Miracle-dz/UniFAR-FTUs huggingface dataset:
T A Friend Recommendation System based on Similarity Metric and Social Graphs

-All the existing social networking services recommend friends to users based only on their social graphs, which is not very appropriate in reflecting user‘s preferences in selecting a friend in real life. In this paper, we present a friend recommending system for social networks, which recommends friends to users based on their life styles as well as social graphs, as the proposed friend recommending mechanism is being integrated into social network. By taking the advantage of sensor-rich smart phones, the proposed system discovers the life styles of users , measures the similarity of life style existing between the users, calculates the friend recommendation score using the proposed similarity metric, and recommends friends to query user who are having high friend recommendation scores. Since the proposed system is integrated into the social network, the existing feature of social network i.e. the social graphs is used for recommending social friends to the user. Therefore on receiving the request, the proposed system returns a list of people with high friend recommendation scores as well as a list of social friends to the query user.
International Journal of Advance Research in Computer Science and Management Studies

This paper presents a review on genetic algorithms based on clustering methods. Clustering is an important form of data mining. It can be used to extract useful and hidden information from the datasets. Clustering techniques have a large area of applications including bioinformatics, web use data analysis and image analysis etc. Traditional clustering algorithms applied to datasets most of the times result in sub-optimal solution due to large search space, so evolutionary algorithms particularly genetic algorithms are best suited for the clustering tasks. The capability of Genetic algorithms is applied to find optimally disjoint partitions and proper number of clusters for a dataset. Genetic Algorithms (GAs) is applied to the clustering algorithm to enhance the performance of clustering algorithms. The capability of GAs is applied to evolve the proper number of clusters and to provide appropriate clustering. This paper present some existing GA based clustering algorithms.
Modified Surgical Correction of Over-riding Second Toe

EDL divides into three slits, a central slit attaches to the base of middle phalanx and another two lateral slits attaches to the distal phalanx. EDL tendon extend the interphalangeal joint (IPJ) of second toe only when the MTPJ is in neutral or flexed position. However, when MTPJ is extended it becomes the deforming force to the MTPJ. This causes dorsal subluxation of the MTPJ. This is the first factor resulting in MTPJ instability. The primary function of dorsal interossei muscle is flexion of the MTPJ. These dorsal interossei muscles passes below the axis of rotation of MTPJ and are inserted into the extensor hood of extensor digitorum longus (EDL) tendon at the MTPJ and also the base of proximal phalanx. In a chronic extended MTPJ, the actions of these two muscle changes as it moves dorsally to the center of rotation of the MTPJ. This will result in a dorsal subluxation of force of the second MTPJ. The lumbrical of the second toe is only present on the medial side of the second MTPJ and causes flexion and adduction of the joint. However, flexion becomes ineffective when the 2 MTPJ is chronically extended. In this event, the muscle Abstract
A Safe Ordered and Speedy Emergency Navigation Approach

In case of emergencies, navigation services guides people to exits while keeping them away from emergencies so as to save human lives. For emergency navigation to be quick, early and automatic detection of potential dangers, and quick response with safe paths to exits are the core requirements, both of which depends on proper and continuous monitoring of the surrounding and reliable data transmission. Wireless sensor networks (WSNs) are a natural choice of the infrastructure to support emergency navigation services, as they are relatively easy to deploy and of affordable costs, and their ability of ubiquitous sensing and communication. Although many efforts have been made to WSN-assisted emergency navigation, almost all existing works neglect to consider the hazard levels of emergencies and the evacuation capabilities of exits. Without considering such aspects, existing navigation approaches may fail to keep people farther away from emergencies of high hazard levels and would probably encounter congestions at exits with lower evacuation capabilities. A Safe, Ordered, and Speedy Emergency Navigation Approach, which takes the hazard levels of emergencies and the evacuation capabilities of exits into account and provides the mobile users the safest navigation paths accordingly is used. We formally model the situation-aware emergency navigation problem and establish a hazard potential field in the network, which is theoretically free of local minima. By guiding users following the descend gradient of the hazard potential field, SEND can thereby achieve guaranteed success of navigation and provide optimal safety. The effectiveness of SEND is validated by both experiments and extensive simulations in planar (2D) and cubic (3D) scenarios.
A Robust Ad hoc Reactive Energy-constraint Multi Path routing protocol for High Mobility Networks

