Miracle-dz/UniFAR-FTUs huggingface dataset:
Social network analysis of calling data records for identifying influencers and communities

Nowadays, Telecommunication service providers produce a huge volume of calling data records (CDR) each day. A clear understanding of their customers is a key success of any company. To analyze the behaviors and relationships between customers, social network analysis (SNA) is usually employed to detect influencers and communities along with calling behaviors (profiles). Unfortunately, the graph of CDR is different from that of other social media, e.g., Twitter, Facebook, etc. So, the results should be mistaken and cannot reflect the real customers if SNA is directly applied to CDR, such as, misinterpret “telesales” as “influencer”. In this paper, we propose a data cleansing process for CDR in order to filter the anomaly numbers. This can improve the accuracy of the analysis and remove any misinterpreted outcomes. Moreover, a measure is invented to capture influencers based on calling behaviors. The experiment was conducted on 2.5 million calling records of a telecommunication in Thailand. The result showed that using our proposed solution and ranking metrics could detect influencers and communities accurately.
Potential Antioxidant Role of Tridham in Managing Oxidative Stress against Aflatoxin-B1-Induced Experimental Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most fatal cancers due to delayed diagnosis and lack of effective treatment options. Significant exposure to Aflatoxin B1 (AFB1), a potent hepatotoxic and hepatocarcinogenic mycotoxin, plays a major role in liver carcinogenesis through oxidative tissue damage and p53 mutation. The present study emphasizes the anticarcinogenic effect of Tridham (TD), a polyherbal traditional medicine, on AFB1-induced HCC in male Wistar rats. AFB1-administered HCC-bearing rats (Group II) showed increased levels of lipid peroxides (LPOs), thiobarbituric acid substances (TBARs), and protein carbonyls (PCOs) and decreased levels of enzymic and nonenzymic antioxidants when compared to control animals (Group I). Administration of TD orally (300 mg/kg body weight/day) for 45 days to HCC-bearing animals (Group III) significantly reduced the tissue damage accompanied by restoration of the levels of antioxidants. Histological observation confirmed the induction of tumour in Group II animals and complete regression of tumour in Group III animals. This study highlights the potent antioxidant properties of TD which contribute to its therapeutic effect in AFB1-induced HCC in rats.
Trade Blocks and the Gravity Model: Evidence from Latin American Countries

We apply the gravity model to examine the effects of the Andean Community and Mercosur on both intra-regional and intra-industrial trade in the period 1980- 1997. After accounting for size distance and competitiveness effects, the Andean Community preferential trade agreements had a significant effect on the reference products but only a marginal effect on the differentiated products, in particular capital-intensive goods. Mercosur preferential trade agreements had a significant positive effect only on the capital-intensive subcategory of the reference products.
University of Amsterdam at INEX 2011: Book and Data Centric Tracks

In this paper we describe our participation in INEX 2011 in the Book Track and the Data Centric Track. For the Book Track we focus on the impact of dierent document representations of book metadata for book search, using either professional metadata, user-generated content or both. We evaluate the retrieval results against ground truths derived from the recommendations in the LibraryThing discussion groups and from relevance judgements obtained from Amazon Mechanical Turk. Our ndings show that standard retrieval models perform better on user- generated metadata than on professional metadata. For the Data Centric Track we focus on the selection of a restricted set of facets and facet values that would optimally guide the user toward relevant information in the Internet Movie Database (IMDb). We explore dierent methods for eective result summarization by means of weighted aggregation. These weighted aggregations are used to achieve maximal coverage of search results, while at the same time penalizing overlap between sets of documents that are summarized by dierent facet values. We expect that weighted result aggregation combined with redundancy avoidance results in a compact summary of available relevant information.
Expert system with cloud database for optimal management of Fruit and Vegetable traceability

