Merging biometrics with cryptography has become more familiar and a great scientific field was born for researchers. Biometrics adds distinctive property to the security systems, due biometrics is unique and individual features for every person. In this study, a new method is presented for ciphering data based on fingerprint features. This research is done by addressing plaintext message based on positions of extracted minutiae from fingerprint into a generated random text file regardless the size of data. The proposed method can be explained in three scenarios. In the first scenario the message was used inside random text directly at positions of minutiae in the second scenario the message was encrypted with a choosen word before ciphering

Television white spaces (TVWSs) refer to the unused part of the spectrum under the very high frequency (VHF) and ultra-high frequency (UHF) bands. TVWS are frequencies under licenced primary users (PUs) that are not being used and are available for secondary users (SUs). There are several ways of implementing TVWS in communications, one of which is the use of TVWS database (TVWSDB). The primary purpose of TVWSDB is to protect PUs from interference with SUs. There are several geolocation databases available for this purpose. However, it is unclear if those databases have the prediction feature that gives TVWSDB the capability of decreasing the number of inquiries from SUs. With this in mind, the authors present a reinforcement learning-ba

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

The aim of this work is the synthesis of new Schiff base derived from PVA and Erythro-ascorbic acid derivative (pentulosono-ɣ-lactone-2,3-enedianisoate) and its metal complexes of biological significance. All synthesized compounds were characterized by Thin layer chromatography (TLC) and FTIR spectra and aldehyde was also characterized by (U.V-Vis), 1HNMR, 13CNMR and mass spectra. The synthesized Schiff base & its metal complexes were screened for their in vitro antimicrobial activity against five pathogenic bacteria (Escherichia coli, Shigella dysentery,Klebsiellapneumonae,Staphylococcusaureus, Staphylococcus Albus) and two fungal (Aspergillus Niger,Yeast).The biological activity ofall complexes is higher than free Schiff base ligand andf

Mixed ligands reaction of [2-[(3-hydroxyphenyl)diazinyl]-1,2-benzothiazol-3(2H)-one-1,1-dioxide] (H2L, primary ligand) and bipyridyl (secondary ligand) with salts of Cr(III), Mn(II), Fe(III), Co(II) and Ni(II) was performed. A series of air-stable complexes with distinctive octahedral moieties was created by equal molar ratio (1:1:1). The formation of these compounds was verified using detecting analysis techniques incorporating mass spectra, which validated the achieved geometries. Fourier transform infrared (FTIR) analysis demonstrated how the ligands (H2L and bipyridyl) are chelated as tridentate (ONO) and bidentate (NN) groups, respectively and the coordination with the metal ions. Thermal decomposition studies using pyrolysis (

حضرت معقدات كل من الفنادايل, الخارصين, النحاس والكادميوم بتكافؤهم الثنائي والذهب بتكافؤه الثلاثي بأستخدام صبغة ازوجديدة (6،4،2-ثلاثي هيدروكسي-3-((3-هيدروكسي فنيل) ثنائي زينيل ) فنيل ) ايثان-1-اون المحضرة من ملح الديازونيوم مع ٦,٤,٢- ثلاثي هيدروكسي اسيتوفينون بعد عزل (E)-1-(2,4,6-trihydroxy-3-((3-hydroxyphenyl)diazenyl)phenyl)ethan-1-one تم تشخيصها بواسطة الطرق الطيفية المتاحة  والتقنيات التشخيصية لكل من التحليل الدقيق للعناصرواطياف كل من ال

The aim of advancements in technologies is to increase scientific development and get the overall human satisfaction and comfortability. One of the active research area in recent years that addresses the above mentioned issues, is the integration of radio frequency identification (RFID) technology into network-based systems. Even though, RFID is considered as a promising technology, it has some bleeding points. This paper identifies seven intertwined deficiencies, namely: remote setting, scalability, power saving, remote and concurrent tracking, reusability, automation, and continuity in work. This paper proposes the construction of a general purpose infrastructure for RFID-based applications (IRFID) to tackle these deficiencies. Finally

Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f