A Robust Student Attendance Monitoring System using NFC Technology and Biometrics

In most of the colleges across the globe, an efficient and authenticated attendance monitoring system for students has not been developed yet. In this paper, we are proposing a non-intrusive system wherein students can record their attendance by providing their fingerprint while they are seated in their places. This system makes use of NFC enabled smart phones, NFC tags, a biometric fingerprint scanner App and Wi-Fi for storing the attendance online. It provides authentication of students and security of data. Secure session is maintained by NFC tags using encryption. The lecture time can be saved since no manual attendance is required

(1,2,3,4-Tetra­hydro­isoquinoline-2-carbo­dithio­ato-κ2 S,S′)(thio­cyanato-κN)(tri­phenyl­phosphane)nickel(II)

The NiII atom in the mononuclear title compound, [Ni(C10H10NS2)(NCS)(C18H15P)], exists within a S2PN donor set that defines a distorted square-planar geometry. A significant asymmetry in the Ni—S bond lengths support the less effective trans effect of SCN− over PPh3

cis-Bis(4-methyl­piperazine-1-carbo­dithio­ato-κ2 S,S′)bis­(pyridine-κN)cadmium

In the title complex, [Cd(C6H11N2S2)2(C5H5N)2], the CdII ion is hexa­coordinated by two N atoms from two pyridine ligands and by four S atoms from two dithio­carbamate ligands in a distorted octa­hedral geometry. The CdII ion lies on a twofold axis. The piperazine ring is in chair conformation and its least-squares plane makes a dihedral angle of 81.4 (1)° with that of the pyridine ring

Bis(μ-N-benzyl-N-furfuryldithio­carbamato)-1:2κ3 S,S′:S′;2:1κ3 S,S′:S′-bis­[(N-benzyl-N-furfuryldithio­carbamato-κ2 S,S′)cadmium]

In the centrosymmetric title compound, [Cd2(C13H12NOS2)4], pairs of dithio­carbamate ligands exhibit different structural functions. Each of the terminal ligands is bidentately coordinated to one CdII atom and forms a planar four-membered CS2Cd chelate ring, whereas pairs of the tridentate bridging ligands link two neighbouring CdII atoms, forming extended eight-membered C2S4Cd2 tricyclic units whose geometry can be approximated by a chair conformation. The coordination polyhedron of the CdII atoms is a distorted square-pyramid. The five-membered furan ring and the benzene ring are disordered over two sets of sites with an occupancy ratio of 0.62 (8):0.38 (8)

Boosting a Hybrid Model Recommendation System for Sparse Data using Collaborative Filtering and Deep Learning

499-502The exponential increase in the volume of online data has generated a confront of overburden of data for online users, which slow down the suitable access to products of pursuit on the Web. This contributed to the need for recommendation systems. Recommender system is a special form of intelligent technique that takes advantage of past user transactions on products to give recommendations of products. Collaborative filtering has turn out to be the commonly adopted method of providing users with customized services, except that it endures the problem of sparsely rated inputs. For collaborative filtering, we introduce a deep learning-based architecture which evaluates a discrete factorisation of vectors from sparse inputs. The characteristics of the products are retrieved using a deep learning model, denoising auto encoders. The traditional collaborative filtering algorithm that predicts and uses the past history of consumer interest and product characteristics are updated with the characteristics obtained by deep learning model for sparse rated inputs. The results of sparse data problem tested on MovieLens data set will greatly enhance the user and product transaction

Effective recommendation model using social network for linking user pursuit to product content

40-45The ongoing advancement of data innovation and the rapid development of the internet has encouraged a blast of data which has highlighted the issue of data overload. In reaction to this issue, recommender programs have evolved and helped users find their fascinating content. With the progressively entangled social setting, how to satisfy customized demands effectively has become another development in customized proposal administration contemplates. To mitigate the sparse issue of recommendation systems, we suggest a new recommendation approach based on fuzzy theory to improve their consistency and flexibility in diverse contexts. The proposed method also employs social network to reflect multifaceted factors of users. In this strategy, we group clients and consider about assortment of complex variables. The results on amazon dataset indicate that the proposed method achieves better efficiency over current methods

Comparative Analysis of Rotation Invariant Pattern and Uniform Pattern in MMLBP Technique for Face Recognition

Recognizing humans based on one or more physical or behavioral traits is referred as Biometrics. Comparing to the traditional methods to authenticate persons, biometric plays a vital role in the area of human recognition. In the field of biometric, face and palm print recognition seeks more attention for the researchers. The failure of recognition is minimum and also the implementation is easier than more other techniques. In this paper we concentrated on face recognition with Local Binary Pattern(LBP), it is simple and fast to recognize face than more other algorithms. Uniform LBP is used to extract features to recognize the face to authenticate the persons. The “non-uniform” patterns are clustered into one pattern due to this lot of information lost. In order to overcome the heavy data which loss in non-uniform patterns a modified multi-scale LBP histogram algorithm is proposed. Hence, the useful non-uniform information is utilized without any training step with entire information without any data loss. We also compare the mapping methods, rotational invariant pattern and uniform with rotational invariant patterns and .hence evaluate the performance of the mapping methods