Miracle-dz/UniFAR-FTUs huggingface dataset:
Telesurgical Robotics and a Kinematic Perspective

Minimally invasive surgery (MIS) has revolutionized the world of surgery. On one hand, it offered many revolutionary advantages; on the other hand, it proved to be a tedious and sophisticated technique for surgeons. Telesurgical robotics came forward to assist surgeons and made surgeries even further innovative, safer, and efficacious. Kinematic—a fundamental and foremost design step—acts as the lynchpin of performance of a surgical robot. It plays a decisive role and defines the capabilities and viability of a robot vis-à-vis its application. This chapter tries to understand the kinematic design approaches in practice so far and discusses their features and potential shortcomings. Some of the notable kinematic structures are explained in detail, and an all-inclusive consideration to the kinematic aspects of the existing designs has been given. Based on the key challenges identified, possible solutions are suggested, which is followed by future research directions and conclusion.
Local frequency adaptive filtering method based on SNR for InSAR interferogram

Phase filtering is one of the key steps in interferometric synthetic aperture radar; its precision will directly lead to the phase unwrapping quality, thereby affect generating DEM reliability. For original algorithm causes inaccurate result in unevenly distributed noise region, so local frequency adaptive filtering method based on SNR is proposed. The local SNR is based on frequency estimation window size, and variable window is used to filter phase, this can make the areas with low SNR strongly filter, while those with high SNR weakly filter. Using simulation and real data to do experiments, results show that this paper method not only can effectively reduce noise, but also can better maintain detail stripes.
PSYCHOLOGICAL CONTRACT BREACH , WORK ENGAGEMENT AND TURNOVER INTENTION Evidence from Banking Industry in Pakistan

Employees are one of the most important assets of an organization. In order to retain them, it is important to evaluate and analyze the exchange relationship of the employees and the organization, known as psychological contract. This study examines the impact of psychological contract breach on employees’ turnover intention with the mediating role of work engagement. An empirical study has been conducted to test the main effects and mediating hypothesis through Hierarchical Multiple Regression. A sample of 302 responses has been collected from private and public banks of Lahore. The results indicate that a negative relationship exists between psychological contract breach and work engagement. Similarly, work engagement negatively correlates with turnover intention of employees. Work engagement partially mediates the relationship between psychological contract breach and employees’ turnover intention. Therefore, if employees perceive psychological contract breach then it leads to low work engagement and high turnover intention. Practical implications of the results have been discussed.
Register Value Prediction using Metapredictors

Value Prediction (VP) is a relatively new technique that increases performance by eliminating true data dependencies constraints. Value prediction architectures allow data dependent instructions to issue and execute speculatively using the predicted values. This technique is built on the concept of value locality, which describes the likelihood of a previously seen value’s recurrence within a storage location. This paper extends the dynamic value prediction by exploiting the concept of register centric prediction instead of instruction centric prediction. The value localities obtained on some registers of MIPS architecture were quite remarkable leading to conclusion that value prediction might be successfully applied, at least on these favorable registers. The idea of attaching a value predictor for the processor’s favorable registers might involve new architectural techniques for improving performance and reducing the hardware cost of speculative microarchitectures. The register value prediction technique consists in predicting registers’ next values based on the previously seen values. It executes the subsequent data dependent instructions using the predicted values and the speculative execution will be validated when the correct values are known. If the value was correctly predicted the critical path is reduced, otherwise the instructions executed with wrong entries must be executed again. In our previous work we implemented a hybrid predictor composed by a context-based predictor and respectively a stride predictor, working together. The context-based predictor had always priority; in this way the value generated by the stride predictor was used only if the context-based predictor cannot generate a prediction. Obviously this fixed prioritisation is not optimal. In this paper our goal is to increase the prediction accuracy using a dynamic prioritisation based on some confidences. We introduce several different metaprediction structures, in order to properly select the current best predictor: two non-adaptive metapredictors and an adaptive one, represented by a neural network. The experimental results obtained using metaprediction applied only to the best four favorable registers (having high value locality degrees) show an average prediction accuracy of 91.40%, measured on SPEC benchmarks. The accuracy gain obtained on these registers versus the old hybrid predictor is 2.27%.
The Effect of Psychological Traits, Compulsive Behavior and Techno Stress on Smartphone Usage

