Miracle-dz/UniFAR-FTUs huggingface dataset:
Blind Authentication of Resampled Images and Rescaling Factor Estimation

The rapid growth of image processing softwares and advancement in digital cameras has given rise to large amount of doctored images with no obvious traces. When altering an image like copy - paste or splicing to conceal traces of tampering, it is often necessary to resize the pasted portion of the image. The resampling operation may highly likely disturb the underlying inconsistency of the pasted portion, that can be used to detect the forgery. In this paper, an algorithm is presented that can blindly detect rescale operation and estimate the rescaling factor in zoom-in or zoom-out using properties of the zero-crossings of the second difference of the tampered image. Experimental results have proved the validity of the algorithm under different interpolation schemes.
A Note on Unscented Filtering and State Propagation in Nonlinear Systems

In this note, we illustrate the eect of nonlinear state propagation in the unscented Kalman lter (UKF). We consider a simple nonlinear system, consisting of a two-axis inertial measurement unit. Our intent is to show that the propagation of a set of sigma points through a nonlinear process model in the UKF can produce a counterintuitive (but correct) updated state estimate. We compare the results from the UKF with those from the well-known extended Kalman lter (EKF), to highlight how the UKF and the EKF dier.
Desempleo y precariedad laboral en mayores de 45 años: una luz al final del túnel

This work shows the main keys for access to employment and some alternatives for this concerning to unemployed people older than 45 years, provided by experts on training and employment. The study is tackled through a discourse analysis of interviews to experts. The results stand out the orientation and qualification between the recommendations for access to employment; and entrepreneurship, submerged economy and mentoring between the employment alternatives. The conclusions value the great possibilities and the human capital that these people can provide, especially in processes of intergenerational learning and mentoring.
Applying Decision Analysis to Component Reuse Assessment

April 2004 N system development has been driven toward component reuse by many factors, including the emergence of rapidly changing technology, faster development timelines and limited budgets, the inability of stove-piped legacy systems to deal with information-/network-centric warfare, and the emergence of new system acquisition policies. Reusing components of existing systems is a viable method to overcome these factors. Effective reuse allows system development to stay current with technology, react to tightening schedules and budgets, and manage development risks. Realizing the benefits of component reuse for the federal government is one of the U.S. Chief Information Officers (CIO) Council’s focus areas. The council is currently developing overarching guidance to define component-based architecting for the federal government and the role of component reuse within it [1]. However, the CIO council’s objective is not to dictate explicit reuse assessment procedures, rather, it hopes to provide the high-level guidance necessary to set out the scope of such a program. Similarly, the U.S. Navy is in the midst of developing a component-based shipboard computing environment called the Open Architecture Computing Environment [2]. The program seeks to specify a broad range of reusable components and entire applications upon which to build new systems. In both cases, and for the engineering community at large, a standardized reuse assessment process would be beneficial. Upon implementing a component reuse assessment process, the first question that comes to the developer’s mind is usually: “Which components should I evaluate for reuse potential? ” For almost any system development effort, there are an overwhelming number of reusable components that might be considered, and attempts to exploit these components through using traditional engineering approaches have been disappointing [3]. A structured and tailorable decision-making process, incorporating both qualitative and quantitative analysis, is needed to filter out components to be evaluated, select the right reuse candidates, and justify reuse decisions. This article advances the current state of research in the application of decisionmaking processes for component reuse by focusing both on the actual evaluation processes and the filtering mechanisms
A modified stretching factor for perfect matched layers in 2D FDTD simulations

A modified definition of the stretching factor for perfectly matched layer is introduced in 2D finite difference time domain method. This modified definition allows us to write equations for only one polarization to calculate both TMz and TEz polarized fields by taking the advantage of duality relations. The wave incident at Brewster angle and wave propagation through Fresnel zone plate are simulated by our developed method.
ECE 544 NA Final Project : Malicious Code Execution Detection Using Bottleneck Stacked Autoencoder

In this project, Bottleneck Stacked Autoencoder, a deep learning method, is used to model the normal program (application) behavior and to detect abnormal behavior in terms of the system call usage. The method is evaluated by applying the proposed approach to an example application in which malicious code are embedded. The evaluation results show its effectiveness in terms of the detection accuracy and false positive rates, which are even comparable to Gaussian Mixture Model.
Machine Learning and Inference Laboratory Progress Report on Learnable Evolution Model

