Miracle-dz/UniFAR-FTUs huggingface dataset:
BIND Battery: Novel Hybrid Battery That Utilizes Mutual Autonomous Control between Lithium-Ion Battery and Lead- Acid Battery

BIND Battery is a novel hybrid battery technology where lithium-ion battery (LiB) and lead-acid battery (PbB) are connected in parallel without DC/DC converter. Most of battery performance during normal use are provided by LiB whereas PbB compensates the intrinsic shortcomings of LiB. During the discharge of BIND Battery, the current distribution between LiB and PbB sub-modules are automatically balanced. In BIND Battery, most of discharge capacity during normal use is provided by LiB and PbB reserves more than half of its capacity as extra energy, resulting in the extension of PbB cycle life. When BIND Battery discharges with relatively high C-rate, LiB takes the majority of total discharge current and reduces the C-rate of PbB. This results in the increase of discharge capacity of PbB. If BIND Battery is overcharged, PbB consumes overcharge energy through its gas recombination reaction and LiB can leave from the overcharge voltage. At extremely low temperature, LiB voltage tend to nose-dive at the beginning of discharge. However, in BIND Battery, PbB supports voltage for a while until LiB voltage recovers by warming up by self-generated heat. PbB also suppresses the degradation of LiB during high-temperature exposure by expelling excess energy and reducing state of charge of LiB. Thus, BIND Battery can withstand harsh environment and provide advanced safety compared to conventional LiB only energy storage system.
Systemic Disease in Patients with Obstructive Sleep Apnea Syndrome

Uykuda solunum bozuklukları, düzenli soluk alıp vermelerin şiddetinde azalma ile kan oksijen düzeyinde düşme, tıkalı farinks varlığında devam eden solunum çabası ve onu takip eden intratorasik basıncın aşırı negatifleşmesi sonucu oluşur. Bunun sonucunda, sempatik aktivitede artış ve uyku yoksunluğuna bağlı sistemik enflamatuvar mediyatörlerde yükselme ile tüm sistemler etkilenmektedir. Obstrüktif uyku apne sendromunda (OUAS), gelişen aşırı sempatik aktivasyon, endotel disfonksiyonu, artmış oksidatif stres, artmış sistemik enflamasyon, koagülasyon ve leptin artışı gibi değişiklikler ile diğer sistem organ ve dokularında fizyopatolojik değişikliklere yol açmaktadır (1,2). OUAS, kronik hipoksi ve hiperkarbinin etkisi ile en fazla nörolojik ve kardiyovasküler sistemde yaşam kalitesini etkileyen komplikasyonlara ve hastalıklara neden olmaktadır. Uykuda görülen kronik aralıklı hipoksi-reperfüzyon hasarına benzer bir etki göstermektedir. Ayrıca, uyku bölünmesi pro-enflamatuvar bir süreci tetikleyerek, interlökin-6, tümör nekrozan faktör alfa salınımını arttırmaktadır. Bunun yanı sıra OUAS’ın kronik solunum yolu hastalıkları, endokrinolojik ve metabolik hastalıklar ile depresyonun gelişmesinde ve ilerlemesinde rol oynadığı bilinmektedir (2). Bu çalışmada, hastanemiz uyku laboratuvarında Aralık 2013Ocak 2015 yılları arasında OUAS tanısı almış 304 olguda, OUAS ile birlikteliği saptanan sistemik hastalıklar ve görülme oranları araştırılmıştır. Objective: In this study, we investigated 304 patients diagnosed with Obstructive sleep apnea syndrome (OSAS) and undergoing standard polysomnography in our sleep laboratory between December, 2013 and January 2015 in terms of anamnesis, drugs used and laboratory test results. Materials and Method: Chronic diseases were detected in patients and their relations between OSAS were investigated. Results: Severity of the disease in all patients was investigated under 3 topics according to Respiratory disturbance index (RDI). According to the results as severity of the OSAS increases, co-occurrence with systemic diseases increases. Conclusion: In this study, co-occurrence of OSAS and chronic systemic diseases, characteristics of OSAS and the relation between OSAS and chronic systemic diseases were investigated.
QUANTUM BASED ADAPTIVE TOPOLOGY CONTROL FOR INTRUSION DETECTION AND ISOLATION IN MANET

