Miracle-dz/UniFAR-FTUs huggingface dataset:
Josephson-type superconducting tunnel junctions as generators of microwave and submillimeter wave radiation

The use of Josephson-type superconducting tunnel junctions (two superconductors separated by a very thin insulating layer) as generators of radiation in the range 5 GHz to 1000 GHz is discussed. To this end, the results of recent experiments on the observation of X-band radiation from such junctions are presented, along with a complete discussion of the theory of such junctions. Their potential use as detectors, voltage sources, and harmonic multipliers is also discussed.
Useable Authentication Mechanisms for Secure Online Banking in Saudi Arabia

Two-factor identity authentication offers the most effective login security, and online and mobile banking users now use multi-factor identity authentication as the simplest and most innovative login security measure available for guaranteeing the privacy and safety of personal data. This system allows banks to recognize a client, while simultaneously verifying for the client whether he/she has accessed the correct bank‟s website or application prior to password entry. All internet and mobile banking authentication techniques may be categorized as preventing two common types of attack: offline credential theft and online channel-breaking attacks. It has therefore been recommended by security experts worldwide that a multi-factor authentication method be used for Internet and mobile banking authentication to ensure the safety of users‟ confidential data without undermining the ease of secure and simple authentication. Multi-factor internet and mobile banking authentication seems, therefore, to offer a solution through which the trade-off between safety and usability may be successfully negotiated. This study‟s primary objective is to propose various practical technological security mechanisms that will enable online banking customers in Saudi Arabia to select their preferred method of signing into online banking websites that are reliant on one-time password (OTP) techniques. The study included a survey aimed at ascertaining the various techniques used and which of these techniques were preferred. The experiment replicated an actual online banking setting utilizing the proposed methods; subsequently, the usability and safety of three different techniques for generating and communicating OTPs were assessed (SMS, e-mail, and soft and hard tokens).
Implementasi Metode String Matching Untuk Pencarian Berita Utama Pada Portal Berita Berbasis Android (Studi Kasus: Harian Rakyat Bengkulu)

Pencocokan string merupakan bagian penting dari sebuah proses pencarian string ( string searching ) dalam sebuah dokumen. Hasil dari pencarian sebuah string dalam dokumen tergantung dari teknik atau cara pencocokan string yang digunakan. portal berita memiliki satu server dan 10 administrator berdasarkan 10 Kabupaten/Kota, dimana aplikasi server memiliki klasifikasi berdasarkan hot news, kategori berita, dan pencarian berita. Sedangkan pada client akan menampilkan informasi secara online klasifikasi berdasarkan hot news, kategori berita, dan pencarian berita. Hal ini didukung dengan perkembangan akses internet yang semakin pesat, sehingga setiap orang di dunia dapat mengakses atau memberikan informasi secara real time (tanpa adanya jeda waktu). hasil dari implementasi dapat menerapkan metode string matching pada berita utama, sehingga dapat menarik minat pembaca bukan hanya dari tulisan yang baik dan mudah dipahami melainkan melalui gambar berdasarkan kategori berita, Kabupaten, serta pewarta berita. Diharapkan untuk kedepannya aplikasi ini diharapkan dapat dikembangkan dengan algoritme ataupun metode yang lain, sehingga dapat mengetahui secara pasti algoritme ataupun metode apa yang sesuai dalam aplikasi portal berita. K ata Kunci: String, Pencarian, Android, Berita, Website .
Resource allocation for uplink non-orthogonal multiple access in virtualized wireless networks

