Miracle-dz/UniFAR-FTUs huggingface dataset:
SVD and DWT Based Iris Recognition Using Beagleboard-xM

— Iris recognition is one of the most accurate biometric methods in use today. However, the iris recognition algorithms are currently implemented on general purpose sequential processing systems, such as generic central processing units (CPUs). One of the remaining problems in iris recognition is the implementation of its efficient hardware systems. This proposed work uses a hardware Beagleboard-xM, which is designed specifically to address the Open Source Community. Unlike regular iris recognition systems, the proposed method also involves pre-processing, normalization, feature extraction and matching. Here the iris normalization is performed using a new method called Circular Masking technique. And for feature extraction, Biorthogonal Wavelet Transform and Singular Value Decomposition (SVD) algorithms are used. And Euclidean distance measure is used in order to find similarity between the iris images. And the results demonstrate significant improvements in iris recognition accuracy. And all these operations are implemented on Beagleboard-xM using OpenCV library functions.
Weighted Isotropic Laplacian Approach for Software Reliability Estimation for a Growth Model

: During the development of software applications many defects may be introduced and often leads to sudden breakdowns, so there is a great need to assess this development process in terms of quality and reliability. In this paper a test statistic comprised of both growth and non growth reliability model is tested . The performance is evaluated under a standard test dataset and proves to be more simpler and efficient in estimating the reliability of an growth model.
A Review on Face Recognition Techniques

In real-time applications, security is most important part. For security purpose, face recognition methods are widely used. In last few decades, a various numbers of face recognition techniques has been developed. Face recognition is related to the field of the machine learning, computer vision & image analysis. Face recognition comprehensively uses a wide range of methods which are mentioned in this paper. This review is of present methodology of face recognition techniques like Principle Component Analysis(PCA), Linear Discriminant Analysis(LDA), Local Binary Pattern(LBP)
Secure Semantic Search over Encrypted Cloud Data with Ranking Integrity

With the advent of cloud computing, more and more information data are outsourced to the public cloud for economic savings and ease of access. However, the privacy information has to be encrypted to guarantee the security. To implement efficient data utilization, search over encrypted cloud data has been a great challenge. The existing solutions depended entirely on the submitted query keyword and didn’t consider the semantics of keyword. Thus the search schemes are not intelligent and also omit some semantically related documents. In view of the deficiency, as an attempt, we propose a semantic expansion based similar search solution over encrypted cloud data. Our solution could return not only the exactly matched files, but also the files including the terms semantically related to the query keyword. In the proposed scheme, a corresponding file metadata is constructed for each file. Then both the encrypted metadata set and file collection are uploaded to the cloud server. With the metadata set, the cloud server builds the inverted index and constructs semantic relationship library (SRL) for the keywords set. After receiving a query request, the cloud server first finds out the keywords that are semantically related to the query keyword according to SRL. Then both the query keyword and the extensional words are used to retrieve the files. The result files are returned in order according to the total relevance score. TPA is used to audit the rank and provide the accurate relevance score. Eventually, detailed security analysis shows that our solution is privacy-preserving and secure under the previous searchable symmetric encryption (SSE) security definition.
Extraction of Spread Spectrum Hidden Data from Image using M-IGLS Algorithm

: Data embedding and extraction schemes are increasing in today’s communication world due to rapid increment of data tracking and tampering attacks. Extracting embedded data without understanding the analysis over a wide band in a spectrum domain of digital medium like image, audio and video and it considered a problem of active blind spread spectrum steganalysis and attempted to recover unknown messages hidden in image hosts via multi-signature spread spectrum embedding. So we need an efficient and robust data hiding schemes to protect from these attacks. We develop novel multi-carrier/signature iterative generalized least-squares (M-IGLS) procedure to find or to extract unknown data hidden in hosts via multicarrier spread spectrum embedding. In this we assumed that the original host and the embedding carriers are available. M-IGLS is a low complexity algorithm and it attains the probability of error recovery equals to known host and embedding carriers. Its peak signal to noise ratio value obtained is high. Experimental studies on images show that the developed algorithm can achieve recovery probability of error close to what may be attained with known embedding carriers and autocorrelation matrix.
A Survey: Attacks on Wireless Networks

– Wireless Sensor Networks are a Collection of Sensor nodes.Wireless sensor network become so much popular in many fields due to its functionality i.e military, industrial area etc.Security is the important and critical issue in the Wireless networks due to the operating nature of WSNs. This Paper describe the security requirements as WSNs are easily prone more attacks than wired networks. This paper studies the security attacks in WSNs that are Popular now days i.e. wormhole attack and their countermeasures in the network Layer .
EVALUATION OF ANTIANXIETY AND ANTIOXIDANT ACTIVITY OF AERIAL PARTS AND ROOT OF EREMURUS HIMALAICUS BAKER

