Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Evaluation of Bellman-Ford, AODV, DSR and DYMO Protocols using QualNet in 1000m◊1000m Terrain Area

Wireless sensor networks (WSNs) offer much promise for target tracking and environmental monitoring. While many WSN routing protocols have been proposed to date, most of these focus on the mobility of observers and assume that targets are fixed. In addition, WSNs often operate under st rict energy constraints, and therefore reducing energy dissipat ion is also an important issue. In this paper w e discuss various protocols like Bellman-Ford, Ad-Hoc on-Demand Routing (AODV), Dynamic Source Routing (DSR), Dynamic MANET On-demand Protocol (DYMO) and compare various parameters like Average End-to-End Delay (sec.), Residual Battery Capacity (mAhr), and Throughput (bits/sec.), Output Received at CBR Server.
Getting Into Networks and Clusters: Evidence on the GNSS composite knowledge process in (and from) Midi-Pyrénées

This paper aims to contribute to the empirical identification of clusters by proposing methodological issues based on network analysis. We start with the detection of a composite knowledge process rather than a territorial one stricto sensu. Such a consideration allows us to avoid the overestimation of the role played by geographical proximity between agents, and grasp its ambivalence in knowledge relations. Networks and clusters correspond to the complex aggregation process of bi or n-lateral relations in which agents can play heterogeneous structural roles. Their empirical reconstitution requires thus to gather located relational data, whereas their structural properties analysis requires to compute a set of indexes developed in the field of the social network analysis. Our theoretical considerations are tested in the technological field of GNSS (Global Satellite Navigation Systems). We propose a sample of knowledge relations based on collaborative R&D projects and discuss how this sample is shaped and why we can assume its representativeness. The network we obtain allows us to show how the composite knowledge process gives rise to a structure with a peculiar combination of local and distant relations. Descriptive statistics and structural properties show the influence or the centrality of certain agents in the aggregate structure, and permit to discuss the complementarities between their heterogeneous knowledge profiles. Quantitative results are completed and confirmed by an interpretative discussion based on a run of semi-structured interviews. Concluding remarks provide theoretical feedbacks.
Considering Impact of Sociolinguistic Findings in Believable Opinion Mining Systems

Opinions are frequent means of communication in human society and automatic approaches to opinion mining in texts attracted therefore much attention. All in all, most approaches apply data mining techniques and extract lexical features (words) as reliable means of classification [1]. Noteworthy that although the interest in opinion mining is huge, there are only few explorations on words extracted in opinion mining. This study considers this drawback and elaborates on a sociolinguistic explanation. We hypothesize: an opinion mining system should be trained for classifying opinions in texts of the same language style. Hence, this contribution focuses on the following questions: 1) do sociolinguistic aspects of corpora, for example, their colloquiality or literariness, influence classification results; 2) how should reliable opinion mining systems train to obtain trustworthy classification results.
Energy Efficient Spectrum Aware Clustering for Cognitive Sensor Networks

Combining cognitive radio technology with wireless sensor networks has been introduced in the literature as a solution to the spectrum deficiency problem. Many clustering algorithms have been proposed for wireless sensor networks. However, most of them are not suitable for cognitive sensor networks as they operate on a fixed channel settings. In this work, we propose a low energy spectrum aware clustering algorithm, CogLEACH-C, based on CogLEACH algorithm in order to improve the performance in terms of system lifetime.To accomplish that, energy level of each sensor node should be taken into account during the selection process. CogLEACH-C uses not only the number of channels sensed idle by the node but also the node energy level in determining the probability for each node to be a cluster head. Hence, allows the base station to select K cluster heads that are in a better position for the nodes in the network. Moreover, as the network consists of primary users (PU) and secondary users sharing the same channels with the priority for the primary users, secondary nodes that are within the coverage of primary users will sense a low number of idle channels depending on the primary user’s activity. As a result, those nodes will experience difficulty to connect with a cluster head and that affects the performance of the network.In particular, when the probability of a channel to be idle is low and the majority of the channels are within the coverage of the PUs. We provide an analysis of the probability of connectivity of a sensor node in cognitive wireless sensor network when CogLeach-C algorithm is used, and we show how that affects the performance of the network in terms of delay and network lifetime.
Coupled effect of feedstock and pyrolysis temperature on biochar as soil amendment