Wireless networks are strained by an exponential growth in mobile network traffic and new applications, such as the internet-of-things (IoT) paradigm and smart cities, are amplifying the problem as the density of networks increases. At the same time, network providers are faced with increasing infrastructure and service deployment costs which are not being offset by increased revenues. Multi-carrier non-orthogonal multiple access (NOMA) and virtualized wireless networks (VWN) are being positioned as promising techniques to jointly meet the needs of future network users and service providers by promoting the mutualization of network hardware and sharing of spectrum resources. With NOMA, sub-carriers can be shared by several users concurrently, with resulting reduction in spectrum requirements via increased spectral efficiency and re-use, increased power efficiency, and network density. Under VWN, hardware and radio resources are shared by several service providers with groups of users isolated from one another by minimum quality of service guarantees. The use of NOMA in VWNs has not been extensively studied and, due to the nature of wireless channels and user mobility, careful dynamic resource allocation is required to maintain system and user performance.The purpose of this work is to study NOMA-based VWNs and propose efficient resource allocation algorithms to leverage the available gains for users and service and infrastructure providers. Specifically, the use of NOMA for uplink transmissions is examined due to the many proposed use-cases, such as distributed sensor networks, for which uplink traffic far outweighs downlink and the greater capability of base stations in processing concurrent user signals. Initially, performance of NOMA VWN in single-input single-output channels with perfect processing of received signals is examined. With the goal of minimizing required transmit power for battery-dependent devices, an efficient iterative algorithm is presented. The proposed algorithm is then extended to multiple-input multiple-output systems and a sensitivity analysis to increased interference from imperfect processing of received signals is presented. Since many of the proposed use-cases support critical applications such as health and public safety monitoring, we then examine the use of NOMA VWN subject to reliability constraints. The resource allocation problem is mapped to its robust counterpart and the techniques of chance-constrained robust optimization are used to develop an efficient iterative algorithm which minimizes required transmit power subject to user rate and outage constraints. In each of these scenarios, simulation results are presented demonstrating the performance of the proposed algorithms and the improvement compared to traditional orthogonal multiple access is evaluated. %%%%Les reseaux sans fil subissent une croissance exponentielle du trafic des reseaux mobiles et les nouvelles applications, tels que le paradigme Internet-des-choses (IoT) et les villes intelligentes, intensifiant le probleme…
Considering Two Sides of One Review Using Stanford NLP Framework

Sentiment analysis is a type of natural language processing for tracking the mood of the public about a particular product or a topic and is useful in several ways. Polarity shift is the most classical task which aims at classifying the reviews either positive or negative. But in many cases, in addition to the positive and negative reviews, there still many neutral reviews exist. However, the performance sometimes limited due to the fundamental deficiencies in handling the polarity shift problem. We propose an Improvised Dual Sentiment Analysis (IDSA) model to address this problem for sentiment classification. We first propose a novel data expansion technique by creating sentiment-reversed review for each training and test review. We develop a corpus based method to construct a pseudo-antonym dictionary. It removes DSA’s dependency on an external antonym dictionary for review reversion. We conduct a range of experiments and the results demonstrates the effectiveness of DSA in addressing the polarity shift in sentiment classification.
Real-time Simulation and Rendering of Large-scale Crowd Motion

Crowd simulations are attracting increasing attention from both academia and the industry field and are implemented across a vast range of applications, from scientific demonstrations to video games and films. As such, the demand for greater realism in their aesthetics and the amount of agents involved is always growing. A successful crowd simulation must simulate large numbers of pedestrians’ behaviours as realistically as possible in real-time. The thesis looks at two important aspects of crowd simulation and real-time animation. First, this thesis introduces a new data structure called Extended Oriented Bounding Box (EOBB) and related methods for fast collision detection and obstacle avoidance in the simulation of crowd motion in virtual environments. The EOBB is extended to contain a region whose size is defined based on the instantaneous velocity vector, thus allowing a bounding volume representation of both geometry and motion. Such a representation is also found to be highly effective in motion planning using the location of vertices of bounding boxes in the immediate neighbourhood of the current crowd member. Second, we present a detailed analysis of the effectiveness of spatial subdivision data structures, specifically for large-scale crowd simulation. For large-scale crowd simulation, computational time for collision detection is huge, and many studies use spatial partitioning data structure to reduce the computational time, depicting their strengths and weaknesses, but few compare multiple methods in an effort to present the best solution. This thesis attempts to address this by implementing and comparing four popular spatial partitioning data structures with the EOBB.
An Introduction to Energy‐Based Blind Separating Algorithm for Speech Signals

