Miracle-dz/UniFAR-FTUs huggingface dataset:
Construction of a Switching Support System for Live Broadcast of Oral Presentation

: In this paper, we propose a switching support system for live broadcast of oral presentation. Analysis of the switching of professional switchers revealed that, in 57 oral presentations, professional switchers carry out switching based on events such as the presenter moving onto a new slide or pointing to the screen. In this paper, with the goal of even switching beginners being able to do switching intuitively, we proposed an event-based switching interface reﬂecting special characteristics of switching. We implemented a prototype of the proposed system and used it to conduct an evaluation experiment. The results of the experiment suggested that the proposed method can be operated as easily as the previous method and that the proposed method conforms to professional switching more than the previous method.
Generating Adversarial Examples for Hardware-Trojan Detection at Gate-Level Netlists

: Recently, the great demand for integrated circuits (ICs) drives third parties to be involved in IC design and manufacturing steps. At the same time, the threat of injecting a malicious circuit, called a hardware Trojan, by third parties has been increasing. Machine learning is one of the powerful solutions for detecting hardware Trojans. However, a weakness of such a machine-learning-based classiﬁcation method against adversarial examples (AEs) has been reported, which causes misclassiﬁcation by adding perturbation in input samples. This paper ﬁrstly proposes a framework generating adversarial examples for hardware-Trojan detection at gate-level netlists utilizing neural networks. The proposed framework replaces hardware Trojan circuits with logically equivalent ones, and makes it di ﬃ cult to detect them. Secondly, we propose a Trojan-net concealment degree (TCD) and a modiﬁcation evaluating value (MEV) as measures of the amount of modiﬁcations. Finally, based on the MEV, we pick up adversarial modiﬁcation patterns to apply to the circuits against hardware-Trojan detection. The experimental results using benchmarks demonstrate that the proposed framework successfully decreases the true positive rate (TPR) by a maximum of 30.15points.
Novel Bi-directional Flow-based Traffic Generation Framework for IDS Evaluation and Exploratory Data Analysis

: Flow-based network tra ﬃ c information has been recently used to detect malicious intrusion. However, several available public ﬂow-based datasets are unidirectional, and bidirectional ﬂow-based datasets are rarely available. In this paper, a novel framework to generate bidirectional ﬂow-based datasets for IDS evaluation is proposed. The generated dataset has the mixed combination of normal background tra ﬃ c and attack tra ﬃ c. The background tra ﬃ c is based on the key tra ﬃ c feature of the MAWI network tra ﬃ c traces, and ﬁve popular attack tra ﬃ cs are generated based on their statistical tra ﬃ c features. The generated dataset is characterized using the PCA approach, and we found out that benign and malicious tra ﬃ c are distinct. With the proposed framework, a dataset of bi-directional ﬂow-based tra ﬃ c is generated and it would be used for evaluating an e ﬀ ective intrusion detection engine.
Replay Attack Detection Based on Spatial and Spectral Features of Stereo Signal

: In this paper, we propose a replay attack detection (RAD) method that uses spatial and spectral features of a stereo signal. To distinguish genuine and replayed utterance, we focus on non-speech segments, in which a human does not emit sound, but a loudspeaker for replay attack might emit some recorded noise or its electromagnetic noise. The generalized cross-correlation (GCC) based spatial features capture this di ﬀ erence. To improve the robustness against the variety of recording environments, we combine the spatial features with spectral features. In particular, we fuse the output scores of GCC-based and spectral feature-based methods. In experiments, we conﬁrm the e ﬀ ectiveness of the combination of spatial and spectral features.
Accurate Contention-aware Scheduling Method on Clustered Many-core Platform

