Performance Evaluation of Face Recognition Algorithms

Biometric - based techniques have emerged for recognizing individuals instead of using passwords, PINs, smart cards, plastic cards, tokens etc fo r authenticating people . Automated face recognition has become a major field of interest. In this field several facial recognition algorithms have been explored in the past few decades . A face recognition system is expected to identify faces present in images and videos automatically. The input to the facial recognition system is a two dimensional image, while the system distinguishes the input image as a users face from a pre - determined library of faces. Finally, the output is a discerned face image. This paper deals wi th the comparison of two popular dimensionality reduction algorithms such as PCA and LDA. Here, our main goal is to evaluate the performance of Principal Component Analysis and Linear Discriminant Analysis for large training data set. Finally, we concluded that LDA outperforms PCA for the large samples of training set

A Technique Using Machine Learning to Anticipate and Differentiate Between Biodegradable and Non-Biodegradable Waste

Urban waste has become a significant issue for planners due to the challenges of identifying and disposing of it. The rise in urban populations has resulted in a corresponding increase in waste and garbage. To address this issue, in this study, the researchers introduce a concrete approach that utilizes a Deep Learning (DL) framework to perform waste sorting at its basic level. In contrast to recognizing objects of a specific category, waste can have various characteristics such as color, shape, material or size making it challenging to detect. To overcome this, the authors proposed a material-based deep learning model called Smart-Bin, which employs an Improved Faster Recurrent Convolution Neural Network (IFRCNN) approach to differentiate between biodegradable and non-biodegradable waste. The aim of this study is to evaluate the performance of various IFRCNN models such as AlexNet, ResNet, InceptionNet, and VGG-16 together with the hardware system implemented for waste classification within the bin, the suggested technique demonstrated superior performance compared to other models. The InceptionNet Neural Network achieved remarkable precision rates of 98.15% and a training dataset loss of 0.10, while achieving 96.23% precision and a loss of 0.13 for the validation dataset

Combining ability for yield and different quality traits in rice (Oryza sativa L.)

Gene action and combining ability for yields and quality traits were analyzed by line x tester analysis in 48 crosses along with 8 lines and 6 testers to find out their usefulness in improvement of quality traits. Analysis of variance revealed that ASD 16 line and Pusa Basmati 1 and Basmati 370 testers were the good combiners for both yield and quality traits. The crosses ADT 36 / GEB 24, ASD 16 / Pusa Basmati 1, ADT 43 / Jeeragasamba, MDU 2 / Pusa Basmati 1 and MDU 5 / Improved White Ponni were identified as the good specific combiners for grain yield and some other quality characters. Dominance gene action was found to be predominant for most of the quality characters along with yield giving way for exploitation of heterosis breeding for meeting out the increasing quality preference of the consumers

Adaptive and Self Healing Routing for Mobile AdHoc Networks Using Cross Layer Design

The construction of reliable and stable routes in a mobile ad hoc network is one of the primary research issues in equipping each device to continuously maintain the information required to properly route traffic. Mobility of nodes often leads to link failures and hence requires route reconstruction to resume the communication between the nodes. The stability factor of a route can reduce the number of times the route is changed or reconstructed. This paper presents a novel idea for discovering a stable set of routes using the metrics from multiple layers rather than depending on network layer along with a finite set of parameters to qualify a link or connecting to a node. The link stability factor and link received signal strength are considered as the main metrics to qualify the stability of a route, derived from the physical and data link layer based on bit or packet error rate, retrieved from the soft output decoder. The simulation results based on the analysis of the proposed algorithm prove to be more efficient in terms of discovering stable routes, reducing frequent reconstruction of routes and hence improving the overall performance of the network

Comparison of Allen Stroke Score and Greek Stroke Score with CT Brain in Clinical Diagnosis of Acute Stroke

BACKGROUND: The aim of the study is to assess the type of stroke using the stroke scoring systems and to determine the accuracy of stroke scores by comparing the stroke scores with CT brain scan findings. PATIENTS & METHODS: Our study included 100 patients admitted with clinical diagnosis of stroke and those who have taken CT scan. RESULTS: In our study we have derived that the Allen stroke score and Greek stroke score has the highest specificity and negative predictive value for Hemorrhage respectively. Hence the scoring systems could not be used alone to differentiate the type of stroke. CONCLUSION: Stroke scoring systems are still not accurate to replace CT scan as investigation of choice, even when the facility is not available

