Miracle-dz/UniFAR-FTUs huggingface dataset:
CLASSIFICATION OF POWER QUALITYDISTURBANCES USING WAVELET TRANSFORM ANDS-TRANSFORM BASED ARTIFICIAL NEURALNETWORK

This paper presents features that characterize power quality disturbances from recorded voltage and current signals using wavelet transformation and S-transform analysis. The disturbance of interest includes sag, swell, transient and harmonics. A 25kv distribution network has been simulated using matlab software. The feature extraction has been done using wavelet transformation and S-transform, the coefficients are collected and given to the neural network for the best classification. The S-transform based classification shows better performance in detecting, localizing and classifying compared to the wavelet transform based Back Propagation Algorithm.
Temporomandibular Joint Synovial Fluid Components Levels: Implications for Arthrocentesis Outcome

Aim: The aim was to evaluate cytological and biochemical findings in the first synovial fluid (SF) aspirate as well in venous blood samples and to estimate the effect of arthrocentesis in the treatment of TMJ disorders. Patients and Methods: Thirty four patients with TMJ involvement (23 with osteoarthritis and 11 with rheumatoid arthritis, Wilkes ́ stages III, IV) after noneffective conservative treatment were treated with arthrocentesis using push and pull technique. The first synovial fluid aspirate (SF) was analysed for presence of crystals, rheumatoid factor (RF), PGE2, glucose level, number of erythrocytes and lymphocytes with cytological investigation. The levels of glucose, RF, CRP, ESR in venous blood were analysed. Preoperative radiographs and the scores preand posttreatment (after 6 months) maximal interincisal opening (MIO) for mandibular movement and visual analogue scale (VAS) for pain estimation were performed. Results: After 6 months MIO improved significantly (p < 0.001) and pain according to VAS had substantially decreased (p = 0.016). Crystals/granules were found in 6 patients (17.6%). There were not statistical significant differences between SF RF and plasma RF values (p > 0.05). Several correlations between the variables were found. Conclusions: The presence of crystals or chondromatosis granules in the synovial fluid, and presence of high level of PGE2 indicates a pathological condition of an inflammatory nature. Arthrocentesis with push and pull technique for the treatment of TMJ disorders offer favourable results with regard to increasing jaw motion and improving function.
BOTULINUM TOXIN IN DENTISTRY- A DEADLY POISON TO A REMARKABLY RESOURCEFUL THERAPEUTIC AGENT

Within the last 100 years, the perception of Botulinum neurotoxin (BTX) has evolved from that of a poison to a versatile clinical agent with various uses. BTX plays a key role in the management of many orofacial and dental disorders. Its indications are rapidly expanding, with ongoing trials for further applications. Over the past two decades the cosmetic and non cosmetic uses of Botulinum toxin in the orofacial region has gained wide popularity. However, despite its clinical use, what BTX specifically does in each condition is still not clear. The main aim of this review is to describe some of the unclear aspects of this potentially useful agent, with a focus on the current research in dentistry.
A Divide and Conquer Approach for Obstacles Overcoming of a Legged Robot

— This paper presents an approach for obstacles overcoming implemented for the four legged walking robot Guará, which was built with obstacle overcoming and avoiding capabilities using only information from contact sensors installed on its feet. The robot was designed as a research robot platform, walking straight and curved paths. The robot was designed with a proprioceptive sensing and the detection system was conceived to implement an approach local to the obstacle and manage an autonomous sequence of integrated movements to move across the obstacle or deviate from it, using only information from sensors installed on its feet, preserving its balance and stability. The complex movements and tracking sequences in operational space are proposed to be built from the combination of a small group of simple movements sequenced according to switching sequence of contact keys installed in the robot's foot. According to obstacle shape and dimensions and to the robot kinematic limits, sets of simple movements are combined to overcome the obstacle, giving navigation skill and autonomy to the legged robot. The approach used can be expanded to other complex autonomous movements like stair climbing and other features with a legged robot. The approach presented here can complement the information of vision-based or localization-based control robots necessary for safe navigation in unstructured environments. This strategy could also be used in searching and mapping of metals and other underground materials, especially antipersonnel landmines detection.
The Relationship Between Contraceptive Methods and Common Vaginal Infections

