Miracle-dz/UniFAR-FTUs huggingface dataset:
iTrustPage: Pretty Good Phishing Protection

In spite of the myriad of solutions proposed by industry and the research community to address the phishing problem, the number of phishing attacks continues to grow at a remarkable rate. This alarming trend suggests that the research community must develop new approaches to solutions that prevent phishing attacks. This paper takes a modest ste p in this direction. We present iTrustPage, an anti-phishing tool that relies on user input and external repositories of information to prev ent users from filling out phishing Web forms. When encountering a suspicious Web form, iTrustPage asks the user to describe the site they intend to access, as if they are entering search terms to a search engine. If the form is found in the top search results, the form is validated, and the user ca n proceed to fill it out. Otherwise, the user is presented with v isual previews of the top search results: these are well-know n sites matching the user supplied search terms. Users can either choose one of these trustworthy sites or refine their search terms. We present a three-pronged evaluation of iTrustPage, investigating its performance, effectiveness, and ease-ofuse. For this, we use previously collected traces of Web traffic, data collected from our real deployment of iTrustPage, and data collected from a controlled usability study of our tool . Our evaluation shows that iTrustPage is effective and easy t o use.
An efficient method for crowd event recognition based on motion patterns

An automated visual monitoring process expands from low level analysis of object detection and tracking to the interpretation of their behaviors. Analyzing human crowd is an emerging trend in intelligent video surveillance for the purpose of detecting abnormalities. Tracking every human being in a crowd and analyzing their behavior is a challenging task due to occlusions. Hence, the crowd can be handled as a group entity instead of tracking the individual in the crowd. The behavior of the crowd can be distinguished with motion patterns due to prominent spatio-temporal characteristics. The proposed system involves a systematic approach to recognize the global events in human crowd through observing motion patterns such as flow, speed and direction. Initially as a preprocessing step, background subtraction is performed to extract the foreground blobs and optical flow is estimated to obtain the velocity and direction of motion. The human crowds are then clustered based on similar direction and proximity using Adjacency Matrix based Clustering (AMC). After clustering, the centroid and orientation of the cluster are extracted inorder to represent the behavior of crowd. Finally the multiclass Support Vector Machine (SVM) is trained to correctly recognize the behavior of crowd.
The impact of high temperatures on Vitis vinifera cv. Semillon grapevine performance and berry ripening

The heat event that occurred in many parts of Australia in 2009 was the worst on record for the past decade, with air temperatures exceeding 40°C for 14 days. Our aim was to assess the impacts of this heat event on vine performance, including ripening, yield, and gas exchange of Vitis vinifera cv. Semillon grown in a Riverina vineyard. To assess the affect of high temperatures on Semillon grapevines, the vines were covered with a protective layer to reduce radiant heating and were compared with vines exposed to ambient conditions. The heat event had major effects on ripening; reducing the rate of ripening by 50% and delaying harvest ripeness and causing a high incidence of berry shrivel and sunburn. Yield was not affected. Photosynthesis was reduced 35% by the heat event while transpiration increased nearly threefold and was accounted for by increased stomatal conductance. The conclusion of this study was that heat events delayed ripening in Semillon berries and caused a significant reduction in berry quality. Strategies to minimize the radiant load during heat events are required and this study has confirmed a protective layer can reduce canopy temperatures and enhance berry quality.
How the live web feels about events

Microblogging platforms, such as Twitter, Tumblr etc., have been established as key components in the contemporary Web ecosystem. Users constantly post snippets of information regarding their actions, interests or perception of their surroundings, which is why they have been attributed the term Live Web. Nevertheless, research on such platforms has been quite limited when it comes to identifying events, but is rapidly gaining ground. Event identification is a key step to news reporting, proactive or reactive crisis management at multiple scales, efficient resource allocation, etc. In this paper, we focus on the problem of automatically identifying events as they occur, in such a user-driven, fast paced and voluminous setting. We propose a novel and natural way to address the issue using notions from emotional theories, combined with spatiotemporal information and employ online event detection mechanisms to solve it at large scale in a distributed fashion. We present a modular framework that incorporates all of our key ideas and experimentally validate its superiority, in terms of both efficiency and effectiveness, over the state-of-the-art using real life data from the Twitter stream. We also present empirical evidence on the importance of spatiotemporal information in event detection for this setting.
Scanstud: A Methodology for Systematic, Fine-Grained Evaluation of Static Analysis Tools

