Miracle-dz/UniFAR-FTUs huggingface dataset:
Secure Logging for Irrefutable Administration

This paper presents a method that allows for securely saving a temporal sequence of data (log lines) in a ﬁle. Log lines are signed by an authority, and are thus unalterable without detection. Data is also encrypted in the ﬁle, and may be accessed with the granularity of a single log line with the possession of a decryption key. Also, it is possible that for some lines data must be accessed by a group of cooperating users.
Major depression in 6050 former drinkers: association with past alcohol dependence.

BACKGROUND The association between alcoholism and major depression in the general population has been explained as misdiagnosed alcohol intoxication and withdrawal effects mistaken for depressive syndromes. To investigate whether this could account for the entire relationship, the association of past alcohol dependence with current major depression (ie, nonoverlapping time frames) was investigated in individuals who no longer drink or who drink very little. We conducted the study using data from the National Longitudinal Alcohol Epidemiologic Survey, a representative sample. METHODS Former drinkers who did not use drugs or smoke in the past year (n = 6050) were divided into those with and without past DSM-IV alcohol dependence. These 2 groups were compared for the presence of current (last 12 months) DSM-IV major depression. The association between prior alcohol dependence and current major depression was tested with linear logistic regression, controlling for other variables. RESULTS Prior alcohol dependence increased the risk of current major depressive disorder more than 4-fold. This relationship was not attenuated by control variables. The majority of subjects with major depression last used substances 2 or more years prior to the interview, which eliminates acute intoxication or withdrawal effects as an explanation of their depressions. CONCLUSIONS The strong, specific association between prior alcohol dependence and current or recent major depression in a nationally representative sample of former drinkers indicates that the association is not entirely an artifact of misdiagnosed intoxication and withdrawal effects. A better understanding of the nature of the relationship between the 2 disorders should be sought and will have important public health significance.
An Experimental Performance Comparison of NoSQL and RDBMS Data Storage Systems in the ERP System

Odoo is an open source, Enterprise Resource Planning (ERP) system. During the lifetime of a running Odoo system, its performance is decreasing due to the growing amount of data. Mail messages and attachments modules are special modules in Odoo. These two modules are used by almost all other Odoo modules. Accordingly, their stored data is getting larger faster than other modules. This problem reduces Odoo performance. In this thesis, we try to improve the latency of Odoo system which is caused by mail messages and attachments modules. In the last decade, new data storage systems have been developed, so-called Not Only SQL or Non SQL (NoSQL) systems. NoSQL systems have been developed to solve Relational Database Management Systems (RDBMSs) scalability problems and to be more efficient systems for managing the big data. To solve Odoo latency problem, we suggest to store the data of mail messages and attachments modules in NoSQL data storage, and modify Odoo to communicate with this new data storage system. After we customized Odoo, we made an experiment to compare the performance between regular Odoo system and our modified Odoo system. The results of this experiment indicate that, for small and medium size companies, Odoo performs better without using NoSQL system. If the amount of data of the mail messages and the attachments module is huge, our modified version of Odoo is faster.
Temporal Bacteriostatic Effect and Growth Factor Loss in Equine Platelet Components and Plasma Cultured with Methicillin-Sensitive and Methicillin-Resistant Staphylococcus aureus: A Comparative In Vitro Study

The aims were (1) to evaluate the bacteriostatic effect of platelet-rich plasma (PRP), platelet-rich gel (PRG), leukocyte-poor plasma (LPP), leukocyte-poor gel (LPG), plasma, and heat-inactivated plasma (IP) on both methicillin-sensitive Staphylococcus aureus (MSSA) and methicillin-resistant Staphylococcus aureus (MRSA) over a period of 24 h; (2) to determine and to compare the concentrations and degradation over time of platelet factor 4 (PF-4), transforming growth factor beta 1 (TGF-β 1), and platelet-derived growth factor isoform BB (PDGF-BB); and (3) to identify any correlations between MSSA and MRSA growth and either the cellular, PF-4, TGF-β 1, or PDGF-BB concentrations in the blood components. PRP and its byproducts from 18 horses were obtained by the tube method. All blood components were cultured with either MSSA or MRSA. Bacterial growth, PF-4, TGF-β 1, and PDGF-BB were determined at 6 h and 24 h. At six hours, bacterial growth was significantly inhibited by all blood components, with the exception of IP. MSSA was more sensitive to the treatments than MRSA. At 24 hours, bacterial growth was significantly higher in IP. MRSA bacterial growth was significantly higher in PRP, LPP, and plasma when compared to MSSA. Growth factor concentrations were not significantly affected by bacteria.
Numerical Shape from Shading and Occluding Contours in a Single View

