Miracle-dz/UniFAR-FTUs huggingface dataset:
The need for a Wiki as a knowledge sharing technology in a research environment

Currently there is much interest in the use of Web 2.0 technologies to support knowledge sharing in organisations. Many successful projects have been reported. These reports emphasise how the use of such technology has unlocked new pathways for knowledge transfer. However, the limitations of Web 2.0 technologies are not yet well understood and potential difficulties may have been overlooked. This paper reports a case study of a Wiki which was implemented to support a group of researchers. Although belonging to the same institution, the group members were relatively dispersed and their research areas were disparate. Nevertheless a short study showed that there were benefits to be gained from sharing knowledge and that many of the researchers felt that a Wiki would be a good mechanism to support this. A Wiki was implemented and was initially very successful. A significant number of researchers contributed to the Wiki and almost all made use of it. However the usage declined over time and attempts to stimulate interest by providing incentives for contributions were unsuccessful. One year after launch use was minimal. A qualitative study was carried out to understand the reasons for this decline in use, and is reported in this paper. Responses suggest that two factors may have been particularly significant in explaining the failure of the system. One problem appears to have been a lack of critical mass. Only a small proportion of users are likely to contribute and there may be a threshold size for a community to be able to support a vibrant Wiki. Time also seems to have been an issue. Some respondents said that they simply were too busy to contribute to or use the system. Organisations which are considering the use of Web 2.0 technologies to support a knowledge management initiative should consider the likely impact of these factors in their own situation. Although technologies such as Wiki have great potential there are also pitfalls in undertaking such projects which are not yet well understood.
WiFi CSI Based Passive Human Activity Recognition Using Attention Based BLSTM

Human activity recognition can benefit various applications including healthcare services and context awareness. Since human actions will influence WiFi signals, which can be captured by the channel state information (CSI) of WiFi, WiFi CSI based human activity recognition has gained more and more attention. Due to the complex relationship between human activities and WiFi CSI measurements, the accuracies of current recognition systems are far from satisfactory. In this paper, we propose a new deep learning based approach, i.e., attention based bi-directional long short-term memory (ABLSTM), for passive human activity recognition using WiFi CSI signals. The BLSTM is employed to learn representative features in two directions from raw sequential CSI measurements. Since the learned features may have different contributions for final activity recognition, we leverage on an attention mechanism to assign different weights for all the learned features. Real experiments have been carried out to evaluate the performance of the proposed ABLSTM for human activity recognition. The experimental results show that our proposed ABLSTM is able to achieve the best recognition performance for all activities when compared with some benchmark approaches.
Virtual Reality or Just Reality ?

3 Sebahattin Emre Dilek (Asst. Prof.), School of Tourism and Hotel Management, Batman University, Batı Raman Campus, Batman 72060 Turkey. Email: s.emre. d@hotmail.com Abstract Developments in information and communication technology are increasingly transforming spatial relationships in tourism from a local into a global dimension. The virtual reality (VR) technology developed in this context is an important tool in this transformation. Virtual reality is an interactive environment generated by computers which enables participants to create countless real and unreal simulated experiences. The aim of this study is to describe virtual reality in the context of the tourism industry, to offer an evaluation by summarizing previous studies and conducting a situation analysis of virtual reality applications in terms of tourism via a SWOT analysis. The results of the situation analysis can be used to remark upon the place of VR technology in the tourism industry. In this framework, some suggestions for the tourism industry and future studies are given.
Dimension of Management Control in Entrepreneurial University

Abstrak. This study aims to investigate the dimensions of management control system from the lecturers point of view. This study explores how the control dimensions are able to motivate individuals. This study used a qualitative approach with phenomenology methods and case study strategies at universities with entrepreneurial characteristics. Data was collected through in-depth interviews and observations. The results show that there are several control dimensions that are able to influence behavior and motivate individual to work
Multilevel Functional Principal Component Analysis for Unbalanced Data

Functional principal component analysis (FPCA) is the key technique for dimensionality reduction and detection of main directions of variability present in functional data. However, it is not the most suitable tool for the situation when analysed dataset contains repeated or multiple observations, because information about repeatability of measurements is not taken into account. Multilevel functional principal component analysis (MFPCA) is the modified version of FPCA developed for data observed at multiple visits. The original MFPCA method was designed for balanced data only, where for each subject the same number of measurements is available. In this article we propose the modified MFPCA algorithm which can be applied for unbalanced functional data. The modified algorithm is validated and tested on real–world sleep data.
Improving Monte Carlo Localization using Reflective Markers : An Experimental Analysis