The aim of this research activity is to develop a modular, fully customizable and remotely operable sprayer. This kind of device can be installed on-board a standard farm tractor/support machine or to be integrated on-board the U-Go robot that is under development with a joined project between the DiGeSA and the DIEEI and co-founded by MIPAAF. The aim of the U-Go robot is to improve worker safety level during harmful operation inside greenhouses as chemicals distribution. The robot has autonomous navigation capabilities and the on-board computer can send command to the sprayer and receive information from the sprayer sensors. All the sprayer parameter can be accessed and modified during operation. These features are not very common in commercial computer controlled sprayer unit that normally use only a touch screen panel as user interface. The device is composed by a hydraulic subsystem and an electronic control unit. The hydraulic part of the sprayer is composed by a 130 l tank with 5 l hand-wash separated reservoir, an electrical actuated pump, a manual pressure regulator, an electric flux regulator, a pressure sensor, a flow rate meter and two electric on/off valves. These two valves can supply two vertical bar equipped with anti-drop, high pressure nozzles for spraying operation inside a standard tomato greenhouse. The pump has a nominal maximum pressure of 25 bar and a maximum flow of 20 l/m. The electronic control unit is composed by two digital/analog I/O modules with Ethernet interface that allows to remotely operate the different hydraulic component and read information from sensors and to manage other control unit parameter. The Ethernet interface will allows remote operation from the robot on-board computer as well as any other remote station with an internet connection using a suitable command set. The proposed architecture, being very modular, will allow component (sensor, actuators) to be added in an easy way. At this stage the sprayer unit is being mounted on-board the U-Go robot. In the meanwhile the electronic control unit is under development at DIEEI laboratory and preliminary functional test has been performed. In order to make totally transparent to a mid-level user all the lowlevel hardware behaviour, a suitable software server has been developed. In this way, user command can be sent as high-level string and sensor information can be received as numeric text string. As the whole system will be integrated, complete test will be performed.
Mesostructure from Specularity

We describe a simple and robust method for surface mesostructure acquisition. Our method builds on the observation that specular reflection is a reliable visual cue for surface mesostructure perception. In contrast to most photometric stereo methods, which take specularities as outliers and discard them, we propose a progressive acquisition system that captures a dense specularity field as the only information for mesostructure reconstruction. Our method can efficiently recover surfaces with fine-scale geometric details from complex real-world objects with a wide variety of reflection properties, including translucent, low albedo, and highly specular objects. We show results for a variety of objects including human skin, dried apricot, orange, jelly candy, black leather and dark chocolate.
Using Small-World Model to Improve the Performance of Alignment Particle Swarm Optimization

Alignment particle swarm optimization (APSO) is a novel variant of particle swarm optimization aiming to improve the population diversity. The topology structure of APSO is gbest model. Since the small-world model is more suit for the natural animal communication network, in this paper, it is incorporated into the methodology of APSO to further improve the performance. Simulation results show this strategy may provide well balance between exploration and exploitation capabilities.
Research on the avionic software quality evaluation based on the WSR methodology

With the development of avionics, software plays a more and more important role. However, software evaluation lags behind, compared with software testing. The main reasons are the difficulties of software measurement and the complexity of human factors. 'Wuli-Shili-Renli'(WSR) methodology is proposed by Professor Gu Ji-fa during his cooperation project about system engineering in the System Engineering Research Center of the University of Hull, UK, in 1994, which is a new academic point of view combining the advantages of Chinese philosophy and western philosophy. Based on WSR methodology, an avionic software evaluation method put forward by the paper is divided into three phrases, which are the Wuli, Shili and Renli. In Wuli phrase, we pay more attention to the nature of the whole evaluation such as the evaluated software information. In the Shili phrase, we focus on how to arrange the evaluation; In the Renli Phrase human factors will be mainly discussed. In the end, an example is given to demonstrate how the method is applied in an altimeter software evaluation project from Software Testing & Evaluation Centre of China Aviation Industry Corporation I&II.
A Genetic Algorithmic Approach to Planning IEEE 802.16 Networks

IEEE 802.16, also known as WiMAX (Worldwide Inter-operability for Microwave Access), is a new wireless access technology for current increasing demand of wireless high-speed broadband service. Efficient and effective deployment of such a network to service an area of users with certain traffic demands is an important network planning problem. This network planning can be formulated as an unsplittable capacitated facility location problem. Different from traditional p-median or splittable capacitated facility location models, which are already known to be NP-complete to obtain exact solutions, the unsplittable capacitated facility location problem is even harder. In this work, we resort to Genetic Algorithms (GAs) in order to yield good approximation solutions. Experiments show that our approach is fairly effective and robust to different scenarios of the network planning problem.
Impact of Rising Rice Prices and Policy Responses in Mali: Simulations with a Dynamic CGE Model

The increase in the international price of rice is likely to have substantial negative impacts on the poor in countries such as Mali which are net importers of rice. This paper relies on a dynamic CGE model to estimate the likely impact of the recent increase in rice prices on poverty with and without policy responses. Two sets of policy responses are considered: import tax cuts on rice and measures to increase productivity of domestic rice production. The results suggest that an increase in productivity would have a much larger positive impact than a reduction in taxes.
Long memory in the Greek stock market