: A mobile ad hoc network (MANET) is an infrastructure-less network where the number of mobile nodes is independently moved in a random direction within the transmission range of the network. Due to the movement of mobile nodes, the network topology is changed arbitrarily. Therefore, various intrusions are presented in MANET. For accurate and robust intrusion detection against several attack and deceiving actions, SIEVE technique was designed in MANET. However, node mobility of the ad hoc network restricts the BP algorithm efficiency and it’s difficult to identify attack behavior. Therefore, security is a most important concern in decentralized structure of mobile network. In order to develop the intrusion detection and isolation in MANET, Quantum based Adaptive Topology Control (QATC) technique is developed. In QATC, an adaptive topology control is designed to adjust the transmission range of the mobile nodes to extend the lifetime of networks by retaining the network connectivity. This topology leaves maximum possible nodes connected in a cluster zone with minimum energy consumption and transmission interference. This helps to increase the packet delivery ratio. After this, the arriving and leaving nodes are monitored and the malicious node is identified from the network, through Quantum Mechanism. Quantum mechanism is typically used to detect the malicious node from the network using specific key distribution. Due to this, the malicious nodes are easily detected and isolated, aiming at improving the Malicious node detection rate with minimum time. A simulation result shows that the Quantum based Adaptive Topology Control (QATC) technique achieves higher packet delivery ratio, malicious node detection rate and reduces energy consumption, and time to identify the malicious node compared to state-of-the-works.
Computer-aided detection of prostate cancer within the peripheral zone in T2-weighted magnetic resonance imaging

The aim of this research is to develop a computer-aided detection system for prostate cancer within the peripheral zone, based on single modality T2-W Magnetic Resonance Imaging. As the most diagnosed and second leading cause of death from cancer in men, prostate cancer is a significant health problem globally. In fact, considering the deficiencies in current clinical screening methods, there is a need for a rapid development of MRI technologies and computer algorithms to better detect prostate cancer. In this thesis, we developed one unsupervised, and two supervised computer algorithms, using different texture descriptors involving different resolutions, filters, techniques and orientations. For classification purposes, we investigated 11 machine learning algorithms to build predictive models. This thesis also investigated the effects of window sizes for all performance metrics. In the proposed unsupervised method a small number of texture descriptors were used to differentiate benign and malignant regions. Subsequently, the fuzzy c-means clustering algorithm was employed to segment malignant regions. The resulting binary segmentations were then combined to find overlapping regions with the highest probability of being malignant. In contrast, the two supervised methods were based on 215 texture descriptors and textons. Both methods used the same machine learning algorithms in the training and classification phases. To evaluate the performance of the proposed methods, the unsupervised and supervised methods were tested based on 37 (275 MRI images) and 45 (418 MRI images) patients, respectively. The performance evaluations showed that the results of all methods were comparable with the state-of-the-art in the literature in terms of area under the curve, classification accuracy, sensitivity and specificity. The contributions of this thesis are three-fold. First, we developed novel supervised and unsupervised computer-aided detection systems for prostate cancer, which are different from those produced hitherto, in the sense of our methods exploit different combinations of texture descriptors and machine learning algorithms. In fact, this thesis is the first study which has thoroughly investigated textons in prostate cancer detection. Secondly, this thesis made an extensive investigation into the effects of window size, both on the methods and feature’s performance itself. Thirdly, we provide an extensive quantitative comparison of the performances of 11 machine learning algorithms and a thorough qualitative comparison between our results and the state-of-the-art in the literature.
A Framework to Ensure Quality of Service with New Trail and Security in Networks

: - We present a method to find another path, after link failures, from a source node to a destination node, before the Interior Gateway Protocol (e.g., OSPF or IS-IS) has had a chance to recon-verge in response to the failure. The target application is a small (up to tens of nodes) regional access sub-network of a service providing networks, which is typical access scale encountered for the practice. We can illustrate the method and prove that it will found in a path if one exists. In the non-swapped mode once the fault is detected on the protected LSP, the LSR takes the packet from the local bu ﬀ er and looks at the packet header (“shim” header or MPLS header) and then proceeds to swap it for the corresponding output label and changes the output interface. Note that this is the second time that the LSR looks at this header. The ﬁrst was when the packet arrived at the LSR for the ﬁrst time to be copied to the local bu ﬀ er. This method introduces delays, processing overhead and additional CPU requirements. When it sending first time we are sending the data in an encryption format and we are selecting two paths of nodes information in that we are sending the encrypted data in first path if in case the data in first path was failed again immediately it will select the another second path and in this second path we are encrypting data again and resending the data after that it received in destination area again they will decrypt the data with the two algorithms we are used and the receiver can receive the data without damage and in a secured manner by using this process like this we can send the data in safe manner and very fast from source to destination .
Mitigation of Interference in GSM Networks by Complex Weights Perturbation of Adaptive Array Antenna