— Existing routing metrics in mobile ad hoc networks are limited to avoid link failures either due to insufficient battery power or high speed of node. Thus, these routing metrics are not able to capture network characteristics completely. This paper proposes a new robust multi path routing protocol for high mobility and scalable ad hoc networks, RARE − MP. It selects route based on the value of Node Reliability Factor which is a function of residual energy, speed and hop count. The key idea of protocol is to compute nodal reliability factor of route in path selection process and sort multiple path by descending nodal reliability factor. In essence, whenever a new route with higher nodal reliability factor is available, data packets are forwarded through a new emerging route. It balances the nodal battery power utilization and reduces the link failures leading to increase the overall life time of network. The simulation result shows that proposed protocol outperforms in comparison with both, energy aware routing protocol and energy unaware routing protocol in high speed and high density environment.
INVESTIGATION THOUGHT DECISION-MAKING TRIAL AND EVALUATION LABORATORY (DEMATEL) IN GREEN SUPPLY CHAIN MANAGEMENT INCLUDE REDUCING AND RECYCLING PHARMACEUTICAL WASTE FOR A PHARMACEUTICAL MANUFACTURER IN INDIA

This study presented an integrated approach for selecting appropriate suppliers in addressing Pharmaceutical Green Supply Chain Management (PGSCM) of environment change via Multiple Criteria Decision Making Method (MCDM). In this study, thirteen criteria of Pharmaceutical Green Supply Chain Management with three dimensions were identified from literature review and interview with three experts in a Pharmaceutical manufacturer. By considering the interrelationships among criteria, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) were applied to deal with the importance and causal relationships among the evaluation criteria of supplier selection. As indicated by the results, the four most important criteria are internal environmental management, involvement in initiatives for negative economic, training related reducing waste management, and green purchasing. The results also found that the top four criteria not only have potential significance in the selection of green suppliers with waste management competencies, but also affect the other twelve criteria, separately.
Determination of Phospholipids in Milk by HPLC

Phospholipids are part of the milk fat globule membrane. Functional and technological properties make them interesting for the development of functional foods or as ingredients of technological interest. In this study an analytical procedure for determination of major phospholipids in milk (phosphatidyl Ethanolamine, phosphatidylinositol, phosphatidyl Choline, phosphatidyl Serine and sphingomyelin) by HPLC with evaporative light scattering detector was optimized and validated. The best calibrations were achieved when an exponential model was applied; the squared correlation coefficients show a satisfactory linearity ranging from 0.975 to 0.993. The limit of detection for the different phospholipids ranged from 0. 17μg for phosphatidyl Serine to 0. 61μg for phosphatidyl Ethanolamine; and the limit of quantification from 0. 40μg for phosphatidyl Serine to 1. 26μg for phosphatidyl Ethanolamine. The intra-day and inter-day precision of the method was below 10% for all the compounds except phosphatidylinositol in the intra-day assay with a value of 12.4%. However, the values of intra-day and inter-day repeatability show that the variations, due to the extraction procedure, do not depend whether the assays were performed after short intervals of time or not. The recovery ranged from 74% for phosphatidil Serine to 112% for phosphatidilcoline. The addition of formic acid to the mobile phase in order to achieve an acidic buffer extends the column life considerably.
Level of Fusion in Multimodal Biometrics: a Review

— User verification systems that use a single biometric indicator often have to contend with noisy sensor data, restricted degree of freedom, non-universality of the biometric trait and unacceptable error rates. So the need of using multimodal biometric system occurred. A multimodal biometric system combines the different biometric traits and provides better recognition performance as compared to the systems based on single biometric trait or modality. In this paper, studies of different modalities are discussed and also discuss the various techniques used in different level of fusion with the objective of improving performance & robustness at each level of fusion.
Lethal effect of Thevetia peruviana leaf extract on larval stages of Musca domestica ( L )

The common house fly, Musca domestica L. (Diptera, Muscidae) is a major domestic insect pest, particularly in tropical countries. House fly management uses several integrated methods to control house fly populations. Chemical insecticides gives many problems such as insect resistance, toxic side effects to human or non-target organism and residues in the environment. Hence in the present study a new effort has been made to assess the larvicidal activity of Thevetia peruviana leaves, extracted with acetone and evaluated against the developmental stages of housefly Musca domestica. The result revealed on the age and concentration and is based on the effect of plant extract against the housefly larvae. LC50 and LC90 were noticed and the values are 153.169, 208.642, 251.332, 479.836, 587.287 and 614.775 ppm against I-III instar larvae respectively. The toxic effect were noticed in the order of I>II>III instar larvae respectively. The larvicidal activity may be due to the presence of phytochemicals alkaloids, steroidal glycosides, phenol, chlorogenic acid, flavonoid and tannin. The phytochemicals individually or synergistically cause the larval mortality.
A Study of Two Stage Operational Transconductance Amplifier using Floating gate MOSFET

This paper presents a two stage operational transconductance amplifier realized using floating gate MOSFETs in differential inputs. A configuration of two stage operational transconductance amplifier using floating gate MOSFET for low power and low voltage applications is presented. Here we design a two stage operational transconductance amplifier using floating gate MOSFET in HSPICE 180nm CMOS technology with the entire transistor in the saturation region. The simulated output transient response and frequency response is shown for a supply voltage of 1V using Cosmos Scope in HSPICE. DC gain is 60dB, settling time 550ns and power consumption 3.06pW.
Can we Measure Speech Perception Ability Objectively in Young Children using Cochlear Implant?