: Embedded systems such as self-driving systems require a computing platform with high computing power and low power consumption. Multi-/ many-core platforms deﬁnitely meet these requirements. However, for hard real-time applications, multiple demands on shared resources can hinder real-time performance. Memory is one of the resources that can most dramatically impair desired performance. Therefore, we addressed contentions induced by shared memory. The ability to predict contentions that may occur during memory access helps to reduce them. We improved the predictability of contentions by dividing tasks into the memory access phase and the execution phase using a Directed Acyclic Graph (DAG). Existing methods can make accurate contention estimations for one Compute Cluster (CC) of a clustered many-core processor. Our method is able to perform accurate contention estimations for multiple CCs, thereby doubling the scalability when contentions are taken into account. Using an Integer Linear Programming (ILP) formulation, we produced a static, non-preemptive, partitioned, and time-triggered schedule. We also conducted an experiment in order to minimize the makespan. The evaluation conﬁrmed that our new method reduced the makespan by increasing the number of CCs.
HIGHLY HOMOGENEOUS NITROGEN DOPED TITANIA NANOMATERIALS: SYNTHESIS AND CHARACTERIZATION

A series of nitrogen doped titania nanomaterials were synthesized via sol-gel method by using tetraethyl ammonium hydroxide as N source. Doping of N into TiO 2 was confirmed via X-ray diffraction (XRD) and fourier transform infrared spectroscopy (FTIR) analyses. Mixture of anatase and rutile phases appeared in the unmodified TiO 2 which was calcined at 773 K. The addition of N to TiO 2 matrix led to formation of single phase of anatase. It has been demonstrated thatTiO 2 and all the N-doped TiO 2 materials were in nanoscale ranging 15.91 – 20.82 nm. Change in surface morphology after N doping was detected by field emission scanning electron microscope (FESEM). Results of EDX mapping analysis indicated homogeneous distribution of N dopants.
STOCK MARKET REACTION TO IRAN NUCLEAR NEWS

Received 12th, September, 2016, Received in revised form 18 th, October, 2016, Accepted 24th, November, 2016, Published online 28th, December, 2016 The purpose of this study is to analyze the consequence of Iran nuclear newson Tehran Stock Exchange (TSE) market. Since 2002 Iranian people and the three governments(Reformist party led by Seyyed Mohammad Khatami, Fundamentalist party led by Mahmoud Ahmadinejad, Moderation and Development Party led by Hasan Rouhani) were involve in nuclear issue. Undoubtedly, according to all the economic experts and politicians economic sanctions are highly affected Iranian economy. We split the nuclear news into two categories (good and bad news) between 2002 to 2015 years. We used univariate asymmetric GARCH model. The results show that TSE had no meaningful reaction to good news and in some exceptional casesshowa slight positive reaction. On the other hand, all bad nuclear news has considerable negative influence on the returns and increase the TSE instability. Further, our results also confirm that bad nuclear news has stronger effect than good nuclear news. Allselectedindustries are also affected by bad news in the same way as TSE index. We also found that sixindustriesBanking, Automotive, Petrochemical, Finical mediation, Pharmaceuticals, Steel respectively are highly affected by bad nuclear news and their reaction to good nuclear news isinsignificant.
Comparative physiological assessment of some edible oil seed crops under drought stress environment using fluorescence and IR imaging techniques

Comparative physiological assessment of some edible oilseed crops under drought stress environments were performed. In this regard, fluorescence and IR thermal imaging techniques were used. Seeds of each sunflower SF0049, SF0054 and soybean NARC-II, William-82 cultivars were germinated. Followed by uniform seedlings of each cultivar were transplanted in rectangular pots of an area 480cm. Three weeks old plants were subjected to drought stress for the next five days. Chlorophyll ‘a’ fluorescence, IR images, relative water content (RWC) and stomatal conductance (gs) were recorded. In drought stress, NARC II and William-82 showed 26-31% reduction in RWC as compared to 18-20% reduction in SF0049 and SF0054. Similarly, 6787% reduction in stomatal conductance was observed in soybean and 59-72% were recorded in sunflower cultivars. Further soybean cultivars displayed 44.4% to 85.7% decrease in performance index (PI) and darkadapted quantum yield (Fv/Fm) as compared to 40% to 87% in sunflower cultivars. Maximum yield of photochemistry of PSII and chlorophyll content index were also reduced up to 28-68% in all tested cultivars under drought stress. Nonphotochemical quenching, heat dissipation, and leaf temperature were increased over control under drought stress showing maximum in soybean as compared to sunflower. The importance of comparative physiological assessment using fluorescence and IR thermal imaging techniques are discussed.
Transliterating Nôm Scripts into Vietnamese National Scripts using Statistical Machine Translation