We introduce the Energy‐Based Blind Separating (EBS) algorithm for extremely fast separation of mixed speech signals without loss of quality, which is performed in two stages: iterative‐form separation and closed‐form separation. This algorithm significantly improves the separation speed simply due to incorporating only some specific frequency bins into computations. Simulation results show that, on average, the proposed algorithm is 43 times faster than the independent component analysis (ICA) for speech signals, while preserving the separation quality. Also, it outperforms the fast independent component analysis (FastICA), the joint approximate diagonalization of eigenmatrices (JADE), and the second‐order blind identification (SOBI) algorithm in terms of separation quality.
Dynamic translation of runtime environments for heterogeneous computing

The recent move toward heterogeneous computer architectures calls for a global rethinking of current software and hardware paradigms. Researchers are exploring new parallel programming models, advanced compiler designs, and novel resource management techniques to exploit the features of many-core processor architectures. Graphics Processing Units (GPUs) have become the platform of choice in this area for accelerating a large range of data-parallel and task-parallel applications. The rapid adoption of GPU computing has been greatly aided by the introduction of high-level programming environments such as CUDA C and OpenCL. However, each vendor implements these programming models differently and we must analyze the internals in order to get a better understanding of the performance results. This dissertation presents the design of Caracal, a dynamic compiler that can translate between runtime environments used in heterogeneous computing. A major challenge of developing such a translation system is the inherent difference in both the underlying instruction set architecture, as well as the runtime system. One of the more challenging questions across different runtime environments is the handling of program control flow by the compiler and the hardware. Some implementations can support unstructured control flow based on branches and labels, while others are based on structured control flow relying solely on if-then and while constructs. Caracal can translate applications based on unstructured control flow so they can run on hardware that requires structured programs. In order to accomplish this, Caracal builds the control tree of the program and creates single-entry, single-exit regions called hammock graphs. We use Caracal to analyze the performance differences between NVIDIA's implementation of CUDA C and AMD's implementation of OpenCL. Our results show that the requirement for structured control flow can impact register pressure, and can degrade performance by as much as 2.5X. We also explore the differences between heterogeneous parallel processors architectures that will impact the design of a translator when attempting to optimize code. We evaluate this issue for two specific compiler optimizations that are highly sensitive to the underlying architecture. We use Caracal to evaluate 1) vectorization and 2) loop unrolling. Our translation system needs to capture rich semantics to be able to effectively translate code to different systems that will exploit these two optimization techniques differently. Our experiments show that by tuning these two optimizations in our translation system, we can reduce execution time by up to 90%.
UML Profile For EJB

ion (from Core) EJBRealizeRemote <<stereotype>> <<baseElement>> <<baseElement>> <<baseElement>> Attribute (f rom Core) EJBCmpField <<stereotype>> <<bas eElement>> EJBPrimaryKeyField <<stereotype>> Operation (from Core) EJBRoleNames [1. *] : String EJBTransAttribute : ( NotSupported, Supports, Required, RequiresNew, Mandatory, Never ) <<TaggedValues>> <<baseElement>> Dependency (from Core) Usage (from Core) Association (from Core) EJBReference <<stereotype>> EJBAccess <<stereotype>> <<baseElement>> <<baseElement>> Figure 5-5. Stereotypes and Tagged Values Defined in EJB Design Model Internal View Rational Software Corporation 58 5/25/2001 Public Draft UML Profile For EJB 5.5. 2 Implementation Model EJB-JAR <<stereotype>> EJBDescriptor <<stereotype>> EJBClientJAR <<stereotype>> Package (from Model Management) JavaArchiveFile (from jar) <<stereotype>> <<baseElement>> Component (from Core) <<baseElement>> Dependency (from Core)
Product reputation mining: bring informative review summaries to producers and consumers

Product reputation mining systems can help customers make their buying decision about a product of interest. In addition, it will be helpful to investigate the preferences of recently released products made by enterprises. Unlike the conventional manual survey, it will give us quick survey results on a low cost budget. In this article, we propose a novel product reputation mining approach based on three dimensional points of view that are word, sentence, and aspect? levels. Given a target product, the aspect? level method assigns the sentences of a review document to the desired aspects. The sentence? level method is a graph-based model for quantifying the importance of sentences. The word? level method computes both importance and sentiment orientation of words. Aggregating these scores, the proposed approach measures the reputation tendency and preferred intensity and selects top-k informative review documents about the product. To validate the proposed method, we experimented with review documents relevant with K5 in Kia motors. Our experimental results show that our method is more helpful than the existing lexicon? based approach in the empirical and statistical studies.
Self-Attention Architectures for Answer-Agnostic Neural Question Generation

