Vision, mission and corporate values. A comparative analysis of the top 50 U.S. companies

The purpose of this paper is to demonstrate the increasing importance of defining vision, mission and corporate values by a successful company. These three entities may be formulated in separate statements, or they may be integrated in a single one. Regardless of their formulation, they have the purpose to communicate internally and externally the existential goal of the company and the core values of their integrated activities. The paper presents a comparative analysis of the way vision, mission and corporate values are formulated by the top 50 U. S. companies. A qualitative and quantitative research has been performed, based on a set of main characteristics these semantic entities have.corporate values, mission, qualitative and quantitative research, vision.

How about "them" - A Roma Museum in the making?

The article builds an argument for the necessity of the representation of Roma prelesional heritage (art crafts) in the Romanian museum discourse and sets forth to analyze the potential contribution of such an evolution in the sustainable economic growth of the Roma communities

On the quasi depth of the Hilbert function of a finitely generated graded module

Let $K$ be a field, $A$ a standard graded $K$-algebra and $M$ a finitely generated graded $A$-module. Inspired by our previous works, we study the invariant called \emph{quasi depth} of $h_M$, that is $$qdepth(h_M)=\max\{d\;:\; \sum\limits_{j\leq k} (-1)^{k-j} \binom{d-j}{k-j} h_{M}(j) \geq 0 \text{ for all } k\leq d\},$$ where $h_M(-)$ is the Hilbert function of $M$, and we prove basic results regard it. Using the theory of hypergeometric functions, we prove that $qdepth(h_S)=n$, where $S=K[x_1,\ldots,x_n]$. We show that $qdepth(h_{S/J})=n$, if $J=(f_1,\ldots,f_d)\subset S$ is a complete intersection monomial ideal with $deg(f_i)\geq 2$ for all $1\leq i\leq d$. Also, we show that $qdepth(h_{\overline M})\geq qdepth(h_M)$ for any finitely generated graded $S$-module $M$, where $\overline M=M\otimes_S S[x_{n+1}]$.Comment: 15 page

Several combinatorial inequalities deduced from the quasi depth of squarefree monomial ideals

Using the fact that the quasi depth is an upper bound for the Stanley depth of a quotient of squarefree monomial ideals, we prove several combinatorial inequalities which involve the coefficients of $f(t)=(1+t+\cdots+t^{m-1})^n$.Comment: 11 pages. arXiv admin note: text overlap with arXiv:2306.11015, arXiv:2306.0945

On the depth and Stanley depth of powers of the path ideal of a cycle graph

Let $J_{n,m}:=(x_1x_2\cdots x_m,\; x_2x_3\cdots x_{m+1},\; \ldots,\; x_{n-m+1}\cdots x_n,\; x_{n-m+2}\cdots x_nx_1, \ldots, x_nx_1\cdots x_{m-1})$ be the $m$-path ideal of the cycle graph of length $n$, in the ring $S=K[x_1,\ldots,x_n]$. We prove several results regarding $\operatorname{depth}(S/J_{n,m}^t)$ and $\operatorname{sdepth}(S/J_{n,m}^t)$.Comment: 18 page

On the arithmetic quasi depth

Let $h:\mathbb Z \to \mathbb Z_{\geq 0}$ be a nonzero function with $h(k)=0$ for $k\ll 0$. We define the quasi depth of $h$ by $qdepth(h)=\max\{d\;:\; \sum_{j\leq k} (-1)^{k-j}\binom{d-j}{k-j}h(j)\geq 0\text{ for all }k\leq d\}$. We show that $qdepth(h)$ is a natural generalization for the quasi depth of a subposet $P\subset 2^{[n]}$ and we prove some basic properties of it. Given $h(j)=aj^p+b$, $j\geq 0$, with $a,b,n$ positive integers, we compute $qdepth(h)$ for $n=1,2$ and we give sharp bounds for $qdepth(h)$ for $p\geq 3$. Also, for $h(j)=a_nj^n+\cdots+a_1j+a_0$, $j\geq 0$, with $a_i\geq 0$, we prove that $qdepth(h)\leq 2^{n+1}$.Comment: 18 page

DEZVOLTAREA EDUCAȚIEI NATO PENTRU ASIGURAREA CALITĂȚII PRIN IMPLEMENTAREA MODELULUI DE INSTRUIRE „ÎNVĂȚĂ-VIZIONEAZĂ-INTREABĂ”

