Miracle-dz/UniFAR-FTUs huggingface dataset:
Advanced in Control Engineeringand Information Science An Improved Apriori Algorithm Based On the Boolean Matrix and Hadoop

The association rule mining plays an important part in the data mining. Association rule mining aims to find rules in the transaction database with the minimum support and minimum confidence which are the user given. In order to find all the frequent item sets from the transaction database efficiently and quickly, an improved Apriori algorithm of mining the association rules in this paper is put forward to solve the bottleneck problems of the traditional Apriori algorithm. First the Boolean matrix array is used to replace the transaction database. Then the “AND” operation and random access characteristics of array are used. Next the mining algorithm is carried out on the Hadoop Platform. According to the number of the Data Nodes of the Hadoop, the matrix is divided into several parts. Each part is operated separately on one Data Node. It can improve the efficiency of the algorithm. © 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [CEIS 2011]
A constructivist approach to student development: Effat University case study

Sustainable education requires a new approach to knowledge acquisition and learning. This approach is manifested in merging student experience inside and outside the classroom, which eventually results in shaping the 21st century lifelong learner. This paper presents an innovative student development model based on the constructivist approach; showing the collaboration between student affairs and academics. Furthermore, it illustrates a unique experience implemented at Effat University for developing the student as a whole person. This is done to complement the student's academic experience with the necessary skills and abilities derived from Effat University mission that focuses on creating women leaders. The student finds herself in a journey of self development and growth throughout the course of her study until graduation. At the time of graduation, she is equipped with all what it takes to be a successful career woman and a leader of change in her society.
Characterization, simulation and macro-modelling of vertical Hall devices

A new macro-model of a vertical Hall sensor and the corresponding procedure for macro-model parameter extraction are presented. The active volume of the sensor is defined by the process simulation. The modulation effects of the active volume of the sensor and the sources of the non-linearity of the sensor response are examined by means of device simulation. In accordance with the simulation results and measured data a macro-model based on the sensor physics is built. The parameters of this model are extracted from the device simulation data.
Challenges in Multilevel Wayfinding: A Case Study with the Space Syntax Technique

In this paper we reanalyse an experiment on wayfinding in complex multilevel buildings, in the light of formal measures derived from space syntax. The empirical study compared the performance of experienced and inexperienced participants in a set of wayfinding tasks, and identified specific strategies for vertical navigation. Inexperienced participants predominantly rely on a central-point strategy, while experienced ones have more accurate knowledge and plan more effectively. This is reflected by space-syntax-based route measures: routes of inexperienced users showed higher values of connectivity and integration as well as step depth to goal. Usability deficits of the complex building could be tied to formal analysis, revealing additional problems of the setting. Special emphasis is put on proper modelling of the vertical connections between the floors in visibility graph analysis. On the basis of the space syntax results, two layout redesigns are proposed, which provide improvements both for general navigability and for orientation at specific locations.
Reducing Under-Five Mortality in India - A Review of Major Encumbrances and Suggestions for Progress

About 128 million of India’s 1.2 billion populations are aged less than 5 years. India’s under-five mortality rate fell from 2.2 million (123/1000 live births) in 1990 to 1.726 million (63/1000 live birth) in 2010. Based on current trends, India is unlikely to meet the 67% reduction in under-five mortality rate by 2015, compared with 1990 baseline (i.e. less than 41/1000 live births), as stipulated in Millennium Development Goal (MDG) 4, Target 4A. This article examines six major factors encumbering efforts to reduce India’s under-five mortality: poorly delivered antenatal and obstetric care; inadequacy of well-resourced birthing resources; weak immunisation programs, particularly for measles and pneumonia, inadequate prevention and treatment of pneumococcal infections, and; chronic childhood undernutrition. Initiatives to address these obstacles are suggested. The authors posit that a well-resourced and efficiently managed continuum of care approach operated within a strong Indian health system, extending from Pre-pregnancy, Pregnancy, Birth, Postnatal, and Childhood is more likely to accelerate progress towards sustainable reductions in India’s under- five mortality compared with the status quo. Particular emphasis should be focussed on improving child care during the neonatal period, given the rising proportion of under-five deaths as percentage of total deaths prior to age 5 years.
General Methodologies for Neural Network Programming

This paper presents a general methodology for designing neural networks by using a priori information on the process under study. The approach is especially useful in developing efficient neural networks for the applications where full-scale models are available but too complicated to implement on conventional computer systems. Traditional neural network development techniques are known to have considerable disadvantages, including a tedious (trial-and-error-based) design process and a long training phase for most real world problems. The presented network design paradigm overcomes these well-known shortcomings. The paper also illustrates the method's application to a real-world problem on the estimation of milling forces in an ideal machining process.
Control of continuous-time nonlinear systems using neural networks

