Miracle-dz/UniFAR-FTUs huggingface dataset:
Useful Measures to Assess Glucose Dynamics

Although useful in clinical practice, metrics proposed for continuous glucose monitoring (CGM) in diabetes control [1] such as mean glucose, SD of glucose, and time or percentage of time spent in hyperand hypoglycemia, are not appropriate to reveal the internal dynamics of CGM time series. These metrics are derived from linear models of glucose analysis and mostly fail to characterize glucose dynamics [2]. As a matter of fact, the variation of blood glucose levels is not linear, and glucose profiles contain nonlinear, non-stationary components [3]. Several nonlinear analytical methods have been recently applied to quantify the complexity of blood glucose signals, including detrended fluctuation analysis (DFA) [4-11], Poincaré plots (PCP) and various entropy measures [12-15].
Divisive Hierarchical Clustering for Random Data Points Based on Farthest Distance (DHCRF)

— The term ‘Clustering’ means grouping of input datasets into subsets, which is commonly called ’clusters’ . The elements in the clusters, are somewhat similar. Many clustering algorithms require the specification of the number of clusters to be produced, prior to execution of the algorithm. The specified method proposes a simple and efficient clustering method. This paper presents an overview of different pattern clustering methods from a statistical pattern recognition perspective. In this paper, we review the possibility of applying a variety of distance metrics and rely on Euclidean distance. The performance of the algorithm is evaluated based on time complexity, execution time and number of clusters formed. The attractive feature of the proposed method is that it solves ‘local minima problem’
STUDY OF SECURITY ENHANCEMENT IN AODV ROUTING PROTOCOL IN AD HOC NETWORKS

Ad hoc network is a dynamically formed network by collection of movable nodes with changing topology, due to nodes mobility and without having centralized administration. Nodes communicate by exchanging data with another node, establishing multi hop network. This type of communication needs vigilant design of routing protocols to satisfy various Quality of Service (QoS) parameters. There is a need to satisfy request of finding a route that utilizes sufficient available resources to meet the QoS constraints in order to achieve low cost or most stable route in real time and military applications. The study of Ad hoc On Demand Distance Vector (AODV) routing protocol has been presented along with security enhancement to AODV routing protocols.
BIOREMEDIAL POTENTIAL OF MARINE BACTERIUM

Reactive Red 81 was selected as model textile dye. The bacteriall strain Marinobacter santoriniensis DR-11 isolated from natural marine environment was screened for decolourization of Reactive Red 81. Optimization was carried out with respect to incubation conditions, carbon source, nitrogen source, pH and temperature. It was found that the optimum pH and temperature were 7.0% and 37 0 C respectively. Glucose and yeast extract at 1.0 % concentration was found to give maximum decolourization. Further, it was found that the culture has brought about almost 98.00% decolourization of a recalcitrant dye, Reactive Red 81(3000μg/ml) at shaking condition within 24 hours. The present isolate also showed the degradation as evidenced from the reduction in the term of COD mg/L to the extent of 88.00 % within 24 hours. The biodegradation was monitored by GC-MS analysis. This study revealed the enormous biodegradation abilities of indigenous marine bacterial flora. The toxicity of the degraded products was checked by the microbial toxicity and fish toxicity and was revealed the degradation of Reactive Red 81 into non-toxic product by Marinobacter santoriniensis DR-11.
A Survey on Load Frequency Control (LFC) Problem in Hybrid Power System

In this paper, an ample literature survey on load–frequency control (LFC) problem in power system has been foreground. The different configurations of power system models and control techniques strategies that related to LFC problem have been considered in conventional as well as distribution generation-based power systems. Hybrid power system (HPS) consisting of multiple power generating units and energy storage units. Further, study on LFC challenges incorporating storage devices BESS/SMES, FACTS devices, wind–diesel and PV system etc have been discussed too.
Experimental Study on Factors Affecting the Recovery of Nickel fromSpent Catalyst

