Miracle-dz/UniFAR-FTUs huggingface dataset:
PERSONALITY ATTRIBUTES AS INFLUENCERS OF MICRO-ENTERPRISE GROWTH AT KAMUKUNJI IN NAIROBI, KENYA

ABSTRACT Several studies indicate significant relationship between personality attributes and microenterprise growth. A correlational survey on 354 micro-enterprises manufacturing metallic products at Kamukunji stipulate positive and negative influences between personality attributes and vertical plus horizontal growth in employees, sales, departments and divisions. Data collection using structured questionnaire administered face to face signifies that desire to be boss and desire to succeed propels growth. Personality attributes model (60.85% variance explained), Kaiser-Meyer-Olkin (KMO = .82) measure of sampling adequacy, and Bartlett’s test of sphericity (.001) remain statistically significant. The 13 hypotheses designate 61.54% acceptance and provides the relationship between personality attributes and micro-enterprise growth. The study implies that there exists a positive relationship between personality attributes of an entrepreneur and growth of microenterprises.
Bias compensation for the bearings-only pseudolinear target track estimator

The bearings-only pseudolinear target track estimator is known to suffer from severe bias problems. This paper presents a bias analysis for the pseudolinear estimator and develops a method of bias compensation, resulting in a closed-form reduced-bias pseudolinear estimator. The reduced-bias estimator is then incorporated into an instrumental variable estimator to produce asymptotically unbiased target motion parameter estimates. Unlike batch iterative estimators, the proposed instrumental variable estimator has a closed-from solution and therefore avoids the convergence problems associated with iterative estimators. The performance of the proposed instrumental variable estimator is illustrated by way of simulation examples and is shown to be almost identical to that of the computationally more demanding iterative maximum likelihood estimator.
Interleukin 12 inhibits antigen-induced airway hyperresponsiveness, inflammation, and Th2 cytokine expression in mice

Allergic asthma is characterized by airway hyperresponsiveness and pulmonary eosinophilia, and may be mediated by T helper (Th) lymphocytes expressing a Th2 cytokine pattern. Interleukin (IL) 12 suppresses the expression of Th2 cytokines and their associated responses, including eosinophilia, serum immunoglobulin E, and mucosal mastocytosis. We have previously shown in a murine model that antigen- induced increases in airway hyperresponsiveness and pulmonary eosinophilia are CD4+ T cell dependent. We used this model to determine the ability of IL-12 to prevent antigen-induced increases in airway hyperresponsiveness, bronchoalveolar lavage (BAL) eosinophils, and lung Th2 cytokine expression. Sensitized A/J mice developed airway hyperresponsiveness and increased numbers of BAL eosinophils and other inflammatory cells after single or repeated intratracheal challenges with sheep red blood cell antigen. Pulmonary mRNA and protein levels of the Th2 cytokines IL-4 and IL-5 were increased after antigen challenge. Administration of IL-12 (1 microgram/d x 5 d) at the time of a single antigen challenge abolished the airway hyperresponsiveness and pulmonary eosinophilia and promoted an increase in interferon (IFN) gamma and decreases in IL-4 and IL-5 expression. The effects of IL-12 were partially dependent on IFN-gamma, because concurrent treatment with IL-12 and anti-IFN-gamma monoclonal antibody partially reversed the inhibition of airway hyperresponsiveness and eosinophilia by IL-12. Treatment of mice with IL-12 at the time of a second antigen challenge also prevented airway hyperresponsiveness and significantly reduced numbers of BAL inflammatory cells, reflecting the ability of IL-12 to inhibit responses associated with ongoing antigen-induced pulmonary inflammation. These data show that antigen-induced airway hyperresponsiveness and inflammation can be blocked by IL-12, which suppresses Th2 cytokine expression. Local administration of IL-12 may provide a novel immunotherapy for the treatment of pulmonary allergic disorders such as atopic asthma.
Preserving Anonymity of Recurrent Location-Based Queries

The anonymization of location based queries through the generalization of spatio-temporal information has been proposed as a privacy preserving technique. We show that the presence of multiple concurrent requests, the repetition of similar requests by the same issuers, and the distribution of different service parameters in the requests can significantly affect the level of privacy obtained by current anonymity-based techniques. We provide a formal model of the privacy threat, and we propose an incremental defense technique based on a combination of anonymity and obfuscation. We show the effectiveness of this technique by means of an extensive experimental evaluation.
Designing and Implementing Malicious Hardware

