Miracle-dz/UniFAR-FTUs huggingface dataset:
FACE SKETCH RECOGNITION BASED ON SIFT AND MLBP

Facial Sketches are most widely used in law enforcement agencies for identification and apprehension of suspects, which may involve in several criminal activities. A forensic artist is commonly used to work with the eyewitness in order to draw a sketch that depicts the facial look of the criminal according to the spoken description. Facial sketches are particularly important when eyewitness' or victim's descriptions are the only form of evidence available it is then disseminated to law enforcement officers and media outlets with the hopes of someone knowing the suspect. In this work we plan to implement an efficient system to recognize a forensic sketch images to a gallary of mug shot images which will help law enforcement agencies. Our approach essentially will be to implement and verify the algorithm of Face Sketch Recognition, which solves the sketch recognition problem for 2-D image of faces, using the local feature based discriminant analysis (LFDA), multiscale local binary patterns(MLBP), Scale Invariant Feature Transform (SIFT) as feature descriptor and principal component analysis. In this work SIFT and MLBP algorithms are explained for feature extraction with an LFDA framework for dimensionality reduction. This report focuses on comparative analysis of SIFT and MLBP algorithms on the basis of experiments performed using 20 sketches with rotation and brightness changes for matching against gallery of photo images also experiments are performed for 40 semi-forensic sketches for matching against gallary of 125 images.
Named Entity Recognition Using Machine Learning Approaches

: The term Named-entity recognition is a subtask of information extraction that seeks to locate and classify the named entities from the given text. This paper surveys about the different approaches and techniques that are used for Named Entity Recognition, which identifies the named entities from the given data. It explains the different machine learning models that are used in the Named Entity Recognition. The performances of various Named Entity Recognition systems that are developed using machine learning models are reviewed. It also enumerates the applications of Named Entity Recognition in various fields and the challenges faced by them.
Multilevel edge detection using quantum and classical genetic algorithms: A comparative study

Summary In this work, we develop a multilevel edge detection method based on the Kapur and Tsal-lis entropies. The multilevel thresholding approach gives rise to an NP-hard optimization problem. We have used the Classical Genetic Algorithm (CGA) and the Quantum Genetic Algorithm (QGA) to solve this problem. The performance of the QGA has been tested on ten sample images and it is shown that the QGA outperforms significantly the CGA on a sample of real-world images. Moreover, it was found that the Kapur entropy is leads to a slightly better image segmentation quality than the Tsallis one.
A Review on 3D Model Reconstruction In Reverse Engineering

— Reconstruction of surface in three dimensions uses point clouds for removing noise. It is done by reverse engineering. Reverse engineering of geometric shapes is the technique of converting a large number of measured data points into a concise and consistent computer representation. The approximation of surface from a given set of samples is called surface reconstruction. Surface reconstruction methods are very helpful to recover the shape of real objects through reverse engineering. A surface is constructed from unorganized point clouds in three dimension space and can be converted into any geometrical shape. This paper reviews various algorithms used for the reconstruction of surfaces from cloud points in different geometrical shapes. Various topologies are possible like ring ,bus and mesh etc. There are number of techniques used to obtain the sample points photogrammetry technique, laser scanner, reflection technique and other. The main advantage of surface reconstruction approach is a much improved robustness with respect to noise. The algorithms used are half maximum length algorithm, advancing front algorithm, crust algorithm. The main issues compared are complexity, repeating points, quality of the surface reconstructed and execution time.
Rehabilitation Outcomes for Children with

Disabling hearing loss affects over 5% of the world’s population about 360 million people worldwide [1]. Hearing impairment can be defined as any loss of the ability to detect sound, and has different causes, depending on the part of the auditory pathway that is being affected. The auditory system consists of three main parts; the external ear, the middle ear, and the inner ear. The external ear is formed by the pinna, the part of the ear that is externally visible, and the ear canal, which both function to funnel sound waves towards the tympanic membrane. The middle ear begins at the tympanic membrane, or eardrum, and is primarily constituted of the ossicles three tiny bones, attached to each other, and to the eardrum on one end and the oval window on the other. As the eardrum vibrates when sound waves hit it, it sets the ossicles into motion too, which transfer this energy on to the fluid in the cochlea via the oval window.
Image Noise in Radiography and Tomography: Causes, Effects and Reduction Techniques

The presence of noise in images produced by medical imaging equipment is common and unavoidable. Image noise can obscure and stimulate pathology, even sometimes to the extent of making them diagnostically unusable. To minimize noise in medical images, it is essential to comprehend the sources of noise and how they occur. In this paper, we have reviewed different sources of noise that are present in images produced in radiography and tomography imaging techniques, the causes, effects and the various ways that are employed in their reduction. In order to completely eliminate noise in radiological imaging systems, we recommend that detectors that are free from noise should be designed and incorporated into future imaging systems.
A NALYSIS OF V ARIOUS F LAWS D ETECTION USING S EGMENTATION T ECHNIQUES IN W ELD I MAGES