Neural architectures based on self-attention, such as Transformers, recently attracted interest from the research community, and obtained significant improvements over the state of the art in several tasks. We explore how Transformers can be adapted to the task of Neural Question Generation without constraining the model to focus on a specific answer passage. We study the effect of several strategies to deal with out-of-vocabulary words such as copy mechanisms, placeholders, and contextual word embeddings. We report improvements obtained over the state-of-the-art on the SQuAD dataset according to automated metrics (BLEU, ROUGE), as well as qualitative human assessments of the system outputs.
jsdare: a new approach to learning programming

We present an online framework for programming education, called jsdare. This framework can be used to create programming courses in, especially for secondary education. In this framework we implement a number of existing interface ideas in a coherent way, including a modern version of the LOGO turtle and Karel the Robot; debugging by quickly stepping forward and backward; a zero-response time compiler using a subset of Javascript; previewing, highlighting and manipulation of statements and expressions; a basic visualisation of variables in different scopes; an integrated reference manual; programming exercises called ‘dares’ in which the objective is to make a short program, similarly to Code Golf; support for events and HTML canvas in order to make games, with support for pausing time, rewinding time, debugging a specific event, editing the program while paused, and abstracting functions over time. Interface and implementation details are rooted in thorough literature research. The programming course has been evaluated in small-scale field trial, the results of which are mostly positive.
Unequal Energy Allocation with Turbo Codes for Nonuniform Sources

Non-systematic channel codes can have a significant advantage over systematic codes when utilizing redundancy left in the data for channel decoding. However, results previously attained show that even with such codes there is a performance gap to the theoretical limits. We study techniques that allow reducing this gap by using unequal energy allocation for both systematic and non-systematic turbo codes. For both types of codes, there are regions of source non-uniformity, for which they outperform codes with equal energy allocation. Systematic codes with unequal allocation perform well at extreme non-uniformities. The non-systematic codes perform well at moderate non-uniformities and still outperform their equal energy allocation counterparts at extreme non-uniformities. A theoretical study of the mutual information attainable by the different classes of codes for different source non-uniformities is presented, and supports the advantage of non-systematic codes with unequal allocation over the other classes of codes. While it also points out that the non-systematic codes should be better for extreme source non-uniformities, simulation results show that the current designs of the systematic codes with unequal energy allocation are still better than those of the non-systematic codes in this region.
Extraction of Flow Phenomena in Turbomachinery Using Visual Data Mining

ターボ機械の内部流れ場では,極 めて複雑な渦流れ現 象が多々発生する. 例 えば,タ ーボ機械の代表構成要素 である動翼列(羽 根車)の 流れ場では,翼 端漏れ渦,馬 蹄形渦,流 路渦およびコーナーは く離渦などの多様な大 規模渦構造が形成 され,そ れ らは流れ場の三次元性 を支 配するとともに,周 囲の壁面境界層と干渉 して複雑 な流 れ形態 を呈する. こ れ らの渦構造はその形成過程 自体に 境界層のはく離を伴 うばか りでな く,形 成後に周囲の壁 面境界層 と干渉する際に,新 たなは く離を引 き起こすこ ともある. こ のようなはく離を伴 う渦流れ場では,渦 構 造の自励振動等が発生 して,流 れ場に大 きな非定常性が 発現することもある. 上述のようなターボ機械の複雑な流れ場 を数値シミュ レーションにより解析する場合,流 線や速度ベク トルの 表示お よび圧力や渦度分布の表示など,物 理量を直接可 視化する従来の後処理技術では,流 動現象を的確 に解析 することは容易でない. 何 らかの方法で流れ場の特徴を 予め抽出しておき,そ の特徴を中心にして流れ場 を表示 する知的可視化(ビ ジュアルデータマイニ ング)技 術が 必要 となる. こ の流れ場の特徴 として,渦 構造 と限界流 線に着 目す ることが肝要である. 流 れ場の特異性 として の渦中心 と限界流線の特異点 ・包絡線を同定 し,流 れ構 造の概略を把握 した上で,流 動現象を詳細 に解析するこ とが,タ ーボ機械における複雑な流動現象の解明にとっ て不可欠である. 以上の観点より,数 値シ ミュレーション結果か ら流体 力学的に意味のある情報 を抽出 ・表示す る知的可視化 (ビジュアルデータマイニング)技 術 と して,こ こでは 渦構造の同定法および限界流線の トポロジー解析を概説 するとともに,そ れらを圧縮機動翼列流れに適用 して翼 端漏れ渦の崩壊現象や小スケール旋回失速の非定常三次 元流れ挙動 を解明 した事例を紹介する. こ の事例をとお して,タ ーボ機械の流動解析には,特 異点理論に基づい た知的可視化技術が最 も有用であることを示す. 2. 渦 構造の同定法
An online resource allocation algorithm to minimize system interference for inband underlay D2D communications

