Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of knee lateral thrust gait to femorotibial angle and lateral joint space in the knee varus patients

Objective To investigate the influence and clinical significance of knee lateral thrust gait to femorotibial angle and lateral joint space in the patients with knee varus deformity. Methods 44 patients (male 10, female 34; range 31-60 years old, mean 41 years old) with knee varus deformity and lateral thrust involved in this study. The femorotibial angle and lateral joint space were measured on the standing anteroposterior film (single-foot loading and double-feet loading) of knee in order to compare the changes of them. The double-feet loading film simulated the corresponding relationship between thighbone and tibiae at double-support time, as early knee lateral thrust. The single-foot loading film simulated the corresponding relationship between thighbone and tibiae at single-support time, as late knee lateral thrust. The changes of femorotibial angle and lateral joint space in the two positions showed the changes of corresponding relation between thighbone and tibiae during knee lateral thrust. Results The mean femorotibial angle was 188.50°±4.48° and 185.50°±4.46° at the time of single-foot loading and double-feet loading respectively. It indicated that the femorotibial angle was increasing at the time of single-foot loading. The mean width of lateral joint space was (9.92±0.86) mm and (7.70±0.78) mm at the time of single-foot loading and double-feet loading respectively. It demonstrated that lateral joint space was widening more at the time of single-foot loading. The result suggested the lateral thrust of knee led to these changes. The increasing of femorotibial angle meant an increase of knee adduction moment during gait. The increasing of lateral joint space led to lateral structures chronic instability. The increased knee adduction moment and lateral structures chronic instability were the important mechanisms for degeneration of knee medial department. Conclusion The knee lateral thrust gait results in the augments of femorotibial angle and lateral joint space. These lead to the increase of the load on knee medial compartment, lateral structures chronic instability and varus deformity increasing. Lateral thrust might cause aggravation of knee varus and gonarthrosis at knee medial compartment.
UML Ninja: Automatic Assessment of Documentation and UML Practices in Open Source Projects

Context: Assessment of software documentation practices in open source projects is important because, besides the source code, information regarding the open source project is in the documentation. Quality of documentation can help in determining the quality of the project. Goal: The goal of this paper is to automate the process of assessing the quality of documentation and UML in open source projects. Method: We conduct a design science research study and evaluate the outcome based on 14 interviews with researchers and practitioners. Result: The result of this paper is UML-Ninja, which is a web tool to automatically assesses quality of documentation in open source projects based on indicators. Conclusion: Both researchers and practitioners found the approach of UML-Ninja tool good and appropriate.
Numerical and Experimental Investigation of Sonotrode for Formation of Piezocomposite Functional Elements

The paper is dedicated to analysis, practical exploitation of sonotrode, whose fundament is multilayer actuator in experiments of mechanical hot imprint. The goal is to compare the quality of microstructures, created by using vibration based on multilayer actuator. Numerical modelling and experimental analysis is performed in order to find resonant frequency of the sonotrode. Having operating frequency, sonotrode applied in mechanical hot imprint process. Microstructures are created on the surface of polycarbonate; the only process variable is vibration. Two types of microstructure quality measurements are performed: measurement of diffraction efficiency, optical microscopy in order to examine quality of replica
Review On SVM Based Method For Identification And Recognition Of Faces By Using Feature Distances

: Support vector machine is a machine learning algorithm that has been developing since the mid-1990s. There are two significant things in face recognition using SVM. One is the component feature extraction from images, the other is the classifier we choose. The relative distance between the features of face is used to uniquely identify a person. These measures are used to train the SVM and the closest match with the input data is results in a successful identification. Minimum distance classifier is used for identification process.
Penentuan Posisi Sudut Matahari Menggunakan ANFIS dalam Aplikasi Tracker Panel Surya

Solar panels have constraints on output power that are not large enough and they are highly depend on natural conditions. Solar panel power depends on the intensity of sunlight received and the temperature of the surrounding environment. In order to get the maximum output power of the solar panel, an additional device called the solar tracker is needed. This research has contributed to increasing the output power of solar panels by directing solar panels perpendicular to sunlight. The use of this research is very useful in the application of the multi-axis tracker application from the sun. By knowing the rising angle of the sun every morning and the circulation angle to sunset, the tracker will work quickly so that the energy used for movement is very small. The reference angle generated by the ANFIS training algorithm is more accurate because the calculated data will be confirmed again by the sensor. And this system can work offline, without being connected to a data center, so it can be used in remote or isolated areas.
Fuzzy-Logic-Based Adaptive Proportional-Integral Sliding Mode Control for Active Suspension Vehicle Systems: Kalman Filtering Approach