The aim of the present study was to determine the in-vitro antioxidant and in-vivo antianxiety activity of crude extracts of Eremurus himalaicus (Asphodelaceae) introduced orally at the dose of 200 mg/kg once daily for a period of 1 week. The anxiolytic activity was determined after single dose administration, 3rd and the 7th day of treatment using elevated plus maze and light and dark arena models. Results of antioxidant activity demonstrated significant DPPH radical scavenging and reducing power of methanolic and aqueous extracts compared to BHT (Butylated Hydroxy Toulene). Results of the antianxiety study of extract treated groups (except chloroform extract) showed a statistically significant increase in the open arm activity and time spent in light box in elevated plus maze and light and dark arena models respectively.
DIGITAL COMMUNICATION RECEIVER BASED ON FPGA DESIGN

— In a digital communications systems where the data transferred in bit stream, the processing need to be very fast and more accuracy than that use in traditional circuits of digital communication system. FPGA package having these facilities so the receiver digital communication carried out in FPGA package for that reason. Research contained two parts; the first part implements digital communication receiver in FPGA package. The second part compare between actual traditional circuit (AICD) and FPGA.The system has been worked in high speed action and high accuracy when implemented in Xilinix-XC-95 FPGA Package and good results have been recorded.
Effect of Ketamine Spraying on the Postoperative Sore Throat and Hoarseness after Tracheal Intubation

Aims: Sore throat, hoarseness, and cough are postoperative complications caused by tracheal intubation in general anesthesia. The aim of this study was to investigate the role of preoperative ketamine splashing on reducing postoperative sore throat. Study Design: A cross-sectional/ randomized, double-blinded clinicall study. Methodology: This study was performed on 68 patients who were randomly assigned into two groups. The control group received 2 cc normal saline and the case group received 25 mg ketamine in 2 cc normal saline. To evaluate ketamine preoperative splashing efficacy, the incidence and severity of postoperative sore throat (post) and other complications caused by tracheal intubation were compared between two groups. Results: In the ketamine group, the incidence and severity of post were less compared to the control group. The findings revealed significant differences in terms of sore throat (in recovery time; 6 h and 12 h after surgery) and hoarseness (in recovery time) among the two groups. The investigation of patient’s vital signs showed a significant difference between groups regarding HR at 5 th and 15 th minutes of surgery among the two groups. No hallucination was found in either group. Conclusion: According to these results, ketamine preoperative splashing can significantly reduce the incidence and severity of postoperative complications of endotracheal intubation such as sore throat, with no side effect.
The Impact of Automation on Human Behavior-A Review

The intelligence is the prime determinant on which humans are both distinguished and considerably unique among all the creatures in this universe. With the advent of the field of Artificial Intelligence, the era of automation has revolutionized the human life. The AI may well be a modeling of the human intelligence. For humans are, to a first approximation, intelligent; they can perceive, act, learn, reason, and communicate successfully despite the enormous complexity of the tasks. Since humans react differently to the functioning of different automated systems, it is imperative to understand, what the impact of automation on human machine interaction is. The interaction between humans and fully automated facilities or machines is a key issue for the researchers in the field of Psychology, Robotics and Ergonomics. This paper focuses on few important aspects the automated systems on human behaviour in different settings and examines the effects produced by them. This study is an evaluation of the effects of automation on the human behavior and to elucidate on both positive and negative impacts of automation on human behavior.
Sphere Decoder for Massive MIMO

-Modern wireless communication systems demanding high data rate operating in bandwidth deficient world is using Multiple Input Multiple Output (MIMO) antenna arrangement. MIMO arrangement helping achieving high data rates with a technique of special multiplexing saves bandwidth but needs efficient receivers with manageable hardware. The receivers employing linear equalizers or Decision Feedback equalizers in detection use less hardware but are of suboptimum. Optimum detectors are realized by Maximum Likelihood Detectors but not suitable for implementation due to the complexity. Therefore suboptimum detectors such as Viterbi Decoding, Sphere Decoding and Genetic Algorithms based detectors are suitable candidates. Here we compare the performance of sphere decoder with some other detector. The complexity and SER rate of sphere decoder is good when compare with other detectors used in MIMO receiver design. The performance of sphere decoder and maximum likelihood decoder is same but complexity is reduced in sphere decoder.
Maternal and Paternal Postpartum Depression: Effects on Early Infant-Parent Interactions

