Lessons learned from the Bosnian Conflict

Utilizing the propositional inventory method, this thesis compares the propositions of various U.S. Government agencies, under the Clinton Administration, and the propositions of Richard Holbrooke, chief negotiator and architect of the Dayton Accords, regarding the Bosnian conflict. Recently, the CIA and the Clinton Presidential Library declassified numerous documents from various government agencies concerning the Balkan Crisis and this thesis focuses its scope on the Bosnian conflict that took place in the time period from 1992 through the Dayton Accords in 1995. By analyzing the differing propositions in contrast to the historical events, it was possible to assess the accuracy of each account. This assessment found that Richard Holbrooke had a higher accuracy rate than did most of the U.S Government agencies regarding the Bosnian conflict

Modelling corporate tax liabilities using company accounts: a new framework

This paper presents a micro-econometric approach to corporate tax modelling. Using firm level panel data of UK companies in three diverse sectors, the paper examines the impact of different variables on corporate tax liabilities of the firms. Many strong results stand out which suggest that firms reduce their tax liabilities through different channels and tax sheltering activities to maximise �after-tax� profits. The evidence shows, inter alia, that not only are trading profits and capital gains important determinants of corporation tax payments but so also are their components, such as gross profit, cost of sales, expenses, and even one-off �exceptional items� and �extraordinary items�. The results also indicate that firms� size, organisational structure, investments, and financial and dividend policies are important factors impacting on corporate tax liabilities. Moreover, different tax reliefs and allowances are strongly associated with corporation tax payments asymmetrically. The findings have implications for microsimulation modelling, financial transparency, and corporate governance

Multi-Hop Wireless Sensor Network for Continuous Oxygen Tank’s Level Detection

Wireless sensor network technology is considered as one of the modern technologies that are used in a lot of areas to measure physical, chemical or environmental variables because of their low of cost and high efficiency in data transmission. This project aims to design a wireless sensor network that will be used to measure pressure or level of Oxygen gas inside the Oxygen tanks that are found in different places in hospitals in order to overcome the problem of the manual checking of tanks level, which may cause a lot of problems because of the lack of accuracy measurement and the absence of a continuous monitoring from the control room. The designing of this project will be based on the concept of multi-hop wireless sensor network using XBee modules. XCTU software will be used to update and configure XBee modules and PROCESSING software will be used to develop a program that reads data from XBee and show it in interactive way on the screen

Phenomenology of Λb→Λcτνˉτ\Lambda_b \to \Lambda_c \tau \bar{\nu}_{\tau} using lattice QCD calculations

In a recent paper we studied the effect of new-physics operators with different Lorentz structures on the semileptonic $\Lambda_b \to \Lambda_c \tau \bar{\nu}_{\tau}$ decay. This decay is of interest in light of the $R({D^{(*)}})$ puzzle in the semileptonic $\bar{B} \to D^{(*)} \tau {\bar\nu}_\tau$ decays. In this work we add tensor operators to extend our previous results and consider both model-independent new physics (NP) and specific classes of models proposed to address the $R({D^{(*)}})$ puzzle. We show that a measurement of $R(\Lambda_c) = {\cal B}[\Lambda_b \to \Lambda_c \tau \bar{\nu}_{\tau}] / {\cal B}[\Lambda_b \to \Lambda_c \ell \bar{\nu}_{\ell}]$ can strongly constrain the NP parameters of models discussed for the $R({D^{(*)}})$ puzzle. We use form factors from lattice QCD to calculate all $\Lambda_b \to \Lambda_c \tau \bar{\nu}_{\tau}$ observables. The $\Lambda_b \to \Lambda_c$ tensor form factors had not previously been determined in lattice QCD, and we present new lattice results for these form factors here.Comment: 44 pages, 105 figure

Intelligent intrusion detection in low power IoTs

Security and privacy of data are one of the prime concerns in today’s Internet of Things (IoT). Conventional security techniques like signature-based detection of malware and regular updates of a signature database are not feasible solutions as they cannot secure such systems effectively, having limited resources. Programming languages permitting immediate memory accesses through pointers often result in applications having memory-related errors, which may lead to unpredictable failures and security vulnerabilities. Furthermore, energy efficient IoT devices running on batteries cannot afford the implementation of cryptography algorithms as such techniques have significant impact on the system power consumption. Therefore, in order to operate IoT in a secure manner, the system must be able to detect and prevent any kind of intrusions before the network (i.e., sensor nodes and base station) is destabilised by the attackers. In this article, we have presented an intrusion detection and prevention mechanism by implementing an intelligent security architecture using random neural networks (RNNs). The application’s source code is also instrumented at compile time in order to detect out-of-bound memory accesses. It is based on creating tags, to be coupled with each memory allocation and then placing additional tag checking instructions for each access made to the memory. To validate the feasibility of the proposed security solution, it is implemented for an existing IoT system and its functionality is practically demonstrated by successfully detecting the presence of any suspicious sensor node within the system operating range and anomalous activity in the base station with an accuracy of 97.23%. Overall, the proposed security solution has presented a minimal performance overhead.</jats:p