Miracle-dz/UniFAR-FTUs huggingface dataset:
Advanced Network Inference Techniques Based on Network Protocol Stack Information Leaks

Side channels are channels of implicit information flow that can be used to find out information that is not allowed to flow through explicit channels. This thesis focuses on network side channels, where information flow occurs in the TCP/IP network stack implementations of operating systems. I will describe three new types of idle scans: a SYN backlog idle scan, a RST rate-limit idle scan, and a hybrid idle scan. Idle scans are special types of side channels that are designed to help someone performing a network measurement (typically an attacker or a researcher) to infer something about the network that they are not otherwise able to see from their vantage point. The thesis that this dissertation tests is this: because modern network stacks have shared resources, there is a wealth of information that can be inferred off-path by both attackers and Internet measurement researchers. With respect to attackers, no matter how carefully the security model is designed, the non-interference property
Homisland-IO: Homogeneous Land Use/Land Cover over the Small Islands of the Indian Ocean

Many small islands are located in the southwestern Indian Ocean. These islands have their own environmental specificities and very fragmented landscapes. Generic land use products developed from low and medium resolution satellite images are not suitable for studying these small territories. This is why we have developed a land use/land cover product, called Homisland-IO, based on remote sensing processing on high spatial resolution satellite images acquired by SPOT 5 satellite between December 2012 and July 2014. This product has been produced using an object-based classification process. The overall accuracy of the product is 86%. Homisland-IO is freely accessible through a web portal and is thus available for future use.
An Empirical Examination of Success Model SAS Application on Teritory of Bengkulu Treasury Office

This study examines determinants of successful of SAS application by reviewing user perception that adapted successful model of information system developed by DeLone and McLean (1992), which system quality, information quality, system use, user satisfaction, and individual impact. Primary data is obtained by questionaries filled by 100 respondents from units in the teritory of of treasury office of Bengkulu. Data analyzed by using Partial Least Square (PLS) as one of the alternative methods of Structural Equation Modeling (SEM). The results show that quality of the system and quality of information affects user satisfaction but did not affect use of the system. Use of the system affected satisfaction of user and level satisfaction of user would affect the use of the system. User satisfaction affects the impact of the individual.Keywords: Individual Impact, Information Quality, Information Systems Success, System Quality, System Use, User Satisfaction
Background noise suppression for speech enhancement and coding

A background noise suppression system developed by Motorola is included as a feature in IS-127, the TIA/EIA standard for the enhanced variable rate codec (EVRC) to be used in CDMA based telephone systems. We describe the algorithm used in this system and its implementation. We then present subjective listening test results showing the advantages of using such a system as a prefilter to a speech coder.
Power and bandwidth optimization for personal communications mobility tracking

Mobile users maintaining communication with a wireline network via wireless links form the basis for personal communications. The wireline network tracks the current location of each user at a coarse level when the user is inactive, and refines this knowledge by paging when the user is called. Conventionally, this task of mobility tracking is achieved as follows. The geographical area of interest is divided into registration areas which consist of a large number of cells, where the cell is the coverage area of an individual radio port. Databases in the network keep track of which registration area the user is in. The user monitors beacons broadcast by the radio ports to detect a change in registration area, and notifies the network of such a change when it happens. When the user is called, all cells in that registration area are paged using wireless broadcast. Paging all cells in a registration area for each call (a call may refer to either voice or data communication) may be wasteful of downlink bandwidth if the user does not move much between calls. This may be particularly important if calls are actually bursts of data to a relatively immobile, though portable, computer. On the other hand, keeping closer track of a user's location involves additional expenditure of portable power and uplink bandwidth for the user to announce his or her location more frequently to the network. In the paper, the author provides a mathematical formulation for this tradeoff. <<ETX>>
Analysis and simulation results of multihop handoff scheme in an ad hoc wireless network

We analyzed the handoff performance of a multihop-based wireless LAN that uses access points (APs) for communication. When a mobile terminal is not able to communicate with any APs, it uses other mobile terminals as terminal repeaters (TRs). The handoff criteria are based on absolute and relative signal strengths. The performance criteria are the average number of handoffs and the average handoff delay. We investigate the relation between the handoff criteria and the performance criteria when both the mobile terminal and the terminal repeaters are moving. Numerical results are presented to show that the average handoff delay decreases but the average number of handoffs increases as the speed of the TRs is increased.
3D ESTIMATION OF SLOW GROUND MOTION USING INSAR AND THE SLOPE ASPECT ASSUMPTION, A CASE STUDY: THE PUNCAK PASS LANDSLIDE, INDONESIA

