Miracle-dz/UniFAR-FTUs huggingface dataset:
Reliability Data Analysis Procedures for Comparing Failure Rates of the System Using Optimal Truncation of Short Tests

111  Abstract—A test was described for two systems, long term and short term with an exponentially distributed time between failures. The test is intended for checking the ratio MTBFl /MTBFs exceeds or equals a prescribed value, versus one that it is less than the prescribed value, by means of long term tests with large average sample number in the earlier system. Our proposed system focus on improving test by using low average sample number in short term which is having the advantage of economy in time requirement and cost. It produces optimum truncated test called binomial Sequential Probability Ratio Test. Criteria are proposed for determining the characteristics of truncated test followed with the discretizing effect of truncation on error probabilities with a view to optimization of its parameters. The search algorithm for truncation apex used in this system achieves closeness to the optimum which depends on successful choice of the initial approximation, search boundaries and on the search step. The enhanced reliability of modern technological systems, combined with the reduced time quotas allotted for creating new system is capable of yielding a highly efficacious test which increases reliability and feasibility of decisions.
ALOE VERA PROTECTS THE ALUMINIUM INDUCED CHANGES IN TESTICULAR ENZYMES ACTIVITY OF ALBINO RATS, RATTUS NORVEGICUS

The current study was carried out to investigate the protective role of Aloe vera plant extract on aluminium induced changes in testicular enzymes of albino rats. Aloe vera is a medicinal plant belonging to the family –Liliaceae, which has a wide range of therapeutic applications such as wound healing, diabetes, burns, for easing intestinal, curing ulcers and arthritic swellings. 30 adult rats were taken and divided into 3 groups 10 (5+5) for each. Control group animals Animals were fed with normal diet and water ad-libitum, as Group I or control group. Group II animals were fed with normal diet and received aluminium in a dose of 98 mg/kg of body weight orally for 30 and 60 days. Group III were fed with normal diet and received aloin (100mg/kg body weight) and aluminium sulphate (98 mg/kg body weight) for 30 and 60 days. On the last day of the experiment animals were sacrificed by cervical dislocation on 30th and 60th days respectively. Testes were removed and homogenized in buffer, homogenate was centrifuged and supernatant was used for further analysis. The results of the present study clearly indicated that aluminium sulphate has significantly altered the normal levels of testicular LPO and testicular GSH of rat testicular enzymes. But after co treatment of rats with aloin the extract of Aloe vera and aluminum sulphate, the levels of testicular LPO, and testicular GSH reached near to normal level, indicating the protective role of aloin against aluminium sulphate toxicity.
TÜRKİYE ’ NİN AKDENİZ KIYISINDAKİ MAVİ YENGEÇ ( Callinectes sapidus )

Özet: Türkiye’nin Akdeniz kıyılarında bulunan mavi yengeç (Callinectes sapidus) populasyonları arasındaki genetik çeşitliliğin ortaya çıkarılmasında mitokondriyal sitokrom c oksidaz I (COI) geninin nükleotid dizisi farklılıklarından yararlanılmıştır. Akdeniz kıyısı boyunca, 8 farklı populasyondan (Akyatan, Fethiye, Beymelek, Güllük, İskenderun, Köyceğiz, Mersin ve Taşucu) elde edilen 143 örnek nükleotid kompozisyonu ve nükleotid çifti frekansı bakımından incelenmiştir. DNA dizilerinin farklılığı kullanılarak tespit edilen genetik farklılığın belirlenmesinde Tamura 3-parameter modeli kullanılmıştır. DNA dizi analizi gerçekleştirilen 143 örnek göz önüne alındığında, 655 baz çitlik bölgede 42 (%6.41) değişken bölge ve ortalama %1.9 varyasyon saptanmıştır. En yüksek genetik farlılık %2.5 ile Akyatan-Güllük populasyonları arasında tespit edilmiş ve ortalama R değeri tüm populasyonlar için 3.59 olarak hesaplanmıştır. Filogenetik ağacın oluşturulmasında unweighted pair-group method of arithmetic average (UPGMA) yöntemi kullanılmıştır. Dal uzunlukları toplamı= 0.07232 olarak hesaplanan filogenetik ağaç değerlendirildiğinde, mavi yengeç populasyonları arasında coğrafik uzaklıkla korele bir genetik gruplaşma olduğu sonucuna varılmıştır.
Socio-Ecological and Livelihood Assessment of Selected Coastal Areas in Sorsogon, Philippines

