Miracle-dz/UniFAR-FTUs huggingface dataset:
A helicopter view of microwave application to chemical processes: reactions, separations, and equipment concepts

Abstract We present a helicopter view of microwave technology application to various reaction and separation processes, including liquid-phase organic syntheses, gas-solid catalytic reactions, polymerizations, extraction, distillation, crystallization, membrane separation, and adsorbent regeneration/dehydration. The overarching aim is to demonstrate the breadth of potential applications of microwave technology to chemical industry, with particular attention to separations, as this is a less explored microwave application area. In this context, some key findings, opinions, and developments in the relevant literature are summarized. In addition, the present microwave equipment concepts for chemical processes are critically reviewed and new ones are put forward, as we believe that an important milestone in the road from laboratory-scale microwave experimentation to industrial-scale microwave-assisted chemical processing is the design and development of innovative microwave equipment concepts tailored for specific chemical processes.
Survey of traffic control protocols in ATM networks

Among the techniques proposed to implement broadband ISDN (B-ISDN), asynchronous transfer mode (ATM) is considered to be the most promising transfer technique because of its efficiency and flexibility. Traffic control protocols in ATM networks are surveyed. The topics covered include congestion control and priority schemes to support multiple classes of traffic in ATM networks. Various preventive control schemes proposed for ATM networks are examined. Among them are admission control and bandwidth enforcement mechanisms, and, in particular, the leaky bucket method. Two priority schemes, a scheduling method and a local congestion control scheme, are discussed. <<ETX>>
A Cryptographic Solution to Privacy-Preserving Two-Party Sign Test Computation on Vertically Partitioned Data

Statistical hypothesis test is an important data analysis theory that has found applications in various research fields. It provides a theoretical foundation to determine whether sufficient evidence exists to reject hypothesis for the trial using experimental results, in order to make a decision. In this paper, we address one of the fundamental test theories: the Nonparametric Sign Test, under the privacy-preserving context. In this context, two parties, Alice and Bob, would like to perform a sign test on their joint dataset, but neither of them is willing to disclose their private raw data to the other party. More specifically, this paper addresses the problem where the joint dataset consists of two vertically partitioned datasets. Our previous work [14] has addressed this problem using data perturbation techniques. However, in a case when the privacy of individual data objects and data subjects are of high concern, using data perturbation techniques may not be sufficient. This paper proposes an alternative solution to this problem by employing an additive homomorphic encryption scheme and an on-line STTP. We show that this solution can offer better privacy preservation, in terms of individual data confidentiality and individual privacy, than the previous solution. A security comparison with TTPV and P22NSTV solutions is also presented.
A TV Camera System Which Extracts Feature Points For Non-Contact Eye Movement Detection

This paper proposes a highly efficient camera system which extracts, irrespective of background, feature points such as the pupil, corneal reflection image and dot-marks pasted on a human face in order to detect human eye movement by image processing. Two eye movement detection methods are sugested: One utilizing face orientation as well as pupil position, The other utilizing pupil and corneal reflection images. A method of extracting these feature points using LEDs as illumination devices and a new TV camera system designed to record eye movement are proposed. Two kinds of infra-red LEDs are used. These LEDs are set up a short distance apart and emit polarized light of different wavelengths. One light source beams from near the optical axis of the lens and the other is some distance from the optical axis. The LEDs are operated in synchronization with the camera. The camera includes 3 CCD image pick-up sensors and a prism system with 2 boundary layers. Incident rays are separated into 2 wavelengths by the first boundary layer of the prism. One set of rays forms an image on CCD-3. The other set is split by the half-mirror layer of the prism and forms an image including the regularly reflected component by placing a polarizing filter in front of CCD-1 or another image not including the component by not placing a polarizing filter in front of CCD-2. Thus, three images with different reflection characteristics are obtained by three CCDs. Through the experiment, it is shown that two kinds of subtraction operations between the three images output from CCDs accentuate three kinds of feature points: the pupil and corneal reflection images and the dot-marks. Since the S/N ratio of the subtracted image is extremely high, the thresholding process is simple and allows reducting the intensity of the infra-red illumination. A high speed image processing apparatus using this camera system is decribed. Realtime processing of the subtraction, thresholding and gravity position calculation of the feature points is possible.
Modélisation et Traitement Informatique de la Synonymie