This paper addresses the research question of total system interference minimization while maintaining a target system sum rate gain in an inband underlay device‐to‐device (D2D) communication. To the best of our knowledge, most of the state of the art research works exploit offline resource allocation algorithms to address the research problem. However, in Long‐Term Evolution (LTE) and beyond systems (4G, 5G, or 5G+), offline resource allocation algorithms do not comply with the fast scheduling requirements because of the high data rate demand. In this paper, we propose a bi‐phase online resource allocation algorithm to minimize the total system interference for inband underlay D2D communication. Our proposed algorithm assumes D2D pairs as a set of variable elements whereas takes the cellular user equipment (UEs) as a set of constant elements. The novelty of our proposed online resource allocation algorithm is that it incurs a minimum number of changes in radio resource assignment between two successive allocations among the cellular UEs and the D2D pairs. Graphical representation of the simulation results suggests that our proposed algorithm outperforms the existing offline algorithm considering number of changes in successive allocation for a certain percentage of sum rate gain maintaining the total system interference and total system sum rate very similar.
WATERMARKING SCHEMES FOR COPY PROTECTION : A SURVEY

DIGITAL WATERMARKING IS THE PROCESS OF EMBEDDING INFORMATION INTO A DIGITAL SIGNAL, I.E. AUDIO , PICTURES , VIDEO , ETC . EMBEDDED MARKS IN THE MESSAGE ARE GENERALLY IMPERCEPTIBLE BUT CAN BE DETECTED OR EXTRACTED. THE EMBEDDING TAKES PLACE BY MANIPULATING THE CONTENT OF THE DIGITAL DATA , WHICH MEANS THE INFORMATION IS NOT EMBEDDED IN THE FRAME AROUND THE DATA . IF THE SIGNAL IS COPIED , THEN THE EMBEDDED INFORMATION IS ALSO IN THE COPY . BY IMPERCEPTIBLY HIDING INFORMATION INTO THE VIDEO CONTENT IT WILL BE POSSIBLE TO PREVENT COPYING OR PLAYBACK OF SUCH CONTENT . SO , WATERMARKING IS AN EMERGING TECHNOLOGY THAT IS CLAIMED TO HAVE AN IMPORTANT APPLICATION IN COPY PROTECTION . A VARIETY OF WATERMARKING TECHNIQUES HAVE BEEN PROPOSED BY RESEARCHERS FOR THE COPY -PROTECTION . THIS PAPER PRESENTS AN EXTENSIVE REVIEW OF THE PREVAILING LITERATURE IN WATERMARKING FOR COPY PROTECTION .
A deep learning-based method for vehicle licenseplate recognition in natural scene

Abstract Vehicle license platerecognition in natural scene is an important research topic in computer vision. The license plate recognition approach in the specific scene has become a relatively mature technology. However, license plate recognition in the natural scene is still a challenge since the image parameters are highly affected by the complicated environment. For the purpose of improving the performance of license plate recognition in natural scene, we proposed a solution to recognize real-world Chinese license plate photographs using the DCNN-RNN model. With the implementation of DCNN, the license plate is located and the features of the license plate are extracted after the correction process. Finally, an RNN model is performed to decode the deep features to characters without character segmentation. Our state-of-the-art system results in the accuracy and recall of 92.32 and 91.89% on the car accident scene dataset collected in the natural scene, and 92.88 and 92.09% on Caltech Cars 1999 dataset.