Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of bedrock-alluvial transition on plant species distribution along a Mediterranean river corridor

Abstract The variation of riparian plant species composition along a river according to lithological features, forming more or less discrete plant assemblages, was tested using multivariate and univariate analyses. Moreover, Sørensen's index was applied to examine similarity between geological and floristic groups, and the Wilson–Shmida index to investigate species turnover. The analyses were based on field data recorded along a Mediterranean river (Rio Santa Lucia, Sardinia, Italy), where the morphology is influenced by the bedrock-alluvial transition. The results obtained from the various analytical techniques were in close agreement, and underlined that the lithological types exerted an important influence on the distribution and richness (peak in the medium and the upper river part) of riparian plants, but also in their life forms (woody species and hemicryptophytes). The distribution patterns of species along the river suggested that primary drivers in the organization of the riparian plant communities were lithological types, geomorphology and altitude. Moreover, the bedrock-alluvial transition marked the highest species turnover, linked also to a different degree of human disturbance. The results of the present study indicate that the bedrock/alluvial influence is an integral component of the patch structure, which strongly influences riparian plant distribution patterns in a Mediterranean environment.
Transformer’s Load Forecasting to Find the Transformer Usage Capacity with Adaptive Neuro-Fuzzy Inference System Method

The development of the tourist destinations of Bali Island, especially Nusa Dua area, should be included with the development of electricity supply in the region. To facilitate a process of electrical energy planning in the region, it is necessary to forecast the electrical load in the area. Forecasting is a process to estimate future events / things to come. In this research, the forecasting of the long-term electrical load for five years and this forecasting method using ANFIS method and use ANN method as a comparison. From the simulation conducted by MAPE which resulted from forecasting the weekly electrical load using ANFIS method is 0.028% while MAPE forecasting using ANN method is 51.57%. From the comparison result, it can be said that the annual electricity load forecasting using the ANFIS method has a better forecasting accuracy than using the ANN method. The forecasting results of this transformer load is used as a reference in planning the electricity system on the Bali Island.
PENGARUH SIT STRETCHING TERHADAP PERUBAHAN SKALA NYERI PUNGGUNG BAWAH PADA KARYAWAN DI PT. RIFAN FINANCINDO BERJANGKA CABANG SEMARANG

Lower back pain is one of musculoskeletal disorder in the shape of pain in the back bone, to be exact is in the forth lumbar to the first sacrum. It is caused by the not appropriate posture (not ergonomic) while working or doing the activities, such as very long standing or sitting. This complaint can be reduced by sit stretching regularly. The aim of this study is to find out impact of sit stretching towards the changes of scale of lower back pain on employees at PT. Rifan Financindo Berjangka Branch Semarang. The method of research is quasy experiment designed in pre test and post test with compare group. Research subjects are 30 male and female employees. Sample taking uses total sampling. Statisitic test utilizes Mann Whitney with level of meaning (α=0,05). The result of pre test statisitc test is p-value = 0,467 (> 0,05), it means that there is no significant difference scale of lower back pain between intervention group and compare group before performing sit stretching to intervention group. The post test statisitic the result is p-value = 0,001 (> 0,05), it means there is a significant difference scale of lower back pain at intervention group with compare group after performing sit stretching on the intervention group. Based on result of p-value on post test can be concluded that there is an impact of sit stretching towards the changes in scale of lower back pain on the employees at PT. Rifan Financindo Berjangka Branch Semarang.
Multiple Kernel Semi-Representation Learning With Its Application to Device-Free Human Activity Recognition