This paper deals with automatic structuring of semantic values in a dictionary of synonyms. The data we used were first extracted from seven French published dictionnaries of synonyms and then merged to obtain the files we worked on. We explain here why a discrete mathematic representation of synonymic relation is not sufficient to produce a semantic structure (that represents the different meanings of a term but also their overlapping). Then we propose a continuous representation (using data analysis) that ables the machine to produce for each term its semantic values. The system also labels these values with prototypic synonyms and detects synonyms that share different semantic "axes" with the headword. It should be noted that these semantic spaces are obtained automatically for each headword from a homogeneous list of synonyms.
Standardization efforts in optical networking focused on architecture and signaling issues

This paper summarizes the present state of optical networking, whereabouts of the optical network by which IP-centric networks carry the traffic. By start out from the assuming that the Internet transport infrastructure is moving towards a model of high speed routers interconnected by optical core networks, various technical issues mainly on optical network architecture and signaling standardization trends are presented in this article. Also, the author present the concepts of generalized multiprotocol label switching (GMPLS) in accordance to the future direction of deploying the IP over optical networks.
Constructing a Consumption Model for Malaysian Consumers

The objective of this research is to construct a consumption model for Malaysian consumers.The research is important for Malaysian national agenda, especially, in achieving a societal integrity, social cohesion, the vision of 2020, and developed country per capita income, with the slogan of “1 Malaysia, People First, Performance Now”. The consumption pattern of Malaysian consumers has changed markedly since 2005 as shown by several indicators such as consumer price index (CPI), per capita income and inflation rate.The per capita income for Malaysia has risen but at a very slow pace. It was USD5372 in 2005 and at the end of 2013 it has amplified to USD6765, a rise of 26 per cent. Therefore, Malaysia has to work harder by 121 percent to achieve the 2020 target of USD15,000 per capita income. Furthermore, as compared to per capita income of the consumers, the rise in consumer prices was incomparable. The consumer price index (CPI) increased from 95.4% in year 2000 to 122.8% in 2013.This implies that the consumer have to pay a higher price for purchase of consumer products nowadays.It has been a source of dissatisfaction among consumers.The price hike was triggered by a few factors such as the increase of the oil palm, rubber and fuel prices.
An Improved Detection Technique for Spread Spectrum Audio Watermarking with a Spectral Envelope Filter

We propose an improved algorithm for detecting audio watermarks based on a spread spectrum in the spectral domain. Since the energy of a watermark is much smaller than that of the cover audio data, pre‐processing to reduce the effect of the cover data is needed to reliably extract watermarks. We introduce a spectral envelope filter as a preprocess that enhances detecting performance by filtering out the intrinsic spectral character of cover data. The proposed watermarking structure can be easily included in the compression system and can extract watermarks from partially decompressed spectral data. Our experimental results demonstrate that with a bit error rate of around 10 dB against general attacks, the proposed detecting scheme works better than detectors without the spectral filter.
Learning dialogue strategies within the Markov decision process framework

We introduce a stochastic model for dialogue systems based on the Markov decision process. Within this framework we show that the problem of dialogue strategy design can be stated as an optimization problem, and solved by a variety of methods, including the reinforcement learning approach. The advantages of this new paradigm include objective evaluation of dialogue systems and their automatic design and adaptation. We show some preliminary results on learning a dialogue strategy for an air travel information system.
Agrometeorological support of fruit production: application in SW Slovenia

Fruit growing in Slovenia has become one of the more important agricultural production branches over the last two decades. Due to climate variability over a relatively small area of 20,000 km2, irrigation practices are not only important but also indispensable agrotechnical measures for obtaining permanent, high quality crop yields in the northeastern and southwestern parts of the country. Hence, accurate estimation of water consumption by agricultural crops with the inclusion of metorological monitoring is essential in the field of water management. As a decision support tool, the Slovenian Agrometeorological Information System (SAgMIS) developed by Agrometeorological Department in the Environmental Agency of the Republic of Slovenia (EARS) and introduced 10 years ago has improved significally over the last two years. Transfer of actual and forecasted agrometeorological data to the end users has been quick and accurate, with the last version of mobile data dissemination in testing use. A case study of water use by irrigated peach trees in the plantation orchards of lower Vipava valley was undertaken from 1996 to 2004. A variety of irrigation systems with diverse irrigation water applications was introduced for the purposes of studying irrigation water benefits derived from accurate weather data and forecasts. The results showed that important savings in the amount of irrigation water used, on an annual average of 20%, could be achieved with accurate and timely irrigation forecasts during the vegetation periods. Copyright © 2006 Royal Meteorological Society
Computer Ondersteunde Vreemde-Taalverwerving op de Hogere Niveaus