The main objective of this paper is to discuss training neural networks for control of continuous-time nonlinear systems. Here multilayer neural networks are employed, which are trained by dynamic and static backpropagations. The control with feedback linearization is applied to solving control of a nonlinear dynamical system. A simulation is given to complete the discussion.
A Trustworthiness Based Ad-Hoc Secure Interoperation Method

A trustworthiness-based ad-hoc secure interoperation method is proposed, in which the concept of trustworthiness is introduced to describe the probability of proper collaboration. The trustworthiness of an autonomic domain on a user is decided jointly by direct experiences of interactions and other domains' assessments on the user. Only the users who satisfy the requirements of target domains' trust policies have the privileges to access entry roles. Records of a user's malicious actions will decrease his trustworthiness and then accordingly reduce his privileges. Target domain uses weighted majority algorithm to update recommender's trustworthiness, which is reduced by unfair ratings. Experimental results show that this method can effectively resist cheating and malicious actions.
Designing for Knowledge Integration: The Impact of Instructional Time

Science educators face constant tradeoffs between allocating time to important topics and including more topics in the curriculum. We study 3,000 students experiencing 4 increasingly streamlined versions of a computer-enhanced middle school thermodynamics curriculum to investigate the impact of instructional time on knowledge integration. Knowledge integration refers to the process of adding new ideas and sorting through connections to develop a cohesive account of scientific phenomena. Our analyses contrast performance on inquiry assessments that require knowledge integration with performance on multiple-choice items. The results show that decreasing instructional time is strongly and significantly related to diminishing student knowledge integration around complex concepts. Whereas the inquiry assessments capture the impact of decreasing instructional time on knowledge integration, the multiple-choice assessments are relatively insensitive to these decreases. To explore further the process of knowledge integration, we follow 50 students through the full curriculum. We then analyze the performance of 1 representative student from middle school through high school. These case studies show why packing the curriculum with many science topics results in superficial understanding for many students. We show why deep understanding of science requires sustained study of carefully designed materials.
An image enhancement effect objective assessment method based on visual information fidelity

Assessment of image visual quality is of fundamental importance to numerous image and video processing applications. Visual information fidelity is a novel criterion that is based on modeling of natural scene statistics, image distortion and the human visual distortion. Traditionally, image QA algorithms interpret image quality as fidelity or similarity with a "reference" or "perfect" image. We apply the VIF method on image enhancement effect which takes distorted image as "reference" image instead of "perfect" image to assess the quality of enhanced image. It provides clear advantages over the traditional approaches because VIF index is combined with HVS features under certain conditions. In particular, it can be measured only rely on the original image and enhanced image. We validate the performance of our method with an extensive subjective study to show that it outperforms current methods in our testing.
A 6 Gb/s Low Power Transimpedance Amplifier with Inductor Peaking and Gain Control for 4-channel Passive Optical Network in 0.13 μm CMOS

This paper presents a 6 Gb/s 4-channel arrayed transimpedance amplifiers (TIA) with the gain control for 4-channel passive optical network in 0.13 ㎜ complementary metal oxide semiconductor (CMOS) technology. A regulated cascode input stage and inductive-series peaking are proposed in order to increase the bandwidth. Also, a variable gain control is implemented to provide flexibility to the overall system. The TIA has a maximum 98.1 ㏈Ω gain and an input current noise level of about 37.8 ㎀/㎐. The die area of the fabricated TIA is 1.9 ㎜ x 2.2 ㎜ for 4-channel. The power dissipation is 47.64 ㎽/1ch.
Soft-output demapper and Viterbi decoder for software-defined radio

Viterbi algorithm is commonly used in communication systems to decode convolutional codes. Soft decision demapping can be used to further improve Viterbi decoder performance. This paper presents implementation of soft-decision demapping and Viterbi decoder for software-defined radio (SDR). Fast simplified algorithms for soft demapping of four modulations common in satellite communications systems (BPSK, QPSK, 8-PSKand 16-APSK) were implemented. To increase software processing speed SIMD (single instruction multiple data) instructions were used.
Channel Estimation and Frequency Synchronization for a Multi-Antenna Wimax System

