Miracle-dz/UniFAR-FTUs huggingface dataset:
MixDroid: A multi-features and multi-classifiers bagging system for Android malware detection

In the past decade, Android platform has rapidly taken over the mobile market for its superior convenience and open source characteristics. However, with the popularity of Android, malwares targeting on Android devices are increasing rapidly, while the conventional rule-based and expert-experienced approaches are no longer able to handle such explosive growth. In this paper, combining with the theory of natural language processing and machine learning, we not only implement the basic feature extraction of permission application features, but also propose two innovative schemes of feature extraction: Dalvik opcode features and malicious code image, and implement an automatic Android malware detection system MixDroid which is based on multi-features and multi-classifiers. According to our experiment results on 20,000 Android applications, detection accuracy of MixDroid is 98.1%, which proves our schemes’ effectiveness in Android malware detection.
Integration of Vestibular and Cervical Information to Code Trunk Motion

The contribution of vestibular signals to motor control has been evidenced in postural, locomotor, and oculomotor studies. Here, we review studies showing that vestibular information also contributes to the control of arm movements during whole-body motion. The data reviewed suggest that vestibular information is used by the arm motor system to maintain the initial hand position or the planned hand trajectory unaltered during body motion. This requires integration of vestibular and cervical inputs to determine the trunk motion dynamics. These studies further suggest that the vestibular control of arm movement relies on rapid and efficient vestibulomotor transformations that cannot be considered automatic. We also reviewed evidence suggesting that the vestibular afferents can be used by the brain to predict and counteract body-rotation-induced torques (e.g., Coriolis) acting on the arm when reaching for a target while turning the trunk.
Expert CF: Solving Data Matrix Sparsity and Computation Complexity Problems

Collaborative Filtering (CF) is widely used to provide recommendations in ecommerce systems. CF works on a large data set by constructing an item-user matrix through association analyses among items and similarity analyses among users. However, CF suffers from data sparsity and computation complexity. This paper introduces a concept of “experts” to overcome the two identified problems. An expert is an artificially created user, who represents a cluster of users in terms of behavior and taste. The construction of experts can be done off-line through data filtering and classification. In actual recommendation, when data are spars, a number of experts can be added as existing users to predicate shopping habit for a particular user. The mechanism of “off-line expert’s construction” and “on-line expert’s addition” in recommendation not only to overcome the data sparsity but also improving on scalability by reduce computation in recommendation phase.
Tomographic imaging of the crust toward south of southern granulite terrain ( SGT ) , India and its geodynamic implications

The crustal tomographic image is obtained toward south of SGT, India using deep seismic sounding data along 220 km N-S Vattalkundu-Kanyakumari profile acquired in 2005. The image depicts both subsurface structural and velocity heterogeneities along with numerous shear zones. The crust is thickest near Vattalkundu (44 km) and gradually thins toward Kanyakumari (36 km) with intracrustal undulations. The P-wave velocities for upper and lower crust range from 6.0-6.4 km/s and 6.7-7.1 km/s, respectively. The thick crust (>40 km) with high average velocity (>6.7 km/s) and high heat-flow (~58 mW/m 2 ) indicates complex tectonothermal evolution of the region. The Bouguer gravity data also show anomalous signatures near the Achankovil shear zone and the density model derived corroborates both preferred and tomographic velocity models. The high velocity (>6.9 km/s) and density (>2.9 g/cm 3 ) magmatic materials in the mid to lower crust is inferred as underplating. The thick (~10 km) lower crust with velocity 7.1 km/s and density 2.98 g/cm 3 show significant Moho upwarping due to mantle upwelling toward southern end. The presence of numerous shear zones with high-grade charnockite massifs in the upper crust exposed in several places reveal large scale exhumation of lower crustal rocks during the Pan-African rifting (~550 Ma). The final tectonic model derived show large compositional changes of rocks having horsts and grabens in the upper crust with exhumed granulites/charnockites forming a complex metamorphic province. The source region of exhumation lies at a depth of 20-30 km. The Moho configuration derived from tomography agrees well with preferred model.
Investigation of Low-Temperature Optical Characteristics of InGaN / GaN Based Nanorod Light Emitting Arrays

