Üzleti teljesítménymérés az értékteremtés szolgálatában

Az üzleti teljesítménymérés az értékteremtés, a vállalati teljesítmény fejlesztésének fontos támogatója lehet. A teljesítménymérés alapfogalmainak, fő fejlődési irányainak rövid áttekintését követően a cikk egy elemzési keretet mutat be, mely a vállalatok teljesítménymérési gyakorlatát abból a szempontból értékeli, hogy az mennyire támogatja az értékteremtés folyamatát. Végül a hazai vállalati gyakorlat jellemzése következik a modell alapján.

The Role of Cannabinoids in the Neurobiology of Sensory Gating: A firing rate model study

Gating of sensory (e.g. auditory) information has been demonstrated as a reduction in the auditory-evoked potential responses recorded in the brain of both normal animals and human subjects. Auditory gating is perturbed in schizophrenic patients and pharmacologically by drugs such as amphetamine, phencyclidine or ketamine, which precipitate schizophrenic-like symptoms in normal subjects. The neurobiological basis underlying this sensory gating can be investigated using local field potential recordings from single electrodes. In this paper we use such technology to investigate the role of cannabinoids in sensory gating. Cannabinoids represent a fundamentally new class of retrograde messengers which are released postsynaptically and bind to presynaptic receptors. In this way they allow fine-tuning of neuronal response, and in particular can lead to so-called depolarization-induced suppression of inhibition (DSI). Our experimental results show that application of the exogenous cannabinoid WIN55, 212-2 can abolish sensory gating as measured by the amplitude of local field responses in rat hippocampal region CA3. Importantly we develop a simple firing rate population model of CA3 and show that gating is heavily dependent upon the presence of a slow inhibitory (GABAB) pathway. Moreover, a simple phenomenological model of cannabinoid dynamics underlying DSI is shown to abolish gating in a manner consistent with our experimental findings.

A lean tudás átadásának gyakorlatai multinacionális hálózatokban

A cikk azt vizsgálja, hogyan áramoltatják a lean menedzsmenttel kapcsolatos tudást a multinacionális vállalatok hálózataikban, azaz a vállalati központ és az egyes leányvállalatok között, illetve a leányvállalatok egymás között. Mivel a lean tudás megosztásával kapcsolatos irodalom még gyerekcipőben jár, kutatási módszerként az esettanulmány-alapú kutatást választották a szerzők. 12 interjú alapján három leányvállalatnál készítettek esettanulmányt. Feltáró kutatásukban 13 tudásmegosztási gyakorlatot azonosítottak. A megosztott tudás jellege, az érintettek és a megosztás gyakorisága alapján osztályozták őket. Kutatásuk rámutat arra, hogy a felső vezetők bevonása a lean tudás megosztásába rendkívül fontos. Ezek a vezetők egyfajta információs ügynök szerepet játszanak (gyűjtik és megosztják a jó gyakorlatokkal kapcsolatos információkat) és iránymutatást adnak a leányvállalati szintű lean erőfeszítéseknek. Kutatásuk további eredménye, hogy a lean fejlődése korántsem egyenes vonalú. A lean hálózati szintű egységes értelmezésének kialakítása alapvető ebben a fejlődési folyamatban. A globális lean tudásközpontnak döntő szerepe van az egységes értelmezési keret kialakításában.

A IV. HR-tükör kutatás legfontosabb eredményei – HR a válság idején

A kutatás a vezetőkben a HR-szervezetről kialakult képet veti össze a HR önképével. Célja, hogy az egyezések, illetve eltérések mentén szervezeti párbeszéd induljon el, melynek fókusza a HR működésének, valamint a HR és a vezetők együttműködésének fejlesztése. Az eredmények azon túl, hogy közvetlenül is szolgálják a HR tevékenységének, valamint a vezetőkkel való együttműködésének a fejlesztését, egyben az egész HR-szakma számára nyújtanak egy helyzetképet. Ezzel lehetővé teszik egy olyan szakma fejlődési dilemmáinak, trendjeinek, valamint legjobb gyakorlatainak nyomon követését, melynek hazai elfogadottsága, elismertsége még kialakulóban van. A kutatással a szakmán belül folyó párbeszédhez és a szakmai identitás erősítéséhez, alakításához is hozzá kívánnak járulni a szerzők.