Static analysis of source code is considered to be a powerful tool for detecting potential security vulnerabilities. However, only limited information regarding the current quality of static analysis tools exist. A public assessment of the capabilities of the competing approaches and products is not available. Also, neither a common benchmark nor a standard evaluation procedure has yet been defined. In this paper, we propose a general methodology for systematically evaluating static analysis tools. We document the design of an automatic execution and evaluation framework to support iterative test case design and reliable result analysis. Furthermore, we propose a methodology for creating test cases which can assess the specific capabilities of static analysis tools on a very fine level of detail. We conclude the paper with a brief discussion of our experiences which we collected through a practical evaluation study of six commercial static analysis products.
Link-State-Estimation-Based Transmission Power Control in Wireless Body Area Networks

This paper presents a novel transmission power control protocol to extend the lifetime of sensor nodes and to increase the link reliability in wireless body area networks (WBANs). We first experimentally investigate the properties of the link states using the received signal strength indicator (RSSI). We then propose a practical transmission power control protocol based on both short- and long-term link-state estimations. Both the short- and long-term link-state estimations enable the transceiver to adapt the transmission power level and target the RSSI threshold range, respectively, to simultaneously satisfy the requirements of energy efficiency and link reliability. Finally, the performance of the proposed protocol is experimentally evaluated in two experimental scenarios-body posture change and dynamic body motion-and compared with the typical WBAN transmission power control protocols, a real-time reactive scheme, and a dynamic postural position inference mechanism. From the experimental results, it is found that the proposed protocol increases the lifetime of the sensor nodes by a maximum of 9.86% and enhances the link reliability by reducing the packet loss by a maximum of 3.02%.
A survey of location inference techniques on Twitter

The increasing popularity of the social networking service, Twitter, has made it more involved in day-to-day communications, strengthening social relationships and information dissemination. Conversations on Twitter are now being explored as indicators within early warning systems to alert of imminent natural disasters such as earthquakes and aid prompt emergency responses to crime. Producers are privileged to have limitless access to market perception from consumer comments on social media and microblogs. Targeted advertising can be made more effective based on user profile information such as demography, interests and location. While these applications have proven beneficial, the ability to effectively infer the location of Twitter users has even more immense value. However, accurately identifying where a message originated from or an author’s location remains a challenge, thus essentially driving research in that regard. In this paper, we survey a range of techniques applied to infer the location of Twitter users from inception to state of the art. We find significant improvements over time in the granularity levels and better accuracy with results driven by refinements to algorithms and inclusion of more spatial features.
Optimization of H.264 encoder based on SSE2

In this paper, instruction level optimization by exploiting SSE2 instructions is proposed to speed up the time-critical modules in H.264 encoder. SSE2 instruction set to execute a large number of small-size native data type operations in parallel to improve the real-time multimedia data processing capability. The contributions of the paper are manifold: Firstly, the paper shows SSE2 instruction set. Secondly, we describe the complexity analysis and theory of H.264 key modules such as integer DCT, invert integer DCT and the sum of absolute transformed difference (SATD). Thirdly, the proposed approach is applied to H.264 video encoding and the experimental results show up to 13% speedup without degrading video quality, compared with results of the original encoder in H.264.
A measure of phonetic similarity to quantify pronunciation variation by using ASR technology