Proper weighting of array elements of an adaptive antenna system enables us to determine the desired beam pattern and place nulls in the direction of the interfering signal. Therefore array pattern synthesis is a very important aspect of the smart antenna system which makes it possible to maximize the signal-to-interference ratio. In this paper, an efficient method for array pattern synthesis in uniform linear arrays with the prescribed null and beamforming is presented. Analysis of interference control by both fixed weight and adaptive patterns synthesis are considered in this presentation.
Detection of UDP and HTTP Anomalies on Real Time Traffic Based on NIDS using OURMON Tool

UDP traffic has recently been used extensively in flooding-based distributed denial of service (DDoS) attacks, most notably by those launched by the Anonymous group. the use of this criterion to classify UDP traffic with the goal of detecting malicious addresses that launch flooding-based UDP DDoS attacks. We conducted our experiments on real time network traffic including large corporations (edge and core), ISPs, universities, financial institutions, etc. In addition, we also conducted experiments on ourmon tool of our own. All the experiments indicate that proportional packet rate assumption generally holds for benign UDP traffic and can be used as a reasonable criterion to differentiate DDoS and non-DDoS traffic. We designed and implemented a prototype classifier based on this criterion and discuss how it can be used to effectively thwart UDP-based flooding attacks.
Air Pollution Measuring System with Mobile Sensor Arrays

Environmental air pollution has significant influence on the concentration of constituents in the atmosphere leading to effects like global warming and acid rains. To avoid such adverse imbalances in the nature, an air pollution measuring system is utmost important. The traditional air quality monitoring system, controlled by the Pollution Control Department, is extremely expensive. Analytical measuring equipment is costly, time and power consuming, and can seldom be used for air quality reporting in real time. Wireless Sensor Networks are a new and very challenging research field for embedded system design automation, as their design must enforce stringent constraints in terms of power and cost. This paper attempts to develop an effective solution for pollution measuring using wireless sensor networks (WSN). The gas sensors are integrated with the ARM controller and location tracer GPS in User terminal. Other parameters like temperature are also sensed along with gas pollutant to enable data analysis through data aggregation techniques. Experimentation carried out using the developed air pollution measuring system under different physical conditions show that the system collects reliable source of fine-grain pollution data along with location of mobile vehicle. The system collects pollution data using mobile hardware modules, transmits the data regularly using GSM MODEM to a back-end server, and integrates the data to generate a pollution frame with geographical location and send to handheld devices of the user.
DESIGN AND DEVELOPMENT OF HYBRID COUPLER WITH FR 4

986 All Rights Reserved © 2013 IJARECE  ABSTRACT Hybrid couplers are widely used in microwave circuit design. The principle of a hybrid coupler is that the input power is split equally between the coupled and through ports, with a 90 degree phase difference. The fourth (isolated) port is terminated by a 50-ohm load. Hybrid coupler can be directly connected to microstrip antenna to get circular polarization. Microstrip patch antennas being popular because of light weight, low volume, thin profile configuration which can be made conformal. Wireless communication systems applications circular polarization antenna is placing vital role. In this study the hybrid coupler is designed for 2.4GHz with impedance (z0) is 50Ω, dielectric constant εr is 4.6 and thickness of dielectric material is 1.6mm. Simulation is done by ADS software.
Hybrid and Adaptive Block Based Watermarking Algorithm Using DWT-DCT and Artificial Neural Network