The interactive self-study programme (called CAVOCA: Computer Assisted VOCabulary Acquisition) is based on generally accepted theories about the mental lexicon (cf. Aitchison's Words in the Mind) and the "levels of processing" theory first advanced by Craik and Lockhart. The programme constitutes a systematic attempt to operationalize the theoretical analysis of the word learning process that recognizes various stages in this same process: learning about the various features of the word, embedding it in various networks, consolidation etc. leading to efficient lexical retrieval. With this end in mind, the words are presented in a variety of L2 contexts, enabling the learner to process the word intensively and facilitating long-term retention. The programme is intended as an alternative to more orthodox word learning techniques such as bilingual word lists with their disappointing long-term retention results. The programme has been contrasted in various experimental (differential treatment) settings with bilingual word lists, and the results confirm the theory concerning the structure of the mental lexicon in that a deeper level of processing results in better long-term retention.
Assessment in Open and Distance Learning System (ODL): A Challenge

Assessment is an integral part of the learning process. The traditional practice of assessment has changed to meet the need of the contemporary society. In this paper assessment strategies used in Open and Distance Education are discussed and constructive suggestions are given to meet the challenges of assessment. Recently we experience a paradigm shift in assessment both in face-to-face and ODL system. Content-based testing has shifted to performance-based assessment. Assessment is no longer used for grading and certification, rather it has linked with learning and skill development of the students. Instead of a single paper pencil test, a variety of techniques and methods are being increasingly conducted. In this context assessment in the ODL system has adopted a new shape to provide better assessment judgments to its students and at the same time helping teachers and administrators. Coping with the changing scenario in ODL we face challenges addressed extensively in this article.
Secured Authentication of Space Specified Token with Biometric Traits - Face and Fingerprint

This paper deals with the efficient authentication model using multimodal face and fingerprint on space specified token. Since space specified token occupies only small amount of data this proposal has been given to minimize the data storage in the card. Here the face images are encrypted and encoded into fingerprint images . The verification accuracy is also high and provides a cheap solution from spoofing and many other attacks.
The simulation of SAR image of nature scene

The remote sensing can help monitoring the nature scene, so it is very useful for agriculture engineering. This paper presents a method to simulate the SAR image of nature scene by the ray tracing and statistical method. The scene is composed of the tree and grass which would be modeled by this two method. The result shows that this method can simulate the SAR image effectively.
Optimization models for selection of programs, considering cost and reliability

The authors present two optimization models for decision support tools for selecting available programs in the market. Information on reliability and cost of the available programs are considered as basic criteria for the selection. These models apply to software packages that consist of several programs where each, upon execution, performs a different function as required by the user. The objective is to maximize the average reliability of the software package, considering the tradeoff between reliability and cost of the programs. In model one, redundancy of the programs is not considered; thus, the authors select one program for each function. In model two, redundancy is considered: thus, the authors identify the optimal set of programs for each function. They begin with a discussion of the underlying concepts that rationalize the composition of the models. >
A review on design, modeling and applications of computer experiments

In this paper, we provide a review of statistical methods that are useful in conducting computer experiments. Our focus is on the task of metamodeling, which is driven by the goal of optimizing a complex system via a deterministic simulation model. However, we also mention the case of a stochastic simulation, and examples of both cases are discussed. The organization of our review first presents several engineering applications, it then describes approaches for the two primary tasks of metamodeling: (i) selecting an experimental design; and (ii) fitting a statistical model. Seven statistical modeling methods are included. Both classical and newer experimental designs are discussed. Finally, our own computational study tests the various metamodeling options on two two-dimensional response surfaces and one ten-dimensional surface.
Adaptive model selection using orthogonal least squares methods

Least squares techniques are commonly used to estimate model parameters from observed data. Often, such data do not become available all at the same time but is rather the result of successive measurements at periodic intervals. In such a case, it is desirable to have methods for updating the parameter estimates using new data as it becomes available. This is particularly important if the underlying model is not stationary. Many algorithms for performing such recursive estimation exist and are widely used in many branches of adaptive signal processing and control theory. At the same time, especially if the model is nonlinear, the number of potential parameters can be extremely large and it is necessary to have some means of picking only the most significant parameters, and discarding the rest. Within the last decade efficient procedures for carrying out such model selection have been developed and are increasingly being used in nonlinear system identification. They have also been applied to a certain class of neural networks to minimize the number of neurons required to accurately model a given problem. The aim of this paper is to combine the above two techniques in order to give an algorithm which can adaptively adjust its choice of model parameters in the light of new data. An example of the application of this algorithm to the adaptive selection of radial basis centres in the prediction of chaotic time series is given.
The generalized postal model-broadcasting in a system with non-homogeneous delays