This paper presents the focus effects on four psychological traits which are locus of control, social interaction anxiety, the need for touch and materialism without considering the gender as indirect effect that can influence the compulsive usage and technostress. The proposed model has been empirically tested using collected data from a survey selected sample of respondents. The survey consists of questionnaire responded by 180 students with 90 % response rate among students in UiTM Puncak Perdana that located in Shah Alam, Malaysia. Data was analyzed by using descriptive analysis, correlation and multiples regression analysis other than common analysis technique. Findings indicated that all variables are positively associated with compulsive usage. Among them, there are three predictors have been identified which are locus of control (LOC), materialism (MAT) and need for touch (NFT) that contribute to more compulsive usage of smartphone. This findings contributed in terms of allowing us to understand the effects of psychological traits towards compulsive behavior and technostress. Besides, this study provides supplementary information which beneficial to the related industries, researchers and practitioners as discussed.
Genetic diversity, genetic variability, and path analysis for yield and its components in indigenous upland rice (Oryza sativa L. var. glutinosa)

Genetic diversity, genetic variability, and relationships of yield and its components are very important data for plant breeders that affect the design of a breeding program. Twenty-two upland rice genotypes were evaluated. The genotypes indicated significant variations in nine traits. High phenotypic and genetic coefficients of variation were observed for yield per plant, number of panicles per plant, and number of spikelets per panicle. High broad-sense heritability and genetic adaptations were found for yield per plant. Positive significant correlations were recorded between flag leaf length, number of panicles per plant, and number of spikelets per panicle. The highest direct effects on yield were attributed to the number of spikelets per panicle and the number of panicles per plant. Cluster analysis grouped the 22 genotypes into groups I, II, and III, and the outgroups consisting of nine, five, six, and two genotypes. These results may facilitate upland rice breeding programs to improve yield.
Mathematical User Profiling Algorithms for Web Recommendation Based on PLSA and LDA Model 1

Web transaction data between Web visitors and Web pages usually convey user task-oriented behavior patterns. We have proposed a mathematical user profiling algorithm for Web recommendation based on PLSA and LDA model. With the discovered usage knowledge from Web usage mining via various latent semantic analysis models, we construct a set of usage access patterns. By measuring the similarities between the active user and the discovered usage patterns, we choose the most similar user profile as the candidate usage pattern. The recommended page list is generated by incorporating the chosen user profile with the top-N weighted scoring scheme for Web recommendation. We have developed two mathematical Web recommendation algorithms with Probabilistic Semantic Latent Analysis(PLSA) and Latent Dirichlet Allocation (LDA) model respectively.
Cenozoic tectonic evolution of Qaidam basin and its surrounding regions ( part 2 ) : Wedge tectonics in southern Qaidam basin and the Eastern Kunlun Range

Our inability to determine the growth history and growth mechanism of the Tibetan plateau may be attributed in part to the lack of detailed geologic information over remote and often inaccessible central Tibet, where the Eastern Kunlun Range and Qaidam basin stand out as the dominant tectonic features. The contact between the two exhibits the largest and most extensive topographic relief exceeding 2 km across their boundary inside the plateau. Thus, determining their structural relationship has important implications for unraveling the formation mechanism of the whole Tibetan plateau. To address this issue, we conducted fi eld mapping and analysis of subsurface and satellite data across the Qimen Tagh Mountains, part of the western segment of the Eastern Kunlun Range, and the Yousha Shan uplift in southwestern Qaidam basin. Our work suggests that the western Eastern Kunlun Range is dominated by south-directed thrusts that carry the low-elevation Qaidam basin over the high-elevation Eastern Kunlun Range. Cenozoic contraction in the region initiated in the late Oligocene and early Miocene (28–24 Ma) and has accommodated at least
Enzyme-assisted and ultrasound-assisted extraction of phenolics from mulberry ( Morus alba ) fruit : comparison of kinetic parameters and antioxidant level

Nowadays, fruit juice with high antioxidant level has attracted great attention. In this study, pectinase preparation and ultrasound were alternatively used in the phenolic extraction from mulberry fruit. On the basis of kinetic model of second-order extraction, the extraction rate constant of total phenolics and anthocyanins in ultrasound-assisted extraction (UAE) increased approximately 16.9 and 21.5 times, respectively, in comparison with that in enzyme-assisted extraction (EAE). The level of total phenolics and anthocyanins in the UAE was 11.3% and 15.9%, respectively higher than that in the EAE. In addition, the antioxidant activity evaluated by Ferric Reducing Ability of Plasma (FRAP) and 2,2’-Azinobis-3-ethylBenzoThiazoline-6Sulfonic acid (ABTS) in the UAE was statistically higher than that in the EAE.
New decision tree classifier for dealing with partially uncertain data Nouvelle méthode d ’ arbre de décision pour le traitement des données partiellement incertaines

