Miracle-dz/UniFAR-FTUs huggingface dataset:
A Collaborative Session-based Recommendation Approach with Parallel Memory Modules

Session-based recommendation is the task of predicting the next item to recommend when the only available information consists of anonymous behavior sequences. Previous methods for session-based recommendation focus mostly on the current session, ignoring collaborative information in so-called neighborhood sessions, sessions that have been generated previously by other users and reflect similar user intents as the current session. We hypothesize that the collaborative information contained in such neighborhood sessions may help to improve recommendation performance for the current session. We propose a Collaborative Session-based Recommendation Machine (CSRM), a novel hybrid framework to apply collaborative neighborhood information to session-based recommendations. CSRM consists of two parallel modules: an Inner Memory Encoder (IME) and an Outer Memory Encoder (OME). The IME models a user's own information in the current session with the help of Recurrent Neural Networks (RNNs) and an attention mechanism. The OME exploits collaborative information to better predict the intent of current sessions by investigating neighborhood sessions. Then, a fusion gating mechanism is used to selectively combine information from the IME and OME so as to obtain the final representation of the current session. Finally, CSRM obtains a recommendation score for each candidate item by computing a bilinear match with the final representation. Experimental results on three public datasets demonstrate the effectiveness of CSRM compared to state-of-the-art session-based recommender systems. Our analysis of CSRM's recommendation process shows when and how collaborative neighborhood information and the fusion gating mechanism positively impact the performance of session-based recommendations.
Multiple Record Extraction from HTML Page Based on Hierarchical Pattern

To tackle the problem of knowledge acquisition in the HTML page information extraction, a new approach based on hierarchical pattern for HTML page information extraction is put forward. The knowledge used in this method (called HPIE) is composed of a few kinds of pattern descriptions, from abstract to concrete for information recognition patterns. Besides the HPIE combines the knowledge about the different objects' relation with information extraction process and its results to help modify its knowledge of information extraction, in order to extract the desired multiple record information from different HTML pages with similar contents successfully. The information extraction experiment made on the American university faculty's paper page shows that the HPIE has a power and adaptive ability to extract the desired information from HTML page having different display format.
Cloning of virulent rabies virus glycoprotein gene in replicase based vector

Rabies is a potentially fatal viral infection that attacks central nervous system. Dogs are reservoir of rabies virus and dog-to-dog transmission occurs very rapidly. Presently exposure to rabid dogs is the cause of >99%of human rabies deaths world-wide (Smith and Siedel, 1993). Rabies is caused by a virus, which is a negative stranded RNA virus of Lyssavirus genus in the family Rhabdoviridae. Although conventional vaccines against rabies are available, these are not ideal for mass vaccination in developing countries like India. Out of five proteins encoded by rabies genome, glycoprotein is the only protein capable of inducing and reacting to virus neutralizing antibodies (VNA) and for conferring protective immunity against lethal challenge with rabies virus. This has laid down the possibility of developing a subunit vaccine against rabies. DNA vaccines against rabies have been reported and found to be successful as pre-exposure and postexposure vaccination in mice (Perrin et al., 2000; Lodmell and Gwalt, 2001; Rai et al. 2002; Lodmell et al., 2002), dogs (Forg, et al., 1998), cats (Akbari et al., 1999) and non-human primates (Krieg, 2000).
Explaining Bond Return Predictability in an Estimated New Keynesian Model

This paper estimates a New Keynesian model that explains key macro series, the ten-year nominal yield curve, and the ability of the spread between long- and short-term bond yields to predict future excess bond returns. The model also generates an upward sloping nominal and real yield curve, produces a positive inflation risk premium, and recovers the prediction by the expectations hypothesis of no return predictability when historical bond yields are risk-adjusted using term premia from the proposed model. Key to obtaining these results is a new specification of stochastic volatility that allows high current inflation to generate high future uncertainty.
CHANGES IN INDIVIDUAL RESILIENCE AFFECTED BY GROUP CHARACTERISTICS : FOCUSED ON THE HOMOGENEITY AND HETEROGENEITY OF GROUPS