In the research of smart buildings, human activity recognition is an important cornerstone for numerous emerging applications. Although several sensing techniques have been proposed for human activity identification, they require either the user instrumentation or additional infrastructure, that are inconvenient, privacy-intrusive, and expensive. To address these issues, a WiFi-enabled device-free human activity recognition system, namely SmartSense, is proposed in this paper. By upgrading commercial WiFi routers with our designed firmware, fine-grained channel state information (CSI) from PHY layer can be directly extracted from the existing WiFi traffic. In this paper, we propose SmartSense, a device-free human activity recognition system that only leverages existing commercial off-the-shelf WiFi routers. By exploiting the prevalence of WiFi infrastructure in buildings, we developed a novel CSI-enabled Internet of Things platform to collect the CSI measurements from regular data frames. To identify different human activities, a novel machine learning tool, namely multiple kernel semi-representation learning (MKSRL) method is established. MKSRL allows the input of expert domain knowledge in a flexible way and conducts automatic and effective multikernel representation learning for the activity recognition task. Each stage of MKSRL is computationally efficient and theoretically guaranteed, and they can be integrated seamlessly within the reproducing kernel framework for the overall information extraction, representation, and fusion. We conducted experiments to comprehensively evaluate the performance of SmartSense in three common indoor environments. Experimental results validate that SmartSense can provide an activity recognition accuracy of 98%, which achieves significant performance gain over the existing methods.
Secure Multicast Communications in Cognitive Satellite-Terrestrial Networks

This letter studies a secure multicast transmission design for cognitive satellite-terrestrial networks with multiple multi-antenna eavesdroppers, where the satellite (SAT) delivers a common confidential message to a group of legitimate users and the interference from the terrestrial base station (BS) is utilized to strengthen the security of the satellite link. Our goal is to minimize the total transmit power, subject to the secrecy rates for the satellite links as well as the information rate for the terrestrial link. The resulting optimization problem involves the joint optimization of the information covariance matrices at the SAT and the BS, which is non-convex and challenging. We have introduced a successive convex approximation method to transform the non-convex constraints into linear ones and proposed an effective iterative algorithm. Simulation results demonstrate the superiority of the proposed algorithm.
VERMIFORM BONES AND THE EVOLUTION OF GIGANTISM IN MEGALANIA—HOW A REPTILIAN FOX BECAME A LION

GREGORY M. ERICKSON', ARMAND DE RICQLES2, VIVIAN DE BUFFRENIL2, RALPH E. MOLNAR3, and MARK K. BAYLESS4, 'Department of Biological Science, Florida State University, Tallahassee, Florida, 32306-1100, U.S.A. ; 2Laboratoire d'Anatomie Comparee, 2 place Jussieu, 75251 Paris Cedex 05, France; 3Museum of Northern Arizona, Flagstaff, Arizona 86001, U.S.A. ; 41406 Holly St., Berkeley, California 94703, U.S.A.
Early Detection and Multidisciplinary Approach to Oral Cancer Patients

“Oral cancer” is a term usually describing oral cavity and oropharyngeal malign tumors. The most histologic type of carcinoma is squamous cell carcinoma, seen in oral and oropharyngeal region with the incidence of 90%. Prevention or early diagnosis of prema- lignant and oral cancer requires increased public awareness and educating practitioners to be skillful in identifying oropharyngeal region pathology. To prevent oral cancers, the etiological factors should be known, and measures must be taken according to those factors. Premalignant lesions are leukoplakia, lichen planus in oral and cutaneous form, erythroplakia, stomatitis nicotina , and submucous fibrosis. Premalignant lesions should be treated, if possible, or followed up on carefully. To date, there are many clinical, his- topathological, radiological, and optical techniques to diagnose or capture precancerous and oral cancer lesions early. The routine management of oral cancers is firstly surgical resection with or without postoperative adjuncts and other therapies such as the use of postoperative chemoradiation and radiation. Successful treatment of oral cancer patients is a complex issue that requires a multidisciplinary approach, including oral and maxillofacial surgeons, oral and maxillofacial radiologists, ENT specialists, medical and radio- logical oncologists, prosthodontists, dentists, speech therapists, supportive care experts, and also pathologists or, if possible, maxillofacial
The Correlation between Serum Zinc Level and Liver Histology in Non-Alcoholic Steatohepatitis