Lucrarea prezintă o analiză detaliată și o metodă de implementare a modelului de instruire „Învață-Vizionează-Întreabă” (IVI), ca o potențială soluție, pentru a îmbunătăți instruirea în domeniul asigurării calității în cadrul NATO. Prin abordarea cerințelor rapid evolutive din cadrul domeniilor specializate, modelul IVI integrează instrumente digitale și metode tradiționale de predare pentru a crea o experiență de învățare care să răspundă nevoilor cursantului. Modelul este alcătuit din trei componente interdependente: modulul Învață, reprezentat de un curs online structurat; modulul Vizionează, susținut de un canal YouTube specializat pentru o înțelegere vizuală îmbunătățită; și modulul Întreabă, creat cu ajutorul unui chatbot bazat pe Inteligență Artificială (IA) pentru o învățare interactivă. Această abordare inovatoare oferă diverse stiluri de învățare, conferind sistemului eficacitate și accesibilitate continuă. Lucrarea analizează în continuare deficiențele identificate în modelele tradiționale de instruire, subliniind nevoia de elemente practice, vizuale și interactive în educația modernă. Este explorată opțiunea integrării asistentului IBM WatsonX ca și chatbot conversațional IA, în cadrul modelul IVI, evidențiind avantajele sale în furnizarea de interacțiuni consistente, precise și ușor de utilizat, comparat cu modelele IA de tip Generative Pre-trained Transformer (GPT). Adițional, este descris un proces alcătuit din șapte pași destinat adaptării modelului IVI la diverse domenii, precum și descrierea unei proces de îmbunătățire continuă pentru asistentul IBM WatsonX, asigurând relevanța și eficiența acestuia în peisajul educațional aflat în evoluție rapidă. Modelul IVI, prin întrebuințarea unică a tehnologiilor educaționale moderne, nu numai că îmbunătățește experiența de învățare din carul cursul NATO de asigurare a calității (S7-137), dar are și potențialul de a fi adaptat în diverse domenii de specialitate, promițând o forță de muncă mai eficientă

ADVANCING NATO'S QUALITY ASSURANCE EDUCATION BY IMPLEMENTING THE 'LEARN-WATCH-ASK' TRAINING MODEL

The paper introduces a detailed analysis and a method of implementing the "Learn-Watch-Ask" (LWA) training model, as a potential solution, to enhance quality assurance training within NATO. By addressing the fast-evolving demands of specialized domains, the LWA model integrates digital tools with traditional teaching methods to create a learning experience that is responsive to the student`s needs. The model is comprised of three interdependent components: the Learn module, represented by a structured online course; the Watch module, supported by a specialized YouTube channel for enhanced visual understanding; and the Ask module, created with an AI-driven chatbot for interactive learning. This innovative approach supports diverse learning styles, offering 24/7 accessibility and effectiveness. The paper further digs deeper into the identified shortcomings of traditional training models, emphasizing the need for practical, visual, and interactive elements in modern education. It explores the integration of the IBM WatsonX Assistant as a conversational AI chatbot in the LWA model, highlighting its advantages in providing consistent, accurate, and user-friendly interactions over Generative Pre-Trained (GPT) AI models. Additionally, a 7-step process for adapting the LWA model to various domains is outlined, as well as the description of a comprehensive continuous improvement loop for the IBM WatsonX Assistant, ensuring its relevance and efficiency in the rapidly evolving educational landscape. The LWA model, with its unique approach to modern educational techniques, not only enhances the learning experience for NATO’s Quality Assurance Course (M7-137) but also has the potential to be adapted across various specialized domains, promising a more effective and efficient workforce

Considerations on anesthesia for posterior fossa-surgery

Neuroanesthesia is a special chapter of anesthesia, referring to surgery that is performed right at the site of action of anesthetic drugs, namely the central nervous system (CNS).Changes induced by general anesthesia on the CNS are accompanied by changes in brain physiology, including cerebral blood flow (CBF), cerebral metabolic rate of oxygen (CMRO2), cerebral perfusion pressure (CPP) and electrophysiological functions.In neuroanesthesia, posterior fossa surgery faces difficult challenges due to the peculiarities observed from an anatomical and physiological point of view, which also requires the patient to be put in a specific position prior to surgery.Therefore, we have considered useful and detailed aspects of general anesthesia in this type of surgery, presenting data both from specialized literature and from personal experience of over 25 years

Checking experiments for stream X-machines

This article is a post-print version of the published article which may be accessed at the link below. Copyright © 2010 Elsevier B.V. All rights reserved.Stream X-machines are a state based formalism that has associated with it a particular development process in which a system is built from trusted components. Testing thus essentially checks that these components have been combined in a correct manner and that the orders in which they can occur are consistent with the specification. Importantly, there are test generation methods that return a checking experiment: a test that is guaranteed to determine correctness as long as the implementation under test (IUT) is functionally equivalent to an unknown element of a given fault domain Ψ. Previous work has show how three methods for generating checking experiments from a finite state machine (FSM) can be adapted to testing from a stream X-machine. However, there are many other methods for generating checking experiments from an FSM and these have a variety of benefits that correspond to different testing scenarios. This paper shows how any method for generating a checking experiment from an FSM can be adapted to generate a checking experiment for testing an implementation against a stream X-machine. This is the case whether we are testing to check that the IUT is functionally equivalent to a specification or we are testing to check that every trace (input/output sequence) of the IUT is also a trace of a nondeterministic specification. Interestingly, this holds even if the fault domain Ψ used is not that traditionally associated with testing from a stream X-machine. The results also apply for both deterministic and nondeterministic implementations