A study was conducted to assess the productive capacity of five villages namely Gimagaan, Sevilla, Sogoy, Milagrosa and Saclayan in Sorsogon, Philippines. Specifically, it aimed to assess the productive resource base, resource use and livelihood patterns and provide management prescriptions in the transition of farms into organic agriculture. Sustainable livelihoods analysis and participatory rapid appraisal were the analytical frameworks used in the study. Result of the study revealed that Gimagaan village had the greatest access to asset capitals compared to the other four villages in Sorsogon, Philippines. Gimagaan village highly benefited from the presence of socio-civic and government organizations, residents are more socially inclined and actively involved in the various social activities, have generally good access to their natural resource stocks and infrastructure facilities. On sustainability assessment, results revealed that Milagrosa village was more capable of sustaining management systems of its natural resources, highly resilient against perturbations and had greater chances of improving capacities for social development enterprises. Saclayan village on the other hand, had the lowest access to asset capitals and lowest score in terms of sustainability indicators. Management prescriptions include introduction of farming and fishing technologies which do not require intensive capital; conduct of an in-depth study of fishery-based livelihood project; strengthening the establishment of community-based sanctuaries and mangrove areas; introduction of crop-diversification farming system; and strengthening of the production-market linkage for fishery-based livelihood projects. Keywords— productive capacity, socio-ecological assessment, asset capital, sustainability assessment
Machine Learning Approach for Detection of Malicious Urls and Spam in Social Network

- Twitter is prostrate to malicious tweets having URLs for spam distribution. Conventional Twitter spam detection methods take advantage of account features such as the ratio of tweets containing URLs and the date of creating an account, or relation features in the Twitter graph. These detection methods are ineffective against feature fabrications or consume much time and resources. In this paper we have proposed a machine learning system to find Malicious URLs and spam and to identify whether a given tweet is spam of not in a Social Network such as Twitter. By collecting dataset and training the classifier we classified the input tweet. The Naive Bayes algorithm, a supervised learning model with associated learning algorithms which are used to analyze data used for classification and regression analysis. After classification the sensitivity of each tweet is calculated. After experimental results it is found that the trained classifier is shown to be accurate and has low false positives and negatives
Survey on Micro Clustering Data Streams using Agglomerative Approach

: Data stream mining is an active research area that has recently evolved to mine knowledge from large amounts of continuously generated data. In this context, surveys of several data stream clustering methodologies have been proposed to perform micro clustering. Data stream clustering imposes several challenges to be rectified, such as dealing with non-stationary, unbounded data that arrive in an online fashion. The intrinsic nature of stream data requires the development of algorithms capable of fast and incremental processing of data objects, suitably addressing time and memory limitations. Most of the micro clustering algorithms are object based. In this research paper, we have presented a small survey of the data stream clustering algorithms. This clustering approach has much advantage over many areas such as market analysis (stock market), detection of crime etc,. In addition, this work presents an overview of the usually-employed experimental methodologies. This context may help future researchers on the data stream clustering.
EFFICIENT RETRIEVAL OF IMAGES USING QUERY BASED CLUSTERING SIGNATURES ON WEB IMAGE RANKING