Background & Objective: The aim of this present study was to assess the relationship between serum zinc levels and liver histopathological findings in non-alcoholic steatohepatitis (NASH) patients. Methods: This case-control study was performed in consecutively selected NASH patients who had been referred to a general hospital. The control group consisted of age and sex-matched individuals with normal physical examinations, laboratory findings, and liver ultrasounds. Serum zinc level was measured using atomic absorption spectrophotometry. Liver histopathological findings were determined based on non-alcoholic fatty liver activity score. Results: A cohort of eighty biopsy-proven NASH patients and eighty controls were enrolled in the study. The mean serum zinc level was significantly lower in the NASH group compared with the controls. The mean serum zinc concen- tration was significantly lower in moderate and severe lobular inflammation groups than the mild group. After multiple adjustments for potential contributing variables, serum zinc level was associated with the severity of lobular inflam- mation. Nonetheless, it was not associated with liver steatosis and fibrosis. A serum zinc value of 89 (µg/dl) yielded a sensitivity and specificity of 93% and 86%, respectively, characterizing patients with lobular inflammation of less than two inflammatory foci per high-power field (HPF) from more advanced groups. Furthermore, a value of 79.55 (µg/dl) yielded a sensitivity and specificity of 87% and 100%, respectively, distinguishing those with a lobular inflammation grade of less than four foci per HPF from more advanced cases. Conclusion: Serum zinc level might be associated with the severity of lobular inflammation in NASH.
Mobile Encrypted Traffic Classification Using Deep Learning: Experimental Evaluation, Lessons Learned, and Challenges

The massive adoption of hand-held devices has led to the explosion of mobile traffic volumes traversing home and enterprise networks, as well as the Internet. Traffic classification (TC), i.e., the set of procedures for inferring (mobile) applications generating such traffic, has become nowadays the enabler for highly valuable profiling information (with certain privacy downsides), other than being the workhorse for service differentiation/blocking. Nonetheless, the design of accurate classifiers is exacerbated by the raising adoption of encrypted protocols (such as TLS), hindering the suitability of (effective) deep packet inspection approaches. Also, the fast-expanding set of apps and the moving-target nature of mobile traffic makes design solutions with usual machine learning, based on manually and expert-originated features, outdated and unable to keep the pace. For these reasons deep learning (DL) is here proposed, for the first time, as a viable strategy to design practical mobile traffic classifiers based on automatically extracted features, able to cope with encrypted traffic, and reflecting their complex traffic patterns. To this end, different state-of-the-art DL techniques from (standard) TC are here reproduced, dissected (highlighting critical choices), and set into a systematic framework for comparison, including also a performance evaluation workbench. The latter outcome, although declined in the mobile context, has the applicability appeal to the wider umbrella of encrypted TC tasks. Finally, the performance of these DL classifiers is critically investigated based on an exhaustive experimental validation (based on three mobile datasets of real human users’ activity), highlighting the related pitfalls, design guidelines, and challenges.
Experimental evaluation of population trend and harvest composition in a Wyoming cougar population

Abstract Cougar (Puma concolor) management has been hindered by inability to identify population trends. We documented changes in sex and age of harvested cougars during an experimentally induced reduction in population size and subsequent recovery to better understand the relationship between sex–age composition and population trend in exploited populations. The cougar population in the Snowy Range, southeast Wyoming, was reduced by increased harvest (treatment phase) from 58 independent cougars (>1 year old) (90% CI=36–81) in the autumn of 1998 to 20 by the spring of 2000 (mean exploitation rate=43%) and then increased to 46 by spring 2003 following 3 years of reduced harvests (mean exploitation rate=18%). Pretreatment harvest composition was 63% subadults (1.0–2.5 years old), 23% adult males, and 14% adult females (2 seasons; n=22). A reduction in subadult harvest, an initial increase followed by a reduction in adult male harvest, and a steady increase in adult female harvest characterized harvest composition trends during the treatment phase. Harvest composition was similar at high and low densities when harvest was light, but proportion of harvested subadult males increased at low density as they replaced adult males removed during the treatment period (high harvest). While sex ratio of harvested cougars alone appears of limited value in identifying population change, when combined with age class the 2 appear to provide an index to population change. Composition of the harvest can be applied to adaptively manage cougar populations where adequate sex and age data are collected from harvested animals.
INTEGRATING MULTI-TEMPORAL SAR IMAGES AND GPS DATA TO MONITOR THREE-DIMENSIONAL LAND SUBSIDENCE