Nom scripts were used as the Vietnamese writing system from the 10th century to the early 20th century. During this period, Nom scripts were the means to record a broad range of historical events, literary works, medical knowledge, as well as wisdom of many other domains. Unfortunately, since hardly any native Vietnamese speaker can read Nom scripts nowadays, these valuable documents have not been fully harnessed. To address this gap, it is necessary to build an automatic transliteration system that can support us in decoding the ancient scripts and gaining knowledge of our Vietnamese ancestors. This study focuses on categorizing and reviewing the current progress on the Statistical Machine Translation (SMT) approaches to transliterate Nom scripts into Vietnamese national scripts. In this paper, we discuss the differences between Nom scripts and Vietnamese national scripts, systematically compare SMT models in transliterating Nom scripts into Vietnamese national scripts, as well as having a thorough outlook on several promising research directions.
Vaginal cuff dehiscence after laparoscopic trachelectomy post hysterectomy: a case report and brief review of the literature

Hysterectomy is a very common gynecologic procedure and is moving more and more towards the minimally invasive field. Vaginal cuff dehiscence (VCD) is a serious complication of hysterectomy with high morbidity. Presentation varies from a small opening in the vagina wound to serious evisceration evisceration/bowel ischemia and sepsis. The incidence of VCD has increased during the last decades as total laparoscopic hysterectomies (TLH) and trachelectomies with laparoscopic closure of the vaginal cuff have become routine. However, it is poorly discussed in the literature, with mostly case reports or case series with most studies being underpowered with heterogeneity and lack of comparison groups. There are numerous factors which have been associated with VCD, such as vaginal opening and closing techniques, the use of electrocoagulation, duration of the procedure, experience of the surgeon, postoperative infection or hematomas, patient characteristics and patient conformity during the recovery period (straining, weight lifting, early onset of sexual intercourse etc). Trying to minimize the impact of this complication one should consider reducing as much as possible the use of thermal energy, possibly use delayed absorbable sutures with adequate tissue bites and ABSTRACT
Finite element method modeling of crankshaft axial im- pact measurements

It has been recently discovered that there is a periodical axial impact phenomenon in a running engine crankshaft. Bending of the shaft causes significant extension of the crankshaft and impact to the engine block through the axial thrust bearing. The aim of this work is to study impact-induced energy fluctuations in a complex-shaped Wärtsilä sixteen vee 32 engine crankshaft by using an explicit finite element method (FEM) during the first 25 ms after impact. Using the FEM allows us to study real components used in industry, and analyze their dynamics in the transient phase. In conclusion, we found interesting results that can be used as guidelines for a full-scale crankshaft measurement instrumentation plan. The full-scale measurements will be performed later in the Wärtsilä Oy facility at Vaasa, Finland. The main finding is that a substantive amount of energy is trapped in the head region and the first two crank pins of the crankshaft, which can affect crankshaft durability regarding high-cycle fatigue.
The Effect of School Climate on Pre-Service Physical Education Teachers’ Burnout Syndrome: The Mediator and Regulatory Role of Class Level