It is necessary to detect suspected defect regions in the radiographic weld images to find the type of flaws. In this paper different segmentation techniques are studied in detail. Various techniques are implemented on radiographic NDT images of weldments for the detection of flaws produced during the welding process. It is necessary to detect suspected regions in the radiographic weld images to find the type of flaws and its causative factors. This requires processing of radiographic images by a suitable approach. Various flaw detection techniques are Flaw detection using Morphological edge based segmentation techniques, Region Growing Segmentation, Morphological Watershed Segmentation Techniques, Support Vector Machine (SVM) Classifier and Artificial Neural Network (ANN). All this techniques has some advantages and disadvantages which are discussed in the paper. Finally it is suggested that if edge based segmentation, region growing Segmentation, morphological operations and Watershed Segmentation are performed simultaneously then maximum number of flaws can be detected.
Secured P2P Network Using Self ORganizing Trust Model: SORT

: In peer to peer network two or more computers are connected in a network and share resources of each other without any centralized server. Existing system do not provide trustworthiness and recommendation about another peer also not provide any mechanism to prevent malicious activity. So, it may happen that, peer node cannot get good quality service from peer network and suffer from the malicious activity. So, our system can provide trustworthiness of particular peer. System provides facility to the user to give satisfaction and weight value to the peer after using the service of particular peer node. It calculates the service trust of each peer node by using service history. It also provides recommendation to the user by calculating service trust. Attacks of malicious activity are minimizing by building trust relationship among peer nodes. So, we have proposed a method to develop trust network and peer can find out malicious peers and develops trust relationships with good peers.
FAKE FACE IDENTIFICATION

: Objective-Automatic face recognition is now widely used in applications ranging from de-duplication of identity to authentication of mobile payment. This popularity of face recognition has raised concerns about face spoof attacks (also known as biometric sensor presentation attacks), where a photo or video of an authorized person‟s face could be used to gain access to facilities or services. While a number of face spoof detection techniques have been proposed, their generalization ability has not been adequately addressed. We propose an efficient and rather robust face spoof detection algorithm based on Image Distortion Analysis (IDA) . Design/Methodology/Approach-Four different features (specular reflection, blurriness, chromatic moment, and color diversity) are extracted to form the IDA feature vector. An ensemble classifier, consisting of multiple SVM classifiers trained for different face spoof attacks (e.g., printed photo and replayed video), is used to distinguish between genuine and spoof faces. The proposed approach is extended to multi-frame face spoof detection in videos using a voting based scheme. We also collect a face spoof database, MSU Mobile Face Spoofing Database (MSU MFSD),using two mobile devices (Google Nexus 5 and MacBook Air) with three types of spoof attacks (printed photo, replayed video with iPhone 5S and iPad Air). Limitations-It is difficulty in separating genuine and spoof faces, especially in cross-database and cross device scenarios. Practical implications-The system ensures user privacy and provides better security. Originality-Two public-domain face spoof databases (Idiap REPLAY-ATTACK and CASIA FASD), and the MSU MFSD database show that the proposed approach outperforms state-of-the-art methods in spoof detection.
Gaining Competitive Advantage by Innovation in Different Aspects of Providing Customer Service

Competitive advantage is a factor or a combination of factors which makes the organization more successful in a competitive environment and competitors cannot imitate it easily (Feverer, 1995). To gain the competitive advantage, an organization should consider its external position (Porte, 1985) beside its domestic capabilities (Barney, 1992). Providing services to customers and its effects on competitive advantages are of important and key discussions in marketing management. Providing services to customers and being customer oriented have an important impact on the success of an organization that is included in gaining competitive advantage. In life today, uncertainty rules over all industries. The economic changes in the work are the issues that organizations always face these days. One of the duties of organizations is to minimize these issues by implementing innovations in their services. Exploiting innovative service opportunities needs development and choosing the best ideas to create new services. In the present study which is qualitative, conceptual and is conducted using library research and comparative tools, by reviewing background of providing service to customers, it has been tried to identify different aspects of customer service and define innovation in each of these aspects as a competitive advantage for every organization and institution. In the end, it has been tried to present a comprehensive model in each aspect of providing customer service that leads to a competitive advantage. This model can be a reference for all the institutions and organizations which want to gain competitive advantage from providing customer service.
Technical Parameters Influencing to the Fermentation of Seeded Banana (Musa Balbisiana) Wine

