Optimization of Energy Harvesting MISO Communication System with Feedback

Optimization of a point-to-point (p2p) multipleinput single-output (MISO) communication system is considered when both the transmitter (TX) and the receiver (RX) have energy harvesting (EH) capabilities. The RX is interested in feeding back the channel state information (CSI) to the TX to help improve the transmission rate. The objective is to maximize the throughput by a deadline, subject to the EH constraints at the TX and the RX. The throughput metric considered is an upper bound on the ergodic rate of the MISO channel with beamforming and limited feedback. Feedback bit allocation and transmission policies that maximize the upper bound on the ergodic rate are obtained. Tools from majorization theory are used to simplify the formulated optimization problems. Optimal policies obtained for the modified problem outperform the naive scheme in which no intelligent management of energy is performed.Comment: 11 page

Overcoming Forensic Implications with Enhancing Security in iOS

As the decades passed, smartphones have come to their greatest inventions. But their history has more than 2500 years starting from a basic thing of strings and beads, i.e. from the Abacus to the latest of our present iPhone. With every special invention in this area brought people together socially over the internet. This, in turn, raised the alarm for having secured communication. With these devices getting popular, development in the technology to enhance the security features in those devices has also been increasing. These advancements have brought Apple operating system (IOS) into light. These devices are one step ahead of all other smartphones regarding storage by having space for storing emails, GPS data and many more. This feature of storage has a major advantage in conducting forensics for investigation purposes. In this research, I performed data acquisition on iPhones with two different OS versions using various forensic tools and then compare the forensic implications with variant security features. I analyzed the forensic implications with enhancements in security and iPhone operating systems over the years. I also used to software to break the iPhone passcode which is the major forensic implication caused

Degradation of Chlorophenols in Swine Waste

Naturally occurring plant derived phenols can be degraded through bacteria in swine waste. Chlorinated phenols, which are not naturally present in the environment, are toxic and generated from industrial activities as such petrochemical, pharmaceutical, plastic, rubber, pesticide, iron, steel, paper production, coal conversion, wood preserving, and cellulose bleaching. Large scale coal gasification and carbonization plants are another source of chlorinated phenols. Although not normally present in the environment, chlorinated phenols are structurally similar to many plant derived phenolics. It is our hypothesis that bacteria located in swine wastes may also have the ability to degrade chlorinated phenols. Identifying situations (and organisms) in which degradation of pollutants occurs is important field of research. Experimental work was focused on measuring the degradation of seven chlorinated phenols in swine waste using solid-phase micro-extraction (SPME) and gas chromatography(GC). Microbes in the waste perform respiration or fermentation to obtain the energy they need to carry out their life processes. Fermentation is a process in which electrons are transferred from one organic substrate to another and which results in incomplete degradation of organic compounds. Anaerobic respiration is a process in which organic substrates are degraded completely to CO2, but using substances other than oxygen as the terminal electron acceptor (such as Fe(III), NO3- or SO42-). Anaerobic respiration using these alternative electron acceptors provides an easier pathway for degradation of aromatics than fermentation alone. Usually the abundance of these electron acceptors in waste is low since microbes consume them readily and thus they must be added to the mixture. Our work focused on development of methods for the quantification of chlorinated phenols in swine wastes and results of bioremediation research. In this study, chlorophenols were extracted by SPME and analysed by GC. This research project mainly focused on the anaerobic degradation of chlorophenols in swine waste. It was observed that the decreased concentration of the chlorophenols was likely due to partitioning of the chlorophenols to solids, sticking to glass bottles and by bacteria present in the swine waste. In summary, it was observed that by ANOVA and gas production analysis 2,6-dichlorophenol and 2,4,5-trichlorophenol were likely to be degraded by bacteria present in swine waste

E-Exam Engine

E-Exam Engine is a web application by which is designed for Educational Institutes like Grad Schools, Colleges, and Private Institutes to conduct logic tests of their students on a regular basis. Design to facilitate administrator and user friendly interface complete and secure information is provided to user scope. The E-Exam Engine is the process of conducting exam online. This project Provide accurate and flexible manner of conducting exam online. This Project provides more accurate and efficient way to take exam. It also provides flexibility to the user as one can give the exam at home. This is a one of the good project for Grad Students. Development process of the system starts with System analysis. System analysis involves creating a formal model of the problem to be solved by understanding requirements