An iterative method of using occluding boundary information is proposed to compute surface slope from shading. We use a stereographic space rather than the more commonly used gradient space in order to express occluding boundary information. Further, we use "average" smoothness constraints rather than the more obvious "closed loop" smoothness constraints. We develop alternate constraints from the definition of surface smoothness. since the closed loop constraints do not work in the stereographic space. We solve the image irradiance equation iteratively using a Gauss-Seidel method applied to the the constraints and boundary information. Numerical experiments show that the method is effective. Finally, we analyze SEM (Scanning Electron Microscope) pictures using this method. Other applications are also proposed.
Obstacle Avoidance of a Class of Underactuated Robot Manipulators: GA based approach

This paper presents a practical collision-free motion planning method for general underactuated robot manipulators. First the dynamic properties of underactuated robot manipulator are analyzed, and then the collision avoidance problem is formulated and solved as a position-based force control problem. Virtual generalized force representing the intrusion of the arm into the obstacle dangerous zone is computed in real time using a virtual spring-damper model. The partly stable controllers are adopted and the energy based fitness function is built, then the best switching sequence of partly stable controllers is obtained by genetic algorithm. Because the proposed method does not make any hypothesis about the degree of freedom, it can be used without modification for arms with a large number of degree of freedom. At last numerical simulations are carried out to illuminate the validity of the proposed method.
Context aware approach for activity recognition based on precondition-effect rules

Context awareness plays an essential role in systems dealing with activity recognition. The context information present to the system, and the way in which it is modelled, shape the performance of the system during activity inference. In this paper we present a novel approach for modelling human behaviour based on preconditions and effects and employing it for generating training-free probabilistic models, that are later used for recognizing the user activities. Furthermore, we use our approach to recognize the activities in a three-person meeting and compare the results from our generated models with those of hand crafted and trained models. Finally, we show that we are able to successfully infer the user state even in models with huge state space.
Are existing procedures enough? Image and video quality assessment: review of subjective and objective metrics

Images and videos are subject to a wide variety of distortions during acquisition, digitizing, processing, restoration, compression, storage, transmission and reproduction, any of which may result in degradation in visual quality. That is why image quality assessment plays a major role in many image processing applications. Image and video quality metrics can be classified by using a number of criteria such as the type of the application domain, the predicted distortion (noise, blur, etc.) and the type of information needed to assess the quality (original image, distorted image, etc.). In the literature, the most reliable way of assessing the quality of an image or of a video is subjective evaluation [1], because human beings are the ultimate receivers in most applications. The subjective quality metric, obtained from a number of human observers, has been regarded for many years as the most reliable form of quality measurement. However, this approach is too cumbersome, slow and expensive for most applications [2]. So, in recent years a great effort has been made towards the development of quantitative measures. The objective quality evaluation is automated, done in real time and needs no user interaction. But ideally, such a quality assessment system would perceive and measure image or video impairments just like a human being [3]. The quality assessment is so important and is still an active and evolving research topic because it is a central issue in the design, implementation, and performance testing of all systems [4, 5]. Usually, the relevant literature and the related work present only a state of the art of metrics that are limited to a specific application domain. The major goal of this paper is to present a wider state of the art of the most used metrics in several application domains such as compression [6], restoration [7], etc. In this paper, we review the basic concepts and methods in subjective and objective image/video quality assessment research and we discuss their performances and drawbacks in each application domain. We show that if in some domains a lot of work has been done and several metrics were developed, on the other hand, in some other domains a lot of work has to be done and specific metrics need to be developed.
Diversity-Multiplexing Tradeoff in Rank-Deficient and Spatially Correlated MIMO Channels

In this paper, we first generalize a recent work of Zheng and Tse on diversity-multiplexing tradeoff (DMT) for some rank-deficient channels (poor scattering). We show that rank deficiency lowers DMT curves from that of i.i. d. Rayleigh fading channels. We show an interesting observation that suggests a fractional diversity gain may be possible at integer multiplexing gains. As the scattering becomes rich, the DMT approaches that of the i.i. d. Rayleigh fading channels. We next focus on spatially correlated multiple-input multiple-output (MIMO) channels. We show that spatial correlation does not change the DMT but still degrades the outage performance and analyze such a degradation at high SNR
Bootstrapping and Decentralizing Recommender Systems