In this study, the recovery of nickel from spent NiMo/Al2O3 catalyst was investigated using 1 L stainless steel autoclave batch reactor. The effect of leaching process parameters such as temperature (40-80°C), time (1-4 h), pressure (1-3 bar), average particle size (69-550 μm) and agitation speed (400-600 min-1) on nickel extraction. The nickel percent in spent catalyst was found about 2.18%. The results obtained show that recovery of about 94% of nickel from spent catalyst was accomplished under the following conditions: temperature 80°C, pressure 1 bar, average particle size 200 μm, agitation speed 600 min-1, nitric acid concentration 40% and solid to liquid ratio1:50 after 4 h.
Direction of Arrival Estimation in Linear Arrays by Using a Hybrid Algorithm

In this study, a new hybrid algorithm for uniform linear antenna (ULA) array was composed by using First Order Forward Prediction (FOFP) and the Minimum Variance Distortionless Response (MVDR) algorithms together. FOFP and MVDR algorithms were discussed as incident signal direction prediction algorithms. The powerful and weak points of these two algorithms were explained. Some scripts were written by using MATLAB. 5 antennas which were spaced with half wavelength, forms an ULA array. Its output data was used as input data of the three algorithms mentioned above. The results obtained from the hybrid algorithm and the individual results of MVDR and FOFP algorithms were compared under the same conditions. An improvement in the proposed hybrid algorithm is observed.
A Review on Approaches for Classification of Sonar Textures

— Texture analysis describes a wide variety of image-analysis techniques that quantify the variation in surface intensity or patterns, including some that are unnoticeable to the human visual system. Texture analysis describes a wide range of techniques that enable calculation of the gray-level patterns, pixel interrelationships, and the spectral properties of an image. The increasing scientific and economic interest in the visual exploration and monitoring of marine areas is creating huge amounts of new underwater image and video data and approach of computational assistance for texture analysis is desperately needed. Side Scan Sonar texture pattern highly depends on incident angles, These types of variance need to be addressed for sonar texture characterization. Recently, more advances have been gained in computer vision for invariant texture recognition by considering invariances to contrast changes and afﬁne transforms.This paper presents a review on different texture analysis approaches and classification of sediments using Side Scan Sonar useful for underwater image analysis.
A Novel Approach of Data Mining Model for Text Classification/Categorization

Classification plays a vital role in many information management and retrieval tasks. This paper studies classification of text document. Text classification is a supervised technique that uses labeled training data to learn the classification system and then automatically classifies the remaining text using the learned system. In this paper, we propose a mining model consists of sentence-based concept analysis, document-based concept analysis, and corpus-based concept-analysis. Then we analyze the term that contributes to the sentence semantics on the sentence, document, and corpus levels rather than the traditional analysis of the document only. After extracting feature vector for each new document, feature selection is performed. It is then followed by K-Nearest Neighbour classification. The approach enhances the text classification accuracy. We define architecture that supports processing of a range of declaratively-specified KDT problems, using such general services.
Decision Oriented Hybrid Spectrum Sensing Approach in Cognitive Radio for OFDM Systems

— Sensing of orthogonal frequency division multiplexing (OFDM) signals is of great importance for cognitive radio communications due to the wide applications of OFDM in many existing and evolving broadband wireless communication. In this research paper, an energy detection based hybrid cooperative spectrum sensing mechanism combining parallel and sequential sensing schemes is proposed to trade-off between sensing accuracy and efficiency. To apply the parallel and sequential sensing approach, a number of cognitive secondary users are appointed to simultaneously sense one and the other channel. Performance of the proposed scheme is evaluated in different channel environments in terms of probability of detection compared with the sequential sensing scheme and parallel sensing scheme.
Zone Based Phytochemical Variability In Different Genotypes Of Moringa Oleifera Lam. Using Ftir Spectroscopy

Infrared (IR) spectra of particular plant species are highly specific fingerprint-like signature which are used to differentiate, classify, and identify diverse plant species. Plant specific IR spectra are useful to detect functional group or structure. The spectral traits can be systematically extracted from the typically broad and complex spectral contours applying resolution enhancement techniques, difference spectroscopy, and pattern recognition methods such as factor‐analysis and cluster‐analysis, and artificial neural networks. The spectral pattern varies with effect of climatic conditions such as stress, salinity, drought and other factors that’s affecting the plant development. FTIR techniques proved to be an effective strategy for identifying the species and for determining their geographical distribution, especially in the assessment of Moringa quality for use in raw herbal medicines. In this study, results of FTIR analysis confirmed the presence of phenol, alkanes, aldehyde, secondary alcohol, amino acid, aromatic amines and halogen compound between 500-4000 cm-1 region and provide a platform for providing variability in spectra of 57 M. oleifera aceessions that collected from different geographic locales of India. Based on the spectrum value the factor analysis and cluster analysis were also done.
Facteurs prédictifs de rechute locorégionale après chimiothérapie néoadjuvante dans les cancers du sein : analyse rétrospective de l’étude prospective EORTC 10994/BIG 1-00

