Miracle-dz/UniFAR-FTUs huggingface dataset:
Alphabet Sign Language Recognition Using Leap Motion Technology and Rule Based Backpropagation-genetic Algorithm Neural Network (Rbbpgann)

Sign Language recognition was used to help people with normal hearing communicate effectively with the deaf and hearing-impaired. Based on survey that conducted by Multi-Center Study in Southeast Asia, Indonesia was on the top four position in number of patients with hearing disability (4.6%). Therefore, the existence of Sign Language recognition is important. Some research has been conducted on this field. Many neural network types had been used for recognizing many kinds of sign languages. However, their performance are need to be improved. This work focuses on the ASL (Alphabet Sign Language) in SIBI (Sign System of Indonesian Language) which uses one hand and 26 gestures. Here, thirty four features were extracted by using Leap Motion. Further, a new method, Rule Based-Backpropagation Genetic Al-gorithm Neural Network (RB-BPGANN), was used to recognize these Sign Languages. This method is combination of Rule and Back Propagation Neural Network (BPGANN). Based on experiment this pro-posed application can recognize Sign Language up to 93.8% accuracy. It was very good to recognize large multiclass instance and can be solution of overfitting problem in Neural Network algorithm.
Design of live video streaming,recording and storage system based on Flex,Red5 and MongoDB

In order to improve the conventional situation that network video does not play smoothly during live or ondemand and find storage strategy of mass video data,this paper presented an overall design scheme of a real-time live video recording and storage system. The open source streaming media server Red5 and the rich Internet application technology Flex were utilized to achieve live video streaming and recording. The recorded video data would be stored in the open source NoSQL database MongoDB. The experimental results illustrate that the platform can meet requirements of multi-user access and data storage.
The Role of Doctoral Study in the Professional Path of Academics

To prepare the next generation of academics is considered the primary function of doctoral education. This study attempts to identify the role of doctoral study on the path of academics. The data were collected by the in-depth interview of Ph.D. graduates who had achieved their doctor degree of education successfully at Palacký University Olomouc in the past decade. The life stories of seven interviewees were included in analyzing by coding process. Six categories were generalized under three themes based on the grounded theory.
Foundation Year 1 doctors’ experience and confidence in catheterisation: A multicentre survey

Objective: This survey sought to review the experience gained by doctors during their first year of training and their confidence in performing this procedure. Materials and methods: All Foundation Year 1 doctors in three hospitals in Scotland were invited to complete an online survey towards the end of their first year of training. The survey asked participants about the number of catheterisations performed, confidence with this procedure and whether they had been signed off as competent. Results: In total, 149 doctors were invited to complete the questionnaire and 98 (65.8%) responded. At the time of survey completion, 97.9% and 93.6% of respondents were signed off as competent for male and female catheterisation respectively. A total of 55.7% had performed fewer than five catheterisations, 28.9% had performed 5–10 and 15.5% had performed more than 10. We found 25.8% were very confident about performing an average-difficulty catheterisation and 6.3% were very confident about performing an above-average difficulty catheterisation. Overall, 7.1% of respondents were very confident about changing a suprapubic catheter. Conclusion: Despite being deemed competent by the end of first year of training and meeting curriculum requirements, confidence levels in performing catheterisation remains low and many doctors do not have sufficient experience and confidence for daily practice. Level of evidence: 2c
Adaptive Canny edge detection algorithm

The traditional Canny edge detection algorithm exists the defect losing details of the edge,so this paper proposed an improved Canny edge detection algorithm. The algorithm used adaptive filter to eliminate the noise. It calculated preserving the more edge information while filtering the noise,the thresholds of Canny algorithm automatically according to the mean of variance and gray-scale. The results demonstrate that the method not only can detect more detail of the edge,but also can have a strong self-adaptability.
Computer-Assisted Research Writing in the Disciplines

It is arguably very important for students to acquire writing skills from kindergarten through high school. In college, students must further develop their writing in order to continue on to graduate school successfully. To obtain their graduate degree, they have to be able to write good theses, dissertations, conference papers, journal manuscripts, and other research genres. However, opportunities to develop research writing skills are often limited to traditional student-advisor discussions (Pearson & Brew, 2002). Part of the problem is that graduate students are expected to be good at such writing, because if they “can think well, they can write well” (Turner, 2012, p. 18). Education and academic literacy specialists oppose this assumption. They argue that advanced academic writing competence is too complex to be automatically acquired while learning about or doing research (Aitchison & Lee, 2006). Aspiring student-scholars need to practice and internalize a style of writing that conforms to discipline-specific conventions, which are norms of writing in particular disciplines, such as chemistry, engineering, agronomy, and psychology.
Real Time Personalization Recommendation Based on Classification