The effects of group characteristics (homogeneity and heterogeneity), on changes in individual resilience through group activities were examined. Participants were students enrolled in Japanese universities. The survey was conducted twice, in early April (pre-program) and mid-July (post-program). Resilience was measured by employing the Bidimensional Resilience Scale (Hirano, 2010). Results of the analysis revealed the scores of all the subscales with the exception of “vitality” significantly increased post-program compared to pre-program. Subsequently, participants were classified into two types of teams depending on the standard deviation (SD) of the scores of innate and acquired resilience factors pre-program; homogeneity and heterogeneity teams with a low and high SD, respectively. Intraclass correlation coefficients between teams and individuals at each point of time were calculated. Consequently, the hierarchy between teams and individuals was confirmed postprogram. “understanding others” in homogeneity groups were extracted based on scores of innate resilience factors and post-program, “self-understanding” in heterogeneity groups, were also extracted based on the scores of innate resilience factors. The results suggest the effectiveness of practice and intervention programs based on different effects of group characteristics, namely, homogeneity and heterogeneity, on individual resilience.
Multi-Variate Time Series Similarity Measures and Their Robustness Against Temporal Asynchrony

The amount of time series data generated is increasing due to the integration of sensor technologies with everyday applications, such as gesture recognition, energyoptimization, health care, video surveillance. The use of multiple sensors simultaneously capturing different aspects of the real world attributes has also led to an increase in dimensionality from uni-variate to multi-variate time series. This has facilitated richer data representation but also has necessitated algorithms determining similarity between two multi-variate time series for search and analysis. Various algorithms have been extended from uni-variate to multi-variate case, such as multi-variate versions of Euclidean distance, edit distance, dynamic time warping. However, it has not been studied how these algorithms account for asynchrony in time series. Human gestures, for example, exhibit asynchrony in their patterns as different subjects perform the same gesture with varying movements in their patterns at different speeds. In this thesis, we propose several algorithms (some of which also leverage metadata describing the relationships among the variates). In particular, we present several techniques that leverage the contextual relationships among the variates when measuring multi-variate time series similarities. Based on the way correlation is leveraged, various weighing mechanisms have been proposed that determine the importance of a dimension for discriminating between the time series as giving the same weight to each dimension can led to misclassification. We next study the robustness of the considered techniques against different temporal asynchronies, including shifts and stretching. Exhaustive experiments were carried on datasets with multiple types and amounts of temporal asynchronies. It has been observed that accuracy of algorithms that rely on data to discover variate relationships can be low under the presence of temporal
Extending Microsoft Project for Real-World Job-Shop Scheduling

Although production scheduling has attracted the research interest of production economics communities for decades, there still remains a gap between academic research and real-world problems. Genetic Algorithms (GA) constitute a technique that has already been applied to a variety of combinatorial problems. We will explain the application of a GA approach to bridge this gap for job-shop scheduling problems, for example to minimize makespan of a production program or to increase the due-date reliability of jobs. The presented approach focuses on integrating a scheduling algorithm, based on GA, into a commercial software product, namely Microsoft Project 2003. We extended Microsoft Project in a range of aspects: A new graphical user interface is introduced to support users by a guided wizard describing the problem for which an optimal schedule is sought. The GA was developed to search for the solution with the maximum results for a given set of production logistical objectives. The developed GA algorithm and operators are tested on real-world data from a oneof-a-kind manufacturing department of a major company. It includes different aggregation operators for combining objectives. Furthermore, the efficiency of the algorithm was compared to benchmark tests available in literature.
Cross-National Research Methodology and Practice

Introduction Linda Hantrais and Steen Mangen. Methodology: Contextualization in Cross-National Comparative Research Linda Hantrais. Qualitative Research Methods in Cross-National Settings Steen Mangen. In Pursuit of Quality: Issues for Cross-National Survey Research Janet Harkness. Practice: Concepts, Context and Discourse in a Comparative Case Study Emma Carmel. Combining Quantitative and Qualitative Research Methods in the Study of International Migration Ann Singleton. Cross-National Qualitative Research: Accommodating Ideals and Reality Monika Zulauf. Context, Culture and Values in Migration Research on Children within the European Union Louise Ackers
Desarrollo de competencias a través de proyectos de investigación