It attracts researchers’ interest how to deﬁne a quantitative measure of phonetic similarity between IPA transcripts of the same sentence read by two speakers. This problem can be divided into how to align two transcripts and how to quantify alignment gap. In this paper, we introduce a method of similarity calculation using phone-based or phoneme-based acoustic models trained with the algorithm used to develop Automatic Speech Recognition (ASR) systems. Use of acoustic models will introduce an issue of speaker dependency because speech spectrums always convey the information of the training speakers’ age and gender, which is totally irrelevant to phonetic similarity calculation. We examine how independent our method is of training speakers and how close the calculated similarity is to the similarity subjectively rated through a listening test. We also compare our method to recent works and show our method can give higher correlation by 4 points to human-rated similarity.
Togetherness: An algorithmic approach to network integration

Network integration refers to a process of building links between two networks so that they dissolve into a single unified network. Togetherness measures the proximity of these two networks as they integrate; this notion is fundamental to social networks as it is relevant to important concepts such as trust, coherence and solidarity. In this paper, we study the algorithmic nature of network integration and formally introduce three notions of togetherness. We analyze the corresponding computational problems of network integration: Given two networks and a desired level of togetherness, build links between members of these networks so that the overall network meets the togetherness criterion. We analyze optimal solutions to this problem, describe several heuristics and compare their performance through experimental analysis.
HUBUNGAN ANTARA SIKAP KEMANDIRIAN BELAJAR DAN PRESTASI BELAJAR SISWA KELAS X PADA PEMBELAJARAN FISIKA BERBASIS PORTOFOLIO

Penelitian ini dilatarbelakangi dari hasil pra-penelitian yang menunjukan bahwa siswa belum memiliki sikap kemandirian belajar yang baik. Kurang baiknya sikap kemandirian belajar yang dimiliki siswa diyakini akan berpengaruh pada kurang baiknya pretasi belajar yang diraihnya. Sikap kemandirian belajar akan membentuk sikap inisistif, tanggung jawab, kedisiplinan, dan kepercayaan diri dalam belajar, serta kemampuan mengevaluasi hasil belajar. Sikap-sikap yang terdapat dalam kemandirian belajar merupakan faktor-faktor yang mempengaruhi prestasi belajar yang diperoleh siswa. Penelitian ini bertujuan untuk mengetahui hubungan antara sikap kemandirian belajar yang dimiliki siswa dengan prestasi belajar yang diraihnya. Jenis penelitian yang digunakan adalah penelitian korelasi yang mendeteksi sejauh mana variansi sikap kemandirian belajar berkaitan dengan dengan variansi prestasi belajar. Penelitian ini menggunakan skala sikap untuk mengukur sikap kemandirian belajar yang dimiliki siswa dan soal objektif berbentuk pilihan ganda untuk mengukur prestasi belajar siswa. Hasil penelitian menunjukan terdapat hubungan positif (searah) yang signifikan (berarti) antara sikap kemandirian belajar dan prestasi belajar. Ini berarti, semakin baik sikap kemandirian belajar yang dimiliki siswa, maka akan semakin baik pula prestasi belajar yang diraih siswa. The study is motivated from the pre-study that shows that students do not have a good attitude to learn independence. Less favorable attitudes students have learned independence believed to affect less favorable interpretation of learning achieved. The attitude of self study will establish a settlement attitude, responsibility, discipline, and confidence in learning, and the ability to evaluate learning outcomes. Attitudes contained in the independent learning are all factors that affect student achievement obtained. This study aimed to determine the relationship between independent learning attitude the student has achieved the learning achievements. Type of research is a correlation study to detect the extent of the variance of the attitude of learning independence in relation to academic achievement variance. This study used an attitude scale to measure attitudes students have learned independence and objective multiple-choice questions to measure student achievement. The results showed that there is a positive relationship (unidirectional) significantly (mean) between the attitude of self learning and academic achievement. This means, the better the attitude of the student learning independence, it will be better the learning achievement of students achieved. The attitude of independence study accounted for 40.96% of the students achieved the learning achievement.
Creating and Evaluating Goal Ordering Structures for Testing Harbour Patrol and Interception Policies