To using user path characteristics to provide the personalization recommendation, this paper presents a new approach of real time personalization recommendation based on the classification approach in web usage mining. The sequence access transaction set is generated by the user access transaction grammar defined by this paper. The grammar is educed from the regular grammar and can get the sequence characteristic from the user access transaction and the result can facilitate the classification. The set can be used to train a classifier that can process the multiple classes. The k -nearest neighbor classification approach is chosen. Authors use recommendation engine to identify the active user, his current access sequence, and his next request. The sequence and the next request are input into the trained classifier to get the new possibly accessed web page. The recommendation web page address is annexed to the requested page and it is returned to the user by the engine. Each user is provided personalization web recommendation. Authors' approach does not require the profile information about the user and the recommendation process will not disturb the user. It can provide the real time personalization recommendation and the experiment manifest the approach is successful in speed and precision.
School bullying and symptoms of depression

Methods: The research included 284 teenagers, of whom 145 (51.1%) were females and 139 (48.9%) males, aged between 13 and 18 years with an average age of (M = 15.5) years and a Standard Deviance 1.2 (SD=1.2) The data were collected through the use of Children’s Depression Inventory (CDI, Kovacs, 1978) and the Reciprocal Relationship Assessment Questionnaire (PRQ) (Rigby & Slee, 1994) and further analysed with the SPSS. 18 package. As the distribtution was not normal, Spearman’s rho and analysis of frequencies were used to test the links between bullying behaviors and depression.
The Implement of LSB Steganography Algorithm based on Image

As the rapid development of multimedia technology, information security has become more and more important, to prevent information from being intercepted and modified, has become a hotspot of research in the field of information security. Here introduced the concept and development of information hiding technology, analyzed the theory of the most common steganography algorithm of LSB, and achieve this algorithm with MATLAB. In the end, development trend of staganography was pointed out.
Assessment of some measurement methods for the inspection of spray application equipment

Several measurement methodologies used for the determination of the uniformity of the spray distribution are assessed. Nozzle adaptors used for flow rate measurements of the nozzles mounted on the sprayer cause a deviation of the measured values from the real ones, mainly in flat fan nozzles working at low pressures. According to the inspection standard, the transverse distribution uniformity in a horizontal boom sprayer can be measured in two ways. If a horizontal patternator is used, less favourable inspection results are found than if the distribution uniformity is estimated in the same conditions from the nozzle flow rate and pressure drop measurements. Finally, it was seen than the shorter overlapping length for the measurement of the boom transverse distribution established in the current standard, provide more favourable inspections compared with the overlapping length of the former one. The results of this work should be taken into account when establishing inspection procedures by the authorities and could also provide useful information for a future revision of the technical standards.
Evaluation of Interaction Activities Between Students and Lecturer Using UUM Online Learning

Learning Management System (LMS) has become a necessity in the universities because it enhances the teaching and learning environment. Universiti Utara Malaysia (UUM) implements LMS since 2000 which was formerly known as Learning Zone and has recently been enhanced capability of the system and is known as UUM Online Learning. The system has a range of functions that support teaching and learning activities between lecturers and students. The interaction between lecturers and students in the LMS is very important. In Moore’s Transactional Distance Theory, interactions are categorized under student-lecturer, student-student, and student-content. Effective interaction will further help lecturers to assess the ability of students and students also can interact with their lecturer and their peer via the LMS without any constraints of time and place. The aim of this study was to evaluate some kind of activities in UUM Online Learning often used by lecturers and students to interact. The research employs a case study of two selected classes that fully utilized UUM Online Learning. The first class consists of 39 students and second class has 95 students. The results showed that the activities of interaction are widely used by lecturers to interact with students. Among them are an online quizzes, online assignment submission and grading, class discussions and forums. Students’ satisfaction is considered an important factor in evaluating the interaction activities. The result from the selected classes indicated that students were satisfied with all the interaction activities with their lecturers. Students, however, have difficulties interacting with their peer due to technology barriers and attitude.
Optimizing rock cutting through computer simulation

This paper presents an original thermomechanical model of rock cutting with evaluation of tool wear. The model has been developed within the framework of the discrete element method, which is a suitable numerical method to study problems of multiple material fractures likes those of rock cutting. The paper presents brief overview of the theoretical formulation, calibration of the discrete element model, and a number of numerical results obtained in simulation of rock cutting processes typical for underground excavation, using both roadheaders and TBMs.
Aggregated multi-criteria model of enterprise management engineering, taking into account the social priorities of the region