In this paper we propose the use of artificial neural networks (ANN) to predict the most suitable areas of an image for embedding. This ANN is trained based on the human visual system (HVS) model. Only blocks which produce least amount of perceivable changes are selected by this method. A joint DWT and DCT based watermarking technique with low frequency watermarking with weighted correction is proposed. DWT has excellent spatial localization, frequency spread and multi-resolution characteristics, which are similar to the theoretical models of the human visual system (HVS). In the proposed method watermark bits are embedded in the low frequency band of each DCT block of selected DWT sub-band. Compared with the similar approach by DCT based approach and DWT based approach, the experimental results show that the proposed algorithm apparently preserves superior image quality and robustness under various attacks such as JPEG compression, scaling, filtering, and so on.
Time Evolving Rating Prediction with Privacy Preserving and Defending Sybil Attack in Online Services

Opinions, Reviews and trust based systems have become essential ingredients of web-based multi-agent systems. All of these systems aggregate agents reviews of one another, as well as about external events, into valuable information. Prefered in companies like development systems like Google's page ranking system , Amazon and E-Bay's recommendation and reputation systems , and the Epinions web of trust/reputation system . Trust-based recommendation systems study how people forming reviews via colleagues , that helps in finding out mal users reviews based on the ratings expressed by trusted friends. Where existing system has has the finding reviews at a particular time. In real life, a user's opinion evolves in the period, although he receives the impact of various reviews in regular basis. In addition, existing work usually asks the reviews of a single review at a particular time; it’s a particular need for predicting many ratings for multiple connected users. To reach all this topics,in this paper it is considered that proposing multiple reviews scheme, Fluid Rating, which uses fluid dynamics theory to reveal the time-evolving rating prediction of human reviews. In this scheme, each user corresponds to a container, and many containers are connecting by a unique direction pipes, corresponding to influence relations.
Original Article International Journal of Basic and Applied Physiology

Background: Many systems have been involved in patients with diabetes mellitus in different ways. It is very crucial to know the electrocardiographic changes that can occur in patients with type 2 diabetes. Objective: To study ECG changes suggestive of myocardial ischemia in asymptomatic type II DM patients. To study correlation between HbA1c values and ECG changes in asymptomatic type II DM patients as compared to nondiabetic subjects (control group). Materials & method: Present cross sectional study carried out in tertiary care hospital from May 2015 to May 2017. 100 diabetic subjects (study group), 100 non diabetic subjects (control group) were selected for study randomly from various department of tertiary care hospital. In all study subject’s blood was tested for HbA1c & ECG changes were recorded. Results: There was significant difference between cases and controls for mean blood sugar level & mean HbA1c (p<0.01). ST segment changes, T wave inversion & Q-QS pattern were more among diabetic patient as compared to controls (p<0.01). Conclusion : ECG changes suggestive of myocardial ischemia or myocardial infarction in the form of ST segment changes, T wave changes and Q-QS pattern were significantly more in the study as compared to control group.
DETERMINATION OF WATER-SOLUBLE VITAMINS B1, B2, B3, B6, B9, B12 AND C ON C18 COLUMN WITH PARTICLE SIZE 3 µM IN SOME MANUFACTURED FOOD PRODUCTS BY HPLC WITH UV-DAD/FLD DETECTION

O bjective: Objective of the study was to develop a simple, precise and accurate RP-HPLC ion-pair method, for the determination of water-soluble vitamins (B 1 , B 2 , B 3 , B 6 , B 9 , B 12 , and C) in some manufactured food products. Methods: RP-HPLC with C 18 BDS (100 x 4.6 mm; 3 µm) column were used. Mobile phase constituents were solvent (A): 5.84 mM of hexane-1-sulfonic acid sodium: acetonitrile (95:5) with 0.1% triethylamine at pH 2.5 and solvent (B): 5.84 mM of hexane-1-sulfonic acid sodium: acetonitrile (50:50) with 0.1% triethylamine at pH 2.5, flow rate 1.6 ml/min, at column temperature 40 °C and suitable detection wavelength. Results: Two different detectors were used: photo diode array detector (UV-DAD) and the fluorescence detector (FLD). Calibration graphs plotted with five concentrations of each vitamin where linear regression coefficients R 2 ˃ 0.9972. LOQ values were 50.0, 81.0, 19.1, 19.0, 30.0, 9.7, 50.0 µg/l with DAD for vitamins B 1 , B 2 , B 3 , B 6 , B 9, B 12 and C respectively, and 5.7, 4.1 µg/l with FLD for vitamins B 2 , B 6 respectively. LOD values were 16.5, 26.7, 6.3, 6.3, 9.9, 3.2, 16.5 µg/l with DAD for vitamins B 1 , B 2 , B 3 , B 6 , B 9, B 12 and C respectively, and 1.9, 1.3 µg/l with FLD for vitamins B 2 , B 6 respectively. Conclusion: The proposed method was successfully applied to analysis mixture of seven water-soluble vitamins in pure form and in manufactured food products, with average recovery of 98.14% to 100.96%.
Feature Extraction and Selection Based Face Recognition Image using Multi-layer Classification Algorithm