El objetivo de este estudio se centra en determinar el efecto de una estrategia de aprendizaje basada en proyectos de investigacion sobre el desarrollo de competencias declarativas, procedimentales y actitudinales en los estudiantes de Biologia de 9no grado de Educacion Basica. Se fundamenta el estudio en las teorias de Pozo y Gomez (2001), Diaz y Hernandez (2002) y Tobon (2006). El diseno de investigacion fue cuasiexperimental, con pre-observacion y post-observacion a dos grupos (control y experimental). La muestra fue censal, conformada por 2 secciones de estudiantes. Se utilizo una guia de preguntas que sirvio de pre-observacion para ubicar el comportamiento de entrada de los estudiantes y post-observacion que midio la conducta de salida. Se diseno y aplico una estrategia basada en los proyectos de investigacion para fortalecer las competencias declarativas, procedimentales y actitudinales en el aprendizaje de las ciencias. Como resultado se comprobo la efectividad de la estrategia basada en proyectos de investigacion sobre el desarrollo de las competencias en los estudiantes, ya que el grupo experimental logro mejores resultados posteriores a su aplicacion. En conclusion, la aplicacion de esta estrategia es efectiva al reflejarse diferencias marcadas de estas competencias entre los grupo experimental y control, en consecuencia, se fortalecen las competencias partir de los proyectos de investigacion, con lo cual se aproxima al perfil deseado en el estudiante
Medium access control layer management for saving energy in wireless sensor networks routing algorithms

Abstract Wireless sensor networks (WSNs) consist of small nodes that are capable of sensing, computing, and communication. One of the greatest challenges in WSNs is the limitation of energy resources in nodes. This limitation applies to all of the protocols and algorithms that are used in these networks. Routing protocols in these networks should be designed considering this limitation. Many papers have been published examining low energy consumption networks. One of the techniques that has been used in this context is cross-layering. In this technique, to reduce the energy consumption, layers are not independent but they are related to each other and exchange information with each other. In this paper, a cross-layer design is presented to reduce the energy consumption in WSNs. In this design, the communication between the network layer and medium access layer has been established to help the control of efforts to access the line to reduce the number of failed attempts. In order to evaluate our proposed design, we used the NS2 software for simulation. Then, we compared our method with a cross-layer design based on an Ad-hoc On-demand Distance Vector routing algorithm. Simulation results show that our proposed idea reduces energy consumption and it also improves the packet delivery ratio and decreases the end-to-end delay in WSNs.
Fingerprint image segmentation algorithm based on gray balance

This paper in view of the characteristic of fingerprint images by MBF200 chip fingerprint gathering,proposes a new method of fingerprint image segmentation.The method,which can segment fingerprint images,is simple,rapid and effective,and meets the real-time requirements of fingerprint identification system.First,the gray balance processing for fingerprint images can be done by this method.And then,this method subdivides the fingerprint images according to the characteristics of the gray-scale images.Finally,fingerprint marginal prospects are amended using the way of mathematical morphology.The method is used to carry on the massive tests with fingerprint images by MBF200 semiconductor fingerprint gathering,which is designed by this laboratory independently.The experimental results show that the method for this type of fingerprint image segmentation is effective.
Collection and analysis of 3D coordinates tag in binocular stereo vision positioning

The key technique of binocular stereo vision is composed of camera calibration,stereo matching and 3D coordinates computing.The 3D coordinates of tag on OPT are given by least square method through the results of stereo matching.The experiment has shown that the tracking system based on binocular stereo vision can position in a high precise level with small error under the current experiment condition.The relative error is less than 1%. Using this tracking system,the method presented in this paper can position and display human meridian in real-time at the primary level and provide more direct analysis foundation for clinical diagnosis treatment and basic education.
The Formalization Description of the Dolev-Yao Intruder Model

Model Checking can verify security protocols automatically.It is an efficient formal method. But there lacks a general method to build the intruder model.It leads to the decrease of the automation degree of model checking. This paper gives a formalization description method of the Dolev-Yao intruder model wich is most widely used in security protocols analysis.According to this method,we can use an arbitrary modeling language to build the Dolev-Yao intruder model by rote.It greatly decreases the components of artificial analysis. Meanwhile,we use this method to verify two security protocols with different goals.It proves that our method is general-purpose.
Attentional Drift: An Exploratory Study into the Development of an Attention Level Monitoring System Based on Human Eye Fixation