In this article, we discuss a method for testing policies that guide groups of agents in simulations for interactions with other agents and the environment that reveal weaknesses of these policies. Our method is based on learning interaction sequences using particle swarm systems and has as one crucial component so-called goal ordering structures that are used to guide the learning towards weakness-revealing interactions. Our discussion centers around the different ways a new measuring idea can be integrated into such an ordering structure using the example of testing patrol and interception policies for harbours. Our experimental evaluation reveals that the position of placement of a new measure in an existing ordering structure can greatly influence the testing results, positively and negatively, but mostly mirrors the intuition associated with the placement.
Intuitive gesture based user identification system

We present an intuitive and very easy to use implicit gesture based identification system that is especially suited for security-wise non-critical applications, such as the user login in the multimedia services. The term “implicit gesture” in our work refers to a natural physical hand manipulation performed by the user who takes hold of the control device and simply picks it up from its neutral motionless position - a “pick-up” gesture. For reference with other related systems, explicit and well defined personal name identification gestures were used as well. User evaluation study results show that 100% recognition accuracy was achieved when using explicit identification signature gestures and over 91% recognition accuracy was achieved when using the implicit “pick-up” gesture. Performance of the proposed system is comparable to results of other respectable related works when using explicit identification gestures, while also showing that implicit gesture based user identification is possible and viable.
A Variable Step-Size Diffusion LMS Algorithm for Distributed Estimation

We propose a new variable step-size diffusion least mean square algorithm for distributed estimation that adaptively adjusts the step-size in every iteration. For a network application, the proposed method determines a suboptimal step-size at each node to minimize the mean square deviation for the intermediate estimate. The algorithm thus adapts the different node environments and profiles across the networks, and requires relatively less user interaction than existing algorithms. In experiments, the algorithm achieves both fast convergence speed and low misadjustment by remarkable improvement in an adaptation stage. We analyze the mean square performance of the proposed algorithm. Also, the proposed algorithm works well even in non-stationary environments.
Nonideal Rayleigh–Taylor mixing

Rayleigh–Taylor mixing is a classical hydrodynamic instability that occurs when a light fluid pushes against a heavy fluid. The two main sources of nonideal behavior in Rayleigh–Taylor (RT) mixing are regularizations (physical and numerical), which produce deviations from a pure Euler equation, scale invariant formulation, and nonideal (i.e., experimental) initial conditions. The Kolmogorov theory of turbulence predicts stirring at all length scales for the Euler fluid equations without regularization. We interpret mathematical theories of existence and nonuniqueness in this context, and we provide numerical evidence for dependence of the RT mixing rate on nonideal regularizations; in other words, indeterminacy when modeled by Euler equations. Operationally, indeterminacy shows up as nonunique solutions for RT mixing, parametrized by Schmidt and Prandtl numbers, in the large Reynolds number (Euler equation) limit. Verification and validation evidence is presented for the large eddy simulation algorithm used here. Mesh convergence depends on breaking the nonuniqueness with explicit use of the laminar Schmidt and Prandtl numbers and their turbulent counterparts, defined in terms of subgrid scale models. The dependence of the mixing rate on the Schmidt and Prandtl numbers and other physical parameters will be illustrated. We demonstrate numerically the influence of initial conditions on the mixing rate. Both the dominant short wavelength initial conditions and long wavelength perturbations are observed to play a role. By examination of two classes of experiments, we observe the absence of a single universal explanation, with long and short wavelength initial conditions, and the various physical and numerical regularizations contributing in different proportions in these two different contexts.
Identifying and utilizing contextual data in hybrid recommender systems

Context-aware recommender systems are becoming a popular topic, still, there are many untouched aspects. In this paper, research involving context identification and the concepts related to hybrid and context-aware systems is presented. A conceptual architecture for a context-aware recommender system for movies and TV shows is furthermore introduced. The system consists of a number of processes for context identification and recommendation. Key contextual features are identified and used for the creation of several sets of recommendations, based on the predicted context. The main focus of the research presented here is the identification of context, which in turn is used for recommendation. The results will be evaluated and incorporated into the recommendation engine of movie and TV recommendation website Moviepilot.
Design of Asymmetric Multi-Element Directional Couplers with Tandem Section as the First Element