Background: Vaginitis is a common medical problem in females. Bacterial vaginosis, vulvovaginal candidiasis and trichomoniasis are the main etiologies of infectious vaginitis. Objectives: This study was designed to assess the relationship between contraceptive methods and common vaginal infections. Methods: In this cross-sectional study, 250 females were evaluated from December 2012 to February 2013. The researcher-made questionnaire included questions about individual characteristics and contraceptive methods. The participants underwent a gynecological exam. Specimens were collected from posterior fornix of the subjects and polymerase chain reaction assay was done to diagnose vaginitis. Data were analyzed using SPSS statistical software (version 17) and also descriptive and analytical statistics (chi-square, t test and fisher’s exact test). P values of < 0.05 were considered statistically significant. Results: On the basis of the findings, 43.6% of females suffered from vaginitis. Overall, 65.56% of participants used contraceptive methods. Condom use was the most prevalent method of contraception. A significant relationship was found between suffering from different types of common vaginal infections and using contraceptive methods (P = 0.017). The percentage of females with candidiasis amongst hormonal contraceptive users, and the percentage of individuals amongst non-hormonal contraceptive users were higher than the others. Conclusions: Contraceptives can increase the risk of vaginitis. Hence, health care providers should consider the probability of vaginitis in addition to the indications and contraindications of contraceptive methods and should guide couples in taking a step forward for improving their sexual and reproductive health.
A REVIEW ON INSTANCE AND FEATURE SELECTION IN BIG DATA ENVIRONMENT

Instance and feature selection has become an effective approach due to the enormous data which is continuously being produced in the field of research. It is difficult to process such large datasets by many systems. Though the traditional techniques are useful for large datasets, the numbers when in hundreds, thousands or millions face scaling problems. The proposed work focuses on, scalable instance and feature selection in big data environment. Locality-sensitive hashing instance selection F (LSH-IS-F) is a two pass method used to find similar instances along with Pearson correlation coefficient for feature selection. Hash function family is used which is a general method of reducing the size of a set; this is achieved by reindexing the elements into buckets. This process find similar instance and features in same bucket, hence instance/features can be reduced. The work aims at improving the performance of locality sensitive hashing by storing extra statistics of the instances and features that is assigned to each class in the bucket and also to improve accuracy of instance and feature selection algorithm by prototype generation.
AN IMPROVED KEY PRE-DISTRIBUTION SCHEME WITH DEPLOYMENT KNOWLEDGE FOR WIRELESS SENSOR NETWORKS

: Smart environments represent the next evolutionary development step in building, utilities, industrial, home, shipboard, and transportation systems automation. Like any sentient organism, the smart environment relies first and foremost on sensory data from the real world. Another unique feature of sensor networks is the cooperative effort of sensor nodes. Sensor nodes are fitted with an onboard processor. Instead of sending the raw data to the nodes responsible for the fusion, they use their processing abilities to locally carry out simple computations and transmit only the required and partially processed data. The challenges in the hierarchy of: detecting the relevant quantities, monitoring and collecting the data, assessing and evaluating the information, formulating meaningful user displays, and performing decision-making and alarm functions are enormous. The information needed by smart environments is provided by Distributed Wireless Sensor Networks, which are responsible for sensing as well as for the first stages of the processing hierarchy. Recent advances in electronic and computer technologies have paved the way for the proliferation of wireless sensor networks (WSN). Sensor networks usually consist of a large number of ultra-small autonomous devices. In typical application scenarios, sensor nodes are spread randomly over the deployment region under scrutiny and collect sensor data. Sensor networks are being deployed for a wide variety of applications, including military sensing and tracking, environment monitoring, patient monitoring and tracking, smart environments, etc. When sensor networks are deployed in a hostile environment, security becomes extremely important, as they are prone to different types of malicious attacks. In this paper, we address a scheme called Bloom’s Scheme; it makes use of asymmetric matrices in place of symmetric matrices in order to establish secret keys between node pairs thereby increasing the connectivity. In this proposed scheme, the network resilience against node capture is substantially improved.
Real-Time Detection of Driver Fatigue using DIP