Speech perception plays a significant role in the development of speech and language ability in children with hearing loss. There are various speech perception tests with the specific protocol to administer and score. Auditory evoked potential is an objective measure used for assessing hearing acuity in young children. Higher cortical evoked potential test provides an effective indication of the physiological status of auditory cortex. CEAP can be obtained in young children with assistive devices. The present research study aims to investigate whether latency and amplitude of aided cortical evoked potential can predict Speech perception score in cochlear implant users. 52 cochlear implant users and 102 typical children were tested. The mean age for children using cochlear implant was 8.05 years, standard deviation 1.4. The normal hearing group had a mean age of 8.12 years and standard deviation 1.46. Cochlear implant users were having at least 15 active electrodes. Speech stimulus was used with 100 ms duration, 20 ms rise/fall, 20 ms plateau tones. The inter-stimulus interval was kept at 1125 ms. During statistical analysis of data, CEAP P1 latencies and speech perception scores were found to be related. A further regression equation was obtained. The present study reveals speech stimuli can evoke distinct neural response patterns from auditory cortex. The present research study also helps in understanding the neural processing of speech in individuals with hearing impairment using Cochlear implant. Statistical analysis of data CEAP P1 latency and speech perception score regression equation were obtained. The result reveals that speech stimuli can evoke distinct neural response patterns from auditory cortex. CEAP finding support speech perception ability and auditory evoked potential help to the study of neural processing of speech in individuals with the cochlear implant. The evoked potential and speech perception ability has a significant relation between them.
TECF: Accomplishment of Content Framework Tactic to Temporal Theme Condensation

: A topic is defined as a developing event which contains many related events and activities. The convenient storage of documents in the internet leads to the difficult in exploration since there are sequence of documents published by different authors for the particular keyword. Due to the phenomenal growth of a large number of documents in the internet it is difficult for the users to read the entire contents and conclude what exactly present in the document. The situation is even worse if the event is time related. In this study we define a task which summarizes the core content in the chronological order and this makes to readers to understand the content easily. The proposed model, called TECF(Theme Encapsulation and Content Framework)derives themes from the documents on the topic with the help of Eigen vectors of the temporal block association matrix, from this the summaries of the document are extracted. Finally the extracted summaries are associated to find the temporal closeness with the help of evolution graph. In the proposed techniques the core content related to the topic is covered in the coherent and consistent manner when compared with the existing separation techniques like human based summaries.
Analysis and Evaluation of Sinusoidal Power clocked Adiabatic Logic Circuits

: Adiabatic switching that works based on the principle of charge recovery is one of the most promising non conventional approaches for low power design of VLSI circuits. This paper focuses on the classification and comparison of adiabatic circuits that are operated by sinusoidal clock signal. The performance analysis and comparison are carried out by implementing the 8-bit array multiplier using static adiabatic logic families, namely, the QSERL, CEPAL and GFCAL. Comparison against the dynamic adiabatic logic families, namely, the CAL, PAL and SCAL have also been made. The performance of all of the circuits is evaluated in terms of the power dissipation for varying range of adiabatic frequencies. The drivability characteristics are also evaluated by using varying capacitive loads. Through post layout simulation of the full adder cells implemented using CEPAL and SCAL, the layout area requirement while keeping the layout density constant, for the static and dynamic adiabatic logic types is studied and compared. All the simulations have been carried out using the industry standard Cadence® Virtuoso tools using the 180nm technology library files.
Survey: Block cipher Methods

— In this paper we give a short overview of Symmetric key block cipher for different algorithms presented in this field according to classified it in cryptography where we classified into categories. first, Mode of operation which is ways helped to apply block cipher to encrypt larger plaintext. second, iterated product cipher which also classified it into Feistel Network, substitution-permutation networks and Unbalanced Feistel Network.
Improved Classification Based Association Rule Mining