This report reviews recent research on Learnable Evolution M del (LEM), and presents selected results from its application to the optimization of complex functions and engi neer ng designs. Among the most significant new contributions is a multi operator methodology for generating individuals (candidate solutions) and the employment of a more advanced learning program, A Q21, as the learning module. The new features have been implemented in the LEM3 program. To ev aluate LEM3’s performance, it was experimentally compared to other evolutionary computation programs, s uch as, EA--a conventional, Darwinian-type evolutionary computation program, CA--a cultural ev olution algorithm, and EDA--an estimation of distribution algorithm on selected function optimization problems. To determine the scalability of LEM3 and compared programs, the number of variabl es in the optimized functions was varied from 2 up to 1000. In every experiment, LEM3 outperformed the oth er programs in terms of the evolution length, sometimes more than an order of magnitude. Another re cent research result is the development of early versions of two LEM-based systems, ISHED and ISCOD, for the optimization of heat exchangers evaporators and condensers, respectively. This w ork was done in collaboration with scientists from the National Institute of Science and Technolog y. In experimental testing, the systems produced designs that matched or were superior to human designs, part icularly, in the cases of nonuniform air flows. This collaboration continues, and may ultimat ely produce systems that NIST will use to develop better designs of heat exchangers and have them implemented by the industry.
Engineering of the Decisional Information System by the reuse Engineering of the Decisional Information System by the reuse Engineering of the Decisional Information System by the reuse Engineering of the Decisional Information System by the reuse of patterns

When analyzing the needs of a DIS, many problems related to in consistency and to the difficulty of modeling requirements, are detected. Thus, we propose a complete approach for analysis and design of a DIS [3] to analyze business requirements collected to establish the star schema. This approach integrates the notion of business context of the organization and provides a process for formalizing business requirements for a DIS directing the treatment of business requirements, collected in the form of goals, in order to systematically extract facts and dimensions. Moreover for reasons of reuse, we opt for an approach guided by the patterns [5] [6] for the analysis of business requirements for a DIS, which consists of proposing a catalog of reusable patterns which capitalize the processes and models of the approach
Leptin regulates GH secretion in the rat by acting on GHRH and somatostatinergic functions.

Leptin is a hormonal product of adipose tissue whose expression reflects the body state of nutritional reserves. Previous experiments have demonstrated that leptin is one of the metabolic signals capable of regulating GH secretion. The aim of the present study was to evaluate whether CNS-mediated mechanisms underlie the GH-releasing activity of leptin. Freely moving mature male rats were injected i.c. v with leptin or isovolumetric amounts of diluent once daily for 3 days and were killed 2 h after the last administration. Central injection of leptin increased pituitary GH mRNA levels by 53. 2% and hypothalamic GHRH mRNA by 61.8%, and reduced somatostatin mRNA levels by 41.5%. To evaluate the direct effect of leptin on the pituitary, it was added alone or in combination with GHRH to primary cultures of anterior pituitary cells. Addition of leptin (10(-11)-10(-7) M) did not alter basal GH release nor the GH-releasing activity of GHRH. These results demonstrate that leptin is a metabolic signal that regulates GH secretion in the rat by acting on hypothalamic GH-regulatory hormones.
Evaluating Information Visualization on Mobile Devices: Gaps and Challenges in the Empirical Evaluation Design Space

With their increasingly widespread use, mobile devices have become a highly relevant target environment for Information Visualization. However, far too little attention has been paid to evaluation of interactive visualization techniques on mobile devices. To fill this gap, this paper provides a structured overview of the commonly used evaluation approaches for mobile visualization. For this, it systematically reviews the scientific literature of major InfoVis and HCI venues and categorizes the relevant work based on six dimensions circumscribing the design and evaluation space for visualization on mobile devices. Based on the 21 evaluations reviewed, reproducibility, device variety and usage environment surface as the three main issues in evaluation of information visualization on mobile devices. To overcome these issues, we argue for a transparent description of all research aspects and propose to focus more on context of usage and technology.
A Review on the Management of Hip and Knee Osteoarthritis

Arthritis is the most common chronic condition affecting patients over the age of 70. The prevalence of osteoarthritis increases with age, and with an aging population, the effect of this disease will represent an ever-increasing burden on health care. The knee is the most common joint affected in osteoarthritis, with up to 41% of limb arthritis being located in the knee, compared to 30% in hands and 19% in hips. We review the current concepts with regard to the disease process and risk factors for developing hip and knee osteoarthritis. We then explore the nonsurgical management of osteoarthritis as well as the operative management of hip and knee arthritis. We discuss the indications for surgical treatment of hip and knee arthritis, looking in particular at the controversies affecting young and obese patients in both hip and knee replacements. Patient and implant related outcomes along with survivorships are addressed as well as the experiences and controversies described in national joint registries.
How Sleep Activates Epileptic Networks?