– A Drowsy Driver Detection System has been developed, based on eye features detection algorithm and using a computer vision based concepts. The system uses a small monochrome security camera that points directly towards the driver’s face and monitors the driver’s eye and head movement in order to detect fatigue. The system deals with using information obtained for the binary version of the image to find the edges of the face, which narrows the area of where the eyes may exist. Once the face area is found, the eyes are found by computing the horizontal averages in the area. Once the accurate eyes are located, measuring the distances between the intensity changes in the eye area determine whether the eyes are open or closed. If the eyes are found closed for 5 consecutive frames, the system draws the conclusion that the driver is falling asleep and issues a warning signal. The system is also able to detect when the eyes cannot be found, and works under reasonable lighting conditions.
DISEASE MANAGEMENT IN ORGANIC AGRICULTURE

Broad management of ecosystem through modification in the cultural practices such as crop rotation, soil quality management through the addition of organic amendments constitute the preliminary defence against the attack of diseases followed by use of the curative methods like use of predators, parasitoids, plant products and ecologically safer chemicals forms the next alternatives of defence against the diseases. Apart from conventional fungicides and microbial biocontrol agents, plant products or extracts have been found effective in organic agriculture. A number of strategies including modification of cultural practices including crop rotation, soil health management, use of disease resistant plants, etc. , use of biological control agents, use of botanicals, entomopathogen, antagonists, microbials and organic pesticides and other permissible pesticides can be taken up for effective management of diseases.
Prevalence of Chronic Kidney Disease and it’s Risk Factors in Patients with Prediabetes in Saudi Population

Methods: For the present study, 850 participants were analyzed between the ages 18 to 98 years. All patients were from the population of the primary health centre at King Fahad Armed Forces Hospital, Jeddah, Saudi Arabia. All data were collected on the basis of a review of electronic medical data and through a personal interview. Weight (kg) and height (cm) were measured were recorded. Body Mass Index (BMI) values classified as overweight or obese (BMI ≥ 25.0 kg/m2). Participants were defined as having prediabetes if HbA1c 5.76. 4. Hypertension (HTN) was defined when the systolic blood pressure was ≥ 130 mmHg and/or diastolic blood pressure was ≥ 85 mmHg in addition to receiving any medication for hypertension. The total numbers of cohort were separated on basis of age values into five groups: <30 years, 30-39 years, 40-49 years, 50-59 years and ≥ 60 years.
A Real Time Virtual Dressing Room Application using Kinect and HD camera

: We present a virtual try-on system - EON Interactive Mirror - that employs one Kinect sensor and one High-Definition (HD) Camera.We first overview the major technical components for the complete virtual try-on system. We then elaborate on several key challenges such as calibration between the Kinect and HD cameras, and shoulder height estimation for individual subjects. Quality of these steps is the key to achieving seamless try-on experience for users. We also present performance comparison of our system implemented on top of two skeletal tracking SDKs: OpenNI and Kinect forWindows SDK (KWSDK). Lastly, we discuss our experience in deploying the system in retail stores and some potential future improvements. SDK We introduce a virtual dressing room application using the Microsoft Kinect sensor. We extract the user from the video stream by using depth and user label data provided by the Kinect sensor, register the cloth model with the Kinect skeletal tracking data, and detect skin to adjust the order of layers. We report an average percentage of overlap between the user and the cloth models of 83.97%.
Routing protocols in VANET: A Review