Thailand is an agricultural country based. A strategy to use biomass is to produce biochar which has original properties that make it a valuable soil amendment. This study investigated the effect of pyrolysis temperatures (350 and 550 °C) using difference types of biomass, including coconut shell, eucalyptus, and sugar cane. The link between biochar properties and its function as soil fertilizer is used to give a definition for biochar quality. Results shown the highest surface area and pore volume were found for coconut shell at 550°C. Biochar pH values were all alkaline whatever the temperature. The first indication of the suitability of soil fertilizer is the nutrient content which has been found the highest for sugar cane at 350°C. The highest ratio (P+K):N, the better the release of the nutrient content. Finally, biochar quality will be driven by raw materials and pyrolysis conditions.
Traitements des images de couleur en représentation luminance / saturation / teinte par norme L 1 Colour image processing from luminance / saturation / hue in L 1 representation

and key words The classical colour polar-based representations, of type (HSV, HLS, etc.), lead to brightness and saturation with non consistent properties. In this paper they are replaced by means of norms, in particular L1 and max-min. Two examples illustrate the suitable relevance of L1 norm with regard to segmentation issues. The first issue deals with the histograms luminance/saturation which are plotted for four different representations. They highlight alignments in the case of the norm L1 and these alignments characterise zones of shadows or of reflections in the image. A model of linearly regionalised spectrum for light flux is proposed for a physical interpretation of this proportionality. The second example relates to morphological colour image segmentation, starting from polar representations. The main underlying idea here is to fully exploit the nature of the saturation component as a balance between the luminance and the hue. More precisely, each of the three components luminance, saturation and hue is processed independently from the others, according to a traditional segmentation technique for numerical functions. In the regions of high saturations, traitement du signal 2004_volume 21_numéro spécial L'image numérique couleur 583
Industrial Management & Data Systems Understanding continuance usage of mobile sites

Purpose – The purpose of this research is to draw on both perspectives of technological perceptions and flow experience to examine continuance usage of mobile sites. Design/methodology/approach – Based on the valid responses collected from a survey questionnaire, structural equation modeling technology was employed to examine the research model. Findings – The results indicated that both perspectives of technological perceptions and flow experience have effects on satisfaction, which in turn affects continuance usage. Technological perceptions include system quality and information quality, whereas flow experience includes perceived enjoyment and attention focus. Among them, perceived enjoyment has the largest effect on satisfaction. Research limitations/implications – This research is conducted in China, where mobile internet is still in its early stage. Thus, the results need to be generalized to other countries that had developed mobile internet. Originality/value – Previous research has focused on the effects of instrumental beliefs such as perceived usefulness on mobile user continuance. However, user behavior may be also affected by intrinsic motivations such as flow. This research tries to fill the gap.
Evaluation and optimization of clustering in gene expression data analysis Journal of Bioinformatics 1 Evaluation and optimization of clustering in gene expression data analysis

Motivation: A measurement of cluster quality is needed to choose potential clusters of genes that contain biologically relevant patterns of gene expressions. This is strongly desirable when large number of gene expression profiles have to be analyzed and proper clusters of genes need to be identified for further analysis, such as the search for meaningful patterns, identification of gene functions or gene response analysis. Results: We propose a new cluster quality method, called stability, by which unsupervised learning of gene expression data can be efficiently performed. The method takes into account a cluster’s stability on partition. We evaluate this method and demonstrate its performance using four independent, real gene expression and three simulated data sets. We demonstrate that our method outperforms other techniques listed in the literature. The method has applications in evaluating clustering validity as well as identifying stable clusters. Availability: Please contact the first author. Contact: fazel.famili@nrc-cnrc.gc. ca
Evaluation and Optimization of Clustering in Gene Expression Data Analysis * Famili

Motivation: A measurement of cluster quality is needed to choose potential clusters of genes that contain biologically relevant patterns of gene expressions. This is strongly desirable when large number of gene expression profiles have to be analyzed and proper clusters of genes need to be identified for further analysis, such as the search for meaningful patterns, identification of gene functions or gene response analysis. Results: We propose a new cluster quality method, called stability, by which unsupervised learning of gene expression data can be efficiently performed. The method takes into account a cluster’s stability on partition. We evaluate this method and demonstrate its performance using four independent, real gene expression and three simulated data sets. We demonstrate that our method outperforms other techniques listed in the literature. The method has applications in evaluating clustering validity as well as identifying stable clusters. Availability: Please contact the first author. Contact: fazel.famili@nrc-cnrc.gc. ca
Challenges in data integration and interoperability in geovisual analytics