Problematique : la chimiotherapie neoadjuvante est devenue le traitement standard des cancers du sein localement avances. L’identification de facteurs clinico-pathologiques predictifs du risque de rechute locoregionale (RLR) serait utile, afin de personnaliser les indications de radiotherapie adjuvante. Le but de ce travail est, apres une revue de la litterature, d’identifier ces facteurs a partir de l’analyse des donnees d’une etude de phase III multicentrique (EORTC 10994). Methodes : les patientes ont ete traitees par chimiotherapie neoadjuvante, chirurgie puis radiotherapie adjuvante. Certaines des patientes ayant un cancer HER2 (Human Epidermal growth factor Receptor 2) positif ont recu un traitement adjuvant par trastuzumab. Une analyse multivariee a ete realisee afin d’isoler les facteurs predictifs de RLR. Le critere de jugement principal etait le temps jusqu’a la RLR (premier evenement). Resultats : le suivi median est de 4,8 ans. Parmi 1553 patientes eligibles, 76 RLR ont ete observees, soit un taux de 4,9% a 5 ans (IC 95% [3,76 – 6,04]). En analyse multivariee, le sous-type moleculaire est significativement predictif de RLR (p<0,0001) : les cancers HER2+ sans trastuzumab (T), HER2+ avec T et triples negatifs ont un risque augmente avec des Hazard Ratio (HR) a 6,26 (IC 95% [2,81-13,93]), 3,37 (IC 95% [1.10-10.34]) et 6,44 (IC 95% [2,83-14,69]) respectivement. Le deuxieme facteur predictif est la reponse histologique avec un risque augmente en cas de persistance d’un envahissement ganglionnaire ≥ 4 ganglions (HR 2,43, IC 95% [1,34-4,10], p<0.0001). L’âge, les statuts cT et cN, le type histologique, le type de chirurgie et les marges R1 ne sont pas significatifs. Conclusion : la reponse histologique et le sous-type moleculaire (triple negatif et HER2+) sont des facteurs predictifs de RLR. D’autres etudes restent necessaires pour identifier un sous-groupe de patientes chez qui une desescalade des indications de radiotherapie adjuvante serait envisageable.
Proximate Composition and Quality Characterization of Oil Extracted From Moringa Oleifera Kernel Using Different Extraction Method

This study investigates proximate composition and characterization of Moringa oleifera seed-oil using four methods of extraction (Cold pressing (CP), Enzyme assisted cold pressing (EACP), Enzyme assisted aqueous extraction (EAAE) and solvent extraction (SE)) and compared with olive oil. The results of proximate analysis of the kernel reveals (7.20 moisture content, 43.12 protein, 33.16 fat, 3.51 Ash, and 6.81 Carbohydrate by difference) %, while the oil yield obtained for CP, EACP, EAAE and SE were (7.75, 12.08, 23.25 and 33.16)%. The fatty acids composition and bioactive compounds were determined through GC-MS analysis. Melting and crystallization temperature ranges: -15.86 to 3.21 and 8.30 to -13.63 °C, respectively. There is a significant difference in term of oil yield, with cold pressing method having the lowest oil yield of 7.8 %. However, the quality of CP extracted Moringa oleifera oil was compared with virgin olive oil; it revealed its potentials as a good source of oleic acid making it to be a good substitute for virgin olive oil.
BRAIN TUMOR SEGMENTATION