Spray Deposition and Characterization of p-type Li doped NiO Thin Films

Undoped and lithium doped nickel oxide (Li doped NiO) thin films have been prepared onto glass substrates at 450 °C by chemical spray pyrolysis technique. The effect of lithium (Li) concentrations on the structural, optical, photoluminescence and electrical properties of the Li doped NiO films were studied by X-ray diffraction (XRD), UV-vis- NIR spectrophotometer, Photoluminescence (PL) spectrophotometer, Hot probe and Hall effect measurement system. The PL results confirmed that the band gap reduces when the lithium concentration increases. The structural properties of undoped and Li doped NiO films showed polycrystalline cubic structure. The optical transmittance and band gap values of the films decreases, while the absorption values increases with the increase in Li concentration. Moreover, it has been observed that the resistivity of the above films decreases with the increase in Li concentration

Comparative evaluation of homogeneity and quality of obturation by different obturation techniques using Cone Beam Computed Tomography: An In Vitro study

BACKGROUND : Newer materials are emerging in the field of endodontics which can be used as root canal filling materials. Most of them are able to provide an adequate coronal and apical seal which is one of the prime requisite’s for successful endodontic therapy. This in vitro study was done inorder to evaluate the homogeneity and quality of four obturating techniques namely, Lateral Compaction, Guttaflow, Beefill and Thermafill using Cone Beam Computed Tomography. MATERIALS AND METHODS : One twenty (120) lower first premolars extracted for orthodontic purposes were used for this study. For the standardization of samples, teeth with single canals and straight roots were selected. The selected teeth were then stored in 5.25% sodium hypochlorite solution for two hours in order to dissolve the attached periodontal ligament fibers. After, which the teeth were made free of calculus and debris by using an ultrasonic scaler and the samples were washed under normal tap water and stored in normal saline solution at 370C and 100% humidity. The access cavities were prepared by using an endo access bur and the working length was estimated with the help of routine radiographs. The canal shaping was done by using the protaper rotary file system upto size 30 by following the crown down technique. 2.5ml of 2.5% Sodium hypochlorite solution was used as the irrigant in between the filing sequences followed by 5ml of 17% EDTA solution and then 2.5 ml of saline was as the final flush. Then a preoperative CBCT analysis was done in order to evaluate the volume of the root canal after standardizing the working length at 15mm. This 15mm is further divided into coronal, middle and apical segments of 5mm each. These 5mm segments were further divided into 0.5mm slices. The prepared root canals were then dried with appropriately sized paper points. AH plus sealer was coated along the walls of the prepared canals by using a lentulospiral at a speed of 300 rpm. Before obturation, the samples were randomly divided into four groups where group I was obturated by Lateral Compaction technique (LC), group II was obturated with Guttaflow (GF), group III was obturated with Thermafill (TF) and group IV was with Beefill (BF) by following the manufacturer’s instructions. Then, the postoperative CBCT analysis was performed by using the CBCT scanner (ORTHOPHOS XG 3D, Sirona Dental systems, Bensheim, Germany). The volume of each segment was then calculated from the linear measurements obtained by the CBCT analysis. The volume of the root canal in each slice was then calculated by multiplying the root canal area with the slice thickness (0.5mm). The Volume Percentage of the voids in the obturated root canal (VP) was calculated by using the formula, (R-V) ×100/R where, R is the volume of the root canal space and V is the volume of the void space. From this formula the volume percentage of the obturated material was calculated. The homogeneity of obturation was then evaluated by estimating the prevalence of voids at the coronal, middle and apical segments of the obturated root canals. STATISTICAL ANALYSIS : The obtained data was then analyzed statistically by using the Statistical Package for Social Sciences, (SPSS) version – 17 Software for Windows. Data entry was done by using the Microsoft office Excel spreadsheet where the data was expressed in its mean and standard deviation and were then analyzed by using ANOVA and multiple comparisons by Post Hoc Bonferroni test. RESULTS : Voids were present in all the groups (LC, GF, TF and BF) but the results were not statistically significant. In the intergroup comparison of the overall total volume percentage between the four groups, the mean overall total volume percentage of the Lateral Compaction group (LC) was the lowest at 88.9407% and Beefill (BF) at 97.9273 % was the highest, which was statistically significant. The overall volume percentage of the obturated material was the highest in the Beefill (BF) group followed by Thermafill (TF), Guttaflow (GF) and the Lateral Compaction techniques (LC). For the presence of extrusion among the four groups, the mean value for Lateral Compaction was 3.07 and for Beefill it was 1.033 which was statistically significant. CONCLUSION : Within the limitations of the present study, it can be concluded that 1. Voids were present in all the four groups (LC,GF,TF,BF). 2. The maximum volume percentage of obturated material was found in the Beefill group (97.9273%) and the least volume percentage was found in the Lateral Compaction technique (88.9407%). 3. Extrusion was present in the Lateral Compaction group (3.07 %). 4. The homogeneity and quality of obturation was better in Beefill followed by Thermafill, Guttaflow and finally by Lateral Compaction