Abstract. The Indonesian Centre of Volcanology and Geological Hazard Mitigation classified the Ciloto district as one of the most landslide prone areas in Indonesia. Some evidence of ground movement and the landslide failures occurred in recent years. Thus, continuous monitoring is necessary for supporting the precautions of an upcoming landslide. This study applies Small Baselines - Slowly Decorrelated Phase Filter (SDPF) for InSAR processing both for the ascending and the descending data. The primary objective is to generate horizontal and vertical components of InSAR results from two different tracks and slope aspect information in order to retrieve a projection to the northward direction. We used the available Sentinel-1 SAR data from 2014 until 2018. Combination of two orbits is approached by the surface and the nearest-neighbor gridding method. The 3D components were examined at the Puncak Pass, Ciloto, an active landslide area. For the case study area, it appeared that soil materials transferred slowly from the top of main body landslide to the accumulated zone near to the buildings owned by a local resort. The cumulative 3D displacements for three years were computed for the depleted zone: it moved −47, 23, −10 mm for dU, dE and dN, respectively. Meanwhile, the accumulated zone was considered having the up-lift motion to maximum 43, −13, 7 mm, respectively.
Predictive Sliding Mode Control Based on Laguerre Functions

This paper deals with Predictive Sliding Mode Control (PSMC) that uses Laguerre functions in the design of a control input signal. Two types of PSMC algorithms are considered: one originating from the digital equivalent control method approach, and another containing an additional sliding mode control component that provides the robustness and determines the system dynamics in reaching mode. A one-step-delayed disturbance estimator is introduced to account for system nonlinearities and unknown disturbances, as well as to ensure better system steady-state accuracy. The proposed algorithms are demonstrated by conducting several real-time experiments on a modular DC servo system. Robustness of the closed loop, affected by tuning parameter values, is demonstrated as well.
EFFECT OF INNOVATION ON THE PERFORMANCE OF SMALL AND MEDIUM ENTERPRISES IN KENYA

Purpose: The focus of the research was to measure the entrepreneurs’ innovation and how this attribute contribute to the performance of an SME. Methodology: The study adopted survey research design focusing on a population of 268,100 licensed small and medium enterprises in Nairobi County in Kenya, from which a sample of 400 firms were selected through a multi-stage probability sampling method where stratified sampling method was used first and then simple random sampling from the strata for the 17 constituencies under the Nairobi county. Quantitative data was collected using questionnaires and analyzed using Statistical Package for Social Science (SPSS) and Microsoft Excel. The study tested the research hypothesis on whether innovation had a significant effect on performance of small and medium size enterprises in Kenya. Results : The regression results established that innovation had positive and significant effect of performance of small and medium size enterprises in Kenya. Based on these findings a unit increase in innovations would results to increase in performance of small and medium size enterprises in Kenya. The study also concluded that adoption of latest innovations in product production, process improvement and marketing process differentiated high performing and sustainable SMEs from the rest. Unique contribution to theory, practice and policy: The study recommends that SMEs managers and owners should invest more in e-commerce which include buying or selling through the Internet to reduce the transactions cost and cost associated with keeping inventory.
A SEMANTIC CENTRALITY MEASURE FOR FINDING THE MOST TRUSTWORTHY ACCOUNT

We propose an algorithmic approach for ranking of differing textual descriptions (accounts) of the same event or story according to their likeliness to best describe the source. Application domains include the ranking of eyewitness reports, historical accounts, and news reports. For this, we developed the concept of „semantic centrality“ as a measure of how central a text is among a collection of texts, in terms of semantic overlap or similarity. This measure is based on natural language processing theory, as well as graph theory. Using three different collections of humanly generated texts (gathered through a recall task, „Chinese Whispers“ task, and real-world news reports), we evaluated the proposed method for ranking textual accounts by their trustworthiness to describe source events. In one experiment algorithmic ranking is compared to human ranking. Results indicate that semantic centrality as a measure for trustworthiness of textual accounts is promising and deserves further research attention.
Performance and memory space optimizations for embedded systems