Background. The relationship between sleep and epilepsy has been long ago studied, and several excellent reviews are available. However, recent development in sleep research, the network concept in epilepsy, and the recognition of high frequency oscillations in epilepsy and more new results may put this matter in a new light. Aim. The review address the multifold interrelationships between sleep and epilepsy networks and with networks of cognitive functions. Material and Methods. The work is a conceptual update of the available clinical data and relevant studies. Results and Conclusions. Studies exploring dynamic microstructure of sleep have found important gating mechanisms for epileptic activation. As a general rule interictal epileptic manifestations seem to be linked to the slow oscillations of sleep and especially to the reactive delta bouts characterized by A1 subtype in the CAP system. Important link between epilepsy and sleep is the interference of epileptiform discharges with the plastic functions in NREM sleep. This is the main reason of cognitive impairment in different forms of early epileptic encephalopathies affecting the brain in a special developmental window. The impairment of cognitive functions via sleep is present especially in epileptic networks involving the thalamocortical system and the hippocampocortical memory encoding system.
Construction Optimal Combination Test Suite Based on Ethnic Group Evolution Algorithm

The optimal test case suite constructing problem is defined thus: given a set of test requirements and a test suite that satisfies all test requirements, find a subset of the test suite containing a minimum number of test cases that still satisfies all test requirements. Existing methods for solving test case suite generation problem do not guarantee that obtained test suite is optimal. In this study, we propose a global optimization and generation method to construct optimal combinatorial testing data. Firstly, an encoding mechanism is used to map the combinatorial testing problem domain to a binary coding space. After that, an improving ethnic group evolution algorithm is used to search the binary coding space in order to find the optimal code schema. Finally, a decoding mechanism is used to read out the composition information of combinatorial testing data from the optimal code schema and construct optimal test case suite according to it. The simulation results show this method is simple and effective and it has the characteristics of less producing test data and time consumption.
''Not Just Right Experiences'' in Adolescents: Phenomenology

Efforts to understand the nature of ''Not Just Right Experiences'' (NJREs) have expanded the scientific understanding of obsessive-compulsive (OC) behavior. Approximately 80 % of unselected adults report experi- encing NJREs and these experiences have been found to highly correlate with OC behavior. The purpose of this study was to assess NJREs in an unselected sample of adolescents (ages 14-17; N = 152), to compare their experience with adults (N = 237), and to assess the rela- tion between NJREs and OC symptoms. Findings from questionnaires completed on the Internet were consistent with previous findings in adults, 81 % of adolescents endorsed recently having an NJRE. Some reactions dif- fered according to age: adults reported NJREs as more frequent and adolescents endorsed feeling more compelled to respond. Surprisingly, OC symptoms were not signifi- cantly related to NJREs in the adolescents. Implications, limitations, and future directions for the study of NJREs in youth are discussed.
Automatic control on transmission power in wireless networking

The automatic control theory plays an important role in modern industries. With the rapid development of the Internet and a variety of wireless networks, its application field has been becoming wider and wider. However, in the design of networking protocols, instead of utilizing the classical control theory, most software engineers favor open-loop control. In reality, closed-loop control may well serve as a simple and efficient part in some cases. In this paper, we try to apply the classical control theory to the adjustment on the transmission power in wireless networking. As a result, we propose APC (Automatic Power Control), a distributed power control algorithm that can be used in conjunction with any routing protocols as long as the routing table of each node provides enough knowledge of local network topology. The basic idea of APC is to adjust the transmission power for each wireless node through an improved version of the classical PID (Proportion-Integral-Differential) control. The network topology derived under APC is also fed back to the routing table that is used as its input. Both theoretical analysis and simulation study show that APC is an effective application of the classical control theory in wireless networking.
Power constrained and delay optimal policies for scheduling transmission over a fading channel

An optimal power and rate scheduling problem for a single user transmitting to a base station on a fading wireless link with the objective of minimizing the mean delay subject to an average power constraint is considered. The base station acts as a controller which, depending upon the transmitter buffer lengths and the signal power to interference ratio (SIR) on the uplink pilot channel, allocates transmission rate and power to the user. We provide structural results for an average cost optimal stationary policy under a long run average transmitter power constraint. We obtain a closed form expression relating the optimal policy when the SIR is the best, to the optimal policy for any other SIR value. We also obtain lower and upper bounds for the optimal policy.
Design approaches for the gamification of production environments: a study focusing on acceptance