The main purpose of this study is to examine the mediating and regulatory role of current classroom levels in the relationship between the school climate as perceived by prospective physical education and sports course teachers and their feelings of burnout. The participants in this study included 303 teaching students, 144 women, and 159 men. The school climate scale and the school burnout scale were used to collect data. Hypotheses were tested using correlation and regression-based path analysis. The results showed that there is a negative significant relationship between perceived school climate at 1st, 2nd and 4th grade levels and school burnout, and a positive significant relationship between perceived school climate at the 3rd grade level and school burnout. In the relationship between the perceived school climate and feelings of burnout, class level has a mediating and regulatory effect. In addition, it has been determined that higher class level strengthens the feeling of burnout, while a low level weakens this feeling. By comparing the obtained results with the findings in the literature, suggestions were made to sports education researchers.
Mobile Data Visualization Techniques Group 4 HCI Winter School

As all kinds of mobile devices continually emerge, mobile visualization is becoming more prevalent. Mobile devices have their own convenience in mobility and input, but also usually limited in terms of display size. Therefore, it’s important to reflect on what has been discovered to date on mobile visualization and to look into the future. In this review, we mainly focus on three subtopics of mobile visualization: Responsive Visualization, Glanceable Visualization, and Extended Reality Visualization. Responsive Visualization is about how to visualize data so that they can fit into different display sizes. Glanceable Visualization aims to visualize data in a way that users can easily get important information in a short glance. These two subtopics are two of the most important basics of mobile visualization. Then we look into some interesting researches about extended reality that could bring more flow experiences and interactions on mobile devices.
Identification of Somatic Antigens of Adult Fasciola gigantica Isolated from Bali Cattle

In most tropical countries, such as Indonesia, fasciolosis is generally caused by Fasciola gigantica known as tropical liver fluke. However, most fasciolosis serodiagnostic tests have been developed solely for diagnosing fasciolosis caused by Fasciola hepatica (non-tropical liver fluke), and very few have been specifically designed for F. gigantica. The aim of this study was to determine the profile of antigenic proteins from the somatic extract of F. gigantica isolated from Bali cattle (Bos javanicus). The liver flukes were collected from a slaughtering house in Mataram, Indonesia. The somatic extracts were prepared by homogenizing in buffers containing 0.05 M NaCl, 0.02 M PMSF, and 0.05% Triton X-100. The characterization of the somatic extract proteins was performed using one-dimension gel electrophoresis and followed by Western blotting to determine the profile of its antigenic proteins. There were 14 bands of the somatic extracts with an estimated molecular weight ranging from 8 to105 8 kDa shown on the gel electrophoresis. The results of the Western blot show that there were five prominent protein bands. Three out of five prominent antigenic proteins with molecular weights of 8, 27, and 33 kDa are promising to enrich the existence of antigens that have immunodiagnostic value for fasciolosis. Therefore, further studies are required to examine more deeply the potency of those three antigenic somatic proteins of F. gigantica.
JMSCR Vol||08||Issue||01||Page 179-183||January