UAV Trajectory Optimization and Tracking for User Localization in Wireless Networks

In this paper, we investigate the problem of UAV-aided user localization in wireless networks. Unlike the existing works, we do not assume perfect knowledge of the UAV location, hence we not only need to localize the users but also to track the UAV location. To do so, we utilize the time-of-arrival along with received signal strength radio measurements collected from users using a UAV. A simultaneous localization and mapping (SLAM) framework building on the Expectation-Maximization-based least-squares method is proposed to classify measurements into line-of-sight or non-line-of-sight categories and learn the radio channel, and at the same, localize the users and track the UAV. This framework also allows us to exploit other types of measurements such as the rough estimate of the UAV location available from GPS, and the UAV velocity measured by an inertial measurement unit (IMU) on-board, to achieve better localization accuracy. Moreover, the trajectory of the UAV is optimized which brings considerable improvement to the localization performance. The simulations show the out-performance of the developed algorithm when compared to other approaches

Design and Quantitation of Membrane Binding Lipid Anchors : Exploring Prion-Prion Interactions on Membrane Surfaces

The prion protein (PrP) is an endogenous, metal binding protein present in the neuronal cells of the central nervous system. Prion is associated with a class of neurodegenerative diseases known as transmissible spongiform encephalopathies. The C-terminal region of the prion protein is anchored to the cell surface by means of a glycophosphatidylinositol (GPI) anchor[superscript]19. Studies indicate that PrP self-recognition may be an important factor in both the normal function and misfunction of PrP. Elucidating the molecular basis for PrP-PrP interactions in the context of its membrane bound state will help in understanding the normal function of PrP, such as the signaling mechanism for endocytosis, and the factors that influence disease causing structural changes. Fluorescently labeled models of prion protein were previously developed to investigate PrP-PrP interactions and metal binding at molecular level. Peptides constituting the metal binding region were anchored to small unilamellar vesicles (liposomes) and PrP-PrP interactions were studied as a function of added metal45. Anchoring the peptides is an essential step to understand the protein interactions in the context of a cell surface. The main objective of this research is to prepare a molecule capable of anchoring the majority of a PrP sample to a liposome and develop a spin-label based assay to determine the percentage of molecules anchored to the liposome surface. Four lipophilic molecules containing a nitroxide spin-label have been synthesized and their electron paramagnetic resonance (EPR) spectra collected in the presence and absence of liposomes. The EPR spectrum of the nitroxide is very sensitive to the motion of the spin label and the proximity to other spin labeled molecules. The anchor with a linear chain of sixteen carbon atoms showed the most dramatic changes in the EPR spectrum and is likely the best anchor. We are planning to use a paramagnetic relaxation agent that aids in the quantitation and fluorescent compounds which aid in determining where the spin-labeled molecules localize. The spin-label methodology will allow us to conduct more quantitative experiments on PrP interactions with respect to metal binding, change in temperature, pH etc.  M.S

Relative Ionenintensitäten von O-Alkyl-Oligosacchariden in ESI IT-MS: Eine quantitative Bewertung