While there is a well-established literature on the detrimental effects of maternal depression on infant-mother interaction and on infant development, the association between paternal postpartum depression and infant development has been rarely investigated. The relative newness of research on paternal postpartum depression, inconsistent research methods, lack of standardized guidelines, clinical heterogeneity and the possible gender-related differences in the expression of emotional disorders pose difficulties in the systematic investigation of the impact paternal postpartum depression has on the quality of infant-father interaction. This editorial highlights the significance of continuing research on maternal and paternal postpartum depression in the course of early infancy and: a) identifies differences in the expression of maternal and paternal behaviors that may indicate depression; b) comments on the self-report measures most commonly used for determining maternal and paternal depression status; c) reviews the prevalence, the onset, the duration and the risk factors of maternal and paternal postpartum depression; d) briefly presents the adverse effects of maternal postpartum depression on early infant-mother interaction and comments on the contrasting findings derived from the limited number of studies on the effect of paternal postpartum depression on certain dimensions of early infant-parent interaction. In connection to this, it is concluded that postpartum depression of mothers and fathers is a “systemic disorder” which affects not only the parent’s functioning and sense of well-being, but it also has an impact on the interaction of parents with their infant and affects the emotional health of their partner; and e) comments on the clinical implications for healthcare professionals and emphasizes the need to focus on the improvement of the quality of parent-infant interaction of depressed mothers and fathers.
Energy Efficient Technique for IoT: A Review & Survey

— Internet of Things is the technology in which the sensed information is passed to the base station which is uploaded on the internet. Due to the decentralized nature of the network security, energy consumption is the major issue of the network. In the base paper technique security to the network is provided in which unidirectional and bi-directional communication is possible. The security to the network takes place in which security keys are generated using the clocks of the sensor nodes. In the paper, it has been discussed that clocks of the sensor nodes are weekly synchronized. Due to weak clock synchronization of the sensor nodes, security of the network gets compromised. In this work, improvement in the existing technique will be proposed by providing strong clock synchronization. The RSA algorithm is been used which will establish secure channel from source to destination. The time-lay technique will be implemented which provide strong clock synchronization between the sensor nodes. The encryption keys are generated for the data encryption is depends upon the clocks of the sensor nodes and strong clock synchronization improved the network security. This improvement will lead to reduce energy consumption of the network and increase network throughput.
VETERINARY DRUG RESIDUES IN FOOD-ANIMAL PRODUCTS: A GLOBAL PUBLIC HEALTH CONCERN

Antibiotics have been used in animal production for more than five decades now primarily to treat or prevent disease. In addition to this, the provision of antibiotics to food animals encompasses a wide variety of nontherapeutic purposes that include growth promotion which has led to their extensive use as antibiotic feed additives in animal feed at sub-therapeutic doses for extended periods. Although this has been beneficial for animal health and productivity, the prolonged and unregulated use of these antimicrobials has led to selection and dissemination of antibiotic resistant strains of antimicrobials. Consumption of food products of animal origin with residual antibiotic has become a major public health concern. Antimicrobial usage and antimicrobial resistance in animal production is now recognized to be an important contributor to the global problem of antimicrobial resistance. It is one of the most alarming problems faced by healthcare providers since the common bacterial infections are becoming difficult to treat due to antibiotic resistant bacteria. This represents a “One Health” challenge that urgently needs to be tackled by the international community. Welldesigned, scientifically sound interventions aimed to tackle excessive antimicrobial usage through development of effective, safe and novel alternatives needs to be investigated in addition to formulation of regulations by the policy makers.
Neural Network Ensemble for the Prediction Of Pathological Complete Response After Neoadjuvant Chemotherapy for Breast Cancer

: Neoadjuvant Chemotherapy is given intravenously during the treatment of breast cancer. Before the surgery, doctors suggest chemotherapy to deflate the large size of encroaching tumor. This research work propounds Neural Network Ensemble Machine Learning framework, which accomplishes ensemble of Machine Learning algorithms for constructing an systematized solution for anticipating the pathological complete response of the patients after Neoadjuvant Chemotherapy. Performance score is calculated by considering ten evaluation metrics namely, Accuracy, Mean Absolute Error, Root Mean Square Error, TP Rate, FP Rate, Precision, Recall, F-Measure, MCC, and, ROC. The outcomes are verified using K Fold cross validation technique and achieving an accuracy of 97.20%. When the execution of the proposed framework is accumulated with the accomplishment of state-of-the-art classifiers such as Bayes Net, Naïve Bayes, Logistic, Multilayer Perceptron, SMO, Voted Perceptron, etc, the results are quite promising. Machine learning can play a key role in saving lives, in the field of cancer detection.
Herpes Zoster Ophthalmicus—Diagnosis and Management

Varicella-zoster virus (VZV) infections are widely distributed in the general population. The lifetime risk of herpes zoster is estimated to be 10–20 %, increasing with age (1–4). Since herpes zoster ophthalmicus (HZO) accounts for 20 % of all locations of shingles, the lifetime risk of HZO is about 1–2 %. The management of ocular complications of VZV infection is now well codified, but sequellae still can occur, despite an armamentarium effective in limiting viral replication and its immune consequences.
ANALYSIS OF COLLABORATIVE FILTERING WITH I-SSU RECOMMENDATION SYSTEM