For InGaN/GaN based nanorod devices using topdown etching process, the optical output power is affected by non-radiative recombination due to sidewall defects (which decrease light output efficiency) and mitigated quantum confined Stark effect (QCSE) due to strain relaxation (which increases internal quantum efficiency). Therefore, the exploration of lowtemperature optical behaviors of nanorod light emitting diodes (LEDs) will help identify the correlation between those two factors. In this work, low-temperature EL spectra of InGaN/GaN nanorod arrays was explored and compared with those of planar LEDs. The nanorod LED exhibits a much higher optical output percentage increase when the temperature decreases. The increase is mainly attributed to the increased carriers and a better spatial overlap of electrons and holes in the quantum wells for radiative recombination. Next, while the nanorod array shows nearly constant peak energy with increasing injection currents at the temperature of 300K, the blue shift has been observed at 190K. The results suggest that with more carriers in the quantum wells, carrier screening and band filling still prevail in the partially strain relaxed nanorods. Moreover, when the temperature drops to 77K, the blue shift of both nanorod and planar devices disappears and the optical output power decreases since there are few carriers in the quantum wells for radiative recombination.
Internet of Things Behavioral-Economic Security Design, Actors & Cyber War

Using security incident history we identify threats to and using the IoT and other ubiquitous devices emerging since 2012, gaining widespread recognition in 2016, and only lightly addressed in either IoT security literature or the press. We show the IoT has likely already been used in cyber war between major powers. The new threats, most notably “hijack,” are larger than previous threats combined, but only mildly affect suppliers, and only a few clients. Using a successful behavioral-economic model we show that traditional mitigation places responsibility on un-affected parties and likely will not work. For suppliers, there are profit-conflicted motives, as the new threat rides on a profit vehicle. The new threat circumvents conventional security architecture at a behavioral level. We analyze each actor-target pair and evaluate technical strategies. More effective technical strategies are suggested where old ones are overmatched by the budgets, technical prowess or regulatory power of hostile actors, or the technical nature of the threats. Consolidated action may be needed, but regulation is difficult because of conflicts of interest within the national security community.
Mini-invasive Surgery

Ablative techniques (AT) offer a combination of nephron-sparing and minimally invasive approaches. AT include different options and cryoablation (CA) and radiofrequency ablation (RFA) have been relatively safe and traditionally can be either performed laparoscopically or percutaneously. CA and RFA have emerged as a leading option for renal ablation, and compared with surgical techniques they offer benefits in preserving renal function with fewer complications, shorter hospitalization times, and allow for quicker convalescence. A mature dataset exists at this time, with intermediate and long-term follow up data available. Generally, laparoscopic access was the first technique used in the past, and typically for anterior and lateral mass. Afterwards, with the improvements in imaging and percutaneous techniques, laparoscopic approaches are progressively decreased and currently limited in few lesions and in relation with the surgeon’s and center’s experience. Nevertheless, laparoscopic CA and RFA could be useful techniques and currently, recommendations as a first-line therapy are made at this time in limited populations, including elderly patients, patients with multiple comorbidities, and those with imperative indications of a nephron sparing surgery. As more data emerge on oncologic efficacy, and technical experience continue to improve, the application of AT will likely be extended in future treatment guidelines and laparoscopic approaches will be a valid option in the era of tailored therapy.
Design and Implementation of Cache Memory with Dual Unit Tile / Line Accessibility

In recent years, the increasing disparity between the data access speed of cache and processing speeds of processors has caused a major bottleneck in achieving high-performance 2-dimensional (2D) data processing, such as that in scientific computing and image processing. To solve this problem, this paper proposes new dual unit tile/line access cache memory based on a hierarchical hybridZ-ordering data layout andmultibank cache organization supporting skewed storage schemes.Theproposed layout improves 2D data locality and reduces L1 cache misses and Translation Lookaside Buffer (TLB) misses efficiently and it is transformed from conventional raster layout by a simple hardware-based address translation unit. In addition, we proposed an aligned tile set replacement algorithm (ATSRA) for reduction of the hardware overhead in the tag memory of the proposed cache. Simulation results using Matrix Multiplication (MM) illustrated that the proposed cache with parallel unit tile/line accessibility can reduce both the L1 cache and TLB misses considerably as compared with conventional raster layout and Z-Morton order layout. The number of parallel load instructions for parallel unit tile/line access was reduced to only about one-fourth of the conventional load instruction.The execution time for parallel load instruction was reduced to about one-third of that required for conventional load instruction. By using 40 nm Complementary Metal-Oxide-Semiconductor (CMOS) technology, we combined the proposed cache with a SIMD-based data path and designed a 5 × 5mm Large-Scale Integration (LSI) chip. The entire hardware overhead of the proposed ATSRA-cache was reduced to only 105% of that required for a conventional cache by using the ATSRA method.
1 EXC / P 209 Plasma Shape Feedback Control on EAST