This paper deals with the problem of synthesizing a fuzzy-logic-based adaptive proportional-integral sliding mode control (FAPISMC) for active suspension systems based on Kalman filtering approach. To improve the performance of the controller and eliminate the effect of the chattering, the switching input is designed based on the fuzzy-logic-based approach with a minimum number of rules. In order to facilitate the stability analysis, the estimation of the state variables is used in designing the sliding surface platform. Furthermore, the gain of the controller is updated by an adaptive law to avoid any pre-knowledge of the disturbance amplitude. Subsequently, the proposed approach is more implementable in real-world processes. Finally, in order to illustrate the effectiveness and merits of the proposed approach, a suspension system is considered and simulated by the real-time hardware-in-the-loop (HiL). In this example, a quarter-car model of suspension systems is considered. Then, the obtained real-time results are compared with the linear quadratic regulator approach.
BOTection: Bot Detection by Building Markov Chain Models of Bots Network Behavior

Botnets continue to be a threat to organizations, thus various machine learning-based botnet detectors have been proposed. However, the capability of such systems in detecting new or unseen botnets is crucial to ensure its robustness against the rapid evolution of botnets. Moreover, it prolongs the effectiveness of the system in detecting bots, avoiding frequent and time-consuming classifier re-training. We present BOTection, a privacy-preserving bot detection system that models the bot network flow behavior as a Markov Chain. The Markov Chain state transitions capture the bots' network behavior using high-level flow features as states, producing content-agnostic and encryption resilient behavioral features. These features are used to train a classifier to first detect flows produced by bots, and then identify their bot families. We evaluate our system on a dataset of over 7M malicious flows from 12 botnet families, showing its capability of detecting bots' network traffic with 99.78% F-measure and classifying it to a malware family with a 99.09% F-measure. Notably, due to the modeling of general bot network behavior by the Markov Chains, BOTection can detect traffic belonging to unseen bot families with an F-measure of 93.03% making it robust against malware evolution.
IMPROVING PERFORMANCE OF VAT SYSTEM IN DEVELOPING EU COUNTRIES: ESTIMATING THE DETERMINANTS OF THE RATIO C-EFFICIENCY IN THE PERIOD 1997-2017

Indirect taxes have a significant place in developing EU countries’ tax systems. The article sums up scholars of different scientists, dealing with the impact of VAT efficiency determinants. The purpose of this study is to investigate the determinants of VAT collection efficiency in the EU developing countries. The study relies on relevant data in transparent international statistical databases, covering the period from 1997 to 2017. The main research question in this paper is: does rise in value added tax rate negatively affect VAT collection efficiency in the EU developing countries. Accordingly, one of the independent variables included in the survey is standard annual VAT rate. In addition to standard VAT rate, as a determinant of VAT collection efficiency, we analyze: economic growth rate, export of goods, export of services, wages and salaries, household consumption. The hypotheses set are analyzed using correlation and regression analyses. Empirical results show a positive effect of economic growth rate, export of goods, and the negative effect of two variables: standard VAT rate and household consumption. The two observed variables, export of services and wages and salaries, do not show a statistically significant effect. The results obtained using appropriate statistical tools serve as guidelines to macroeconomic policy makers to generate higher tax revenues from VAT. By analyzing the C-efficiency determinant, we design a relevant development strategy approach for economically underdeveloped EU countries.
Scalable Working Set Estimation Method For Chip Multicores Using Tagged Bloom Filter And Its Application

In chip multicore platforms (CMPs), leakage power consumption of large on-chip caches has already become a major power consuming component of the memory subsystem. Leakage power can be saved by switching off over-allocated ways in associative cache. However, the state-of-the-art heuristics such as average memory latency or cache miss rate fail to achieve near-optimal energy savings. This is either due to dispersed nature of large caches or they are not fast enough to respond to changes in working set size (WSS), especially in case of over-provisioning of cache. Hence, we first propose a new kind of bloom filter, which we call it as a “tagged bloom filter (TBF)”. We implement TBF implicitly in last level cache on a scalable tiled chip multicore platform. TBF is then used to estimate WSS of an application and switch-off over-allocated cache ways in Static and Dynamic Nonuniform Cache Architecture (SNUCA, DNUCA) accordingly. In our implementation of adaptable way SNUCA and DNUCA caches, associativity decision is taken locally by each L2 controller, making it scalable with the number of tiles present on CMP. It gives average of 22% and 23% more EDP savings than average memory latency and cache miss rate heuristics on SNUCA, respectively.
Improved estimation methods for VaR, Expected Shortfall and the risk contributions with high precisions

The (marginal) risk contribution is very useful for analysing the concentration risk in a portfolio. However, it is difficult to estimate the risk contributions for VaR and ES precisely, especially by the Monte Carlo simulation. Against this difficulty, we applied the saddlepoint approximation to estimate the distribution function, so that the difficulty of estimating the risk contributions for VaR was dissolved. In this article we propose new estimation methods for ES and the risk contributions for ES based on the conditional independence and the saddlepoint approximation. Numerical studies confirm that the new methods are much better than the existing ones.
Investigating to what extent Need for Closure, Need for Cognition, and Gender Role Attitudes can predict Genderism and Transphobia.