Social recommendation is common and prosperous among varied urban property applications like merchandise recommendation, on-line sharing and looking services. Users build use of those applications to create many implicit social networks through their daily social interactions. The users in such social networks will rate some fascinating things and provides comments. the bulk of the present studies investigate the rating prediction and recommendation of things supported user-item bipartite graph and user-user social graph, therefore referred to as social recommendation. However, the spacial issue wasn't thought-about in their recommendation mechanisms. With the speedy development of the service of location-based social networks, the spacial info step by step affects the standard and correlation of rating and recommendation of things. This paper survey a location-based social network (LBSN) doesn't solely mean adding a location to Associate in Nursing existing social network so individuals within the social organisation will share location-embedded info, however conjointly consists of the new social organisation created from people connected by the interdependence derived from their a panorama of the recommendations locations within the physical world still as their location-tagged media content, like photos, videos and text. During this paper survey on in location-based social networks with a balanced depth, facilitating analysis into this rising topic.
EFFECT OF PRE-INGESTION OF COLA NITIDA ON POST EXERCISE HEART RATE IN THE PHASES OF THE MENSTRUAL CYCLE

Cola nitida and estrogen, a predominant hormone of the follicular phase of the menstrual cycle have been documented to have some cardiovascular effects. Although at normal resting state, cardiovascular effects such as changes in heart rate may not obvious. This study is therefore aimed at assessing post-exercise heart rate adjustment time in subjects who ingested Cola nitida during the follicular and luteal phases of the menstrual cycle. Sixtyfour healthy volunteers with 32 subjects in the follicular phase and 32 subjects in the luteal phase of the menstrual cycle were studied. The thirty two subjects in each phase were further sub-divided into 4 subgroups with 8 subjects each group. The first groups of subjects were not given cola nitida while the remaining groups of subjects were given 100mg/kg, 200mg/kg and 400mg/kg of Cola nitida respectively. All subjects had their serum estrogen concentrations and base line heart rates assessed using standard methods before administering Cola nitida. 90 minutes post ingestion of Cola nitida, subjects were exposed to exercise for 35 minutes. The heart rates of subjects in sitting position were recorded every minute until they returned to baseline values. Results were presented as mean ± SD, p < 0.05 was considered to be statistically significant. Overall the percentage of subjects that experienced tachycardia was more in the luteal phase compared to follicular phase, although it was not statistically significant (p > 0.05) and the dose of Cola nitida ingested was observed to be inversely proportional to the heart rate adjustment time.
IMAP-INTELLIGENT MANAGEMENT OF ATTENDANCE PROCESSING USING VJ ALGORITHM FOR FACE DETECTION

-Every institute has its own methodology during this regard. Some area unit taking group action manually mistreatment the recent paper or file based mostly approach and a few have adopted strategies of automatic group action mistreatment some biometric techniques. The biometric systems on the market for face detection area unit time intense and need lots of cupboard space additionally the scholars need to stay up for an extended time to induce their group action marked. Face recognition technique is employed to boost potency and accuracy of detection method. In our project we tend to use the face recognition system for the aim of marking group action mechanically. A camera is employed to require the image of the schoolroom mistreatment the IPWebcam application on the golem system. The camera captures a picture within the starting of each hour and sends it to the administrator through wireless fidelity. The algorithmic program we tend to use is employed to extract the options of the face. The options area unit checked with the information and therefore the group action for everyone who is gift is marked. I
Evaluation of Power Delay Product for Low Power Full Adder Circuits based on GDI Logic Cell using Mentor Graphics

- This paper presents high speed and low power full adder cells designed with an alternative internal logic structure and Gate Diffusion Input (GDI) logic styles and hybrid CMOS logic style that lead to have a reduced Power Delay Product (PDP). The main design objective for this adder module is not only providing low-power dissipation and high speed but also full-voltage swing. In the first design, hybrid logic style is employed. The second design is based on a different new approach which eliminates the need of XOR/XNOR gates for designing full adder cell and also by utilizing GDI, technique in its structure, it provides Ultra Low-Power and high speed digital component as well as a full voltage swing circuit. The work carried out makes a comparison against other full adders reported for low PDP in terms of speed and power consumption. All the full adders were designed with 180nm technology, and were tested using a comprehensive test bench that allowed measuring the current taken from the full adder in-outs, besides the current provided from the power supply. Post layout simulations are expected to show that the full adder’s output from its counterpart’s exhibiting an average PDP advantage of close to 80%.