The Effective Personnel Selection Via Multi-criteria Decision-making Method Analytic Hierarchy Process (AHP): A Web-based Application

Decision-making is a process that people encounter in their daily or business lives. The process aims at reaching a conclusion depending on the aims of the people. Multiple factors affect the process of decision-making depending on the characteristics of these factors. These factors that affect the process of decision-making complicate encountered problems, and in this stage as a solution, multi-criteria decision-making methods are preferred to use by the decision-makers. Decision-making methods are categorized according to specific goals served to give the best results to decisionmakers. Certainly, the most important goal for organizations is to ensure that the right person works in the right job in line with his/her goals. The problems that are encountered by human resources managers is decision-making problems. A small mistake made by human resource department during the personnel selection can cause negative consequences in short or long term for companies. In this study, a web-based application was developed in order to solve the personnel-selection problems of human resources management. A model that is based on multi-criteria selection has been developed to ensure the elimination of candidates through the program based on solution algorithm of Analytic Hierarchy Process (AHP), which is one of the most widely used decision-making methods designed as a web-based application so far.     Keywords: multi-criteria decision-making, analytic hierarchy process, human resources management, personnel selection, web-based applicatio

Assembly as a noncooperative game of its pieces: the case of endogeneous disk assemblies

We propose an event-driven approach to planning and control of robot assembly problems using ideas from non-cooperative game theory. We report on the results of an extensive simulation study for a very simple two degree of freedom case - the arrangement of disks on a plane by a disk shaped robot

Feedback-Based Event-Driven Parts Moving

A collection of unactuated disk-shaped parts must be brought by an actuated manipulator robot into a specified configuration from arbitrary initial conditions. The task is cast as a noncooperative game played among the parts—which in turn yields a feedback-based event-driven approach to plan generation and execution. The correctness of this approach, an open question, has been demonstrated in simpler settings and is further suggested by the extensive experiments reported here using an actual working implementation with EDAR—a mobile robot operating in a purely feedback-based event-driven manner. These results verify the reliability of this approach against uncertainties in sensory information and unanticipated changes in workspace configuration

On the Coordinated Navigation of Multiple Independent Disk-Shaped Robots

This paper addresses the coordinated navigation of multiple independently actuated disk-shaped robots - all placed within the same disk-shaped workspace. Assuming perfect sensing, shared centralized communications and computation, as well as perfect actuation, we encode complete information about the goal, obstacles and workspace boundary using an artificial potential function over the cross product space of the robots’ simultaneous configurations. The closed-loop dynamics governing the motion of each robot take the form of the appropriate projection of the gradient of this function. We show, with some reasonable restrictions on the allowable goal positions, that this function is an essential navigation function - a special type of artificial potential function that is ensured of connecting the kinematic planning with the dynamic execution in a manner that guarantees collision-free navigation of each robot to its destination from almost all initial free placements. We summarize the results of an extensive simulation study investigating such practical issues as average resulting trajectory length and robustness against simulated sensor noise

EDAR - mobile robot for parts moving based on a game-theoretic approach

EDAR (event-driven assembler robot) — a mobile robot capable of moving a collection of disk-shaped parts located on a two-dimensional workspace from an arbitrary initial configuration to a desired configuration while avoiding collisions in a purely reactive manner, is presented. Since EDAR uses a higher-level scheduler to switch among the subtasks of moving individual parts, it is viewed as mediating a noncooperative game played among the parts

The Use of Artificial Neural Network for Prediction of Dissolution Kinetics

Colemanite is a preferred boron mineral in industry, such as boric acid production, fabrication of heat resistant glass, and cleaning agents. Dissolution of the mineral is one of the most important processes for these industries. In this study, dissolution of colemanite was examined in water saturated with carbon dioxide solutions. Also, prediction of dissolution rate was determined using artificial neural networks (ANNs) which are based on the multilayered perceptron. Reaction temperature, total pressure, stirring speed, solid/liquid ratio, particle size, and reaction time were selected as input parameters to predict the dissolution rate. Experimental dataset was used to train multilayer perceptron (MLP) networks to allow for prediction of dissolution kinetics. Developing ANNs has provided highly accurate predictions in comparison with an obtained mathematical model used through regression method. We conclude that ANNs may be a preferred alternative approach instead of conventional statistical methods for prediction of boron minerals

Protein sociology of ProA, Mip and other secreted virulence factors at the Legionella pneumophila surface

The pathogenicity of L. pneumophila, the causative agent of Legionnaires’ disease, depends on an arsenal of interacting proteins. Here we describe how surface-associated and secreted virulence factors of this pathogen interact with each other or target extra- and intracellular host proteins resulting in host cell manipulation and tissue colonization. Since progress of computational methods like AlphaFold, molecular dynamics simulation, and docking allows to predict, analyze and evaluate experimental proteomic and interactomic data, we describe how the combination of these approaches generated new insights into the multifaceted “protein sociology” of the zinc metalloprotease ProA and the peptidyl-prolyl cis/trans isomerase Mip (macrophage infectivity potentiator). Both virulence factors of L. pneumophila interact with numerous proteins including bacterial flagellin (FlaA) and host collagen, and play important roles in virulence regulation, host tissue degradation and immune evasion. The recent progress in protein-ligand analyses of virulence factors suggests that machine learning will also have a beneficial impact in early stages of drug discovery

New Physics at the LHC. A Les Houches Report: Physics at TeV Colliders 2009 - New Physics Working Group

We present a collection of signatures for physics beyond the standard model that need to be explored at the LHC. First, are presented various tools developed to measure new particle masses in scenarios where all decays include an unobservable particle. Second, various aspects of supersymmetric models are discussed. Third, some signatures of models of strong electroweak symmetry are discussed. In the fourth part, a special attention is devoted to high mass resonances, as the ones appearing in models with warped extra dimensions. Finally, prospects for models with a hidden sector/valley are presented. Our report, which includes brief experimental and theoretical reviews as well as original results, summarizes the activities of the "New Physics" working group for the "Physics at TeV Colliders" workshop (Les Houches, France, 8-26 June, 2009).Comment: 189 page

Mapping interactions with the chaperone network reveals factors that protect against tau aggregation.

A network of molecular chaperones is known to bind proteins ('clients') and balance their folding, function and turnover. However, it is often unclear which chaperones are critical for selective recognition of individual clients. It is also not clear why these key chaperones might fail in protein-aggregation diseases. Here, we utilized human microtubule-associated protein tau (MAPT or tau) as a model client to survey interactions between ~30 purified chaperones and ~20 disease-associated tau variants (~600 combinations). From this large-scale analysis, we identified human DnaJA2 as an unexpected, but potent, inhibitor of tau aggregation. DnaJA2 levels were correlated with tau pathology in human brains, supporting the idea that it is an important regulator of tau homeostasis. Of note, we found that some disease-associated tau variants were relatively immune to interactions with chaperones, suggesting a model in which avoiding physical recognition by chaperone networks may contribute to disease