Embedded systems have three common principles: real-time performance, low power consumption, and low price (limited hardware). Embedded computers use chip multiprocessors (CMPs) to meet these expectations. However, one of the major problems is lack of efficient software support for CMPs; in particular, automated code parallelizers are needed. The aim of this study is to explore various ways to increase performance, as well as reducing resource usage and energy consumption for embedded systems. We use code restructuring, loop scheduling, data transformation, code and data placement, and scratch-pad memory (SPM) management as our tools in different embedded system scenarios. The majority of our work is focused on loop scheduling. Main contributions of our work are: We propose a memory saving strategy that exploits the value locality in array data by storing arrays in a compressed form. Based on the compressed forms of the input arrays, our approach automatically determines the compressed forms of the output arrays and also automatically restructures the code. We propose and evaluate a compiler-directed code scheduling scheme, which considers both parallelism and data locality. It analyzes the code using a locality-parallelism graph representation, and assigns the nodes of this graph to processors. We also introduce an Integer Linear Programming based formulation of the scheduling problem. We propose a compiler-based SPM conscious loop scheduling strategy for array/loop based embedded applications. The method is to distribute loop iterations across parallel processors in an SPM-conscious manner. The compiler identifies potential SPM hits and misses, and distributes loop iterations such that the processors have close execution times. We present an SPM management technique using Markov chain based data access prediction for irregular accesses. We propose a compiler directed integrated code and data placement scheme for 2-D mesh based CMP architectures. Using a Code-Data Affinity Graph (CDAG) to represent the relationship between loop iterations and array data, it assigns the sets of loop iterations to processing cores and sets of data blocks to on-chip memories. We present a memory bank aware dynamic loop scheduling scheme for array-intensive applications. The goal is to minimize the number of memory banks needed for executing the group of loop iterations.
Facial Feature Extraction Based On FPD andGLCM Algorithms

Image mining is defined as the discovery of image patterns in a given collection of images. It is an effort that fundamentally draws upon knowledge in computer vision, image processing, data mining, machine learning, database, and artificial intelligence. Facial recognition helps to analyze and compare the patterns from the facial images. Facial feature extraction is an automatic recognition of human faces by detecting its features i.e. eyes, eyebrows and lips. In this research work, features are extracted from the human facial images by using the existing Face Part Detection (FPD) algorithm and the newly proposed Gray Level Co-occurrence Matrix (GLCM) algorithm. FPD uses bounding box method and GLCM uses affine moment invariants method. Performance factors applied here are feature extraction accuracy and execution time. The implementation of this work is performed in MATLAB 7.0. Based on the experimental results, it is observed that the proposed GLCM algorithm extracted the features more accurately with minimum execution time than FPD algorithm.
Automatically enriching knowledge bases using Wikipedia PhD Transfer Report

This document describes my PhD proposal. There are two main objectives which I hope to achieve with my thesis. The first is to develop novel methods for extracting information from the online encyclopedia Wikipedia in order to enrich knowledge bases. Previous work has successfully developed an ontology which combined the category structure of Wikipedia with the WordNet synset hierarchy (Suchanek et al., 2007). The aim in this thesis is to build on this ontology by extracting information from the articles using relation extraction methods based on the methods developed in Snow et al. (2005), which extracted hyponyms using a classifier on dependency parsed text. The second objective is to evaluate the effectiveness of these knowledge bases for language processing applications, specifically question answering. Question answering systems typically comprise at least two components: one which retrieves relevant documents, and another which extracts answers from these documents. Previous work has shown that enriched versions of WordNet have been useful in both these tasks (Moldovan and Novischi, 2002), by expanding queries for information retrieval, and by providing related words when searching for answers. This thesis aims to evaluate knowledge bases for both these tasks to see if richer knowledge bases can improve performance as hoped.
The Impact of Anti-Money Laundering Oversight on Banks' Suspicious Transaction Reporting: Evidence from Italy