: Wireless networks are continuously attracting attention for their potential use in several fields such as adhoc networks, mesh networks, and vehicular adhoc networks. Vehicular adhoc networks (VANET) are expected to be massively deployed in upcoming vehicles, because their use can improve the road safety and comfort. The effective implementation of vehicular communication could improve traffic management system. This effectiveness could be achieved by designing and implementing efficient vehicular network protocols. Comparative analysis of several VANET protocols along with their advantages and limitations is presented in this paper.
Improving Feature Selection through Global Discretization for Content-based Image Retrieval and Classiﬁ cation

: Content Based Image Retrieval (CBIR) and Computer Aided Diagnosis (CAD) system use a mathematical representation (feature vector) of an image in the image retrieval process. The feature vector-based description of an image in CBIR system generates semantic gap problem. An image represented by a large size feature vector shows to be a solution for the semantic gap problem but it directs to the dimensionality curse problem. It does not assist executing image retrieval process and makes the classi ﬁ cation process enormously slow down. To raise the performance of the CBIR system, Feature selection methods are used. Here, we suggest a new supervised feature selection algorithm called IICBMergeFS (Interval InConsistency Based Merge for Feature Selection) to enhance the result of medical image diagnosis. IICBMergeFS is an easy and ordinary algorithm that employs the inconsistency rate to discretize numeric features continually until some irregularities are found in the data. Furthermore, the performance of the classi ﬁ cation and retrieval method is processed in terms of Precision, Sensitivity, and Speci ﬁ city. The test result shows that the proposed method provides an accurate classi ﬁ cation result and helps in retrieval of relevant images from the image database.
Chemical Functionalization of Graphene and Graphene oxide -A review

Graphene is a material that has generated enormous research interest and activity in the past few years due to its remarkable properties and wide applications in the fields, such as nanoelectronics, sensors, nanocomposites, batteries, supercapacitors, hydrogen storage, transparent conductors and energy storage materials. (Reduced) graphene oxides have a great potential as a functional chemical building block in fabrication of various carbon-based nanostructures and their composites, for which chemical functionalization of the materials is critically important. Functionalization of graphene is one of the key topics in graphene research. Graphene has found to be the best known transparent conductor or semiconductor. The graphene was synthesized by using chemical methods. This article aims to provide broad based coverage on the recent solution-based functionalization methods of graphene in a concise and mechanistic manner. This paper focuses on the reactions of the graphene sp backbone, such as nucleophilic addition, cycloaddition, free radical addition, substitution and rearrangement, and reduction of graphene oxide and its various environmental applications.
Localization of a cerebral pathology on magnetic resonance images by the level set without re-initialization and local region based method

The rapid development of medical imaging technology is revolutionizing medicine every day. Medical imaging allows scientists and doctors to disclose potentially vital information by scanning the human body noninvasively. The objective of this study is to locate or detect a cerebral pathology by the method of the active contour. The present work is a study on the possibility to define the outline of brain pathology using two methods: Level Set without re-initialization and local based region method. The processed images are given by a magnetic resonance scanner (MRI) 1.5 tesla; of three patients included in the medical imaging center A BOUKHATEM Oran in Algeria. Knowing that the images are T2, T1 weighted. To give credibility to this study, a comparative study is implemented between the two methods studied. In the final analysis, we will reap the benefits of each method and the Downside. Results have been able shown that the evolution of the level set algorithm without re-initialization is faster than the algorithm of based local Region, but is still less accurate in the localization of the pathology. For cons, the evolution of the algorithm based local area is very slow but much more accurate than the level set method without re-initialization. The only inconvenience is the requirement to initialize the curve C adjacent of pathology instead of taking the whole image. It was found that the time required for calculating the contour of the image by using magnetic resonance in the two methods, is considerably reduced and the image quality obtained at the end of treatment is remarkable to be able make a good medical diagnosis.
Evaluation of conventional and real-time PCR assays for Molecular diagnosis of Johne's disease in dairy cattle