Implantation d’une innovation au sein d’une région rurale éloignée au Québec : le rôle d’infirmière praticienne spécialisée en soins de première ligne- une étude de cas multiples

Introduction : La situation de l’accès, de la continuité et de la coordination des services de santé au Canada et au Québec est des plus préoccupantes. Pour contribuer à résoudre ces problématiques, l’élargissement des champs de pratique professionnels a été proposé. Lorsqu’il est question d’élargir le rôle des infirmières, la pratique infirmière avancée (PIA) est fréquemment abordée. Au Québec, ce n’est qu’en 2006 qu’un rôle associé à la PIA en première ligne a pu officiellement être mis en place, celui d’infirmière praticienne spécialisée en soins de première ligne (IPSPL) (Durand, Allard, & Ménard, 2006). L’implantation du rôle d’IPSPL est récente et peut être conçue comme une innovation. Les difficultés liées à l’implantation des rôles de PIA font l’objet d’un consensus. Pour pallier à ces difficultés, il est proposé d’approfondir la compréhension de la façon dont les rôles de PIA sont implantés, et ce, en considérant les contextes. Encore peu de recherches s’intéressent au processus d’implantation du rôle d’IPSPL au Québec, et aucune n’est centrée sur le contexte rural éloigné. But : Cette recherche vise à comprendre le processus d’implantation du rôle d’IPSPL au sein d’une région rurale éloignée du Québec, à travers l’éclairage d’un cadre de référence intégrant les théories de la diffusion de l’innovation et des transitions. Méthode : Cette étude de trois cas se situe dans un paradigme pragmatique, avec des visées descriptive et explicative. Des stratégies de collecte de données mixtes ont été utilisées auprès de personnes provenant du contexte québécois, de la région ciblée et des cas (IPSP, médecins partenaires, DSI, DSP, gestionnaires, personnes soignées et leur famille). Résultats : L’implantation est un processus multidimensionnel, multifactoriel et évolutif. Le contexte, le déroulement, la compréhension, les acteurs et le temps sont des parties intégrantes de l’implantation et sont étroitement inter-reliés. Le déroulement de l’implantation et des transitions se produit simultanément. Discussion : Cette recherche a permis de mettre en lumière la raison pour laquelle le processus d’implantation du rôle d’IPSPL doit être considéré comme un processus complexe. Cette thèse contribue à éclairer la recherche axée sur l’efficacité en permettant de mieux comprendre les différentes composantes de l’implantation. Mots-clés : implantation, rôle, infirmière praticienne, première ligne, rural, éloigné, innovation, transition.

Screening a Case Base for Stroke Disease Detection

Stroke stands for one of the most frequent causes of death, without distinguishing age or genders. Despite representing an expressive mortality fig-ure, the disease also causes long-term disabilities with a huge recovery time, which goes in parallel with costs. However, stroke and health diseases may also be prevented considering illness evidence. Therefore, the present work will start with the development of a decision support system to assess stroke risk, centered on a formal framework based on Logic Programming for knowledge rep-resentation and reasoning, complemented with a Case Based Reasoning (CBR) approach to computing. Indeed, and in order to target practically the CBR cycle, a normalization and an optimization phases were introduced, and clustering methods were used, then reducing the search space and enhancing the cases re-trieval one. On the other hand, and aiming at an improvement of the CBR theo-retical basis, the predicates` attributes were normalized to the interval 0…1, and the extensions of the predicates that match the universe of discourse were re-written, and set not only in terms of an evaluation of its Quality-of-Information (QoI), but also in terms of an assessment of a Degree-of-Confidence (DoC), a measure of one`s confidence that they fit into a given interval, taking into account their domains, i.e., each predicate attribute will be given in terms of a pair (QoI, DoC), a simple and elegant way to represent data or knowledge of the type incomplete, self-contradictory, or even unknown.

Prediction of Length of Hospital Stay in Preterm Infants - A Case-Based Reasoning View

The length of stay of preterm infants in a neonatology service has become an issue of a growing concern, namely considering, on the one hand, the mothers and infants health conditions and, on the other hand, the scarce healthcare facilities own resources. Thus, a pro-active strategy for problem solving has to be put in place, either to improve the quality-of-service provided or to reduce the inherent financial costs. Therefore, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a Logic Programming approach to knowledge representation and reasoning, complemented with a case-based problem solving methodology to computing, that caters for the handling of incomplete, unknown, or even contradictory in-formation. The proposed model has been quite accurate in predicting the length of stay (overall accuracy of 84.9%) and by reducing the computational time with values around 21.3%.