The shape feedback control was realized for diverted plasma using RTEFIT for the plasma equilibrium reconstruction and ISOFLUX control method in EAST PCS (EAST Plasma Control System). In a typical divertor plasma discharge, the plasma shape is feedback controlled from circular shape to elongated and fully diverted shape using different control algorithms. The smooth shape transition is essential for volt-seconds saving and plasma disruption avoidance. In order to achieve such aim, there is a trajectory used in EAST PCS for switching the control methods. The implementation details and experiment results are presented in this paper. Now, EAST has obtained stable double-null plasma operation for longer than 60 seconds with auxiliary heating and current drive by Low Hybrid Wave.
Toward A Typology of Dialogue and Deliberation by

Dialogue groups that bring together civilians with many perspectives on a conflict and hold face-to-face discussions differ. Facilitators f dialogue groups often claim that their type of dialogue is especially conducive to long-te rm peace and stability and results in a wider-ranging set of beneficial effects. To evaluat e such claims, this paper delineates dialogue groups and their goals by type (and offers a case study to illustrate its structure): 1) dialogue that transforms human relationships in order to build interpersonal trust and reduce prejudice (E.g. Jewish-Palestinian Living Ro om Dialogue focused on the ArabIsraeli conflict); 2) dialogue that transforms unde rstanding of political interest through consideration of the political interest of others i n order to build a common political vision for the future (E.g. Community Dialogue based on th e conflict in Northern Ireland); and 3) dialogue that transforms political decision-maki ng from interest-oriented to publicspirited-oriented dialogue in order to find mutuall y agreeable solutions (E.g. Deliberative Polling Weekends based on problems within mainly de veloped, peaceful Western countries like America). There is no evidence that one type is superior in transformational potential; the paper concludes by uggesting that the effectiveness of different types of dialogue is contingent upon the problem being addressed. Thesis Supervisor: Professor David D. Laitin Title: James T. Watkins IV and Elise V. Watkins Pro fessor in the School of Humanities and Sciences
Design methods of transversally laminated synchronous reluctance machines

Transversally laminated synchronous reluctance machine (SynRM) are usually designed with multiple-layer flux barriers to achieve high electromagnetic performance. This paper summarizes three design methods to optimize the machine. Related implementation procedures are detailed. Besides, advantages and disadvantages of these methods are discussed. Based on these conventional techniques, a comprehensive optimization method is proposed, with which a prototype SynRM is designed. The performances of this prototype are discussed to verify the optimal design method.
A COMPARATIVE ANALYSIS OF PHISHING WEBSITE DETECTION USING XGBOOST ALGORITHM

As most of human activities are being moved to cyberspace, phishers and other cybercriminals are making the cyberspace unsafe by causing serious risks to users and businesses as well as threatening global security and economy. Nowadays, phishers are constantly evolving new methods for luring user to reveal their sensitive information. To avoid falling victim to cybercriminals, a phishing detection algorithms is very necessary to be developed. Machine learning or data mining algorithms are used for phishing detection such as classification that categorized cyber users in to either malicious or safe users or regression that predicts the chance of being attacked by some cybercriminals in a given period of time. Many techniques have been proposed in the past for phishing detection but due to dynamic nature of some of the many phishing strategies employed by the cybercriminals, the quest for better solution is still on. In this paper, we propose a new phishing detection model based on Extreme Gradient Boosted Tree (XGBOOST) algorithm. Experimental results demonstrated that XGBOOST-based phishing detection model is promising by returning an accuracy of 97.27% which outperformed both probabilistic Neural Network (PNN) and Random forest (RF) that returned accuracies of 96.79% and 95.66% respectively. Keyword: Machine Learning, Feature Selection, Classification, XGBOOST, Phishing.
MODELING VOLATILITY USING GARCH MODEL : NASDAQ-100 APPLICATION

Modeling and forecasting stock market volatility is very important issue in many financial applications, and it has been the subject of numerous studies in financial markets, both theoretical and practical. In finance, volatility can be interpreted as a measure of fluctuation in a financial security price around its expected value. The main problem, which arises from the very definition of volatility, is the unstable nature of observed time series and its heteroscedasticity, making it impossible to apply certain time series models. First models to overcome these difficulties were ARCH and GARCH, followed by various extensions and modifications of GARCH model. This study empirically investigates the forecasting performance of GARCH model for the NASDAQ-100 stock index over the period Jan 2005– June 2011. NASDAQ-100 stock index reflects companies listed on the NASDAQ stock market across major industry groups including computer hardware and software, telecommunications, retail/wholesale trade and biotechnology. Future research can be directed towards integration of the proposed volatility forecasting model with artificial neural networks in order to capture nonlinear patterns.
Integrative Harm Reduction Psychotherapy : A Case of Substance Use , Mult iple Trauma