Hidden malicious circuits provide an attacker with a stealthy attack vector. As they occupy a layer below the entire software stack, malicious circuits can bypass traditional defensive techniques. Yet current work on trojan circuits considers only simple attacks against the hard-ware itself, and straightforward defenses. More complex designs that attack the software are unexplored, as are the countermeasures an attacker may take to bypass proposed defenses. We present the design and implementation of Illinois Malicious Processors (IMPs). There is a substantial design space in malicious circuitry; we show that an attacker, rather than designing one specific attack, can instead design hardware to support attacks. Such flexible hardware allows powerful, general purpose attacks, while remaining surprisingly low in the amount of additional hardware. We show two such hardware designs, and implement them in a real system. Further, we show three powerful attacks using this hardware, including a login backdoor that gives an attacker complete and high-level access to the machine. This login attack requires only 1341 additional gates: gates that can be used for other attacks as well. Malicious processors are more practical, more flexible, and harder to detect than an initial analysis would suggest.
An improved Kalman Smoother for atmospheric inversions

Abstract. We explore the use of a fixed-lag Kalman smoother for sequential estimation of atmospheric carbon dioxide fluxes. This technique takes advantage of the fact that most of the information about the spatial distribution of sources and sinks is observable within a few months to half of a year of emission. After this period, the spatial structure of sources is diluted by transport and cannot significantly constrain flux estimates. We therefore describe an estimation technique that steps through the observations sequentially, using only the subset of observations and modeled transport fields that most strongly constrain the fluxes at a particular time step. Estimates of each set of fluxes are sequentially updated multiple times, using measurements taken at different times, and the estimates and their uncertainties are shown to quickly converge. Final flux estimates are incorporated into the background state of CO2 and transported forward in time, and the final flux uncertainties and covariances are taken into account when estimating the covariances of the fluxes still being estimated. The computational demands of this technique are greatly reduced in comparison to the standard Bayesian synthesis technique where all observations are used at once with transport fields spanning the entire period of the observations. It therefore becomes possible to solve larger inverse problems with more observations and for fluxes discretized at finer spatial scales. We also discuss the differences between running the inversion simultaneously with the transport model and running it entirely off-line with pre-calculated transport fields. We find that the latter can be done with minimal error if time series of transport fields of adequate length are pre-calculated.
On the Tradeoff Between Multiuser Diversity and Training Overhead in Multiple Access Channels

We consider a single antenna narrowband multiple access channel in which users send training sequences to the base station and scheduling is performed based on minimum mean square error (MMSE) channel estimates. In such a system, there is an inherent tradeoff between training overhead and the amount of multiuser diversity achieved. We analyze a block fading channel with independent Rayleigh distributed channel gains, where the parameters to be optimized are the number of users considered for transmission in each block and the corresponding time and power spent on training by each user. We derive closed form expressions for the optimal parameters in terms K and L, where K is the number of users considered for transmission in each block and L is the block length in symbols. Considering the behavior of the system as L grows large, we optimize K with respect to an approximate expression for the achievable rate, and obtain second order expressions for the resulting parameters in terms of L.
An Efficient Blind Detection Algorithm of Median Filtered Image

Due to the significant advances of digital photography and the availability of many powerful photo editing tools, it becomes easier to create forgery images by non-professional users. Median filtering that is usually applied to erase the forensically significant fingerprints has recently received increased attention. In this paper, we present an effective blind forensic algorithm to detect the median filtering manipulation. First, the median filtered residual (MFR) is generated by computing the difference between a testing image and a median filtered version of itself. Then, three feature sets including histogram, autocorrelation and gradient are extracted from the median filter residual. Last, those features are fetched into support vector machine (SVM) for training and classification. Our experimental results demonstrate that our proposed forensic method achieves not only better detection rate but also lower computational complexity compared with other existing median filtering detection methods. Our proposed forensic method also can locate local median filtering of image effectively.
Shoot4U: Using VMM Assists to Optimize TLB Operations on Preempted vCPUs