Abstract. Synthetic aperture radar (SAR) is an effective means of monitoring land subsidence, and differential interferometric SAR (DInSAR) is commonly used to acquire the necessary data. In particular, persistent scatterer interferometry (PSI) can be used to measure land subsidence accurately over a wide area from multi-temporal SAR images. However, the estimated displacement is obtained only in the radar line-of-sight (LOS) direction, making it necessary to develop a method for measuring three-dimensional displacements by combining multidirectional observations. Therefore, we propose herein a method for estimating three-dimensional displacement velocities by combining the results from PSI and geodetic deformation measurements, namely, Global Positioning System and leveling data. We apply the least-squares method to Kansai International Airport in Japan by using 13 ALOS-2/PALSAR-2 ascending images from 2014 to 2018 and 17 ALOS-2/PALSAR-2 descending images from 2015 to 2018. In validation, the rootmean- square errors are 14, 16, and 14 mm/year for the east–west, north–south, and vertical components, respectively, showing that combining PSI results and geodetic deformation measurements is effective for monitoring land subsidence.
The Role of the Hallyu Phenomenon in Shaping a Destination Image among Malaysian Adolescents

Hallyu refers to the surge of global visibility of popular Korean cultural products, such as Korean entertainment including music, television (TV) shows, dramas and films, cuisine, and fashion. The commodification of these products by the Korean Government to sustain and strengthen their culture worldwide has led to the emergence of Korea as one of the top tourism destinations in the world. However, the exponential growth of the country’s broadcasting and entertainment industry appears to greatly impact the values and ways of life among people, especially adolescents. Given the scarcity of tourism studies that investigate this impact, it is the aim of this research to analyse the mediating role of the idolisation of celebrities among adolescents in the State of Terengganu, Malaysia on the Korean music, TV shows and dramas, and the destination image. The data was collected through convenience sampling, where 301 usable questionnaires were subsequently analysed using descriptive, regression, and mediating analyses. It can be reported that both music, and television shows and dramas have a statistically significant relationship with the idolisation and the destination image. This is also the case in the context of the relationship between idolisation and the destination image. Interestingly, idolisation does not have the mediating impact on both independent variables and the destination image. These empirical results provide valuable insights to relevant stakeholders for the purpose of the strategic marketing of cultural products abroad and through the improvement of national brand value.
Smart distribution system

The main idea in smart-grid concept is the integration of active communication in the power system. Traditionally, the communication in the power system is more toward the one-way approach. All the instructions of operations are given by the utility and will be operated by the controller at the load side, either by using supervisory control and data acquisition or by other simple means of communication. However, in a smart-grid topology, the load should be able to give the information to the utility or even be able to make decisions based on the feedback provided by the end user. In this chapter, the discussion on the concept of communication integration in balancing the system frequency is discussed. The load demand will adjust the power consumption by changing their operation mode, depending on their frequency condition. The technology in telecommunications has advanced tremendously within the recent decades; we do not have to reinvent the wheel. The same technology, such as the network protocols and standards, can be implemented to the existing power system to add the smart element with the aim to make the system more efficient and robust. Furthermore, the whole world is moving toward connectivity and ubiquity; the best way forward is to embrace this change and synergize the power system components with the telecommunications components to create a smarter and efficient power control system.
UTILIZING E‐LEARNING TOOLS TO FOSTER KNOWLEDGE MANAGEMENT PRACTICES IN MARITIME EDUCATION & TRAINING