Decision tree is one of the most common classification approaches and has been widely used in several fields, notably in Data Mining and Machine Learning. However, the classical decision tree building algorithms have not the ability to handle uncertainty, in particular the epistemic one. In this paper, we propose to adapt the decision tree technique to an uncertain environment. Concretely, we tackle the case where object’s attribute values are uncertain and where this uncertainty is represented within the belief function framework. Our proposed method will concern both the decision tree building task and the classification of new objects.
Syntax-Based Reordering in Phrase-Based English – Hungarian Statistical Machine Translation

Phrase-based statistical machine translation systems can generate quite high quality translations in the case of language pairs with similar structure and word order. However if the languages are more distant from a grammatical point of view, the quality of translations is much behind the expectations, since the baseline translation system cannot cope with long distance reordering of words and morphological synchronization. In our paper, we present a method that tries to overcome these problems in the case of English-to-Hungarian translation. We describe how we defined some reordering rules on the English sentences in order to approximate the syntax of a hypothesized Hungarian translation prior to the actual process of translation. Due to the limited training corpus and data sparseness, and problems caused by the agglutinating characteristics of Hungarian, we applied a morpheme-based translation system. We show that although automatic evaluation cannot reliably reflect the improvement, human evaluation of the systems shows that readability and grammatical correctness of the translations were improved.
Ontologies models for supplement set of knowledge required for design software

Uzyskał stopień doktora nauk technicznych w zakresie informatyka na Wydziale Informatyki i Zarządzania Politechniki Wrocławskiej. Autor jest adiunktem w Instytucie Informatyki i Elektroniki Uniwersytetu Zielonogórskiego oraz współpracuje z firmami z branŜy informatycznej. Głównymi tematami zainteresowań naukowych są: projektowanie systemów informatycznych, metodyki projektowania uŜywane w inŜynierii oprogramowania oraz systemy rozproszone.
In situ evaluation of recommender systems : Framework and instrumentation

This paper deals with the evaluation of the recommendation functionality inside a connected consumer electronics product in prototype stage. This evaluation is supported by a framework to access and analyze data about product usage and user experience. The strengths of this framework lie in the collection of both objective data (i.e., ‘‘What is the user doing with the product? ’’) and subjective data (i.e., ‘‘How is the user experiencing the product? ’’), which are linked together and analyzed in a combined way. The analysis of objective data provides insights into how the system is actually used in the field. Combined with the subjective data, personal opinions and evaluative judgments on the product quality can be then related to actual user behavior. In order to collect these data in a most natural context, remote data collection allows for extensive user testing within habitual environments. We have applied our framework to the case of an interactive TV recommender system application to illustrate that the user experience of recommender systems can be evaluated in real-life usage scenarios. & 2010 Elsevier Ltd. All rights reserved.
Chinese Text Summarization Algorithm Based on Word2vec

In order to extract some sentences that can cover the topic of a Chinese article, a Chinese text summarization algorithm based on Word2vec is used in this paper. Words in an article are represented as vectors trained by Word2vec, the weight of each word, the sentence vector and the weight of each sentence are calculated by combining word-sentence relationship with graph-based ranking model. Finally the summary is generated on the basis of the final sentence vector and the final weight of the sentence. The experimental results on real datasets show that the proposed algorithm has a better summarization quality compared with TF-IDF and TextRank.
Way of Carbon Emission Reduction in Coal Mines Based on Carbon Balance Method and BWilson Method

This study is to analyze carbon balance method and B-Wilson method in carbon emission reduction in coal mines. The carbon balance method and B-Wilson method are studied in four open-pit coal mines in Yimin River, Anjialing, Heidaigou and Buzhaoba. It is found that continuous process can effectively improve the unit production capacity, and has positive effect on unit coal emission. It is also found that the production process system has certain effect on the carbon emission in open-pit coal mines. Conclusion has been drawn that the coal mining process system has certain application and research value in the research on way of carbon emission reduction in open-pit coal mines.
THE SNAIL : A REAL-TIME SOFTWARE APPLICATION TO VISUALIZE SOUNDS