This thesis consists of three papers on recommender systems. The first paper addresses the problem of making decentralized recommendations using a peer-to-peer architecture. Collaborating recommender agents are connected into a network of neighbors that exchange user recommendations to find new items to recommend. We achieved a performance comparable to a centralized system. The second paper deals with the bootstrapping problem for centralized recommender systems. Most recommender systems learn from experience but initially there are no users and no rated items to learn from. To deal with this problem we have developed the Genesis method. The method bootstraps a recommender system with artificial user profiles sampled from a probabilistic model built from prior knowledge. The paper describes how this was done for a k-nearest neighbor recommender algorithm in the movie domain. We were able to improve the performance of a k-nearest neighbor algorithm for single predictions but not for rank ordered lists of recommendations. The third paper identifies a new domain for recommendations – product configuration – where new recommender algorithms are needed. A system that helps users configuring their own PCs is described. Recommendations and a cluster-based help system together with a rule-based configurator assist the users in selecting appropriate features or complete PC configurations. The configurator ensures that users cannot choose incompatible components while the recommender system adds social information based on what other users have chosen. This introduces new complexity in the recommendation process on how to combine the recommendations from the configurator and the recommender system. The paper proposes (1) three new recommender algorithms on how to make recommendations in the domain of product configuration, (2) a method for adding social recommendations to a rule-based configurator and (3) a method for applying the Genesis method in this domain. In this case the Genesis method is implemented by a Bayesian belief net that captures the designers’ prior knowledge on how to configure PCs. Then instances of complete configurations are sampled from the model and added to the recommender algorithm.
Measuring food security using household expenditure surveys

Food is one of the most basic needs for human survival. Access to it is a basic human right. Moreover, the pursuit of the Millennium Development Goal to cut hunger requires a sound understanding of the related food security issues. For these reasons, accurate measurement of the food security status of populations—or their ability to gain access to sufficient high-quality food to enable them to live an active, healthy life—is imperative to all international development efforts. It is necessary for effectively targeting food-insecure populations, researching and planning appropriate interventions, and monitoring progress. As past efforts have shown, accurately estimating the amount of food people eat is costly in terms of time and money, and such measurements have thus been carried out mostly in small populations. Where measurement has been extended to large populations, such as entire countries, it has been necessary to rely on less accurate, indirect techniques based on the availability of food at the national level. This technical guide presents a new avenue for measuring food security, for both small and large populations, based on the data collected as part of household expenditure surveys on the quantities of food acquired by households. It shows how these data can be used to measure a variety of food security indicators, including the prevalence of food energy deficiency and indicators of dietary quality and economic vulnerability to food insecurity. In keeping with the approach of IFPRI's Food Security in Practice series for practitioners, the manual guides readers step by step through the process of assessing the food security status of a population. It begins by offering guidance on choosing an appropriate strategy for calculating quantities of foods acquired by households, given time constraints, financial constraints, and the nature of the population's diet. The guide then leads the practitioner through the steps of collecting the data, processing and cleaning the data, and calculating the indicators. It concludes by illustrating how to conduct some basic food security analyses. I hope that this guide will assist practitioners in increasing the accuracy of the measurement of food insecurity for a greater number of populations, including those at the country level. Greater accuracy at the country level will provide the necessary foundations for overcoming food insecurity globally
The structure of spiral galaxies — II. Near‐infrared properties of spiral arms

ABSTRACT We have imaged a sample of 45 face-on spiral galaxies in the K-band, to determinethe morphology of the old stellar population, which dominates the mass in the disk.The K-band images of the spiral galaxies have been used to calculate diﬀerent char-acteristics of the underlying density perturbation such as arm strengths, proﬁles andcross-sections, and spiral pitch angles. Contrary to expectations, no correlation wasfound between arm pitch angle and Hubble type, and combined with previous resultsthis leads us to conclude that the morphology of the old stellar population bears littleresemblance to the optical morphology used to classify galaxies.The arm properties of our galaxies seem inconsistent with predictions from thesimplest density wavetheories, and some observations, such as variationsin pitch anglewithin galaxies, seem hard to reconcile even with more complex modal theories. Barshave no detectable eﬀect on arm strengths for the present sample.We have also obtained B-band images of three of the galaxies. For these galaxieswe have measured arm cross-sections and strengths, to investigate the eﬀects of diskdensity perturbations on star formation in spiral disks. We ﬁnd that B-band arms leadK-band arms and are narrower than K-band arms, apparently supporting predictionsmade by the large scale shock scenario, although the eﬀects of dust on B-band imagesmay contribute towards these results.Key words: galaxies: spiral - galaxies: structure - galaxies: fundamental parameters
A Report on Genetic Algorithm based Steganography for Image Authentication

Image authentication is done by embedding image/ message in spatial domain or frequency domain. A mask is chosen from the source image in row major order. Bits of the authenticating image are embedded in each byte of the source image block where the position is chosen using hash function. A hash function is a function that takes variable size inputs and return fixed size output. The position will vary from 0 to 4. The hash function is used to find out the position of embedding that vary for every byte of image and is gives more security of the hidden information. The embedding process is repeated throughout the image. The dimension of the authenticating image along with the content are embedded. Genetic Algorithm is used to minimize the difference between the source & embedded image.
Maximizing Quality of Aggregation in Delay-Constrained Wireless Sensor Networks