Gamification is an ever more popular method to increase motivation and user experience in real-world settings. It is widely used in the areas of marketing, health and education. However, in production environments, it is a new concept. To be accepted in the industrial domain, it has to be seamlessly integrated in the regular work processes. In this work we make the following contributions to the field of gamification in production: (1) we analyze the state of the art and introduce domain-specific requirements; (2) we present two implementations gamifying production based on alternative design approaches; (3) these are evaluated in a sheltered work organization. The comparative study focuses acceptance, motivation and perceived happiness. The results reveal that a pyramid design showing each work process as a step on the way towards a cup at the top is strongly preferred to a more abstract approach where the processes are represented by a single circle and two bars.
Distinct GAGE and MAGE-A expression during early human development indicate specific roles in lineage differentiation.

BACKGROUND Expression of cancer/testis-associated proteins (CTAs) has traditionally been considered to be restricted to germ cells in normal tissues and to different types of malignancies. We have evaluated the potential role of CTAs in early human development. METHODS Using immunohistochemistry and RT-PCR, we investigated the expression of CTAs in differentiated human embryonic stem cells (hESC) and in late embryos and early fetuses. RESULTS We found that melanoma antigen A (MAGE-A) family members were expressed during differentiation of hESC to embryoid bodies and in teratomas, and overlapped with expression of the neuroectodermal markers beta-tubulin 3, Pax6 and nestin. A widespread expression of MAGE-A was also observed in neurons of the early developing central nervous system and peripheral nerves. G antigen (GAGE) expression was present in the early ectoderm of embryos, including cells of the ectodermal ring and apical epidermal ridge. Neuroectodermal cells in the floor plate and adjacent processes and endfeet of radial glial cells also expressed GAGE. In addition, GAGE family members were expressed in the peripheral adrenal cortex of 6-9-week-old embryos and fetuses, which specifically correlated with massive cellular proliferation and establishment of the definitive and fetal zones. Overlapping expression of MAGE-A and GAGE proteins occurred in migrating primordial germ cells. CONCLUSIONS Our results show that CTAs, in addition to their role in germ cells, may be involved in early development of various types of somatic cells, and suggest that they are implicated in specific differentiation processes.
eul.icio.us: Euler Diagrams for del.icio.us

EulerView incorporates a non-hierarchical classification structure to enable enhanced resource management. We apply the EulerView concept to the use of urls, constructing eli.icio. us which is a tool that realizes the EulerView concept and integrates it with del.icio. us. Currently, in del.icio. us, users can tag urls and browse for similar urls and the results can be displayed via an alphabetically sorted tag cloud. As well as facilitating easy tag management, using an EulerView display has the advantage that the user can use this representation for both tagging urls and for searching or browsing tasks, thus reducing any cognitive difficulties of users due to interacting with multiple representations.
A Damage Assessment System for Aero-engine Borscopic Inspection Based on Support Vector Machines

Defects are often arise on the inner surface of an aeroengine, but most of the aeroengine borescopes can only detect the damages and cannot determine the degree of damages. We propose a novel borescope assessment expert system (ES) to evaluate the degree of typical flaws of an engine and to provide the corresponding maintenance advices. The system put typical damage images and relevant maintenance rules into knowledge bases as the standard cases. A binary-tree-based support vectors machine (SVM) was used as the reasoning machine to obtain case knowledge and implement the logic reasoning, which enhanced the learning ability, inference speed and precision of the expert system. The application to CFM56 aero-engine shows that the system with both the advantages of SVM and ES has higher assessing accuracy than traditional ES method.
Using Reinforcement Learning to Control Life Support Systems

Advanced life support systems have many interacting processes and limited resources. Controlling and optimizing advanced life support systems presents unique challenges that are addressed in this paper. In particular, advanced life support systems are nonlinear coupled dynamical systems and it is difficult for humans to take all interactions into account to design an effective control strategy. We have developed a controller using reinforcement learning [1], that actively explores the space of possible control strategies, guided by rewards from a user specified long term objective function. We evaluated this controller using a discrete event simulation of an advanced life support system. This simulation, called BioSim, has multiple, interacting life support modules including crew, food production, air revitalization, water recovery, solid waste incineration and power. These are implemented in a consumer/producer relationship in which certain modules produce resources that are consumed by other modules. Stores hold resources between modules. Control of this simulation is via adjusting flows of resources between modules and into/out of stores. This paper describes the results of using reinforcement learning to control the flow of resources in BioSim. Our technique discovered unobvious strategies for maximizing mission length. By exploiting non-linearities in the simulation dynamics, the learned controller outperforms a handwritten controller.