This paper develops several issues related to a multiple input multiple output - orthogonal frequency division multiplexing (MIMO-OFDM) system based on IEEE 802.16d standard. This standard just proposes a typical SISO system, and leaves as optional the development of a multiple input - single output (MISO) 2 times 1 scheme employing Alamouti space-time codification (STC). Apart from comparing both systems in terms of data transfer rate and bit error rate (BER), the inclusion of a second antenna in the receiver is studied. Following exactly the preamble structure provided for fixed broadband wireless OFDM access (IEEE 802.16d), several scenarios are studied: single input - single output (SISO) systems, MISO systems, (both applying and not applying STC) and MIMO systems (both applying and not applying STC). Therefore this study can be considered as an extension to the wireless metropolitan area networks (WMAN) standard, known as Wimax, which just proposes two of these five scenarios. In all of these communication schemes two algorithms are compared to obtain an accurate channel estimation. The first one is a maximum likelihood (ML) estimator in the frequency domain (Fernandez-Getino Garcia, 2004) and the second one is a least squares (LS) estimator in the time domain (Balamurali, 2004). Both of them are studied in terms of mean squared error (MSE) of the estimation and BER at the receiver. Moreover, algorithms for frequency offset estimation are also developed and analyzed both for SISO and MIMO systems based on IEEE 802.16d standard.
Voting-based Intra Mode Bit Skip Using Pixel Information in Neighbor Blocks

Intra coding is an indispensable coding tool since it can provide random accessibility as well as error resiliency. However, it is the problem that intra coding has relatively low coding efficiency compared with inter coding in the area of video coding. Even though H.264/AVC has significantly improved the intra coding performance compared with previous video standards, H.264/AVC encoder complexity is significantly increased, which is not suitable for low bit rate interactive services. In this paper, a Voting-based Intra Mode Bit Skip (V-IMBS) scheme is proposed to improve coding efficiency as well as to reduce encoding time complexity using decoder-side prediction. In case that the decoder can determine the same prediction mode as what is chosen by the encoder, the encoder does not send that intra prediction mode; otherwise, the conventional H.264/AVC intra coding is performed. Simulation results reveal a performance increase up to 4.44% overall rate savings and 0.24 dB in peak signal-to-noise ratio while the frame encoding speed of proposed method is about 42.8% better than that of H.264/AVC.
Frequency Count Attribute Oriented Induction of Corporate Network Data for Mapping Business Activity

Companies increasingly rely on Internet for effective and efficient business communication. As Information Technology infrastructure backbone for business activities, corporate network connects the company to Internet and enables its activities globally. It carries data packets generated by the activities of the users performing their business tasks. Traditionally, infrastructure operations mainly maintain data carrying capacity and network devices performance. It would be advantageous if a company knows what activities are running in its network. The research provides a simple method of mapping the business activity reflected by the network data. To map corporate users’ activities, a slightly modified Attribute Oriented Induction (AOI) approach to mine the network data was applied. The frequency of each protocol invoked were counted to show what the user intended to do. The collected data was samples taken within a certain sampling period. Samples were taken due to the enormous data packets generated. Protocols of interest are only Internet related while intranet protocols are ignored. It can be concluded that the method could provide the management a general overview of the usage of its infrastructure and lead to efficient, effective and secure ICT infrastructure.
Aqueous Humor Levels of Different Interleukins 1-β, 2, 6 and 10, Tumor Necrosis Factor-α and Vascular Endothelial Growth Factor in Uveitis Treated with Adalimumab.

Purpose: To assess changes in aqueous humor levels of different interleukins (IL), tumor necrosis factor (TNF)-α and vascular endothelial growth factor (VEGF) in patients with uveitis treated with adalimumab. Methods: In this study, 24 aqueous humor samples including 12 pre- and post-treatment samples from 6 patients with uveitis treated with subcutaneous adalimumab and 12 samples from patients with cataracts (serving as controls) were evaluated. The levels of IL-1β, IL-2, IL-6, IL-10, TNF-α and VEGF were measured using a Luminex ® 200™ flow cytometer (Merckmillipore, Merck KGaA, Darmstadt, Alemania) and a highly sensitive ELISA system. Results: The levels of IL-1β, IL-2, IL-6 and IL-10 in the aqueous humor before and after treatment with adalimumab did not show significant differences. Aqueous VEGF levels significantly reduced after treatment with adalimumab (P = 0.028). Aqueous TNF-α levels did not significantly change after treatment with adalimumab, however the post-treatment level was significantly higher in patients as compared to control subjects (P = 0.032). IL-2 showed significantly higher levels in uveitis patients before treatment as compared to controls (P = 0.024), while its post-treatment levels were almost normalized. Conclusion: Decrease in the aqueous humor levels of VEGF and IL-2 after treatment with systemic adalimumab indicates that anti-TNF-α therapy induces modifications of some inflammatory mediators involved in the pathogenesis of uveitis. Aqueous humor samples may be useful to assess the effect of adalimumab on intraocular inflammation through measurement of cytokines.
Irrational Use of Antibiotics and Antibiotic Resistance in Southern Rural Bangladesh: Perspectives from Both the Physicians and Patients