: Association rule mining and classification are two important techniques of data mining in knowledge discovery process. Integration of these two techniques is an important research focus and has many applications in data mining. Integration of these two techniques has produced new approaches called Class Association Rule Mining or Associative Classification Technique. These two combined approaches provide better classification accuracy in classifying the data. Content based information retrieval research areas require high efficiency and performance. In these applications association rule mining discovers association patterns from data and based on association patterns we classify target classes. Our paper mainly focuses on combining classification and association rule mining for classifying the data accurately. In this paper we proposed to implement two new algorithms CPAR (Classification Based on Predictive Association Rule) and CMAR (Classification Based on Multiple-class Association Rules) which combines the advantages of both associative classification and traditional rule-based classification. Instead of generating a large number of candidate rules as in associative classification, CPAR adopts a greedy algorithm to generate rules directly from training data. Moreover, CPAR generates and tests more rules than traditional rule-based classifiers to avoid missing important rules. To avoid over fitting, CPAR uses expected accuracy to evaluate each rule and uses the best k rules in prediction. CMAR applies a CR-tree structure to store and retrieve mined association rules efficiently, and prunes rules effectively based on confidence, correlation and database coverage. The classification is performed based on a weighted χ2 analysis using multiple strong association rules. Our extensive experiments show that CMAR is consistent, highly effective at classification of various kinds of databases and has better average classification accuracy in comparison with FOIL (First Order Inductive Learner) and PRM (Predictive Rule Mining). The proposed algorithms are superior in terms of memory requirements, time complexity and eliminate intermediate data structures in implementation
Genetic Algorithm Based Denoising of Medical Image

In image processing, the qualities of images are conjectured by improvising the reduction of noises in the images. Digital images are obtruded with variety of noises that affects the quality of an image. One of the most important process is image de-noising in the image processing techniques as it forms the basis of all other image processing algorithms such as image segmentation, image feature extraction etc. The main goal in de-noising of an image is to obtain the original details of an image as maximum as possible. This paper presents an adaptive genetic algorithm which denoises an image and produces best sample. On the basis of parameter performance can be calculated i.e. PSNR (peak-signal-to-noise-ratio) & SSIM (Structure Similarity). The experiments are done in the mat lab programming language and the results are plotted.
Statically Analysis on Big Data Using R Programming & SVM

:- Over the past decade, big data analysis has seen an exponential growth and will certainly continue to witness spectacular developments due to the emergence of new interactive multimedia applications and highly integrated systems driven by the rapid growth in information services and microelectronic devices. So far, most of the current mobile systems are mainly targeted to voice communications with low transmission rates. In the near future, however, big data access at high transmission rates will be. This is a review on accessible big-data systems that include a set of tools and technique to load, extract, and improve dissimilar data while leveraging the immensely parallel processing power to perform complex transformations and analysis. “Big-Data” system faces a series of technical challenges.
The Role of Mitochondria in Neurodegeneration Development

Mitochondria are highly specialized organelles that are crucial players in cell physiology and pathophysiology. Known as “powerhouse of the cell”, their major function is ATP production, but also regulation of cytosolic calcium homeostasis and ROS generation. Mitochondrial dysfunction is associated with neurodegenerative diseases due to neuronal cells dependence on mitochondria. Parkinson’s and Alzheimer’s diseases are consequences out of misfolding and aggregation of crucial proteins in the brain α-synleucin and β-amyloid, which interact with mitochondria in neurons and astrocytes. What is more, in neurodegeneration development, mitochondrial dynamics and quality control were also found interrupted.
Oral Health and Quality of Life Among 45- to 64-year-old Patients Attending a Clinic in Iasi, Romania

Aim: The aim of this study was to investigate the impact of oral health conditions on the quality of life of 45-64-yearolds in Romania. Methods: Data were collected from a convenience sample of 170 subjects (age range: 45-64 years; 64% females, 36% males) who attended a community dental clinic in Iasi, Romania, for routine care and treatment. The patients were clinically examined according to the World Health Organization (WHO) 1997 criteria. Oral health-related quality of life was assessed with the short version of the Oral Health Impact Profile (OHIP-14). Results: The most affected quality of life dimensions were physical disability (56%) and physical pain (41%). The next most commonly reported dimensions were psychological disability (24%), especially embarrassment (24%) and social disability (23%). Only 7% of the respondents reported functional limitations. Significant correlations were found between several oral health indicators and the OHIP-14 scores such as between the indicators “partial denture used” and “physical disability” (r=0.42), “physical pain” (r=0.32), “psychological disability” (r=-0.31), and between the oral health indicator “emergency treatment needed” and the “social disability” index (r=0.44). Conclusions: The data showed that significant percentages of the patients surveyed had impaired oral health-related quality of life and that several oral health indicators, especially for the indicator “partial dentures used”, correlated with some OHIP-14 indicators. Gaining a better understanding of how oral health—such as the use of partial prostheses—affects patients’ quality of life could contribute to a more patient-centred approach to providing oral health care.