Geographic information technologies are evolving from stand-alone systems to a distributed model of independent web services. In parallel, voluminous geographic data are being collected with modern data acquisition techniques such as remote sensing and personal navigation devices. There is an urgent need for effective and efficient methods to integrate and explore relationships between remote sensing and trajectory datasets. When it comes to integration, one would commonly rely on a conventional chain of GIS operations to match trajectory locations to grid values: download grid data, georeference, match each trajectory record to a corresponding image cell, perform overlay, extract cell values for a given location and time and compose values into a resulting table. If one has to deal with large and dynamic spatio-temporal data sets, this approach is clearly unmanageable. We propose an alternative approach: a four-layered system architecture that utilises web services for the integration of trajectory and remote sensing data. We demonstrate how this integration service can be embedded into distributed components for manipulation, analysis and visualisation of geospatial trajectories, using Antarctic iceberg trajectories and wind data as a case study. The prototype can be accessed on the web. Future research will include optimisation and integration of more variables extracted from grid data sets, but the main focus will be on extension of the analytical component by implementing more mechanisms to discover patterns in the integrated data set, and on better visualisation.
Internetworking Indonesia Journal

—Business Intelligence (BI) is becoming an important IT framework that can help organizations managing, developing and communicating their intangible assets such as information and knowledge. Thus it can be considered as an imperative framework in the current knowledge-based economy arena. In this paper, we will explain the role BI is playing in providing organizations with a way to plan and achieve their business strategy. We will experiment this role using a case study in the field of high education, especially helping one of the new private university in Syria (Arab International University)planning and achieving their business strategy.
Electromagnetic resonance through narrow slots in a transmission cavity in a thick conducting screens

Since H. A. Bethe reported his work [1] on the electromagnetic coupling through a small hole in the conducting plane, it has been well-known that the transmitted power through the small aperture in an infinite conducting plane is expressed by multiplication of the incident power density / and the transmission cross section TCS T[ which scaled as / for the hole diameter D much smaller than the wavelength λ. So the transmitted power through the small aperture becomes very small as D decreases. Recently lots of researches have been done with a view of enhancing transmission efficiency of small(subwavelength) aperture for the applications such as optical compact data storage, nanolithography, and nano-microscopy. As a result it has been found that the transmission efficiency can be significantly enhanced by reforming the aperture shape as in the circular ridged aperture [2] or by employing a small coupling aperture-to-cavity-to aperture system, i.e., a transmission resonant cavity system in a thick conducting screen. To distinguish between the two kinds of structures, we call the former and the latter TRA(Transmission resonant aperture) and TRC(Transmission resonant cavity) structure respectively. It is interesting to note also that TCS T for both the above two structures can be increased to the maximum value of 3 /4 for the TRA case and for the TRC case that input(incident side) and output coupling hole are the same to each other as a small hole. This means that incident power on the much larger area than actual aperture area is funneled into the physical aperture and transmitted through TRA/TRC structure and radiated into the opposite half space to incident side under the transmission resonance where the transmitted power becomes maximum. In this article, we focus our interest to investigating the unsymmetrical transmission resonance cavity(TRC) case where input coupling aperture and output coupling aperture are different from each other. In particular we deal with the case that the input/output coupling holes are of narrow slot type for the convenience of analysis.
A Study on the Conceptual Modeling and Implementation of a Semantic Search System

This paper proposes a design and realization for the semantic search system. The proposed model includes three Architecture Layers of a Semantic Search System ; (they are conceptually named as) the Knowledge Acquisition, the Knowledge Representation and the Knowledge Utilization. Each of these three Layers are designed to interactively work together, so as to maximize the users' information needs. The Knowledge Acquisition Layer includes index and storage of Semantic Metadata from various source of web contents(eg : text, image, multimedia and so on). The Knowledge Representation Layer includes the ontology schema and instance, through the process of semantic search by ontology based query expansion. Finally, the Knowledge Utilization Layer includes the users to search query intuitively, and get its results without the users'knowledge of semantic web language or ontology. So far as the design and the realization of the semantic search site is concerned, the proposedsemantic search system will offer useful implications to the researchers and practitioners so as to improve the research level to the commercial use.
Protein Structure Determination via Distance Geometry Structural Similarity based Initialization