The goal of this approach is to annotate the image s with some manually defined concepts, using visual and contextual features for learning a latent space. Specifically, by feeding the latent vectors into existing classification models, it can be applied to multimedia annotation, which is one of the most important problems in multimedia retrieval. Furthermore, we show a more sophisticated algorithm which can directly incorporate the discriminate information in training example for multimedia annotation without using mapping as a pre-step. It jointly explores the context and content information based on a latent structure in the semantic concept space. As a future enhancement we propose the problem of solving the ambiguity. This solution is the future enhancement where the contribution of providing more accuracy to the proposed system by enhancing using ambiguity resolving problem. Ambiguity is, Middle vision is the stage in visual processing that combines all the basic features in the scene into distinct, recognizable object groups.
ANTIBACTERIAL ACTIVITY AND PHYTOCHEMICAL ANALYSIS OF QUERCUS INFECTORIA AND TERMINALIA CHEBULA

Plants are commonly used as herbal medicine because it contains various secondary metabolites such as alkaloids, flavonoids, saponins and terpenoid etc.Quercus infectoria and Terminalia chebula Retz. Were examined for their antibacterial activity against Methicillin Resistant Staphylococcus aureus. Antibacterial activity ofQuercus infectoria andT. chebula Retz. Was carried out by using the well diffusion method. Ethanol extract of T. chebula were more significant activity against MRSA compared with other solvents. Methanol extract of Q. infectoria showed highest zone of inhibition than other solvents. Minimum inhibitory Concentration of T. chebulawere observed at the ranges from <0.24 to 7.81 mg/ml for all extracts. MIC of theQ. infectoria were showed at the ranges from <0.24 to3.90 mg/ml. This results indicate that the both T. chebula and Q. infectoria have found greatest antibacterial activity against Methicillin Resistant Staphylococcus aureus.
Design of 15T SRAM Bit Cell in 180nm Technology Using Cadence Tool

: SRAM can be found in the cache memory of a computer or as a part of the RAM digital to analog converter on a video card. Static RAM is also used for high-speed registers, caches and small memory banks like a frame buffer on a display adapter. The SRAM consist of bitcell,conventional SRAM of 6T bitcell.the design process with conventional, then 13T SRAM cell with dual feedback method. Stack approach is a leakage power reduction technique, which forces a stack effect.Using stacking effect to the two inverters in the cell and designed 15T SRAM with reduced leakage current and delay.
Semantic Analysis of App Review for Fraud Detection using Fuzzy Logic

— Now-a-days, use of apps has increased with the increasing craze towards mobiles. For all types of mobile application, users are preferring smartphones. Generally, depending on how many users already have downloaded that application? , what are the ratings and reviews? , what are the comments? , etc., users download mobile applications. In the mobile app market, fraud ranking points to false activity that has a reason to push up the mobile apps in the popularity list. Certainly, it turns more periodic for app developers to use fake mechanism. Here, the paper proposes semantic analysis of app review for fraud detection in mobile apps. Firstly we propose to correctly detect the misrepresentation by excavating the active periods, also called as leading sessions, of the mobile apps. Furthermore, we will inspect two types of evidences, namely, ranking-based evidences, review-based evidences and use natural language processing (NLP) to get action words. Next, convert review to ratings and finally perform pattern analysis on session with app data gathered from the app store. So, the paper proposes approach to validate its effectiveness, and also show the scalability of the detection algorithm.
Effects of Nonisothermality and Wind-Shears on the Propagation of Gravity Waves (II): Ray-Tracing Images

Noncommercial 3.0 Unported License http://creativecommons.org/licenses/by-nc/3.0/), permitting all non commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Global Journal of Science Frontier Research: F Mathematics and Decision Sciences Volume 16 Issue 3 Version 1.0 Year 2016 Type : Double Blind Peer Reviewed International Research Journal Publisher: Global Journals Inc. (USA) Online ISSN: 2249-4626 & Print ISSN: 0975-5896
DISTRIBUTED CHANNEL ALLOCATION IN SMART GRID NETWORKS USING PARTICLE SWARM OPTIMIZATION