Robust localization is a basic requirement for many applications in mobile robotics. Despite many techniques have been devised to find solutions to the localization problem, symmetrical or featureless environments represent a great challenge for most of the commonly used approaches. In this paper, we investigate how artificial landmarks can be used to reduce the chances of failure of the localization process. More specifically, an experimental analysis of a probabilistic sensor model designed to employ reflective markers is presented. The analysis will focus on two central parameters of the model, several experiments are carried out to evaluate their effect on the overall localization process.
Evolutionary approach for 'healthy bundle' wellbeing recommendations

The purpose of this paper is to introduce an Evolutionary Recommender System focused on promoting a healthy lifestyle through suggestions that jointly considermeals and physical activities, based on users’ aims and their preferences. Our solution considers a Genetic Algorithm as the main driver of the recommendation process. An experimental study of algorithmic performance is conducted on users with different goals, along with a cohort study to analyse how real users perceive the recommendations suggested to them.
Learning MultiModality Features for Scene Classification of High-Resolution Remote Sensing Images

Scene classification of high-resolution remote sensing (HRRS) image is an important research topic and has been applied broadly in many fields. Deep learning method has shown its high potential to in this domain, owing to its powerful learning ability of characterizing complex patterns. However the deep learning methods omit some global and local information of the HRRS image. To this end, in this article we show efforts to adopt explicit global and local information to provide complementary information to deep models. Specifically, we use a patch based MS-CLBP method to acquire global and local representations, and then we consider a pretrained CNN model as a feature extractor and extract deep hierarchical features from full-connection layers. After fisher vector (FV) encoding, we obtain the holistic visual representation of the scene image. We view the scene classification as a reconstruction procedure and train several class-specific stack denoising autoencoders (SDAEs) of corresponding class, i.e., one SDAE per class, and classify the test image according to the reconstruction error. Experimental results show that our combination method outperforms the state-of-the-art deep learning classification methods without employing fine-tuning.
TRAFFIC AWARE PARTITIONING AND AGGREGATION USING MAP REDUCE WITH DATA SECURITY

Cloud computing which is one of the new and an emerging concepts that can provide a lot of resources for processing the big data, the most important problem is to handle the data from various locations and also some sort of security are needed if the data are very much sensitive, the solution which are proposed for the problem is to handle all the data using map reduce and thus the security is provided by using blow fish algorithm
Scheme for Vertical Advection in Oceanic Modeling

13 An oceanic model with an Eulerian vertical coordinate and an explicit vertical advection 14 scheme is subject to the Courant–Friedrichs–Lewy (CFL) limitation. Depending on the hor15 izontal grid spacing, the horizontal-to-vertical grid resolution ratio and the flow pattern this 16 limitation may easily become the most restrictive factor in choosing model time step, with 17 the general tendency to become more severe as horizontal resolution becomes finer. Us18 ing terrain-following coordinate makes local vertical grid spacing depend on topography, 19 ultimately resulting in very fine resolution in shallow areas in comparison with other mod20 els, z-coordinate, and isopycnic, which adds another factor in restricting time step. At the 21 same time, terrain-following models are models of choice for the fine-resolution coastal 22 modeling, often including tides interacting with topography resulting in large amplitude 23 baroclinic vertical motions. In this article we examine the possibility of mitigating vertical 24 CFL restriction, while at the same time avoiding numerical inaccuracies associated with 25 standard implicit advection schemes. In doing so we design a combined algorithm which 26 acts like a high-order explicit scheme when Courant numbers are small enough to allow 27 explicit method (which is usually the case throughout the entire modeling domain except 28 just few “hot spots”), while at the same time has the ability to adjust itself toward implicit 29 scheme should it became necessary to avoid stability limitations. This is done in a seamless 30 manner by continuously adjusting weighting between explicit and implicit components. 31
Student ’ s Perception on the Selected Facets of Reputation Quotient : A Case of a Malaysian Public University *

_______________________________________________________________ Abstract Past empirical studies have shown that specific facets of Reputation Quotient model positively influenced the reputation. However, the relevance of applying the Reputation Quotient model that focuses on the university setting in developing economies is still under researched. Hence, this study aims to examine the perception of current students about the dimensions of Reputation Quotient in one of the Malaysian higher education institutions (HEIs). In particular, the study aims to find out the differences between the subscales of Reputation Quotient pertaining to products and services, social responsibility, vision and leadership, financial performance, and emotional appeal facets. Multistage sampling was employed in this study, whereby simple random sampling and convenience sampling were applied. A quantitative (survey) method was employed in this study, in which questionnaires were distributed to 383 current students (local and international), but with 378 valid responses received. The data were then analyzed using descriptive statistics and one sample T-test. Based on the findings, the current students at the public HEI have a positive view about the reputation of the university. Data revealed that the students perceived positively on the subscales of Reputation Quotient pertaining to the five facets mentioned. The results call upon the management of the public HEI to focus on the dimensions mentioned in order to enhance the good perception and images from various constituents that will increase the survival of the institution in this competitive business market.
RFID and Arduino : Managing RFID Events on a Real World Prototype