Virtual Machine based approaches to workload consolidation, as seen in IaaS cloud as well as datacenter platforms, have long had to contend with performance degradation caused by synchronization primitives inside the guest environments. These primitives can be affected by virtual CPU preemptions by the host scheduler that can introduce delays that are orders of magnitude longer than those primitives were designed for. While a significant amount of work has focused on the behavior of spinlock primitives as a source of these performance issues, spinlocks do not represent the entirety of synchronization mechanisms that are susceptible to scheduling issues when running in a virtualized environment. In this paper we address the virtualized performance issues introduced by TLB shootdown operations. Our profiling study, based on the PARSEC benchmark suite, has shown that up to 64% of a VM's CPU time can be spent on TLB shootdown operations under certain workloads. In order to address this problem, we present a paravirtual TLB shootdown scheme named Shoot4U. Shoot4U completely eliminates TLB shootdown preemptions by invalidating guest TLB entries from the VMM and allowing guest TLB shootdown operations to complete without waiting for remote virtual CPUs to be scheduled. Our performance evaluation using the PARSEC benchmark suite demonstrates that Shoot4U can reduce benchmark runtime by up to 85% compared an unmodified Linux kernel, and up to 44% over a state-of-the-art paravirtual TLB shootdown scheme.
Th World Congresses of Structural and Multidisciplinary Optimization Conceptions for Mdo in Structural Design of Buildings

1. Abstract In order to apply structural optimization to load-bearing structures in building design various adaptations are required to develop a comprehensive model for all relevant aspects. We aim to transfer the method of Multidisciplinary Design Optimization (MDO) used in aerospace technologies to building design. MDO seems to be auspiciously for the implementation of optimization in this new field. First, the objectives in building design will be discussed with a special focus on the non-numerical aspects which are of major importance in building design in contrast to other engineering disciplines. As decomposition is able to bring non-numerical information into the optimization process, the second part deals with the decomposition of load-bearing structures for building design and proposes an approach where components for decomposition are derived from their function in the structure. In the third and last part, a hall based on a frame structure is decomposed and an optimization is applied in order to demonstrate the process. This prototype considers the amount of material, the surface of the construction, and the number of joints as objective relevant values. It serves to show the flow of data as well as the necessary analysis and available results which support decisions and the dimensioning for the load-bearing structure. 2. The mathematical and technical foundations of structural optimization are developed to a large extent. However, in the design of load-bearing structures of buildings, optimization is hardly applied. The cause is an insufficient adaptation to the needs of building design. In the aerospace technologies, a method called Multidisciplinary Design Optimization (MDO) has been developed which is capable to handle the particular challenge of optimization in design. The modular and parameterized model which constitutes a basis of MDO meets the needs of designing through its flexibility. As this method provides several tools for optimization it is necessary to set up a modular and parameterized model for load-bearing structures of buildings for applying these tools. The application of design optimization in this field has to face the strong interaction between the architectural design and the load-bearing structure of the building. As this interaction appears in the phase of conceptual design, it is required to apply optimization in this stage of planning. A later included optimization process would have either no particular effect on the design or it would cause major effort for revising the planning because the effort for redesign increases superproportional the later a change takes …
HIP 2013 FamilySearch Competition - Contribution of IRISA

In this paper, we present the method that we have proposed for ICDAR'2013 HIP Workshop FamilySearch Competition. This method is based on the study of the arrangement of local descriptors called Points of Interest (POI). The points of interest are used in this context to realize some word spotting. Then, the word spotting is exploited at two levels in the competition: the localization of regions of interest in the document and the clustering of similar text regions. Due to lack of time, we have submitted a very first version of our method, but we hope to improve it in future work.
GymSkill: A personal trainer for physical exercises

We present GymSkill, a personal trainer for ubiquitous monitoring and assessment of physical activity using standard fitness equipment. The system records and analyzes exercises using the sensors of a personal smartphone attached to the gym equipment. Novel fine-grained activity recognition techniques based on pyramidal Principal Component Breakdown Analysis (PCBA) provide a quantitative analysis of the quality of human movements. In addition to overall quality judgments, GymSkill identifies interesting portions of the recorded sensor data and provides suggestions for improving the individual performance, thereby extending existing work. The system was evaluated in a case study where 6 participants performed a variety of exercises on balance boards. GymSkill successfully assessed the quality of the exercises, in agreement with the professional judgment provided by a physician. User feedback suggests that GymSkill has the potential to serve as an effective tool for motivating and supporting lay people to overcome sedentary, unhealthy lifestyles. GymSkill is available in the Android Market as `VMI Fit'.
Generalized Points-to Graphs: A New Abstraction of Memory in the Presence of Pointers

