Miracle-dz/UniFAR-FTUs huggingface dataset:
08 Waldo lo

Jini technology assumes a changing network, in terms of both the components that make up the network and the way these components interact. Networks are generally long-lived entities that, as they grow to include ever-larger populations of users and machines, become increasingly difficult to upgrade as a single entity. That’s why the Jini architecture is designed around support for incrementally upgrading network components (hardware and software) [9]. So, for example, installing a
National Culture and MNE Subsidiary Control

We investigate expatriate assignments as a vehicle for managerial control in multinationals. Our theoretical development and hypotheses indicate that not only will power distance be a particularly powerful predictor of expatriate assignment—both at home country level as well as in terms of cultural distance—but also that there will be an asymmetrical effect of home versus host country culture. We also investigate an age effect of expatriate incidence in high power distance contexts over time. Data collected from a multi-country sample of 236 subsidiaries allowed for analyses using various techniques and two different measures of the expatriate assignment. Results indicate support for all the hypotheses.
Error-Correct A General Metho Multiclass Inductive

Multiclass learning problems involve finding a definition for an unknown function f(x) whose range is a discrete set containing Ic > 2 values (i.e., k " classes "). The definition is acquired by studying large collections of training examples of the form (xi, f(xi)). Existing approaches to this problem include (a) direct application of multiclass algorithms such as the decision-tree algorithms ID3 and CART, (b) application of binary concept learning algorithms to learn individual binary functions for each of the Ic classes, and (c) application of binary concept learning algorithms with distributed output codes such as those employed by Sejnowski and Rosenberg in the NETtalk system. This paper compares these three approaches to a new technique in which BCH error-correcting codes are employed as a distributed output representation. We show that these output representations improve the performance of ID3 on the NETtalk task and of backpropagation on an isolated-letter speech-recognition task. These results demonstrate that error-correcting output codes provide a general-purpose method for improving the performance of inductive learning programs on multi-class problems.
Exploiting Spatial Variability for Disparity Estimation

for disparity estimation is introduced. In the proposed approach the size of the matching window is adapted according to the spatial variability of the matching areas. That is, the window size is constrained by the variations of the image intensity. A modified semivariogram function is proposed to measure the spatial variability of concerned sampling positions. Results of computer experiments aimed at validating the performance of the proposed approach are reported. As expected, using adaptive matching window size provides better disparity estimations than those obtained by using a fixed window.
Saving power by synthesizing gated clocks for sequential circuits

Portable devices demand low power consumption to prolong battery life. Gating the clock is one strategy for saving power. The authors' technique identifies self-loops in an FSM and uses the function described by the self-loops to gate the clock. Applying these techniques to standard benchmarks achieved an average 25% less power dissipation at a cost of only 5% more area. <<ETX>>
The Fragility and Robustness of Trust

Although it is well known that trust is an important component of the fulfilment of incomplete contracts, less is known regarding how robust it is to past experiences. We present an experiment in which trust is required for transactions to occur, and nature provides a series of shocks along the path of play. Although the shocks have a short-term impact, we find that trust is surprisingly robust in the long-term. We argue that trust, through fragile in one way, is in another way more robust and stable over time than previously known. The results shed light on the resilence of economic institutions with incomplete contracts.
INTELLIGENT USER INTERACTIVE MODEL FOR REAL TIME TEXT-GRAPHIC GENERATION

Real-time graphic generation from text inputs has visited by various researchers and many methods have been proposed earlier in this decade to simplify the task of graphic generation. But still the problem of providing sophisticated and accurate has not been met with any of the solution provided. We propose an intelligent interactive framework to generate graphics by processing the text input and the text processor interactively acquires the necessary parameters of the object to be generated on graphics which supports the user on generating quality graphics. The presented model has three components namely interactive text processor, Hybrid Property Manager and Graphics Generator. The hybrid property manager maintains multi object properties in hybrid nature using which the text processor acquires the necessary values for the properties of any object mentioned. Upon receiving a text input the interactive text processor identifies the set of objects mentioned in the input, and for each object provided it requests the level by level property value acquisition using hybrid property manager. The acquired values of object properties will be given for the graphic generator, which generates graphics based on object properties. The proposed model has produced higher accurate results and supported user, to make graphics easier.
Autoimmunity as a Predisposition for Infectious Diseases

Autoimmunity refers to an inappropriate immune response against self-components of the host that results in pathological conditions. Autoimmune diseases are characterized by an activation of autoreactive T and B cells, are associated in some cases with the production of pathogenic autoantibodies against self-molecules, culminating in inflammation and tissue damage. The reasons for the breakdown of tolerance mechanisms leading to autoimmunity are not clearly known. However, a combination of genetic, immunological, and environmental factors plays a critical role in the pathogenesis of autoimmunity [1]–[5].
Domain Adaptation in Sequence Analysis