Radio Frequency Identification (RFID) is a technology that is growing fast, becoming part of our daily lives more often and opening way to the Internet of Things. It can identify physical objects automatically, almost in real-time. Unfortunately, the learning curve for the technology is steep and a variety of tools are necessary just to implement a simple prototype. This paper provides an introduction to RFID through the implementation of a prototype, covering both hardware and software. We have deployed open-source software to monitor an Arduino robot carrying tagged objects in a small “warehouse”.
Lock Picking in the Era of Internet of Things

Smart locks are a recent development in the Internet of Things that aim to modernise traditional key-based padlock systems. They allow users to operate the lock with their smartphone instead of carrying around a physical key. Typically, smart locks have a cloud system for sharing access with other people, which makes them ideal for schemes such as communal lockers or bike sharing. One of the smart locks available on the market is that produced by Master Lock. They are an established brand, and unlike many of the single product companies that have provided insecure offerings, Master Lock have so far shown that their locks are reasonably secure and resistant to known attacks such as shimming, fuzzing, and replay attacks. This paper provides a security analysis of the Master Lock Bluetooth padlock. More importantly, it reveals that there were several security vulnerabilities, including a serious one in the Application Programming Interface used by Master Lock to provide a crucial feature for managing access. We carried out a responsible disclosure exercise to Master Lock, but communication proved to be quite a challenge. In the end we managed to establish contact, and as a result the most serious vulnerabilities have now been patched. This indicates that responsible disclosure is a valuable exercise, but we still need better report-and-response mechanisms.
A comparative study on Phytochemical evaluation of peels of Citrus auriantum , Citrus maxima and Citrus sinensis using different solvents – Profiting Fruit Waste

Citrus fruits have been appreciated for their refreshing juice and health benefits. They also known to have phytochemicals which are not of nutritional use but can work towards the deterrence of diseases. As they can be absorbed by human body, they show numerous therapeutic proprieties like minimizing free radical damage to the cells due to oxidative stress, antiviral, anticancer, anti-inflammatory activities, inhibition of platelet aggregation, capillary fragility and minimizing age related muscular degradation. This study provides a clear perception about Citrus maxima, Citrus auriantum and Citrus sinensis peels, as known to have a greater number of phytochemicals. The present phytochemical screening of citrus peels extracts using different solvents revealed the presence of tannins, flavonoids, carotenoids, saponins and carbohydrates. Flavonoids were highly detected in all extracts of Citrus maxima. Tannins, triterpenoids and saponins were also found in C. maxima peel extracts. Citrus auriantum peels showed the presence of tannins, flavonoids, saponins, and triterpenoids in comparatively less amount from different solvents. Whereas Citrus sinensis revealed the presence of alkaloids, triterpenoids, tannins and flavonoids. This work shows the availability of phytochemicals from the peels of Citrus maxima, Citrus auriantum and Citrus sinensis for various industrial application.
Preparation of nano-sized mixed crystal TiO 2-coated Er 3 + : YAlO 3 by sol – gel method for photocatalytic degradation of organic dyes under visible light irradiation

Jun Wang (corresponding author) Jia Li Yingpeng Xie Guangxi Han Xiangdong Zhang Department of Chemistry, Liaoning University, Shenyang 110036, China E-mail: wangjun890@126.com Jun Wang (corresponding author) Bin Liu Liqun Zhang Department of Pharmacy, Liaoning University, Shenyang 110036, China Ying Li Center of Analysis and Test, Liaoning University, Shenyang 110036, China In this work, an upconversion luminescence agent, crystallized Er :YAlO3, was synthesized and then coated by the nano-sized TiO2 film through sol–gel technique. A novel TiO2 photocatalyst, Er :YAlO3/TiO2, with high activity in visible light was subsequently prepared. The Er 3+ :YAlO3 and Er :YAlO3/TiO2 were characterized by X-ray diffraction (XRD) and transmission electron microscope (TEM). The photocatalytic activity of Er :YAlO3/TiO2 photocatalyst was tested by the degradation of acid red B in aqueous solution as the primary model compound under visible light irradiation. The experimental results proved that the prepared TiO2-coated crystallized Er 3+ :YAlO3 was able to decompose the acid red B efficiently, and it is promising to use the idea to develop new TiO2 photocatalyst with high activity for photocatalytic degradation under visible light.
Study of the Role of Lysine 16 for the Molecular Switching Mechanism of Ras Protein p 21