In this letter, both the number of participating nodes and spatial dispersion are incorporated to establish a bi-objective optimization problem for maximizing the quality of aggregation under interference and delay constraints in tree-based wireless sensor networks (WSNs). The formulated problem is proved to be NP-hard with respect to Weighted-sum scalarization and a distributed heuristic aggregation scheduling algorithm, named SDMAX, is proposed. Simulation results show that SDMAX not only gives a close approximation of the Pareto-optimal solution, but also outperforms the best, to our knowledge, existing alternative proposed so far in the literature.
An Hybrid Data Transfer Optimization Technique for GPGPU

Graphical Processing Units (GPU) can provide tremendous computing power. Current NVidia and ATI hardware display a peak performance of hundreds of gigaflops. However, because of the data transfer speed between CPU and GPU is limited, those devices are difficult to use to accelerate numerical applications. In this paper we propose a software hybrid technique for automatically optimizing data transfer based on static and dynamic information on data accesses.
Effects of Land Use Change and Seasonality of Precipitation on Soil Nitrogen in a Dry Tropical Forest Area in the Western Llanos of Venezuela

We evaluated changes of different soil nitrogen forms (total N, available ammonium and nitrate, total N in microbial biomass, and soil N mineralization) after conversion of semideciduous dry tropical forest in 5- and 18-year-old pastures (YP and OP, resp.) in the western Llanos of Venezuela. This evaluation was made at early rainy season, at end rainy season, and during dry season. With few exceptions, no significant differences were detected in the total N in the three study sites. Compared to forest soils, YP showed ammonium losses from 4.2 to 62.9% and nitrate losses from 20.0 to 77.8%, depending on the season of the year. In OP, the ammonium content increased from 50.0 to 69.0% at the end of the rainy season and decreased during the dry season between 25.0 and 55.5%, whereas the nitrate content increased significantly at early rainy season. The net mineralization and the potentially mineralizable N were significantly higher (P < 0.05) in OP than in forest and YP, which would indicate a better quality of the substrate in OP for mineralization. The mineralization rate constant was higher in YP than in forest and OP. This could be associated with a reduced capacity of these soils to preserve the available nitrogen.
Sequential decoding for the exponential server timing channel

We show the existence of a good tree code with a sequential decoder for the exponential server timing channel. The expected number of computations before moving one step ahead is upper-bounded by a finite number. The rate of information transfer for this code is /spl mu//(2e) nats per second i.e., one half of the capacity. The cutoff rate for the exponential server queue is therefore at least /spl mu//(2u) nats per second.
A simple algorithm to search for all minimal cutsets with unreliable nodes

A minimal cutset is a cut between source node and sink node such that any proper subset of such minimal cutset is not a cut. A simple method is proposed to determine all minimal cutsets in a network subject to both arc and node failure. The proposed method exactly determines minimal cutsets for an unreliable network from the minimal cutsets of the associated network with perfect nodes and arcs. This eliminates the further checking required by the best known algorithm for this procedure and hence provides a more efficient approach. The proposed method requires only elementary concepts and is simple to understand and implement. By coping with unreliable nodes and arcs the algorithm provides a valuable tool for analyzing the reliability of an existing network.
Space-Filling Curve Based Point Clouds Index

Managing large volume points clouds data generated from laser scanner is a challenging problem in Geographic Information System (GIS) and spatial database. Based on analyzing the pros and cons of the existing management methods, this paper presents a method to manage lidar data in databases based on the Hilbert space-filling curve. Each lidar data point (X, Y, and Z) is encoded (indexed) by the 3-D Hilbert curve. Data points are organized together according to their Hilbert codes. The initial encoding level of Hilbert curve is determined by the total number of points and the target record size. The data points are first encoded with this initial level Hilbert curve. After refining and combining processes, the data volume of each group is controlled under the desired size. One record in database represents one data group; the binary blob of the record contains all the data points in one group. Details on constructing 3-D Hilbert curve are discussed. Typical query process “window query” is implemented. Reported in this paper are results based on synthetic and real lidar data collected from ground tripod lidar and airborne lidar equipments.
Longitudinal/Goldstone boson equivalence and phenomenology of probing the electroweak symmetry breaking

We formulate the equivalence between the longitudinal weak-boson and the Goldstone boson as a criterion for sensitively probing the electroweak symmetry breaking mechanism and develop a precise power counting rule for chiral Lagrangian formulated electroweak theories. With these we semi-quatitatively analyze the sensitivities to various effective operators related to electrowaeak symmetry breaking via weak-boson scatterings at the CERN Large Hadron Collider (LHC).