In the field of polysaccharides, studying the distribution of different substituents over the polymer chain is a key to understand the properties of these widely applied derivatives, e.g. cellulose or starch ethers. Electrospray ionization coupled with mass spectrometry (ESI-MS) is an important analytical technique for the analysis of polysaccharide derivatives. It uses substitution patterns in mixtures of oligomers to recognize heterogeneities, bimodality or blocky sequences. Partial de-polymerization and subsequent analysis of molar composition of the oligosaccharide mixture with respect to substituent distribution is often applied. Quantitative analysis is hampered, however, by the fact that compounds of different chemistry and molar mass usually show different ionization efficiencies (IE). Direct analysis of the de-polymerized mixture by syringe pump infusion or with LC coupled to Electrospray Ionizaiton-Ion Trap-Mass Spectrometry (ESI-IT-MS) is the method of choice for such complex mixtures. However, DS-dependent differences in chemistry and mass cause discrimination and thus distortion of the DS-profile for a certain DP, which cannot be corrected due to the lack of standard compounds. IE depends on properties chemistry of analyte, e.g. ion complexation ability, polarity, solvation energy, surface activity, molecular weight, etc., and also on the instrumental parameters. Therefore, we studied the influence on various parameters on relative ion intensities in ESI-IT-MS to understand the principles and examine whether they follow certain trends. Binary and complex mixtures of O-alkylated maltooligosaccharides of defined composition were prepared which differed in chemistry, size, mass (DP) etc. and analyzed under defined MS conditions.Im Bereich von Polysacchariden, die Verteilung der verschiedenen Substituenten über die Polymerkette zu studieren ist ein Schlüssel, um die Eigenschaften dieser weit angewendeten Derivate zu verstehen, z.B. Cellulose oder Stärkenether. Elektrosprayionisierung Massenspektrometrie (ESI-MS) ist eine wichtige analytische Technik für die Analyse von Polysaccharidderivaten. Es verwendet Substitutionsmuster in Mischungen von Oligomeren Heterogenitäten, Bimodalität oder Blocky Sequenzen zu erkennen. Teil de-Polymerisation und die anschließende Analyse der molaren Zusammensetzung der Oligosaccharidmischung bezüglich Substituentenverteilung wird häufig angewendet. Die quantitative Analyse wird trotzdem erschwert durch die Tatsache, dass man Verbindungen unterschiedlicher Chemie und Molmasse der Regel verschiedene Ionisierung Effizienzen (IE) zeigen. Direkte Analyse der de-polymerisierten Mischung durch eine Spritzenpumpe Infusion oder mit LC gekoppelt Elektrosprayionisierung-Ionenfalle-Massenspektrometrie (ESI-IT-MS) ist die Methode der Wahl für solche komplexen Mischungen. Aber DS-abhängige Unterschiede in der Chemie und Massen Ursache Diskriminierung und somit eine Verzerrung des DS-Profil für einen bestimmten DP, die nicht aufgrund des Fehlens von Standardverbindungen korrigiert werden. IE hängt von Eigenschaften Chemie des Analyten, z.B. Ionen-Komplexierung Fähigkeit, Polarität, Solvatationsenergie, Oberflächenaktivität, Molekulargewicht, usw., und auch auf den instrumentellen Parameter. Daher untersuchten wir den Einfluß von verschiedenen Parametern auf die relative Ionenintensitäten in ESI-IT-MS, die Prinzipien zu verstehen und zu prüfen, ob sie gewisse Trends folgen. Binäre und komplexe Mischungen von O-alkylierte Maltooligosaccharide definierter Zusammensetzung wurden hergestellt, die in der Chemie unterschied, Größe, Masse (DP) usw. und unter definierten Bedingungen MS analysiert

Network Intrusion Detection Method Using Stacked BILSTM Elastic Regression Classifier with Aquila Optimizer Algorithm for Internet of Things (IoT)

Globally, over the past ten years, computer networks and Internet of Things (IoT) networks have grown significantly due to the increasing amount of data that has been collected, ranging from zettabytes to petabytes. As a result, as the network has expanded, security problems have also emerged. The large data sets involved in these types of attacks can make detection difficult. The developing networks are being used for a multitude of sophisticated purposes, such as smart homes, cities, grids, gadgets, and objects, as well as e-commerce, e-banking, and e-government. As a result of the development of numerous intrusion detection systems (IDS), computer networks are now protected from security and privacy threats. Data confidentiality, integrity, and availability will suffer if IDS prevention efforts fail. Complex attacks can't be handled by traditional methods.  There has been a growing interest in advanced deep learning techniques for detecting intrusions and identifying abnormal behavior in networks. This research aims to propose a novel network namely stacked BiLSTM elastic regression classifier (Stack_BiLSTM-ERC) with Aquila optimizer algorithm for feature selection. This optimization method computes use of a cutting-edge transition function that enables it to be transformed into a binary form of the Aquila optimizer. A better solution could be secured once number of possible solutions are found from diverse regions of the search space utilizing the Aquila optimizer method. NSL-KDD and UNSW-NB15 are two datasets that enable learning characteristics from the raw data in order to detect harmful prerequisites characteristics and effective framework patterns. The proposed Stack_BiLSTM-ERC achieves 98.l3% of accuracy, 95.1% of precision, 94.3% of recall and 95.4 of F1-score for NSL-KDD dataset. Moreover, 98.6% of accuracy, 97.2% of precision, 98.5 of recall and 97.5% of F1-score