Quantum chemical computations using the ab initio molecular orbital (MO) method have been performed to investigate the molecular switching mechanism of Ras protein p21, which has an important role in intracellular signal cascades. Lys was demonstrated to be crucial to the function of Ras p21, and the hydrolysis of GTP to GDP was found to be an one-step reaction. The potential energy barrier of this hydrolysis reaction from GTP to (GDP 1 P) was calculated to be ;42 kcal/mol. The role of GAP (GTPase-activating protein) was also discussed in terms of the delivery of the water molecules required for the hydrolysis.
Success Matters Understanding College Application Decisions : Why College Sports

Using a unique, national data set that indicates where students choose to send their SAT scores, the authors find that college sports success has a large impact on student application decisions. For example, a school that has a stellar year in basketball or football on average receives up to 10% more SAT scores. Certain demographic groups (males, Blacks, out-of-state students, and students who played sports in high school) are more likely to be influenced by sports success than their counterparts. The authors explore the reasons why students might be influenced by these sporting events and present evidence that attention/accessibility helps explain these findings.
S Status Competition and Peer Relationships in Childhood

While the underlying fabric and structures of human groups are diverse, two processes seem ubiquitous to social life: individuals desire affiliation with others and form social hierarchies. From the formal social organization of businesses to the relationships within some of the most egalitarian societies that lack formal structures of power (reviewed in Cheng et al. 2014), individuals assort hierarchically, with people occupying different strata within a group based on their standing in multiple culturally valued domains (Henrich and Gil-White 2001). The reason for the universality of both processes is that their presence provides a solution to the competition over relatively scarce social, sexual, and material resources that characterize most group-living species. These processes not only reduce costly conflict, aggression, and warfare, but may also generate and sustain cooperation within a group (Henrich et al. 2015). Although these relationships are present and important during adulthood, an understanding of the social world, and the positions that individuals occupy within that world, develops during childhood as early as in the first few months after birth. Both the desire for peer relationships and status competition are present throughout the developmental periods of human life, although they take different forms and serve diverse purposes during each developmental stage. However, the means by which individuals both attain social status and successfully manage peer relationships seem to fall into two routes across a range of developmental periods: dominance and prestige (Cheng et al. 2010; Sijtsema et al. 2009; Hawley 2002). The vast and growing body of research supporting
Arterial Blood Pressure and Neurological Outcome After Resuscitation From Cardiac Arrest

Critical Care Medicine www.ccmjournal. org 1 Objectives: Guidelines for post–cardiac arrest care recommend blood pressure optimization as one component of neuroprotection. Although some retrospective clinical studies suggest that postresuscitation hypotension may be harmful, and laboratory studies suggest that a postresuscitation hypertensive surge may be protective, empirical data are few. In this study, we prospectively measured blood pressure over time during the postresuscitation period and tested its association with neurological outcome. Design: Single center, prospective observational study from 2009 to 2012. Patients: Inclusion criteria were age 18 years old or older, prearrest independent functional status, resuscitation from cardiac arrest, and comatose immediately after resuscitation. Measurements and Main Results: Our research protocol measured blood pressure noninvasively every 15 minutes for the first 6 hours after resuscitation. We calculated the 0to 6-hour timeweighted average mean arterial pressure and used multivariable logistic regression to test the association between increasing time-weighted average mean arterial pressures and good neurological outcome, defined as Cerebral Performance Category 1 or 2 at hospital discharge. Among 151 patients, 44 (29%) experienced good neurological outcome. The association between blood pressure and outcome appears to have a threshold effect at time-weighted average mean arterial pressure value of 70 mm Hg. This threshold (mean arterial pressure > 70 mm Hg) had the strongest association with good neurological outcome (odds ratio, 4.11; 95% CI, 1.34–12.66; p = 0.014). A sustained intrinsic hypertensive surge was relatively uncommon and was not associated with neurological outcome. Conclusions: We found that time-weighted average mean arterial pressure was associated with good neurological outcome at a threshold of mean arterial pressure greater than 70 mm Hg. (Crit Care Med 2014; XX:00–00)
A Reexamination of Inflation and Growth

I rely on the empirical model created by Pollin and Zhu (2006) to examine the relationship between inflation and growth beyond the short-term. I replicate their set of countries and extend the period of time examined to 1961-2010. I cannot duplicate their results and find that extensive data revisions may be a key reason for the discrepancy. I test slight adjustments of their model to reduce omitted variable bias. The enhanced model can be directly compared with the empirical work of Mankiw, Romer, and Weil (1992), allowing a contrast of my findings with one of the literature’s foundations. The combination of the Pollin and Zhu and Mankiw, Romer, and Weil empirical models leads to increased explanatory power and more reliable estimates. From the combined model, there are indications of significant impacts of inflation on growth in the mediumterm (over five years), but negligible impacts over the long-term (twenty-five years). This is most evident in highly developed countries; the relationship between inflation and growth in less developed countries is less clear.