A rare case of acute lumbar strain

Introduction: Acute lumbar pain is a suddenly caused pain in the lower back region, and there are spasms in the lower back that result in more severe pain. It occurs in all age groups. The first attack of the lower back pain is typically caused at the age of 30-50. Acute lumbar strain is caused by pushing or tugging and weight lifting heavy objects too heavy for the person's capacity. Most cases of acute lumbar strain can be treated in two to three weeks; if you can cure or take a proper precaution, then it will not cause any injury in the low back region and cannot cause any complications in the health. The lower back pain is healed by cold applications such as ice bags (to reduce the pain and swelling), and heat is applied to the back to prevent the pain. Clinical findings: Pain in the lower back region also creates spasms in the lower back region. Diagnostic evaluation: Blood test: Hb-15.6 gm%, Total RBC count-4.7millions/cu mm, Total WBC count-70000-8000/cu mm, Total Platelet count-2.8 lacs/cu mm, Albumin-4.5 gm%, Bilirubin (conjugated)-0.3 gm%, Bilirubin (unconjugated)-1.0 gm%. Therapeutic intervention: The physician suggests non-steroidal anti-inflammatory drugs and pain killers, and a physiotherapist recommends muscle relaxation exercises. Outcome: After the specialized Treatment, the patient's pain is relieved, and the patient feels very relaxed; now, the patient has a good condition till the last date of care. Conclusion: The patient was admitted with a chief complaint of pain in the lower back region, pain associated while walking, and the patient was not able to sleep properly; there was a disturbed sleeping pattern of the patient. Diagnosed with a case of acute lumbar strain after getting proper treatment and the patient condition was improved

Recurrence Quantification Analysis of EEG signals for Children with ASD

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by impairment in sensory modulation, repetitive behavior etc. It would lead to difficulties in adaptive behavior and intellectual functioning. Subjective scales as childhood autism rating scale, 3Di, etc. are available to assess the symptoms of Autism. Currently there are no reliable objective diagnostic methods available for assessment of Autism. Also, Early diagnosis of will help in designing customized training and putting those kids in regular stream. The purpose of this research is to observe the response of the brain for auditory/visual stimuli in typically Developing (TD) and children with autism through electroencephalography (EEG). Application of nonlinear methods for EEG signal analysis may help in characterization of brain activity to describe the neurophysiological commonalities and differences between typically developing and autism children. Among the various non-linear methods, the underlying dynamics can be analyzed well with Recurrent Quantification Analysis (RQA). But, the performance of RQA based classification depends on the choice of parameters like embedding dimension, time delay, neighborhood selection and distance metric. Different experiments were conducted by varying methods for neighborhood selection and distance metric. In this research, for better information retrieval cosine distance metric is additionally considered for analysis and compared      with other distance metrics in RQA. Each computational combination of RQA measures and the responding channels were analyzed and discussed. It was observed that FAN neighborhood with cosine distance parameters were able to discriminate between ASD and TD