Miracle-dz/UniFAR-FTUs huggingface dataset:
A software tool for the decentralized control of AGV systems

This paper presents a software tool for the simulation of a decentralized control strategy to assign tasks to Autonomous Guided Vehicles (AGV) and coordinate their paths to avoid deadlock and collisions. We consider a zone-controlled guidepath network where a set of intelligent vehicles (agents) has to autonomously reach a consensus about the distribution of a set of tasks, i.e., a set of zones to be reached. To this aim, first the agents apply a discrete consensus algorithm in order to locally minimize the global cost for reaching the destination zone, then they move according to a decentralized coordination protocol that is based on a zone-controlled approach with the aim of avoiding deadlock and collisions. The software tool allows the user to define the guidepath network, then randomly generates the positions of AGVs and destinations and runs the two algorithms visually showing their behavior.
Nonlinear singular spectrum analysis by neural networks

Singular spectrum analysis (SSA), a linear univariate and multivariate time series technique, is essentially principal component analysis (PCA) applied to the time series and additional copies of the time series lagged by 1 to K time steps. Neural network theory has meanwhile allowed PCA to be generalized to nonlinear PCA (NLPCA). In this paper, NLPCA is further extended to perform nonlinear SSA (NLSSA): First, SSA is applied to the data, then the leading principal components of the SSA are chosen as inputs to an NLPCA network (with a circular node at the bottleneck), which performs the NLSSA by nonlinearly combining all the input SSA modes into a single NLSSA mode. This nonlinear spectral technique allows the detection of highly anharmonic oscillations, as illustrated by a stretched square wave imbedded in white noise, which shows NLSSA to be superior to SSA and classical Fourier spectral analysis. NLSSA is also applied to the Southern Oscillation Index (a monthly time series of the equatorial Pacific air pressure conditions from 1866 to 2000), which reveals a first mode with period of 52 months, and a second mode of 39 months.
Use of small imaging sonars for diver identification

Defence Research and Development Canada has recently wrapped up a 4-year project to demonstrate an integrated system for force protection in harbours, the Canadian Underwater Protection System (CUwPS). The intention of the Maritime Force Protection Technology Demonstration Project was to provide advice to the Canadian Navy on countering underwater threats to ships (divers, swimmers, AUVs) in harbours and anchorages. The project program was designed around a series of trials, which included a major international trial in Sydney, Australia, in February 2009, an evaluation for potential use in security measures for the 2010 Winter Olympics and participation in exercises prior to and during the International Fleet Review and Royal visit in July 2010. The CUwPS itself is comprised of COTS equipment with modest integration. A critical aspect of the CUwPS concept of operations is the requirement to positively identify threats that have been flagged by a wide-area-coverage diver detection sonar system. This is accomplished by tasking a response boat outfitted with a high resolution imaging sonar to investigate contacts or areas and if appropriate, to issue loud-hailer warnings. During the trials conducted through the course of the MFP TDP, several different small imaging sonars were tested for this identification role, with varying degrees of success. Assessment of the performance of the imaging sonars has been undertaken with the goal of obtaining an objective measure of the suitability of any one sonar for the identification task. The results of this assessment exercise will be presented along with some lessons learned.
Rendering of Wet Materials

The appearance of many natural materials is largely influenced by the environment in which they are situated. Capturing the effects of such environmental factors is essential for producing realistic synthetic images. In this work, we model the changes of appearance due to one such environmental factor, the presence of water or other liquids. Wet materials can look darker, brighter, or more specular depending on the type of material and the viewing conditions. These differences in appearance are caused by a combination of the presence of liquid on the surface and inside the material. To simulate both of these conditions we have developed an approach that combines a reflection model for surface water with subsurface scattering. We demonstrate our approach with a variety of example scenes, showcasing many characteristic appearances of wet materials.
Towards the Construction of Expressed Proteomes Using a Leishmania tarentolae Based Cell-Free Expression System