The article is devoted to the development of an aggregated multi-criteria model of enterprise management engineering. The basis of the proposed approach is the understanding of the significance of a modern engineering enterprise not only for the economic, but also the social development of the region. The article focuses on the social priorities of the region in creating new jobs and increasing nominal wages at the enterprises of the machine-building complex. The model takes into account the main economic dependencies of the operation of the enterprise, as well as restrictions on the achievement of the values of the labor force required for the region and the average nominal wage. As the criteria of optimality, the maximization of the total profit for the period of profit, taking into account the profit tax, was chosen; the maximization of the minimum in time of return on capital (ROA) was taken. The software implementation and discussion of the calculation results confirmed the practical significance of the research carried out for the management of the region and the machine-building enterprise, and also outlined ways for its further improvement.
Application of computer science in bioinformatics

Bioinformatics is a newly\|developed crossing branch of science. Researchers and developers in computer science have recently been concerned with an urgent problem in their field as to how to bring about quick and good use of computer science in bioinformatics. Through an analysis of the present situations and futures prospects of computer application in this new science branch,t his article is to offer some inspirations for computer scientists to find more practical applications.
Effect of corrective feedback for learning verb second

Abstract This paper presents a detailed study on the role of corrective feedback (CF) in the development of second language (L2) oral proficiency. Learners practiced speaking with a computer-assisted language learning (CALL) system that employs automatic speech recognition (ASR) technology to provide CF. The system tracks learner behaviour by logging the system-user interactions. Two language learning conditions are compared. In the CF condition learners received immediate, automatic CF on the grammaticality of their spoken output. In theOCF condition, learners practiced speaking with the option to self-correct. The target structure under investigation is Dutch verb second (V2) in the main clause. The results show that learner proficiency improved in both conditions. The CF condition shows an additional benefit for learning that is related to the learner’s initial knowledge of the target structure (which we call V2 proficiency). Learners at a lower V2 proficiency level benefitted more from practice with CF than learners in the NOCF condition. Learner evaluations are in line with these results: both the CF and the NOCF groups positively evaluated practice with the system, but the CF condition was preferred by learners starting at a lower V2 proficiency level. For more information on these outcome measures, we investigated the learners’ behaviour during practice. The two groups were found to receive equal amounts of input, but learners in the CF condition produced more (grammatically correct) output during treatment. We found that the CF group repaired their errors in fewer attempts as they progressed through practice. Learners in the NOCF condition generally did not (attempt to) repair their errors. However, the learners answered correctly more often as they progressed in the training. The log data, therefore, shows learning of the target structure in both conditions. We discuss these results and how learning outcome is related to learner behaviour.
Signal reconstruction with a small set Gabor filters

A normalization algorithm is proposed that improves the reconstructions of signals. After decomposing a signal in even linear bandpass filtered signals and a low-pass residual, it can be reconstructed reasonable well for a good choice of filters. However, to obtain good results the filter parameters must be chosen in such a way that they cover the frequency domain sufficiently well. This is often difficult for a small set of filters. We derive and demonstrate that in many situations it can be profitable to normalize the reconstructed image with respect to two global statistical parameters of the original image.
A Conventional Orthography for Maghrebi Arabic

Maghrebi Arabic is the set of dialects of the Arabic language spoken in the Maghreb (Tunisia, Algeria, Morocco, Libya and Mauritania). This set of dialects is under-resourced and has neither a standard orthography nor large collections of written text and dictionaries. Actually, there is no strict separation between Modern Standard Arabic, the official language of the government, media and education, and Maghrebi Arabic; the two exist on a continuum dominated by mixed forms. In this paper, we present a conventional orthography for Maghrebi Arabic, following a previous effort on developing a conventional orthography for Dialectal Arabic (or CODA) demonstrated for Egyptian, Tunisian and Algerian Arabic. We explain the design principles of CODA and provide a detailed description of its guidelines as applied to Maghrebi Arabic.
Using Socio-Spatial Context in Mobile Cloud Process Offloading for Energy Conservation in Wireless Devices