Banana fruit has flesh not only rich in starch which changes into sugars on ripening but is also a good source of resistant starch. Banana is known to be rich in carbohydrates, dietary fibres, certain vitamins, and minerals. Banana is one of fruits with high level of potassium. Due to its high nutrient values, bananas are nutritious food recommended for people at all ages, especially for baby, also diet food for adults. In order to accelerate the added value of this valuable fruit, we investigated the wine fermentation from ripen banana. Substrate concentration, pH, and soluble dry matter content in Banana juice were an important parameters strongly affecting to wine fermentation. We used bentonite and isinglass as coagulant supporting for the clarification. Our results showed that banana juice must be diluted at ratio (1.0: 1.0, juice: water) ready for the fermentation. The fermentation process could be accomplished at the 14 day at pH = 4.2, Brix = 20. Turbidity in the fermented fluid could be removed effectively by treating with 1.0 gram of bentonite per 1 litter of fermented fluid in 6 weeks to get a good appearance of wine bottle.
Energy-Aware Robust Key Management Scheme for Dynamic Wireless Sensor Networks

: Security of communications over WSN is very important. Unlike their wired counterparts, WSNs throws many challenges apart from resource constrained nature such as open network architecture, highly dynamic network topology. Therefore an energy-aware scheme is required to protect communications. There are many key distribution schemes for WSN are existed in the literature but most of them are static in nature. In this paper we explore a new key distribution scheme for dynamic WSNs. In such network where the nodes are dynamic in nature and nodes have mobility, it is essential to have a mechanism for key updating. This is achieved using a self-organizing binary tree known as AVL tree. This data structure is capable of adapting to the dynamic situations of WSN and updates the key values in real time. We proposed algorithms to achieve this. We also built a prototype application that demonstrates the application of the scheme for secure video distribution in a network. Our empirical results reveal that the proposed scheme is energy efficient and secure.
Investigation of the Effect of Dynamic Capillary Pressure on Waterflooding in Extra Low Permeability Reservoirs

The dynamic capillary pressure is one of the important factors affecting the two phase percolation mechanism of waterflooding in extra low permeability reservoir. It is crucial to understand the effect of dynamic capillary pressure on oil displacement process in order to improve the waterflooding effectiveness. In this paper the dynamic capillary pressure effect was investigated quantitatively and a numerical flow model was built, in which the dynamic capillary pressure is considered. The effects of dynamic capillary pressure and water injection rate on the waterflooding effectiveness were analyzed. The results show that the dynamic capillary pressure has a significant influence on the oil displacement effectiveness. The bigger the dynamic capillary pressure, the more adverse waterflooding effectiveness is obtained. The water injection rate will influence the change of fluid saturation in the reservoir, which leads to the different dynamic capillary pressure effect. There is an optimum water injection rate which causes the minimum dynamic capillary pressure and percolation resistance.
System Model of VAMOS for GSM Receiver

— GSM network is seeing its greatest expansion because of the growing demand for mobile voice services in emerging markets recently while maintaining backward compatibility with the legacy system A newly proposed technology , Voice services over Adaptive Multiuser channels on One Slot (VAMOS) feature has the potential to double voice capacity of the existing GSM mobile communication system while maintaining backward compatibility with the legacy system would help operators in densely populated cities to alleviate the strain on their networks concept of MUROS is based on multiplexing two or more users onto one time slot without degrading the speech quality is based on Orthogonal Sub-Channel (OSC) approach. Lot of research work is dedicated to signal generation and especially to new receiver concepts as well as power control in order to implement VAMOS transmissions. The aim of our work is to implement a model system able to evaluate performance parameters related to downlink transmission in VAMOS. The model implements generation of the VAMOS modulated signal with power control and receiving solutions based on a modified MLSD (Maximum Likelihood sequence Detector) structure that allows comparison of performances in VAMOS downlink transmission.
SAT0365 Risk Factors for Visual Loss in Giant Cell Arteritis (GCA)