The machine learning approach to problems from computational biology is to learn models from labeled training examples. A common problem in supervised learning is the lack of sufficient training data. Often, however, there exists a large body of data on a different, but related problem. In order to boost performance on our problem of interest, we would like to utilize information from this related domain. The field of domain adaptation formalizes this scenario and provides intelligent algorithms to transfer information between domains. The aim of this work is to compare, extend and develop domain adaptation algorithms suited for problems in computational biology. A central part of this work is the evaluation of domain adaptation methods in large scale computational experiments. To our knowledge, this work constitutes the first thorough experimental comparison of available domain adaptation algorithms in a well controlled experimental framework. Furthermore, we are one of the first to apply such methods to problems in computational biology, which appears to provide a wealth of potential applications. Representative for the class of sequence-based classification problems we chose the problem of splice site prediction an important subproblem in computational gene finding. In splice site prediction, challenges arise from an extremely high dimensional feature space, unbalanced data sets and the fact that there is very little labeled data available for newly sequenced organisms. To improve performance on the organism of interest, we turn to other organisms as additional sources of information. Experiments were conducted for a set of target organisms of varying phylogenetic distance to the source organism and for multiple data set sizes. Comparing the methods over a range of conditions allows us to draw conclusions under what circumstances which methods perform well. We observed that the methods that learn solutions on all data sources simultaneously perform best. Furthermore, methods based on simple convex combinations provide the most cost-effective solution to the domain adaptation problem. The largest improvements over baseline methods can be observed if the organisms are only distantly related. Using the example of splice site prediction, we can show that domain adaptation algorithms are well suited to considerably boost predictive performance on sequence based classification problems.
Salivary gland tumours in Tanzania.

OBJECTIVE To determine the pattern of occurrence of salivary gland tumours in Tanzania over a period of twenty years. DESIGN Cross-sectional retrospective study. SETTING Two referral centres; Muhimbili National Hospital (MNH) and Kilimanjaro Christian Medical Centre (KCMC). METHODS Medical records of patients who presented with tumours of the salivary glands in the two major referral centres over a period of twenty years from 1982 to 2001 were reviewed. Data regarding demographic, clinical and histologic information was analysed. RESULTS Salivary gland tumours constituted 6.3% of all oral-facial tumours and tumour like lesions. Among the salivary gland tumours, 54% were benign and 46% malignant, which occurred in 80 males and 53 females. Peak age was between 20 and 49 years, with a male-female ratio of 1.5:1 (p<0.05). Pleomorphic adenoma was the commonest occurring tumour (44.4%) followed by adenoid cystic carcinoma (24.8%), mucoepidermoid carcinoma (9.8%) and adenocarcinoma (6.5%). Among the benign tumours, pleomorphic adenoma dominated (83.9%), followed by adenoma (9.9%). Among malignant tumours adenoid cystic carcinoma occurred in 54.3% followed by mucoepidemoid carcinoma (22.9%) and adenocarcinoma (11.4%). The parotid gland was the commonest site of occurrence followed by the palate. At initial stages the only complaint from the patients was essentially a slowly growing painless swelling. Treatment modality was mainly surgical in both benign and malignant tumours, however, for malignant tumours radiotherapy alone or in combination with surgery was sometimes employed. CONCLUSION On average salivary gland tumours occurred at a relatively younger age compared to that reported in Western countries. Contrary to reports from Europe and America, adenoid cystic carcinoma was the most frequently occurring malignant salivary gland tumour. Late presentation was seen as a problem that needs to be addressed in order to maximise the effectiveness of treatment.
Counterinsurgency in Afghanistan

This study explores the nature of the insurgency in Afghanistan, the key challenges and successes of the campaign, and the capabilities necessary to wage effective counterinsurgency operations. It argues that successful counterinsurgency requires effective indigenous security forces, especially police; a viable and legitimate local government; and the suppression of external support for insurgents.An examination of the U.S.-led campaign in Afghanistan illustrates that successful counterinsurgency requires effective indigenous security forces, especially police; a viable local government; and the suppression of external support for insurgents.
KMS with hierarchical administrative architecture: A knowledge administrator perspective