The adaptation of organisms to a parasitic life style is often accompanied by the emergence of novel biochemical pathways absent in free-living organisms. As a result, the genomes of specialized parasitic organisms often code for a large number (>50%) of proteins with no detectable homology or predictable function. Although understanding the biochemical properties of these proteins and their roles in parasite biogenesis is the next challenge of molecular parasitology, analysis tools developed for free-living organisms are often inadequate for this purpose. Here we attempt to solve some of these problems by developing a methodology for the rapid production of expressed proteomes in cell-free systems based on parasitic organisms. To do so we take advantage of Species Independent Translational Sequences (SITS), which can efficiently mediate translation initiation in any organism. Using these sequences we developed a single-tube in vitro translation system based on the parasitic protozoan Leishmania tarentolae. We demonstrate that the system can be primed directly with SITS containing templates constructed by overlap extension PCR. To test the systems we simultaneously amplified 31 of L. tarentolae's putative translation initiation factors and phosphatases directly from the genomic DNA and subjected them to expression, purification and activity analysis. All of the amplified products produced soluble recombinant proteins, and putative phosphatases could be purified to at least 50% purity in one step. We further compared the ability of L. tarentolae and E. coli based cell-free systems to express a set of mammalian, L. tarentolae and Plasmodium falciparum Rab GTPases in functional form. We demonstrate that the L. tarentolae cell-free system consistently produced higher quality proteins than E. coli-based system. The differences were particularly pronounced in the case of open reading frames derived from P. falciparum. The implications of these developments are discussed.
Computing Semantic Relatedness of GermaNet Concepts

We present a system designed to compute the semantic relatedness between a pair of GermaNet concepts (word senses). Five different metrics have been implemented. Three of them are information content based and incorporate the Two metrics constitute the application of a Lesk algorithm (Lesk 1986) to artificial conceptual glosses generated from GermaNet. We show that four metrics correlate very well with a set of human judgments of semantic relatedness. We conclude with implementation issues and a description of a graphical user interface to compute the semantic relatedness of German words. semantischen Beziehung zwischen Wortbedeutungen in GermaNet.
Censure Politics and Criminal Justice

Contemporary socialist criminology renewing sociological theory rethinking deviance - towards a sociology of censure reflections on a sociological theory of criminal justice the politics of censure magistrates courts and the struggle for local democracy 1886-1981 the censure of "Communism" and the political trial in South Africa media, censure and politics dramatic power television images of crime and law enforcement strategies of censure and the "Suffragette" movement the press censure of "Dissident Minorities".
Human eye movements as a trait for biometrical identification

This research work proposes an innovative processing scheme for the exploitation of eye movement dynamics on the field of biometrical identification. As the mechanisms that derive eye movements highly depend on each person's idiosyncrasies, cues that reflect at a certain extent individual characteristics may be captured and subsequently deployed for the implementation of a robust identification system. Our methodology involves the employment of a non - parametric statistical test, the multivariate Wald - Wolfowitz test (WW-test), in order to compare the distributions of saccadic velocity and acceleration features, which are extracted while a person fixates on visual stimuli. In the evaluation section we use two publicly available datasets that supply recorded eye movements from a number of subjects during the observation of a moving spot on a computer screen. The resulting identification rates exhibit the efficacy of the suggested scheme to adequately segregate people according to their eye movement traits.
A robust MPC/ISM hierarchical multi-loop control scheme for robot manipulators

In this paper, we propose a robust hierarchical multi-loop control scheme aimed at solving motion control problems for robot manipulators. The kernel of the proposed control scheme is the inverse dynamics-based feedback linearized robotic MIMO system. A first loop is closed relying on an Integral Sliding Mode (ISM) controller, so that matched disturbances and uncertain terms due to unmodelled dynamics, which are not rejected by the inverse dynamics approach, are suitably compensated. An external loop based on Model Predictive Control (MPC) optimizes the evolution of the controlled system in the respect of state and input constraints. The motivation for using ISM, apart from its property of providing robustness to the scheme in front of a significant class of uncertainties, is also given by its capability of enforcing sliding modes of the controlled system since the initial time instant, which is a clear advantage in the considered case, allowing one to solve the model predictive control optimization problem relying on a set of linearized decoupled SISO systems which are not affected by uncertain terms. As a consequence, a standard MPC can be used and the resulting control scheme is characterized by a low computational load with respect to conventional nonlinear robust solutions. The verification and the validation of our proposal have been carried out with satisfactory results in simulation, relying on a model of an industrial robot manipulator with injected noise, to better emulate a realistic set up. Both the model and the noise have been identified on the basis of real data.
Mining spatio-temporal co-location patterns with weighted sliding window