Aims: Antibiotic resistance is one of the widely recognized public health challenges in Bangladesh. The present study was aimed to analyze the current status of irrational use of antibiotics in rural Bangladesh and to explore the views from both physicians’ and patients’ perspective. Study Design: Population based survey. Place and Duration of Study: The survey was conducted among 6,000 patients and 580 physicians in the rural areas of Dhaka and Rajshahi divisions of Bangladesh from July 2012 to December 2012. Methodology: The survey followed a face-to-face interview protocol. 24 Upazila Health Complexes and 112 Union Health Centers of Dhaka and Rajshahi divisions were conveniently surveyed by trained volunteer interviewers. Two separate survey questionnaires were developed for physician and patient survey. Results: From the physician survey it was found that significantly more doctors prescribe antibiotics in suspected infections (P<.0001). Around forty-four (44.1) percent doctors prescribe antibiotics in cold and fever before diagnosis. A significant proportion of physicians never receive any feedback about the antibiotic they prescribe (31.9%, P<.0001) and more than 50% doctors claimed that they receive feedback occasionally, not always (P<.0001). According to the physician’s patient non-compliance is the main cause of antibiotic resistance in the country (68.8%). Though 48.6% patients think that it is important to strictly follow the doctor’s prescription, a significant percentage believe that it is not always necessary (26.7%, P<.0001) and more than 50% patient stop taking the antibiotic as soon as the symptoms disappear, while only 25.2% patient complete their full course. Only 6.3% patients consult their doctor if they miss the dose of an antibiotic and more than 50% take the next dose on time (P<.0001). When a drug does not work the patient usually consider the doctor is incompetent (25.6%) and many (24.5%) believe that the quality of the drug is not up to the mark. Conclusion: The result of this survey indicates that the antibiotics are used among the rural people in irrational way. To overcome this situation close supervision of the relevant authority is required in order to minimize the growing antibiotic resistance in Bangladesh.
GPU Matrix Sort (An Efficient Implementation of Merge Sort)

Sorting is one of the frequent used operations in computer science. Due to highly parallel computing nature of GPU architecture; it can be utilized for sorting purpose. We have considered the input array that is to be sorted in a 2D matrix form and applied a modified version of merge sort on that matrix. This modification leads to a much efficient sorting algorithm with reduced complexity. Therefore a lot of work has already been done to improve the efficiency of sorting algorithms. In this paper We have used the GPU architecture for solving the sorting problem.
The Latest Research Progress of Personalized Information Recommend Based on the Tag

In web2.0 era, tag marks that users have become from passive consumers into active information creators. Users can create and use any tags which represent their will freely on the Internet; they can also share all kinds of tags which other users have created. At the same time, personalized information recommendation can solve the problem of the flood of information, so how to conduct personalized information recommendation based on tags has become the focus of many scholars. This paper summarized three categories about the information recommendation model based on tags: Graph theory- based model, Tensor-based model and Topic-based model, then the author put forward the defects of the existing model and the problems that need to be solved in the future, such as how to reduce noise, how to use social network analysis method to study social tag system and so on.
Vector Quantization Multi-User Scheduling in Broadcast Channel

This paper deals with the research on user scheduling algorithm in downlink MIMO systems with limited feedback of channel state information (CSI). In this paper, we use vector quantization to simplify the procedure of user selection. By quantizing MIMO channel into several un-overlapped channel regions, we can get semi-orthogonal region sets with predefined threshold. Then, based on the semi-orthogonal region sets, we present a low complexity user scheduling algorithm. Simulation results show that the achieved sum rate by the presented algorithm can achieve nearly optimal sum rate while with much lower complexity than that of the existing algorithms
Classifying words for improved statistical language models

A method for assigning a word to many classes based on the context in which the word occurs is presented. A trigram language model is used to determine the classes which are called statistical synonyms for that word. This classification method is used to build an adaptive language model that incorporates unknown words after their first occurrence by using their statistical synonyms in determining the model's probabilities for the added words. It is shown that the dynamic coverage of the language model increases significantly with a rather low perplexity on the added words. <<ETX>>
Wie läuft die Entstehung und Progression eines Optikusschadens bei einem primären Offenwinkelglaukom ab und welche Bedeutung haben diese Erkenntnisse für die Glaukomdiagnostik?

Zusammenfassung Aufgrund der meist langwierigen Prozesse bei der Entwicklung einer glaukomatösen Optikusneuropathie kommt es bei den retinalen Ganglienzellen nicht spontan zu einem Zelluntergang, sondern zu einem schleichenden Zelltod. Daraus begründet sich die Vorstellung, dass funktionelle Tests besser geeignet sind für die Frühdiagnostik eines primären Offenwinkelglaukoms als bildgebende Verfahren, die erst dann Veränderungen aufzeigen können, wenn die retinalen Ganglienzellen und mit ihnen die retinalen Nervenfasern am Ende der biologischen Kaskade zugrunde gegangen sind. Durch neue perimetrische Verfahren wird die Frühdiagnostik beim Glaukom verbessert.