An analysis is presented of a class of asymmetric multi-element directional couplers (ADC) for any number of elements and with tandem section (TS) as the first of its. A table of element values is given for three-and four-element 3-dB couplers for various ripple levels. It is shown that described approach overcomes the tight coupling problem associated with the method proposed by R. Levy, but that it introduces a bandwidth contraction penalty.
Tumor-Targeting Salmonella typhimurium A1-R in Combination with Trastuzumab Eradicates HER-2-Positive Cervical Cancer Cells in Patient-Derived Mouse Models

We have previously developed mouse models of HER-2-positive cervical cancer. Tumors in nude mice had histological structures similar to the original tumor and were stained by anti-HER-2 antibody in the same pattern as the patient’s cancer. We have also previously developed tumor-targeting Salmonella typhimurium A1-R and have demonstrated its efficacy against patient-derived tumor mouse models, both alone and in combination. In the current study, we determined the efficacy of S. typhimurium A1-R in combination with trastuzumab on a patient-cancer nude-mouse model of HER-2 positive cervical cancer. Mice were randomized to 5 groups and treated as follows: (1) no treatment; (2) carboplatinum (30 mg/kg, ip, weekly, 5 weeks); (3) trastuzumab (20 mg/kg, ip, weekly, 5 weeks); (4) S. typhimurium A1-R (5 × 107 CFU/body, ip, weekly, 5 weeks); (5) S. typhimurium A1-R (5 × 107 CFU/body, ip, weekly, 5 weeks) + trastuzumab (20 mg/kg, ip, weekly, 5 weeks). All regimens had significant efficacy compared to the untreated mice. The relative tumor volume of S. typhimurium A1-R + trastuzumab-treated mice was smaller compared to trastuzumab alone (p = 0.007) and S. typhimurium A1-R alone (p = 0.039). No significant body weight loss was found compared to the no treatment group except for carboplatinum-treated mice (p = 0.021). Upon histological examination, viable tumor cells were not detected, and replaced by stromal cells in the tumors treated with S. typhimurium A1-R + trastuzumab. The results of the present study suggest that S. typhimurium A1-R and trastuzumab in combination are highly effective against HER-2-expressing cervical cancer.
VIS Standards Deployment and Integration: A Study of Antecedents and Benefits

Drawing on institutional theory and the literature on inter-organizational systems (IOS), this paper develops a research model for assessing the use of vertical information systems (VIS) standards. Extending prior research on IOS use, we differentiated between two distinct dimensions characterizing organizations’ use of VIS standards: the extent to which organizations adopt VIS standards across a wide range of business processes, and the extent of systems and business process integration. We examine how VIS standards deployment and integration differentially influence operational and strategic benefits that standards users obtain. We also examine how various institutional pressures (coercive, mimetic, and normative) influence the extent of deployment and integration of the VIS standards in different ways. The hypotheses are tested using survey data collected from organizations in Asia who have implemented RosettaNet standards.
The Synthesis and Molecular Structure of 1-(3,4-Dihydroxyphenethyl)-3-hydroxy-2-methylpyridin-4(1H)-one Hydrochloride Methanol Solvate

A 3-hydro-4-pyridinone compound derived from maltol and dopamine has been prepared using a microwave reactor. The molecular structure of the protonated product was confirmed by single crystal X-ray diffraction. Crystals were obtained from a saturated solution of methanol and belong to the triclinic space group P-1 with unit cell parameters a = 8.3801(11) A; b = 9.2583(12) A; c = 11.5671(15) A; α = 73.566(2)°; β = 84.514(2)°; γ = 66.578(2)°. The asymmetric unit contains two molecules.