A Knowledge Management System (KMS) refers to a system for managing knowledge in organizations, supporting creation, capture, storage and dissemination of information. KMS is viewed as an essential tool to extract tacit knowledge from data, convert it to explicit knowledge and preserve the same for future utilization. The system involves creation of a knowledge repository using the extracted knowledge and disseminating it in the form of query response systems. In this work, we have proposed the architecture for an administrator-centric KMS which revolves around the concept of Knowledge Administrator (KA) with a Knowledge Worker (KW) standard. KA is responsible for maintenance as well as security and efficiency of the framework which are essential for a reliable KMS. In this system, the Knowledge Worker (KW) structure is hierarchical which provides scope for building a knowledge repository which is often encountered to be critical in some of its applications. The Knowledge Base (KB) is built on tag extraction based on inverted indexing. The system was a learning automation which used the available client feedback in response to the query answered from the knowledge base. The knowledge repository interacted with data using a framework created based on inverted indexing. A salient feature of the architecture is the notion of Probabilistic Optimum Performance (POP) factor used for rating KWs. The rating which is determined by past performance and client feedback acts as a driving force for a more comprehensive KB as its interaction with its environment increases.
Investigation of orthogonal space-time block codes using a MIMO hardware demonstrator

In this paper we present a multiple antenna system for industrial, scientific, and medical (ISM)-band transmission (MASI). The hardware demonstrator was developed and realized at our institute. It enables multiple input multiple output (MIMO)-communication applications and is capable to transmit arbitrary signals using 8 transmit and 8 receive antennas in parallel. It operates in the 2.4 GHz ISM-band. The hardware concept is introduced and some design specifications are discussed. As an application example, we will focus on one specific class of transmit diversity schemes: orthogonal space-time block codes (OSTBC). Channel estimation and carrier offset estimation are essential tasks in coherent receivers. However, they are also some kind of error sources due to the imperfectness of the employed algorithm. We will show by simulation and measurement results, that OSTBC based systems are more sensitive to channel estimation errors and/or carrier frequency offsets than conventional single transmit antenna systems. The consequence is that the diversity gain decreases significantly in the case of estimation errors.
Response: Commentary: Control of Body Weight by Eating Behavior in Children

To the Editor: We thank Dr. Tony Kuo for his valuable comments on our review. As Dr. Kuo correctly points out, interventions aiming at manipulating internal mechanisms related to body weight, e.g., ­pharmacology and diets, have had limited success in reversing the increase in pediatric body weight. We agree with him that the alternative suggestion that body weight is under external control is in line with many recent public health initiatives aiming at improving the food environment. Dr. Kuo listed many of the newer policies, some of which we were unaware of and so we learnt a great deal from reading Dr. Kuo’s commentary paper. Yet, we feel confident that Dr. Kuo agrees with us that the success of these initiatives in curbing further increase in body weight among children has also been limited. We beg to disagree, however, with Dr. Kuo that the hypothesis that body weight is under external control is “opposed to the viewpoint that cognition plays a predominant role,” and that our method is somehow related to “cognitive control. ” We refer to the compelling work of Dr. Brian Wansink, showing that the role of cognition in eating behavior is negligible (1). Undesirable cognitions, including “dietary restraint,” among obese individuals are more likely the results of failed attempts at dieting than causes of their weight problem (2). Interestingly, a sustained reduction of body weight has been obtained with cognitive behavioral therapy (3), but it is clear from the protocol that the effect was obtained by behavioral intervention, i.e., establishing normal eating behavior; whatever effect the cognitive intervention exerted was less important (4). At the same time, we certainly agree with Dr. Kuo that our suggestion that body weight can increase among the underweight and decrease among the overweight if they learn how to eat normally by using feedback on a computer screen requires further investigation. However, the facts that this method has brought 75% of patients with eating disorders into remission, reduced the rate of relapse to 10% over 5 years of follow-up, and eliminated the mortality are encouraging (5). We have outlined the neurobiological mechanisms on which the method relies in detail (references in our review). The approach was adapted to the treatment of childhood obesity because anorexia and obesity are at the extreme opposites of the same behavioral and biochemical continuum (6). Dr. Kuo is right in suggesting that the success of this approach on a larger scale needs to be tested. And, of course, creating healthy environments, including advice on diets and physical activity, remains important not least “for those who live in low socioeconomic status areas. ”
Towards soft computing object-oriented logic programming

Logic programming, object-oriented programming and soft computing have provided advantageous methodologies and techniques for computer-based problem solving. This paper proposes a framework that combines these three disciplines to exploit their own advantages in dealing with real world problems. The framework is a logic-based one in which class and object properties are represented by clauses. Vague data in properties are represented by fuzzy sets interpreted as possibility distributions. Uncertain applicability of a property to a class or an object is represented either by a support pair defining probability lower and upper bounds, or by a certainty lower bound. Fundamental issues of uncertain membership and inheritance are then discussed and solutions to them are proposed. The result forms a basis for development of soft computing object-oriented programming systems.
City of Stone: The Hidden History of Jerusalem