Spatial co-location patterns represent the subsets of features (co-location) whose events are frequently located together in geographic space. Spatio-temporal co-location (co-occurrence) pattern mining extends the mining task to the scope of both space and time. However, embedding the time factor into spatial co-location pattern mining process is a subtle problem. Previous researches either treat the time factor as an alternative dimension or simply carry out the mining process on each time segment. In this paper, we propose a weighted sliding window model (WSW-Model) which introduces the impact of time interval between the spatio-temporal events into the interest measure of the spatio-temporal co-location patterns. We figure out that the aforementioned two approaches fit into the two special cases in our proposed model. We also propose an algorithm (STCP-Miner) to mine spatio-temporal co-location patterns. The experimental evaluation with both the synthetic data sets and a real world data set shows that our algorithm is relatively effective with different parameters.
On Sustainability of Context-Aware Services Among Heterogeneous Smart Spaces

Most of ambient intelligence studies have tried to employ inductive meth- ods (e.g., data mining) to discover useful information and patterns from data streams on sensor networks. However, since the spaces have been sharing their information with each other, it is difficult for such inductive methods to conduct the discovery process from the sensor streams intermixed from the heterogeneous sensor networks. In this paper, we propose an ontology-based middleware system to improve sustainability of context-aware service in the interconnected smart spaces. Two main challenges of this work are i) sensor data preprocessing (i.e., session identification) and ii) information fusion (i.e., information integration). The ontology in each sensor space can provide and describe semantics of data measured by each sensor. By aligning these ontologies from the sensor spaces, the semantics of sensor data captured inside can be compared. Thus, we can find out not only relationships between sensor streams but also tempo- ral dynamics of a data stream. To evaluate the proposed method, we have collected sensor streams from in our building during 30 days. By using two well-known data mining methods (i.e., co-occurrence pattern and sequential pattern), the results from raw sensor streams and ones from sensor streams with preprocessing were compared with respect to two measurements recall and precision.
Attenuation of N-nitrosodimethylamine induced hepatotoxicity by Operculina turpethum in Swiss Albino mice

Objective(s): To appraise the antihepatotoxic efficacy of ethanolic extract of Operculum turpethum root on the liver of Swiss albino mice. Materials and Methods: Hepatic fibrosis was induced in adult male albino mice through intraperitoneal administrations of N-nitrosodimethylamine (NDMA) at the concentration of 10 mg/kg body weight. The liver toxicity and therapeutic effect of the plant ethanolic extract was assessed by the analysis of liver marker enzymes and antioxidant enzymes and liver histopathological studies. Results: Hepatotoxicity was manifested by significantly decreased (P<0.01) levels of the activities of the enzymatic and non enzymatic antioxidants such as superoxide dismutase, catalase, GSH and increased levels of cholesterol, AST, ALT, ALP and lipid peroxidation. The plant extract significantly restored the antioxidant enzyme level in the liver and exhibited significant dose dependent curative effect against NDMA induced toxicity which was also supported by histopathological studies of the liver. Conclusion: O. turpethum manifested therapeutic effects by significantly restoring the enzymatic levels and reducing the hepatic damage in mice. This work intends to aid researchers in the study of natural products which could be useful in the treatment of liver diseases including cancer.
Genome-Wide Identification, Evolutionary Analysis, and Stress Responses of the GRAS Gene Family in Castor Beans

Plant-specific GRAS transcription factors play important roles in regulating growth, development, and stress responses. Castor beans (Ricinus communis) are important non-edible oilseed plants, cultivated worldwide for its seed oils and its adaptability to growth conditions. In this study, we identified and characterized a total of 48 GRAS genes based on the castor bean genome. Combined with phylogenetic analysis, the castor bean GRAS members were divided into 13 distinct groups. Functional divergence analysis revealed the presence of mostly Type-I functional divergence. The gene structures and conserved motifs, both within and outside the GRAS domain, were characterized. Gene expression analysis, performed in various tissues and under a range of abiotic stress conditions, uncovered the potential functions of GRAS members in regulating plant growth development and stress responses. The results obtained from this study provide valuable information toward understanding the potential molecular mechanisms of GRAS proteins in castor beans. These findings also serve as a resource for identifying the genes that allow castor beans to grow in stressful conditions and to enable further breeding and genetic improvements in agriculture.
Culture and Economic Performance

Culture, defined as shared values and beliefs, can influence the performance of an economy in many ways. The culture of a group, whether national, regional or ethnic, may be regarded as a particular type of intangible public good. The chapter summarizes and critiques a positive theory of inter-cultural competition. According to this theory, culture is created by leaders, who specialize in the production of culture, and is shared by their followers. Leaders compete for followers in order to increase the rents that they can extract from their groups. Whilst some of these rents may be pecuniary, most are non-pecuniary, such as the enjoyment of pursuing a public project which glorifies the leader and their group. There are four main dimensions of culture which influence performance, and there are trade-offs between them which are governed by the environment of the social group. The positive theory is useful in interpreting historical evidence on the rise and decline of societies, institutions, and organizations of various kinds.
PLC Based Adaptive Fuzzy PID Speed Control of DC Belt Conveyor System