Abstract : This study was designed to determine if future research into the development of an attention monitoring device based on eye fixation duration is both feasible and warranted. Attentional Drift is an insidious form of distraction where primary task attention is slowly eroded by secondary tasking. It most often occurs in very low or very high cognitive demand situations. Recent studies have shown that eye fixation duration and glance duration measures are related to attentional demand in visual tasks. In this study, participants completed two 20-minute driving periods in a STISIM II (trademark) simulator wearing a head-mounted eye-tracking system. Eye fixation measures recorded in a single-task low mental demand test did not show an expected increase in eye fixation duration over time in all but a few participants. A second test incorporating dual tasking through conversation did show that eye fixation duration values were affected by the added cognitive workload. Eye fixation measures showed statistically significant changes in duration as a direct result of varying secondary cognitive demand. It is concluded that further experimentation with significantly lengthened test runs incorporating an eye blink rate factor, a gaze dwell time function, and a fixed-base eye-tracking system is both feasible and warranted.
Gamifying science – the issue of data validation

In this paper we will present the idea of gamifying scientific processes. Game design techniques appear to be very useful when we are dealing with processing enormous amounts of scientific data (think of domains such as biology or astronomy, for example). We will focus our attention on the issue of the effectiveness of such an approach, as well as on the issue of procedures and techniques that ensure the high quality of results obtained via gamified scientific processes.
A cloud computing-based implementation of regional medical information sharing

Objective To establish a regional medical information sharing platform used to promote the sharing of regional medical data such as electronic medical records( EMR) and medical images in order to improve medical services. Methods With reference to results and experience of the domestic and foreign research and by virtualizing re-establishment of the existing medical information resources,a regional medical information sharing platform was established based on cloud computing,SOA,and Web services,and then the heterogeneous information systems in different medical institutions were integrated. Results A novel cloud platform solution was proposed for clinical information exchange between medical institutions based on Web services that exchanged data and ensured the data security and privacy using XML encryption and compression. The prototype developed in a cloud environment was put into use in dozens of military hospitals to enable the sharing of clinical information. Conclusion This cloud computing platform has the advantages of dynamic scalability,distributed and ubiquitous access. It is highly feasible and practical for regional medical informatization.
A Monadic Slicing Algorithm for a Program with Pointers

Program slicing is a family of program decomposition techniques.By introducing point-to analysis to the previous monadic slicing,the authors present and implement an approach of monadic slicing for a program with pointers.This approach obtains the point-to information through the data-flow iteration.Being different from the traditional methods,the point-to information and slicing are computed in the same phase in the method,by combining the forward monad slicing with data-flow iteration.Instead of recording point-to information for every statement,it is only needed to record the information for current analysis statements.So the method saves space without losing the precision.In addition,the approach also reserve the excellent properties of compositionality and language-flexibility from the original monadic slicing method.
Conceptual modeling of emergent processes in dynamic complex systems

The proper study of Dynamical Systems (DS) considers phenomenal dynamics, from which it is possible to reach an approximate description of its operation and an explanation for their behavior, often complex and unpredictable. Studying dynamic systems (DSs) currently requires an integrated framework of concepts, which should allow analysis from a broader perspective. In response, this work expands the vision of Dynamic System (DS) from its complexity way and from the related dimensions of its Self-organization and Emergence, in addition with Homeostasis, and Autopoiesis dimensions (SEHA approach). Thus, in this document, firstly, DS is described and supported on the basis of its SEHA and, secondly, develops notions for each of the SEHA phenomena, which are described in detail based on its integration to a concept map model that facilitates the observation of their relations, especially regarding DS self-organization. This approach is a synergic and promising way to understand processes and mechanisms that govern surrounding or constructed DS-SEHA, at the time it sets up the bases for a future formalization with modeling aims.
Filtering Method of the Sonar Images with Mixed Noise

In this paper,a combinatorial algorithm of median filtering and morphological filtering for the sonar images with mixed noise is proposed,the commonly used methods and their combination are analyzed and compared.The simulation results show that the combinatorial algorithm of median filtering and morphological filtering is better for sonar images with mixed noise.
DES Key Extension Method

Data Encryption Standard(DES) is a realization of Feistel algorithm,but the length of its key is too short.It can not meet the needs of network security now.Aiming at this problem,this paper proposes a simple method of key extension for the DES.This method extends DES key from 56 bit to 112 bit,and proves its validity by experimental result.
Seductions of crime : moral and sensual attractions in doing evil

* Introduction * Righteous Slaughter * Sneaky Thrills * Ways of the Badass * Street Elites * Doing Stickup * Action, Chaos, and Control: Persisting with Stickup * Of Hardmen and Bad Niggers: Gender and Ethnicity in the Background of Stickup * Primordial Evil: Sense and Dynamic in Cold-Blooded, Senseless Murder * Seductions and Repulsions of Crime