In many communication systems we may assume that every node is directly connected to every other node. It does not matter whether the system is a massively parallel computer where each processor is a node and the connectivity is achieved using a software communication library or if the system is the Internet where each node is a computer and the connectivity is achieved using IP. The postal model started with this assumption and in addition assumed that the process of delivering a message between two nodes takes a constant amount of time called the communication delay (greater than one unit of time), and that when a node sends a message or receives a message it wastes a single time unit. In this paper, we enhanced the postal model by removing the assumption that the communication delay is constant. Without this constraint. The broadcasting problem is NP-complete and therefore we study two directions. (i) We present heuristic algorithms and analyze them. (ii) We evaluate simple topologies of networks (by assuming large delays when there is not a direct connection). We have also tested the heuristic algorithms with simulations and compared them to the optimal solutions.
Tactile Audio Tools for Graphicacy and Mobility "A circle is either a circle or it is not a circle."

Just as literacy is a right for all, so too is graphicacy. Literacy and graphicacy should be linked. Some tools that may improve graphicacy levels are outlined. They are designed to enable visually impaired and sighted people to create, read and exchange graphical Information. The tools are a suite of programmes and integrated hardware called TAGD (DOS) and TAGW (WINDOWS), where TAG stands for Tactile Audio Graphics. A brief description of the main tools is presented.
Author-Topic-Sentiment Mixture(ATSM) model for Author's Sentiment Analysis

In this paper,we propose a probabilistic modeling framework,called Author-Topic-Sentiment Mixture(ATSM) model,which based on Latent Dirichlet Allocation (LDA) to include authorship information and sentiments information.The proposed model can reveal the sentimenttopic and author’s sentiment.Each author associated with a distribution of the sentiment-topics,and each sentiment-topic is associated with a distribution of the words.Unlike other approaches to sentiment classification which often require labeled corpora or sentiment seed words,the proposed ATSM model is unsupervised . We show sentiment-topics recovered and the author’s distribution of sentiment-topic by the ATSM model.We compare the performance with two other generative models for documents :LDA and ATM,and illustrative a possible application of the ATSM. Keywords-LDA; author-topic; ATSM; Sentiment analysis; probabilistic topic models;Gibbs sampling; LDA
Face Recognition Using Two Dimensional Discrete Cosine Transform, Linear Discriminant Analysis And K Nearest Neighbor Classifier

In this paper, a new Face Recognition method based on Two Dimensional Discrete Cosine Transform with Linear Discriminant Analysis (LDA) and K Nearest neighbours (KNN) classifier is proposed. This method consists of three steps, i) Transformation of images from special to frequency domain using Two dimensional discrete cosine transform ii) Feature extraction using Linear Discriminant Analysis and iii) classification using K Nearest Neighbour classifier. Linear Disceminant Analysis searches the directions for maximum discrimination of classes in addition to dimensionality reduction. Combination of Two Dimensional Discrete Cosine transform and Linear Discriminant Analysis is used for improving the capability of Linear Discriminant Analysis when few samples of images are available. K Nearest Neighbour classifier gives fast and accurate classification of face images that makes this method useful in online applications. Evaluation was performed on two face data bases. First database of 400 face images from AT&T face database, and the second database of thirteen students are taken. The proposed method gives fast and better recognition rate when compared to other classifiers. The main advantage of this method is its high speed processing capability and low computational requirements in terms of both speed and memory utilizations. DOI: http://dx.doi. org/10.11591/ij-ai.v1i4. 767 Full Text: PDF
Performance analysis for tracking of variable scale objects using mean-shift algorithm

Classic mean-shift trackers have no integrated scale adaptation, which limits their performance in tracking variable scale objects. By analyzing the similarity of object kernel histograms, we found that the changes of object scale and position within the fixed kernel make the Bhattacharyya coefficient monotonic decreasing. The work plays a guiding role in solving scaling problems within the mean-shift framework. © 2005 Society of Photo-Optical Instrumentation Engineers.
Pattern Oriented Software Development: Moving Seamlessly from Requirements to Architecture

Requirements Engineering (RE) deals with the early phases of software engineering namely requirement elicitation, modeling, specification and validation. Architecture of a software system emphasizes the structural constraints imposed on the application. Potential reuse in the form of software patterns are available for software designers to structure their applications. This paper proposes a pattern oriented methodology for software development. Using this approach, the skeleton of the application can be perceived up-front by using knowledge of previously identified patterns. Functional requirements of the application can subsequently be made evolving around this basic structure. The methodology thus bridges the gap between requirements specification and the architecture of the application. This approach not only leads to highly flexible and reusable design solutions, but also provides traceability of requirements in design solutions making maintenance less