Paratuberculosis (PTB, Johne s disease) is nowadays viewed as one of the most serious chronic bacterial diseases of ruminants such as cattle, sheep and goats (Stabel et al., 2004; Fernández-Silva et al., 2014). The disease is also found in wild animals (Machackova et al., 2004; Fischer et al., 2005). World-wide, the prevalence of the disease can range from 3-4% of the herds in regions with low incidence such as England (Cetinkaya et al., 1996), to 70.4% of cattle dairy operations in regions of high incidence such as the United States (Lombard et al., 2013). In the most of the African countries, at least one incident of the disease or the disease was suspected in cattle, sheep or ISSN: 2319-7706 Volume 3 Number 10 (2014) pp. 969-981 http://www.ijcmas. com
REVIEW ON - IOT BASED ENVIRONMENT MONITORING SYSTEM

This paper reviews on IOT based environment monitoring system. The main objective of proposed system is to provide environmental parameters at remote location using internet. The proposed system provides a viable and straightforward solution for environmental and ambient monitoring applications. The system represents the environmental and ambient parameter monitoring using low-power wireless sensors connected to the Internet, which send their measurements to a central server. Finally, data from all over the world, stored on the base station, can be remotely visualized from every device connected to the Internet. The development of a cyber physical system that monitors the environmental conditions or the ambient conditions at remote locations. The resulted solution provides the possibility of logging measurements from locations all over the world and of visualizing and analyzing the gathered data from any device connected to the Internet. This work encompasses the complete solution, a cyber-physical system, starting from the physical level, consisting of sensors and the communication protocol, and reaching data management and storage at the cyber level. It overcomes the problem of system integration and interoperability, providing a well-defined architecture that simplifies the transmission of data from sensors with different measurement capabilities and increases supervisory efficiency .
Predictive Biomarkers to Therapy, do they Exist in Hepatocellular Carcinoma?

In the rapid evolving field of oncology, a large body of evidence points to the importance of predictive biomarkers – a definitive amount of tissue or serum material we can measure and clearly follow to hopefully predict how a cancer patient responds to chemotherapy. We now see that even the same stage of disease in the same type of patients diagnosed at the same age with similar co-morbidities can exhibit diverse biology and therapeutic responses to chemotherapy. What is of most interest to many oncologists is whether we can tell a patient can respond to a certain type of chemotherapy, either traditional cytotoxics or novel targeted agents.
International Journal of Current Research in

Article Info In the present study, the edible fungus Pleurotus sajor-caju was investigated for its ability to grow on different lignocellulosic substrates namely, water hyacinth, wood chips and paddy and to produce various lignocellulolytic enzymes such as cellulase, xylanase and pectinase. The production pattern of the extracellular enzymes, total proteins and reducing sugar level was studied during the growth of this fungus under Solid State Fermentation (SSF) for a period of 56 days. Wheat grains were rapidly utilized and consumed by the fungus as a simple carbon source and were used for spawn formation. Different lignocellulosic complex carbon sources served as substrates and exhibited better induction process for more enzyme biosynthesis and production. The maximum activity of enzymes was obtained on 28 th and 56 th day of culture growth. The total yield of mushroom grown on different lignocellulosic substrates and levels of cellulose, pectinase and xylanase was also detected. Accepted: 25 January 2017 Available Online: 20 February 2017
Cyclostationary Spectrum Sensing in Cognitive Radio

— Cognitive radio allows unlicensed users to access licensed frequency bands through dynamic spectrum access so as to reduce spectrum scarcity. This requires intelligent spectrum sensing techniques. This paper investigates the use of cyclostationary detector and its simulation in MATLAB for licensed user detection. In this paper we present a theoretical discussion followed by application-oriented examples of the cyclostationary signatures used in practical cognitive radio and dynamic spectrum usage scenarios. We focus on orthogonal frequency division multiplexing (OFDM) based systems and present an analysis of a transceiver implementation employing these techniques developed on a cognitive radio test platform