Brain tumor is an abnormal growth of the cells in the brain. The location, shape and region of the tumor is very important for identifying the tumor. Even the doctors can identify these tasks with their knowledge, but, it is a time consuming process. In order to save the time of the doctors, there is a need for the automation of the Brain tumor segmentation. Here, we have made an attempt for developing the algorithm for Brain tumor segmentation. Illumination normalization is an important criterion for the images, for reducing the lighting effects on images. In order to avoid the wrong prediction of the tumor location in brain images, which was caused due to illumination, there is a need to eliminate the illumination. So, here, illumination also considered, while detecting the tumor. We used the preprocessing techniques Local Binary Pattern and for segmentation used Morphological operations. The proposed algorithm is developed using MATLAB.
Inhibitory Effect of DPPH Radical Scavenging Activity and Hydroxyl Radicals (OH) Activity of Chelidonium majus var. asiaticum

The present study was investigated plant extracts as sources of natural antioxidants and to examine whether Chelidonium majus var. asiaticum having significant1diphenyl 2-picrylhyorazyl (DPPH) activity and hydroxyl radicals (OH) activity.DPPH scavenging activity of stem extracts of C. majus var. asiaticum was evaluated at 4.0 mg/ml was 55.8% and that of leaves was 23.3% at same concentration. DPPH scavenging activity of root extracts of C. majus var. asiaticum was evaluated at 4.0 mg/ml was only 19.6% at same concentration. When the L-Ascorbic acid used as a control, extract for stems of C. majus var. asiaticum was 50.3% effects on the activation of DPPH and that of leaves and roots were 31.3% and 23.2%. The highest OH activity was recorded in the stem extract among three vegetative organs. OH activity of matured leaves was 52.7% at 4.0 mg/ml and leaves and roots were 43.3% and 25.6% at same concentration, respectively. When the H2O2 used as a control, extract for stems of C. majus var. asiaticum was 38.3% effects on the activation of OH and that of leaves and roots were 36.2% and 23.5%, respectively. Strong activity of DPPH enzymes and OH by extract from C. majus var. asiaticum makes this pharmacopeial plant material an interesting topic for further biological and phytochemical examination.
BIOREMEDIATION OF CRUDE OIL AND STUDY OF THE HYDROCARBON DEGRADING ISOLATES, THEIR BIOSURFACTANT ACTIVITY AGAINST HUMAN PATHOGENS

Oil spill is a major threat to marine environment in recent years. Bioremediation of crude oil is of significant importance as chemical dispersants are highly toxic. Crude oil is mainly composed of hydrocarbons, which cause environmental pollution and health hazards to all living beings. Hydrocarbon-degrading microorganisms were isolated from sea water sample and percentage of degradability was estimated by gravimetric analysis. The gravimetric analysis study revealed that 53.4% and 51.9% of crude oil added to the medium were degraded by Bacillus and Pseudomonas aeruginosa respectively. Production of biosurfactant by isolated hydrocarbon degrading microorganisms were analysed by primary, secondary and quantitative test such as blood haemolysis test, oil displacement test, drop collapse test and emulsification test. Biosurfactants were extracted from all four bacterial isolates Bacillus, Pseudomonas aeruginosa, Micrococcus luteus, and Serratia marcescens by acid precipitation method. The crude biosurfactant was tested for its antimicrobial activity against human pathogens such as Bacillus sp. , Pseudomonas sp. , Staphylococcus aureus, E. coli and Shigella spp. , by agar well diffusion method. Maximum antimicrobial activity was reported by Biosurfactant extracted from Bacillus and Serratia marcescens against all tested pathogens. Isolated hydrocarbon degrading microorganisms were identified by 16s rRNA sequencing and standard biochemical testing. The isolates C1, C2, C3 and C4 were identified to be Bacillus, Pseudomonas aeruginosa, Micrococcus luteus and Serratia marcescens respectively.
STATIC HANDWRITTEN SIGNATURE RECOGNITION BASED ON FOURIER DESCRIPTORS AND HOGS USING KNN CLASSIFIER

: Handwritten signature is used as a means of personal recognition and authentication in financial, commercial and legal transactions. Similar to other behavioral biometric it is considered as one of the potential research area of image processing and pattern recognition. In this paper, we present a study on static handwritten (ie offline) signature recognition using two feature extraction methods, namely, Fourier Descriptors and Histogram of Oriented Gradients (HOG). Recognition process is carried out using KNN classifier with Euclidean distance as a distance computation measure. Experiments are performed on signature images from local database and results are encouraging.
Influence of Anthropometry on the Kinematics of the Cervical Spine in Frontal Sled Tests