Background visual loss is the most frequent ischemic complication and the main cause of permanent disability among patients with GCA. To identify factors related to this complication may help physicians to start an early treatment and assay new therapies Objectives To analyse clinical and histological findings related to visual loss in patients with GCA Methods demographic, clinical and histological features of patients with biopsy-proven GCA recruited at 10 Hospitals from Spain (REVAS Study) were analysed. Statistical analysis was performed using SPSS vs. 20 Results 418 patients were included: 290 (69.4%) females (ratio F/M: 2.3/1). The mean age at diagnosis was 75.5 ± 7 (53–92), 55% patients being older than 75y. The median diagnosis delay was 7 weeks (IQR 4–12). Cardiovascular risk factors were present in 45% of patients (hypertension in 48.8%, hypercholesterolemia in 26.6%, diabetes mellitus in 19.4%). The most frequent symptoms at CGA diagnosis were recent onset headache (81%), constitutional symptoms (47%) and polymyalgia rheumatic (44.5%). Jaw claudication, cranial hyperesthesia and amaurosis fugax were reported by 44.5%, 31.8% and 16.5%2 of patients, respectively. A total of 84 patients suffered vision loss (in 4 cases involving both eyes), due to anterior optic ischemic neuropathy (AION) in 78 (92.8%), and to central retinal artery occlusion in 6 (7.1%). CVA was recorded in 6.5% of cases. Anemia was present in 76.3% of patients. Mean ESR was 98±23.4. Patients with visual loss presented more frequently jaw claudication (71.6% vs 39.2%), cranial hyperesthesia (52.6% vs 28.7%) and amaurosis fugax (52.6% vs 8.6%), and less frequently low-grade fever (16.7% vs 43.1%) and toxic syndrome (37.2% vs 53.4%). Regarding to histological findings: patients with visual loss presented on TAB more intimal hyperplasia (70.5% vs 57.7%) and lumen occlusion >50% (53.8 vs 19.4%). No other differences were found. Univariated analysis showed than AION was significantly related to the presence of amaurosis fugax (OR 12.8, 95% CI 7.0–23.3, p<0.001), jaw claudication (OR 4, 95%CI 2.3–7.1, p<0.001), cranial hyperesthesia (OR 2.4, 95%CI 1.5–4), and age at diagnosis ≥75 years old (OR 2.7, 95% CI 1.5–4.6, p<0.001). An inverse relationship between AION and the presence of low-grade fever and toxic syndrome was found. No significant relationship was found between visual loss development and cardiovascular risk factors or CVA Conclusions AION is the most frequent cause of vision loss in GCA. Jaw claudication, cranial hyperesthesia, amaurosis fugax, and age >75 older at diagnosis are significantly related to AION. A wider recognition of the disease would potentially reduce the prevalence of irreversible visual loss among GCA patients. Disclosure of Interest None declared
An Improved Shortest Job First Scheduling Algorithm to Decrease Starvation in Cloud Computing

: The introduced work is a change in the non-preemptive existing scheduling algorithm called SJF (Shortest Job First) in a cloud computing. The cloud computing is steadily retrieved by miscellaneous users. On the other hand as the amount over the server increments, in such instance to achieve the operational account time some scheduling algorithm is mandatory. Also, there is the prerequisite of an operational schedule that will designate the process for implementation from the queue. One of the operational scheduling techniques is SJF, but this tactic surges the starvation for small priority processes or the processes with enormous execution time. The introduced work is about to resolve all these difficulties and to decrease the average waiting time.
Studies on PWM Inverter Employing Series- Connected Capacitors Paralleled to a Single DC Voltage Source

This paper presents an effective circuit configuration of a multilevel inverter of single DC independent voltage source that can increase the number of output voltage levels with a less number of circuit components. To produce the output voltage levels the Seven-level pulse width modulation inverter consists of a single dc voltage source with a series of three capacitors, two diodes, three active switches and H-bridge cell. Here using modified switching strategy to solve the voltage unbalancing that occurred in series connected capacitors and THDv. MATLAB/Simulink software is used in the simulation and results are compared with the published data. Keywords—multilevel inverter, single DC sources, PWM, H-Bridge, Voltage unbalancing, THDv.
Automatic Hard Exudates Detection from Multi-Resolution Retinal Images Using HAAR Dual Tree Wavelet Transform

Diabetic retinopathy is the leading cause of vision loss in the worldwide. Therefore the prevention of vision loss is significant by monitoring the retinal health of diabetic patients. Hard exudates are one of the most occurring lesions caused by DR. They are yellowish or white patches of vascular damage with leakage, varying in sizes, shapes, and locations. They are either individual spots, clusters, or in large rings. The wavelet transform is powerful multi-resolution analysis tool. Here, Haar orthogonal wavelet family is used. The green channel is separated from retinal fundus images. Four databases MISP, DB0, DB1 and STARE are used. The KNN classifier is applied in order to separate images into exudates or non-exudates. The good sensitivity and accuracy obtained 75% and 77.14% respectively for MISP database. The specificity and NPV for STARE database obtained 97.05% and 99.53% respectively.
Power Efficiency of Half Adder Design using MTCMOS Technique in 35 Nanometre Regime

A novel high speed low power half adder cell is proposed in this paper. The critical path consist of an AND gate and an EX-OR gate. This cell offers higher speed, lower power consumption than the standard implementation of the half adder. In this paper a MTCMOS (Multi Threshold Complementary Metal Oxide Semiconductor) technique is proposed to reduce the leakage current and leakage power also and got better result as compared to standard half adder cell. MTCMOS is an effective circuit level technique that improves the performance and design low power cell by utilizing both low and high threshold voltage transistors. Leakage current of half adder is reduced by 50.24% using MTCMOS technique as compared to CMOS technique. Leakage power consumption of the half adder therefore reduced by 32.21% as compared to CMOS technique. All the simulation result based on 35 nm CMOS technology and simulated by cadence tool.