Flow- and context-sensitive points-to analysis is difficult to scale; for top-down approaches, the problem centers on repeated analysis of the same procedure; for bottom-up approaches, the abstractions used to represent procedure summaries have not scaled while preserving precision. We propose a novel abstraction called the Generalized Points-to Graph (GPG) which views points-to relations as memory updates and generalizes them using the counts of indirection levels leaving the unknown pointees implicit. This allows us to construct GPGs as compact representations of bottom-up procedure summaries in terms of memory updates and control flow between them. Their compactness is ensured by the following optimizations: strength reduction reduces the indirection levels, redundancy elimination removes redundant memory updates and minimizes control flow (without over-approximating data dependence between memory updates), and call inlining enhances the opportunities of these optimizations. We devise novel operations and data flow analyses for these optimizations. Our quest for scalability of points-to analysis leads to the following insight: The real killer of scalability in program analysis is not the amount of data but the amount of control flow that it may be subjected to in search of precision. The effectiveness of GPGs lies in the fact that they discard as much control flow as possible without losing precision (i.e., by preserving data dependence without over-approximation). This is the reason why the GPGs are very small even for main procedures that contain the effect of the entire program. This allows our implementation to scale to 158kLoC for C programs.
MSGC Development for HERA-B

The Inner Tracker System of the HERA-B experiment at DESY consists of 184 Microstrip Gas Chambers (MSGC) with a total number of 147 456 electronic read out channels. The detectors have to cope with particle fluxes up to 25 kHz/mm**2 and to tolerate radiation doses of 1 Mrad per year. During the development of these chambers it was found that conventional MSGC, operated in intenses hadronic fluxes, are rapidly destroyed due to induced discharges. The introduction of a Gas Electron Multiplier (GEM) as pre-amplification structure offers the possibility to build robust and reliable detectors allowing for ample gain reserve in the hostile environment of HERA-B.
Macroeconometric Modelling with a Global Perspective

This paper provides a synthesis and further development of a global modelling approach introduced in Pesaran, Schuermann and Weiner (2004), where country specific models in the form of VARX* structures are estimated relating a vector of domestic variables, xit, to their foreign counterparts, x*it, and then consistently combined to form a Global VAR (GVAR). It is shown that the VARX* models can be derived as the solution to a dynamic stochastic general equilibrium (DSGE) model where over-identifying long-run theoretical relations can be tested and imposed if acceptable. This gives the system a transparent long-run theoretical structure. Similarly, short-run over-identifying theoretical restrictions can be tested and imposed if accepted. Alternatively, if one has less confidence in the short-run theory the dynamics can be left unrestricted. The assumption of the weak exogeneity of the foreign variables for the long-run parameters can be tested, where x*it variables can be interpreted as proxies for global factors. Rather than using deviations from ad hoc statistical trends, the equilibrium values of the variables reflecting the long-run theory embodied in the model can be calculated. This approach has been used in a wide variety of contexts and for a wide variety of purposes. The paper also provides some new results.
Double‐core evolution and the formation of neutron star binaries with compact companions

We present the results of a systematic exploration of an alternative evolutionary scenario to form double neutron star (DNS) binaries, first proposed by Brown (1995), which does not involve a neutron star passing through a common envelope. In this scenario, the initial binary components have very similar masses, and both components have left the main sequence before they evolve into contact; preferably the primary has already developed a CO core. We have performed population synthesis simulations to study the formation of DNS binaries via this channel and to predict the orbital properties and system velocities of such systems. We obtain a merger rate for DNSs in this channel in the range of 0.1-12 Myr -1 . These rates are still subject to substantial uncertainties such as the modelling of the contact phase.
Monte-Carlo Go Reinforcement Learning Experiments

This paper describes experiments using reinforcement learning techniques to compute pattern urgencies used during simulations performed in a Monte-Carlo Go architecture. Currently, Monte-Carlo is a popular technique for computer Go. In a previous study, Monte-Carlo was associated with domain-dependent knowledge in the Go-playing program Indigo. In 2003, a 3times3 pattern database was built manually. This paper explores the possibility of using reinforcement learning to automatically tune the 3times3 pattern urgencies. On 9times9 boards, within the Monte-Carlo architecture of Indigo, the result obtained by our automatic learning experiments is better than the manual method by a 3-point margin on average, which is satisfactory. Although the current results are promising on 19times19 boards, obtaining strictly positive results with such a large size remains to be done
Equivalent Elmore delay for RLC trees

Closed form solutions for the 50% delay, rise time, overshoots, and settling time of signals in an RLC tree are presented, These solutions have the same accuracy characteristics as the Elmore delay model for RC trees and preserves the simplicity and recursive characteristics of the Elmore delay. The solutions introduced here consider all damping conditions of an RLC circuit including the underdamped response, which is not considered by the classical Elmore delay model due to the non-monotone nature of the response. Also, the solutions have significantly improved accuracy as compared to the Elmore delay for an overdamped response. The solutions introduced here for RLC trees can be practically used for the same purposes that the Elmore delay is used for RC trees.