Knowledge management is widely considered as a key driver for an organization’s innovations. Indeed, better utilizing intellectual property and promoting expertise exchange is a topic that has been discussed extensively within the MET discipline. With the fast advancement in information communication technology, there are opportunities for an organization in the maritime industry, includes MET institutions, to tackle some traditional barriers to knowledge management practices in an effective manner. However, depending on various situations, there are a number of factors that might affect the processes of managing knowledge within an organization. The causes of these failures range from lack of management support; improper planning, design, coordination and evaluation; inadequate skill of knowledge manager and worker; having problem with organizational cultural and structure; Disoriented implementation of supportive technology, budgeting and excessive cost. This paper reviews, synthesises, and discusses some key factors that affect the knowledge management practices in relation to the maritime sector. Several challenges that can hinder the implementation process are identified and discussed. We suggest how a MET institution effectively can utilize modern technologies, including E-learning tools, other various existing web-based application and cloud-based application to foster knowledge management practices. We also introduce an knowledge management application framework that describe the possibilities of how these technologies can interact with each others and with the users of an organization.
A CONTEMPORARY OUTLOOK ON HUMAN ELEMENT IN ENERGY EFFICIENT SEABORNE TRANSPORTATION

This paper addresses human element issues in the current discussions on energy efficiency in the maritime transport. Shipping is generally known as the most environmentally friendly mode of transport (Boon, 2007) in terms of CO2 produced per ton nautical mile. Nevertheless, there is still immense potential in various technical and operational areas remained for improving energy efficiency in the sector. These measures, not limited to, include ship design, hull and propeller efficiency, alternative fuels, renewable energy, weather routing, fleet management and so forth. Despite an extensive amount of research available to improve energy efficiency in shipping, the implementation of such measures has not been progressed by the industry as expected (Johnson and Andersson, 2014). In addition, the area of human element when operationalising the concept of energy management in practice is under-researched. This paper draws attention to barriers, human behaviour, and change management theory in the process of integrating energy management measures into the workplace from the organisational to personal level. For example, how does the organisational change influence human behaviour in the context of energy management? How do the personnel in a maritime organization or on board a vessel take on energy management in their routines of work? What leads to cultivate a mindset of energy efficiency among workers in the organisations? This paper revisits the contemporary discussions related to energy efficiency in shipping and focuses on human element to support the process of implementing energy management for a sustainable maritime transport system (IMO, 2013). It can be concluded that more emphasis on human element in the area of energy management will help the development of an implementation mechanism for the sustainable shipping, and thereby human element should be focused both in education and research on energy management. Such academic efforts will make a substantial contribution to the contemporary debates in interdisciplinary science and technology.
High Gain Bow-Tie Slot Antenna Array Loaded With Grooves Based on Printed Ridge Gap Waveguide Technology

The development of wireless and satellite communication has led to a demand for high-performance microwaves and mm-wave components in terms of cost, losses, and fabrication complexity. Gap waveguide is one of the emerging technologies in 5G and mm-wave applications due to their low cost, low losses, and high power handling capability. In this paper, a groove-based wideband bow-tie slot antenna array is designed at 30 GHz based on printed ridge gap waveguide technology (PRGW). A two-section T-shaped ridge is designed to feed a bow tie slot placed on the upper ground of the PRGW. The gain of the proposed slot antenna is enhanced by using a horn-like groove. Then, the proposed high gain element is deployed to build up a 1 bow-tie slot antenna array loaded with three-layer groove antenna. The proposed antenna array is fabricated and measured, where the measured results show a −10-dB impedance bandwidth from 29.5 to 37 GHz (22%). The fabricated prototype achieves a high gain of 15.5 dBi and a radiation efficiency higher than 80% over the operating frequency bandwidth.