Introduction: Sepsis with multi organ dysfunction syndrome (MODS) is a common cause of Intensive Care Unit mortality and morbidity. Scoring systems helps to quantify the disease severity probability of mortality in hospital. But, this study focuses mainly on Sequential Organ Failure Assessment (SOFA) score. Patients and Methods: 50 patients admitted with a diagnosis of Sepsis were included in the study. Results: Among 50 patients, 18 patients died and 32 patients survived.various parameters of SOFA score were assessed among survivors and Nonsurvivors. Conclusion: Daily measurement of SOFA score during first week is useful tool in predicting the outcome. The trend of SOFA score was progressively declining in survivors while non-survivors had stable higher score during thefirst week. Introduction Sepsis with multi organ dysfunction syndrome (MODS) is a common cause of Intensive Care Unit mortality and morbidity. The primary cause; infectious or non infectious, triggers an uncontrollable inflammatory response. Sepsis can be reversed, but as sepsis progresses to severe sepsis and septic shock the mortality rate substantially increases. Multi organ dysfunction syndrome is well established as the final stage of the continuum. Due to the high mortality associated with sepsis and its complications it is necessary to rapidly diagnose and treat the underlying cause. Various clinical, biochemical and haematological parameters in septic patients serve as the indicators of organ dysfunction and hence, can be used to define the prognosis in a patient with sepsis. When a patient is admitted in ICU, the aetiology is usually not established. The intensivists have very little data to treat such patients in the first 24 to 48 hours which are crucial in reversing the process of sepsis and multi organ dysfunction. There are many scoring systems which are helpful in prognosticating the severity and outcome. Scoring systems helps to quantify the disease severity and probability of mortality in hospital. It also guides the physician regarding the patient prognosis. There are many scores available at present. But, this study focuses mainly on Sequential Organ Failure Assessment (SOFA) score. Patients and Methods The study was carried from December 2017 to August 2019 and 50 patients were included in the study. The patients satisfying criteria according to American College of Chest Physicians/Society of Critical Care Medicine (ACCP/SCCM) Consensus Committee in 1992 were included in the study. The http://jmscr.igmpublication. org/home/ ISSN (e)-2347-176x ISSN (p) 2455-0450 DOI: https://dx.doi. org/10.18535/jmscr/v8i1.24
Innovation and technological watch on Wall-Sized Displays

Wall-sized displays are parts of many innovative systems and are the key to a large number of prototypes for future possible designs. Indeed, previous works show that wall-sized screens are useful tools that provide a large screen allowing great advantages for collaborative works, data visualization and novel forms of interactions. The non-commercialization of wall-sized displays to the general public makes it even more interesting to explore since there is no interaction anchored in the common spirit yet. Therefore, there is no standard way of interacting with Wall-sized displays which is an advantage for creating new interaction techniques but which can become a disadvantage for analyzing and classifying new techniques in terms of efficiency. Through previous works reviews, we discuss about different interactions possible on wall-sized displays and situations where the use of a wall-sized display can be beneficial for future designs.
IKKe in osteoclast inhibits the progression of methylprednisolone-induced osteonecrosis

Previous studies have described that NF-κB signaling mediated by NFκB-inducing kinase (NIK) plays a critical role of the differentiation of osteoclasts. We aim to explore the role of IKKe in methylprednisolone -induced osteonecrosis of the femoral head (ONFH). Methylprednisolone-induced ONFH mice model was successfully established, and subjected to micro computed tomography to detect the femoral head image of the mice. Bone marrow cells from experimental mice were collected and cultured. qPCR and immunoblot were performed to examine the possible signal pathways of IKKe involvement, and osteoclast-related gene expressions in IKKe+/+ and IKKe-/- cells in vitro and in vivo were examined. It was found that the levels of IKKe decreased in ONFH patients, and IKKe interacted with NIK in the NF-κB signal pathway to suppress osteoclasts via inhibiting the transcription of NIK. Furthermore, IKKe knockout promoted the osteoclastogenesis in mice model. Finally, IKKe knockout suppressed methylprednisolone-induced ONFH and pro-inflammatory responses in mice model. Our findings show a mechanism of IKKe inhibition of the progression of methylprednisolone-induced ONFH via the NIK/NF-κB pathway.
Learning Sparse Matrix Row Permutations for Efficient SpMM on GPU Architectures

Achieving peak performance on sparse operations is challenging. The distribution of the non-zero elements and underlying hardware platform affect the execution efficiency. Given the diversity in workloads and architectures, no unique solution always wins. In this paper, we improve SpMM efficiency on GPUs. We propose several simple, but effective, sparse data permutations on the CSR data structure. Picking the right permutation over 1,688 datasets improves performance by 1.4×, on average, compared to plain CSR and 2.6× against NVIDIA cuSPARSE. Furthermore, we propose a set of novel features to describe sparsity patterns and their interactions with the kernel and hardware. Using these features, we develop a predictor to select the best permutation for each matrix. Predicted permutations' average gain achieves 96% of oracle gains.