Harm reduction is a new paradigm that seeks to reduce the harmful consequences of substance use and other risky behaviors without requiring abstinence. This article discusses integrative harm reduction psychotherapy, one application of harm reduction principles to psychotherapy. Seven therapeutic tasks are described with attention to clinical process, skills, and strategies. A case is presented that illustrates the application of this approach with life-threatening substance use that was related to multiple trauma and suicidal depression. & 2010 Wiley Periodicals, Inc. J Clin Psychol: In Session 66: 123–135, 2010.
Bangladesh BOOTSTRAP BANDWIDTH SELECTION FOR A SMOOTH SURVIVAL FUNCTION ESTIMATOR FROM CENSORED DATA

Since the seminal paper by Efron [5], the bootstrap technique has been applied extensively to problems in the analysis of censored data. In this paper, the general problem is discussed, and a brief literature review is given. A new smooth estimator for the survival function is proposed, and its strong consistency proved. A bandwidth selection procedure based on Efron’s censored bootstrap that incorporates a plug-in principle is proposed to determine a choice for the optimal bandwidth. Simulations indicates favorable performance of the proposed estimator when compared to the original Kaplan-Meier estimator.
Diamond schemes:An organization of parallel memories for efficient array processing

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Diamond schemes:An organization of parallel memories for efficient array processing William Jalby, Jean-Marc Frailong, Jacques Lenfant
Constructing a Source Model Composed of Super Asperities for the 2011 off the Pacific Coast of Tohoku Earthquake

A source model was newly developed for the 2011 off the Pacific coast of Tohoku, Japan, earthquake (M9.0) to explain strong ground motions. The source model involves 9 subevents with relatively small size, located off-the-coast of Miyagi through off-the-coast of Ibaraki. Strong ground motions due to the earthquake were calculated based on site amplification and phase characteristics, using the constructed source model. The agreement between the observed and calculated ground motions is quite satisfactory, especially for the velocity waveforms (0.2-1.0 Hz) including near-source pulses. The author refers to the small subevents as “super asperities” in this article based the work of Matsushima and Kawase (2006), because the size of the subevents used in this study is much smaller than the size of the “asperities” or “SMGAs” conventionally assumed for a huge subduction earthquake.
Artificial Dreams : Contemporary Intersections Between Art and Technology

This paper approaches the intersectional field between art and technology from a Flusserian perspective applied to an interesting example: images generated through the program Google Deep Dream. These digital images that look like surrealist paintings are made through a distortion in Google’s artificial neural networks. I argue that these images problematize philosophical dualisms, like those between human intelligence and artificial intelligence, authorship and anonymity, individuality and collectivity, domination and deviation, art and technology.
Subjective Well-Being of Tourists

Title: Subjective Well-Being of Tourists Abstract: For the last decades adaptations of the SERVQUAL model have been used to measure tourist satisfaction. However, recent articles about tourist happiness put these models into question. Some authors argue that tourist satisfaction can more accurately be measured by taking the tourists’ well-being and happiness into account. Subjective Well-Being (SWB) represents the core of happiness research and is the scientific term for an individual’s evaluation of his or her experienced positive and negative affect, happiness or satisfaction with life. This paper shows how the positive and negative affects schedule (PANAS) can be adapted and used for the measurement of tourist satisfaction and its development over the course of the holidays.
A Global-Local Noise Removal Approach to Remove High Density Impulse Noise

Impulse noise removal from images is one of the most important concerns in digital image processing. Noise must be removed in a way that the main and important information of image is kept. Traditionally, the median filter has been the best way to deal with impulse noise; however, the image quality obtained in high noise density is not desirable. The aim of this paper is to propose an algorithm in order to improve the performance of adaptive median filter to remove high density impulse noise from digital images. The proposed method consists of two main stages of noise detection and noise removal. In the first stage, noise detection includes two global and local phases and in the second stage, noise removal is also done based on a two-phase algorithm. Global noise detection is done by a pixel classification approach in each block of the image and local noise detection is performed by automatically determining two threshold values in each block. In the noise removal stage only noise pixels detected from the first stage of the algorithm are processed by estimating noise density and applying adaptive median filter on noise-free pixels in the neighborhood. Comparing experimental results obtained on standard images with other proposed methods proves the success of the proposed algorithm.