Abstract Conveyor belt system is one of the most common transfer systems used in industry to transfer goods from one point to another in a limited distance. It is used in industries such as the electro- mechanical/mechanical assembly manufacturing to transfer work piece from one station to another or one process to another in food industries. The belt conveyor system discussed in this paper is driven by a DC motor and two speed controllers. The PID speed controller is designed to provide comparison to the main controller which is the Adaptive Fuzzy PID Speed controller. Both controllers are implemented in a real hardware where the algorithm will be written in PLC using SCL language. The experimental result shows that Adaptive Fuzzy PID controller performs better and adapted to the changes in load much faster than the conventional PID controller. This project has also proved that PLC is capable of performing high level control system tasks.
Proof-of-concept of a robotic apple harvester

There are no mechanical harvesters for the fresh market apple industry commercially available. The absence of automated harvesting technology is a critical problem because of rising production costs and increasing uncertainty about future labor availability. This paper presents the preliminary design of a robotic apple harvester. The approach adopted was to develop a low-cost, `undersensed' system for modern orchard systems with fruiting wall architectures. A machine vision system fuses Circular Hough Transform and blob analysis to detect clustered and occluded fruit. The design includes a custom, six degree of freedom manipulator with an underactuated, passively compliant end-effector. After fruit localization, the system makes a linear approach to the apple and replicates the human picking process. Integrated testing of the robotic harvesting system has been completed in a laboratory environment with a replica apple tree for proof-of-concept demonstration. Experimental results show that the system picked 95 of the 100 fruit attempted with average localization and picking times of 1.2 and 6.8 seconds, respectively, per fruit. Additional work planned in preparation for field evaluation in a commercial orchard is also described.
FlexiMod: Flexible Coexistence Support for Programming Models

The rapid growth in big data is driving the development and evolution of numerous analytics frameworks optimized for the different needs of applications. Emerging big data applications comprise rich multi-faceted workflows with both compute-intensive and data-intensive tasks with intricate communication patterns. Thus, a single framework cannot support all application types and needs. For example, while the MapReduce model has proven to be effective for common data-intensive tasks with well-defined execution phases, the MPI programming model may be better suited for extracting high-performance for compute-intensive tasks and handling arbitrary communication patterns. Researchers have recognized this need to employ specialized models for different phases of a workflow, e.g., performing computations using MPI followed by visualizations using MapReduce. As a result, compromises have to be made either to use multi-cluster approaches that entail large data movement across clusters, or to sacrifice some aspects of the applications, e.g., using MapReduce solely with a higher communication overhead. Consequently, there is a crucial need for supporting coexisting disparate programming models on the same set of resources that are managed in a holistic manner. The objective of this research is to provide an efficient solution for the above problem by designing FLEXIMOD, a holistic approach for supporting coexistence of multiple programming models. The envisioned solution includes a user-friendly workflow generation tool, a runtime environment that feeds the different tasks to different programming frameworks and transparently executes the workflow, and an underlying scheduling system that co-ordinates and co-host different frameworks in the same set of resources under a multi-tenant environment. Our pilot project, GERBIL, a framework for co-hosting unmodified MPI applications alongside MapReduce applications on top of YARN. GERBIL bridges the fundamental mismatch between YARN and MPI by designing an MPI-aware resource allocation mechanism. Our initial evaluation shows that GERBIL enables MPI executions with performance comparable to a native MPI setup, and improve compute-intensive application performance by up to 133% when compared to corresponding MapReduce version of the applications.
A coalitional game analysis for selfish packet-forwarding networks

In wireless packet-forwarding networks, selfish nodes always want to maximize their utilities and do not like to help others forward data streams, thus causing severe network performance degradation. To solve the packet-forwarding problem, a novel coalitional game approach based on the selective decode-and-forward (SDF) relaying scheme is proposed. In the game-theoretic analysis, we study the properties and stability of the coalitions and prove that the cohesive behavior can be obtained by the aspect of outage probability. Simulation results show that the proposed SDF coalitional game can enforce cooperation and is beneficial in forming the cooperative groups.