: FR (Face Recognition) starts with feature extracting the co-ordinates of features like as a width of wyes, pupil area and compare the consequence with the measurements deposited stored in the database and return the closest dataset in facial parameters. In current years, there are a lot of face recognition methods and techniques search and developed around the world. FR becomes an interesting research area and topic. It is established by several number of published papers regarded with FR add inf FE (Feature Extraction), FS (Feature Selection), Facial Algorithm Enhancements and Face recognition designs. The research work are to get the face recognition method (key points) given by the Scale and Localization by comparison with the existing work and algorithms. Feature Extraction using Scale Invariant Feature Extraction Algorithm. SIFT is significantly more effective strategy and extract the features in the form of key-points. Reduce the feature data using ant colony optimization algorithms are computer programs that simulate the procedures of natural evolution in arranging to solve complex and to model evolutionary systems. Classify and Recognition the reduce features i.e. Multilayer Perceptron neural network. Key-point and Select Features implement inside the Bank and Attendance System returns between 70 per cent to 90 per cent same for Real Face Images. In simulation Tool using MATLAB 2016a and enhance the accuracy rate and reduce the error rates in the given system.
Design and Verification of Efficient Majority Logic Fault Detection and Correction for Memory Applications

— Memory is important for storing data and also to retrieve data in any digital circuit but the main problem is SEUs (Single Event Upsets). SEUs are the bigger concerns for memory applications as it alters the normal working of digital circuits and gives an error. This paper presents a fault detection and correction method which reduces access time when there is no error while reading data for difference-set cyclic codes with majority logic decoding as it can be applied to correct a large number of errors.
Advanced Research in Computer Science and Software Engineering

— Now-a-days, security is a major fretfulness in the world. Biometrics is very helpful and it’s easy to implement for security purpose. It is classified into two categories: such as, Physiological and Behavioural. Physiological Biometrics’ are Finger Print, Iris, Face, Retina, voice, etc. Behavioural Biometrics’ are signature, gait, etc. In this paper is to represent the survey of some selection techniques are used in Face Recognition.
FATTY ACID COMPOSITION AND ANTIDERMATOPHYTIC AND ANTIDIARRHEAL ACTIVITY OF NELUMBO NUCIFERA SEED OIL

The seeds of Nelumbo nucifera were collected from different localities of Coimbatore District. Extraction of oil from plant seed was performed using Soxhlet's procedure. Based on the physicochemical screening the lotus seed was found to be an excellent source of crude oil. The crude fat content of the ground seeds of N. nucifera was determined by GC-MS and identified by spectral library comparison and by the mass spectral fragmentation pattern. HPTLC analysis showed the presence of flavonoids. The hexane extract of the N. nucifera seed oil showed 66% inhibition of the radical DPPH. Whereas the standard ascorbic acid showed IC50 value of 15 ± 1.0 μg/ml. ABTS activity of N. nucifera seed oil (IC50 = 124 ± 1.0 μg/ml) was observed as the strongest activity. The antidiarrhoeal activity of N.nucifera seed oil was evaluated and it strongly inhibited the strains namely Shigella sp. , Salmonella sp. , Klebsiella sp. , Escherichia Coli. , Pseudomonas sp. , and Staphylococcus aureus by disk diffusion method. The inhibitory activity of N.nucifera seed oil was pronounced against the dermatophytes like Malassezia furfur, Trichophyton rubrum and Trichophyton mentagrophytes with the extract concentration of 25μg/mL. This study systematically supports the usage of seed as a medicine for superficial bacterial and fungal infections, alternative source of nutrition and as well as renewable resources.