Tests are made of the stochastic long memory in the Greek stock market, an emerging capital market. The fractional differencing parameter is estimated using the spectral regression method. Contrary to findings for major capital markets, significant and robust evidence of positive long-term persistence is found in the Greek stock market. As compared to benchmark linear models, the estimated fractional models provide improved out-of-sample forecasting accuracy for the Greek stock returns series over longer forecasting horizons.
Real-Time Network Processing : An Investigation

In this paper, we introduce a benchmark suite on RTP/RTCP processing. The suite consists of three benchmarks, namely RTP Sender, RTP Receiver and RTCP Processing. For each benchmark, three aspects are specified: functions, measurements and environments. After implementing the benchmarks, we perform profiling in order to determine the time-critical functions and investigate the architectural characteristics. Finally, the results on architectural characteristics show that the proposed benchmarks differ significantly from MediaBench and NetBench. Keywords—Benchmarking, real-time network processing, RTP/RTCP, profiling, architectural characteristics.
Parallel and digit-serial implementations of area-efficient 3-Operand Decimal Adders

In this paper, parallel and digit-serial implementations of area-efficient 3-operand decimal adders are proposed. By using proposed analyzer circuits and the generation of correction terms with recursive schemes, our proposed decimal adders could perform efficient additions with three operands. Unit gate estimates and synthesis results show that our proposed adders are more area-efficient than those previously proposed decimal adders with three operands under the same delay constraints. Also the power consumptions for our decimal adders are lesser. In addition to parallel implementations, the digit-serial 3-operand adders are easily developed to increase the throughput and the operating frequency due to area efficiency. Our proposed decimal adders could be applied to ease the tremendous computation efforts for decimal computations such as multi-operand decimal additions, decimal multiplications and divisions.
Segmenting acoustic signal with articulatory movement using Recurrent Neural Network for phoneme acquisition

This paper proposes a computational model for phoneme acquisition by infants. Human infants perceive speech sounds not as discrete phoneme sequences but as continuous acoustic signals. One of critical problems in phoneme acquisition is the design for segmenting these continuous speech sounds. The key idea to solve this problem is that articulatory mechanisms such as the vocal tract help human beings to perceive speech sound units corresponding to phonemes. That is, the ability to distinguish phonemes is learned by recognizing unstable points in the dynamics of continuous sound with articulatory movement. We have developed a vocal imitation system embodying the relationship between articulatory movements and sounds produced by the movements. To segment acoustic signal with articulatory movement, we apply the segmenting method to our system by recurrent neural network with parametric bias (RNNPB). This method determines the multiple segmentation boundaries in a temporal sequence using the prediction error of the RNNPB model, and the PB values obtained by the method can be encoded as kind of phonemes. Our system was implemented by using a physical vocal tract model, called the Maeda model. Experimental results demonstrated that our system can self-organize the same phonemes in different continuous sounds. This suggests that our model reflects the process of phoneme acquisition.
A goal-based technique for requirements prioritization

It is a well-known fact that the number of software requirements from customers usually exceeds the number of features that can be implemented within a given time and available resources. Therefore, requirements prioritization (RP) is essential during the requirements elicitation activity of the requirements engineering phase of software development. In addition, not all requirements can be implemented within one release, so RP is also essential for release planning. There are many RP techniques available in the literature, which are mostly attempting to solve a multi-criteria decision making problem. However, most of them work well on a small number of requirements, and many still suffer from different shortcomings such as scalability, uncertainty, a lot of stakeholders' time consumption, and complexity. According to many studies, none of the RP techniques can be considered the best; the best RP technique depends on the situation. In addition, most of the RP techniques don't take into account the effects of the required goals on the final alternatives' ranking. In this paper, we present a brief survey of the most popular decision making RP techniques, before presenting our new goal-based RP technique. Our goal-based RP technique is based on generating a relative weight for the requirements with respect to the identified goals by stakeholders. It is inspired from prioritization decision making techniques in an attempt to enhance reported RP problems of time consumption, scalability and complexity.
Inequality in Ghana : Gini Coefficient of Education

Continuing the debate over the issue of ‘’equity of what? ’’ the paper looks at one of the concerns of what needs to equalised: opportunities people face, that has taken a centre stage in the discussions in the development literature. Using quantitative measures including gini coefficient calculations our study attempts to explain the effects of Ghana’s educational reforms on access to educational opportunities by various groups including males and females in various ecological zones of Ghana. The study finds evidence of declining education inequality and increases in average years of schooling over time similar to that observed in many other developing countries as traces of the positive impact of the reform. It, however, finds an increase in the already existing wide education gendergab, in spite of the emphasis on girl child education under the reform.
Using Kernel Discriminant Analysis to Improve the Characterization of the Alternative Hypothesis for Speaker Verification