Objective: The objective of this study was to investigate the influence of anthropometric factors on the kinematics of the cervical spine during in-vivo frontal collisions. Methods: Therefore a frontal collision with a mean velocity change (delta-V) of 10.2 km/h was simulated in a sled test with ten healthy volunteers (seven men and three women). A high-speed camera was used to document motion data. Acceleration data were recorded using accelerometers. The study analyzed the association of anthropometric factors with defined kinematical characteristics.Results: A smaller neck circumference led to an earlier peak of the dorsal horizontal head acceleration (r=0.602), an earlier beginning of the ventral head translation (r=0.742) and a greater maximal head flexion (r=-0.717). A smaller body weight led to a later beginning of the head flexion acceleration (r=-0.713) and a greater maximal head flexion (r=-0.620). With a smaller thorax circumference the beginning of the dorsal horizontal head acceleration (r=0.623), the peak of the head flexion acceleration (r=0.756) and the peak of the head extension acceleration (r=0.679) were reached earlier. Conclusions: The main findings of the present study consist in the identification of relevant anthropometric parameters (neck and thorax circumference and body weight) on the cervical spine kinematics. Specific anthropometric factors increasing the risk of injury could not be identified. The head movement is mainly associated with the neck circumference and the body weight. The onset and occurrence of the acceleration parameter is mainly associated with the thorax circumference.
Review Paper on Frequency Multiplier at Terahertz Range

Frequency multiplier is an electronic circuit which generates the output frequency which is an integer multiple of the applied frequency. For this purpose, nonlinear devices such as BJT, FET, schottky diode, varactor diode, step recovery diode are used. The nonlinear region of their characteristics is utilized to design frequency multiplier. In terahertz range stability and broad bandwidth are required factors to design heterodyne receiver. For this purpose, only schottky diode is the best option because its cutoff frequency is so high and due to this reason switching frequency of this diode is high compared to its other comparable. The design of frequency multiplier consists of three parts namely the diode structure, input and output matching circuit. The detailed discussion about sources available at terahertz frequency range, different design methods of frequency multiplier with active and passive devices, comparison of available passive frequency multiplier are presented in this paper.
Fundus Autofluorescence Imaging, Optical Coherence Tomography, and Multifocal Elecroretinogram Analysis of Congenital Grouped Albinotic Spots

A 7-year-old Japanese girl displayed multiple, variably sized, sharply circumscribed, placoid, white lesions in both eyes, with no additional symptoms. The appearance of these lesions was consistent with congenital grouped albinotic spots of the retina. Fundus autofluorescence imaging showed clearly-defined abnormal autofluorescence, corresponding to these albinotic spots. The outer retinal layer and the photoreceptor inner/outer segment junctions were observed to be irregular and discontinued corresponding to some albinotic spots, by optical coherence tomography. Multifocal electroretinograms of both eyes displayed decreased amplitudes. Therefore, we have described a case of congenital grouped albinotic spots in the eyes with functional deterioration.
Various Rule Pruning Techniques and Accuracy measures for Fuzzy rules

Interpretability is the most desired property for any knowledge based systems. The Fuzzy logic systems are well known for their interpretable results, due to use of linguistic variables. However it has been observed that the fuzzy systems produce a large rule set, thus affecting the interpretability of the system. Also the generated rule base is complex, thus making the overall inference system complex. Many rule pruning techniques have being found by researchers. The main aim of this paper is to make a comparative study of all the techniques for rule pruning. The different accuracy measures used for rating a rule is also studied and compared here.
OPTIMIZING THE POWER USING FUSED ADD MULTIPLIER

– Many Digital Signal Processing (DSP) applications carry out a large number of complex arithmetic operations. Multiplier take important role in high performance of the system, reduce in power and area. This paper is focus on optimizing the design of Fused Add Multiply (FAM) operator. This implements a new technique by direct recoding of sum two numbers in Modified Booth (MB) form. It is used for both signed and unsigned Radix-4 which is a parallel multiplier. An efficient multiplier with reduce partial product by N/2 where N is the number of multiplicand. The proposed FAM unit is coded in VHDL, simulated and synthesized using Xilinx ISE tool. The performance of FAM unit is compared with other existing technique in terms of power consumption and critical path. The proposed FAM unit yields considerable reduction in terms of critical delay and power consumption.