Jerusalem is more than a holy city built of stone. Domain of Muslims, Jews, and Christians, Jerusalem is a perpetual contest, and its shrines, housing projects, and bulldozers compete in a scramble for possession. Now one of Jerusalem's most respected authorities presents a history of the city that does not fall prey to any one version of its past. Meron Benvenisti begins with a reflection on the 1996 celebration of Jerusalem's 3000-year anniversary as the capital of the Kingdom of Israel. He then juxtaposes eras, dynasties, and rulers in ways that provide grand comparative insights. But unlike recent politically motivated histories written to justify the claims of Jews and Arabs now living in Jerusalem, Benvenisti has no such agenda. His history is a polyphonic story that lacks victors as well as vanquished. He describes the triumphs and defeats of all the city's residents, from those who walk its streets today to the meddlesome ghosts who linger in its shadows. Benvenisti focuses primarily on the twentieth century, but ancient hatreds are constantly discovered just below the surface. These hostilities have created intense social, cultural, and political interactions that Benvenisti weaves into a compelling human story. For him, any claim to the city means recognizing its historical diversity and multiple populations. A native son of Jerusalem, Benvenisti knows the city well, and his integrated history makes clear that all of Jerusalem's citizens have enriched the Holy City in the past. It is his belief that they can also do so in the future.
Universality of the Network and Bubble Topology in Cosmological Gravitational Simulations

Using percolation statistics we, for the first time, demonstrate the universal character of a network pattern in the real space, mass distributions resulting from nonlinear gravitational instability of initial Gaussian fluctuations. Percolation analysis of five stages of the nonlinear evolution of five power law models reveals that all models show a shift toward a network topology if seen with high enough resolution. However, quantitatively, the shift is significantly different in different models: the smaller the spectral index ,n, the stronger the shift. On the contrary, the shift toward the "bubble" topology is characteristic only for the n <= -1 models. We find that the mean density of the percolating structures in the nonlinear density distributions generally is very different from the density threshold used to identify them and corresponds much better to a visual impression. We also find that the maximum of the number of structures (connected regions above or below a specified density threshold) in the evolved, nonlinear distributions is always smaller than in Gaussian fields with the same spectrum, and is determined by the effective slope at the cutoff frequency.
NEW HIERARCHICAL METHOD FOR PATH PLANNING OF LARGE- SCALE ROBOTS

In this paper, a new coordination me- thod based on non-linear hierarchical control for large-scale robots is presented. The large-scale sys- tem is considered as combination of subsystems so that each subsystem has interaction with others. The procedure is to use interaction prediction principle with optimal control for each subsystem. At the first level, applying optimal control principle to each sub- system with guessed interaction variables results in Two Point Boundary Value Problem (TPBVP). By solving TPBVP the new interaction parameters are generated. At the second level, the resulted interac- tions are exchanged between subsystems and the in- teraction variables are improved within interaction prediction principle. Difference between guessed and achieved interaction in each step is used in general cost function to coordinate subsystems. Hence con- tinuing the algorithm causes to converging the inte- ractions to each other. The new method results in less time by parallel processing for each subsystem, and has less sensitivity for different initial guess in comparison with centralized use of optimal control for large-scale robots because of using small sized sub-systems which is a step toward real-time plan- ning of mobile manipulators, also the proposed me- thod has the ability to solve problems with insepara- ble cost functions which is an important benefit for robots path planning in presence of obstacles and specified path for end-effector. The method is simu- lated and verified by previous work in this area. The simulation results show effectiveness of proposed method for large-scale robots. The approaches valid- ity is checked via simulations and experiments with a 2-link nonholonomic mobile manipulator named Scout.
Length scales in orientational order of vertically aligned single walled carbon nanotubes

We have studied the orientational order in films of vertically aligned single walled carbon nanotubes, by means of resonant Raman spectroscopy, resonant X‐ray absorption, and direct imaging. These methods investigate the hierarchical morphology at different length scales. Here, we discuss the systematic comparison of orientational order as function of wavelength in films with different inherent morphologies and provide thus a basis to quantitatively evaluate and compare the different experimental approaches.
An Efficient Framework for Brain Tumor Segmentation in Magnetic Resonance Images

The main objective of this paper is to provide an efficient tool for delineating brain tumors in three-dimensional magnetic resonance images. To achieve this goal, we use basically a region-based level-set approach and some conventional methods. Our proposed approach produces good results and decreases processing time. We present here the main stages of our system, and preliminary results which are very encouraging for clinical practice.