Lesbian, Gay, Bisexual, Transgender and other (LGBT+) individuals are still marginalised and stigmatised despite recent progress in social, academic, and political areas. Transgender, or ‘gender variant’, individuals are often targets of transphobia, prejudicial behaviour such as assault and discrimination. Transphobia is underpinned by genderism, a set of beliefs which reinforces negative evaluations of gender nonconformity. Genderism and transphobia have serious implications on quality of life and mental health of gender variant individuals, necessitating exploration of ways to reduce such prejudice. One way to explore this is to examine and address constructs which may predict genderism and transphobia. Considering such constructs in education and intervention could improve individuals’ reception to positive messages around gender variance. In turn, this can reduce genderist views and transphobic behaviours, improving experiences and quality of life for gender variant individuals. This study used a multiple regression analysis on 71 students at the Manchester Metropolitan University. It investigated to what extent three constructs – need for closure, need for cognition, and gender role attitudes – can predict genderism and transphobia. Gender role attitudes were found to be a significant predictor; need for closure was marginally significant; need for cognition was non-significant. Findings, implications, benefits, and limitations of this study are discussed.
Public Governance efficiency and macroeconomic stability: examining convergence of social and political determinants

The purpose of this article is to propose the integrated index of Public Governance efficiency based on the Fishburne’s method, considering the impact’s power and direction of the different sub-indexes (Worldwide Government Indicators) on macroeconomic stability and eliminating the issue of multicollinearity. The object of the study was 11 European countries that had two common features: 1) in the political sphere, during 1990–1992 the countries started the political transformation process by refusing the monopoly of the communistic regime; 2) in the economic sphere, the countries experienced transformation from planned to market economy. Based on these criteria, the following countries were selected: Lithuania, Latvia, Poland, Bulgaria, Croatia, Romania, Armenia, Belorussia, Georgia, Moldova, and Ukraine. The research findings proved a connection between the political and social determinants and the macroeconomic stability for the all the countries. Moreover, the research results confirmed the existence of a cycle of social and political conflict, which depends on inter-relation of Public Governance and the society, where the efficiency of Public Governance cannot be achieved without the support from the society, and the society cannot cooperate with non-effective Public Governance.
Screening and characterisation of gamma-aminobutyric acid (GABA) producing lactic acid bacteria isolated from Thai fermented fish (Plaa-som) in Nong Khai and its application in Thai fermented vegetables (Som-pak)

Gamma-aminobutyric acid (GABA) is a non-protein amino acid produced through the decarboxylation of glutamate by glutamate decarboxylase and wildly distributes among animals, plants and microorganisms (Ueno, 2000). GABA possesses well-known beneficial bioactivities such as neurotransmission, the induction of hypertension and a tranquilising effect (Pearl et al., 2006). On addition, it can stimulate immune cells (Dh et al., 2003) and is involved in the treatment of sleeplessness, depression and autonomic disorders (Dkada et al., 2000) as well as the improved prevention of diabetes (Hagiwara et al., 2004). This results in increasing commercial demand and extensive study to synthesis GABA in large amounts (Choi et al., 2006; Plokhov et al., 2000). However, the direct addition of GABA to food is considered unsafe and unnatural, while the utilisation of GABA-rich foods produced by natural techniques is more favourable (Dhakal et al., 2012). Many microorganisms are able to produce GABA, including bacteria, fungi and yeast. Among them, lactic acid bacteria (LAB) have been given more attention in research because of their utilisation in the food industry and the fact they are generally regarded as safe (GRAS) and known as probiotic. The production of GABA by LAB in fermented products can provide alternative, naturally fermented health products.
ENDOUROLOGY AND STONE DISEASE The Prevalence of Urinary Tract Infection Following Flexible Ureterenoscopy and the Associated Risk Factors

Result: 111 patients were included in the study with a mean age of 47.5 years (range: 14-84 years). Postoperative infection rate was 12.6% (n= 14). SWL, preoperative double J stent insertion, localization, gender, and the operation side had no impact on origination of infectious complications (P > .05 for all). Preoperative infection history (P = .002, OR=7.96, %95CI: 2.030.5), comorbidity score (P = .008, OR=7.79, CI%95: 1.735.5), and residual fragments (P = .045, OR=5.12, CI%95: 1.03 – 25.36) were found to be the significant risk parameters of postoperative infectious complications.
‘Plastic Deformation, Mechanical and Adhesive Properties of Bio-Plastic Material