The problem of ﬁnding the conﬁguration of points given partial information on pairwise inter-point distances, the Euclidean distance geometry problem, appears in multiple applications. In this paper, we propose an approach that integrates structural similarity and a nonconvex distance geometry algorithm for the protein structure determination problem. When initialized with a homologous structure, reconstruction of ubiquitin structure with our non convex algorithm resulted in an RMSE of less than 2 ˚A with 1 . 5% available inter proton distance and up to 20% relative error in the input distances. To test the robustness of this algorithm with regard to initialization, we also initialized with a nonhomologous structure on a larger protein with pdb coordinate 1W2E. Even though the initialization structure 1JYB is far diﬀerent from 1W2E with an RMSE of 25 ˚A, reconstruction generated structures with RMSE of close to 2 ˚A, using 1 . 7% available proton distances and up to 10% relative error in input distances. These results suggest EDG-based approach may be applied to fast NMR structure determination in the future.
THE DIVISIVENESS OF DESIGN THINKING

If you aren’t familiar with design thinking, Tim Brown, CEO of design consultancy IDEO, defines it as “a human-centered approach to innovation that draws from the designer’s toolkit to integrate the needs of people, the possibilities of technology, and the requirements for business success” [4]. It’s taking the process designers have used to make chairs, cars, and toasters, and applying it to business strategy and large systems problems. Insights
Convergence Analysis of a Proximal Point Algorithm for Minimizing Differences of Functions

Several optimization schemes have been known for convex optimization problems. However, numerical algorithms for solving nonconvex optimization problems are still underdeveloped. A progress to go beyond convexity was made by considering the class of functions representable as differences of convex functions. In this paper, we introduce a generalized proximal point algorithm to minimize the difference of a nonconvex function and a convex function. We also study convergence results of this algorithm under the main assumption that the objective function satisfies the Kurdyka - \L ojasiewicz property.
Public Versus Private Sector Wage Gap in Egypt: Evidence from Quantile Regression on Panel Data

This paper considers the public and private sector wage earners in Egypt and examines their wage distribution during 1998-2012 using Egyptian Labor Market Panel Survey. We estimate the public-private sector wage gap with Mincer wage equations both at the mean and at different quantiles of the wage distribution. In this process we take into account observable and unobservable characteristics of the individuals using the panel feature of the data with a fixed effects model. We address sector of employment selection issue for both males and females. We find that there is very little evidence of sample selection in our data. Therefore, we present both the selection corrected results and the results with no selection correction. We find a persistent public sector wage penalty for males and public sector wage premium for females in the face of extensive sensitivity checks. They are larger when unobserved heterogeneity is taken into account for males but insignificant for females. They are similar across the quantiles for males but, smaller at the top than at the bottom of the conditional wage distribution for females. We further examine the public sector wage gap over time and in different sub-groups according to age and education. The public sector wage penalty for males has decreased recently over time and is larger for the better educated and younger. We also find substantial regional differences in public sector wage gap for males.
A distributed evolutionary algorithmic approach to the least-cost connected constrained sub-graph and power control problem Extended

Wireless sensor networks will require some form of logical layering of nodes to minimize energy consumption and maximize throughput. Adjusting the transmit power of the sensor nodes imposes a natural clustering on the network. But how does one determine the appropriate transmit energy of each sensor node? A possible approach, motivated by an evolutionary optimization technique, Particle Swarm Optimization(PSO) is proposed and extended in a novel way. A fully distributed version of PSO is developed and explored using experimental fitness to attempt to achieve an approximation of least-cost connectivity. This problem is directly related to clustering a wireless sensor network. Imagine a fully connected network of 8 sensor nodes as in Figure 1.
Evolutionary game analysis of enterprise R&D decision-making in the production and learning alliance

In this paper, the evolution game model is used to investigate the difference of the profit and game strategies of the cooperative innovation of enterprises participating in the cooperative innovation of enterprises under the constraints of enterprise cooperation and non-cooperation (competition). Results indicate that Under the constraint of inter-enterprise cooperative strategy, there are two steady-state convergent equilibrium points. The direction of strategy convergence depends on the net gain of cooperative innovation. Under the constraint of non-cooperative strategy between enterprises, whether the enterprise chooses to participate or not participate fully depends on whether the net income can be obtained under the participation strategy. At the same time, both the increase of gain and the decrease of cost can increase the probability of participation strategy selection. Further, the above analysis shows that the government's policy of stimulating enterprises to participate in the collaborative innovation of production through direct and indirect financial subsidies is reasonable. However, the incentive effect of government subsidy under non-cooperative constraint can realize the existence threshold.