: Interference between concurrent transmissions can cause severe performance degradation in Smart Grid wireless Mesh networks (SGM). Channel assignments can alter the network topology, which results in higher probability of network partitions, making some nodes unreachable, and can also have an adverse effect on flow of data in an already established wireless mesh network. An Improvised Channel Allocation Mechanism for SGM Networks is proposed, which selects the available channels in a mesh by calculating traffic and bandwidth, and using Particle Swarm Optimization algorithm to select the best or optimal channel among the channels in the pool. The selected channels are assigned to Smart Grid Mesh radios for transmission of data packets. The performance evaluation of the proposed model is simulated in NS-2 and the results are compared with some existing model, and found that the total throughput, the end to end delay and other performance metrics shows better results.
Alzheimer’s Disease and Dementia, Under-Recognized Public Health Crisis in China

Exponential rise in aging population in China projects that the country will be facing an upsurge in the dementia population in next few decades. It is pertinent to improve public knowledge through better understanding of the epidemiology, impact on financial and health system and family, and intervention strategies. This review was conducted to collect Chinese journal publications, government policies, and project documents of Alzheimer’s or dementia over past two decades, as well as to consult Chinese psychiatrists and neurologists with expertise in the field. The results showed that the emerging prevalence of dementia in China is rising far faster than thought, and it has been imposing tremendous challenge to the health and financial system, as well as the community and family members. However, the public awareness is poor, basic and clinical researches are paucity, national supportive strategies are lacking, and the availability of social benefit is inadequate.
Modeling and Optimization of EDM Process Parameters : A Review

Electric discharge machining (EDM) process is one of the most extensively used non-conventional machining processes. The EDM process removes metal without having any direct contact with the work piece. There are different performance parameters which influence on the response parameters such as Metal removal rate and Surface Roughness. Optimization is a techniques used in the manufacturing field to arrive the best manufacturing conditions, which is an essential need for the industries towards manufacturing of quality products. In machining process, it is very difficult to determine optimal cutting parameters for improving machining performance and modeling techniques is necessary to relate the precise relationship between the input and output parameters. This paper provides a review on the various research activities carried out in modeling and optimization of EDM process parameters by various techniques.
IMPROVED OBJECT DETECTION WITH NEURAL NETWORK - SURVEY

Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos.In Image Processing two methods are used CLAASIFICATION and DETECTION. CNN is a one type of Feature Extraction but it is used for detect multiple shape and object. CNN is used as a classification.In this paper we focuses on convolution neural networks and Deep Pyramid technique allowing further insights into their internal operation. After giving a brief introduction to neural networks and its layers, we review supervised training of neural networks in detail. The second section introduces the different types of layers present in recent convolutional neural networks. Based on these basic building blocks, we discuss the architecture of the convolutional neural network. In the third section we focuses on the deep pyramid technique. In DeepPyramid, or pyramid representation, is a type of multi-scale signal representation developed by the computer vision, image processing and signal processing communities, in which a signal or an image is subject to repeated smoothing and sub sampling.
IN VITRO STUDIES ON THE EFFECT OF GARDENIA GUMMIFERA METHANOL EXTRACTS IN MDA-MB-231CELL LINES

The leaves of Gardenia gummifera is commonly known as gummy gardenia/cambi gum tree. It is traditional medicinal plant grown in India, and also has many properties like include anthelmintic, antispasmodic, carminative, diaphoretic, expectorant and used for the treatment of dyspepsia, flatulence for cleaning foul ulcers and wounds. These leaves extracts are found to have antioxidant and anticancer activities. Cycloartanes is the active principle which is responsible for anticancer beneficial effects. This work was aimed to study the effect of Gardenia gummifera on MDA-MB-231 cell lines and the Methanolic extracts of Gardenia gummifera leaves has found to have phytochemical compounds that are moderate inhibitory scavenging and more anticancer activities.
An Efficient Denial-of-Service Attack Detection System Based on Multivariate Correlation Analysis