We provide the first thorough investigation of the effect of anti-money laundering inspections on banks' reporting of suspicious transactions. We do so by using highly detailed data from Bank of Italy and UIF (Italian authority for anti-money laundering), which include information on i) on-site inspections by authorities and follow-up actions, and ii) quantity and quality of suspicious transactions reports being filed by banks before and after inspections. Through a difference-in-differences econometric analysis we find that inspections (notably when followed by some type of intervention by the authority) induce, ceteris paribus, an increase in suspicious transaction reports being filed by banks. Crucially, the effect is not limited to low-quality reports, as feared in the literature ('crying wolf' effect) but is spread to high-quality reports. Authorities' oversight is thus shown to increase the quantity of information shared by banks without deteriorating its quality.
Discovering pattern using automata

DISCOVERING PATTERN USING AUTOMATA by Ahmad M. Yazdankhah Most documents written by humans are not just a collection of words, sentences and paragraphs combined at random. It is believed that there is a pattern hidden behind those piles of characters that represents the author's style of writing. In the previous works and in this thesis, we assumed that the aforementioned belief was a true statement and tried to discover and represent the pattern by automata machines. We used the Alergia algorithm to form an automaton from a prefix-tree-accepter. By testing, we verified that the Alergia algorithm was correctly implemented in our software. Our tests showed that we captured only the patterns of the collections of single sentences in a book. Unfortunately, that is not the full content of a book. Therefore, establishing variable chopping units or a less forceful chopping approach would be a promising approach that is beyond the scope of this master thesis.
Practical fast 1-D DCT algorithms with 11 multiplications

A class of practical fast algorithms is introduced for the discrete cosine transform (DCT). For an 8-point DCT only 11 multiplications and 29 additions are required. A systematic approach is presented for generating the different members in this class, all having the same minimum arithmetic complexity. The structure of many of the published algorithms can be found in members of this class. An extension of the algorithm to longer transformations is presented. The resulting 16-point DCT requires only 31 multiplications and 81 additions, which is, to the authors' knowledge, less than required by previously published algorithms. <<ETX>>
Modeling of ultra‐wideband indoor channels with the modified leapfrog ADI‐FDTD method

Full‐wave time‐domain electromagnetic methods are usually effective in rigorously modeling and evaluating ultra‐wideband (UWB) wireless channels. However, their computational expenditures are expensive, when they are used to deal with electrically large‐size problems consisting of fine structures. In order to reduce computational time, the unconditionally stable leapfrog alternating‐direction implicit finite‐difference time‐domain (leapfrog ADI‐FDTD) method has been proposed recently. In this paper, the leapfrog ADI‐FDTD algorithm is developed for simulating lossy objects, such as office walls, floors, and ceilings, for UWB communication channel characterization. It leads to effective UWB channel characterization with power‐decay time constant, path loss exponent, and probability distribution of power gain. In comparison with the conventional FDTD, the proposed method can achieve 60% saving in computational time while retaining good accuracy. Copyright © 2014 John Wiley & Sons, Ltd.
Integration Of Laser Rangefinder And Multispectral Video Data For Forest Measurements

Attempts to improve the accuracy and timeliness of forest measurements have led to the applica­ tion of new sensor technologies which collect high resolution digital data sets from an airborne configuration. Two devices which have shown particular promise are the laser rangefinder and the multispectral video camera. These instruments are capable of measuring a number of primary forest Parameters, including tree height, accurately and economically. Used in an integrated sensor package, they can generate three dimensional views of the forest body and underlying terrain; however, the data sets collected are large, with a high level of complexity. The objective of the work described herein was to develop a system for extracting forest information from simultaneously acquired coinci­ dent laser and video data. Test data sets were acquired over an area in west central Alberta and consisted of multiple low level flight lines over a variety of forest cover types. An integrated sensor package was used, consisting of a high frequency laser rangefinder and a six band multispectral video ,camera. Extensive ground data were compiled and supplemented with historical data from permanent sample plots maintained by the Alberta Forest Service. This information was used to develop and test a system for filtering and correlating the remote­ ly sensed data in a semi-automatic manner. Analysis of the information derived showed a high degree of accuracy in the measurement of tree heights and stand densities, while species, crown diameters, and vigor could be estimated. Current research is aimed at the generalization of the software system to provide support for a wide variety of forest cover types as well as a direct and logical interface to forestry GIS systems.