Speaker verification can be viewed as a task of modeling and testing two hypotheses: the null hypothesis and the alternative hypothesis. Since the alternative hypothesis involves unknown impostors, it is usually hard to characterize a priori. In this paper, we propose improving the characterization of the alternative hypothesis by designing two decision functions based, respectively, on a weighted arithmetic combination and a weighted geometric combination of discriminative information derived from a set of pretrained background models. The parameters associated with the combinations are then optimized using two kernel discriminant analysis techniques, namely, the kernel Fisher discriminant (KFD) and support vector machine (SVM). The proposed approaches have two advantages over existing methods. The first is that they embed a trainable mechanism in the decision functions. The second is that they convert variable-length utterances into fixed-dimension characteristic vectors, which are easily processed by kernel discriminant analysis. The results of speaker-verification experiments conducted on two speech corpora show that the proposed methods outperform conventional likelihood ratio-based approaches.
Pseudo-relevance feedback query based on Wikipedia

The traditional information retrieval (IR) model always only use the BOW (bag-of-words)-based retrieval model or Concepts-based retrieval model. However BOW-based model ignore the rich semantic relations between the words and text, and Concept-based model always bring in the noisy concepts and loss the precision. Pseudo-relevance feedback (PRF) is a widely used method for improving retrieval effectiveness, but it is strongly dependent on the precision of initial retrieval results. In order to solve these issues, this paper proposes a new concept generator called Enrichment-ESA which is the enrichment of the Explicit Semantic Analysis (ESA) method. With the help of Enrichment-ESA, we propose a novel PRF method which combined the BOW-based retrieval model and Concept-based retrieval model together to solve shortcomings of the existing IR model in some degree. The experimental results show that our method improves over the baseline method and performs better than the common PRF method.
An Empirical Study on GSN Usage Intention: Factors Influencing the Adoption of Geo-Social Networks

Nowadays, geosocial networks (GSNs) have become a significant component of people's daily lives as they are one of the most popular applications that are being widely accessed through smart devices such as smartphones and tablets. Their rapid widespread use and their invasion of our private life warrant a better understanding. In particular, the impact of trust in GSN, the privacy concerns of users, their perception of risk and the social influence on the use of such mobile applications is not yet fully understood. In this paper, we study the factors influencing the usage intention of GSN users. To realize this, we propose a model based on the user's perspective. Our model focuses on four overall factors that influence the users' concerns and in turn their intention and aim of using GSNs: privacy concerns, trust, social influence and risk perception. We tested empirically the proposed research model by running a web-based survey. The participants consisted of 396 persons with at least a past experience with GSNs. The results revealed that among all the possible factors the privacy concerns, social influence and trust have a significant impact on the intention and usage of GSNs. In contrast, personality traits have almost no effects on trust or social influence. One notable exception is computer self-efficacy that was found to induce a strong influence on the four principal factors.
Accuracy Assessment of Digital Elevation Models based on Approximation Theory

Empirical research in DEM accuracy assessment has observed that DEM errors are correlated with terrain morphology, sampling density, and interpolation method. However, theoretical reasons for these correlations have not been accounted for. This paper introduces approximation theory adapted from computational science as a new framework to assess the accuracy of DEMs interpolated from topographic maps. By perceiving DEM generation as a piecewise polynomial simulation of the unknown terrain, the overall accuracy of a DEM is described by the maximum error at any DEM point. Three linear polynomial interpolation methods are examined, namely linear interpolation in 1D, TIN interpolation, and bilinear interpolation in a rectangle. Their propagation error and interpolation error, whose sum is the total error at a DEM point, are derived. Based on the results, the theoretical basis for the correlation between DEM error and terrain morphology and source data density is articulated for the first time.
Delay Range Stability of Distributed Time Delay Systems

Abstract This paper is dedicated to the stability analysis of a class of uncertain distributed delay systems, the kernel of which can be modeled as a polynomial function. The results are constructed by rewriting the system as an uncertain interconnected model. Appropriate robust control tools, i.e. quadratic separation, are then used to address the stability issue. To this end, some relations that highlight relevant characteristics of the delayed term are added to the interconnected model leading then to the conservatism reduction. Finally, numerical examples show the effectiveness of the proposed method.