
Angiotensin-II Induced Reactive Oxygen Species: Implications in Neurogenic Hypertension

Abbreviations: Ang II: Angiotensin II; AT1R: Angiotensin Type 1 Receptor; BDNF: Brain-Derived Neurotrophic Factor; CREB: cAMP Response Element Binding Protein; MAP: Mean Arterial Pressure; O2 ●-: Superoxide Anion; ROS: Reactive Oxygen Species; RVLM: Rostral Ventrolateral Medulla; SOD: Superoxide Dismutase; SHR: Spontaneously Hypertensive Rat; TrkB: Tropomyosin receptor kinase B; WKY: Wistar–Kyoto; UCP: Uncoupling Protein; BBB: Blood Brain Barrier ; CaMKII: Calmodulin Kinase II; MAPK: Mitogen-Activated Protein Kinase; TF: Transcriptional Factors; NFκB: Nuclear FactorκB; TH: Tyrosine Hydroxylase; AP-1: Activator Protein-1; 2K1C: Two Kidney One Clip; RVH: Renovascular Hypertension; ESRK: Extracellular Signal-Regulated Kinase; RSK: ribosomal Protein S6 Kinase; COX: Cyclooxygenase; PGE: Prostaglandin E2; IP3: Inositol Triphosphate; SFO: Subfornical Organ; PVN: Paraventricular Nucleus; NTS: Nucleus Tractus Solitaries; ETC: Electron Transport Capacity