Given the added need for eco-friendly material, environmental scientists are constantly on the look-out for new solutions. In this respect, biodegradable polymer proved to be a promising one. The Selfix material, being a bioplastic, is biodegradable and, unlike other plastic products, can be considered feasible for the industry as a smart material capable of biodegrading at the end of its life cycle. Using Selfix, waste paper can be re-used, thus eliminating the need for recycling and helping to reduce the CO2 emissions. The present paper develops 3D models with Selfix material to offer benefits such as easy-cutting and sticking properties in a way that can be educational for children. We examine the mechanical properties of this material using tensile testing, laser-cutting, CNC milling, surface roughness and also scanning electron microscope or SEM.
UAV Control Architecture: Review

Since civil Unmanned Aerial Vehicles (UAVs) are expected to perform a wide rang of mission, the subject of designing an efficient control architecture for autonomous UAV is a very challenging problem. Several contributions had been done in order to implement an autonomous UAV. The key challenge of all these contributions is to develop the global strategy. Robotic control approaches could be classified into six categories: Deliberative, Reactive, Hybrid, Behavior, Hybrid Behavior and subsumption approach. In this paper, we will review the existing control architectures to extract the main features of civil UAVs. The definition, advantage and drawback of each architecture will be highlighted to finally provide a comparative study of the mentioned control approaches.
How Participation Management Influences Work Engagement: The Mediating Role of Perceived Fit and Leader-Member Exchange

How does participative management influence work motivation? The empirical evidence is mixed. We bridged contradictory findings by proposing previously unexamined mediational mechanisms that link participative management practices to work engagement. The results show that participative management practices have the potential to prompt employees to act in line with the organization's goal and values that, in turn, leads to work engagement. In particular, person-organization (PO) fit, need-supply (NS) fit, and leader-member exchange (LMX) are central to setting the relations among participative management practices, perceived fit, and work engagement. The results suggest that participative management should provide multiple avenues to fulfill human needs, thus strengthening employee engagement at work.
Performance Evaluation of IoT Messaging Protocol Implementation for E-Health Systems

Now-a-days, e-health and healthcare applications in the internet of things are growing rapidly. These applications are starting from remote monitoring of patient's parameters in home to monitoring patients during his life activities at work, transportation, etc. So we can monitor patients at any place outside of hospitals and clinical settings. By using this technology, we can save lives and reduce the number of emergency visits to hospitals. In contemporary time, there are great progress and opportunities for the internet of things (IoT) related E-health systems. Most IoT e-health platforms consist of three main parts; client nodes (patient or doctor), IoT server and IoT communication messaging protocol. One of E-health systems design over IoT challenge is choosing the most suitable IoT messaging protocol for E-health applications. In this paper, IoT remote patient and e-Health monitoring system was designed for monitoring physiological medical signals of patients based on most two famous IoT messaging protocols, MQTT and CoAP. These medical signals can be include parameters like heart rate signals, electro-cardio graph (ECG), patient temperature, blood pressure, etc. This practical comparison between CoAP and MQTT is to choose most suitable for e-health systems. The proposed approach was evaluated based on most significant protocol parameters like capability, efficiency, communication method and message delay. Practical and simulation results show the performance of the proposed E-health systems over IoT for different network infrastructure with different losses percentages.
CAFT: Cost-aware and Fault-tolerant routing algorithm in 2D mesh Network-on-Chip

By increasing, the complexity of chips and the need to integrating more components into a chip has made network –on- chip known as an important infrastructure for network communications on the system, and is a good alternative to traditional ways and using the bus. By increasing the density of chips, the possibility of failure in the chip network increases and providing correction and fault tolerance methods is one of the principles of today's chip design. Faults may have undesirable effects on the correct system operation and system performance. In this paper the communication infrastructure failure has been considered as same as link and router failure and the fault tolerance low cost routing algorithm has been suggested base on local fault information By using quad neighbor fault information to avoid back tracking in routing in order to select possible minimal path to destination. In this article, we have suggested cost aware fault tolerance (CAFT) routing algorithm. Our contribution in this algorithm is minimum local fault information, minimum routing decision overhead by implementing routing logic base and determining shortest possible path. For deadlock freedom using an additional virtual channel along Y dimension and prohibiting certain routing turns. In order to evaluate the performance of our routing, we compared it with other fault tolerant routing in terms of average packet latency, throughput and power.