Abstract The high proliferation of on-line gaming along with the high demands of availability of network resources, created the need for the development of Cloudified services that will augment computation capabilities of mobile devices. To this end, this work elaborates on the design, the development and the comparative evaluation with other similar models, as well as with real-time comparisons through emulators, of a process-offloading scheme that is based on a mobile opportunistic cloud computing approach. According to the proposed approach, each mobile device with access to interactive -delay sensitive- multimedia content (i.e. online gaming with processing power requirements) exploits several network-centric parameters, by using Nano-Mobile Data Centers for an interactive, collaborative and real-time manipulation of the available resources. The communication and the social context is used by the mobile nodes with other communication related parameters, towards achieving the efficient execution of the offloading process in order to support adequate quality of service. The proposed scheme allows interactive mobile users to efficiently exploit their resources, while the processes that cannot be locally handled (by each device), are effectively offloaded. The scheme aims at prolonging the lifetime of each mobile device and maximizing the efficiency in running context interactive applications. The efficiency of the proposed scheme is validated through comparative performance evaluations with other similar schemes, indicating the level of the mobile nodes lifetime extensibility that is offered, in contrast to existing approaches.
A Research on Web Content Extraction and Noise Reduction through Text Density Using Malicious URL Pattern Detection

A Web Page has large amount of information including some additional contents like hyperlinks, header footer, navigational panel; advertisements which may cause the content extraction to be complicated. Page Segmentation is used to detect the noisy content block by detecting malicious URL from Web Pages. Main aim of this research is detecting malicious URL during content extraction by checking different patterns of URL. Performance is analysed based on precision, recall, execution time and noise detected using proposed algorithm.
Ecient Data Deduplication System Considering File Modication Pattern

In a data deduplication system, the performance of data deduplication algorithms are varying on the condition of le contents. For example, if a le is modied at the end of le region then Fixed-length Chunking algorithm superior to Variable-length Chunking in terms of computation time with similar space reduction result. Therefore, it is important to predict in which location of a le is modied in a deduplication system. In this paper, we discuss a new approach to one of the key methods that is invariably applied to data deduplication. The essential idea is to exploit an ecient le pattern checking scheme that can be used for data deduplication. The contribution of this paper is to nd in which region of a le is modied using le similarity information. The le modication pattern can be used for elaborating data deduplication system for selecting deduplication algorithm. Experiment result shows that the proposed system can predict le modication region with high probability.
Online Spam Filtering Based on Ensemble Learning of Multi-filter

Spam filtering is defined as a task trying to label Emails with Spam or Ham in an online situation,which is essentially a self-learning procedure with user's feedback.There are already some simple filters applying the linguistic features or behavior features.In this paper,we use the ensemble learning method to combine multi-filter and achieve a higher performance than the single one could.The experiment result shows the single feature learning is fast and the ensemble learning has better effects,in which the proposed SVM ensemble method has the highest performance.
Formalizing the Evaluation of OCL Constraints

Domain-specific modeling has growing importance in many fields of software enginering, such as modeling control flows of data processing, or in man-machine systems. Customizable language dictionary and customizable notations of the model elements offered by domain-specific technologies make software systems easier to create and maintain. However, visual model definitions have a tendency to be incomplete, or imprecise; the definitions can be extended by textual constraints attached to the model items. Textual constraints can eliminate the incompleteness stemming from the limitations of the structural definition as well. The Object Constraint Language (OCL) is one of the most popular constraint languages in the field of UML and Domain Specific Modeling Languages. OCL is a flexible, yet formal language with a mathematical background. Existing formalisms of OCL does not describe dynamic behavior of constraints. Our research aims at creating an OCL optimization solution and prove its correctness formally. However, the shortcomings of the existing formalism has led us to create a new formalism. The paper presents OCLASM, a new formalism for OCL, which can describe both the semantics and the dynamical behavior of the language constructs, thus, it is capable of describing proofs of optimization algortihms. OCLASM is based on the Abstract State Machines technique.
A Generative Learning Method for the Recognition of Blurred Characters Taken by Portable Cameras

あらまし 近年,ディジタルカメラ,カメラ付携帯電話が普及しており,それらの機器を用いた文字認識技術 の実用化が期待されている. しかし,撮影された画像は低解像度なものになりやすく,更にぼけやぶれなどの影 響を受けるため,高精度な認識は難しい. 我々の提案する生成型学習法は,人工的に劣化を加えて生成した画像 を学習データとすることで,特に携帯ディジタルカメラで問題となる光学的ぼけ,手ぶれ,低解像度化に対処す るものである. 従来は,学習データを撮影により収集する手法が用いられてきたが,撮影環境が異なるデータに 対応するために様々な条件のもとで学習データを収集する必要があり,実用上の難点がある. それに対し本手法 は,学習データを原画像から生成するため効率的である. また生成時のパラメータを変化させることで多種の劣 化に対応する学習データが生成できる. 本手法を用い,実際の劣化を学習に反映させることで,ぼけやぶれを含 む低品質文字の認識率が向上することを実験によって示した. キーワード 生成型学習法,文字認識,低品質文字,部分空間法