: Internet is increasingly being used in almost every aspect of our lives and it is becoming a critical resource whose disruption has serious implications. Attacks that aimed at blocking availability of an internet services are generally referred to as denial of service (DoS) attacks. They cause financial losses, as in the case of an attack that prevented users from having steady connectivity to major e-commerce Web sites and imply threat to public safety and national security as in the case of taking down confidential government websites. The consequences of denial of service attacks can be very damaging. Therefore, it is crucial to deter, or otherwise minimize, the damage caused by denial of service attacks. A DoS attack detection system adapted should be able to detect all variants of DoS attacks with efficient computational costs. Thus far various methods have been introduced; however most of them failed to detect new variants of DoS attack and have destitute computation cost. In Multivariate Correlation Analysis based scheme a network features based detection system is introduced. The detection is done based on a normal profile which is generated by applying statistical analysis on the network features. Even though this system has quite good detection rates, some type of DoS attacks are left undetected and have high computation costs. The problems are due to the data used in detection, where the basic features in the original data are in different scales and not optimized. So an efficient detection system is designed by applying Statistical Normalization technique and Particle Swarm Optimization on the raw data to provide efficient detection rates and immaculate computation cost.
Studies on controlled release formulations of a macrolide antibiotic drug: Influence of HPMC of different grades as matrix former

In the present study, several combinations of different grades of hydroxy propyl methyl cellulose (HPMC) such as HPMC-K4M, HPMC-K15M, HPMC-K100M as hydrophilic polymers and hydrophobic polymer like ethyl cellulose(EC) are used to prepare the matrix tablets that resulted in desired and controlled drug release profile. Hydrophobic polymers provide several advantages including good stability at varying pH ranges and effectively retard the release of water soluble drug(s) along with hydrophilic polymers. Erythromycin ethylsuccinate is a model drug and having short half-life of 1.5 hours. Tablets containing 100 mg of drug were formulated by wet granulation. Pre-compression and post-compression parameters were evaluated for all the formulations, which are in the acceptable range. The dissolution data were fitted into zero-order, first-order, Higuchi and Korsemeyer–Peppas models to identify the pharmacokinetics and drug release mechanism. The optimized formulation (F5) prepared with EC: HPMC-K4M in the ratio 10 mg: 5 mg show 99.02% drug release in 24 hours, which is comparable with marketed sample. Kinetic results reveal that all formulations followed zero order. Hence, it can be concluded that the use of low viscous hydrophilic polymer can extend the release of drug up to 24 hours.
POWER QUALITY ENHANCEMENT USING GRID INTERFACED DUAL VOLTAGE SOURCE INVERTER

-------------------------------------------------------------------------------------------------------------------------------------------------Abstract –This paper demonstrates the functions of a dual voltage source inverter (DVSI) to improve power quality and reliability of the microgrid system using instantaneous symmetrical component theory (ISCT). The proposed DVSI scheme consists of two inverters named main voltage source inverter (MVSI) and auxilary voltage source inverter (AVSI) connected to the grid and load at the point of common coupling (PCC). Control algorithms are developed using ISCT to operate MVSI in grid injecting and grid sharing mode and AVSI in compensating reactive, harmonic and unbalanced components in load. Therefore, DVSI scheme has advantages like increase in reliability due to the decrease in failure rate of components and reduction in filter design.
A New Method for Study of Shoot Apices using Epi-illumination Light Microscopy

For study of plant organogenesis, epi-illumination light microscopy (ELM) is considered as an efficient procedure due to its simplicity and low cost feature. In this study, the advantage of digital ELM use in conjunction with new staining method was demonstrated for study of shoot apex ontogeny in Tanasetum baltisma. Anilline blue stained materials revealed good image contrast and quality in compare to previous methods. On the other hands, the new staining method in this study was very fast and simple. Using digital ELM, we were capable to study in detail of the first stages of organ initiation as well as the developmental patterns of shoot apices. Upon our findings, we suggest implementation of the digital ELM as a rapid and low cost technique for plant science investigations. Keyword: Organogenesis, floral initiation, epi-illumination, SEM, aniline blue, depth-of-focus