A Case-Based Approach to Nosocomial Infection Detection

The nosocomial infections are a growing concern because they affect a large number of people and they increase the admission time in healthcare facilities. Additionally, its diagnosis is very tricky, requiring multiple medical exams. So, this work is focused on the development of a clinical decision support system to prevent these events from happening. The proposed solution is unique once it caters for the explicit treatment of incomplete, unknown, or even contradictory information under a logic programming basis, that to our knowledge is something that happens for the first time.

Waiting Time Screening in Diagnostic Medical Imaging - A Case-Based View

Due to the high standards expected from diagnostic medical imaging, the analysis of information regarding waiting lists via different information systems is of utmost importance. Such analysis, on the one hand, may improve the diagnostic quality and, on the other hand, may lead to the reduction of waiting times, with the concomitant increase of the quality of services and the reduction of the inherent financial costs. Hence, the purpose of this study is to assess the waiting time in the delivery of diagnostic medical imaging services, like computed tomography and magnetic resonance imaging. Thereby, this work is focused on the development of a decision support system to assess waiting times in diagnostic medical imaging with recourse to operational data of selected attributes extracted from distinct information systems. The computational framework is built on top of a Logic Programming Case-base Reasoning approach to Knowledge Representation and Reasoning that caters for the handling of in-complete, unknown, or even self-contradictory information.

A Case Based approach to assess Waiting Time Prediction at an Intensive Care Unity

Waiting time at an intensive care unity stands for a key feature in the assessment of healthcare quality. Nevertheless, its estimation is a difficult task, not only due to the different factors with intricate relations among them, but also with respect to the available data, which may be incomplete, self-contradictory or even unknown. However, its prediction not only improves the patients’ satisfaction but also enhance the quality of the healthcare being provided. To fulfill this goal, this work aims at the development of a decision support system that allows one to predict how long a patient should remain at an emergency unit, having into consideration all the remarks that were just stated above. It is built on top of a Logic Programming approach to knowledge representation and reasoning, complemented with a Case Base approach to computing.

Length of Stay in Intensive Care Units - A Case Base Evaluation

As a matter of fact, an Intensive Care Unit (ICU) stands for a hospital facility where patients require close observation and monitoring. Indeed, predicting Length-of-Stay (LoS) at ICUs is essential not only to provide them with improved Quality-of-Care, but also to help the hospital management to cope with hospital resources. Therefore, in this work one`s aim is to present an Artificial Intelligence based Decision Support System to assist on the prediction of LoS at ICUs, which will be centered on a formal framework based on a Logic Programming acquaintance for knowledge representation and reasoning, complemented with a Case Based approach to computing, and able to handle unknown, incomplete, or even contradictory data, information or knowledge.

Percezione depth guidata mediante proiezione virtuale di pattern

L’utilizzo di informazioni di profondità è oggi di fondamentale utilità per molteplici settori applicativi come la robotica, la guida autonoma o assistita, la realtà aumentata e il monitoraggio ambientale. I sensori di profondità disponibili possono essere divisi in attivi e passivi, dove i sensori passivi ricavano le informazioni di profondità dall'ambiente senza emettere segnali, bensì utilizzando i segnali provenienti dall'ambiente (e.g., luce solare). Nei sensori depth passivi stereo è richiesto un algoritmo per elaborare le immagini delle due camere: la tecnica di stereo matching viene utilizzata appunto per stimare la profondità di una scena. Di recente la ricerca si è occupata anche della sinergia con sensori attivi al fine di migliorare la stima della depth ottenuta da un sensore stereo: si utilizzano i punti affidabili generati dal sensore attivo per guidare l'algoritmo di stereo matching verso la soluzione corretta. In questa tesi si è deciso di affrontare questa tematica da un punto di vista nuovo, utilizzando un sistema di proiezione virtuale di punti corrispondenti in immagini stereo: i pixel delle immagini vengono alterati per guidare l'algoritmo ottimizzando i costi. Un altro vantaggio della strategia proposta è la possibilità di iterare il processo, andando a cambiare il pattern in ogni passo: aggregando i passi in un unico risultato, è possibile migliorare il risultato finale. I punti affidabili sono ottenuti mediante sensori attivi (e.g. LiDAR, ToF), oppure direttamente dalle immagini, stimando la confidenza delle mappe prodotte dal medesimo sistema stereo: la confidenza permette di classificare la bontà di un punto fornito dall'algoritmo di matching. Nel corso della tesi sono stati utilizzati sensori attivi per verificare l'efficacia della proiezione virtuale, ma sono state anche effettuate analisi sulle misure di confidenza: lo scopo è verificare se le misure di confidenza possono rimpiazzare o assistere i sensori attivi.