The Snail is a real-time software application that offers possibilities for visualizing sounds and music, for tuning musical instruments, for working on pitch intonation, etc. It incorporates an original spectral analysis technology (patent-pending) combined with a display on a spiral representation: the center corresponds to the lowest frequencies, the outside to the highest frequencies, and each turn corresponds to one octave so that tones are organized with respect to angles. The spectrum magnitude is displayed according to perceptive features, in a redundant way: the loudness is mapped to both the line thickness and its brightness. However, because of the time-frequency uncertainty principle, using the Fourier spectrum (or also Q-transform, wavelets, etc) does not lead to a sufficient accuracy to be used in a musical context. The spectral analysis is completed by frequency precision enhancer based on a postprocessing of the demodulated phase of the spectrum. This paper presents the scientific principles, some technical aspects of the software development and the main display modes with examples of use cases.
Creation , Transfer and Application of Knowledge and its Importance for Business Innovation and Organizational Performance

This study pursues to advance understanding and to provide empirical evidence of how knowledge management can affect business innovation improving performance of the firm. Such knowledge management components as creation, transfer and application of knowledge, and its importance for business innovation and organizational performance are analyzed at theoretical and empirical level. The predicted effects are tested with data collected through 160 firms of 10 European countries (Austria, Belgium, Denmark, France, Germany, Italy, Netherlands, Poland, Spain and United Kingdom). Results of this investigation confirm that 1) knowledge management and organizational learning are closely related and have effects on business innovation and organizational performance, 2) business innovation improves company performance.
Analysis of the Impact of ICT on the Performance of Students in Secondary School , Oyo State

The use of ICT in schools requires skilled teaching staff and visionary school leadership. Teachers and school leaders need to be knowledgeable about the potential that ICT presents during teaching and learning in schools. According to Higgins & Moseley, (2011) where this knowledge is lacking, policies formulated by government and investments made towards implementation of ICT in schools, frequently miss opportunities to realize the desired school reforms. The use of ICTs in Nigeria and African countries generally is increasing and dramatically growing. However, while there is a great deal of knowledge about how ICTs are being used in developed countries, there is not much information on how ICTs are being introduced into schools in developing countries (BeukesAmiss and Chiware, 2006). The use of ICTs by teachers to teach the students is highly advantageous. This is because its enable them to demonstrate understanding of the opportunities and implications of the uses for learning and teaching in the curriculum context; plan, implement, and manage learning and teaching in open and flexible learning environment (UNESCO, 2004).
2 Exploring Plastic Deformation of Metallic Materials by the Acoustic Emission Technique

In determination of direct correlation between material properties and parameters of testing environment, the non-destructive in-situ methods play an important role. Nondestructive experimental techniques facilitate correlation of material parameters to those of the testing environment in real time. Among the tools emerging in the last decades, the acoustic emission (AE) technique belongs to the most powerful and reliable ones. The AE method allows to determine, which external parameters are critical for behaviour of the investigated material. Thus the results of AE measurements could give an integral hint for further post mortem investigations (e.g. scanning or transmission electron microscopy), in which the material properties are evaluated just after the exposure of the specimen to the external environment.
ASSOCIATION ANALYSIS OF HAWTHORN FLAVONES CONTENT 2265 of Cp CHS through gel electrophoresis and then the PCR production were purified from agarose gel by using TaKaRa MiniBEST Agarose Gel DNA

In this study, 87 hawthorn (Crataegus pinnatifida Bge.) accessions were obtained from National Hawthorn Germplasm Nursery in Shenyang Agricultural University of China and flavones contents including vitexin-rhamnoside, vitexin, rutin, hyperin and quercetin were detected by high performance liquid chromatography (HPLC) in 2014 and 2015. Chalcone Synthase genes (CpCHS) of 87 hawthorn accessions were cloned and sequenced, and then SNPs (Single Nucleotide Polymorphisms) among the result of sequencing were screened out, based on thees SNPs, we conducted the association analysis between the SNPs and phenotypic traits of hawthorn flavones content, the significant associated SNPs wre then discovered. The result showed that, in total of 71SNPs were discovered and three putative causal SNPs were associated with vitexin content both in 2014 and 2015, some SNPs were associated with vitexin-rhamnoside, rutin, hyperin and quercetin. This result can be used for molecular assisted breeding of hawthorn flavone content and also provide the reference for woody plants in association analysis filed.
Analysis of Huntington ' s disease gene expression profiles using Constrained Clustering

In this paper we looked at the possibility of analyzing gene expression data by using constrained clustering. The clustering was used as a way to relate Huntington’s disease patient pathological data with its corresponding microarray data, and it was performed by using a generic system for constructing decision trees. This resulted in genes whose expression level could possibly serve as an indicator of the progress of the disease.